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Master Thesis of 2004. Still gives you a fairly good overview about what's microfinance is about (and some "German English").
Citation preview
The Impact and Outreach of Microfinance Institutions
The Effect of Interest Rates
by
Sebastian Schwiecker
(sebastianschwiecker at helpedia dot org)
wwwhelpediaorg
Revised November 2004
This paper was originally submitted in part fulfilment of the requirements for the degree of
Diplom-Volkswirt (German equivalent to Master in Economics) from the University of
Tuumlbingen in October 2004
1
Contents
Contents 1
Figures 3
Acronyms 4
1 Introduction 5
2 The Development of Microfinance 721 What is Microfinance 7
22 The Origin of Microfinance 8
23 Microfinance after the Second World War9
24 Microfinance Today11
3 The Impact of Microcredit 1332 The Eradication of extreme Poverty and Hunger13
33 Achievement of universal primary Education 15
34 Promote gender Equality and empower Women16
35 Reduce Child Mortality and improve Maternal Health17
36 Combat HIVAIDS Malaria and other diseases 18
37 Ensure environmental Sustainability 20
38 Develop a global Partnership for Development 21
4 Microcredit Outreach 2441 The Demand for Microcredit24
42 The Supply of Microcredit 25
43 Meeting the Demand26
44 Microfinance and the Capital Markets 29
5 Credit Rationing 3151 The imperfect Information Paradigm 31
52 Adaptation to the Microfinance Sector 33
53 Overcoming Credit Rationing for the Microfinance Sector 35
6 Interest Rates 4161 Setting the right Interest Rate41
62 Can Micro-Entrepreneurs bear these Rates43
63 Should the Interest Rate be subsidized anyway 44
7 Empirical verification 4671 Setting up a Sample 46
2
72 Examining the Sample47
8 Conclusions 52
Appendix 54Appendix 1 Average loan balance54
Appendix 2 Portfolio at Risk 56
Appendix 3 Transaction Costs 58
Appendix 4 Portfolio Growth 60
Appendix 5 Portfolio vs Equity 60
Appendix 6 Internal Rate of Return 61
Appendix 7 Subsidized Interest Rates and the Net Gains to Society62
Appendix 8 Interest Rate vs Loan Size vs FSS vs PAR 63
Appendix 9 Inflation vs GDP per Capita 65
References 67
Internet References 71
Ratings 76
Other Sources 78
3
Figures
Figure 1 Expected Bank Return and the Interest Rate 32
Figure 2 The extended Model 34
Figure 3 Marginal Productivity of Capital 36
Figure 4 The extended Model 39
Figure 5 Loan Size vs Interest Rate 48
Figure 6 Interest Rate vs PAR 49
Figure 7 Interest Rate vs FSS 50
4
Acronyms
BDB Bank Dagan Bali
BRAC Bangladesh Rural Advancement Committee
BRI Bank Rakyat Indonesia
CF Cost of Funds
CGAP Consultative Group to Assist the Poor(est)
FSS Financial Self-Sufficiency
GDP Gross Domestic Product
GNP Gross National Product
I Interest Rate
IADB Inter-American Development Bank
II Investment Income
IMI Internationale Mikro Investitionen Aktiengesellschaft
IPCC Intergovernmental Panel on Climate Change
K Capitalization Rate
LL Loan Loss
MBB MikroBanking Bulletin
MDG Millennium Development Goal
MFI Microfinance Institution
NGO Non Governmental Organization
NGS Net Gains to Society
PAR Portfolio at Risk
TA Transaction Costs
UN United Nations
USA United States of America
5
1 Introduction
The poor stay poor not because they are lazy but because they have no access to
capital1 If this claim made by nobel laureate Milton Friedman actually holds will be
discussed in the initial part of this paper
First a short overview of the development of the microfinance sector will be given
showing that the concept of providing financial services to low income people is much
older than still believed by many development practitioners and bankers around the
world This is important since it underlines the contribution that microfinance
institutions (MFIs) can make to the development of the financial sector in their
respective countries Subsequently the various ways how such services can assist low
income people will be discussed demonstrating that even the poorest can benefit from
the provision of small loans This is a view that is still questioned in the academia
In the second part of this paper it will be shown that although some 10000
organizations are involved in microfinance already2 they are not even close to meet the
tremendous demand for low scale financial services This sector is still widely neglected
by for profit investors and traditional bankers After examining why these groups
continue to avoid investments in the microfinance industry it will be checked if the
assumptions that underline their arguments actually hold The possibility if MFIs could
raise their interest rates to an extend that would allow them generate profits sufficiently
high to attract for profit investors will be discussed
According to Hulme and Mosley MFIs ldquocan either go for growth and put their resources
into underpinning the success of established and rapidly growing institutions or go for
poverty impact and put their resources into poverty-focused operations with a higher
risk of failure and a lower expected returnrdquo3 If this is true will be examined in the third
part by checking if poor borrowers are able to bear interest rates significantly above
1 See Friedman (nd)2 See BlueOrchard (2004a)3 See Hulme and Mosley (1996) p 206
6
those charged by conventional banks Finally a sample of 39 MFIs will be used to verify
the drawn conclusions by examining the effects their interest rates have on their
financial performances and their repayment record
7
2 The Development of Microfinance
21 What is Microfinance
According to the Journal of Microfinance the term defines what ldquois arguably the most
innovative strategy to address the problems of global povertyldquo4 This view is shared by
the United Nations (UN) which declared that the year 2005 would be the international
year of microcredit5 while their General Secretary Kofi Annan stated in 2002 that
ldquo[m]icrocredit is a critical anti-poverty tool and a wise investment in human capitalrdquo6
Hossain describes microfinance as ldquothe practice of offering small collateral free loans
to members of cooperatives who otherwise would not have access to the capital
necessary to begin a small business or other income generating activitiesrdquo7 This view is
to narrow since it not only excludes such services as saving accounts and insurances8
but also ignores the possibility of collateral demanding MFIs Although it is true that
many MFIs do not take collateral especially if they are focusing on the poorest which
normally do not possess any collateral9 several MFIs in fact do require some form of
collateral10
Roth and Steinwand give a more general definition They describe microfinance as ldquothe
provision of a wide range of financial services like saving accounts loans payment
services and insurances for people with no regular access to financial services through
traditional financial institutionsrdquo11 Here it is important not to confuse the terms
traditional or conventional with the term formal If for example an illiterate beggar
takes a $10 loan from the Grameen Bank in Bangladesh she becomes a client of a
4 See Woodworth and Woller (1999) p 65 See United Nations (1999) p 16 Annan (2002)7 Hossain (2004)8 See The Microfinance Gateway (nd) Robinson (2001) p9 Otero (1999) p 89 See chapter 3 for a more detailed discussion on poverty10 See Robinson 2002 p 24311 See Roth and Steinwand (2004) p 2 ldquodie Bereitstellung einer breiten Palette von Finanzdiensteistungen wie Spareinlagen Kredite Zahlungsverkehr und Versicherungsleistungen fuumlr Wirtschaftsakteure die keinen regelmaumlszligigen Zugang zu Finanzdienstleistungen durch klassische Finanzinstitutionen habenldquo
8
formal financial institution (a registered bank) but obviously not of a traditional or
conventional one12
Although the other services have become more important in recent years microcredit is
still considered their central service by most MFIs In many countries it refers to loans
below $ 100013 however for significant cross country comparison it is more
meaningful to look at the ratio of the loan amount to the gross national product (GNP)
or gross domestic product (GDP) per capita for the respective countries While a loan of
$1000 is more than four times larger than the GNP per capita in Uganda it represents
less than 20 of the GNP per capita in Mexico The MicroBanking Bulletin (MBB) has
categorized the target market for MFIs by the average outstanding loan amount as a
percentage of the GNP per capita ranging from Low-end (less than 20) to Small
Business (more than 250)14 Especially for the latter category one must to look closely
at the condition of the financial service market where an institution is active Although
MFIs exist in industrialized countries15 one would definitely turn to a traditional
financial institution for a loan bigger than 250 of the GNP per capita and therefore not
to a MFI according to the definition presented above
22 The Origin of Microfinance
Although neither of the terms microcredit or microfinance were used in the academic
literature nor by development aid practitioners before the 1980s or 1990s16
respectively the concept of providing financial services to low income people is much
older
While the emergence of informal financial institutions in Nigeria dates back to the 15th
century17 they were first established in Europe during the 18th century as a response to
the enormous increase in poverty since the end of the extended European wars (1618 ndash
12 See Yunus (2002) p 19 for a more detailed description of the destitute member program of the Grameen Bank which focuses exclusively on persons with no regular income and no assets at all 13 See MicroBanking Bulletin (1997) p 614 See MicroBanking Bulletin (2003) p 5415 See Yunus (1998a) pp 229 et sqq16 See Robinson (2001) p XXX17 See Seibel (2003a) p 12
9
1648)18 In 1720 the first loan fund targeting poor people was founded in Ireland by the
author Jonathan Swift19 After a special law was passed in 1823 which allowed charity
institutions to become formal financial intermediaries a loan fund board was established
in 1836 and a big boom was initiated Their outreach peaked just before the government
introduced a cap on interest rates in 1843 At this time they provided financial services
to almost 20 of Irish households20
The credit cooperatives21 created in Germany in 1847 by Friedrich Wilhelm Raiffeisen
served 14 million people by 191022 He stated that the main objectives of these
cooperatives ldquoshould be to control the use made of money for economic improvements
and to improve the moral and physical values of people and also their will to act by
themselvesrdquo23
In the 1880s the British controlled government of Madras in South India tried to use the
German experience to address poverty which resulted in more than nine million poor
Indians belonging to credit cooperatives by 194624 During this same time the Dutch
colonial administrators constructed a cooperative rural banking system in Indonesia
based on the Raiffeisen model25 which eventually became Bank Rakyat Indonesia
(BRI) now known as the largest MFI in the world26
23 Microfinance after the Second World War
Because of further prudential regulation and effective supervision eg through bank
superintendencies the banking sector in the now developed world experienced
continuous growth Today the vast majority of the citizens of the industrialized
countries have access to financial services with many of them being customers of
former MFIs27
18 See Steinwand (2001) p 5119 See Robinson (2002) p 9620 See Seibel (2003a) p 1021 first known as Darlehnsvereine and now called Raiffeisenbanken22 See Morduch (1999a) p 157323 Raiffeisen (1966) quoted in Richardson (2000) p 324 See Morduch (1999a) p 157425 See Robinson (2002) p 9726 See Roth Steinwand (2004) p 327 See Seibel (2003a) p 11
10
This is not true for most developing countries where market penetration of financial
institutions is far from reaching the majority of the inhabitants (see chapter 4) A variety
of reasons is responsible for this including that the banking sector in the most
developing countries have developed in a very different way to than those in
industrialized countries
One of the most important reasons is that in contrast to the industrialized countries little
attention has been paid to the legal recognition prudential regulation and effective
supervision of informal financial institutions28 This insecure legal environment leads to
several problems Since the regulatory framework for mobilizing savings often does not
fit the needs of institutions targeting low income people many organizations are not
permitted to do so and are therefore missing funds to on-lend as credit29 An additional
problem is the lack of a deposit insurances This not only increases the risk of a bank
run but also keeps people from depositing their savings in a financial institution30 In
addition inappropriate interest rate ceilings prevail in many countries While politics
claim they are lowering the interest rates charged to the poor they de facto only limit
their access to financial services (see chapter 5)31
Another problem that retarded the growth of the financial sector in developing countries
was the supply-leading finance theory which dominated the development strategies of
many countries after the second world war32 This theory ldquo refers to the provision of
loans in advance of the demand for credit for the purpose of inducing economic
growthrdquo33 Since it was believed that poor people were neither able to save (and thus
dependent on outside funding) nor capable of paying commercial rates of interest
massive subsidized credit programs were established34 The results were alarming
Repayment rates often did not exceed 50 percent and some government financed
programs even had default rates of more than 90 percent35 The main reason being that
credit was not provided according to business management principles but instead
28 See Seibel (1998) p 829 See Robinson (2001) p 4930 See Staschen (1999) p 1431 See Gibbons (2000) p 1532 See Morduch (1999a) p 157033 Robinson (2001) p 14034 See Borst (2004) pp 33 et sqq35 See Yunus (1998a) p 154 Robinson (2001) p 145
11
according to political objectives Therefore receiving loans was seen as a reward for the
constituents rather than as a business transaction Most of the funds earmarked for the
poor also never reached them ending up instead in the hands of the local elites
Attracted by the below market interest rates and the possibility not to pay back at all
these groups lobbied to be treated privileged and often used the money received for
consumption or for on-lending at higher rates36 But subsidized credit not only
encouraged corruption it also discouraged sustainable financial institutions since they
could not compete with interest rates that were not aimed to cover all costs and were
sometimes even lower than the interest paid on savings37 The low or negative spread
also worked as a negative incentive to institutionsrsquo effort to mobilize savings which in
turn intensified the problem of credit rationing (see chapter 5)
24 Microfinance Today
In the 1970s a paradigm shift started to take place The failure of subsidized government
or donor driven institutions to meet the demand for financial services in developing
countries let to several new approaches Some of the most prominent ones are presented
below
Bank Dagan Bali (BDB) was established in September 1970 to serve low income people
in Indonesia without any subsidies and is now ldquowell-known as the earliest bank to
institute commercial microfinancerdquo38 While this is not true with regard to the
achievements made in Europe during the 19th century it still can be seen as a turning
point with an ever increasing impact on the view of politicians and development aid
practitioners throughout the world In 1973 ACCION International a United States of
America (USA) based non governmental organization (NGO) disbursed its first loan in
Brazil39 and in 1974 Professor Muhammad Yunus started what later became known as
the Grameen Bank by lending a total of $27 to 42 people in Bangladesh40 One year
later the Self-Employed Womenrsquos Association started to provide loans of about $15 to
36 See Robinson (2001) pp 144 et sqq37 Before BRI underwent a major transformation in 1983 a negative spread between interest rates on loans and savings existed While the bank lent at a 12 annual effective interest rate it paid 15 on savingsSee Robinson (2001) p 10638 Wardhana (2001) p XXVII39 See ACCION (nd)40 See Yunus (1998a) p 16 et sqq
12
poor women in India41 Although the latter examples still were subsidized projects they
used a more business oriented approach and showed the world that poor people can be
good credit risks with repayment rates exceeding 9542 even if the interest rate charged
is higher than that of traditional banks Another milestone was the transformation of
BRI starting in 1984 Once a loss making institution channeling government subsidized
credits to inhabitants of rural Indonesia it is now the largest MFI in the world being
profitable even during the Asian financial crisis of 1997 ndash 199843
In February 1997 more than 2900 policymakers microfinance practitioners and
representatives of various educational institutions and donor agencies from 137
different countries gathered in Washington DC for the first Micro Credit Summit This
was the start of a nine year long campaign to reach 100 million of the world poorest
households with credit for self employment by 200544 According to the Microcredit
Summit Campaign Report 67606080 clients have been reached through 2527 MFIs by
the end of 2002 with 41594778 of them being amongst the poorest before they took
their first loan45 Since the campaign started the average annual growth rate in reaching
clients has been almost 40 percent46 If it has continued at that speed more than 100
million people will have access to microcredit by now and by the end of 2005 the goal
of the microcredit summit campaign would be reached As the president of the World
Bank James Wolfensohn has pointed out providing financial services to 100 million of
the poorest households means helping as many as 500 ndash 600 million poor people47
41 See Bhatt (1997)42 See Yunus (1998a) p 143 et sqq43 See Robinson (2002) p 38044 See Daley-Harris (2003) p 345 ldquoThe Microcredit Summit Campaign defines ldquopoorestrdquo as those who are in the bottom half of those living below their nationrsquos poverty line or are living on less than $1 a day adjusted for purchasing power parity (PPP)rdquo See Daley-Harris (2003) p 3 This definition will also be used throughout this paper46 See Daley-Harris (2003) p 1847 See Morduch (1999a) p 1570
13
3 The Impact of Microcredit
31 Microcredit and the Millennium Development Goals
In 1996 Ismail Serageldin the then chair of the Consultative Group to Assist the Poorest
(CGAP)48 claimed that ldquo[m]icrofinance is a proven instrument to assist the very poorrdquo49
This view is also shared by the World Watch Institute50 and underlines what has been
stated above namely that microfinance can be used as a strong anti-poverty tool But
does microfinance actually meet these expectations and keep this promise51
The impact that microcredit has on the lives of poor people will be demonstrated by
showing how it contributes to each of the eight Millennium Development Goals
(MDGs)52 which are related to the reduction of poverty in all its forms These goals
were resolved in September 2000 by the General Assembly of the UN in their
Millennium Declaration53
32 The Eradication of extreme Poverty and Hunger
The aim of the first MDG is to halve the proportion of people who live on less than $1 a
day between 1990 and 2015 According to current population projections of the World
Bank54 this would equal 849 million people in 201555
48 The Consultative Group to Assist the Poorest is a consortium of 28 public and private development agencies working together to expand access to financial services for the poor in developing countries and was established by the World Bank in 1995 Recently it changed its name to Consultative Group to Assist the Poor49 See Serageldin (1996) p 1150 See Gardner (2002) p 1851 See Morduch (1999a) pp 1569 et sqq52 The Millennium Development Goals are (1) eradicate extreme poverty and hunger (2) achieve universal primary education (3) promote gender equality and empower women (4) reduce child mortality (5) improve maternal health (6) combat HIVAIDS malaria and other diseases (7) ensure environmental sustainability and (8) develop a global partnership for development53 See United Nations (2000)54 See World Bank (2004) p 38 et sqq55 Although it is not explicitly mentioned in the Millennium Declaration it is commonly assumed that the share of people living on less than $1 in low and middle income countries should be halved If the share would be calculated with regard to the worldrsquos total population the goal for 2015 would 818 million people For the worldrsquos total population in 1990 see US Census Bureau (2004)
14
Today almost 11 billion people live on less than $1 and more than 27 Billion live on
less than $2 per day56 The mean income for those living under $1 a day is $077 and it
is $125 for those living under $2 a day57 While the number of people living on less
than $1 per day is slowly decreasing and is expected to be 913 million in 2015 the
number of people living on less than $2 a day is actually increasing58 One of the
outcomes from this degree of poverty is that more than 27000 children die every day
from mostly preventable diseases many of them related to hunger59
Microcredit enables poor people to start new businesses or to diversify existing ones
which helps them to increase their income In addition to large amounts of anecdotal
evidence several studies have documented the positive economic impact microcredit
has on its clients Cloud and Panjaitan-Drioadisuryo have found that the average income
of a sample of BRI borrowers has increased by 112 percent and that 90 percent of their
families have crossed the poverty line60 Only 12 out of the 121 respondents of that
study reported that their income had not increased61 According to the Grameen Bank
website 5109 percent of their clients have crossed the poverty line since they took their
first loan62
A study conducted by Barnes showed that the program of the Zambuko Trust a local
MFI in Zambia had a considerable impact on the poorest clients consumption of meat
fish and chicken63 While 76 percent of the continuing clients of the MFI called Share in
India significantly increased their income and 50 percent have crossed the poverty line 64 Khandker discovered in his well known study ldquoFighting poverty with microcreditrdquo
that there is a connection between the microcredit programs of three Bangladeshi MFIs
and household per capita expenditure For every dollar borrowed by a Grameen Bank
member household consumption increases by $018 In addition he found that 5 percent
56 See Chen and Ravallion (2004) p 2957 In fact those people live on less than $108 and $215 respectively a day in 1993 PPP This means that the nominal dollar value of their income is considerably lower See Chen and Ravallion (2004) p 9 58Both numbers are decreasing in Asia but increasing in the rest of the world See Chen and Ravallion (2004) p 22 et sqq59 See UNICEF (2002) p 660 A consistent definition of the term ldquopoverty linerdquo does not exists among different nations Therefore the term will be used according to the definition of the respective country in this paper61 See Panjaitan-Drioadisuryo and Cloud (1999) p 77562 See Grameen Bank (2004) 63 See Barnes (2001) p 8664 See Simanowitz and Walter (2002) p 16
15
of Grameen Bank borrowers move out of poverty every year65 Supposing Khandkerrsquos
findings were correct for all MFIs worldwide and the Microcredit Summit Campaign
achieved its goal of reaching 100 million of the poorest households with microcredit by
2005 then 25 million people (assuming an average family size of five) would leave
poverty every year66 Although this number would have to be adjusted in order take into
consideration the MFI clients who have crossed the poverty line already and of course
the experiences made in Bangladesh can not be transferred precisely to other countries
it still demonstrates the enormous effect that microcredit can have on assisting the
poorest to move out of poverty
Although a 1996 study of Hulme and Mosley states that providing microcredit can also
have a negative impact on the income of the poorest households67 these findings can
be considered as disproved by the recent bulk of evidence drawing favorable
conclusions68
33 Achievement of universal primary Education
The aim of the second MDG is to ensure that all children will be able to complete
primary school by 2015
Currently more than 100 million children most of them girls are not in school69
Besides school fees poor households often can not afford to send their children to
school because they need them to help in the family business
Microcredit programs mainly contribute to the second MDG by increasing families
income and therefore enabling parents to send their children to school Barnes Gaile
and Kibombo found that clients of an MFI in Uganda spent significantly more on
childrenrsquos education than non-clients70 and in Zambia Barnes showed that ongoing
participation in the Zambuko Trustrsquos program had a positive impact on the members
65 See Khandker (1998) p 5666 See Daley-Harris (2003) p 2467 See Hulme and Mosley (1996) p 180 et sqq 68 See Gibbons and Meehan (1998) p 13669 See UNICEF (2002) p 2270 See Barnes Gaile and Kibombo (2001) p 64
16
children staying in school71 In Bangladesh the probability of girls enrolling in school
increased by 19 percent for every 1 percent increase in Grameen Bank loans to female
clients For boys this number was even higher with the mean being 24 percent72
34 Promote gender Equality and empower Women
The aim of the third MDG is to eliminate the disparity in the ratios of girls to boys in
primary secondary and tertiary education in the ratio of literate females to males and to
increase the share of women in the labor market and in parliament73
At present the literacy rate for women is lower than for man all over the world
According to the Human Development Report 2004 the average female literacy rate as
a percentage of male literacy rate is 759 in developing countries and is as low as 37 in
Niger74 But women are not only discriminated against in education but also in access to
medical services and therefore have a higher mortality rate than man75 The worldwide
tendency for women to be underrepresented in the labor market and in the parliaments is
even more severe in developing countries76 Although several women have become
heads of state in various Asian countries (eg Bangladesh India and Indonesia) this is
probably due to them being wives or daughters of former respected male politicians
Since women have a higher repayment rate than man77 and also tend to invest increases
in income on the household and on their children rather than on themselves78 most
MFIs prefer female clients79 Therefore they empower women in many ways Often
MFIs not only encourage women to become involved in financial transactions for the
first time but also to become independent active members of the economy and to
acquire assets in their own names Cheston and Kuhn found that 68 percent of the
women participating in an MFI program in Nepal ldquohellip experienced an increase their
71 See Barnes (2001) p 8472 See Khandker (1998) p 4973 See World Bank (2001) p 2074 See UNDP (2004) pp 225 et sqq75 See Sen (2000) p 23276 See Sen (2000) pp 242 et sqq77 See Littlefield Morduch and Hashemi (2003) p 778 See Yunus (1998a) pp 116 et sqq79 According to the Microcredit Summit Campaign Report 79 or 37677080 of the poorest clients were women See Daley-Harris (2003) p 3
17
decision-making roles in the areas of family planning childrenrsquos marriage buying and
selling property and sending their daughters to school - all areas of decision making
traditionally dominated by menrdquo80 The program of the Lower Pra Rural Bank in Ghana
had an positive impact on womenrsquos participation in the community81 which is true as
well for the CRECER program in Bolivia82 In Bangladesh the Grameen Bank and the
Bangladesh Rural Advancement Committee (BRAC) the two biggest MFIs of the
country had a significant positive effect on womenrsquos empowerment measured through
eight different indicators83 After joining Grameen Bank only 21 percent of the female
members considered themselves as unemployed while this number was 50 percent
before joining84 According to the Grameen Bank website 93 percent of the Bankrsquos
shares are owned by their borrowers which elect the members of the board every three
years They also get familiar with the election process by more frequently voting for
representatives at the lower level of the organizational structure Partly because of this
experience they are more likely to run for public office In the 2003 local government
elections Grameen Bank members constituted 24 of the seats reserved for women
while they represent less than 10 of Bangladeshi adult female population85 Female
clients of MFIs from countries like the Philippines Bolivia and Nepal have reported
similar occurrences86
35 Reduce Child Mortality and improve Maternal Health
The aim of the fourth MDG is to reduce the under-five mortality rate by two-thirds
between 1990 and 2015 and the fifth MDG strives for a three quarter reduction in the
maternal mortality ratio by the same date
As has been stated above more than 10 million children are dying annually in the
developing world of mostly preventable causes with malnutrition playing a role in over
80 See Cheston and Kuhn (2002) p 1881 See MkNelly and Dunford (1998) p 5482 See MkNelly and Dunford (1999) p 7183 The eight different indicators are ldquofreedom of movement economic security ability to make small and larger independent purchases participation in important family decisions relative freedom from domination by the family political and legal awareness and participation in political campaigning and public protestsrdquo Hashemi and Schuler (1998) p 3684 See Holcombe (1995) p 5185 See Grameen Bank (2004)and CIA (2004)86 See Littlefield Morduch and Hashemi (2003) p 8
18
half of the childrsquos deaths and in over 50 countries child mortality rates are greater than
100 deaths per 1000 live births87 Maternal mortality is also a significant problem in the
developing world with more than 500000 women dying every year from pregnancy
related causes88
MFIs are mainly contributing to the these MDGs by increasing families income and
therefore enabling the households to afford better nutrition and medical services
Furthermore they are often linked with microinsurance or health education programs
In addition to what has been showed in chapter 31 Pitt Khandker and Millimet
estimate that a 10 percent increase in the loan size of a female borrower in Bangladesh
increases the arm circumference of their daughters by 6389 Smith and Jain found that
village banking in Ecuador had a positive effect on child diarrhea90 which is responsible
for 15 of child deaths91 Since Sen argues that an improved status of women within
the family reduces child mortality92 the empowerment of women through MFIs is also
contributing to this cause
Although no study has been conducted so far on the direct impact of microcredit on
maternal health it can be assumed that an overall improvement of access to medical
services reduces maternal mortality as well A study of the Morgan State University for
example suggests that microcredit has a positive effect on the prevalence of
contraceptives93 which leads to a decrease of unwanted pregnancies and therefore
reduces maternal death
36 Combat HIVAIDS Malaria and other diseases
The aim of the sixth MDG is to halt and begin to reverse by 2015 the spread of
HIVAIDS malaria and other major diseases and to assist children orphaned by HIV
87 See World Bank (2001) p 888 See WHO (2004) 89 See Pitt Khandker and Millimet (2003) p 11390 See Smith and Jain (1999) p 3791 See WHO (2001) 92 See Sen (2000) p 23593 See Amin et al (2001) p 1614
19
In 2003 29 million people died because of HIV and about 48 million became infected
the greatest number since AIDS was discovered 23 years ago94 This pandemic has lead
to a tremendous decrease in the life expectancy in the hardest hit countries Botswana
for example one of the richest and most democratic countries in Africa has a
HIVAIDS adult prevalence rate of 388 and a life expectancy at birth of less than 31
years95
Malaria not only causes more than one million deaths annually it leads also to 300 ndash
500 million clinical cases a year Both numbers have been steadily increasing over the
past two decades96 More than two million people a year are killed by tuberculosis
another global health problem This curable disease is estimated to cost poor
communities about $12 billion every year since even those who survive normally lose
more than 3 month of work time while recovering97
MFIs contribute to the sixth MDG in several ways By increasing clientrsquos income they
help households affected by HIV or other diseases to better cope with the situation
Besides spending more money on health services and nutrition MFI clients also tend to
be more able and willing to support AIDS orphans than non clients98 In addition to the
already stated increase in the use of contraceptives99 several innovative approaches to
deal with disease related crisis have also arisen This is of course necessary not only to
counteract the devastating effect the above discussed epidemics can have on MFI
clients but also to not put the viability of the respective institution at risk One option is
to integrate education services in the MFI programs and encourage clients to form
solidarity groups100 It has been shown that these services do not necessarily decrease
the effectiveness of the institutionsrsquo employees101 Another way is to strengthen the ties
to NGOs specialize in dealing with the respective disease Synergies gained through this
cooperation can help clients to better deal with the situation and in the end increase their
94 See UNAIDS (2004) p 2395 See CIA (2004)96 See World Bank (2001) p 1697 See World Bank (2001) p 1298 See Barnes (2001) p 6499 See also Kim et al (2002) p 18100 See Donahue and Sussman (1999) p A 14101 See Donahue Kabbucho and Osinde (2001) p 25
20
repayment rates Various MFIs also have introduced loan and health insurance products
or cultivated linkages with organizations doing so102
It has to be stated that despite the benefits MFIs can provide to people effected by
HIVAIDS or other diseases microcredit can also be a burden for those who are already
chronically ill These people can still benefit through loans provided to members of the
family or the community or through one of the other services mentioned above
37 Ensure environmental Sustainability
The aims of the seventh MDG are to support and promote the principles of sustainable
development and put them into action and to improve the lives of slum dwellers and
people without sustainable access to safe drinking water and sanitation
Today climate change is considered as the major environmental problem103 The
Intergovernmental Panel on Climate Change (IPCC) states that human activities
contribute to most of the 06 degC increase in global average temperature over the 20th
century and the predicted increase of another 14 to 58 degC between 1990 and 2100104
Emission of carbon from fossil fuel is reported to have the dominant influence on this
development While the total emission was 16 billion tons in 1950 it was already 65
billion tons in 2000 and is expected to continue to grow105 This development would
lead to a rise in the average sea level of between 9 and 88 centimeters during the next
century106 Furthermore it is predicted that global warming increases the risk of extreme
events like cyclones or floods leads to an increase in the number of people infected by
diseases like malaria and decreases the potential crop harvest and water availability
especially in developing countries107 In 2000 already 11 billion people lacked access to
clean drinking water and 24 billion to basic sanitation108
102 See Barnes (2001) p 40 Barnes Gaile and Kibombo (2001) p 13 and Grameen Bank (2004)103 See Gardner (2002) p 5104 See IPCC (2001) pp 2 et sqq105 Worldwatch Institute (2002) p 52 et sqq106 See IPCC (2001) p 16107 See Dunn and Flavin p 29108 See UNFPA (2004) p 18
21
MFIs contribute to achieving the seventh MDG in several ways By providing loans for
the purchase of renewable energy technologies they help people in developing
countries to increase their per capita energy consumption without increasing the carbon
dioxide emission In a 2003 survey of 140 MFIs from 80 different countries 21 said
they provide credits for solar home systems and another 19 stated they are interested in
becoming engaged in this business109 While Grameen Shakti a rural energy service
company cooperating with the Grameen Bank in Bangladesh has already installed more
than 23000 solar home systems110 a 2000 World Bank study reports twelve projects
providing solar home systems to rural households with a target of 500000
installations111 It has also been suggested that MFIs should raise environmental
awareness among their clients112 but so far no data is available on how staff can cope
with this additional task Many MFIs also provide loans for improvements in sanitation
and the water supply of their clients Varley gives several examples from Africa Asia
and Latin America on how microcredit not only has helped to invest in rainwater
collection systems but also how it has enabled households to increase their water
supply through community water associations113 In addition many MFIs provide credit
for the construction of sanitary latrines114 The situation of slum dwellers is also
positively effected by MFIs Directly through their services in poor urban communities
and indirectly by creating jobs in rural areas and therefore easing the pressure on urban
labor markets
38 Develop a global Partnership for Development
The eight MDG is about the means to achieve the other seven MDGs It calls for all
players involved in the endeavor of development and poverty eradication to work as
partners in a global context
Again MFIs are contributing to the eight MDG in many ways This is occurring through
international networks that provide funding and technical assistance through internet
information portals and specialized journals through social and for profit investors and
109 See Wimmer and Barua (2004) p 174110 Barua (2004) 111 See Martinot and Cabraal (2000) p 6112 See Pallen (1997) p 11 Lal (nd)113 See Varley (1995) pp 39 et sqq114 See Jalvaani (1999) pp 1 et sqq Varley (1995) pp 39 et sqq
22
specialized rating agencies The Bangladesh-based Grameen Trust is one of around 30
networks in operation Besides collaborating with over 200 MFIs around the world it
has directly operated three projects in Afghanistan Kosovo and Myanmar115 While the
ACCION network serves almost 12 million active clients in 19 countries throughout
America and sub-Saharan Africa116 FINCArsquos network operates in three different
continents where it serves more than 200000 customers117 In November 1997 the
MicroBanking Bulletin (MBB) was first published by the microfinance program at the
Economic Institute at the University of Colorado118 Its aim is to develop a database on
the financial performance of MFIs from all over the world which is now available
through the Mix Market an internet portal that also provides information about more
than 300 MFIs investors donor institutions and other related development
organizations119 Two years later the Marriott School at Brigham Young University
started to publish the Journal of Microfinance which has an editorial board of
microfinance experts from all over the world and offers the latest research on this
topic120 In the late 1990s a number of companies became attracted by the microfinance
market and started to invest in MFIs The German based Internationale Mikro
Investitionen Aktiengesellschaft (IMI) for example has already invested more than euro46
million in 19 MFIs in four different continents and plans to invest another euro27 million
before October 2004121 BlueOrchard Finance a microfinance investment consultancy
has channeled more than $60 million worth of private capital to some 40 MFIs
worldwide through investment funds and bond issues122 Big commercial banks like
Citigroup Deutsche Bank and ABN Amro also started to get involved in the
microfinance sector although this is mainly still perceived as a public relation activity
and not as a for-profit investment123 There are also several rating agencies specializing
in MFIs Dependent on their rating these institutions can help MFIs to receive money
from donors or investors Four of the most prominent rating agencies are PlanetFinance
115 See Grameen Trust (nd)116 See ACCION (nd)117 See FINCA (nd)118 See MicroBanking Bulletin (1997) p 5119 See The Mix (2004)120 See Woodworth and Woller (1999) p 6121 See IMI (2004)122 See BlueOrchard (2004b) p 3123 See Busch and Kort (2004) p 8 Fischer (2003) p 6
23
with headquarters in France M-Cril based in India Microfinanza in Italy and
MicroRate with offices in the USA and South Africa124
124 See Microfinance Rating and Assessment Fund (2004)
24
4 Microcredit Outreach
41 The Demand for Microcredit
Although it has been shown that microcredit is one of the most effective poverty
eradication tools that it is considered a human right by some of its advocates125 and it
can contribute considerably to the development of the financial sector in developing
countries an enormous gap still exists between supply and demand for microcredit
Estimates on the demand for microcredit vary greatly While USAID estimates the
number of potential microfinance clients is between 100 and 200 million126 the
Microcredit Summit Campaign states the total demand is more than 234 million
people127 CGAP recognizes some 500 million micro-entrepreneurs who have the
potential to become customers of MFIs128
Marguerite Robinson calculates the demand as follows ldquoAssuming five people to a
household among the 45 billion people living in low- and lower-middle-income
economies in 1999 (World Bank World Development Report 20002001) there are 900
million households in those economies If estimating conservatively we assume that
informal commercial moneylenders supply credit to 30 percent of these households at
least once a year this would mean that there are 270 million households borrowing
from informal moneylenders in a year Undoubtedly however many of these
households borrow multiple times within a yearrdquo129 Although this is a very rough
estimate assuming big differences in demand for microcredit in different countries the
number seems to be the most meaningful In contrast to the estimate of the Microcredit
Summit Campaign it does not include every single household living on less than $1 a
day but according to the definition presented in chapter 1 it counts everyone who has
no regular access to traditional financial institutions but demands such services
Obviously not all people who draw on moneylenders have financial needs that could be
matched through MFIs On the other hand interest rates charged by moneylenders tend
125 See Yunus (1998b) 126 See Christen et al (1995) p 15127 See Daley Harris (2003) p 22 128 See Robinson (2001) p 26129 See Robinson (2001) p 215
25
to be considerably higher than those of MFIs The former normally charge effective
monthly rates between ten and several hundred percent per month the latter generally
charge between 15 and five percent which enables them to attract additional clients130
42 The Supply of Microcredit
In spite of the impressive growth of MFIs around the world the demand for microcredit
is far from being met and this it is not likely to change in the near future The
Microcredit Summit Campaign reported that by the end of 2002 67606080 clients131
were reached through MFIs and that this number has increased by almost 40 percent
annually for the last five years132 It is likely that this tremendous speed of growth is at
least partly due to including MFIs which have not been reporting to the Campaign from
its start in 1997 although they have already existed at that time These institutions
contributed 22 percent to the growth in poorest clients in 2000 578 percent in 2001 and
338 percent in 2002 The growth of the poorest clients increased at least party because
of an expanded definition of the term ldquopoorestrdquo133 Since the contribution of MFIs
which previously have not been considered can be expected to decrease dramatically
the growth rate as stated by the Microcredit Summit Campaign can not be used to
predict the future development of the microfinance sector Another factor likely to slow
down the growth is the concentration of microfinance activities in some Asian countries
where almost 90 percent of the poorest microfinance clients live today134 Even if one
takes into consideration the relative size of Asiarsquos population and the fact that many
MFI customers in Latin America are relatively better off and therefore are not included
in this numbers the coverage of this part of the world far exceeds the others In
Bangladesh for example the microfinance market is close to saturation More than
eleven million households were served by several hundred MFIs in 2001135 Among
them are Grameen Bank and BRAC two of the best known MFIs in the world both
providing their services to more than three million customers With an average
household size of five it can be assumed that in Bangladesh the number of people
130 See Gibbons and Meehan (1999) pp 144 et sqq131 41594778 of them belonged to the poorest before they took their first loan The relative numbers in the following are for these poorest clients only since no other current data was available It can be assumed though that this works as a good proxy for the total number of clients 132 See Daley Harris (2003) p 3133 See Daley Harris (2003) p 17134 See Daley Harris (2003) p 21135 See Ahmed (2003)
26
benefiting from microcredit already surpasses the number of people living below the
poverty line which is estimated to be slightly higher than 50 million136 Therefore
Bangladesh will not contribute to the growth of the microfinance sector as much as it
has done in previous years This is also true for Vietnam Thailand and to a lesser
extent Indonesia Eight of the nine MFIs serving more than one million clients are based
in these countries while the ninth is based in India where due to its one billion
inhabitants the microfinance market is still far from saturation137 In contrast the
supply in Brazil meets less than two percent of the demand which is estimated to be
about 58 million potential clients138 For these reasons greater amount of future growth
must come from smaller or new MFIs in Latin America India China and especially
Africa where almost 30 percent of the worldrsquos poorest live139
43 Meeting the Demand
To fill the gap between the demand and supply for microcredit tremendous investments
are necessary to increase the loan funds of MFIs and build up their capacity through
upgrading existing institutions or building new ones Again estimates on how much
capital is needed vary greatly with the highest being at more than $300 billion140
In 1997 the Microcredit Summit Campaign estimated that $216 billion would be
needed to achieve their goal of providing microcredit to 100 million of the poorest
households This was calculated in the following way Since some 8 million people
already received microcredit in 1997 another 92 million needed to be reached
Assuming $200 ($150 for loan fund and $50 for capacity building) would be needed per
person for 88 million people in developing countries and $1000 ($500 for loan fund and
$500 for capacity building) would be needed for 4 million people in industrialized
countries the capital required ends up to be $216 billion141 For several reasons this
136 See CIA (2004)137 These institutions are The Grameen Bank BRAC Proshika and the Association for Social Advancement (ASA) in Bangladesh the Vietnam Bank for Agriculture and Rural Development (VBARD) and the Vietnam Bank for the Poor (VBA) in Vietnam BRI in Indonesia Bank for Agriculture and Agricultural Co-operatives (BAAC) in Thailand the National Bank for Agriculture and Rural Development (NABARD) in India See Ahmed (nd) p 1 Llanto (nd) p 337138 See Mezzera (2002) p 23139 See See Chen and Ravallion (2004) p 29140 See Clear Profit (2004) Prisma (2002)141 See The Microcredit Summit (1997)
27
number is not qualified to predict the total amount of capital needed to meet the demand
for microcredit On the one hand it focuses mainly on the low end of the market and
therefore underestimates the average loan fund needed On the other hand it does not
take the increasing capital demand from established MFIs into account A survey of 119
MFIs found that the average loan size to increased from $406 in 2002 to $498 in
2003142 This is mainly due to the fact that MFI clients once they have paid back their
loans usually demand larger ones for the continual development of their businesses
and therefore further increase the demand for capital of established MFIs The Grameen
Bank for example has a ceiling on its loans which increases or decreases depending on
the borrowers performance regarding repayments and savings143 While the maximum
amount for the first loan is fixed at approximately $75144 the largest loan disbursed so
far was $17195145 Thus if one estimates that by now 100 million people are borrowing
from MFIs146 another 170 million need to be reached to meet the estimated demand
Assuming an average of $600 ($400 for loan fund and $200 for capacity building) is
needed for every new client and another $200 is needed for every existing client to meet
the demand for larger loans a total of $122 billion is required This rough estimate
helps to convey the approximate amount of capital needed to meet the demand for
microcredit
So far the demand for funds is being partly met by donors which annually provide
between $500 million and $1 billion147 and through the mobilization of local savings
Obviously the amount of money provided by donors will not be able to meet the capital
demand for microcredit in the short term The mobilization of savings on the other hand
has been extremely successful in some cases with BRI probably being the most
prominent example After adapting commercial principals in October 1984 BRI was
able to raise its deposits from $161060 to more than $32 billion in 2003 which equals
almost two times its current loan portfolio148 Many other MFIs like BDB in Indonesia
142 Own calculations Without BRI the numbers would be $343 and $409 See Appendix 1143 See Grameen Bank (2003) p 13144 The accurate amount is 5000 Taka See Interview with Shaw Newaz145 Grameen Bank (2004)146 According to the data provided by the Daley Harris (2003) an annual increase in MFI clients ofapproximately 25 percent from 31122002 till the 3092004 would be needed to reach 100 million clients by now This rated is considerably below the average of the previous five years (38 percent) Therefore it can be assumed as realistic despite the growth hindering factors presented above147 See CGAP (2003) p 8148 See Robinson (2002) p 273 Mix Market (2004)
28
XacBank in Mongolia the Equity Building Society in Kenya or the Centenary Rural
Development Bank in Uganda also have managed to cover their loan portfolio fully
through internally mobilized resources149 The Grameen Bank is also expected to do so
in the first half of 2005150 In addition to raising much needed capital for on-lending the
provision of saving services can deliver notable social benefits itself151
Despite these impressive achievements even the combination of donor money and local
savings at their current levels will not be able to provide the capital needed to continue
the rapid growth of the microfinance sector Especially in their early years MFIs rely on
outside funding BRI for example needed six years before the amount of locally
mobilized savings surpassed the total amount of outstanding loans During this time
expenses and the loan portfolio were covered through a government grant worth $20
million and two World Bank loans of $5 and $97 million respectively152 It also
benefited from a network of more than 3600 branches which were established
throughout the country during the 1970s and early 80s in order to provide government
subsidized credit in rural areas153
The Grameen Bank also widely known as a best practice MFI has received about $175
million in direct and indirect subsidies between 1985 and 1996154 and continues to rely
on outside funding at below market interest rates This is made possible either through
special loans from the Bangladesh Bank or through offering bonds guaranteed by the
Bangladesh government155 - an option most MFIs do not have BDB might be one of the
very few examples which were able to finance their activities through savings and
commercial loans from the start but its outreach did not reach a large scale nor did it
serve the low end of the market In 2000 after 30 years of operation BDB provides
credit to only 10417 clients with an average loan balance of more than $5000156
approximately eight times the countries GDP per capita157
149 See Mix Market (2004)150 See Grameen Bank (2004)151 See Robinson (2001) pp 263 et sqq152 See Seibel and Schmidt (2000) p 4153 See Robinson (2002) p 180154 See Morduch (1999b) p 8155 See Morduch (1999ba) p 25 et sqq156 See Robinson (2002) p 387157 See CIA (2004)
29
Another problem keeping many MFIs from collecting savings is that they do not want
to become a regulated financial institution or do not meet the criteria in their respective
country and therefore they are simply not allowed to mobilize savings from the public
In summary the examples and numbers presented in this chapter support the argument
that the amount of capital that can be raised through donors and locally mobilized
savings is not enough for continuous rapid growth of the microfinance sector If this
lack of capital is not met through other sources the microfinance sector will fail to
contribute its full potential to the achievement of the MDGs
44 Microfinance and the Capital Markets
Regardless of whether the amount of capital needed for the development of the
microfinance sector is $20 or $300 billion it represents only a tiny fraction of the
worldwide capital markets which are estimated at $30 trillion158 Therefore if the
microfinance industry were able to tap the financial markets it would be able to grow
much faster and soon serve the millions of micro-entrepreneurs which currently can not
develop theirs businesses because of capital constrains Another advantage would be
that scarce donor money currently used for the development of the microfinance sector
could be used for other projects that do not have the potential to draw money from
commercial sources This view is shared by Michael Chu the former CEO of ACCION
who made the following statement in 1998 ldquoMicrofinance today stands at the threshold
of its next major stage the connection with the capital marketsrdquo159 Many attempts have
been made since that time Successful MFIs like BancoSol in Bolivia further
strengthened their ties to the capital markets which in some cases already provide the
majority of their funding160 Microfinance investment advisors like BlueOrchard
Finance have become middlemen for MFIs and the financial markets Nevertheless
these links are still far from reaching major scale Currently only approximately 20
percent of MFIs funding comes from commercial sources161 and the biggest bond issue
dedicated to fund MFIs totals only $40 million In addition these funds mainly end up
158 See Brynjolfsson (2004) 159 Chu (1998) quoted in Robinson (2001) p 23160 See Robinson (2001) p 69161 See Dominiceacute (2004)
30
in established institutions in Latin America or Eastern Europe162 while smaller
organizations only benefit indirectly if at all
162 See Clear Profit (2004) IMI (2004)
31
5 Credit Rationing
Until recently the predominant answer to why commercial banks or venture capital
companies did not invest in the microfinance sector was that the poor are not bankable
Besides lacking education and therefore not being able to deal with formal financial
institutions they were viewed as bad credit risk who were unable to invest the borrowed
money in a way that would allow them to repay the loan and interest at a commercial
rate163 Another reason that kept attention away from the idea of providing financial
services to low income people was the belief that informal moneylenders already met
this demand These skeptics felt affirmed through the poor performance of subsidized
credit programs as described in chapter 22 Although it is true that moneylenders
serve a huge number of people in the developing world they more often than not charge
usury interest rates of up to 20000 percent per month164 While the argument that poor
people are not able to participate in the formal financial market can be overcome by
adapting the services accordingly165 the claim of low returns on their investments is not
only proved wrong by empirical evidence but also contradicts economic theory as will
be shown in chapter 53
51 The imperfect Information Paradigm
A more elaborate explanation for the short supply of financial services to low income
people that can be derived from the imperfect information paradigm based
predominantly on the works of Akerlof166 and Stiglitz and Weiss167 After giving a brief
summary of their argument an adaptation of their findings to the microfinance market
will be presented and subsequently it will be shown how their conclusions can be
overcome
Behind the imperfect information paradigm lies the theory of asymmetric information
which simply states that if two parties conduct a transaction one is likely to have more
163 See Ghatak (1983) p 21 et sqq Yunus (1998) p 102 et sqq Robinson (2001) p 35 et sqq164 See Robinson (2001) p 17165 See Seibel (2003b) p 2 BRAC (2003) pp 15et sqq Yunus (1998) pp 151 et sqq 166 See Akerlof (1970) pp 488 et sqq167 See Stiglitz and Weiss (1981) pp 393 et sqq
32
information than the other and is trying to use that for its own advantage168 Applied to
the banking sector this means that a person applying for credit can better judge the
likelihood of repaying the loan than the bank This is because the borrower has better
knowledge of the market she wants to invest in her skills and her willingness to repay
Moreover the bank might not be able to observe if the borrower uses the loan for the
agreed purpose These occurrences can lead to what is known as adverse selection and
moral hazard In this case adverse selection refers to the problem that banks might
attract borrowers with a low probability of repayment if they can not distinguish
between high and low risk loan applicants Moral hazard occurs after the provision of
the loan when the borrower spends the money on a purpose different to the prescribed
purpose and therefore lowers the probability of repayment This can happen eg by
investing in a more risky project or through spending the money on consumption If the
bank is not able to find a cost effective way to avoid these problems it might raise its
interest rate in order to compensate for the increased risk
Figure 1 Expected Bank Return and the Interest Rate
Source Stiglitz and Weiss (1981) p 394
Since this might discourage low risk borrowers from applying for credit and encourage
borrowers who continue to take loans to invest in riskier projects the share of high risk
168 See Neus (1998) p 85 et sqq
INTEREST RATEI
EX
PE
CT
ED
RE
TU
RN
TO
TH
E B
AN
K
33
borrowers could increase and therefore reinforce the problems stated above Thus
increasing the interest rate beyond a certain point actually leads to a decrease in the
expected return to the lender This context is illustrated in figure 1 with I being the
interest rate which maximizes the expected returns to the bank Obviously the bank
would charge the interest rate I in order to maximize its expected return However this
price for capital was not determined through supply and demand as economic theory
would predict It is conceivable that at the interest rate I the demand for credit exceeds
the supply but even if loan applicants would offer to pay a higher interest rate the bank
would refuse because it associates such a loan with high risk As a result credit might
be rationed169
52 Adaptation to the Microfinance Sector
Through some adaptations this model can also help to explain the lack of funds
provided to low income people In the original model of Stiglitz and Weiss several
assumptions have been made that need to be suspended in order to compare the credit
markets for low and high income people and give an explanation why the latter is
widely neglected by institutional investors
Evidently the assumptions that the amount borrowed is equal for each loan applicant
and that transaction costs170 need not to be taken into account171 are not suitable for this
context While the average loan size of MFI customers is much smaller than that of
clients from traditional banks the transaction costs as a share of the loan are
considerably higher because the lenderrsquos costs for conscientious processing a credit
applications are only slightly smaller for a $50 loan than for a $100000 or a
$10000000 loan
In figure 2 the R(I)large curve represents the return to the bank for large loans with
regard to the interest rate I and the R(I)small curve describes the same correlation for
small loans It is shifts downwards to reflect the assertion that the imperfect information
169 See Stiglitz and Weiss (1981) p 394170 In this paper the term bdquotransaction costsldquo refers to the operating expense ratio as defined by MicroRate It ldquois calculated by dividing all expenses related to the operation of the institution (including all the administrative and salary expenses depreciation and board fees) by the period average gross portfoliordquo See MicroRate and Inter-American Development Bank (IADB) (2003) p 16 171 See Stiglitz and Weiss (1981) p 396
34
paradigm has a more severe effect on poor people than on the better off They are
expected to have less profitable investment opportunities at their disposal172 and
therefore are more likely to invest in riskier projects which increase the probability of
default and hence decrease the expected return to the bank Additionally one might
expect poor people to be more likely than others to spend borrowed money on
consumption instead of an income generating activity particularly if a crisis arises It
seems understandable that food or urgently needed medicine are given priority over
repaying a loan
The second shift downwards is due to transaction costs As stated above they are
relatively higher for smaller loans Obviously transaction costs are incurred in the
provision of a large loan as well but since they are much smaller with regard to the loan
amount they are not included in the diagram for reasons of clarity
Figure 2 The extended Model
Source Own diagram adapted from Stiglitz and Weiss (1981) p 394
172 See Khandker (1998) p 8
INTEREST RATE I
SmallLoans
LargeLoans
Transaction costs
Lack of investment opportunities
R(I)large
R(I)small
EX
PE
CT
ED
RE
TU
RN
TO
TH
E B
AN
K
35
53 Overcoming Credit Rationing for the Microfinance Sector
If the conclusions in chapter 51 hold it is rational for a profit maximizing investor to
neglect the microfinance sector as long as no surplus funds in the market for large loans
exist This finding can help to explain the small amount of money provided to the
microfinance sector from commercial investors On the other hand it has to be stated
that this theory is reflexive as defined by Soros173 It not only explains but also forms
reality since it has the potential to reinforce the view of potential investors that
microfinance is a less profitable business174 Therefore demonstrating under which
conditions microfinance can be profitable and in some cases be more profitable than
traditional businesses is of crucial importance
To provide a fairer view of the microfinance sector a further assumption of the Stiglitz
and Weiss model that needs to be suspended is that all investments made by the
borrowers have the same expected return175 As stated above this contradicts economic
theory which claims ceteris paribus capital productivity decreases while the amount of
fixed capital increases In combination with a low capital endowment micro-enterprises
are usually faced with an excess supply of unskilled labor especially in developing
countries176 Hence small enterprises use far less capital per employee than big business
and therefore their marginal productivity of capital is much higher177 This is intuitive if
one imagines an economic actor who wants to invest several packages of capital
Obviously she would invest the first package where she expects the highest return the
second package where she expects the second highest return and so on Each additional
investment opportunity would lead to lower or at best equal returns178 While this
simplified example has limitations it demonstrates how the marginal productivity of
capital can diminish Although it might actually increase until a certain point179 this can
be expected to be so low in this context that it has no influence on the correlation as
shown in figure 2
173 See Soros (1998) pp 14 et sqq174 See Goodwin-Groen (1999) p 8175 See Stiglitz and Weiss (1981) p 395176 See Perkins et al (2001) pp 95 et sqq177 See Tschach (2000) p 8178 See Rosenberg (2002) p 11179 See Rechard G Lipsey (1979) pp 211 et sqq
36
Figure 3 Marginal Productivity of Capital
Source Dornbusch and Fischer (1995) p 406
Even if good investment opportunities for poor people exist the question remains if it is
possible to distinguish between high and low risk borrowers The problem of adverse
selection is overcome in a cost effective way in many MFIs180 For the better off poor
for example institutions like BRI base their decision on whether or not to approve a
loan by assessing the repayment ability of potential borrowers from their current income
flows and not from the uncertain returns generated by the loan181 Additionally
collateral is used in some cases to attract low risk borrowers182 In contrast to
industrialized countries this is usually not done to cover the potential losses of the
lender but to punish the defaulter and therefore increase her willingness to repay183
Obviously this does not always work for the poorest since they often neither posses any
goods that could work as collateral nor do they have sufficient earnings prior to
obtaining a loan for starting an income generating activity Here the so called group-
lending model can help to identify creditworthy borrowers The most prominent
institution using this approach is the Grameen Bank which only provides credit to
180 See Farrington (2000) p 20181 See Robinson (2001) p 80 Robinson (2002) p 238182 See Bester (1985) p 850 et sqq183 See Schmidt and Tschach (2001) p 15 Robinson (2002) p 244
FIXED CAPITAL 0
MA
RG
INA
L P
RO
DU
CT
IVIT
Y
37
members of a group of five These groups are formed by their members without
interference of the Grameen Bank Although in this particular case no joint liability
exists for the members of the group nobody can receive a new loan if another member
of the group fails to repay on time184 Therefore the group formation work as a
screening process Since the borrowers do not want to risk their ability to obtain further
loans they carefully select with whom to form a group Usually the members know
each other for a long period of time and therefore they can make a meaningful judgment
of each othersrsquo ability to repay the loan Other MFIs even require the members of a
group to mutually guarantee each othersrsquo loans185 While this might further increase
borrowersrsquo efforts to search for trustworthy group members it might also keep potential
borrowers from applying for a loan since she does not want be held responsible for
defaulting members This mechanism enables MFIs to partly pass on the transaction
costs related to the selection of low risk borrowers to the borrowers themselves186
Many MFIs have also largely overcome the problem of moral hazard by creating
incentives to ensure a high repayment rate even among the poorest In some cases their
customers go hungry in order to pay back their loan even though no legal action would
be taken against them if they would refuse to do so187 One way to achieve this is to
build up peer pressure through the formation of groups as described above188 Another
and probably the most important is to limit access to future loans to those borrowers
who repay on time The demand for successive loans is extremely high In a 1996
survey 98 percent of BRI borrowers planed to apply for another loan189 and in 1993
less than 30 percent of Grameen Bank loans went to first time borrowers190 Especially
the poorest highly value the option to reborrow191 and many MFIs see this as their
primary incentive to ensure repayment192 According to Schmidt and Tschach ldquothe net
present value of future access to credit works out to be roughly half the value of the
economic advantage to be gained from the intended non-repaymentrdquo193 This can also
184 See Yunus (1998) p 135185 See Schmidt and Zeitinger (1997) p 6186 See Stiglitz (1990) p353187 Own observation at the Grameen Bank in Bangladesh (2003)188 See Hoff and Stiglitz (1990) p 249189 See Robinson (2002) p 251190 See Khandker Khalily and Khan (1995) p 93191 See Gibbons (2000) p 15 Hashemi and Schuler (1997) p 43192 See Gibbons and Meehan (1999) p 160193 See Schmidt and Tschach (2001) p 16
38
explain the occurrence of a drop in the repayment rate once a MFI is no longer seen as
viable and therefore is not expected to provide loans in the future194
With the help of the described mechanisms MFIs around the world are able to keep
repayment rates high A survey of 69 MFIs from 36 different countries each serving
more than 10000 clients in 2002 found the portfolio at risk (PAR)195 varied between
zero and 231 percent While the average was 36 percent the median was found to be
229 percent196 One of the MFIs included in this sample is BRIs whorsquos 12-month loss
ratio has never exceeded five percent since the start of its transformation in 1984 and
from 1997 to 1998 the ratio actually fell from 22 to 194 percent197 The latter deserves
special attention because the Asian financial crisis reached its peak at that time with
Indonesia being hardest hit as illustrated by a statement from The Economist in July
1998 Even with the fierce competition from its neighbors Indonesia would probably
walk away with the prize for Asias most desperate banking systemrdquo198
The findings that MFIs can adapt their services to low income people in order to ensure
a high repayment rate and that poor people do not lack profitable investment
opportunities are illustrated in figure 4 From this diagram it can be seen that under the
new assumptions the interest rate at which the bank maximizes its return differs for
large (I(l)) and small loans (I(s)) According to the assumption that micro-
entrepreneurs can realize a higher return on their investments the bank can charge them
a higher rate of interest without bearing an increased risk Nevertheless in this example
the bank would still serve the market for large loans first because of the higher
transaction costs for smaller loans
The view as described in figure 4 is shared among most traditional banks and investors
in industrialized as well as in developing countries In addition to neglecting the
possibility of generating profits by offering microcredit themselves199 they also hesitate
to lend to MFIs because they consider their business too risky
194 See Schreiner (1997) p 64195 ldquoPAR shows the real risk of the portfolio by comparing outstanding loan balances for loans with atleast one late payment to the outstanding loan portfoliordquo Gross and de Silva (2002) p 22196 Own calculations See Appendix 2197 See Seibel (2000) p 11198 The Economist (1998) pp 92 et sqq199 Busch and Kort (2004) p 8
39
Figure 4 The extended Model
Source Own diagram adapted from Stiglitz and Weiss (1981) p 394 Tschach (2000)
p 17
This attitude can be observed by comparing the ratio of equity to liabilities which is
considerably higher for MFIs than for conventional banks200 When it comes to MFI
start-ups and those MFIs serving the low end market in remote areas even experienced
microfinance practitioners are skeptical if interest rates that fully recover all costs can
be charged201
Theoretically there are two ways to adjust this model to arrive at a conclusion which is
more favorable with regard to the profitability of microcredit One is to cut the
transaction costs and therefore reduce the downward shift of the R(I)small curve the
other is to allow the bank to further raise the interest rate without experiencing a
decrease in its return This means to increase I(s) and the respective rate of return
While in 2000 Tschach stated that transaction costs vary between 10 and 20 percent for
loans provided through the group lending model and between 15 and 30 percent for
200 See MicroRate and IADB (2003) p 30201 See Volkery (2004) p 33 Gibbons (2000) p 15 Gibbons and Meehan (2002) p 29 Goodwin-Groen (1999) p 8
INTEREST RATE I(l)
SmallLoans
LargeLoans
Transaction costs
I(s)
R(i)large
R(i)small
EX
PE
CT
ED
RE
TU
RN
TO
TH
E B
AN
K
40
individual loans202 it was recommended in 1999 that MFIs should target a range
between 15 and 25 percent203 Some best practices on the other hand have already
achieved single digit numbers Currently BDB might be the most efficient MFI in the
world with transaction costs at just 47 percent in 2001204 Even though the low costs of
BDB have to be acknowledged its achievement has to be put in perspective As stated
above with an average loan balance of more than $5000 it does not serve the low end
market In addition it works in an environment with a high population density which
means that it can reach a relatively large group of borrowers per branch This is a
comparative advantage many Asian MFIs enjoy as can be illustrated by comparing
Bangladesh and Bolivia Both countries are at the forefront of the development of
microfinance in their respective continent but while in Bangladesh more than 1000
people are living per square kilometer the average for Bolivia is only eight205
Therefore it is consistent that the most efficient MFI in Latin America Fondo
Financiero Privado para el Fomento a Iniciativas Economicas has transaction costs of
114 percent206 With an average loan size greater than the annual GDP per Capita this
institution also does not serve the low end market207
Despite the impressive efficiency gains in the described examples most MFIs are far
from achieving these numbers and many are unlikely to reach them due to the
environment within which they work A survey of 67 MFIs from 31 countries found the
average transactions costs in 2002 to be 279 percent with a median of 206 percent208
However even if these institutions were to increase their efficiency to best practice
standards their transaction costs would still be significantly higher than those of
traditional banks providing much larger loans For these banks the respective costs vary
in a range between 05 and 3 percent209 According to this argument charging interest
rates considerably higher than conventional banks is the only way for MFIs to generate
higher returns and hence successfully compete for capital
202 See Tschach (2000) pp 100 et sqq203 See Gibbons and Meehan (1999) p 149204 See M-Cril (2001b) p 4205 See CIA (2004)206 See MicroRate (2004)207 In this paper the term ldquolow endrdquo refers to the definition of the MBB (2003) p 54 Loans worth less than 20 percent of the respective countryrsquos GDP per capita are described that way 208 Own calculations See Appendix 3209 See M-Cril (2004a) p 16
41
6 Interest Rates
61 Setting the right Interest Rate
Before addressing the questions to what extend MFIs can raise their interest rates
without putting the repayment rate or the social benefits of their customers at risk a
basic model will be presented This model will illustrate how a MFI should set their
rates in order to not only cover their costs but also to generate an appropriate profit to
finance further growth and attract additional capital
In 2002 CGAP revised its 1996 paper ldquoMicrocredit Interest Ratesrdquo210 which outlines
the standard method of setting sustainable interest rates for commercially oriented
MFIs According to this model the annual effective interest rate (I) should be calculated
as shown below
(1) I = LL
IIKCFLLTA
minusminus+++
1
With each variable being a decimal fraction of the average outstanding loan portfolio
whereby TA stands for the transaction costs as described above LL represents the
annual loan loss and II stands for investment income eg on liquid assets The cost of
funds (CF) consist of the interest and administrative costs needed to obtain deposits and
commercial loans as well as of the imputed costs on equity due to inflation K stands for
the capitalization rate which represents the net real profit Keeping this rate high is
important to finance the future growth of the loan portfolio This can be either done
through investors attracted by high profitability or through borrowing For the latter an
increase in equity is inevitable since it is required as a safety cushion by lenders
Since this model ignores the timing of cash flows and does not take taxes into account
it has to be regarded as fairly imprecise and hence should not be used for business
planning Nevertheless it can be used for an approximation of the interest rate that a
MFI would need to charge to provide its services as planned In the following I will
210 See Rosenberg (2002) pp 1 et sqq
42
apply this model on a fictitious MFI working in a rural area of Latin America with low
end customers In this setting it seems realistic to estimate transaction costs of 35
percent and loan loss rate of two percent211 If funds were borrowed at commercial
terms their costs can be assumed to equal at least 15 percent of the average outstanding
loan portfolio212 Estimating the capitalization rate is more challenging First the
targeted portfolio growth rate is set at 75 percent This is slightly below the 751 percent
average annual portfolio growth between 2000 and 2002 found by a survey of 25
different MFIs based in Central and South America213 If the extend to which the MFI
can leverage stays constant the loan portfolios growth would be limited by the growth
rate of the equity To express the capital needed for this growth as a share of the loan
portfolio it is necessary to estimate the ratio between the equity and the outstanding
loan amount According to the survey mentioned above the loan portfolios of the 25
Latin American MFIs equal on average 215 times their equity214 With this number the
capital needed to increase the equity by 75 percent would corresponds to approximately
35 percent of outstanding loan amount (075215) Finally the investment income has to
be estimated Since liquid assets that are available short term do not generate high
returns say five percent it does not seem advisable for the MFI to hold more than a
quarter of its loan portfolio in this form Hence the profit generated in this way would
equal 125 percent of the outstanding loan amount Using these numbers the equation to
calculate the annual effective interest rate reads as follows
(2) I = LL
IIKCFLLTA
minusminus+++
1 =
0201
01250350150020350
minusminus+++
= 0875
As a result the MFI would need to charge an annual effective interest rate of
approximately 875 percent on its loans in order to sustainable provide its services and
finance its growth without depending on donor money This rate might decrease once
the MFI matures the growth slows down and cheaper funds become available but it
will stay significantly higher than any rate charged by conventional banks
211 MicroRate and IADB (2004) pp 6 and 16212 See MicroRate and IADB (2004) p 616 and 28213 Own calculation See Appendix 4214 Own calculations See Appendix 5
43
62 Can Micro-Entrepreneurs bear these Rates
Although most MFIs charge rates significantly below 875 percent many critics have
strenuously argued against any rates exceeding those of traditional banks Rosanna
Barbero of Oxfam labeled an interest rate of 52 percent charged by a Cambodian MFI
ldquoludicrous evil and disgusting and stated that ldquo[n]o business in the world can make a
profit at these interest ratesldquo215 The former finance minister of Bangladesh Shah Kibria
even categorized the 20 percent effective rate charged by the Grameen Bank as to
high216 Many practitioners therefore believe in a strong negative correlation between
the interest rate and the demand for loans217 Others have argued more generally that
concentrating on profitability and therefore charging high interest rates diverts MFIs
from serving the poorest218
These views are still shared among many MFI managers donor agencies and especially
investors and politicians While the former are unwilling to charge interest rates for
funds they received ldquocheaplyrdquo (through grants or subsidized loans) and are worried
about undermining their social goals by charging higher rates of interest219 the latter are
reluctant to invest for reasons stated above or impose interest caps to catch the attention
of the public by pretending to protect the poor from usury rates220
In chapter 53 it has been described that micro-entrepreneurs due to their smaller
capital endowment have even better investment opportunities than big business The
extend to which this is true has not yet been answered An indication is the high
repayment rate observed within MFIs around the globe If their customers capital yield
did not exceed the charged interest rate how would they be able to repay According to
Gibbons and Meehan customers of MFIs can generally generate returns of more than
100 percent on their invested capital221 and ldquo[r]esearch in India Kenya and the
Philippines found that the average annual return on investments in microenterprises
215 See Kate and Roeun (2004)216 See Hodson (2001) min 1100217 See Morduch (1999a) p 1594218 See Prisma (2002) p 1219 See Schreiner (1997) p 60 Khandker (1998) p 106 220 See Gross and de Silva (2002) p 32 Jansson and Wenner (1997) p 36 et sqq Campion (2002) p 59221 See Gibbons and Meehan (1999) p 131
44
ranged from 117 to 847 percentrdquo222 Schmidt and Tschach found the marginal
productivity of capital to be as high as 1000 percent for the smallest loans provided by
the Bolivian MFI Caja Los Andes223 These findings are confirmed by the observation
of Rosenberg who found while working as a microfinance consultant for ten years he
never heard of a single MFI having problems to attract clients because interest rates
were too high224
To get a better understanding of the investment opportunities of low income people in
developing countries a typical example on how MFI clients invest their loans is as
follows
Zobair is working as a rickshaw puller in Bangladesh Like most of his colleagues he
does not own the rickshaw he is riding Therefore he has to pay a daily rent of about
$030 to the owner Since his average income of approximately $15 per day is hardly
enough to feed his family he is not able to save the $100 necessary to buy a rickshaw
on his own 225 If he could do so through obtaining a loan his income would increase by
$030 every day because he would not have to pay the rent for the rickshaw anymore
Assuming an average of six working days per week 226 and a life span of the rickshaw
of 5 years his internal rate of return would equal 15324 percent annually227
Consequently any interest rate charged by a MFI would be advantageous to him as long
as it would not exceed 15324 percent228
63 Should the Interest Rate be subsidized anyway
Despite the fact that numerous micro-entrepreneurs are able to generate tremendous
returns on their investment obviously not all are able to use capital in such a productive
way and therefore can not afford microcredit at commercial rates In order to reach
these people as well many MFIs continue to use donor money in order to keep their
interest rates low But even if the problems related to subsidized credit as described in
222 See Helms and Reille (2004) p 3223 See Schmidt and Tschach (2001) p 6224 See Rosenberg (2002) p 10225 This examples draws on observations made by the author in Dhaka (Bangladesh) during 2003226 Obviously extended holidays are not a viable option in this surrounding 227 Own calculation See Appendix 6228 This result is only valid if the loan is repaid in daily instalments For a weekly repayment schedule the interest rate charged by the MFI must not exceed 15119 percent in order to still be beneficial for Zobair
45
chapter 23 do not arise it might still not be the most effective tool to help poor people
as will be illustrated in the following example
A MFI faces two groups of potential clients one with businesses able to generate a
return of 125 percent on borrowed capital and another with a possible returns of 50
percent Assuming budget costs according to equation (2) the institution needs to
charge an interest rate of 875 percent and therefore only serves the former group
Supposed each group consists of 50 members demanding $100 loans the net gains to
society (NGS) could be calculated as follows
(3) NGS = 50 times ($125 ndash $875) = $1875
These gains would be due to the investments of the more profitable group which were
made possible through the loans provided by the MFI The less profitable group would
not borrow since their expected returns are not sufficient to pay for the interest If the
interest rate would be lowered to 30 percent both groups would be able to generate net
gains and therefore borrow from the MFI In order to provide loans at this rate the
institution would need to raise additional capital from non commercial sources The
NGS would be calculated as follows
(4) NGS = 50 times ($125 - $30) + 50 times ($50 - $30) + 100 times ($30 - $875) = 0
While the first terms represent the net gains to the respective groups the last describes
the costs incurred in providing the loans At a rate of 30 percent each loan would need
to be subsidized with $575 Hence the NGS actually fall after the introduction of the
subsidized loan This is due to the fact that the less profitable group is encouraged to
invest in relatively unproductive businesses In addition future growth of the MFI could
be jeopardized due to scarce donor money which is needed to finance the interest rate
subsidy Therefore it seems more advisable to continue to charge a rate of 875 percent
and spend the money used for subsidization on other programs such as health care or
education229
229 In Appendix 7 it will be shown that this result generally holds
46
7 Empirical verification
71 Setting up a Sample
To see if the findings of the previous chapters hold the effects which interest rates
charged by MFIs have on their performance will be analyzed in the following Up to
now such a study does not exist mainly because of a lack of adequate data Most MFIs
do not provide accurate information about the annual effective interest rate they charge
and therefore make an evaluation difficult
In 2002 Rosenberg distinguished eight different categories on how microcredit interest
rates are quoted230 These categories differ in several ways On the contrary to
traditional banks for example it is common for MFIs to state interest rates calculated on
a ldquoflatrdquo balance rather than on a declining one This means that the total loan amount is
used to determine the interest rate ignoring installments paid by the borrowers normally
on a weekly or monthly basis In addition many MFIs charge a certain upfront fee prior
to the loan disbursement require compulsory savings at a lower rate or state their
interest rate for semi annual terms only On the one hand this is done to provide
numbers that are more meaningful to MFI customers who often lack the necessary math
skills to deal with compound interest on the other hand it is done to circumvent interest
rate ceilings imposed by the government231 Another problem is that most MFIs offer
different loan products without itemizing their respective shares to their total loan
portfolio As a result it is not possible to calculate a weighted average even if the rate
stated by the respective MFI could be transformed into an effective interest rate
Usually the portfolio yield is used as a proxy in order to make statements about the
interest rate charged by a certain MFI232 It is generally ldquocalculated by dividing total
cash financial revenue (all income generated by the loan portfolio but not accrued
interest) by the period average gross portfoliordquo233 The advantage of this method is that
even the hidden costs are considered Nevertheless it also has a severe shortcoming by
not taking late or defaulted payments into account Therefore the portfolio yield does
230 See Rosenberg (2002) p 5231 MicroRate (2002) p 8232 See MicroRate (nd)233 MicroRate and IADB (2003) p 39
47
not allow to draw conclusions regarding the correlation between the interest rate
charged by a MFI and its PAR
72 Examining the Sample
Through the appearance of rating agencies specialized in the microfinance sector more
adequate information has become available in recent years While MicroRate only
publishes the portfolio yield of rated MFIs M-Cril Microfinanza Microserve and
Planet Rating actually provide information about the annual effective interest rate for at
least some of the MFIs they analyze Although it is labelled differently from all of the
four institutions234 the term describes what is ldquothe highest income or yield that an
organisation can earn from its portfolio based on the terms of its loansrdquo235
Currently236 reports of 39 different MFIs from 20 countries providing accurate
information about the effective annual interest rate are available to the public This
sample should be used to verify the findings of the previous chapters237 Since a
comparison is made between the performances of MFIs based in different countries and
the ratings have been carried out in different years several adjustments are necessary
First the inflation of the respective country and the respective year(s)238 has to be taken
into account in order to only compare the real rates239 In addition the average
outstanding loan amount per borrower is divided by the respective countryrsquos GDP per
capita Since it can be assumed that ldquoonly the poorer households will be willing to take
the smallest loansrdquo240 this number can be used as a proxy for the poverty level
Although the sample size is far to small to represent the microfinance sector as a whole
and the results are statistically not significant the findings can still be used to underline
the theoretical conclusions drawn in the previous chapters In figure 5 the connection
234 M-Cril uses the name ldquoannual percentage raterdquo See eg M-Cril (2004a) p 25 Microfinanza uses the name ldquoexpected portfolio yieldrdquo See eg Microfinanza (2002c) p 25 Planet Rating uses the name ldquoannual effective interest raterdquo See eg Planet Rating (2004d) p 1 Microserve uses the name ldquotheoretical yieldrdquo See Microserve (2003) p 62235 See M-Cril (2004a) p 25236 As of September 28th 2004237 See Appendix 8 For exchange rates see FXTOP (2004)238 Where necessary a weighted average of the annual inflation rate was used See Appendix 9239 This is done through the following formula ir = (I ndash F) (1 + F100) While ir represents the real annual effective interest rate F represents the inflation rate 240 Morduch (1998) p 1572
48
between the average loan size and the transaction costs as a share of the average loan
portfolio is illustrated
Figure 5 Loan Size vs Interest Rate241
Source Own diagram
000
1000
2000
3000
4000
5000
6000
7000
8000
9000
10000
0 100 200 300 400 500 600
Loan Size
Inte
res
t R
ate
It can be seen that the interest rate is negative correlated to the loans size This can be
explained by the relative higher transaction cost for smaller loans as described in
chapter 52 In order to cover their costs MFIs serving the low end market need to
charge higher rates to their customers than those organizations serving the better off
poor Obviously there are several assumptions to this general finding Especially
striking are the two MFIs with an average loan size of approximately five times their
countries GDP per capita which still high interest rates This occurrence can be
explained by taking a closer look to the respective organizations One was established
less than two years prior to its rating and therefore still bears a lot of start up costs242
241 The equation for the regression line reads as follows Y = -00219X + 365 The correlation coefficient is 014242 See Microfinanza (2002b) p 1
49
the other managed to stay profitable while it almost quadrupled its loan portfolio in the
last two years243
Figure 6 Interest Rate vs PAR244
Source Own diagram
0
5
10
15
20
25
30
35
0 20 40 60 80 100 120
Interest Rate
PA
R
In Figure 6 the crucial correlation between the interest rates charged by a MFIs and its
PAR245 is examined According to the given sample the view of traditional banks and
investors that a higher interest rate leads to a higher default rate does not hold
Obviously one has to avoid to draw the opposite conclusion namely that a high interest
rates decreases the PAR The connection illustrated in figure 6 has to be interpreted as
follows Since high interest rates are related to small loans the low PAR for MFIs
charging high interest rates can actually be explained by the tremendous profitability of
small size investments Despite the high rates their customers are even more likely to
repay
243 See Planet Rating (2003b)244 The equation for the regression line reads as follows Y = -00768X + 68433 The correlation coefficient is 0235245 M-Cril only publishes the PAR for overdues greater than 60 days Therefore these ratios are used as a proxy for the industry standard of 30 days for some Asian MFIs
50
Finally it has to be examined if charging high interest rates actually enables MFI to
generate higher returns Although it can be expected that the combination of a low PAR
and a high interest rate leads to a high profitability it still has to be checked if this is not
outdone by soaring transaction costs Figure 7 illustrates the correlation between the
interest rate charged by a MFI and its financial self-sufficiency (FSS) The latter is the
ldquo[r]atio of total income to total adjusted expenses for the year Adjustments are made
for subsidised cost of funds (relative to market interest rate) equity (with respect to
inflation) and in-kind donationsrdquo246 It can be seen that the regression line actually does
indicate a positive correlation between the interest rate and the profitability of a MFI
Figure 7 Interest Rate vs FSS247
Source Own diagram248
0
20
40
60
80
100
120
140
160
180
0 20 40 60 80 100
Interest Rate
FS
S
246 M-Cril (2004a) p 53247 The equation for the regression line reads as follows Y = 02839X + 8901 The correlation coefficient is 0174248 Since the interest rate the customers of the MFI Foccas have to pay includes fees which are not passed on to the institution its interest rate in this diagram is set at 723 percent instead of the 10715 percent used for figure 6 See Planet Rating (2003b) p 1
51
This result does not necessarily disprove the findings of Stiglitz and Weiss since it can
be argued that MFIs simply do no increase their interest rates to the point where they
would maximize their expected returns But if this would be true why do MFIs not
charge higher rates of interest given the demand described in chapter 41 and 43 In
mature markets competition normally ensures prices not to exceed a certain level but
since many MFIs still operate in a ldquosellerrsquos marketrdquo249 this can not explain the findings
as described in figure 7 Therefore it has to be assumed that a combination of the
unwillingness of many microfinance practitioners to burden their customers with high
interest rates and the plain disbelief of traditional investors that micro-entrepreneurs can
bear those rates is responsible for this occurrence
249 See MicroRate and IADB (2003) p 9
52
8 Conclusions
It has been shown that MFIs are not only contributing significantly to the development
of the financial sector in their respective countries but also that they play an important
role to eradicate poverty by providing much needed capital to low income people which
are able to generate tremendous returns on their investments
The fact that the demand for microcredit is not met is mainly due to the view of most
for profit investors and traditional banks that offering financial services to poor people
can not be done profitable Because of this conviction they hardly invest in the
microfinance sector This does not have to be the case according to the findings of this
paper Although faced with relatively high transaction costs MFIs are able to charge
interest rates at levels that fully recover their costs Elizabeth Rhynersquos claim ldquothat the
most financially viable programs differed from their less viable peers in their
willingness to set interest rates at levels that would fully recover costsrdquo250 is backed by
the findings of this paper that high profitability is correlated to high interest rates
Theoretical models based on the findings of Stiglitz and Weiss can not be used as a
justification to ration credit for the microfinance sector since the interest rate that
maximizes profits to the lender can be assumed to exceed 100 percent for many MFIs
Nevertheless this rate is hardly charged although it has been shown that it can be done
The Mexican MFI Compartamos for example manages to keep its PAR as low as one
percent while charging an effective interest rate of more than 100 percent to
approximately 160000 clients251 In combination with this case the conclusions drawn
from examining the sample of MFIs in chapter 7 the claim of Hulme and Mosley as
stated in the introduction can be considered as wrong MFIs are in fact able to finance
rapid growth stay profitable by charging corresponding interest rates and still have a
significantly positive impact on the poverty level of their clients In the long run gains
in efficiency economies of scale a slowdown in growth and competition will ensure
interest rates drop as it has already been the case in countries like Bangladesh and parts
of Bolivia252
250 See Rhyne (1998) p 7251 See MicroRate (2004)252 See Microrate and IADB (2003) p 9
53
According to a MicroRate survey many MFIs are more profitable than Citibank and also
generate a higher return on investment than commercial banks in their respective
countries253 Investments companies like IMI or Blue Orchard will soon be able to
present a meaningful track record of their microfinance investments to potential
investors Ultimately the capital markets can not ignore the facts proving that it actually
can be profitable to invest in the microfinance sector but in order to raise money
quickly microfinance practitioners will have to continue to intensively promote their
cause not only to for profit investors but also to donors and multilateral agencies like
the World Bank
253 See MicroRate (2002) p 10
54
Appendix
Appendix 1 Average loan balance
Source Data is available through the Mix Market (2004)
Organization
Loan Portfolio 2002 (US$)
Loan Portfolio 2003 (US$)
Number of borrowers 2002
Number of Borrowers 2003
2CM 1263602 1400438 3622 3708ACF 955503 1611401 285 370ACLEDA 26846703 39391301 82598 98905ACME 1460881 1714844 4283 4600ADIM 369065 407798 1122 1395AFK 933306 1706577 250 467AgroInvest 4684249 9697411 5208 9629Al Amana 15593277 28677666 78114 101610AMSSFMC 612167 1040756 6183 6886AREGAK 3285273 3987011 11841 14377AVFS 214331 269819 1883 2866BancoSol 83629049 91175000 42290 56707BESA 10563980 15114430 4488 5061BPR AK 613362 876130 1730 3879BPR BMMS 133949 237946 1755 1779BRI 1344006170 1720072773 3056103 3100358BZMF 1592508 1922097 1250 1331CBDIBA 216587 242465 5764 2877CCA 2146235 4582302 4070 6585CCCP 447534 851678 6265 9450CEP 3795400 5261957 32291 42132CERUDEB 25093643 34873228 34490 44796CMEDFI 227674 250244 3467 3781CMM - Bogota 4836000 8135968 15635 22038CMMB 34880 56964 42 190COAC Maquita Cushunchic
870084 1855718 6603 7732
CODES 280843 263091 60 60CODESARROLLO 6714007 12935951 4391 6896Constanta 2943822 3536047 16134 18588COOPEC CAMEC MN
7152 29821 92 77
Crear - Tacna 3891116 4636094 3671 4948CREDIT 642094 81838 7532 8097CRYSTAL FUND 366456 421403 1379 1061DBACD 3473701 3876526 12812 19606ECLOF - ECU 1154292 728312 860 416ECLOF - MAL 441734 407227 1118 1500EKI 11833244 19245751 8999 13323EMT 4481589 5765281 84781 92173ESED 8579460 6834742 22790 20035
55
Eshet 185741 462569 3308 6540Faulu - KEN 9027332 7206344 17463 15000FDL 12503027 16545332 21306 25106FIE 35818903 41597315 26468 33100FINADEV 5512586 9770323 12775 14709Finance Salone 211312 434298 2225 7159Finca - TAN 1293430 1854834 20648 27499Finca - UGA 2451703 2798869 35610 36912FINCORP 4761288 10236896 941 858FJN 5473563 8037662 8107 11133FMFB 308158 1188896 713 3558FMM -Bucaramanga
6355518 10227000 25814 42464
FODEM 739181 939824 1909 2501FundaciESPOIR
898561 1883446 5911 9464
FUNDESER 798907 1373113 4072 5065Gasha 323748 413742 5504 6423GGLS Save the Children
64235 137957 1291 2362
GK 56986 166971 951 2718HKL 1363365 1420357 6648 5372HOPE 402799 603488 1098 1562IAMD 42132 56550 2780 2772IDECE 21312 39453 150 232IDF 2031944 2626382 31003 36580IMCEC - Dakar 254759 688449 1018 2983IMCEC - Thies 199799 571122 1164 1261
ISSIA 221615 246792 1409 1698JMCC 1962355 2609723 1471 2333KAFC 21710638 29241051 24850 32097KAMURJ 1003935 1411258 5559 5691Kashf 2355965 6271498 29655 59389KMBI 721409 1626666 11973 27266KPSCA 109299 128063 362 794K-Rep 14490447 20699963 38739 45379KSCS 18978 43740 140 297KVT 44075 70621 241 373LAPO 922478 1194633 18740 19139MEC ADEFAP 27788 69248 198 202MEC Bosangani 14357 31086 364 540MEDF 104113 136257 1278 1184Meklit 233170 252232 2084 3577Metemamen 22123 57778 943 1501MFSC 109261 171090 511 687MIKRA 2951028 5008784 4145 6095MIKROFIN 9560502 18380263 5633 7426Miselini 737387 1026639 10182 11431MRFC 11475440 9133130 163000 180000Mushuc Runa 2089076 5418325 3139 6232Nirdhan 2886777 3016171 29589 27457OCSSC 5245186 7658413 42157 6215o
56
Otiv Diana 95992 638422 229 1073Otiv Sambava 188094 437974 2002 1442Otiv Tana 66465 673175 337 1269Partner 9976448 15321304 7139 11935PCA 6878257 6885926 63113 58147PEACE 420746 627295 4192 5428PEDF 164399 254233 2357 3340Piyeli 809447 1206656 8674 4745PRESTANIC 2827502 3540367 1477 2605PRIDE - MAL 991888 854631 5376 5601PRIZMA 3881581 6838978 8112 10968ProMujer -Nicaragua
1006871 1424437 10436 13047
PTF 891566 1068881 8500 9070RBST 818594 1058115 619 723REMECU 1381705 1483471 10330 13996
RUSCA 60887 100820 454 994
SCSCS 89423 157472 873 1007SFPI 709497 903556 7728 9552Sidama 934260 1011798 10267 11346SPBD 117807 186029 647 1740Sunlink 819138 1056823 3401 3833Sunrise 5412366 8782868 4560 7256TEBA 108032426 176300111 163021 157776TIAVO 281978 838905 2049 459TPC 1140429 2267148 22869 31668TSPI 4650989 5383755 49649 75617UNICECAM 3442843 5943804 16039 19031Wasasa 230657 274908 2850 3728Wisdom 1306066 1404463 10524 12054XacBank 4910098 9829503 11063 18610Zakoura 15907288 12444768 103720 118980
Appendix 2 Portfolio at Risk
Source Data is available through the Mix Market (2004)
Organization PAR 2002ABA 202ACEP 464ACLEDA 175ACODEP 452ACSI 209Al Amana 010Apoyo Integral
483
AREGAK 692Banco Solidario
500
BancoSol 660BASIX 1296
57
BRI 437BURO Tangail
350
CEP 200CERUDEB 103CMAC -Sullana
567
CMM -Bogota
176
Compartamos 111Constanta 304Credi Fe 212CREDIAMIGO 409DBACD 010EBS 847EMT 010ESED 1311FADES 2311Faulu - KEN 246Faulu - UGA 096FDL 212FECECAM 428FED 436FIE 598FINADEV 021Finamerica 1133Finca - TAN 000Finca - UGA 297FMM -Bucaramanga
094
FMM -Popayan
088
FONDEP 013FORA 064Genesis Empresarial
1197
IDF 017KAFC 106Kashf 000KMBI 128K-Rep 229MiBanco 309MRFC 1742Nirdhan 373
PADME 079PAMECAS 284PCA 379PRIDE - TAN 018ProMujer -Nicaragua
073
RCPB 600REMECU 157SHARE 000
58
Soluci 182Spandana 014TEBA 106TSPI 355UMU 125UNICECAM 405Urwego 290UWFT 363WAGES 736WWB -Medellin
235
XacBank 061Zakoura 095
Appendix 3 Transaction Costs
Source Data is available through the Mix Market (2004)
OrganizationTransaction Costs
Acci Rural 1154ACEP 858ACLEDA 2430ACODEP 2920ACSI 924Al Amana 2576AREGAK 2856AssEF 1919Banco Solidario
1826
BancoSol 1210BASIX 1317BRI 1353BURO Tangail
2053
CEP 1759CERUDEB 5109CMAC -Sullana
1784
CMM -Bogota
2089
Compartamos 3341Constanta 4597Credi Fe 1978CREDIAMIGO 2525DBACD 1742EBS 2377EMT 3220ESED 1343FADES 1673FAMA 2436
59
Faulu - KEN 2253Faulu - UGA 4962FDL 1726FECECAM 2587FED 4083FIE 1125Finamerica 1563Finca - TAN 10753Finca - UGA 9096FMM -Bucaramanga
1925
FMM -Popayan
1112
FONDEP 5477FORA 3481Genesis Empresarial
1626
IDF 1695
K-Rep 1909LAPO 3511MiBanco 2456Nirdhan 1325NWTF 3109OCSSC 1155PADME 1131PAMECAS 1705PCA 1670PRIDE - TAN 4273ProMujer -Nicaragua
5078
RCPB 2059SHARE 2308Sidama 2662Soluci 2906Spandana 641TEBA 1213TSPI 3898UMU 4023UNICECAM 10120Urwego 7437Wisdom 1906WWB -Medellin
1703
XacBank 4144Zakoura 1881
60
Appendix 4 Portfolio Growth
Source Data is available through the Mix Market (2004)
Organization
Total Loan Portfolio in 2000
Total Loan Portfolio in 2002
ACODEP 5889394 7258487Adelante 4327 88594ADRI 1514681 2591240AgroCapital 11100088 12018280Banco Solidario 39632165 103420000
BancoSol 78031172 83629049CMAC - Sullana 14596365 28055720
COAC Maquita Cushunchic
348443 870084
CODESARROLLO 1374801 6714007Compartamos 10804279 41825248Crear - Tacna 3778816 3891116
Credi Fe 781616 9393936ECLOF - ECU 179247 1154292
FADES 11948814 15501578FAMA 6201411 8835134FIE 22524645 35818903Finamerica 16575104 16097113FINCOMUN 3278938 5696556FMM - Popayan 6241821 12212867
FONDECO 3456625 5101801Genesis Empresarial
11154234 17746288
MiBanco 36964072 95873333Mushuc Runa 90737 2089076ProMujer -Nicaragua
426541 1006871
WWB - Medellin 2891207 4580998
Appendix 5 Portfolio vs Equity
Source Data is available through the Mix Market (2004)
OrganizationLoan Portfolio Equity
ACODEP 7258487 1921447Adelante 88594 72973
ADRI 2591240 781477AgroCapital 12018280 10766101Banco Solidario 103420000 12961000BancoSol 83629049 15299415CMAC - Sullana 28055720 6210291
61
COAC Maquita Cushunchic
870084 260331
CODESARROLLO 6714007 1285103
Compartamos 41825248 18350446
Crear - Tacna 3891116 1016912Credi Fe 9393936 863848ECLOF - ECU 1154292 459226FADES 15501578 4138972FAMA 8835134 6377663FIE 35818903 5360484Finamerica 16097113 3817960FINCOMUN 5696556 1042241FMM - Popayan 12212867 8510494FONDECO 5101801 1658075Genesis Empresarial
17746288 4765816
MiBanco 95873333 24261889Mushuc Runa 2089076 434311ProMujer -Nicaragua
1006871 1196015
WWB - Medellin 4580998 2213249
Appendix 6 Internal Rate of Return
Source Excel (German Version) calculation based on own data
A B C D E F
1 Date Cash Flow
Interest Rate Internal Rate of Return Balance Interest Principal
23 01012004 -100 15324 100 025489547 0045104534 02012004 03 999548955 025489547 0045104535 03012004 03 99909676 02547805 004521956 04012004 03 998643412 025466524 0045334767 05012004 03 998188909 025454968 0045450328 06012004 03 997733247 025443383 0045566179 08012004 03 999826083 050928361 -0209283610 09012004 03 999374595 025485114 004514886
hellip hellip hellip hellip hellip helliphellip hellip hellip hellip hellip hellip helliphellip hellip hellip hellip hellip hellip hellip1562 23122008 03 177951388 000528711 0294712891563 25122008 03 148859724 000908336 0290916641564 26122008 03 119239161 000379437 0296205631565 27122008 03 089543096 000303935 0296960651566 28122008 03 059771337 000228241 0297717591567 29122008 03 029923692 000152354 0298476461568 30122008 03 -3434E-07 000076274 029923726
62
The formula in the square C3 reads as follows
ldquoXINTZINSFUSS(B3B1568A3A156815)rdquo
Appendix 7 Subsidized Interest Rates and the Net Gains to Society
SourceOwn calculations
For simplicity only two groups of potential clients are distinguished This is possible
since using a continuum of potential clients would lead to the same results In addition it
is assumed that the amount of every loan (L) is equal and that all clients invest the
whole loan amount Group H consist of NH potential clients with a rate of return (rH) on
their invested capital higher than the cost recovering interest rate charged by the MFI
(iC) Group L consists of NL potential clients with a rate of return (rL) on their invested
capital lower than iC If the MFI charges iC the NGS can be calculated as follows
NGSC = NH times (rH - iC) times L
Since rH is bigger than iH (rH gt iC) according to the definition presented above the term
NGSH must be positive as long as NH does not equal zero If the MFI introduces a
subsidised interest rate (iS) lower than rL the NGS can be calculated as follows
(1) NGSS = NH times (rH - iS) times L + NLtimes (rL - iS) times L + (NH + NL) times (iS - iC) times L
(2) NGSS = NH times (rH- iC) times L + NLtimes (rL - iC) times L
The term (NH + NL) times (iS - iC) times L describes the amount of money that is needed in order
to subsidize the interest rate to the level iS By setting up an inequation it can be
examined under which conditions the NGSS are bigger than the NGSC
(3) NGSS gt NGSC
(4) NH times (rH- iC) times L + NLtimes (rL - iC) times L gt NH times (rH - iC) times L
(5) NLtimes (rL - iC) times L gt 0
(6) rL gt iC
63
So the NGSS could only be bigger than the NGSC if equation 6 holds This is
impossible since it violated the definitions presented above Therefore the introduction
of subsidized interest rates is always accompanied with a drop in the NGS
Appendix 8 Interest Rate vs Loan Size vs FSS vs PAR
Source Data is available through the Mix Market (2004)
Organization Country
Real Interest Rate
Loan Size (divided by the GDP per Capita) FSS PAR
BTFFKyrgyz Republic 3803 48260 1487 698
BesaFoundation Albania 2184 16076 684 260RFF Albania 1198 5783 4764 277PSHM Albania 2194 000 5758 198Mi-Bospo Bosnia 2974 5499 1261 020Prizma Bosnia 3474 3569 103 064Agroinvest Serbia 2201 4401 875 020KCLF Kazakhstan 5713 1713 865 090
Foccas Uganda10716 (723) 1550 584 29
ACEP Senegal 3280 20941 1643 1Padme Benin 2715 13575 1667 08Papme Benin 3086 53659 1405 24Vital Finance Benin 2676 9394 1015 17Finadev Benin 1738 14850 1024 21ABA Egypt 2579 1613 1168 88ASBA Egypt 2597 1702 1252 68DBACD Egypt 2490 1643 1073 0SBACD Egypt 2500 1734 982 67AMSSF Morocco 6926 787 1306 04Fondep Morocco 5199 650 889 071Zakoura Morocco 4414 900 98 006ENDA Tunisia 4008 1351 110 102BSFL India 1954 3269 856 99Share India 3426 1440 951 0Spandana India 2942 1618 1367 026SWC India 1864 2626 42 3036SKS India 2248 1912 578 0Grama Vidiya India 3176 1221 76 18Sneha India 3451 1433 933 0Buro Bangladesh 3206 1882 1093 17Upap Pakistan 2073 8183 757 03Seeds Sri Lanka 1004 1088 605 287EMT Cambodia 4324 1676 1016 01TPC Cambodia 4470 2035 832 27
64
WTF Phillippines 5816 1095 941 74TSKI Phillippines 5794 777 96 79Cacja Ecuador 862 6189 9460 897ACME Haiti 6043 6934 11685 450Grupo Cama Mexico 8961 267 10717 288
65
Appendix 9 Inflation vs GDP per Capita
Source IMF (2004)
Country Subject Description Units Scale 2000 2001 2002 2003 2004
Albania Gross domestic product per capita current prices US dollars Units 1083988 1238206 1396172 1757778 2229712
Albania Inflation annual percent change Percent 00 31 52 24 34
Bangladesh Gross domestic product per capita current prices US dollars Units 329310 327980 344494 369495 393717
Bangladesh Inflation annual percent change Percent 22 15 38 54 64
Benin Gross domestic product per capita current prices US dollars Units 361340 368213 405951 494725 560129
Benin Inflation annual percent change Percent 42 40 24 15 26
Bosnia and Herzegovina Gross domestic product per capita current prices US dollars Units 1255837 1321429 1466090 1807392 2070508
Bosnia and Herzegovina Inflation annual percent change Percent 50 32 03 02 09
Cambodia Gross domestic product per capita current prices US dollars Units 276413 280352 296577 305940 321247
Cambodia Inflation annual percent change Percent -08 02 33 12 20
Ecuador Gross domestic product per capita current prices US dollars Units 1227711 1590267 1804362 1957183 2082156
Ecuador Inflation annual percent change Percent -77 377 126 79 32
Egypt Gross domestic product per capita current prices US dollars Units 1550982 1461431 1278462 1188060 1083158
Egypt Inflation annual percent change Percent 28 24 24 32 52
India Gross domestic product per capita current prices US dollars Units 454206 458849 472915 542554 602625
India Inflation annual percent change Percent 40 38 43 38 47
Kazakhstan Gross domestic product per capita current prices US dollars Units 1236159 1490946 1655148 2000598 2579554
Kazakhstan Inflation annual percent change Percent 134 83 59 64 68
Kyrgyz Republic Gross domestic product per capita current prices US dollars Units 278256 306130 321079 349632 380637
Kyrgyz Republic Inflation annual percent change Percent 187 69 21 31 45
66
Mexico Gross domestic product per capita current prices US dollars Units 5957486 6274468 6425203 6111754 6377064
Mexico Inflation annual percent change Percent 95 64 50 45 44
Morocco Gross domestic product per capita current prices US dollars Units 1161302 1162154 1199584 1432725 1541041
Morocco Inflation annual percent change Percent 19 06 28 12 20
Pakistan Gross domestic product per capita current prices US dollars Units 437381 400356 440471 492913 538120
Pakistan Inflation annual percent change Percent 44 31 32 29 46
Philippines Gross domestic product per capita current prices US dollars Units 979423 900225 950707 963765 1018710
Philippines Inflation annual percent change Percent 43 61 31 30 54
Russia Inflation annual percent change Percent 208 215 158 137 103
Senegal Gross domestic product per capita current prices US dollars Units 478704 474460 507408 634171 714622
Senegal Inflation annual percent change Percent 09 30 23 -00 08
Serbia and Montenegro Gross domestic product per capita current prices US dollars Units 1031263 1389384 1882036 2491799 2795805
Serbia and Montenegro Inflation annual percent change Percent 699 911 212 113 79
Sri Lanka Gross domestic product per capita current prices US dollars Units 846811 796025 828256 904330 982466
Sri Lanka Inflation annual percent change Percent 62 142 96 63 64
Tunisia Gross domestic product per capita current prices US dollars Units 2034360 2065140 2149421 2534823 2881273
Tunisia Inflation annual percent change Percent 30 19 28 28 34
Uganda Gross domestic product per capita current prices US dollars Units 293404 249682 279587 280802 287204
Uganda Inflation annual percent change Percent 45 -20 57 51 35
67
References
Akerlof George A The Market for ldquoLemonsrdquo Qualitative Uncertainty and the Market Mechanism in Quarterly Journal of Economics Vol 84 (1970) pp 488-500
Amin Ruhul et al Integration of an Essential Service Package (ESP) in Child and Reproductive Health and Family Planning with a Micro-Credit Program for poor Women Experience from a Pilot Project in Rural Bangladesh in World Development Vol 29 (2001) No 9 pp 1611-1621
Bester Helmut Screening vs Rationing in Credit Markets with Imperfect Information in The American Economic Review Vol 75 (1985) No 4 pp 850855
Borst Dietmar Microfinance ndash Theoretische Grundlagen fuumlr den Einsatz sowie die Abschaumltzung des Potentials anhand einer Datenbankuntersuchung zur Verwundbarkeit der laumlndlichen Bevoumllkerung in Vietnam unpublished diploma thesis Karlsruhe 2004
BRAC Annual Report 2002 Dhaka 2003
Busch Alexander Kort Katharina Die Peanuts-Banker und ihre Kunden in Handelsblatt Nr 150 published August 5th 2004 p 8
Campion Anita Challenges to Microfinance Commercialization in Journal of Microfinance Vol 4 (1999) No 2 pp 57-65
Chu Michael Key Issues of Development Finance Somerville (MA) 1998
Dornbusch Ruumldiger Fischer Stanley Makrooumlkonomie Oldenburg 1995
Dunn Seth Flavin Christopher Moving the Climate Change Agenda Forward in State of the World New York London 2002 pp 24-50
Farrington Todd Efficiency in Microfinance Institutions in The MicroBanking Bulletin Issue No 4 pp 18-24
Gardner Gary The Challenge for Johannesburg Creating a More Secure World in State of the World New York London 2002 pp 3-23
Ghatak Subrata On Interregional Variations in Rural Interest Rates in Journal of Developing Areas Issue 18 pp 21-34
Gibbons David Serving the Poorest Sustainably in The MicroBanking Bulletin Issue No 5 (2000) pp 13-16
Gibbons David Meehan Jennifer W The Microcredit Summitrsquos Challenge WorkingToward Institutional Financial Self-Sufficiency While Maintaining a Commitment to Serving the Poorest Families in Journal of Microfinance Vol 1 (1999) No 1 pp 131-192
68
Goodwin-Groen Ruth Do Asian MFIs Access Funds from Commercial Banks inThe MicroBanking Bulletin Issue No 3 pp 8-10
Grameen Bank (ed) Grameen Generalized System Dhaka 2003
Gross Alexandra de Silva Samantha Social Fund Support of Microfinance A Reviewof Implementation Experience The World Bank Social Protection Discussion Paper No 0215 Washington DC 2002
Hashemi Syed M Schuler Sidney R Sustainable Banking with the Poor A Case Study of Grameen Bank Dhaka 1997
Helms Brigit Reille Xavier Interest Rate Ceilings and Microfinance The story so farConsultative Group to assist the Poor Occasional Paper No 9 September 2004 Washington DC 2004
Hoff Karla Stiglitz Joseph E Introduction Imperfect Information and Rural Credit Markets-Puzzles and Policy Perspectives in The World Bank Economic Review Vol 4 (1990) No 3 pp 235-250
Holcombe Susan Managing to Empower The Grameen Bankrsquos Experience of Poverty Allevation Dhaka 1995
Hulme David Mosley Paul Finance against Poverty London 1996
Jalvaani (ed) Flush with loans Micro credit for rural sanitation Vol 2 (1999) No 2 pp 1-2
Khandker Shahidur R Fighting Poverty with Microcredit Experience in Bangladesh Oxford et al 1998
Khandker Shahidur R Khalily Baqui Khan Zahed Grameen Bank Performance andSustainability The World Bank Discussion Paper No 306 Washington DC 1995
Lipsey Rechard G An Introduction to Positive Economics 5th edition London 1979
Littlefield Elizabeth Morduch Jonathan Hashemi Syed M Is Microfinance an Effective Strategy to Reach the Millennium Development Goals Consultative Group to Assist the Poorest Focus Note No 24 Washington DC 2003
Martinot Eric Cabraal Anil World Bank Solar Home Systems Projects Experience and Lessons Learned 1993-2000 in Renewable Energy Oxford 2000 pp 1-8
M-Cril Microfinance Review 2003 revised February 2004 Gurgaon 2004a
Mezzera Jaime Microcredit in Brazil The Gap Between Supply and Demand in The MicroBanking Bulletin Issue No 8 (2000) pp 22-24
The MicroBanking Bulletin (ed) Note to the Reader Vol 1 (1997) Issue No 1 pp 5-8
69
The MicroBanking Bulletin (ed) An Introduction to the Peer Groups and Tables Issue No 9 (2003) pp 53-60
MicroRate IADB Performance Indicators for Microfinance Institutions Technical Guide 3rd edition Washington DC 2003
MkNelly Barbara Dunford Christopher Impact of Credit with Education on Mothers and Their Young Childrenrsquos Nutrition Lower Pra Rural Bank Credit with Education Program in Ghana Freedom from Hunger Research Paper No 4 Davis (CA) 1998
MkNelly Barbara Dunford Christopher Impact of Credit with Education on Mothers and Their Young Childrenrsquos Nutrition CRECER Credit with Education Program in Bolivia Freedom from Hunger Research Paper No 5 Davis (CA) 1999
Morduch Jonathan The Microfinance Promise in Journal of Economic Literature Vol 37 (1999b) No 4 pp 1569-1614
Neus Werner Einfuumlhrung in die Betriebswirtschaftslehre Tuumlbingen 1998
Otero Maria Bringing Development Back into Microfinance Journal of Microfinance Vol 1 (1999) No 1 pp 8-19
Panjaitan-Drioadisuryo Rosintan D M Cloud Kathleen Gender self-employment and microcredit programs An Indonesian case study in The Quarterly Review of Economics and Finance Vol 39 (1999) pp 769ndash779
Perkins Dwight H et al Economics of Development 5th edition New York London 2001
Pitt Mark M Khandker Shahidur R Credit Programs for the Poor and the Health Status of Children in Rural Bangladesh in International Economic Review Vol 44 (2003) No 1 pp 87-118
Raiffeisen Friedrich W The Credit Unions 8th edition Neuwied 1966
Rhyne Elizabeth The Yin and Yang of Microfinance Reaching the Poor and Sustainability in The MicroBanking Bulletin Issue No 2 (1998) pp 6-9
Richardson David C Unorthodox Microfinance The Seven Doctrines of Success in The MicroBanking Bulletin Issue No 4 (2000) pp 3-7
Robinson Marguerite S The Microfinance Revolution Sustainable Finance for the Poor Washington DC 2001
Robinson Marguerite S The Microfinance Revolution Volume 2 Lessons from Indonesia Washington DC 2002
Rosenberg Richard Microcredit Interest Rates Consultative Group to assist the Poorest Occasional Paper No 1 revised November 2002 Washington DC 2002
70
Roth Michael Steinwand Dirk Mikrofinanz Weltweites Erfolgsmodell nur nicht inDeutschland Zur Uumlbertragbarkeit der Erfahrungen aus Entwicklungslaumlndern auf Deutschland Deutsche Gesellschaft fuumlr Technische Zusammenarbeit (ed) Eschborn2004
Schmidt Reinhard H Tschach Ingo Microfinance as a Nexus of Incentives Finance and Accounting Working Paper No 87A Frankfurt 2001
Schreiner Mark A Framework for the Analysis of the Performance and Sustainability of Subsidized Microfinance Organizations with Application to Banco Sol of Bolivia and Grameen Bank of Bangladesh unpublished PhD dissertation Columbus (O) 1997
Seibel Hans D Recent Developments in Microfinance Development Research Center Working Paper No 1998-5 Cologne 1998
Seibel Hans D History matters in microfinance in Small Enterprise Development ndashAn International Journal of Microfinance and Business Development Vol 14 (2003a) No 2 pp 10-12
Seibel Hans D Schmidt Petra How an Agricultural Development Bank Revolutionized Rural Finance The Case of Bank Rakyat Indonesia International Fund for Agricultural Development Rural Finance Working Paper B 5 Rome 2000
Sen Amartya Oumlkonomie fuumlr den Menschen ndash Wege zu Gerechtigkeit und Solidaritaumlt in der Marktwirtschaft Muumlnchen Wien 2000
Serageldin Ismail The View of the Chair in Consultative Group to Assist the Poorest Newsletter Issue No1 (1996) pp 1 11-12
Soros George Die Krise des globalen Kapitalismus Offene Gesellschaft in Gefahr Berlin 1998
Staschen Stefan Regulation and Supervision of Microfinance Institutions State of Knowledge Deutsche Gesellschaft fuumlr Technische Zusammenarbeit (ed) Eschborn 1999
Steinwand Dirk The Alchemy of Microfinance The Evolution of the IndonesianPeoples Credit Banks (BPR) to 1999 and a Contemporary Analysis Berlin 2001
Stiglitz Joseph E Peer Monitoring and Credit Markets in The World Bank Economic Review Vol 4 (1990) No 3 pp 351-366
Stiglitz Joseph E Weiss Andrew Credit Rationing in Markets with Imperfect Information in The American Economic Review Vol 71 (1981) No 3 pp 393-410
Tschach Ingo Theorie der Entwicklungsfinanzierung Mit Kleinkreditprogrammen Kredit- und Arbeitsmarktsegmentierung uumlberwinden Frankfurt 2000
UNDP Human Development Report 2004 New York 2004
71
UNFPA state of the world population 2004 New York 2004
UNICEF The State of the Worldrsquos Children 2002 NewYork Geneva 2002
Varley Robert C G Financial Services and Environmental Health Household Credit for Water and Sanitation Environmental Health Project Applied Study No 2 Washington DC 1995
Volkery Carsten Kampf um Straszligenhaumlndler in Die Zeit Nr 23 published May 27th
2004 p 33
Wardhana Ali Introduction in The Microfinance Revolution ndash Sustainable Finance for the Poor Washington DC 2001 pp XVII-XXVII
Woodworth Warner Woller Gary Greetings from the Editors Journal of Microfinance Vol 1 (1999) No 1 p 6
The World Bank Group World Development Indicators 2004 Washington DC 2004
Worldwatch Institute (2002) Vital Signs 2002 New York London 2002
Wimmer Nancy Barua Dipal Less is more Microfinance for solar energy in rural areas in Renewable Energy World Review Issue 2004-2005 Vol 7 (2004) No4 pp 170-179
Yunus Muhammad Grameen Bank II ndash Designed to Open new Possibilities Dhaka 2002
Yunus Muhammad Grameen ndash Eine Bank fuumlr die Armen dieser Welt Muumlnchen 1998a
Internet References
Abishek Lal (nd) An Overview of Microfinance and Environmental Management [http wwwgdrcorgicmenvironabhishekhtml] (availability date October 5 2004)
ACCION (nd) our history [httpwwwaccionorgabout_our_historyasp] (availability date October 5 2004)
ACCION (nd) key statistics [httpwwwaccionorgabout_key_statsasp] (availability date October 5 2004)
Ahmad Zulfiqar (nd) Forms of Regional Cooperation in Microfinance in South Asia [httpwwwbwtporgarcmpakistanIV_News_and_EventsBWTPworkshopZulfiqar20Ahmad20paper20(BWTP-PMN2029Jan04)pdf (availability date October 6 2004)
72
Ahmed Salehuddin (2003) Foreword [httpwwwpksf-bdorgaprm_summit_brochure htm] (availability date September 30 2004)
Annan Kofi (2002) Statement at The Microcredit Summit +5 [httpwww microcreditsummitorgenews2003-03_sp_chowdhuryhtml) (availability date October 5 2004)
Barnes Carolyn (2001) Microfinance Program Clients and Impact An Assessment of Zambuko Trust Zimbabwe [httpwwwmicrofinancegatewayorgfiles18553_Barnes_Zambuko_Trust_2001pdf] (availability date October 5 2004)
Barnes Carolyn Gaile Gary Kibombo Richard (2001) The Impact of Three Microfinance Programs in Uganda [httpwwwmicrofinancegatewayorgfiles2935_Barnes_2001pdf] (availability date October 5 2004)
Barua Dipal (2004) Success of Grameen Shakti in the Field of Renewable Energy Sector in Bangladesh [httpwwwrenewables2004depptPresentation1-SessionVA(14-1530h)-Baruapdf] (availability date September 30 2004)
Bhatt Ela (1997) In 1975 [httpwwwmicrocreditsummitorgdeclarationhtm] (availability date September 30 2004)
BlueOrchard (2004a) Microfinance [httpwwwblueorchardchenmicrofinance_institutions asp] (availability date October 5 2004)
BlueOrchard (2004b) January 2004 Newsletter [httpwwwblueorchardchmedialibrarywebsitenewsletter_jan_2004pdf] (availability date October 5 2004)
Brynjolfsson John (2004) John Brynjolfsson Discusses Recent Trends in TIPS Issuance [httpwwwpimcocomLeftNavPIMCO+Spotlight2004Spotlight_2_04htm] (availability date October 5 2004)
CGAP (2003) Report to the Board of Executive Directors [httpwww-wdsworldbankorgservletWDSContentServerWDSPIB20031208000012009_20031208101736RenderedPDF27441pdf] (availability date October 5 2004)
Chen Shaohua Ravallion Martin (2004) How have the worldrsquos poorest fared since the early 1980s [httpwwwworldbankorgresearchpovmonitorMartinPapersHow_have_the_poorest_fared_since_the_early_1980spdf] (availability date October 5 2004)
Cheston Susy Kuhn Lisa (2002) Empowering Women through Microfinance[httpwwwmicrofinancegatewayorgfiles3240_Cheston_2002doc] (availability date October 5 2004)
Christen Robert P et al (1995) Maximizing the Outreach of Microenterprise FinanceAn Analysis of Successful Microfinance Programs [httpwwwdecorgpdf_docsPNABS519 pdf] (availability date October 5 2004)
73
CIA (2004) The World Factbook [httpwwwciagovciapublicationsfactbook] (availability date October 5 2004)
Clear Profit (2004) Microfinance Bond Record May Double [httpwwwclear-profitcomissuescpsep04txt] (availability date September 30 2004)
Daley-Harris Sam (2003) State of the Microcredit Summit Campaign Report 2003 [httpwwwmicrocreditsummitorgpubsreportssocr2003SOCR03-E[txt]pdf] (availability date September 30 2004)
Dominiceacute Robert (2004) Interview in Microfinance Bond Record May Double [httpwwwclear-profitcomissuescpsep04txt] (availability date September 30 2004)
Donahue Jill Kabbucho Kamau Osinde Sylvia (2001) HIVAIDSmdashResponding To A Silent Economic Crisis Among Microfinance Clients In Kenya and Uganda [httpwwwmicrosave-africacomget_fileaspdownload_id=541] (availability date September 30 2004)
Donahue Jill Sussman Linda (1999) Building a Multi-Sectoral Response Follow-Up Assessment of Programming for Children and Families Affected by HIVAids in Kenya [httpwwwdecorgpdf_docspnacg778pdf] (availability date September 30 2004)
The Economist (1998) [httpwwweconomistcomdisplaystorycfmstory_id=S2629H3C28Q13F240A] (availability date September 30 2004)
Finca (nd) Introduction [httpvillagebankingorgwhereindexphp3] (availability date September 30 2004)
Fischer Stanley (2003) Statement at The Asia Society and Womens World BankingAnnual Microfinance Conference [httpwwwiiecomfischerpdffischer051303pdf] (availability date September 30 2004)
Friedman Milton (nd) Samuha [httpwwwsamuhaorgm-1htm] availability date September 30 2004)
FXTOP (2004) Historical Exchange Rates [httpfxtopcomdehistoratesphp3] (availability date September 30 2004)
Gibbons David Meehan Jennifer W (2002) Financing Microfinance for Poverty Reduction [httpwwwmicrocreditsummitorgpapersfinancing_finalpdf] (availability date September 30 2004)
Grameen Bank (2004) Grameen Bank At a Glance [httpwwwgrameen-infoorgbankcdshtml] (availability date September 30 2004)
Grameen Trust (nd) Grameen Bank Replication Program [httpwwwgrameen-infoorggrameengtrustreplicationhtml8721] (availability date September 30 2004)
74
Hossain Farhad (2004) Microfinance in Development [httpwwwvalthelsinkifi staff jkoponenb1104FarhadFeb2304pdf] (availability date October 5 2004)
IMF (2004) Data [httpwwwimforgexternalpubsftweo200402datadbginimcfm] (availability date October 5 2004)
IMI (2004) Investments [httpwwwimi-agcomoverviewindexhtml] (availability date September 30 2004)
IPCC (2001) Summary for Policymakers [httpwwwipccchpubspm22-01pdf] (availability date September 30 2004)
Jansson Tor Wenner Mark (1997) Financial Regulation and its Significance for Microfinance in Latin America and the Caribbean [httpwwwgdrcorgicmgoverniadb-janssonpdf] (availability date October 5 2004)
Ken Daniel Ten Roeun Van (2004) The Cycle of Debt - As Microcredit Institutions Grow Some Question Their Effect on Poverty [httpwwwcamnetcomkhcambodiadaily selected_featurescd-21-02-04htm] (availability date September 30 2004)
Kim Julia (2002) Social Interventions for HIVAIDS - Intervention with Microfinance for AIDS and Gender Equity [httpwwwwitsaczaradarPDF20filesIntervention_monograph_no_picspdfpdf] (availability date September 30 2004)
Llanto Gilberto (nd) Vietnam [httpwwwadborgDocumentsBooksCentral_Banks_MicrofinanceCountry_Studiesvietnampdf] (availability date September 30 2004)
The Microfinance Gateway (nd) Frequently Asked Questions [httpwwwmicrofinance gatewayorgsectionfaq1] (availability date October 5 2004)
Microfinance Rating and Assessment Fund (2004) Qualified Raters [httpwwwmfrating orgmfi_institutionsqualified_ratershtml] (availability date October 5 2004)
Microcredit Summit (1997) Declaration and Plan of Action [httpwwwmicrocreditsummit orgdeclarationhtm] (availability date September 30 2004)
MicroRate (nd) Performance Indicators and Ratios [httpwwwmicroratecomENGLISHsiteRATINGSindicatorshtml] (availability date September 30 2004)
MicroRate (2002) The Finance of Microfinance [httpwwwmicroratecomPDFFinance20of20Microfinancepdf] (availability date September 30 2004)
MicroRate (2004) Adjusted comparison table [httpwwwmicroratecomENGLISHsitePDFAdjusted20Comparison20Table060320engpdf] (availability date October 5 2004)
75
Mix Market (2004) The Mix Market [httpwwwmixmarketorg] (availability date October 5 2004)
Morduch Jonathan (1999b) The Grameen Bank A Financial Reckoning [httpwwwwwsprincetonedu~rpdsmacarthurdownloadsmorduch_grameen_bankpdf] (availability date September 30 2004)
Pallen Dean (1997) Environmental Sourcebook for Micro-Finance Institutions [httpwwwacdi-idagccaINETIMAGESNSFvLUImagesea20summaries$fileSOURC Epdf] (availability date September 30 2004)
Prisma (2002) The Case for Private Capital Market Creation in the Development Field of Microfinance [httpwwwsocialenterprisenetpdfsprivate_capital_marketpdf] (availability date September 30 2004)
Schmidt Reinhard H Zeitinger C-P (1997) Critical Issues in Microbusiness Finance and the Role of Donors No 6 [httpwwwgdrcorgicmmfi-donorpdf] (availability date September 30 2004)
Seibel Hans D (2003b) Commodity finance a commercial proposition Micro- and Mesofinance for Agricultural Commodity Production Processing and Trade [httpwwwuni-koelndeew-fakaef05-20042003-420Commodity20Financepdf] (availability date September 30 2004)
Simanowitz Anton Walter Alice (2002) Ensuring Impact Reaching the Poorest while Building Financially Self-sufficient Institutions and Showing Improvement in the Lives of the Poorest Families [httpwwwidsacukimpactPublicationsWorkingPapersOP3MCSSumdoc] (availability date September 30 2004)
Smith Stephen C Jain Sanjay (1999) Village Banking and Maternal and Child Health Theory and Evidence from Ecuador and Honduras[httphomegwuedu~scsmith healthrevwd801pdf] (availability date September 30 2004)
United Nations (1999) International Year of Microcredit 2005 [httpods-dds-nyunorgdoc UNDOCGENN9976933PDFN9976933 pdfOpenElement] (availability date October 5 2004)
United Nations (2000) United Nations Millennium Declaration [httpods-dds-nyunorgdocUNDOCGENN0055951PDFN0055951pdfOpenElement] (availability date October 5 2004)
US Census Bureau (2004) Total Midyear Population for the World 1950-2050 [httpwwwcensusgovipcwwwworldpophtml] (availability date October 5 2004)
WHO (2004) Making pregnancy safer [httpwwwwhointmediacentrefactsheets fs276en] (availability date September 30 2004)
WHO (2001) Child Health [httpwwwwhointmipfiles2082AAGChildHealthpdf] (availability date September 30 2004)
76
The World Bank Group (nd) Health Nutrition and Population and the Millennium Development Goals [www1worldbankorghnpMDGMDG20-20HNPbookletpdf] (availability date September 30 2004)
Yunus Muhammad (1998) Championing the Right to Credit for Poor Women Around the World [httpaspgrameencom dialoguedialogue34interviewhtml] (availability date September 30 2004)
UNAIDS (2004) [httpwwwunaidsorgbangkok2004GAR2004_pdfUNAIDSGlobalReport2004_enpdf] (availability date September 30 2004)
Ratings
M-Cril (2000) SPANDANA [httpwwwratingfundorgspanishdocsSPANDANA_RatingReportpdf] (availability date October 7 2004)
M-Cril (2001a) BASIX [httpwwwbasixindiacomMcrilasp] (availability date October 7 2004)
M-Cril (2001b) BDB [httpwwwratingfundorgspanishdocsRF_BDBpdf] (availability date October 7 2004)
M-Cril (2001c) SNEHA [httpwwwratingfundorgspanishdocsRF_Sneha-u1pdf] (availability date October 7 2004)
M-Cril (2002a) KCLF [httpwwwratingfundorgdocsRF-KCLF-risk20reportdoc] (availability date October 7 2004)
M-Cril (2002b) NWTF [httpwwwratingfundorgspanishdocsRF_NWTFpdf] (availability date October 7 2004)
M-Cril (2002c) SEEDS [httpwwwratingfundorgspanishdocsRF_SEEDS_2002_Ratingpdf] (availability date October 7 2004)
M-Cril (2002c) Share [httpwwwratingfundorgspanishdocsRF_SHAREpdf] (availability date October 7 2004)
M-Cril (2002d) TSKI [httpwwwratingfundorgspanishdocsRF_Tski_mcrilfinal(-) reportpdf] (availability date October 7 2004)
M-Cril (2003a) ASA [httpwwwratingfundorgdocsASA20updatepdf] (availability date October 7 2004)
M-Cril (2003b) BURO [httpwwwm-crilcomburopdf] (availability date October 7 2004)
M-Cril (2003c) EMT [httpwwwratingfundorgdocsEMTpdf] (availability date October 7 2004)
77
M-Cril (2003d) SKS [httpwwwmixmarketorgendemanddemandshowprofileaspett=25ampshowinfo=adjusted] (availability date October 7 2004)
M-Cril (2003d) TPC [httpwwwratingfundorgdocsTPC_Finalpdf] (availability date October 7 2004)
M-Cril (2004b) UPAP [httpwwwratingfundorgdocsUPAP_2004pdf] (availability date October 7 2004)
Microfinanza (2002a) ACME [httpwwwratingfundorgspanishdocsACME_finalpdf] (availability date October 7 2004)
Microfinanza (2002b) BTFF [httpwwwratingfundorgspanishdocsBTFF_RatingReportpdf] (availability date October 7 2004)
Microfinanza (2002c) BESA [httpwwwratingfundorgspanishdocsBESA_RatingReportpdf] (availability date October 7 2004)
Microfinanza (2002d) CAME [httpwwwratingfundorgdocsEvaluacionCAME(-) Finaldoc] (availability date October 7 2004)
Microfinanza (2002e) RFF [httpwwwratingfundorgdocsRFF20finalpdf] (availability date October 7 2004)
Microfinanza (2002f) PSHM [httpwwwratingfundorgspanishdocsPSHM_Reportpdf] (availability date October 7 2004)
Microfinanza (2003) CAJCA [httpwwwratingfundorgdocsCalificacion_Jardin_Azuayo_ratingpdf] (availability date October 7 2004)
Microserve (2003) ENDA [httpwwwmixmarketorgendemanddemandshowprofileaspett=865ampshowinfo=adjusted] (availability date October 7 2004)
Planet Rating (2002a) FONDEP [httpwwwmfratingorgRatingscompleted_ratingshtml] (availability date October 7 2004)
Planet Rating (2002b) PRIZMA [httpwwwmixmarketorgendemanddemandshowprofileaspett=111ampshowinfo=adjusted] (availability date October 7 2004)
Planet Rating (2002c) SWS [httpwwwratingfundorgspanishdocsSWC_reportpdf] (availability date October 7 2004)
Planet Rating (2002d) ZAKOURA [httpwwwratingfundorgspanishdocsRF_Zakourapdf] (availability date October 7 2004)
Planet Rating (2003a) AMSSF [httpwwwratingfundorgdocsPlanetRating_AMSSF_010803pdf] (availability date October 7 2004)
Planet Rating (2003b) FOCCAS [httpwwwratingfundorgdocsPlanetRatingFOCCAS120803pdf] (availability date October 7 2004)
78
Planet Rating (2003c) PADME [httpwwwmfratingorgdocsPlaNetRatingPADME070302_Englishpdf] (availability date October 7 2004)
Planet Rating (2003d) PAPME [httpwwwmfratingorgdocsPAPME_PlanetRating080903pdf] (availability date October 7 2004)
Planet Rating (2003e) VITAL FINANCE [httpwwwmfratingorgdocsVital20Finance_Sept202003pdf] (availability date October 7 2004)
Planet Rating (2004a) ABA [httpwwwratingfundorgdocsABA_April202004pdf] (availability date October 7 2004)
Planet Rating (2004b) ACEP [httpwwwmfratingorgdocsACEPSeacuteneacutegal_2004pdf] (availability date October 7 2004)
Planet Rating (2004c) AGROINVEST [httpwwwratingfundorgdocsAgroInvest_June202004pdf] (availability date October 7 2004)
Planet Rating (2004d) ASBA [httpwwwratingfundorgdocsASBA_April202004pdf] (availability date October 7 2004)
Planet Rating (2004e) DBACD [httpwwwratingfundorgdocsDBACD_April202004pdf] (availability date October 7 2004)
Planet Rating (2004f) FINADEV [httpwwwmfratingorgdocsFinadev_2004pdf] (availability date October 7 2004)
Planet Rating (2004g) MI-BOSPO [httpwwwratingfundorgdocsMIBOSPO_160404pdf] (availability date October 7 2004)
Planet Rating (2004h) SBACD [httpwwwratingfundorgdocsSBACD_PlanetRating300604pdf] (availability date October 7 2004)
Other Sources
Interview Shaw Newaz Deputy General Manager of the Grameen Bank October 30th
2003
Hodson Charles (2001) Your Business Your World Jim Boulden CNN (ed) Dhaka 2001
1
Contents
Contents 1
Figures 3
Acronyms 4
1 Introduction 5
2 The Development of Microfinance 721 What is Microfinance 7
22 The Origin of Microfinance 8
23 Microfinance after the Second World War9
24 Microfinance Today11
3 The Impact of Microcredit 1332 The Eradication of extreme Poverty and Hunger13
33 Achievement of universal primary Education 15
34 Promote gender Equality and empower Women16
35 Reduce Child Mortality and improve Maternal Health17
36 Combat HIVAIDS Malaria and other diseases 18
37 Ensure environmental Sustainability 20
38 Develop a global Partnership for Development 21
4 Microcredit Outreach 2441 The Demand for Microcredit24
42 The Supply of Microcredit 25
43 Meeting the Demand26
44 Microfinance and the Capital Markets 29
5 Credit Rationing 3151 The imperfect Information Paradigm 31
52 Adaptation to the Microfinance Sector 33
53 Overcoming Credit Rationing for the Microfinance Sector 35
6 Interest Rates 4161 Setting the right Interest Rate41
62 Can Micro-Entrepreneurs bear these Rates43
63 Should the Interest Rate be subsidized anyway 44
7 Empirical verification 4671 Setting up a Sample 46
2
72 Examining the Sample47
8 Conclusions 52
Appendix 54Appendix 1 Average loan balance54
Appendix 2 Portfolio at Risk 56
Appendix 3 Transaction Costs 58
Appendix 4 Portfolio Growth 60
Appendix 5 Portfolio vs Equity 60
Appendix 6 Internal Rate of Return 61
Appendix 7 Subsidized Interest Rates and the Net Gains to Society62
Appendix 8 Interest Rate vs Loan Size vs FSS vs PAR 63
Appendix 9 Inflation vs GDP per Capita 65
References 67
Internet References 71
Ratings 76
Other Sources 78
3
Figures
Figure 1 Expected Bank Return and the Interest Rate 32
Figure 2 The extended Model 34
Figure 3 Marginal Productivity of Capital 36
Figure 4 The extended Model 39
Figure 5 Loan Size vs Interest Rate 48
Figure 6 Interest Rate vs PAR 49
Figure 7 Interest Rate vs FSS 50
4
Acronyms
BDB Bank Dagan Bali
BRAC Bangladesh Rural Advancement Committee
BRI Bank Rakyat Indonesia
CF Cost of Funds
CGAP Consultative Group to Assist the Poor(est)
FSS Financial Self-Sufficiency
GDP Gross Domestic Product
GNP Gross National Product
I Interest Rate
IADB Inter-American Development Bank
II Investment Income
IMI Internationale Mikro Investitionen Aktiengesellschaft
IPCC Intergovernmental Panel on Climate Change
K Capitalization Rate
LL Loan Loss
MBB MikroBanking Bulletin
MDG Millennium Development Goal
MFI Microfinance Institution
NGO Non Governmental Organization
NGS Net Gains to Society
PAR Portfolio at Risk
TA Transaction Costs
UN United Nations
USA United States of America
5
1 Introduction
The poor stay poor not because they are lazy but because they have no access to
capital1 If this claim made by nobel laureate Milton Friedman actually holds will be
discussed in the initial part of this paper
First a short overview of the development of the microfinance sector will be given
showing that the concept of providing financial services to low income people is much
older than still believed by many development practitioners and bankers around the
world This is important since it underlines the contribution that microfinance
institutions (MFIs) can make to the development of the financial sector in their
respective countries Subsequently the various ways how such services can assist low
income people will be discussed demonstrating that even the poorest can benefit from
the provision of small loans This is a view that is still questioned in the academia
In the second part of this paper it will be shown that although some 10000
organizations are involved in microfinance already2 they are not even close to meet the
tremendous demand for low scale financial services This sector is still widely neglected
by for profit investors and traditional bankers After examining why these groups
continue to avoid investments in the microfinance industry it will be checked if the
assumptions that underline their arguments actually hold The possibility if MFIs could
raise their interest rates to an extend that would allow them generate profits sufficiently
high to attract for profit investors will be discussed
According to Hulme and Mosley MFIs ldquocan either go for growth and put their resources
into underpinning the success of established and rapidly growing institutions or go for
poverty impact and put their resources into poverty-focused operations with a higher
risk of failure and a lower expected returnrdquo3 If this is true will be examined in the third
part by checking if poor borrowers are able to bear interest rates significantly above
1 See Friedman (nd)2 See BlueOrchard (2004a)3 See Hulme and Mosley (1996) p 206
6
those charged by conventional banks Finally a sample of 39 MFIs will be used to verify
the drawn conclusions by examining the effects their interest rates have on their
financial performances and their repayment record
7
2 The Development of Microfinance
21 What is Microfinance
According to the Journal of Microfinance the term defines what ldquois arguably the most
innovative strategy to address the problems of global povertyldquo4 This view is shared by
the United Nations (UN) which declared that the year 2005 would be the international
year of microcredit5 while their General Secretary Kofi Annan stated in 2002 that
ldquo[m]icrocredit is a critical anti-poverty tool and a wise investment in human capitalrdquo6
Hossain describes microfinance as ldquothe practice of offering small collateral free loans
to members of cooperatives who otherwise would not have access to the capital
necessary to begin a small business or other income generating activitiesrdquo7 This view is
to narrow since it not only excludes such services as saving accounts and insurances8
but also ignores the possibility of collateral demanding MFIs Although it is true that
many MFIs do not take collateral especially if they are focusing on the poorest which
normally do not possess any collateral9 several MFIs in fact do require some form of
collateral10
Roth and Steinwand give a more general definition They describe microfinance as ldquothe
provision of a wide range of financial services like saving accounts loans payment
services and insurances for people with no regular access to financial services through
traditional financial institutionsrdquo11 Here it is important not to confuse the terms
traditional or conventional with the term formal If for example an illiterate beggar
takes a $10 loan from the Grameen Bank in Bangladesh she becomes a client of a
4 See Woodworth and Woller (1999) p 65 See United Nations (1999) p 16 Annan (2002)7 Hossain (2004)8 See The Microfinance Gateway (nd) Robinson (2001) p9 Otero (1999) p 89 See chapter 3 for a more detailed discussion on poverty10 See Robinson 2002 p 24311 See Roth and Steinwand (2004) p 2 ldquodie Bereitstellung einer breiten Palette von Finanzdiensteistungen wie Spareinlagen Kredite Zahlungsverkehr und Versicherungsleistungen fuumlr Wirtschaftsakteure die keinen regelmaumlszligigen Zugang zu Finanzdienstleistungen durch klassische Finanzinstitutionen habenldquo
8
formal financial institution (a registered bank) but obviously not of a traditional or
conventional one12
Although the other services have become more important in recent years microcredit is
still considered their central service by most MFIs In many countries it refers to loans
below $ 100013 however for significant cross country comparison it is more
meaningful to look at the ratio of the loan amount to the gross national product (GNP)
or gross domestic product (GDP) per capita for the respective countries While a loan of
$1000 is more than four times larger than the GNP per capita in Uganda it represents
less than 20 of the GNP per capita in Mexico The MicroBanking Bulletin (MBB) has
categorized the target market for MFIs by the average outstanding loan amount as a
percentage of the GNP per capita ranging from Low-end (less than 20) to Small
Business (more than 250)14 Especially for the latter category one must to look closely
at the condition of the financial service market where an institution is active Although
MFIs exist in industrialized countries15 one would definitely turn to a traditional
financial institution for a loan bigger than 250 of the GNP per capita and therefore not
to a MFI according to the definition presented above
22 The Origin of Microfinance
Although neither of the terms microcredit or microfinance were used in the academic
literature nor by development aid practitioners before the 1980s or 1990s16
respectively the concept of providing financial services to low income people is much
older
While the emergence of informal financial institutions in Nigeria dates back to the 15th
century17 they were first established in Europe during the 18th century as a response to
the enormous increase in poverty since the end of the extended European wars (1618 ndash
12 See Yunus (2002) p 19 for a more detailed description of the destitute member program of the Grameen Bank which focuses exclusively on persons with no regular income and no assets at all 13 See MicroBanking Bulletin (1997) p 614 See MicroBanking Bulletin (2003) p 5415 See Yunus (1998a) pp 229 et sqq16 See Robinson (2001) p XXX17 See Seibel (2003a) p 12
9
1648)18 In 1720 the first loan fund targeting poor people was founded in Ireland by the
author Jonathan Swift19 After a special law was passed in 1823 which allowed charity
institutions to become formal financial intermediaries a loan fund board was established
in 1836 and a big boom was initiated Their outreach peaked just before the government
introduced a cap on interest rates in 1843 At this time they provided financial services
to almost 20 of Irish households20
The credit cooperatives21 created in Germany in 1847 by Friedrich Wilhelm Raiffeisen
served 14 million people by 191022 He stated that the main objectives of these
cooperatives ldquoshould be to control the use made of money for economic improvements
and to improve the moral and physical values of people and also their will to act by
themselvesrdquo23
In the 1880s the British controlled government of Madras in South India tried to use the
German experience to address poverty which resulted in more than nine million poor
Indians belonging to credit cooperatives by 194624 During this same time the Dutch
colonial administrators constructed a cooperative rural banking system in Indonesia
based on the Raiffeisen model25 which eventually became Bank Rakyat Indonesia
(BRI) now known as the largest MFI in the world26
23 Microfinance after the Second World War
Because of further prudential regulation and effective supervision eg through bank
superintendencies the banking sector in the now developed world experienced
continuous growth Today the vast majority of the citizens of the industrialized
countries have access to financial services with many of them being customers of
former MFIs27
18 See Steinwand (2001) p 5119 See Robinson (2002) p 9620 See Seibel (2003a) p 1021 first known as Darlehnsvereine and now called Raiffeisenbanken22 See Morduch (1999a) p 157323 Raiffeisen (1966) quoted in Richardson (2000) p 324 See Morduch (1999a) p 157425 See Robinson (2002) p 9726 See Roth Steinwand (2004) p 327 See Seibel (2003a) p 11
10
This is not true for most developing countries where market penetration of financial
institutions is far from reaching the majority of the inhabitants (see chapter 4) A variety
of reasons is responsible for this including that the banking sector in the most
developing countries have developed in a very different way to than those in
industrialized countries
One of the most important reasons is that in contrast to the industrialized countries little
attention has been paid to the legal recognition prudential regulation and effective
supervision of informal financial institutions28 This insecure legal environment leads to
several problems Since the regulatory framework for mobilizing savings often does not
fit the needs of institutions targeting low income people many organizations are not
permitted to do so and are therefore missing funds to on-lend as credit29 An additional
problem is the lack of a deposit insurances This not only increases the risk of a bank
run but also keeps people from depositing their savings in a financial institution30 In
addition inappropriate interest rate ceilings prevail in many countries While politics
claim they are lowering the interest rates charged to the poor they de facto only limit
their access to financial services (see chapter 5)31
Another problem that retarded the growth of the financial sector in developing countries
was the supply-leading finance theory which dominated the development strategies of
many countries after the second world war32 This theory ldquo refers to the provision of
loans in advance of the demand for credit for the purpose of inducing economic
growthrdquo33 Since it was believed that poor people were neither able to save (and thus
dependent on outside funding) nor capable of paying commercial rates of interest
massive subsidized credit programs were established34 The results were alarming
Repayment rates often did not exceed 50 percent and some government financed
programs even had default rates of more than 90 percent35 The main reason being that
credit was not provided according to business management principles but instead
28 See Seibel (1998) p 829 See Robinson (2001) p 4930 See Staschen (1999) p 1431 See Gibbons (2000) p 1532 See Morduch (1999a) p 157033 Robinson (2001) p 14034 See Borst (2004) pp 33 et sqq35 See Yunus (1998a) p 154 Robinson (2001) p 145
11
according to political objectives Therefore receiving loans was seen as a reward for the
constituents rather than as a business transaction Most of the funds earmarked for the
poor also never reached them ending up instead in the hands of the local elites
Attracted by the below market interest rates and the possibility not to pay back at all
these groups lobbied to be treated privileged and often used the money received for
consumption or for on-lending at higher rates36 But subsidized credit not only
encouraged corruption it also discouraged sustainable financial institutions since they
could not compete with interest rates that were not aimed to cover all costs and were
sometimes even lower than the interest paid on savings37 The low or negative spread
also worked as a negative incentive to institutionsrsquo effort to mobilize savings which in
turn intensified the problem of credit rationing (see chapter 5)
24 Microfinance Today
In the 1970s a paradigm shift started to take place The failure of subsidized government
or donor driven institutions to meet the demand for financial services in developing
countries let to several new approaches Some of the most prominent ones are presented
below
Bank Dagan Bali (BDB) was established in September 1970 to serve low income people
in Indonesia without any subsidies and is now ldquowell-known as the earliest bank to
institute commercial microfinancerdquo38 While this is not true with regard to the
achievements made in Europe during the 19th century it still can be seen as a turning
point with an ever increasing impact on the view of politicians and development aid
practitioners throughout the world In 1973 ACCION International a United States of
America (USA) based non governmental organization (NGO) disbursed its first loan in
Brazil39 and in 1974 Professor Muhammad Yunus started what later became known as
the Grameen Bank by lending a total of $27 to 42 people in Bangladesh40 One year
later the Self-Employed Womenrsquos Association started to provide loans of about $15 to
36 See Robinson (2001) pp 144 et sqq37 Before BRI underwent a major transformation in 1983 a negative spread between interest rates on loans and savings existed While the bank lent at a 12 annual effective interest rate it paid 15 on savingsSee Robinson (2001) p 10638 Wardhana (2001) p XXVII39 See ACCION (nd)40 See Yunus (1998a) p 16 et sqq
12
poor women in India41 Although the latter examples still were subsidized projects they
used a more business oriented approach and showed the world that poor people can be
good credit risks with repayment rates exceeding 9542 even if the interest rate charged
is higher than that of traditional banks Another milestone was the transformation of
BRI starting in 1984 Once a loss making institution channeling government subsidized
credits to inhabitants of rural Indonesia it is now the largest MFI in the world being
profitable even during the Asian financial crisis of 1997 ndash 199843
In February 1997 more than 2900 policymakers microfinance practitioners and
representatives of various educational institutions and donor agencies from 137
different countries gathered in Washington DC for the first Micro Credit Summit This
was the start of a nine year long campaign to reach 100 million of the world poorest
households with credit for self employment by 200544 According to the Microcredit
Summit Campaign Report 67606080 clients have been reached through 2527 MFIs by
the end of 2002 with 41594778 of them being amongst the poorest before they took
their first loan45 Since the campaign started the average annual growth rate in reaching
clients has been almost 40 percent46 If it has continued at that speed more than 100
million people will have access to microcredit by now and by the end of 2005 the goal
of the microcredit summit campaign would be reached As the president of the World
Bank James Wolfensohn has pointed out providing financial services to 100 million of
the poorest households means helping as many as 500 ndash 600 million poor people47
41 See Bhatt (1997)42 See Yunus (1998a) p 143 et sqq43 See Robinson (2002) p 38044 See Daley-Harris (2003) p 345 ldquoThe Microcredit Summit Campaign defines ldquopoorestrdquo as those who are in the bottom half of those living below their nationrsquos poverty line or are living on less than $1 a day adjusted for purchasing power parity (PPP)rdquo See Daley-Harris (2003) p 3 This definition will also be used throughout this paper46 See Daley-Harris (2003) p 1847 See Morduch (1999a) p 1570
13
3 The Impact of Microcredit
31 Microcredit and the Millennium Development Goals
In 1996 Ismail Serageldin the then chair of the Consultative Group to Assist the Poorest
(CGAP)48 claimed that ldquo[m]icrofinance is a proven instrument to assist the very poorrdquo49
This view is also shared by the World Watch Institute50 and underlines what has been
stated above namely that microfinance can be used as a strong anti-poverty tool But
does microfinance actually meet these expectations and keep this promise51
The impact that microcredit has on the lives of poor people will be demonstrated by
showing how it contributes to each of the eight Millennium Development Goals
(MDGs)52 which are related to the reduction of poverty in all its forms These goals
were resolved in September 2000 by the General Assembly of the UN in their
Millennium Declaration53
32 The Eradication of extreme Poverty and Hunger
The aim of the first MDG is to halve the proportion of people who live on less than $1 a
day between 1990 and 2015 According to current population projections of the World
Bank54 this would equal 849 million people in 201555
48 The Consultative Group to Assist the Poorest is a consortium of 28 public and private development agencies working together to expand access to financial services for the poor in developing countries and was established by the World Bank in 1995 Recently it changed its name to Consultative Group to Assist the Poor49 See Serageldin (1996) p 1150 See Gardner (2002) p 1851 See Morduch (1999a) pp 1569 et sqq52 The Millennium Development Goals are (1) eradicate extreme poverty and hunger (2) achieve universal primary education (3) promote gender equality and empower women (4) reduce child mortality (5) improve maternal health (6) combat HIVAIDS malaria and other diseases (7) ensure environmental sustainability and (8) develop a global partnership for development53 See United Nations (2000)54 See World Bank (2004) p 38 et sqq55 Although it is not explicitly mentioned in the Millennium Declaration it is commonly assumed that the share of people living on less than $1 in low and middle income countries should be halved If the share would be calculated with regard to the worldrsquos total population the goal for 2015 would 818 million people For the worldrsquos total population in 1990 see US Census Bureau (2004)
14
Today almost 11 billion people live on less than $1 and more than 27 Billion live on
less than $2 per day56 The mean income for those living under $1 a day is $077 and it
is $125 for those living under $2 a day57 While the number of people living on less
than $1 per day is slowly decreasing and is expected to be 913 million in 2015 the
number of people living on less than $2 a day is actually increasing58 One of the
outcomes from this degree of poverty is that more than 27000 children die every day
from mostly preventable diseases many of them related to hunger59
Microcredit enables poor people to start new businesses or to diversify existing ones
which helps them to increase their income In addition to large amounts of anecdotal
evidence several studies have documented the positive economic impact microcredit
has on its clients Cloud and Panjaitan-Drioadisuryo have found that the average income
of a sample of BRI borrowers has increased by 112 percent and that 90 percent of their
families have crossed the poverty line60 Only 12 out of the 121 respondents of that
study reported that their income had not increased61 According to the Grameen Bank
website 5109 percent of their clients have crossed the poverty line since they took their
first loan62
A study conducted by Barnes showed that the program of the Zambuko Trust a local
MFI in Zambia had a considerable impact on the poorest clients consumption of meat
fish and chicken63 While 76 percent of the continuing clients of the MFI called Share in
India significantly increased their income and 50 percent have crossed the poverty line 64 Khandker discovered in his well known study ldquoFighting poverty with microcreditrdquo
that there is a connection between the microcredit programs of three Bangladeshi MFIs
and household per capita expenditure For every dollar borrowed by a Grameen Bank
member household consumption increases by $018 In addition he found that 5 percent
56 See Chen and Ravallion (2004) p 2957 In fact those people live on less than $108 and $215 respectively a day in 1993 PPP This means that the nominal dollar value of their income is considerably lower See Chen and Ravallion (2004) p 9 58Both numbers are decreasing in Asia but increasing in the rest of the world See Chen and Ravallion (2004) p 22 et sqq59 See UNICEF (2002) p 660 A consistent definition of the term ldquopoverty linerdquo does not exists among different nations Therefore the term will be used according to the definition of the respective country in this paper61 See Panjaitan-Drioadisuryo and Cloud (1999) p 77562 See Grameen Bank (2004) 63 See Barnes (2001) p 8664 See Simanowitz and Walter (2002) p 16
15
of Grameen Bank borrowers move out of poverty every year65 Supposing Khandkerrsquos
findings were correct for all MFIs worldwide and the Microcredit Summit Campaign
achieved its goal of reaching 100 million of the poorest households with microcredit by
2005 then 25 million people (assuming an average family size of five) would leave
poverty every year66 Although this number would have to be adjusted in order take into
consideration the MFI clients who have crossed the poverty line already and of course
the experiences made in Bangladesh can not be transferred precisely to other countries
it still demonstrates the enormous effect that microcredit can have on assisting the
poorest to move out of poverty
Although a 1996 study of Hulme and Mosley states that providing microcredit can also
have a negative impact on the income of the poorest households67 these findings can
be considered as disproved by the recent bulk of evidence drawing favorable
conclusions68
33 Achievement of universal primary Education
The aim of the second MDG is to ensure that all children will be able to complete
primary school by 2015
Currently more than 100 million children most of them girls are not in school69
Besides school fees poor households often can not afford to send their children to
school because they need them to help in the family business
Microcredit programs mainly contribute to the second MDG by increasing families
income and therefore enabling parents to send their children to school Barnes Gaile
and Kibombo found that clients of an MFI in Uganda spent significantly more on
childrenrsquos education than non-clients70 and in Zambia Barnes showed that ongoing
participation in the Zambuko Trustrsquos program had a positive impact on the members
65 See Khandker (1998) p 5666 See Daley-Harris (2003) p 2467 See Hulme and Mosley (1996) p 180 et sqq 68 See Gibbons and Meehan (1998) p 13669 See UNICEF (2002) p 2270 See Barnes Gaile and Kibombo (2001) p 64
16
children staying in school71 In Bangladesh the probability of girls enrolling in school
increased by 19 percent for every 1 percent increase in Grameen Bank loans to female
clients For boys this number was even higher with the mean being 24 percent72
34 Promote gender Equality and empower Women
The aim of the third MDG is to eliminate the disparity in the ratios of girls to boys in
primary secondary and tertiary education in the ratio of literate females to males and to
increase the share of women in the labor market and in parliament73
At present the literacy rate for women is lower than for man all over the world
According to the Human Development Report 2004 the average female literacy rate as
a percentage of male literacy rate is 759 in developing countries and is as low as 37 in
Niger74 But women are not only discriminated against in education but also in access to
medical services and therefore have a higher mortality rate than man75 The worldwide
tendency for women to be underrepresented in the labor market and in the parliaments is
even more severe in developing countries76 Although several women have become
heads of state in various Asian countries (eg Bangladesh India and Indonesia) this is
probably due to them being wives or daughters of former respected male politicians
Since women have a higher repayment rate than man77 and also tend to invest increases
in income on the household and on their children rather than on themselves78 most
MFIs prefer female clients79 Therefore they empower women in many ways Often
MFIs not only encourage women to become involved in financial transactions for the
first time but also to become independent active members of the economy and to
acquire assets in their own names Cheston and Kuhn found that 68 percent of the
women participating in an MFI program in Nepal ldquohellip experienced an increase their
71 See Barnes (2001) p 8472 See Khandker (1998) p 4973 See World Bank (2001) p 2074 See UNDP (2004) pp 225 et sqq75 See Sen (2000) p 23276 See Sen (2000) pp 242 et sqq77 See Littlefield Morduch and Hashemi (2003) p 778 See Yunus (1998a) pp 116 et sqq79 According to the Microcredit Summit Campaign Report 79 or 37677080 of the poorest clients were women See Daley-Harris (2003) p 3
17
decision-making roles in the areas of family planning childrenrsquos marriage buying and
selling property and sending their daughters to school - all areas of decision making
traditionally dominated by menrdquo80 The program of the Lower Pra Rural Bank in Ghana
had an positive impact on womenrsquos participation in the community81 which is true as
well for the CRECER program in Bolivia82 In Bangladesh the Grameen Bank and the
Bangladesh Rural Advancement Committee (BRAC) the two biggest MFIs of the
country had a significant positive effect on womenrsquos empowerment measured through
eight different indicators83 After joining Grameen Bank only 21 percent of the female
members considered themselves as unemployed while this number was 50 percent
before joining84 According to the Grameen Bank website 93 percent of the Bankrsquos
shares are owned by their borrowers which elect the members of the board every three
years They also get familiar with the election process by more frequently voting for
representatives at the lower level of the organizational structure Partly because of this
experience they are more likely to run for public office In the 2003 local government
elections Grameen Bank members constituted 24 of the seats reserved for women
while they represent less than 10 of Bangladeshi adult female population85 Female
clients of MFIs from countries like the Philippines Bolivia and Nepal have reported
similar occurrences86
35 Reduce Child Mortality and improve Maternal Health
The aim of the fourth MDG is to reduce the under-five mortality rate by two-thirds
between 1990 and 2015 and the fifth MDG strives for a three quarter reduction in the
maternal mortality ratio by the same date
As has been stated above more than 10 million children are dying annually in the
developing world of mostly preventable causes with malnutrition playing a role in over
80 See Cheston and Kuhn (2002) p 1881 See MkNelly and Dunford (1998) p 5482 See MkNelly and Dunford (1999) p 7183 The eight different indicators are ldquofreedom of movement economic security ability to make small and larger independent purchases participation in important family decisions relative freedom from domination by the family political and legal awareness and participation in political campaigning and public protestsrdquo Hashemi and Schuler (1998) p 3684 See Holcombe (1995) p 5185 See Grameen Bank (2004)and CIA (2004)86 See Littlefield Morduch and Hashemi (2003) p 8
18
half of the childrsquos deaths and in over 50 countries child mortality rates are greater than
100 deaths per 1000 live births87 Maternal mortality is also a significant problem in the
developing world with more than 500000 women dying every year from pregnancy
related causes88
MFIs are mainly contributing to the these MDGs by increasing families income and
therefore enabling the households to afford better nutrition and medical services
Furthermore they are often linked with microinsurance or health education programs
In addition to what has been showed in chapter 31 Pitt Khandker and Millimet
estimate that a 10 percent increase in the loan size of a female borrower in Bangladesh
increases the arm circumference of their daughters by 6389 Smith and Jain found that
village banking in Ecuador had a positive effect on child diarrhea90 which is responsible
for 15 of child deaths91 Since Sen argues that an improved status of women within
the family reduces child mortality92 the empowerment of women through MFIs is also
contributing to this cause
Although no study has been conducted so far on the direct impact of microcredit on
maternal health it can be assumed that an overall improvement of access to medical
services reduces maternal mortality as well A study of the Morgan State University for
example suggests that microcredit has a positive effect on the prevalence of
contraceptives93 which leads to a decrease of unwanted pregnancies and therefore
reduces maternal death
36 Combat HIVAIDS Malaria and other diseases
The aim of the sixth MDG is to halt and begin to reverse by 2015 the spread of
HIVAIDS malaria and other major diseases and to assist children orphaned by HIV
87 See World Bank (2001) p 888 See WHO (2004) 89 See Pitt Khandker and Millimet (2003) p 11390 See Smith and Jain (1999) p 3791 See WHO (2001) 92 See Sen (2000) p 23593 See Amin et al (2001) p 1614
19
In 2003 29 million people died because of HIV and about 48 million became infected
the greatest number since AIDS was discovered 23 years ago94 This pandemic has lead
to a tremendous decrease in the life expectancy in the hardest hit countries Botswana
for example one of the richest and most democratic countries in Africa has a
HIVAIDS adult prevalence rate of 388 and a life expectancy at birth of less than 31
years95
Malaria not only causes more than one million deaths annually it leads also to 300 ndash
500 million clinical cases a year Both numbers have been steadily increasing over the
past two decades96 More than two million people a year are killed by tuberculosis
another global health problem This curable disease is estimated to cost poor
communities about $12 billion every year since even those who survive normally lose
more than 3 month of work time while recovering97
MFIs contribute to the sixth MDG in several ways By increasing clientrsquos income they
help households affected by HIV or other diseases to better cope with the situation
Besides spending more money on health services and nutrition MFI clients also tend to
be more able and willing to support AIDS orphans than non clients98 In addition to the
already stated increase in the use of contraceptives99 several innovative approaches to
deal with disease related crisis have also arisen This is of course necessary not only to
counteract the devastating effect the above discussed epidemics can have on MFI
clients but also to not put the viability of the respective institution at risk One option is
to integrate education services in the MFI programs and encourage clients to form
solidarity groups100 It has been shown that these services do not necessarily decrease
the effectiveness of the institutionsrsquo employees101 Another way is to strengthen the ties
to NGOs specialize in dealing with the respective disease Synergies gained through this
cooperation can help clients to better deal with the situation and in the end increase their
94 See UNAIDS (2004) p 2395 See CIA (2004)96 See World Bank (2001) p 1697 See World Bank (2001) p 1298 See Barnes (2001) p 6499 See also Kim et al (2002) p 18100 See Donahue and Sussman (1999) p A 14101 See Donahue Kabbucho and Osinde (2001) p 25
20
repayment rates Various MFIs also have introduced loan and health insurance products
or cultivated linkages with organizations doing so102
It has to be stated that despite the benefits MFIs can provide to people effected by
HIVAIDS or other diseases microcredit can also be a burden for those who are already
chronically ill These people can still benefit through loans provided to members of the
family or the community or through one of the other services mentioned above
37 Ensure environmental Sustainability
The aims of the seventh MDG are to support and promote the principles of sustainable
development and put them into action and to improve the lives of slum dwellers and
people without sustainable access to safe drinking water and sanitation
Today climate change is considered as the major environmental problem103 The
Intergovernmental Panel on Climate Change (IPCC) states that human activities
contribute to most of the 06 degC increase in global average temperature over the 20th
century and the predicted increase of another 14 to 58 degC between 1990 and 2100104
Emission of carbon from fossil fuel is reported to have the dominant influence on this
development While the total emission was 16 billion tons in 1950 it was already 65
billion tons in 2000 and is expected to continue to grow105 This development would
lead to a rise in the average sea level of between 9 and 88 centimeters during the next
century106 Furthermore it is predicted that global warming increases the risk of extreme
events like cyclones or floods leads to an increase in the number of people infected by
diseases like malaria and decreases the potential crop harvest and water availability
especially in developing countries107 In 2000 already 11 billion people lacked access to
clean drinking water and 24 billion to basic sanitation108
102 See Barnes (2001) p 40 Barnes Gaile and Kibombo (2001) p 13 and Grameen Bank (2004)103 See Gardner (2002) p 5104 See IPCC (2001) pp 2 et sqq105 Worldwatch Institute (2002) p 52 et sqq106 See IPCC (2001) p 16107 See Dunn and Flavin p 29108 See UNFPA (2004) p 18
21
MFIs contribute to achieving the seventh MDG in several ways By providing loans for
the purchase of renewable energy technologies they help people in developing
countries to increase their per capita energy consumption without increasing the carbon
dioxide emission In a 2003 survey of 140 MFIs from 80 different countries 21 said
they provide credits for solar home systems and another 19 stated they are interested in
becoming engaged in this business109 While Grameen Shakti a rural energy service
company cooperating with the Grameen Bank in Bangladesh has already installed more
than 23000 solar home systems110 a 2000 World Bank study reports twelve projects
providing solar home systems to rural households with a target of 500000
installations111 It has also been suggested that MFIs should raise environmental
awareness among their clients112 but so far no data is available on how staff can cope
with this additional task Many MFIs also provide loans for improvements in sanitation
and the water supply of their clients Varley gives several examples from Africa Asia
and Latin America on how microcredit not only has helped to invest in rainwater
collection systems but also how it has enabled households to increase their water
supply through community water associations113 In addition many MFIs provide credit
for the construction of sanitary latrines114 The situation of slum dwellers is also
positively effected by MFIs Directly through their services in poor urban communities
and indirectly by creating jobs in rural areas and therefore easing the pressure on urban
labor markets
38 Develop a global Partnership for Development
The eight MDG is about the means to achieve the other seven MDGs It calls for all
players involved in the endeavor of development and poverty eradication to work as
partners in a global context
Again MFIs are contributing to the eight MDG in many ways This is occurring through
international networks that provide funding and technical assistance through internet
information portals and specialized journals through social and for profit investors and
109 See Wimmer and Barua (2004) p 174110 Barua (2004) 111 See Martinot and Cabraal (2000) p 6112 See Pallen (1997) p 11 Lal (nd)113 See Varley (1995) pp 39 et sqq114 See Jalvaani (1999) pp 1 et sqq Varley (1995) pp 39 et sqq
22
specialized rating agencies The Bangladesh-based Grameen Trust is one of around 30
networks in operation Besides collaborating with over 200 MFIs around the world it
has directly operated three projects in Afghanistan Kosovo and Myanmar115 While the
ACCION network serves almost 12 million active clients in 19 countries throughout
America and sub-Saharan Africa116 FINCArsquos network operates in three different
continents where it serves more than 200000 customers117 In November 1997 the
MicroBanking Bulletin (MBB) was first published by the microfinance program at the
Economic Institute at the University of Colorado118 Its aim is to develop a database on
the financial performance of MFIs from all over the world which is now available
through the Mix Market an internet portal that also provides information about more
than 300 MFIs investors donor institutions and other related development
organizations119 Two years later the Marriott School at Brigham Young University
started to publish the Journal of Microfinance which has an editorial board of
microfinance experts from all over the world and offers the latest research on this
topic120 In the late 1990s a number of companies became attracted by the microfinance
market and started to invest in MFIs The German based Internationale Mikro
Investitionen Aktiengesellschaft (IMI) for example has already invested more than euro46
million in 19 MFIs in four different continents and plans to invest another euro27 million
before October 2004121 BlueOrchard Finance a microfinance investment consultancy
has channeled more than $60 million worth of private capital to some 40 MFIs
worldwide through investment funds and bond issues122 Big commercial banks like
Citigroup Deutsche Bank and ABN Amro also started to get involved in the
microfinance sector although this is mainly still perceived as a public relation activity
and not as a for-profit investment123 There are also several rating agencies specializing
in MFIs Dependent on their rating these institutions can help MFIs to receive money
from donors or investors Four of the most prominent rating agencies are PlanetFinance
115 See Grameen Trust (nd)116 See ACCION (nd)117 See FINCA (nd)118 See MicroBanking Bulletin (1997) p 5119 See The Mix (2004)120 See Woodworth and Woller (1999) p 6121 See IMI (2004)122 See BlueOrchard (2004b) p 3123 See Busch and Kort (2004) p 8 Fischer (2003) p 6
23
with headquarters in France M-Cril based in India Microfinanza in Italy and
MicroRate with offices in the USA and South Africa124
124 See Microfinance Rating and Assessment Fund (2004)
24
4 Microcredit Outreach
41 The Demand for Microcredit
Although it has been shown that microcredit is one of the most effective poverty
eradication tools that it is considered a human right by some of its advocates125 and it
can contribute considerably to the development of the financial sector in developing
countries an enormous gap still exists between supply and demand for microcredit
Estimates on the demand for microcredit vary greatly While USAID estimates the
number of potential microfinance clients is between 100 and 200 million126 the
Microcredit Summit Campaign states the total demand is more than 234 million
people127 CGAP recognizes some 500 million micro-entrepreneurs who have the
potential to become customers of MFIs128
Marguerite Robinson calculates the demand as follows ldquoAssuming five people to a
household among the 45 billion people living in low- and lower-middle-income
economies in 1999 (World Bank World Development Report 20002001) there are 900
million households in those economies If estimating conservatively we assume that
informal commercial moneylenders supply credit to 30 percent of these households at
least once a year this would mean that there are 270 million households borrowing
from informal moneylenders in a year Undoubtedly however many of these
households borrow multiple times within a yearrdquo129 Although this is a very rough
estimate assuming big differences in demand for microcredit in different countries the
number seems to be the most meaningful In contrast to the estimate of the Microcredit
Summit Campaign it does not include every single household living on less than $1 a
day but according to the definition presented in chapter 1 it counts everyone who has
no regular access to traditional financial institutions but demands such services
Obviously not all people who draw on moneylenders have financial needs that could be
matched through MFIs On the other hand interest rates charged by moneylenders tend
125 See Yunus (1998b) 126 See Christen et al (1995) p 15127 See Daley Harris (2003) p 22 128 See Robinson (2001) p 26129 See Robinson (2001) p 215
25
to be considerably higher than those of MFIs The former normally charge effective
monthly rates between ten and several hundred percent per month the latter generally
charge between 15 and five percent which enables them to attract additional clients130
42 The Supply of Microcredit
In spite of the impressive growth of MFIs around the world the demand for microcredit
is far from being met and this it is not likely to change in the near future The
Microcredit Summit Campaign reported that by the end of 2002 67606080 clients131
were reached through MFIs and that this number has increased by almost 40 percent
annually for the last five years132 It is likely that this tremendous speed of growth is at
least partly due to including MFIs which have not been reporting to the Campaign from
its start in 1997 although they have already existed at that time These institutions
contributed 22 percent to the growth in poorest clients in 2000 578 percent in 2001 and
338 percent in 2002 The growth of the poorest clients increased at least party because
of an expanded definition of the term ldquopoorestrdquo133 Since the contribution of MFIs
which previously have not been considered can be expected to decrease dramatically
the growth rate as stated by the Microcredit Summit Campaign can not be used to
predict the future development of the microfinance sector Another factor likely to slow
down the growth is the concentration of microfinance activities in some Asian countries
where almost 90 percent of the poorest microfinance clients live today134 Even if one
takes into consideration the relative size of Asiarsquos population and the fact that many
MFI customers in Latin America are relatively better off and therefore are not included
in this numbers the coverage of this part of the world far exceeds the others In
Bangladesh for example the microfinance market is close to saturation More than
eleven million households were served by several hundred MFIs in 2001135 Among
them are Grameen Bank and BRAC two of the best known MFIs in the world both
providing their services to more than three million customers With an average
household size of five it can be assumed that in Bangladesh the number of people
130 See Gibbons and Meehan (1999) pp 144 et sqq131 41594778 of them belonged to the poorest before they took their first loan The relative numbers in the following are for these poorest clients only since no other current data was available It can be assumed though that this works as a good proxy for the total number of clients 132 See Daley Harris (2003) p 3133 See Daley Harris (2003) p 17134 See Daley Harris (2003) p 21135 See Ahmed (2003)
26
benefiting from microcredit already surpasses the number of people living below the
poverty line which is estimated to be slightly higher than 50 million136 Therefore
Bangladesh will not contribute to the growth of the microfinance sector as much as it
has done in previous years This is also true for Vietnam Thailand and to a lesser
extent Indonesia Eight of the nine MFIs serving more than one million clients are based
in these countries while the ninth is based in India where due to its one billion
inhabitants the microfinance market is still far from saturation137 In contrast the
supply in Brazil meets less than two percent of the demand which is estimated to be
about 58 million potential clients138 For these reasons greater amount of future growth
must come from smaller or new MFIs in Latin America India China and especially
Africa where almost 30 percent of the worldrsquos poorest live139
43 Meeting the Demand
To fill the gap between the demand and supply for microcredit tremendous investments
are necessary to increase the loan funds of MFIs and build up their capacity through
upgrading existing institutions or building new ones Again estimates on how much
capital is needed vary greatly with the highest being at more than $300 billion140
In 1997 the Microcredit Summit Campaign estimated that $216 billion would be
needed to achieve their goal of providing microcredit to 100 million of the poorest
households This was calculated in the following way Since some 8 million people
already received microcredit in 1997 another 92 million needed to be reached
Assuming $200 ($150 for loan fund and $50 for capacity building) would be needed per
person for 88 million people in developing countries and $1000 ($500 for loan fund and
$500 for capacity building) would be needed for 4 million people in industrialized
countries the capital required ends up to be $216 billion141 For several reasons this
136 See CIA (2004)137 These institutions are The Grameen Bank BRAC Proshika and the Association for Social Advancement (ASA) in Bangladesh the Vietnam Bank for Agriculture and Rural Development (VBARD) and the Vietnam Bank for the Poor (VBA) in Vietnam BRI in Indonesia Bank for Agriculture and Agricultural Co-operatives (BAAC) in Thailand the National Bank for Agriculture and Rural Development (NABARD) in India See Ahmed (nd) p 1 Llanto (nd) p 337138 See Mezzera (2002) p 23139 See See Chen and Ravallion (2004) p 29140 See Clear Profit (2004) Prisma (2002)141 See The Microcredit Summit (1997)
27
number is not qualified to predict the total amount of capital needed to meet the demand
for microcredit On the one hand it focuses mainly on the low end of the market and
therefore underestimates the average loan fund needed On the other hand it does not
take the increasing capital demand from established MFIs into account A survey of 119
MFIs found that the average loan size to increased from $406 in 2002 to $498 in
2003142 This is mainly due to the fact that MFI clients once they have paid back their
loans usually demand larger ones for the continual development of their businesses
and therefore further increase the demand for capital of established MFIs The Grameen
Bank for example has a ceiling on its loans which increases or decreases depending on
the borrowers performance regarding repayments and savings143 While the maximum
amount for the first loan is fixed at approximately $75144 the largest loan disbursed so
far was $17195145 Thus if one estimates that by now 100 million people are borrowing
from MFIs146 another 170 million need to be reached to meet the estimated demand
Assuming an average of $600 ($400 for loan fund and $200 for capacity building) is
needed for every new client and another $200 is needed for every existing client to meet
the demand for larger loans a total of $122 billion is required This rough estimate
helps to convey the approximate amount of capital needed to meet the demand for
microcredit
So far the demand for funds is being partly met by donors which annually provide
between $500 million and $1 billion147 and through the mobilization of local savings
Obviously the amount of money provided by donors will not be able to meet the capital
demand for microcredit in the short term The mobilization of savings on the other hand
has been extremely successful in some cases with BRI probably being the most
prominent example After adapting commercial principals in October 1984 BRI was
able to raise its deposits from $161060 to more than $32 billion in 2003 which equals
almost two times its current loan portfolio148 Many other MFIs like BDB in Indonesia
142 Own calculations Without BRI the numbers would be $343 and $409 See Appendix 1143 See Grameen Bank (2003) p 13144 The accurate amount is 5000 Taka See Interview with Shaw Newaz145 Grameen Bank (2004)146 According to the data provided by the Daley Harris (2003) an annual increase in MFI clients ofapproximately 25 percent from 31122002 till the 3092004 would be needed to reach 100 million clients by now This rated is considerably below the average of the previous five years (38 percent) Therefore it can be assumed as realistic despite the growth hindering factors presented above147 See CGAP (2003) p 8148 See Robinson (2002) p 273 Mix Market (2004)
28
XacBank in Mongolia the Equity Building Society in Kenya or the Centenary Rural
Development Bank in Uganda also have managed to cover their loan portfolio fully
through internally mobilized resources149 The Grameen Bank is also expected to do so
in the first half of 2005150 In addition to raising much needed capital for on-lending the
provision of saving services can deliver notable social benefits itself151
Despite these impressive achievements even the combination of donor money and local
savings at their current levels will not be able to provide the capital needed to continue
the rapid growth of the microfinance sector Especially in their early years MFIs rely on
outside funding BRI for example needed six years before the amount of locally
mobilized savings surpassed the total amount of outstanding loans During this time
expenses and the loan portfolio were covered through a government grant worth $20
million and two World Bank loans of $5 and $97 million respectively152 It also
benefited from a network of more than 3600 branches which were established
throughout the country during the 1970s and early 80s in order to provide government
subsidized credit in rural areas153
The Grameen Bank also widely known as a best practice MFI has received about $175
million in direct and indirect subsidies between 1985 and 1996154 and continues to rely
on outside funding at below market interest rates This is made possible either through
special loans from the Bangladesh Bank or through offering bonds guaranteed by the
Bangladesh government155 - an option most MFIs do not have BDB might be one of the
very few examples which were able to finance their activities through savings and
commercial loans from the start but its outreach did not reach a large scale nor did it
serve the low end of the market In 2000 after 30 years of operation BDB provides
credit to only 10417 clients with an average loan balance of more than $5000156
approximately eight times the countries GDP per capita157
149 See Mix Market (2004)150 See Grameen Bank (2004)151 See Robinson (2001) pp 263 et sqq152 See Seibel and Schmidt (2000) p 4153 See Robinson (2002) p 180154 See Morduch (1999b) p 8155 See Morduch (1999ba) p 25 et sqq156 See Robinson (2002) p 387157 See CIA (2004)
29
Another problem keeping many MFIs from collecting savings is that they do not want
to become a regulated financial institution or do not meet the criteria in their respective
country and therefore they are simply not allowed to mobilize savings from the public
In summary the examples and numbers presented in this chapter support the argument
that the amount of capital that can be raised through donors and locally mobilized
savings is not enough for continuous rapid growth of the microfinance sector If this
lack of capital is not met through other sources the microfinance sector will fail to
contribute its full potential to the achievement of the MDGs
44 Microfinance and the Capital Markets
Regardless of whether the amount of capital needed for the development of the
microfinance sector is $20 or $300 billion it represents only a tiny fraction of the
worldwide capital markets which are estimated at $30 trillion158 Therefore if the
microfinance industry were able to tap the financial markets it would be able to grow
much faster and soon serve the millions of micro-entrepreneurs which currently can not
develop theirs businesses because of capital constrains Another advantage would be
that scarce donor money currently used for the development of the microfinance sector
could be used for other projects that do not have the potential to draw money from
commercial sources This view is shared by Michael Chu the former CEO of ACCION
who made the following statement in 1998 ldquoMicrofinance today stands at the threshold
of its next major stage the connection with the capital marketsrdquo159 Many attempts have
been made since that time Successful MFIs like BancoSol in Bolivia further
strengthened their ties to the capital markets which in some cases already provide the
majority of their funding160 Microfinance investment advisors like BlueOrchard
Finance have become middlemen for MFIs and the financial markets Nevertheless
these links are still far from reaching major scale Currently only approximately 20
percent of MFIs funding comes from commercial sources161 and the biggest bond issue
dedicated to fund MFIs totals only $40 million In addition these funds mainly end up
158 See Brynjolfsson (2004) 159 Chu (1998) quoted in Robinson (2001) p 23160 See Robinson (2001) p 69161 See Dominiceacute (2004)
30
in established institutions in Latin America or Eastern Europe162 while smaller
organizations only benefit indirectly if at all
162 See Clear Profit (2004) IMI (2004)
31
5 Credit Rationing
Until recently the predominant answer to why commercial banks or venture capital
companies did not invest in the microfinance sector was that the poor are not bankable
Besides lacking education and therefore not being able to deal with formal financial
institutions they were viewed as bad credit risk who were unable to invest the borrowed
money in a way that would allow them to repay the loan and interest at a commercial
rate163 Another reason that kept attention away from the idea of providing financial
services to low income people was the belief that informal moneylenders already met
this demand These skeptics felt affirmed through the poor performance of subsidized
credit programs as described in chapter 22 Although it is true that moneylenders
serve a huge number of people in the developing world they more often than not charge
usury interest rates of up to 20000 percent per month164 While the argument that poor
people are not able to participate in the formal financial market can be overcome by
adapting the services accordingly165 the claim of low returns on their investments is not
only proved wrong by empirical evidence but also contradicts economic theory as will
be shown in chapter 53
51 The imperfect Information Paradigm
A more elaborate explanation for the short supply of financial services to low income
people that can be derived from the imperfect information paradigm based
predominantly on the works of Akerlof166 and Stiglitz and Weiss167 After giving a brief
summary of their argument an adaptation of their findings to the microfinance market
will be presented and subsequently it will be shown how their conclusions can be
overcome
Behind the imperfect information paradigm lies the theory of asymmetric information
which simply states that if two parties conduct a transaction one is likely to have more
163 See Ghatak (1983) p 21 et sqq Yunus (1998) p 102 et sqq Robinson (2001) p 35 et sqq164 See Robinson (2001) p 17165 See Seibel (2003b) p 2 BRAC (2003) pp 15et sqq Yunus (1998) pp 151 et sqq 166 See Akerlof (1970) pp 488 et sqq167 See Stiglitz and Weiss (1981) pp 393 et sqq
32
information than the other and is trying to use that for its own advantage168 Applied to
the banking sector this means that a person applying for credit can better judge the
likelihood of repaying the loan than the bank This is because the borrower has better
knowledge of the market she wants to invest in her skills and her willingness to repay
Moreover the bank might not be able to observe if the borrower uses the loan for the
agreed purpose These occurrences can lead to what is known as adverse selection and
moral hazard In this case adverse selection refers to the problem that banks might
attract borrowers with a low probability of repayment if they can not distinguish
between high and low risk loan applicants Moral hazard occurs after the provision of
the loan when the borrower spends the money on a purpose different to the prescribed
purpose and therefore lowers the probability of repayment This can happen eg by
investing in a more risky project or through spending the money on consumption If the
bank is not able to find a cost effective way to avoid these problems it might raise its
interest rate in order to compensate for the increased risk
Figure 1 Expected Bank Return and the Interest Rate
Source Stiglitz and Weiss (1981) p 394
Since this might discourage low risk borrowers from applying for credit and encourage
borrowers who continue to take loans to invest in riskier projects the share of high risk
168 See Neus (1998) p 85 et sqq
INTEREST RATEI
EX
PE
CT
ED
RE
TU
RN
TO
TH
E B
AN
K
33
borrowers could increase and therefore reinforce the problems stated above Thus
increasing the interest rate beyond a certain point actually leads to a decrease in the
expected return to the lender This context is illustrated in figure 1 with I being the
interest rate which maximizes the expected returns to the bank Obviously the bank
would charge the interest rate I in order to maximize its expected return However this
price for capital was not determined through supply and demand as economic theory
would predict It is conceivable that at the interest rate I the demand for credit exceeds
the supply but even if loan applicants would offer to pay a higher interest rate the bank
would refuse because it associates such a loan with high risk As a result credit might
be rationed169
52 Adaptation to the Microfinance Sector
Through some adaptations this model can also help to explain the lack of funds
provided to low income people In the original model of Stiglitz and Weiss several
assumptions have been made that need to be suspended in order to compare the credit
markets for low and high income people and give an explanation why the latter is
widely neglected by institutional investors
Evidently the assumptions that the amount borrowed is equal for each loan applicant
and that transaction costs170 need not to be taken into account171 are not suitable for this
context While the average loan size of MFI customers is much smaller than that of
clients from traditional banks the transaction costs as a share of the loan are
considerably higher because the lenderrsquos costs for conscientious processing a credit
applications are only slightly smaller for a $50 loan than for a $100000 or a
$10000000 loan
In figure 2 the R(I)large curve represents the return to the bank for large loans with
regard to the interest rate I and the R(I)small curve describes the same correlation for
small loans It is shifts downwards to reflect the assertion that the imperfect information
169 See Stiglitz and Weiss (1981) p 394170 In this paper the term bdquotransaction costsldquo refers to the operating expense ratio as defined by MicroRate It ldquois calculated by dividing all expenses related to the operation of the institution (including all the administrative and salary expenses depreciation and board fees) by the period average gross portfoliordquo See MicroRate and Inter-American Development Bank (IADB) (2003) p 16 171 See Stiglitz and Weiss (1981) p 396
34
paradigm has a more severe effect on poor people than on the better off They are
expected to have less profitable investment opportunities at their disposal172 and
therefore are more likely to invest in riskier projects which increase the probability of
default and hence decrease the expected return to the bank Additionally one might
expect poor people to be more likely than others to spend borrowed money on
consumption instead of an income generating activity particularly if a crisis arises It
seems understandable that food or urgently needed medicine are given priority over
repaying a loan
The second shift downwards is due to transaction costs As stated above they are
relatively higher for smaller loans Obviously transaction costs are incurred in the
provision of a large loan as well but since they are much smaller with regard to the loan
amount they are not included in the diagram for reasons of clarity
Figure 2 The extended Model
Source Own diagram adapted from Stiglitz and Weiss (1981) p 394
172 See Khandker (1998) p 8
INTEREST RATE I
SmallLoans
LargeLoans
Transaction costs
Lack of investment opportunities
R(I)large
R(I)small
EX
PE
CT
ED
RE
TU
RN
TO
TH
E B
AN
K
35
53 Overcoming Credit Rationing for the Microfinance Sector
If the conclusions in chapter 51 hold it is rational for a profit maximizing investor to
neglect the microfinance sector as long as no surplus funds in the market for large loans
exist This finding can help to explain the small amount of money provided to the
microfinance sector from commercial investors On the other hand it has to be stated
that this theory is reflexive as defined by Soros173 It not only explains but also forms
reality since it has the potential to reinforce the view of potential investors that
microfinance is a less profitable business174 Therefore demonstrating under which
conditions microfinance can be profitable and in some cases be more profitable than
traditional businesses is of crucial importance
To provide a fairer view of the microfinance sector a further assumption of the Stiglitz
and Weiss model that needs to be suspended is that all investments made by the
borrowers have the same expected return175 As stated above this contradicts economic
theory which claims ceteris paribus capital productivity decreases while the amount of
fixed capital increases In combination with a low capital endowment micro-enterprises
are usually faced with an excess supply of unskilled labor especially in developing
countries176 Hence small enterprises use far less capital per employee than big business
and therefore their marginal productivity of capital is much higher177 This is intuitive if
one imagines an economic actor who wants to invest several packages of capital
Obviously she would invest the first package where she expects the highest return the
second package where she expects the second highest return and so on Each additional
investment opportunity would lead to lower or at best equal returns178 While this
simplified example has limitations it demonstrates how the marginal productivity of
capital can diminish Although it might actually increase until a certain point179 this can
be expected to be so low in this context that it has no influence on the correlation as
shown in figure 2
173 See Soros (1998) pp 14 et sqq174 See Goodwin-Groen (1999) p 8175 See Stiglitz and Weiss (1981) p 395176 See Perkins et al (2001) pp 95 et sqq177 See Tschach (2000) p 8178 See Rosenberg (2002) p 11179 See Rechard G Lipsey (1979) pp 211 et sqq
36
Figure 3 Marginal Productivity of Capital
Source Dornbusch and Fischer (1995) p 406
Even if good investment opportunities for poor people exist the question remains if it is
possible to distinguish between high and low risk borrowers The problem of adverse
selection is overcome in a cost effective way in many MFIs180 For the better off poor
for example institutions like BRI base their decision on whether or not to approve a
loan by assessing the repayment ability of potential borrowers from their current income
flows and not from the uncertain returns generated by the loan181 Additionally
collateral is used in some cases to attract low risk borrowers182 In contrast to
industrialized countries this is usually not done to cover the potential losses of the
lender but to punish the defaulter and therefore increase her willingness to repay183
Obviously this does not always work for the poorest since they often neither posses any
goods that could work as collateral nor do they have sufficient earnings prior to
obtaining a loan for starting an income generating activity Here the so called group-
lending model can help to identify creditworthy borrowers The most prominent
institution using this approach is the Grameen Bank which only provides credit to
180 See Farrington (2000) p 20181 See Robinson (2001) p 80 Robinson (2002) p 238182 See Bester (1985) p 850 et sqq183 See Schmidt and Tschach (2001) p 15 Robinson (2002) p 244
FIXED CAPITAL 0
MA
RG
INA
L P
RO
DU
CT
IVIT
Y
37
members of a group of five These groups are formed by their members without
interference of the Grameen Bank Although in this particular case no joint liability
exists for the members of the group nobody can receive a new loan if another member
of the group fails to repay on time184 Therefore the group formation work as a
screening process Since the borrowers do not want to risk their ability to obtain further
loans they carefully select with whom to form a group Usually the members know
each other for a long period of time and therefore they can make a meaningful judgment
of each othersrsquo ability to repay the loan Other MFIs even require the members of a
group to mutually guarantee each othersrsquo loans185 While this might further increase
borrowersrsquo efforts to search for trustworthy group members it might also keep potential
borrowers from applying for a loan since she does not want be held responsible for
defaulting members This mechanism enables MFIs to partly pass on the transaction
costs related to the selection of low risk borrowers to the borrowers themselves186
Many MFIs have also largely overcome the problem of moral hazard by creating
incentives to ensure a high repayment rate even among the poorest In some cases their
customers go hungry in order to pay back their loan even though no legal action would
be taken against them if they would refuse to do so187 One way to achieve this is to
build up peer pressure through the formation of groups as described above188 Another
and probably the most important is to limit access to future loans to those borrowers
who repay on time The demand for successive loans is extremely high In a 1996
survey 98 percent of BRI borrowers planed to apply for another loan189 and in 1993
less than 30 percent of Grameen Bank loans went to first time borrowers190 Especially
the poorest highly value the option to reborrow191 and many MFIs see this as their
primary incentive to ensure repayment192 According to Schmidt and Tschach ldquothe net
present value of future access to credit works out to be roughly half the value of the
economic advantage to be gained from the intended non-repaymentrdquo193 This can also
184 See Yunus (1998) p 135185 See Schmidt and Zeitinger (1997) p 6186 See Stiglitz (1990) p353187 Own observation at the Grameen Bank in Bangladesh (2003)188 See Hoff and Stiglitz (1990) p 249189 See Robinson (2002) p 251190 See Khandker Khalily and Khan (1995) p 93191 See Gibbons (2000) p 15 Hashemi and Schuler (1997) p 43192 See Gibbons and Meehan (1999) p 160193 See Schmidt and Tschach (2001) p 16
38
explain the occurrence of a drop in the repayment rate once a MFI is no longer seen as
viable and therefore is not expected to provide loans in the future194
With the help of the described mechanisms MFIs around the world are able to keep
repayment rates high A survey of 69 MFIs from 36 different countries each serving
more than 10000 clients in 2002 found the portfolio at risk (PAR)195 varied between
zero and 231 percent While the average was 36 percent the median was found to be
229 percent196 One of the MFIs included in this sample is BRIs whorsquos 12-month loss
ratio has never exceeded five percent since the start of its transformation in 1984 and
from 1997 to 1998 the ratio actually fell from 22 to 194 percent197 The latter deserves
special attention because the Asian financial crisis reached its peak at that time with
Indonesia being hardest hit as illustrated by a statement from The Economist in July
1998 Even with the fierce competition from its neighbors Indonesia would probably
walk away with the prize for Asias most desperate banking systemrdquo198
The findings that MFIs can adapt their services to low income people in order to ensure
a high repayment rate and that poor people do not lack profitable investment
opportunities are illustrated in figure 4 From this diagram it can be seen that under the
new assumptions the interest rate at which the bank maximizes its return differs for
large (I(l)) and small loans (I(s)) According to the assumption that micro-
entrepreneurs can realize a higher return on their investments the bank can charge them
a higher rate of interest without bearing an increased risk Nevertheless in this example
the bank would still serve the market for large loans first because of the higher
transaction costs for smaller loans
The view as described in figure 4 is shared among most traditional banks and investors
in industrialized as well as in developing countries In addition to neglecting the
possibility of generating profits by offering microcredit themselves199 they also hesitate
to lend to MFIs because they consider their business too risky
194 See Schreiner (1997) p 64195 ldquoPAR shows the real risk of the portfolio by comparing outstanding loan balances for loans with atleast one late payment to the outstanding loan portfoliordquo Gross and de Silva (2002) p 22196 Own calculations See Appendix 2197 See Seibel (2000) p 11198 The Economist (1998) pp 92 et sqq199 Busch and Kort (2004) p 8
39
Figure 4 The extended Model
Source Own diagram adapted from Stiglitz and Weiss (1981) p 394 Tschach (2000)
p 17
This attitude can be observed by comparing the ratio of equity to liabilities which is
considerably higher for MFIs than for conventional banks200 When it comes to MFI
start-ups and those MFIs serving the low end market in remote areas even experienced
microfinance practitioners are skeptical if interest rates that fully recover all costs can
be charged201
Theoretically there are two ways to adjust this model to arrive at a conclusion which is
more favorable with regard to the profitability of microcredit One is to cut the
transaction costs and therefore reduce the downward shift of the R(I)small curve the
other is to allow the bank to further raise the interest rate without experiencing a
decrease in its return This means to increase I(s) and the respective rate of return
While in 2000 Tschach stated that transaction costs vary between 10 and 20 percent for
loans provided through the group lending model and between 15 and 30 percent for
200 See MicroRate and IADB (2003) p 30201 See Volkery (2004) p 33 Gibbons (2000) p 15 Gibbons and Meehan (2002) p 29 Goodwin-Groen (1999) p 8
INTEREST RATE I(l)
SmallLoans
LargeLoans
Transaction costs
I(s)
R(i)large
R(i)small
EX
PE
CT
ED
RE
TU
RN
TO
TH
E B
AN
K
40
individual loans202 it was recommended in 1999 that MFIs should target a range
between 15 and 25 percent203 Some best practices on the other hand have already
achieved single digit numbers Currently BDB might be the most efficient MFI in the
world with transaction costs at just 47 percent in 2001204 Even though the low costs of
BDB have to be acknowledged its achievement has to be put in perspective As stated
above with an average loan balance of more than $5000 it does not serve the low end
market In addition it works in an environment with a high population density which
means that it can reach a relatively large group of borrowers per branch This is a
comparative advantage many Asian MFIs enjoy as can be illustrated by comparing
Bangladesh and Bolivia Both countries are at the forefront of the development of
microfinance in their respective continent but while in Bangladesh more than 1000
people are living per square kilometer the average for Bolivia is only eight205
Therefore it is consistent that the most efficient MFI in Latin America Fondo
Financiero Privado para el Fomento a Iniciativas Economicas has transaction costs of
114 percent206 With an average loan size greater than the annual GDP per Capita this
institution also does not serve the low end market207
Despite the impressive efficiency gains in the described examples most MFIs are far
from achieving these numbers and many are unlikely to reach them due to the
environment within which they work A survey of 67 MFIs from 31 countries found the
average transactions costs in 2002 to be 279 percent with a median of 206 percent208
However even if these institutions were to increase their efficiency to best practice
standards their transaction costs would still be significantly higher than those of
traditional banks providing much larger loans For these banks the respective costs vary
in a range between 05 and 3 percent209 According to this argument charging interest
rates considerably higher than conventional banks is the only way for MFIs to generate
higher returns and hence successfully compete for capital
202 See Tschach (2000) pp 100 et sqq203 See Gibbons and Meehan (1999) p 149204 See M-Cril (2001b) p 4205 See CIA (2004)206 See MicroRate (2004)207 In this paper the term ldquolow endrdquo refers to the definition of the MBB (2003) p 54 Loans worth less than 20 percent of the respective countryrsquos GDP per capita are described that way 208 Own calculations See Appendix 3209 See M-Cril (2004a) p 16
41
6 Interest Rates
61 Setting the right Interest Rate
Before addressing the questions to what extend MFIs can raise their interest rates
without putting the repayment rate or the social benefits of their customers at risk a
basic model will be presented This model will illustrate how a MFI should set their
rates in order to not only cover their costs but also to generate an appropriate profit to
finance further growth and attract additional capital
In 2002 CGAP revised its 1996 paper ldquoMicrocredit Interest Ratesrdquo210 which outlines
the standard method of setting sustainable interest rates for commercially oriented
MFIs According to this model the annual effective interest rate (I) should be calculated
as shown below
(1) I = LL
IIKCFLLTA
minusminus+++
1
With each variable being a decimal fraction of the average outstanding loan portfolio
whereby TA stands for the transaction costs as described above LL represents the
annual loan loss and II stands for investment income eg on liquid assets The cost of
funds (CF) consist of the interest and administrative costs needed to obtain deposits and
commercial loans as well as of the imputed costs on equity due to inflation K stands for
the capitalization rate which represents the net real profit Keeping this rate high is
important to finance the future growth of the loan portfolio This can be either done
through investors attracted by high profitability or through borrowing For the latter an
increase in equity is inevitable since it is required as a safety cushion by lenders
Since this model ignores the timing of cash flows and does not take taxes into account
it has to be regarded as fairly imprecise and hence should not be used for business
planning Nevertheless it can be used for an approximation of the interest rate that a
MFI would need to charge to provide its services as planned In the following I will
210 See Rosenberg (2002) pp 1 et sqq
42
apply this model on a fictitious MFI working in a rural area of Latin America with low
end customers In this setting it seems realistic to estimate transaction costs of 35
percent and loan loss rate of two percent211 If funds were borrowed at commercial
terms their costs can be assumed to equal at least 15 percent of the average outstanding
loan portfolio212 Estimating the capitalization rate is more challenging First the
targeted portfolio growth rate is set at 75 percent This is slightly below the 751 percent
average annual portfolio growth between 2000 and 2002 found by a survey of 25
different MFIs based in Central and South America213 If the extend to which the MFI
can leverage stays constant the loan portfolios growth would be limited by the growth
rate of the equity To express the capital needed for this growth as a share of the loan
portfolio it is necessary to estimate the ratio between the equity and the outstanding
loan amount According to the survey mentioned above the loan portfolios of the 25
Latin American MFIs equal on average 215 times their equity214 With this number the
capital needed to increase the equity by 75 percent would corresponds to approximately
35 percent of outstanding loan amount (075215) Finally the investment income has to
be estimated Since liquid assets that are available short term do not generate high
returns say five percent it does not seem advisable for the MFI to hold more than a
quarter of its loan portfolio in this form Hence the profit generated in this way would
equal 125 percent of the outstanding loan amount Using these numbers the equation to
calculate the annual effective interest rate reads as follows
(2) I = LL
IIKCFLLTA
minusminus+++
1 =
0201
01250350150020350
minusminus+++
= 0875
As a result the MFI would need to charge an annual effective interest rate of
approximately 875 percent on its loans in order to sustainable provide its services and
finance its growth without depending on donor money This rate might decrease once
the MFI matures the growth slows down and cheaper funds become available but it
will stay significantly higher than any rate charged by conventional banks
211 MicroRate and IADB (2004) pp 6 and 16212 See MicroRate and IADB (2004) p 616 and 28213 Own calculation See Appendix 4214 Own calculations See Appendix 5
43
62 Can Micro-Entrepreneurs bear these Rates
Although most MFIs charge rates significantly below 875 percent many critics have
strenuously argued against any rates exceeding those of traditional banks Rosanna
Barbero of Oxfam labeled an interest rate of 52 percent charged by a Cambodian MFI
ldquoludicrous evil and disgusting and stated that ldquo[n]o business in the world can make a
profit at these interest ratesldquo215 The former finance minister of Bangladesh Shah Kibria
even categorized the 20 percent effective rate charged by the Grameen Bank as to
high216 Many practitioners therefore believe in a strong negative correlation between
the interest rate and the demand for loans217 Others have argued more generally that
concentrating on profitability and therefore charging high interest rates diverts MFIs
from serving the poorest218
These views are still shared among many MFI managers donor agencies and especially
investors and politicians While the former are unwilling to charge interest rates for
funds they received ldquocheaplyrdquo (through grants or subsidized loans) and are worried
about undermining their social goals by charging higher rates of interest219 the latter are
reluctant to invest for reasons stated above or impose interest caps to catch the attention
of the public by pretending to protect the poor from usury rates220
In chapter 53 it has been described that micro-entrepreneurs due to their smaller
capital endowment have even better investment opportunities than big business The
extend to which this is true has not yet been answered An indication is the high
repayment rate observed within MFIs around the globe If their customers capital yield
did not exceed the charged interest rate how would they be able to repay According to
Gibbons and Meehan customers of MFIs can generally generate returns of more than
100 percent on their invested capital221 and ldquo[r]esearch in India Kenya and the
Philippines found that the average annual return on investments in microenterprises
215 See Kate and Roeun (2004)216 See Hodson (2001) min 1100217 See Morduch (1999a) p 1594218 See Prisma (2002) p 1219 See Schreiner (1997) p 60 Khandker (1998) p 106 220 See Gross and de Silva (2002) p 32 Jansson and Wenner (1997) p 36 et sqq Campion (2002) p 59221 See Gibbons and Meehan (1999) p 131
44
ranged from 117 to 847 percentrdquo222 Schmidt and Tschach found the marginal
productivity of capital to be as high as 1000 percent for the smallest loans provided by
the Bolivian MFI Caja Los Andes223 These findings are confirmed by the observation
of Rosenberg who found while working as a microfinance consultant for ten years he
never heard of a single MFI having problems to attract clients because interest rates
were too high224
To get a better understanding of the investment opportunities of low income people in
developing countries a typical example on how MFI clients invest their loans is as
follows
Zobair is working as a rickshaw puller in Bangladesh Like most of his colleagues he
does not own the rickshaw he is riding Therefore he has to pay a daily rent of about
$030 to the owner Since his average income of approximately $15 per day is hardly
enough to feed his family he is not able to save the $100 necessary to buy a rickshaw
on his own 225 If he could do so through obtaining a loan his income would increase by
$030 every day because he would not have to pay the rent for the rickshaw anymore
Assuming an average of six working days per week 226 and a life span of the rickshaw
of 5 years his internal rate of return would equal 15324 percent annually227
Consequently any interest rate charged by a MFI would be advantageous to him as long
as it would not exceed 15324 percent228
63 Should the Interest Rate be subsidized anyway
Despite the fact that numerous micro-entrepreneurs are able to generate tremendous
returns on their investment obviously not all are able to use capital in such a productive
way and therefore can not afford microcredit at commercial rates In order to reach
these people as well many MFIs continue to use donor money in order to keep their
interest rates low But even if the problems related to subsidized credit as described in
222 See Helms and Reille (2004) p 3223 See Schmidt and Tschach (2001) p 6224 See Rosenberg (2002) p 10225 This examples draws on observations made by the author in Dhaka (Bangladesh) during 2003226 Obviously extended holidays are not a viable option in this surrounding 227 Own calculation See Appendix 6228 This result is only valid if the loan is repaid in daily instalments For a weekly repayment schedule the interest rate charged by the MFI must not exceed 15119 percent in order to still be beneficial for Zobair
45
chapter 23 do not arise it might still not be the most effective tool to help poor people
as will be illustrated in the following example
A MFI faces two groups of potential clients one with businesses able to generate a
return of 125 percent on borrowed capital and another with a possible returns of 50
percent Assuming budget costs according to equation (2) the institution needs to
charge an interest rate of 875 percent and therefore only serves the former group
Supposed each group consists of 50 members demanding $100 loans the net gains to
society (NGS) could be calculated as follows
(3) NGS = 50 times ($125 ndash $875) = $1875
These gains would be due to the investments of the more profitable group which were
made possible through the loans provided by the MFI The less profitable group would
not borrow since their expected returns are not sufficient to pay for the interest If the
interest rate would be lowered to 30 percent both groups would be able to generate net
gains and therefore borrow from the MFI In order to provide loans at this rate the
institution would need to raise additional capital from non commercial sources The
NGS would be calculated as follows
(4) NGS = 50 times ($125 - $30) + 50 times ($50 - $30) + 100 times ($30 - $875) = 0
While the first terms represent the net gains to the respective groups the last describes
the costs incurred in providing the loans At a rate of 30 percent each loan would need
to be subsidized with $575 Hence the NGS actually fall after the introduction of the
subsidized loan This is due to the fact that the less profitable group is encouraged to
invest in relatively unproductive businesses In addition future growth of the MFI could
be jeopardized due to scarce donor money which is needed to finance the interest rate
subsidy Therefore it seems more advisable to continue to charge a rate of 875 percent
and spend the money used for subsidization on other programs such as health care or
education229
229 In Appendix 7 it will be shown that this result generally holds
46
7 Empirical verification
71 Setting up a Sample
To see if the findings of the previous chapters hold the effects which interest rates
charged by MFIs have on their performance will be analyzed in the following Up to
now such a study does not exist mainly because of a lack of adequate data Most MFIs
do not provide accurate information about the annual effective interest rate they charge
and therefore make an evaluation difficult
In 2002 Rosenberg distinguished eight different categories on how microcredit interest
rates are quoted230 These categories differ in several ways On the contrary to
traditional banks for example it is common for MFIs to state interest rates calculated on
a ldquoflatrdquo balance rather than on a declining one This means that the total loan amount is
used to determine the interest rate ignoring installments paid by the borrowers normally
on a weekly or monthly basis In addition many MFIs charge a certain upfront fee prior
to the loan disbursement require compulsory savings at a lower rate or state their
interest rate for semi annual terms only On the one hand this is done to provide
numbers that are more meaningful to MFI customers who often lack the necessary math
skills to deal with compound interest on the other hand it is done to circumvent interest
rate ceilings imposed by the government231 Another problem is that most MFIs offer
different loan products without itemizing their respective shares to their total loan
portfolio As a result it is not possible to calculate a weighted average even if the rate
stated by the respective MFI could be transformed into an effective interest rate
Usually the portfolio yield is used as a proxy in order to make statements about the
interest rate charged by a certain MFI232 It is generally ldquocalculated by dividing total
cash financial revenue (all income generated by the loan portfolio but not accrued
interest) by the period average gross portfoliordquo233 The advantage of this method is that
even the hidden costs are considered Nevertheless it also has a severe shortcoming by
not taking late or defaulted payments into account Therefore the portfolio yield does
230 See Rosenberg (2002) p 5231 MicroRate (2002) p 8232 See MicroRate (nd)233 MicroRate and IADB (2003) p 39
47
not allow to draw conclusions regarding the correlation between the interest rate
charged by a MFI and its PAR
72 Examining the Sample
Through the appearance of rating agencies specialized in the microfinance sector more
adequate information has become available in recent years While MicroRate only
publishes the portfolio yield of rated MFIs M-Cril Microfinanza Microserve and
Planet Rating actually provide information about the annual effective interest rate for at
least some of the MFIs they analyze Although it is labelled differently from all of the
four institutions234 the term describes what is ldquothe highest income or yield that an
organisation can earn from its portfolio based on the terms of its loansrdquo235
Currently236 reports of 39 different MFIs from 20 countries providing accurate
information about the effective annual interest rate are available to the public This
sample should be used to verify the findings of the previous chapters237 Since a
comparison is made between the performances of MFIs based in different countries and
the ratings have been carried out in different years several adjustments are necessary
First the inflation of the respective country and the respective year(s)238 has to be taken
into account in order to only compare the real rates239 In addition the average
outstanding loan amount per borrower is divided by the respective countryrsquos GDP per
capita Since it can be assumed that ldquoonly the poorer households will be willing to take
the smallest loansrdquo240 this number can be used as a proxy for the poverty level
Although the sample size is far to small to represent the microfinance sector as a whole
and the results are statistically not significant the findings can still be used to underline
the theoretical conclusions drawn in the previous chapters In figure 5 the connection
234 M-Cril uses the name ldquoannual percentage raterdquo See eg M-Cril (2004a) p 25 Microfinanza uses the name ldquoexpected portfolio yieldrdquo See eg Microfinanza (2002c) p 25 Planet Rating uses the name ldquoannual effective interest raterdquo See eg Planet Rating (2004d) p 1 Microserve uses the name ldquotheoretical yieldrdquo See Microserve (2003) p 62235 See M-Cril (2004a) p 25236 As of September 28th 2004237 See Appendix 8 For exchange rates see FXTOP (2004)238 Where necessary a weighted average of the annual inflation rate was used See Appendix 9239 This is done through the following formula ir = (I ndash F) (1 + F100) While ir represents the real annual effective interest rate F represents the inflation rate 240 Morduch (1998) p 1572
48
between the average loan size and the transaction costs as a share of the average loan
portfolio is illustrated
Figure 5 Loan Size vs Interest Rate241
Source Own diagram
000
1000
2000
3000
4000
5000
6000
7000
8000
9000
10000
0 100 200 300 400 500 600
Loan Size
Inte
res
t R
ate
It can be seen that the interest rate is negative correlated to the loans size This can be
explained by the relative higher transaction cost for smaller loans as described in
chapter 52 In order to cover their costs MFIs serving the low end market need to
charge higher rates to their customers than those organizations serving the better off
poor Obviously there are several assumptions to this general finding Especially
striking are the two MFIs with an average loan size of approximately five times their
countries GDP per capita which still high interest rates This occurrence can be
explained by taking a closer look to the respective organizations One was established
less than two years prior to its rating and therefore still bears a lot of start up costs242
241 The equation for the regression line reads as follows Y = -00219X + 365 The correlation coefficient is 014242 See Microfinanza (2002b) p 1
49
the other managed to stay profitable while it almost quadrupled its loan portfolio in the
last two years243
Figure 6 Interest Rate vs PAR244
Source Own diagram
0
5
10
15
20
25
30
35
0 20 40 60 80 100 120
Interest Rate
PA
R
In Figure 6 the crucial correlation between the interest rates charged by a MFIs and its
PAR245 is examined According to the given sample the view of traditional banks and
investors that a higher interest rate leads to a higher default rate does not hold
Obviously one has to avoid to draw the opposite conclusion namely that a high interest
rates decreases the PAR The connection illustrated in figure 6 has to be interpreted as
follows Since high interest rates are related to small loans the low PAR for MFIs
charging high interest rates can actually be explained by the tremendous profitability of
small size investments Despite the high rates their customers are even more likely to
repay
243 See Planet Rating (2003b)244 The equation for the regression line reads as follows Y = -00768X + 68433 The correlation coefficient is 0235245 M-Cril only publishes the PAR for overdues greater than 60 days Therefore these ratios are used as a proxy for the industry standard of 30 days for some Asian MFIs
50
Finally it has to be examined if charging high interest rates actually enables MFI to
generate higher returns Although it can be expected that the combination of a low PAR
and a high interest rate leads to a high profitability it still has to be checked if this is not
outdone by soaring transaction costs Figure 7 illustrates the correlation between the
interest rate charged by a MFI and its financial self-sufficiency (FSS) The latter is the
ldquo[r]atio of total income to total adjusted expenses for the year Adjustments are made
for subsidised cost of funds (relative to market interest rate) equity (with respect to
inflation) and in-kind donationsrdquo246 It can be seen that the regression line actually does
indicate a positive correlation between the interest rate and the profitability of a MFI
Figure 7 Interest Rate vs FSS247
Source Own diagram248
0
20
40
60
80
100
120
140
160
180
0 20 40 60 80 100
Interest Rate
FS
S
246 M-Cril (2004a) p 53247 The equation for the regression line reads as follows Y = 02839X + 8901 The correlation coefficient is 0174248 Since the interest rate the customers of the MFI Foccas have to pay includes fees which are not passed on to the institution its interest rate in this diagram is set at 723 percent instead of the 10715 percent used for figure 6 See Planet Rating (2003b) p 1
51
This result does not necessarily disprove the findings of Stiglitz and Weiss since it can
be argued that MFIs simply do no increase their interest rates to the point where they
would maximize their expected returns But if this would be true why do MFIs not
charge higher rates of interest given the demand described in chapter 41 and 43 In
mature markets competition normally ensures prices not to exceed a certain level but
since many MFIs still operate in a ldquosellerrsquos marketrdquo249 this can not explain the findings
as described in figure 7 Therefore it has to be assumed that a combination of the
unwillingness of many microfinance practitioners to burden their customers with high
interest rates and the plain disbelief of traditional investors that micro-entrepreneurs can
bear those rates is responsible for this occurrence
249 See MicroRate and IADB (2003) p 9
52
8 Conclusions
It has been shown that MFIs are not only contributing significantly to the development
of the financial sector in their respective countries but also that they play an important
role to eradicate poverty by providing much needed capital to low income people which
are able to generate tremendous returns on their investments
The fact that the demand for microcredit is not met is mainly due to the view of most
for profit investors and traditional banks that offering financial services to poor people
can not be done profitable Because of this conviction they hardly invest in the
microfinance sector This does not have to be the case according to the findings of this
paper Although faced with relatively high transaction costs MFIs are able to charge
interest rates at levels that fully recover their costs Elizabeth Rhynersquos claim ldquothat the
most financially viable programs differed from their less viable peers in their
willingness to set interest rates at levels that would fully recover costsrdquo250 is backed by
the findings of this paper that high profitability is correlated to high interest rates
Theoretical models based on the findings of Stiglitz and Weiss can not be used as a
justification to ration credit for the microfinance sector since the interest rate that
maximizes profits to the lender can be assumed to exceed 100 percent for many MFIs
Nevertheless this rate is hardly charged although it has been shown that it can be done
The Mexican MFI Compartamos for example manages to keep its PAR as low as one
percent while charging an effective interest rate of more than 100 percent to
approximately 160000 clients251 In combination with this case the conclusions drawn
from examining the sample of MFIs in chapter 7 the claim of Hulme and Mosley as
stated in the introduction can be considered as wrong MFIs are in fact able to finance
rapid growth stay profitable by charging corresponding interest rates and still have a
significantly positive impact on the poverty level of their clients In the long run gains
in efficiency economies of scale a slowdown in growth and competition will ensure
interest rates drop as it has already been the case in countries like Bangladesh and parts
of Bolivia252
250 See Rhyne (1998) p 7251 See MicroRate (2004)252 See Microrate and IADB (2003) p 9
53
According to a MicroRate survey many MFIs are more profitable than Citibank and also
generate a higher return on investment than commercial banks in their respective
countries253 Investments companies like IMI or Blue Orchard will soon be able to
present a meaningful track record of their microfinance investments to potential
investors Ultimately the capital markets can not ignore the facts proving that it actually
can be profitable to invest in the microfinance sector but in order to raise money
quickly microfinance practitioners will have to continue to intensively promote their
cause not only to for profit investors but also to donors and multilateral agencies like
the World Bank
253 See MicroRate (2002) p 10
54
Appendix
Appendix 1 Average loan balance
Source Data is available through the Mix Market (2004)
Organization
Loan Portfolio 2002 (US$)
Loan Portfolio 2003 (US$)
Number of borrowers 2002
Number of Borrowers 2003
2CM 1263602 1400438 3622 3708ACF 955503 1611401 285 370ACLEDA 26846703 39391301 82598 98905ACME 1460881 1714844 4283 4600ADIM 369065 407798 1122 1395AFK 933306 1706577 250 467AgroInvest 4684249 9697411 5208 9629Al Amana 15593277 28677666 78114 101610AMSSFMC 612167 1040756 6183 6886AREGAK 3285273 3987011 11841 14377AVFS 214331 269819 1883 2866BancoSol 83629049 91175000 42290 56707BESA 10563980 15114430 4488 5061BPR AK 613362 876130 1730 3879BPR BMMS 133949 237946 1755 1779BRI 1344006170 1720072773 3056103 3100358BZMF 1592508 1922097 1250 1331CBDIBA 216587 242465 5764 2877CCA 2146235 4582302 4070 6585CCCP 447534 851678 6265 9450CEP 3795400 5261957 32291 42132CERUDEB 25093643 34873228 34490 44796CMEDFI 227674 250244 3467 3781CMM - Bogota 4836000 8135968 15635 22038CMMB 34880 56964 42 190COAC Maquita Cushunchic
870084 1855718 6603 7732
CODES 280843 263091 60 60CODESARROLLO 6714007 12935951 4391 6896Constanta 2943822 3536047 16134 18588COOPEC CAMEC MN
7152 29821 92 77
Crear - Tacna 3891116 4636094 3671 4948CREDIT 642094 81838 7532 8097CRYSTAL FUND 366456 421403 1379 1061DBACD 3473701 3876526 12812 19606ECLOF - ECU 1154292 728312 860 416ECLOF - MAL 441734 407227 1118 1500EKI 11833244 19245751 8999 13323EMT 4481589 5765281 84781 92173ESED 8579460 6834742 22790 20035
55
Eshet 185741 462569 3308 6540Faulu - KEN 9027332 7206344 17463 15000FDL 12503027 16545332 21306 25106FIE 35818903 41597315 26468 33100FINADEV 5512586 9770323 12775 14709Finance Salone 211312 434298 2225 7159Finca - TAN 1293430 1854834 20648 27499Finca - UGA 2451703 2798869 35610 36912FINCORP 4761288 10236896 941 858FJN 5473563 8037662 8107 11133FMFB 308158 1188896 713 3558FMM -Bucaramanga
6355518 10227000 25814 42464
FODEM 739181 939824 1909 2501FundaciESPOIR
898561 1883446 5911 9464
FUNDESER 798907 1373113 4072 5065Gasha 323748 413742 5504 6423GGLS Save the Children
64235 137957 1291 2362
GK 56986 166971 951 2718HKL 1363365 1420357 6648 5372HOPE 402799 603488 1098 1562IAMD 42132 56550 2780 2772IDECE 21312 39453 150 232IDF 2031944 2626382 31003 36580IMCEC - Dakar 254759 688449 1018 2983IMCEC - Thies 199799 571122 1164 1261
ISSIA 221615 246792 1409 1698JMCC 1962355 2609723 1471 2333KAFC 21710638 29241051 24850 32097KAMURJ 1003935 1411258 5559 5691Kashf 2355965 6271498 29655 59389KMBI 721409 1626666 11973 27266KPSCA 109299 128063 362 794K-Rep 14490447 20699963 38739 45379KSCS 18978 43740 140 297KVT 44075 70621 241 373LAPO 922478 1194633 18740 19139MEC ADEFAP 27788 69248 198 202MEC Bosangani 14357 31086 364 540MEDF 104113 136257 1278 1184Meklit 233170 252232 2084 3577Metemamen 22123 57778 943 1501MFSC 109261 171090 511 687MIKRA 2951028 5008784 4145 6095MIKROFIN 9560502 18380263 5633 7426Miselini 737387 1026639 10182 11431MRFC 11475440 9133130 163000 180000Mushuc Runa 2089076 5418325 3139 6232Nirdhan 2886777 3016171 29589 27457OCSSC 5245186 7658413 42157 6215o
56
Otiv Diana 95992 638422 229 1073Otiv Sambava 188094 437974 2002 1442Otiv Tana 66465 673175 337 1269Partner 9976448 15321304 7139 11935PCA 6878257 6885926 63113 58147PEACE 420746 627295 4192 5428PEDF 164399 254233 2357 3340Piyeli 809447 1206656 8674 4745PRESTANIC 2827502 3540367 1477 2605PRIDE - MAL 991888 854631 5376 5601PRIZMA 3881581 6838978 8112 10968ProMujer -Nicaragua
1006871 1424437 10436 13047
PTF 891566 1068881 8500 9070RBST 818594 1058115 619 723REMECU 1381705 1483471 10330 13996
RUSCA 60887 100820 454 994
SCSCS 89423 157472 873 1007SFPI 709497 903556 7728 9552Sidama 934260 1011798 10267 11346SPBD 117807 186029 647 1740Sunlink 819138 1056823 3401 3833Sunrise 5412366 8782868 4560 7256TEBA 108032426 176300111 163021 157776TIAVO 281978 838905 2049 459TPC 1140429 2267148 22869 31668TSPI 4650989 5383755 49649 75617UNICECAM 3442843 5943804 16039 19031Wasasa 230657 274908 2850 3728Wisdom 1306066 1404463 10524 12054XacBank 4910098 9829503 11063 18610Zakoura 15907288 12444768 103720 118980
Appendix 2 Portfolio at Risk
Source Data is available through the Mix Market (2004)
Organization PAR 2002ABA 202ACEP 464ACLEDA 175ACODEP 452ACSI 209Al Amana 010Apoyo Integral
483
AREGAK 692Banco Solidario
500
BancoSol 660BASIX 1296
57
BRI 437BURO Tangail
350
CEP 200CERUDEB 103CMAC -Sullana
567
CMM -Bogota
176
Compartamos 111Constanta 304Credi Fe 212CREDIAMIGO 409DBACD 010EBS 847EMT 010ESED 1311FADES 2311Faulu - KEN 246Faulu - UGA 096FDL 212FECECAM 428FED 436FIE 598FINADEV 021Finamerica 1133Finca - TAN 000Finca - UGA 297FMM -Bucaramanga
094
FMM -Popayan
088
FONDEP 013FORA 064Genesis Empresarial
1197
IDF 017KAFC 106Kashf 000KMBI 128K-Rep 229MiBanco 309MRFC 1742Nirdhan 373
PADME 079PAMECAS 284PCA 379PRIDE - TAN 018ProMujer -Nicaragua
073
RCPB 600REMECU 157SHARE 000
58
Soluci 182Spandana 014TEBA 106TSPI 355UMU 125UNICECAM 405Urwego 290UWFT 363WAGES 736WWB -Medellin
235
XacBank 061Zakoura 095
Appendix 3 Transaction Costs
Source Data is available through the Mix Market (2004)
OrganizationTransaction Costs
Acci Rural 1154ACEP 858ACLEDA 2430ACODEP 2920ACSI 924Al Amana 2576AREGAK 2856AssEF 1919Banco Solidario
1826
BancoSol 1210BASIX 1317BRI 1353BURO Tangail
2053
CEP 1759CERUDEB 5109CMAC -Sullana
1784
CMM -Bogota
2089
Compartamos 3341Constanta 4597Credi Fe 1978CREDIAMIGO 2525DBACD 1742EBS 2377EMT 3220ESED 1343FADES 1673FAMA 2436
59
Faulu - KEN 2253Faulu - UGA 4962FDL 1726FECECAM 2587FED 4083FIE 1125Finamerica 1563Finca - TAN 10753Finca - UGA 9096FMM -Bucaramanga
1925
FMM -Popayan
1112
FONDEP 5477FORA 3481Genesis Empresarial
1626
IDF 1695
K-Rep 1909LAPO 3511MiBanco 2456Nirdhan 1325NWTF 3109OCSSC 1155PADME 1131PAMECAS 1705PCA 1670PRIDE - TAN 4273ProMujer -Nicaragua
5078
RCPB 2059SHARE 2308Sidama 2662Soluci 2906Spandana 641TEBA 1213TSPI 3898UMU 4023UNICECAM 10120Urwego 7437Wisdom 1906WWB -Medellin
1703
XacBank 4144Zakoura 1881
60
Appendix 4 Portfolio Growth
Source Data is available through the Mix Market (2004)
Organization
Total Loan Portfolio in 2000
Total Loan Portfolio in 2002
ACODEP 5889394 7258487Adelante 4327 88594ADRI 1514681 2591240AgroCapital 11100088 12018280Banco Solidario 39632165 103420000
BancoSol 78031172 83629049CMAC - Sullana 14596365 28055720
COAC Maquita Cushunchic
348443 870084
CODESARROLLO 1374801 6714007Compartamos 10804279 41825248Crear - Tacna 3778816 3891116
Credi Fe 781616 9393936ECLOF - ECU 179247 1154292
FADES 11948814 15501578FAMA 6201411 8835134FIE 22524645 35818903Finamerica 16575104 16097113FINCOMUN 3278938 5696556FMM - Popayan 6241821 12212867
FONDECO 3456625 5101801Genesis Empresarial
11154234 17746288
MiBanco 36964072 95873333Mushuc Runa 90737 2089076ProMujer -Nicaragua
426541 1006871
WWB - Medellin 2891207 4580998
Appendix 5 Portfolio vs Equity
Source Data is available through the Mix Market (2004)
OrganizationLoan Portfolio Equity
ACODEP 7258487 1921447Adelante 88594 72973
ADRI 2591240 781477AgroCapital 12018280 10766101Banco Solidario 103420000 12961000BancoSol 83629049 15299415CMAC - Sullana 28055720 6210291
61
COAC Maquita Cushunchic
870084 260331
CODESARROLLO 6714007 1285103
Compartamos 41825248 18350446
Crear - Tacna 3891116 1016912Credi Fe 9393936 863848ECLOF - ECU 1154292 459226FADES 15501578 4138972FAMA 8835134 6377663FIE 35818903 5360484Finamerica 16097113 3817960FINCOMUN 5696556 1042241FMM - Popayan 12212867 8510494FONDECO 5101801 1658075Genesis Empresarial
17746288 4765816
MiBanco 95873333 24261889Mushuc Runa 2089076 434311ProMujer -Nicaragua
1006871 1196015
WWB - Medellin 4580998 2213249
Appendix 6 Internal Rate of Return
Source Excel (German Version) calculation based on own data
A B C D E F
1 Date Cash Flow
Interest Rate Internal Rate of Return Balance Interest Principal
23 01012004 -100 15324 100 025489547 0045104534 02012004 03 999548955 025489547 0045104535 03012004 03 99909676 02547805 004521956 04012004 03 998643412 025466524 0045334767 05012004 03 998188909 025454968 0045450328 06012004 03 997733247 025443383 0045566179 08012004 03 999826083 050928361 -0209283610 09012004 03 999374595 025485114 004514886
hellip hellip hellip hellip hellip helliphellip hellip hellip hellip hellip hellip helliphellip hellip hellip hellip hellip hellip hellip1562 23122008 03 177951388 000528711 0294712891563 25122008 03 148859724 000908336 0290916641564 26122008 03 119239161 000379437 0296205631565 27122008 03 089543096 000303935 0296960651566 28122008 03 059771337 000228241 0297717591567 29122008 03 029923692 000152354 0298476461568 30122008 03 -3434E-07 000076274 029923726
62
The formula in the square C3 reads as follows
ldquoXINTZINSFUSS(B3B1568A3A156815)rdquo
Appendix 7 Subsidized Interest Rates and the Net Gains to Society
SourceOwn calculations
For simplicity only two groups of potential clients are distinguished This is possible
since using a continuum of potential clients would lead to the same results In addition it
is assumed that the amount of every loan (L) is equal and that all clients invest the
whole loan amount Group H consist of NH potential clients with a rate of return (rH) on
their invested capital higher than the cost recovering interest rate charged by the MFI
(iC) Group L consists of NL potential clients with a rate of return (rL) on their invested
capital lower than iC If the MFI charges iC the NGS can be calculated as follows
NGSC = NH times (rH - iC) times L
Since rH is bigger than iH (rH gt iC) according to the definition presented above the term
NGSH must be positive as long as NH does not equal zero If the MFI introduces a
subsidised interest rate (iS) lower than rL the NGS can be calculated as follows
(1) NGSS = NH times (rH - iS) times L + NLtimes (rL - iS) times L + (NH + NL) times (iS - iC) times L
(2) NGSS = NH times (rH- iC) times L + NLtimes (rL - iC) times L
The term (NH + NL) times (iS - iC) times L describes the amount of money that is needed in order
to subsidize the interest rate to the level iS By setting up an inequation it can be
examined under which conditions the NGSS are bigger than the NGSC
(3) NGSS gt NGSC
(4) NH times (rH- iC) times L + NLtimes (rL - iC) times L gt NH times (rH - iC) times L
(5) NLtimes (rL - iC) times L gt 0
(6) rL gt iC
63
So the NGSS could only be bigger than the NGSC if equation 6 holds This is
impossible since it violated the definitions presented above Therefore the introduction
of subsidized interest rates is always accompanied with a drop in the NGS
Appendix 8 Interest Rate vs Loan Size vs FSS vs PAR
Source Data is available through the Mix Market (2004)
Organization Country
Real Interest Rate
Loan Size (divided by the GDP per Capita) FSS PAR
BTFFKyrgyz Republic 3803 48260 1487 698
BesaFoundation Albania 2184 16076 684 260RFF Albania 1198 5783 4764 277PSHM Albania 2194 000 5758 198Mi-Bospo Bosnia 2974 5499 1261 020Prizma Bosnia 3474 3569 103 064Agroinvest Serbia 2201 4401 875 020KCLF Kazakhstan 5713 1713 865 090
Foccas Uganda10716 (723) 1550 584 29
ACEP Senegal 3280 20941 1643 1Padme Benin 2715 13575 1667 08Papme Benin 3086 53659 1405 24Vital Finance Benin 2676 9394 1015 17Finadev Benin 1738 14850 1024 21ABA Egypt 2579 1613 1168 88ASBA Egypt 2597 1702 1252 68DBACD Egypt 2490 1643 1073 0SBACD Egypt 2500 1734 982 67AMSSF Morocco 6926 787 1306 04Fondep Morocco 5199 650 889 071Zakoura Morocco 4414 900 98 006ENDA Tunisia 4008 1351 110 102BSFL India 1954 3269 856 99Share India 3426 1440 951 0Spandana India 2942 1618 1367 026SWC India 1864 2626 42 3036SKS India 2248 1912 578 0Grama Vidiya India 3176 1221 76 18Sneha India 3451 1433 933 0Buro Bangladesh 3206 1882 1093 17Upap Pakistan 2073 8183 757 03Seeds Sri Lanka 1004 1088 605 287EMT Cambodia 4324 1676 1016 01TPC Cambodia 4470 2035 832 27
64
WTF Phillippines 5816 1095 941 74TSKI Phillippines 5794 777 96 79Cacja Ecuador 862 6189 9460 897ACME Haiti 6043 6934 11685 450Grupo Cama Mexico 8961 267 10717 288
65
Appendix 9 Inflation vs GDP per Capita
Source IMF (2004)
Country Subject Description Units Scale 2000 2001 2002 2003 2004
Albania Gross domestic product per capita current prices US dollars Units 1083988 1238206 1396172 1757778 2229712
Albania Inflation annual percent change Percent 00 31 52 24 34
Bangladesh Gross domestic product per capita current prices US dollars Units 329310 327980 344494 369495 393717
Bangladesh Inflation annual percent change Percent 22 15 38 54 64
Benin Gross domestic product per capita current prices US dollars Units 361340 368213 405951 494725 560129
Benin Inflation annual percent change Percent 42 40 24 15 26
Bosnia and Herzegovina Gross domestic product per capita current prices US dollars Units 1255837 1321429 1466090 1807392 2070508
Bosnia and Herzegovina Inflation annual percent change Percent 50 32 03 02 09
Cambodia Gross domestic product per capita current prices US dollars Units 276413 280352 296577 305940 321247
Cambodia Inflation annual percent change Percent -08 02 33 12 20
Ecuador Gross domestic product per capita current prices US dollars Units 1227711 1590267 1804362 1957183 2082156
Ecuador Inflation annual percent change Percent -77 377 126 79 32
Egypt Gross domestic product per capita current prices US dollars Units 1550982 1461431 1278462 1188060 1083158
Egypt Inflation annual percent change Percent 28 24 24 32 52
India Gross domestic product per capita current prices US dollars Units 454206 458849 472915 542554 602625
India Inflation annual percent change Percent 40 38 43 38 47
Kazakhstan Gross domestic product per capita current prices US dollars Units 1236159 1490946 1655148 2000598 2579554
Kazakhstan Inflation annual percent change Percent 134 83 59 64 68
Kyrgyz Republic Gross domestic product per capita current prices US dollars Units 278256 306130 321079 349632 380637
Kyrgyz Republic Inflation annual percent change Percent 187 69 21 31 45
66
Mexico Gross domestic product per capita current prices US dollars Units 5957486 6274468 6425203 6111754 6377064
Mexico Inflation annual percent change Percent 95 64 50 45 44
Morocco Gross domestic product per capita current prices US dollars Units 1161302 1162154 1199584 1432725 1541041
Morocco Inflation annual percent change Percent 19 06 28 12 20
Pakistan Gross domestic product per capita current prices US dollars Units 437381 400356 440471 492913 538120
Pakistan Inflation annual percent change Percent 44 31 32 29 46
Philippines Gross domestic product per capita current prices US dollars Units 979423 900225 950707 963765 1018710
Philippines Inflation annual percent change Percent 43 61 31 30 54
Russia Inflation annual percent change Percent 208 215 158 137 103
Senegal Gross domestic product per capita current prices US dollars Units 478704 474460 507408 634171 714622
Senegal Inflation annual percent change Percent 09 30 23 -00 08
Serbia and Montenegro Gross domestic product per capita current prices US dollars Units 1031263 1389384 1882036 2491799 2795805
Serbia and Montenegro Inflation annual percent change Percent 699 911 212 113 79
Sri Lanka Gross domestic product per capita current prices US dollars Units 846811 796025 828256 904330 982466
Sri Lanka Inflation annual percent change Percent 62 142 96 63 64
Tunisia Gross domestic product per capita current prices US dollars Units 2034360 2065140 2149421 2534823 2881273
Tunisia Inflation annual percent change Percent 30 19 28 28 34
Uganda Gross domestic product per capita current prices US dollars Units 293404 249682 279587 280802 287204
Uganda Inflation annual percent change Percent 45 -20 57 51 35
67
References
Akerlof George A The Market for ldquoLemonsrdquo Qualitative Uncertainty and the Market Mechanism in Quarterly Journal of Economics Vol 84 (1970) pp 488-500
Amin Ruhul et al Integration of an Essential Service Package (ESP) in Child and Reproductive Health and Family Planning with a Micro-Credit Program for poor Women Experience from a Pilot Project in Rural Bangladesh in World Development Vol 29 (2001) No 9 pp 1611-1621
Bester Helmut Screening vs Rationing in Credit Markets with Imperfect Information in The American Economic Review Vol 75 (1985) No 4 pp 850855
Borst Dietmar Microfinance ndash Theoretische Grundlagen fuumlr den Einsatz sowie die Abschaumltzung des Potentials anhand einer Datenbankuntersuchung zur Verwundbarkeit der laumlndlichen Bevoumllkerung in Vietnam unpublished diploma thesis Karlsruhe 2004
BRAC Annual Report 2002 Dhaka 2003
Busch Alexander Kort Katharina Die Peanuts-Banker und ihre Kunden in Handelsblatt Nr 150 published August 5th 2004 p 8
Campion Anita Challenges to Microfinance Commercialization in Journal of Microfinance Vol 4 (1999) No 2 pp 57-65
Chu Michael Key Issues of Development Finance Somerville (MA) 1998
Dornbusch Ruumldiger Fischer Stanley Makrooumlkonomie Oldenburg 1995
Dunn Seth Flavin Christopher Moving the Climate Change Agenda Forward in State of the World New York London 2002 pp 24-50
Farrington Todd Efficiency in Microfinance Institutions in The MicroBanking Bulletin Issue No 4 pp 18-24
Gardner Gary The Challenge for Johannesburg Creating a More Secure World in State of the World New York London 2002 pp 3-23
Ghatak Subrata On Interregional Variations in Rural Interest Rates in Journal of Developing Areas Issue 18 pp 21-34
Gibbons David Serving the Poorest Sustainably in The MicroBanking Bulletin Issue No 5 (2000) pp 13-16
Gibbons David Meehan Jennifer W The Microcredit Summitrsquos Challenge WorkingToward Institutional Financial Self-Sufficiency While Maintaining a Commitment to Serving the Poorest Families in Journal of Microfinance Vol 1 (1999) No 1 pp 131-192
68
Goodwin-Groen Ruth Do Asian MFIs Access Funds from Commercial Banks inThe MicroBanking Bulletin Issue No 3 pp 8-10
Grameen Bank (ed) Grameen Generalized System Dhaka 2003
Gross Alexandra de Silva Samantha Social Fund Support of Microfinance A Reviewof Implementation Experience The World Bank Social Protection Discussion Paper No 0215 Washington DC 2002
Hashemi Syed M Schuler Sidney R Sustainable Banking with the Poor A Case Study of Grameen Bank Dhaka 1997
Helms Brigit Reille Xavier Interest Rate Ceilings and Microfinance The story so farConsultative Group to assist the Poor Occasional Paper No 9 September 2004 Washington DC 2004
Hoff Karla Stiglitz Joseph E Introduction Imperfect Information and Rural Credit Markets-Puzzles and Policy Perspectives in The World Bank Economic Review Vol 4 (1990) No 3 pp 235-250
Holcombe Susan Managing to Empower The Grameen Bankrsquos Experience of Poverty Allevation Dhaka 1995
Hulme David Mosley Paul Finance against Poverty London 1996
Jalvaani (ed) Flush with loans Micro credit for rural sanitation Vol 2 (1999) No 2 pp 1-2
Khandker Shahidur R Fighting Poverty with Microcredit Experience in Bangladesh Oxford et al 1998
Khandker Shahidur R Khalily Baqui Khan Zahed Grameen Bank Performance andSustainability The World Bank Discussion Paper No 306 Washington DC 1995
Lipsey Rechard G An Introduction to Positive Economics 5th edition London 1979
Littlefield Elizabeth Morduch Jonathan Hashemi Syed M Is Microfinance an Effective Strategy to Reach the Millennium Development Goals Consultative Group to Assist the Poorest Focus Note No 24 Washington DC 2003
Martinot Eric Cabraal Anil World Bank Solar Home Systems Projects Experience and Lessons Learned 1993-2000 in Renewable Energy Oxford 2000 pp 1-8
M-Cril Microfinance Review 2003 revised February 2004 Gurgaon 2004a
Mezzera Jaime Microcredit in Brazil The Gap Between Supply and Demand in The MicroBanking Bulletin Issue No 8 (2000) pp 22-24
The MicroBanking Bulletin (ed) Note to the Reader Vol 1 (1997) Issue No 1 pp 5-8
69
The MicroBanking Bulletin (ed) An Introduction to the Peer Groups and Tables Issue No 9 (2003) pp 53-60
MicroRate IADB Performance Indicators for Microfinance Institutions Technical Guide 3rd edition Washington DC 2003
MkNelly Barbara Dunford Christopher Impact of Credit with Education on Mothers and Their Young Childrenrsquos Nutrition Lower Pra Rural Bank Credit with Education Program in Ghana Freedom from Hunger Research Paper No 4 Davis (CA) 1998
MkNelly Barbara Dunford Christopher Impact of Credit with Education on Mothers and Their Young Childrenrsquos Nutrition CRECER Credit with Education Program in Bolivia Freedom from Hunger Research Paper No 5 Davis (CA) 1999
Morduch Jonathan The Microfinance Promise in Journal of Economic Literature Vol 37 (1999b) No 4 pp 1569-1614
Neus Werner Einfuumlhrung in die Betriebswirtschaftslehre Tuumlbingen 1998
Otero Maria Bringing Development Back into Microfinance Journal of Microfinance Vol 1 (1999) No 1 pp 8-19
Panjaitan-Drioadisuryo Rosintan D M Cloud Kathleen Gender self-employment and microcredit programs An Indonesian case study in The Quarterly Review of Economics and Finance Vol 39 (1999) pp 769ndash779
Perkins Dwight H et al Economics of Development 5th edition New York London 2001
Pitt Mark M Khandker Shahidur R Credit Programs for the Poor and the Health Status of Children in Rural Bangladesh in International Economic Review Vol 44 (2003) No 1 pp 87-118
Raiffeisen Friedrich W The Credit Unions 8th edition Neuwied 1966
Rhyne Elizabeth The Yin and Yang of Microfinance Reaching the Poor and Sustainability in The MicroBanking Bulletin Issue No 2 (1998) pp 6-9
Richardson David C Unorthodox Microfinance The Seven Doctrines of Success in The MicroBanking Bulletin Issue No 4 (2000) pp 3-7
Robinson Marguerite S The Microfinance Revolution Sustainable Finance for the Poor Washington DC 2001
Robinson Marguerite S The Microfinance Revolution Volume 2 Lessons from Indonesia Washington DC 2002
Rosenberg Richard Microcredit Interest Rates Consultative Group to assist the Poorest Occasional Paper No 1 revised November 2002 Washington DC 2002
70
Roth Michael Steinwand Dirk Mikrofinanz Weltweites Erfolgsmodell nur nicht inDeutschland Zur Uumlbertragbarkeit der Erfahrungen aus Entwicklungslaumlndern auf Deutschland Deutsche Gesellschaft fuumlr Technische Zusammenarbeit (ed) Eschborn2004
Schmidt Reinhard H Tschach Ingo Microfinance as a Nexus of Incentives Finance and Accounting Working Paper No 87A Frankfurt 2001
Schreiner Mark A Framework for the Analysis of the Performance and Sustainability of Subsidized Microfinance Organizations with Application to Banco Sol of Bolivia and Grameen Bank of Bangladesh unpublished PhD dissertation Columbus (O) 1997
Seibel Hans D Recent Developments in Microfinance Development Research Center Working Paper No 1998-5 Cologne 1998
Seibel Hans D History matters in microfinance in Small Enterprise Development ndashAn International Journal of Microfinance and Business Development Vol 14 (2003a) No 2 pp 10-12
Seibel Hans D Schmidt Petra How an Agricultural Development Bank Revolutionized Rural Finance The Case of Bank Rakyat Indonesia International Fund for Agricultural Development Rural Finance Working Paper B 5 Rome 2000
Sen Amartya Oumlkonomie fuumlr den Menschen ndash Wege zu Gerechtigkeit und Solidaritaumlt in der Marktwirtschaft Muumlnchen Wien 2000
Serageldin Ismail The View of the Chair in Consultative Group to Assist the Poorest Newsletter Issue No1 (1996) pp 1 11-12
Soros George Die Krise des globalen Kapitalismus Offene Gesellschaft in Gefahr Berlin 1998
Staschen Stefan Regulation and Supervision of Microfinance Institutions State of Knowledge Deutsche Gesellschaft fuumlr Technische Zusammenarbeit (ed) Eschborn 1999
Steinwand Dirk The Alchemy of Microfinance The Evolution of the IndonesianPeoples Credit Banks (BPR) to 1999 and a Contemporary Analysis Berlin 2001
Stiglitz Joseph E Peer Monitoring and Credit Markets in The World Bank Economic Review Vol 4 (1990) No 3 pp 351-366
Stiglitz Joseph E Weiss Andrew Credit Rationing in Markets with Imperfect Information in The American Economic Review Vol 71 (1981) No 3 pp 393-410
Tschach Ingo Theorie der Entwicklungsfinanzierung Mit Kleinkreditprogrammen Kredit- und Arbeitsmarktsegmentierung uumlberwinden Frankfurt 2000
UNDP Human Development Report 2004 New York 2004
71
UNFPA state of the world population 2004 New York 2004
UNICEF The State of the Worldrsquos Children 2002 NewYork Geneva 2002
Varley Robert C G Financial Services and Environmental Health Household Credit for Water and Sanitation Environmental Health Project Applied Study No 2 Washington DC 1995
Volkery Carsten Kampf um Straszligenhaumlndler in Die Zeit Nr 23 published May 27th
2004 p 33
Wardhana Ali Introduction in The Microfinance Revolution ndash Sustainable Finance for the Poor Washington DC 2001 pp XVII-XXVII
Woodworth Warner Woller Gary Greetings from the Editors Journal of Microfinance Vol 1 (1999) No 1 p 6
The World Bank Group World Development Indicators 2004 Washington DC 2004
Worldwatch Institute (2002) Vital Signs 2002 New York London 2002
Wimmer Nancy Barua Dipal Less is more Microfinance for solar energy in rural areas in Renewable Energy World Review Issue 2004-2005 Vol 7 (2004) No4 pp 170-179
Yunus Muhammad Grameen Bank II ndash Designed to Open new Possibilities Dhaka 2002
Yunus Muhammad Grameen ndash Eine Bank fuumlr die Armen dieser Welt Muumlnchen 1998a
Internet References
Abishek Lal (nd) An Overview of Microfinance and Environmental Management [http wwwgdrcorgicmenvironabhishekhtml] (availability date October 5 2004)
ACCION (nd) our history [httpwwwaccionorgabout_our_historyasp] (availability date October 5 2004)
ACCION (nd) key statistics [httpwwwaccionorgabout_key_statsasp] (availability date October 5 2004)
Ahmad Zulfiqar (nd) Forms of Regional Cooperation in Microfinance in South Asia [httpwwwbwtporgarcmpakistanIV_News_and_EventsBWTPworkshopZulfiqar20Ahmad20paper20(BWTP-PMN2029Jan04)pdf (availability date October 6 2004)
72
Ahmed Salehuddin (2003) Foreword [httpwwwpksf-bdorgaprm_summit_brochure htm] (availability date September 30 2004)
Annan Kofi (2002) Statement at The Microcredit Summit +5 [httpwww microcreditsummitorgenews2003-03_sp_chowdhuryhtml) (availability date October 5 2004)
Barnes Carolyn (2001) Microfinance Program Clients and Impact An Assessment of Zambuko Trust Zimbabwe [httpwwwmicrofinancegatewayorgfiles18553_Barnes_Zambuko_Trust_2001pdf] (availability date October 5 2004)
Barnes Carolyn Gaile Gary Kibombo Richard (2001) The Impact of Three Microfinance Programs in Uganda [httpwwwmicrofinancegatewayorgfiles2935_Barnes_2001pdf] (availability date October 5 2004)
Barua Dipal (2004) Success of Grameen Shakti in the Field of Renewable Energy Sector in Bangladesh [httpwwwrenewables2004depptPresentation1-SessionVA(14-1530h)-Baruapdf] (availability date September 30 2004)
Bhatt Ela (1997) In 1975 [httpwwwmicrocreditsummitorgdeclarationhtm] (availability date September 30 2004)
BlueOrchard (2004a) Microfinance [httpwwwblueorchardchenmicrofinance_institutions asp] (availability date October 5 2004)
BlueOrchard (2004b) January 2004 Newsletter [httpwwwblueorchardchmedialibrarywebsitenewsletter_jan_2004pdf] (availability date October 5 2004)
Brynjolfsson John (2004) John Brynjolfsson Discusses Recent Trends in TIPS Issuance [httpwwwpimcocomLeftNavPIMCO+Spotlight2004Spotlight_2_04htm] (availability date October 5 2004)
CGAP (2003) Report to the Board of Executive Directors [httpwww-wdsworldbankorgservletWDSContentServerWDSPIB20031208000012009_20031208101736RenderedPDF27441pdf] (availability date October 5 2004)
Chen Shaohua Ravallion Martin (2004) How have the worldrsquos poorest fared since the early 1980s [httpwwwworldbankorgresearchpovmonitorMartinPapersHow_have_the_poorest_fared_since_the_early_1980spdf] (availability date October 5 2004)
Cheston Susy Kuhn Lisa (2002) Empowering Women through Microfinance[httpwwwmicrofinancegatewayorgfiles3240_Cheston_2002doc] (availability date October 5 2004)
Christen Robert P et al (1995) Maximizing the Outreach of Microenterprise FinanceAn Analysis of Successful Microfinance Programs [httpwwwdecorgpdf_docsPNABS519 pdf] (availability date October 5 2004)
73
CIA (2004) The World Factbook [httpwwwciagovciapublicationsfactbook] (availability date October 5 2004)
Clear Profit (2004) Microfinance Bond Record May Double [httpwwwclear-profitcomissuescpsep04txt] (availability date September 30 2004)
Daley-Harris Sam (2003) State of the Microcredit Summit Campaign Report 2003 [httpwwwmicrocreditsummitorgpubsreportssocr2003SOCR03-E[txt]pdf] (availability date September 30 2004)
Dominiceacute Robert (2004) Interview in Microfinance Bond Record May Double [httpwwwclear-profitcomissuescpsep04txt] (availability date September 30 2004)
Donahue Jill Kabbucho Kamau Osinde Sylvia (2001) HIVAIDSmdashResponding To A Silent Economic Crisis Among Microfinance Clients In Kenya and Uganda [httpwwwmicrosave-africacomget_fileaspdownload_id=541] (availability date September 30 2004)
Donahue Jill Sussman Linda (1999) Building a Multi-Sectoral Response Follow-Up Assessment of Programming for Children and Families Affected by HIVAids in Kenya [httpwwwdecorgpdf_docspnacg778pdf] (availability date September 30 2004)
The Economist (1998) [httpwwweconomistcomdisplaystorycfmstory_id=S2629H3C28Q13F240A] (availability date September 30 2004)
Finca (nd) Introduction [httpvillagebankingorgwhereindexphp3] (availability date September 30 2004)
Fischer Stanley (2003) Statement at The Asia Society and Womens World BankingAnnual Microfinance Conference [httpwwwiiecomfischerpdffischer051303pdf] (availability date September 30 2004)
Friedman Milton (nd) Samuha [httpwwwsamuhaorgm-1htm] availability date September 30 2004)
FXTOP (2004) Historical Exchange Rates [httpfxtopcomdehistoratesphp3] (availability date September 30 2004)
Gibbons David Meehan Jennifer W (2002) Financing Microfinance for Poverty Reduction [httpwwwmicrocreditsummitorgpapersfinancing_finalpdf] (availability date September 30 2004)
Grameen Bank (2004) Grameen Bank At a Glance [httpwwwgrameen-infoorgbankcdshtml] (availability date September 30 2004)
Grameen Trust (nd) Grameen Bank Replication Program [httpwwwgrameen-infoorggrameengtrustreplicationhtml8721] (availability date September 30 2004)
74
Hossain Farhad (2004) Microfinance in Development [httpwwwvalthelsinkifi staff jkoponenb1104FarhadFeb2304pdf] (availability date October 5 2004)
IMF (2004) Data [httpwwwimforgexternalpubsftweo200402datadbginimcfm] (availability date October 5 2004)
IMI (2004) Investments [httpwwwimi-agcomoverviewindexhtml] (availability date September 30 2004)
IPCC (2001) Summary for Policymakers [httpwwwipccchpubspm22-01pdf] (availability date September 30 2004)
Jansson Tor Wenner Mark (1997) Financial Regulation and its Significance for Microfinance in Latin America and the Caribbean [httpwwwgdrcorgicmgoverniadb-janssonpdf] (availability date October 5 2004)
Ken Daniel Ten Roeun Van (2004) The Cycle of Debt - As Microcredit Institutions Grow Some Question Their Effect on Poverty [httpwwwcamnetcomkhcambodiadaily selected_featurescd-21-02-04htm] (availability date September 30 2004)
Kim Julia (2002) Social Interventions for HIVAIDS - Intervention with Microfinance for AIDS and Gender Equity [httpwwwwitsaczaradarPDF20filesIntervention_monograph_no_picspdfpdf] (availability date September 30 2004)
Llanto Gilberto (nd) Vietnam [httpwwwadborgDocumentsBooksCentral_Banks_MicrofinanceCountry_Studiesvietnampdf] (availability date September 30 2004)
The Microfinance Gateway (nd) Frequently Asked Questions [httpwwwmicrofinance gatewayorgsectionfaq1] (availability date October 5 2004)
Microfinance Rating and Assessment Fund (2004) Qualified Raters [httpwwwmfrating orgmfi_institutionsqualified_ratershtml] (availability date October 5 2004)
Microcredit Summit (1997) Declaration and Plan of Action [httpwwwmicrocreditsummit orgdeclarationhtm] (availability date September 30 2004)
MicroRate (nd) Performance Indicators and Ratios [httpwwwmicroratecomENGLISHsiteRATINGSindicatorshtml] (availability date September 30 2004)
MicroRate (2002) The Finance of Microfinance [httpwwwmicroratecomPDFFinance20of20Microfinancepdf] (availability date September 30 2004)
MicroRate (2004) Adjusted comparison table [httpwwwmicroratecomENGLISHsitePDFAdjusted20Comparison20Table060320engpdf] (availability date October 5 2004)
75
Mix Market (2004) The Mix Market [httpwwwmixmarketorg] (availability date October 5 2004)
Morduch Jonathan (1999b) The Grameen Bank A Financial Reckoning [httpwwwwwsprincetonedu~rpdsmacarthurdownloadsmorduch_grameen_bankpdf] (availability date September 30 2004)
Pallen Dean (1997) Environmental Sourcebook for Micro-Finance Institutions [httpwwwacdi-idagccaINETIMAGESNSFvLUImagesea20summaries$fileSOURC Epdf] (availability date September 30 2004)
Prisma (2002) The Case for Private Capital Market Creation in the Development Field of Microfinance [httpwwwsocialenterprisenetpdfsprivate_capital_marketpdf] (availability date September 30 2004)
Schmidt Reinhard H Zeitinger C-P (1997) Critical Issues in Microbusiness Finance and the Role of Donors No 6 [httpwwwgdrcorgicmmfi-donorpdf] (availability date September 30 2004)
Seibel Hans D (2003b) Commodity finance a commercial proposition Micro- and Mesofinance for Agricultural Commodity Production Processing and Trade [httpwwwuni-koelndeew-fakaef05-20042003-420Commodity20Financepdf] (availability date September 30 2004)
Simanowitz Anton Walter Alice (2002) Ensuring Impact Reaching the Poorest while Building Financially Self-sufficient Institutions and Showing Improvement in the Lives of the Poorest Families [httpwwwidsacukimpactPublicationsWorkingPapersOP3MCSSumdoc] (availability date September 30 2004)
Smith Stephen C Jain Sanjay (1999) Village Banking and Maternal and Child Health Theory and Evidence from Ecuador and Honduras[httphomegwuedu~scsmith healthrevwd801pdf] (availability date September 30 2004)
United Nations (1999) International Year of Microcredit 2005 [httpods-dds-nyunorgdoc UNDOCGENN9976933PDFN9976933 pdfOpenElement] (availability date October 5 2004)
United Nations (2000) United Nations Millennium Declaration [httpods-dds-nyunorgdocUNDOCGENN0055951PDFN0055951pdfOpenElement] (availability date October 5 2004)
US Census Bureau (2004) Total Midyear Population for the World 1950-2050 [httpwwwcensusgovipcwwwworldpophtml] (availability date October 5 2004)
WHO (2004) Making pregnancy safer [httpwwwwhointmediacentrefactsheets fs276en] (availability date September 30 2004)
WHO (2001) Child Health [httpwwwwhointmipfiles2082AAGChildHealthpdf] (availability date September 30 2004)
76
The World Bank Group (nd) Health Nutrition and Population and the Millennium Development Goals [www1worldbankorghnpMDGMDG20-20HNPbookletpdf] (availability date September 30 2004)
Yunus Muhammad (1998) Championing the Right to Credit for Poor Women Around the World [httpaspgrameencom dialoguedialogue34interviewhtml] (availability date September 30 2004)
UNAIDS (2004) [httpwwwunaidsorgbangkok2004GAR2004_pdfUNAIDSGlobalReport2004_enpdf] (availability date September 30 2004)
Ratings
M-Cril (2000) SPANDANA [httpwwwratingfundorgspanishdocsSPANDANA_RatingReportpdf] (availability date October 7 2004)
M-Cril (2001a) BASIX [httpwwwbasixindiacomMcrilasp] (availability date October 7 2004)
M-Cril (2001b) BDB [httpwwwratingfundorgspanishdocsRF_BDBpdf] (availability date October 7 2004)
M-Cril (2001c) SNEHA [httpwwwratingfundorgspanishdocsRF_Sneha-u1pdf] (availability date October 7 2004)
M-Cril (2002a) KCLF [httpwwwratingfundorgdocsRF-KCLF-risk20reportdoc] (availability date October 7 2004)
M-Cril (2002b) NWTF [httpwwwratingfundorgspanishdocsRF_NWTFpdf] (availability date October 7 2004)
M-Cril (2002c) SEEDS [httpwwwratingfundorgspanishdocsRF_SEEDS_2002_Ratingpdf] (availability date October 7 2004)
M-Cril (2002c) Share [httpwwwratingfundorgspanishdocsRF_SHAREpdf] (availability date October 7 2004)
M-Cril (2002d) TSKI [httpwwwratingfundorgspanishdocsRF_Tski_mcrilfinal(-) reportpdf] (availability date October 7 2004)
M-Cril (2003a) ASA [httpwwwratingfundorgdocsASA20updatepdf] (availability date October 7 2004)
M-Cril (2003b) BURO [httpwwwm-crilcomburopdf] (availability date October 7 2004)
M-Cril (2003c) EMT [httpwwwratingfundorgdocsEMTpdf] (availability date October 7 2004)
77
M-Cril (2003d) SKS [httpwwwmixmarketorgendemanddemandshowprofileaspett=25ampshowinfo=adjusted] (availability date October 7 2004)
M-Cril (2003d) TPC [httpwwwratingfundorgdocsTPC_Finalpdf] (availability date October 7 2004)
M-Cril (2004b) UPAP [httpwwwratingfundorgdocsUPAP_2004pdf] (availability date October 7 2004)
Microfinanza (2002a) ACME [httpwwwratingfundorgspanishdocsACME_finalpdf] (availability date October 7 2004)
Microfinanza (2002b) BTFF [httpwwwratingfundorgspanishdocsBTFF_RatingReportpdf] (availability date October 7 2004)
Microfinanza (2002c) BESA [httpwwwratingfundorgspanishdocsBESA_RatingReportpdf] (availability date October 7 2004)
Microfinanza (2002d) CAME [httpwwwratingfundorgdocsEvaluacionCAME(-) Finaldoc] (availability date October 7 2004)
Microfinanza (2002e) RFF [httpwwwratingfundorgdocsRFF20finalpdf] (availability date October 7 2004)
Microfinanza (2002f) PSHM [httpwwwratingfundorgspanishdocsPSHM_Reportpdf] (availability date October 7 2004)
Microfinanza (2003) CAJCA [httpwwwratingfundorgdocsCalificacion_Jardin_Azuayo_ratingpdf] (availability date October 7 2004)
Microserve (2003) ENDA [httpwwwmixmarketorgendemanddemandshowprofileaspett=865ampshowinfo=adjusted] (availability date October 7 2004)
Planet Rating (2002a) FONDEP [httpwwwmfratingorgRatingscompleted_ratingshtml] (availability date October 7 2004)
Planet Rating (2002b) PRIZMA [httpwwwmixmarketorgendemanddemandshowprofileaspett=111ampshowinfo=adjusted] (availability date October 7 2004)
Planet Rating (2002c) SWS [httpwwwratingfundorgspanishdocsSWC_reportpdf] (availability date October 7 2004)
Planet Rating (2002d) ZAKOURA [httpwwwratingfundorgspanishdocsRF_Zakourapdf] (availability date October 7 2004)
Planet Rating (2003a) AMSSF [httpwwwratingfundorgdocsPlanetRating_AMSSF_010803pdf] (availability date October 7 2004)
Planet Rating (2003b) FOCCAS [httpwwwratingfundorgdocsPlanetRatingFOCCAS120803pdf] (availability date October 7 2004)
78
Planet Rating (2003c) PADME [httpwwwmfratingorgdocsPlaNetRatingPADME070302_Englishpdf] (availability date October 7 2004)
Planet Rating (2003d) PAPME [httpwwwmfratingorgdocsPAPME_PlanetRating080903pdf] (availability date October 7 2004)
Planet Rating (2003e) VITAL FINANCE [httpwwwmfratingorgdocsVital20Finance_Sept202003pdf] (availability date October 7 2004)
Planet Rating (2004a) ABA [httpwwwratingfundorgdocsABA_April202004pdf] (availability date October 7 2004)
Planet Rating (2004b) ACEP [httpwwwmfratingorgdocsACEPSeacuteneacutegal_2004pdf] (availability date October 7 2004)
Planet Rating (2004c) AGROINVEST [httpwwwratingfundorgdocsAgroInvest_June202004pdf] (availability date October 7 2004)
Planet Rating (2004d) ASBA [httpwwwratingfundorgdocsASBA_April202004pdf] (availability date October 7 2004)
Planet Rating (2004e) DBACD [httpwwwratingfundorgdocsDBACD_April202004pdf] (availability date October 7 2004)
Planet Rating (2004f) FINADEV [httpwwwmfratingorgdocsFinadev_2004pdf] (availability date October 7 2004)
Planet Rating (2004g) MI-BOSPO [httpwwwratingfundorgdocsMIBOSPO_160404pdf] (availability date October 7 2004)
Planet Rating (2004h) SBACD [httpwwwratingfundorgdocsSBACD_PlanetRating300604pdf] (availability date October 7 2004)
Other Sources
Interview Shaw Newaz Deputy General Manager of the Grameen Bank October 30th
2003
Hodson Charles (2001) Your Business Your World Jim Boulden CNN (ed) Dhaka 2001
2
72 Examining the Sample47
8 Conclusions 52
Appendix 54Appendix 1 Average loan balance54
Appendix 2 Portfolio at Risk 56
Appendix 3 Transaction Costs 58
Appendix 4 Portfolio Growth 60
Appendix 5 Portfolio vs Equity 60
Appendix 6 Internal Rate of Return 61
Appendix 7 Subsidized Interest Rates and the Net Gains to Society62
Appendix 8 Interest Rate vs Loan Size vs FSS vs PAR 63
Appendix 9 Inflation vs GDP per Capita 65
References 67
Internet References 71
Ratings 76
Other Sources 78
3
Figures
Figure 1 Expected Bank Return and the Interest Rate 32
Figure 2 The extended Model 34
Figure 3 Marginal Productivity of Capital 36
Figure 4 The extended Model 39
Figure 5 Loan Size vs Interest Rate 48
Figure 6 Interest Rate vs PAR 49
Figure 7 Interest Rate vs FSS 50
4
Acronyms
BDB Bank Dagan Bali
BRAC Bangladesh Rural Advancement Committee
BRI Bank Rakyat Indonesia
CF Cost of Funds
CGAP Consultative Group to Assist the Poor(est)
FSS Financial Self-Sufficiency
GDP Gross Domestic Product
GNP Gross National Product
I Interest Rate
IADB Inter-American Development Bank
II Investment Income
IMI Internationale Mikro Investitionen Aktiengesellschaft
IPCC Intergovernmental Panel on Climate Change
K Capitalization Rate
LL Loan Loss
MBB MikroBanking Bulletin
MDG Millennium Development Goal
MFI Microfinance Institution
NGO Non Governmental Organization
NGS Net Gains to Society
PAR Portfolio at Risk
TA Transaction Costs
UN United Nations
USA United States of America
5
1 Introduction
The poor stay poor not because they are lazy but because they have no access to
capital1 If this claim made by nobel laureate Milton Friedman actually holds will be
discussed in the initial part of this paper
First a short overview of the development of the microfinance sector will be given
showing that the concept of providing financial services to low income people is much
older than still believed by many development practitioners and bankers around the
world This is important since it underlines the contribution that microfinance
institutions (MFIs) can make to the development of the financial sector in their
respective countries Subsequently the various ways how such services can assist low
income people will be discussed demonstrating that even the poorest can benefit from
the provision of small loans This is a view that is still questioned in the academia
In the second part of this paper it will be shown that although some 10000
organizations are involved in microfinance already2 they are not even close to meet the
tremendous demand for low scale financial services This sector is still widely neglected
by for profit investors and traditional bankers After examining why these groups
continue to avoid investments in the microfinance industry it will be checked if the
assumptions that underline their arguments actually hold The possibility if MFIs could
raise their interest rates to an extend that would allow them generate profits sufficiently
high to attract for profit investors will be discussed
According to Hulme and Mosley MFIs ldquocan either go for growth and put their resources
into underpinning the success of established and rapidly growing institutions or go for
poverty impact and put their resources into poverty-focused operations with a higher
risk of failure and a lower expected returnrdquo3 If this is true will be examined in the third
part by checking if poor borrowers are able to bear interest rates significantly above
1 See Friedman (nd)2 See BlueOrchard (2004a)3 See Hulme and Mosley (1996) p 206
6
those charged by conventional banks Finally a sample of 39 MFIs will be used to verify
the drawn conclusions by examining the effects their interest rates have on their
financial performances and their repayment record
7
2 The Development of Microfinance
21 What is Microfinance
According to the Journal of Microfinance the term defines what ldquois arguably the most
innovative strategy to address the problems of global povertyldquo4 This view is shared by
the United Nations (UN) which declared that the year 2005 would be the international
year of microcredit5 while their General Secretary Kofi Annan stated in 2002 that
ldquo[m]icrocredit is a critical anti-poverty tool and a wise investment in human capitalrdquo6
Hossain describes microfinance as ldquothe practice of offering small collateral free loans
to members of cooperatives who otherwise would not have access to the capital
necessary to begin a small business or other income generating activitiesrdquo7 This view is
to narrow since it not only excludes such services as saving accounts and insurances8
but also ignores the possibility of collateral demanding MFIs Although it is true that
many MFIs do not take collateral especially if they are focusing on the poorest which
normally do not possess any collateral9 several MFIs in fact do require some form of
collateral10
Roth and Steinwand give a more general definition They describe microfinance as ldquothe
provision of a wide range of financial services like saving accounts loans payment
services and insurances for people with no regular access to financial services through
traditional financial institutionsrdquo11 Here it is important not to confuse the terms
traditional or conventional with the term formal If for example an illiterate beggar
takes a $10 loan from the Grameen Bank in Bangladesh she becomes a client of a
4 See Woodworth and Woller (1999) p 65 See United Nations (1999) p 16 Annan (2002)7 Hossain (2004)8 See The Microfinance Gateway (nd) Robinson (2001) p9 Otero (1999) p 89 See chapter 3 for a more detailed discussion on poverty10 See Robinson 2002 p 24311 See Roth and Steinwand (2004) p 2 ldquodie Bereitstellung einer breiten Palette von Finanzdiensteistungen wie Spareinlagen Kredite Zahlungsverkehr und Versicherungsleistungen fuumlr Wirtschaftsakteure die keinen regelmaumlszligigen Zugang zu Finanzdienstleistungen durch klassische Finanzinstitutionen habenldquo
8
formal financial institution (a registered bank) but obviously not of a traditional or
conventional one12
Although the other services have become more important in recent years microcredit is
still considered their central service by most MFIs In many countries it refers to loans
below $ 100013 however for significant cross country comparison it is more
meaningful to look at the ratio of the loan amount to the gross national product (GNP)
or gross domestic product (GDP) per capita for the respective countries While a loan of
$1000 is more than four times larger than the GNP per capita in Uganda it represents
less than 20 of the GNP per capita in Mexico The MicroBanking Bulletin (MBB) has
categorized the target market for MFIs by the average outstanding loan amount as a
percentage of the GNP per capita ranging from Low-end (less than 20) to Small
Business (more than 250)14 Especially for the latter category one must to look closely
at the condition of the financial service market where an institution is active Although
MFIs exist in industrialized countries15 one would definitely turn to a traditional
financial institution for a loan bigger than 250 of the GNP per capita and therefore not
to a MFI according to the definition presented above
22 The Origin of Microfinance
Although neither of the terms microcredit or microfinance were used in the academic
literature nor by development aid practitioners before the 1980s or 1990s16
respectively the concept of providing financial services to low income people is much
older
While the emergence of informal financial institutions in Nigeria dates back to the 15th
century17 they were first established in Europe during the 18th century as a response to
the enormous increase in poverty since the end of the extended European wars (1618 ndash
12 See Yunus (2002) p 19 for a more detailed description of the destitute member program of the Grameen Bank which focuses exclusively on persons with no regular income and no assets at all 13 See MicroBanking Bulletin (1997) p 614 See MicroBanking Bulletin (2003) p 5415 See Yunus (1998a) pp 229 et sqq16 See Robinson (2001) p XXX17 See Seibel (2003a) p 12
9
1648)18 In 1720 the first loan fund targeting poor people was founded in Ireland by the
author Jonathan Swift19 After a special law was passed in 1823 which allowed charity
institutions to become formal financial intermediaries a loan fund board was established
in 1836 and a big boom was initiated Their outreach peaked just before the government
introduced a cap on interest rates in 1843 At this time they provided financial services
to almost 20 of Irish households20
The credit cooperatives21 created in Germany in 1847 by Friedrich Wilhelm Raiffeisen
served 14 million people by 191022 He stated that the main objectives of these
cooperatives ldquoshould be to control the use made of money for economic improvements
and to improve the moral and physical values of people and also their will to act by
themselvesrdquo23
In the 1880s the British controlled government of Madras in South India tried to use the
German experience to address poverty which resulted in more than nine million poor
Indians belonging to credit cooperatives by 194624 During this same time the Dutch
colonial administrators constructed a cooperative rural banking system in Indonesia
based on the Raiffeisen model25 which eventually became Bank Rakyat Indonesia
(BRI) now known as the largest MFI in the world26
23 Microfinance after the Second World War
Because of further prudential regulation and effective supervision eg through bank
superintendencies the banking sector in the now developed world experienced
continuous growth Today the vast majority of the citizens of the industrialized
countries have access to financial services with many of them being customers of
former MFIs27
18 See Steinwand (2001) p 5119 See Robinson (2002) p 9620 See Seibel (2003a) p 1021 first known as Darlehnsvereine and now called Raiffeisenbanken22 See Morduch (1999a) p 157323 Raiffeisen (1966) quoted in Richardson (2000) p 324 See Morduch (1999a) p 157425 See Robinson (2002) p 9726 See Roth Steinwand (2004) p 327 See Seibel (2003a) p 11
10
This is not true for most developing countries where market penetration of financial
institutions is far from reaching the majority of the inhabitants (see chapter 4) A variety
of reasons is responsible for this including that the banking sector in the most
developing countries have developed in a very different way to than those in
industrialized countries
One of the most important reasons is that in contrast to the industrialized countries little
attention has been paid to the legal recognition prudential regulation and effective
supervision of informal financial institutions28 This insecure legal environment leads to
several problems Since the regulatory framework for mobilizing savings often does not
fit the needs of institutions targeting low income people many organizations are not
permitted to do so and are therefore missing funds to on-lend as credit29 An additional
problem is the lack of a deposit insurances This not only increases the risk of a bank
run but also keeps people from depositing their savings in a financial institution30 In
addition inappropriate interest rate ceilings prevail in many countries While politics
claim they are lowering the interest rates charged to the poor they de facto only limit
their access to financial services (see chapter 5)31
Another problem that retarded the growth of the financial sector in developing countries
was the supply-leading finance theory which dominated the development strategies of
many countries after the second world war32 This theory ldquo refers to the provision of
loans in advance of the demand for credit for the purpose of inducing economic
growthrdquo33 Since it was believed that poor people were neither able to save (and thus
dependent on outside funding) nor capable of paying commercial rates of interest
massive subsidized credit programs were established34 The results were alarming
Repayment rates often did not exceed 50 percent and some government financed
programs even had default rates of more than 90 percent35 The main reason being that
credit was not provided according to business management principles but instead
28 See Seibel (1998) p 829 See Robinson (2001) p 4930 See Staschen (1999) p 1431 See Gibbons (2000) p 1532 See Morduch (1999a) p 157033 Robinson (2001) p 14034 See Borst (2004) pp 33 et sqq35 See Yunus (1998a) p 154 Robinson (2001) p 145
11
according to political objectives Therefore receiving loans was seen as a reward for the
constituents rather than as a business transaction Most of the funds earmarked for the
poor also never reached them ending up instead in the hands of the local elites
Attracted by the below market interest rates and the possibility not to pay back at all
these groups lobbied to be treated privileged and often used the money received for
consumption or for on-lending at higher rates36 But subsidized credit not only
encouraged corruption it also discouraged sustainable financial institutions since they
could not compete with interest rates that were not aimed to cover all costs and were
sometimes even lower than the interest paid on savings37 The low or negative spread
also worked as a negative incentive to institutionsrsquo effort to mobilize savings which in
turn intensified the problem of credit rationing (see chapter 5)
24 Microfinance Today
In the 1970s a paradigm shift started to take place The failure of subsidized government
or donor driven institutions to meet the demand for financial services in developing
countries let to several new approaches Some of the most prominent ones are presented
below
Bank Dagan Bali (BDB) was established in September 1970 to serve low income people
in Indonesia without any subsidies and is now ldquowell-known as the earliest bank to
institute commercial microfinancerdquo38 While this is not true with regard to the
achievements made in Europe during the 19th century it still can be seen as a turning
point with an ever increasing impact on the view of politicians and development aid
practitioners throughout the world In 1973 ACCION International a United States of
America (USA) based non governmental organization (NGO) disbursed its first loan in
Brazil39 and in 1974 Professor Muhammad Yunus started what later became known as
the Grameen Bank by lending a total of $27 to 42 people in Bangladesh40 One year
later the Self-Employed Womenrsquos Association started to provide loans of about $15 to
36 See Robinson (2001) pp 144 et sqq37 Before BRI underwent a major transformation in 1983 a negative spread between interest rates on loans and savings existed While the bank lent at a 12 annual effective interest rate it paid 15 on savingsSee Robinson (2001) p 10638 Wardhana (2001) p XXVII39 See ACCION (nd)40 See Yunus (1998a) p 16 et sqq
12
poor women in India41 Although the latter examples still were subsidized projects they
used a more business oriented approach and showed the world that poor people can be
good credit risks with repayment rates exceeding 9542 even if the interest rate charged
is higher than that of traditional banks Another milestone was the transformation of
BRI starting in 1984 Once a loss making institution channeling government subsidized
credits to inhabitants of rural Indonesia it is now the largest MFI in the world being
profitable even during the Asian financial crisis of 1997 ndash 199843
In February 1997 more than 2900 policymakers microfinance practitioners and
representatives of various educational institutions and donor agencies from 137
different countries gathered in Washington DC for the first Micro Credit Summit This
was the start of a nine year long campaign to reach 100 million of the world poorest
households with credit for self employment by 200544 According to the Microcredit
Summit Campaign Report 67606080 clients have been reached through 2527 MFIs by
the end of 2002 with 41594778 of them being amongst the poorest before they took
their first loan45 Since the campaign started the average annual growth rate in reaching
clients has been almost 40 percent46 If it has continued at that speed more than 100
million people will have access to microcredit by now and by the end of 2005 the goal
of the microcredit summit campaign would be reached As the president of the World
Bank James Wolfensohn has pointed out providing financial services to 100 million of
the poorest households means helping as many as 500 ndash 600 million poor people47
41 See Bhatt (1997)42 See Yunus (1998a) p 143 et sqq43 See Robinson (2002) p 38044 See Daley-Harris (2003) p 345 ldquoThe Microcredit Summit Campaign defines ldquopoorestrdquo as those who are in the bottom half of those living below their nationrsquos poverty line or are living on less than $1 a day adjusted for purchasing power parity (PPP)rdquo See Daley-Harris (2003) p 3 This definition will also be used throughout this paper46 See Daley-Harris (2003) p 1847 See Morduch (1999a) p 1570
13
3 The Impact of Microcredit
31 Microcredit and the Millennium Development Goals
In 1996 Ismail Serageldin the then chair of the Consultative Group to Assist the Poorest
(CGAP)48 claimed that ldquo[m]icrofinance is a proven instrument to assist the very poorrdquo49
This view is also shared by the World Watch Institute50 and underlines what has been
stated above namely that microfinance can be used as a strong anti-poverty tool But
does microfinance actually meet these expectations and keep this promise51
The impact that microcredit has on the lives of poor people will be demonstrated by
showing how it contributes to each of the eight Millennium Development Goals
(MDGs)52 which are related to the reduction of poverty in all its forms These goals
were resolved in September 2000 by the General Assembly of the UN in their
Millennium Declaration53
32 The Eradication of extreme Poverty and Hunger
The aim of the first MDG is to halve the proportion of people who live on less than $1 a
day between 1990 and 2015 According to current population projections of the World
Bank54 this would equal 849 million people in 201555
48 The Consultative Group to Assist the Poorest is a consortium of 28 public and private development agencies working together to expand access to financial services for the poor in developing countries and was established by the World Bank in 1995 Recently it changed its name to Consultative Group to Assist the Poor49 See Serageldin (1996) p 1150 See Gardner (2002) p 1851 See Morduch (1999a) pp 1569 et sqq52 The Millennium Development Goals are (1) eradicate extreme poverty and hunger (2) achieve universal primary education (3) promote gender equality and empower women (4) reduce child mortality (5) improve maternal health (6) combat HIVAIDS malaria and other diseases (7) ensure environmental sustainability and (8) develop a global partnership for development53 See United Nations (2000)54 See World Bank (2004) p 38 et sqq55 Although it is not explicitly mentioned in the Millennium Declaration it is commonly assumed that the share of people living on less than $1 in low and middle income countries should be halved If the share would be calculated with regard to the worldrsquos total population the goal for 2015 would 818 million people For the worldrsquos total population in 1990 see US Census Bureau (2004)
14
Today almost 11 billion people live on less than $1 and more than 27 Billion live on
less than $2 per day56 The mean income for those living under $1 a day is $077 and it
is $125 for those living under $2 a day57 While the number of people living on less
than $1 per day is slowly decreasing and is expected to be 913 million in 2015 the
number of people living on less than $2 a day is actually increasing58 One of the
outcomes from this degree of poverty is that more than 27000 children die every day
from mostly preventable diseases many of them related to hunger59
Microcredit enables poor people to start new businesses or to diversify existing ones
which helps them to increase their income In addition to large amounts of anecdotal
evidence several studies have documented the positive economic impact microcredit
has on its clients Cloud and Panjaitan-Drioadisuryo have found that the average income
of a sample of BRI borrowers has increased by 112 percent and that 90 percent of their
families have crossed the poverty line60 Only 12 out of the 121 respondents of that
study reported that their income had not increased61 According to the Grameen Bank
website 5109 percent of their clients have crossed the poverty line since they took their
first loan62
A study conducted by Barnes showed that the program of the Zambuko Trust a local
MFI in Zambia had a considerable impact on the poorest clients consumption of meat
fish and chicken63 While 76 percent of the continuing clients of the MFI called Share in
India significantly increased their income and 50 percent have crossed the poverty line 64 Khandker discovered in his well known study ldquoFighting poverty with microcreditrdquo
that there is a connection between the microcredit programs of three Bangladeshi MFIs
and household per capita expenditure For every dollar borrowed by a Grameen Bank
member household consumption increases by $018 In addition he found that 5 percent
56 See Chen and Ravallion (2004) p 2957 In fact those people live on less than $108 and $215 respectively a day in 1993 PPP This means that the nominal dollar value of their income is considerably lower See Chen and Ravallion (2004) p 9 58Both numbers are decreasing in Asia but increasing in the rest of the world See Chen and Ravallion (2004) p 22 et sqq59 See UNICEF (2002) p 660 A consistent definition of the term ldquopoverty linerdquo does not exists among different nations Therefore the term will be used according to the definition of the respective country in this paper61 See Panjaitan-Drioadisuryo and Cloud (1999) p 77562 See Grameen Bank (2004) 63 See Barnes (2001) p 8664 See Simanowitz and Walter (2002) p 16
15
of Grameen Bank borrowers move out of poverty every year65 Supposing Khandkerrsquos
findings were correct for all MFIs worldwide and the Microcredit Summit Campaign
achieved its goal of reaching 100 million of the poorest households with microcredit by
2005 then 25 million people (assuming an average family size of five) would leave
poverty every year66 Although this number would have to be adjusted in order take into
consideration the MFI clients who have crossed the poverty line already and of course
the experiences made in Bangladesh can not be transferred precisely to other countries
it still demonstrates the enormous effect that microcredit can have on assisting the
poorest to move out of poverty
Although a 1996 study of Hulme and Mosley states that providing microcredit can also
have a negative impact on the income of the poorest households67 these findings can
be considered as disproved by the recent bulk of evidence drawing favorable
conclusions68
33 Achievement of universal primary Education
The aim of the second MDG is to ensure that all children will be able to complete
primary school by 2015
Currently more than 100 million children most of them girls are not in school69
Besides school fees poor households often can not afford to send their children to
school because they need them to help in the family business
Microcredit programs mainly contribute to the second MDG by increasing families
income and therefore enabling parents to send their children to school Barnes Gaile
and Kibombo found that clients of an MFI in Uganda spent significantly more on
childrenrsquos education than non-clients70 and in Zambia Barnes showed that ongoing
participation in the Zambuko Trustrsquos program had a positive impact on the members
65 See Khandker (1998) p 5666 See Daley-Harris (2003) p 2467 See Hulme and Mosley (1996) p 180 et sqq 68 See Gibbons and Meehan (1998) p 13669 See UNICEF (2002) p 2270 See Barnes Gaile and Kibombo (2001) p 64
16
children staying in school71 In Bangladesh the probability of girls enrolling in school
increased by 19 percent for every 1 percent increase in Grameen Bank loans to female
clients For boys this number was even higher with the mean being 24 percent72
34 Promote gender Equality and empower Women
The aim of the third MDG is to eliminate the disparity in the ratios of girls to boys in
primary secondary and tertiary education in the ratio of literate females to males and to
increase the share of women in the labor market and in parliament73
At present the literacy rate for women is lower than for man all over the world
According to the Human Development Report 2004 the average female literacy rate as
a percentage of male literacy rate is 759 in developing countries and is as low as 37 in
Niger74 But women are not only discriminated against in education but also in access to
medical services and therefore have a higher mortality rate than man75 The worldwide
tendency for women to be underrepresented in the labor market and in the parliaments is
even more severe in developing countries76 Although several women have become
heads of state in various Asian countries (eg Bangladesh India and Indonesia) this is
probably due to them being wives or daughters of former respected male politicians
Since women have a higher repayment rate than man77 and also tend to invest increases
in income on the household and on their children rather than on themselves78 most
MFIs prefer female clients79 Therefore they empower women in many ways Often
MFIs not only encourage women to become involved in financial transactions for the
first time but also to become independent active members of the economy and to
acquire assets in their own names Cheston and Kuhn found that 68 percent of the
women participating in an MFI program in Nepal ldquohellip experienced an increase their
71 See Barnes (2001) p 8472 See Khandker (1998) p 4973 See World Bank (2001) p 2074 See UNDP (2004) pp 225 et sqq75 See Sen (2000) p 23276 See Sen (2000) pp 242 et sqq77 See Littlefield Morduch and Hashemi (2003) p 778 See Yunus (1998a) pp 116 et sqq79 According to the Microcredit Summit Campaign Report 79 or 37677080 of the poorest clients were women See Daley-Harris (2003) p 3
17
decision-making roles in the areas of family planning childrenrsquos marriage buying and
selling property and sending their daughters to school - all areas of decision making
traditionally dominated by menrdquo80 The program of the Lower Pra Rural Bank in Ghana
had an positive impact on womenrsquos participation in the community81 which is true as
well for the CRECER program in Bolivia82 In Bangladesh the Grameen Bank and the
Bangladesh Rural Advancement Committee (BRAC) the two biggest MFIs of the
country had a significant positive effect on womenrsquos empowerment measured through
eight different indicators83 After joining Grameen Bank only 21 percent of the female
members considered themselves as unemployed while this number was 50 percent
before joining84 According to the Grameen Bank website 93 percent of the Bankrsquos
shares are owned by their borrowers which elect the members of the board every three
years They also get familiar with the election process by more frequently voting for
representatives at the lower level of the organizational structure Partly because of this
experience they are more likely to run for public office In the 2003 local government
elections Grameen Bank members constituted 24 of the seats reserved for women
while they represent less than 10 of Bangladeshi adult female population85 Female
clients of MFIs from countries like the Philippines Bolivia and Nepal have reported
similar occurrences86
35 Reduce Child Mortality and improve Maternal Health
The aim of the fourth MDG is to reduce the under-five mortality rate by two-thirds
between 1990 and 2015 and the fifth MDG strives for a three quarter reduction in the
maternal mortality ratio by the same date
As has been stated above more than 10 million children are dying annually in the
developing world of mostly preventable causes with malnutrition playing a role in over
80 See Cheston and Kuhn (2002) p 1881 See MkNelly and Dunford (1998) p 5482 See MkNelly and Dunford (1999) p 7183 The eight different indicators are ldquofreedom of movement economic security ability to make small and larger independent purchases participation in important family decisions relative freedom from domination by the family political and legal awareness and participation in political campaigning and public protestsrdquo Hashemi and Schuler (1998) p 3684 See Holcombe (1995) p 5185 See Grameen Bank (2004)and CIA (2004)86 See Littlefield Morduch and Hashemi (2003) p 8
18
half of the childrsquos deaths and in over 50 countries child mortality rates are greater than
100 deaths per 1000 live births87 Maternal mortality is also a significant problem in the
developing world with more than 500000 women dying every year from pregnancy
related causes88
MFIs are mainly contributing to the these MDGs by increasing families income and
therefore enabling the households to afford better nutrition and medical services
Furthermore they are often linked with microinsurance or health education programs
In addition to what has been showed in chapter 31 Pitt Khandker and Millimet
estimate that a 10 percent increase in the loan size of a female borrower in Bangladesh
increases the arm circumference of their daughters by 6389 Smith and Jain found that
village banking in Ecuador had a positive effect on child diarrhea90 which is responsible
for 15 of child deaths91 Since Sen argues that an improved status of women within
the family reduces child mortality92 the empowerment of women through MFIs is also
contributing to this cause
Although no study has been conducted so far on the direct impact of microcredit on
maternal health it can be assumed that an overall improvement of access to medical
services reduces maternal mortality as well A study of the Morgan State University for
example suggests that microcredit has a positive effect on the prevalence of
contraceptives93 which leads to a decrease of unwanted pregnancies and therefore
reduces maternal death
36 Combat HIVAIDS Malaria and other diseases
The aim of the sixth MDG is to halt and begin to reverse by 2015 the spread of
HIVAIDS malaria and other major diseases and to assist children orphaned by HIV
87 See World Bank (2001) p 888 See WHO (2004) 89 See Pitt Khandker and Millimet (2003) p 11390 See Smith and Jain (1999) p 3791 See WHO (2001) 92 See Sen (2000) p 23593 See Amin et al (2001) p 1614
19
In 2003 29 million people died because of HIV and about 48 million became infected
the greatest number since AIDS was discovered 23 years ago94 This pandemic has lead
to a tremendous decrease in the life expectancy in the hardest hit countries Botswana
for example one of the richest and most democratic countries in Africa has a
HIVAIDS adult prevalence rate of 388 and a life expectancy at birth of less than 31
years95
Malaria not only causes more than one million deaths annually it leads also to 300 ndash
500 million clinical cases a year Both numbers have been steadily increasing over the
past two decades96 More than two million people a year are killed by tuberculosis
another global health problem This curable disease is estimated to cost poor
communities about $12 billion every year since even those who survive normally lose
more than 3 month of work time while recovering97
MFIs contribute to the sixth MDG in several ways By increasing clientrsquos income they
help households affected by HIV or other diseases to better cope with the situation
Besides spending more money on health services and nutrition MFI clients also tend to
be more able and willing to support AIDS orphans than non clients98 In addition to the
already stated increase in the use of contraceptives99 several innovative approaches to
deal with disease related crisis have also arisen This is of course necessary not only to
counteract the devastating effect the above discussed epidemics can have on MFI
clients but also to not put the viability of the respective institution at risk One option is
to integrate education services in the MFI programs and encourage clients to form
solidarity groups100 It has been shown that these services do not necessarily decrease
the effectiveness of the institutionsrsquo employees101 Another way is to strengthen the ties
to NGOs specialize in dealing with the respective disease Synergies gained through this
cooperation can help clients to better deal with the situation and in the end increase their
94 See UNAIDS (2004) p 2395 See CIA (2004)96 See World Bank (2001) p 1697 See World Bank (2001) p 1298 See Barnes (2001) p 6499 See also Kim et al (2002) p 18100 See Donahue and Sussman (1999) p A 14101 See Donahue Kabbucho and Osinde (2001) p 25
20
repayment rates Various MFIs also have introduced loan and health insurance products
or cultivated linkages with organizations doing so102
It has to be stated that despite the benefits MFIs can provide to people effected by
HIVAIDS or other diseases microcredit can also be a burden for those who are already
chronically ill These people can still benefit through loans provided to members of the
family or the community or through one of the other services mentioned above
37 Ensure environmental Sustainability
The aims of the seventh MDG are to support and promote the principles of sustainable
development and put them into action and to improve the lives of slum dwellers and
people without sustainable access to safe drinking water and sanitation
Today climate change is considered as the major environmental problem103 The
Intergovernmental Panel on Climate Change (IPCC) states that human activities
contribute to most of the 06 degC increase in global average temperature over the 20th
century and the predicted increase of another 14 to 58 degC between 1990 and 2100104
Emission of carbon from fossil fuel is reported to have the dominant influence on this
development While the total emission was 16 billion tons in 1950 it was already 65
billion tons in 2000 and is expected to continue to grow105 This development would
lead to a rise in the average sea level of between 9 and 88 centimeters during the next
century106 Furthermore it is predicted that global warming increases the risk of extreme
events like cyclones or floods leads to an increase in the number of people infected by
diseases like malaria and decreases the potential crop harvest and water availability
especially in developing countries107 In 2000 already 11 billion people lacked access to
clean drinking water and 24 billion to basic sanitation108
102 See Barnes (2001) p 40 Barnes Gaile and Kibombo (2001) p 13 and Grameen Bank (2004)103 See Gardner (2002) p 5104 See IPCC (2001) pp 2 et sqq105 Worldwatch Institute (2002) p 52 et sqq106 See IPCC (2001) p 16107 See Dunn and Flavin p 29108 See UNFPA (2004) p 18
21
MFIs contribute to achieving the seventh MDG in several ways By providing loans for
the purchase of renewable energy technologies they help people in developing
countries to increase their per capita energy consumption without increasing the carbon
dioxide emission In a 2003 survey of 140 MFIs from 80 different countries 21 said
they provide credits for solar home systems and another 19 stated they are interested in
becoming engaged in this business109 While Grameen Shakti a rural energy service
company cooperating with the Grameen Bank in Bangladesh has already installed more
than 23000 solar home systems110 a 2000 World Bank study reports twelve projects
providing solar home systems to rural households with a target of 500000
installations111 It has also been suggested that MFIs should raise environmental
awareness among their clients112 but so far no data is available on how staff can cope
with this additional task Many MFIs also provide loans for improvements in sanitation
and the water supply of their clients Varley gives several examples from Africa Asia
and Latin America on how microcredit not only has helped to invest in rainwater
collection systems but also how it has enabled households to increase their water
supply through community water associations113 In addition many MFIs provide credit
for the construction of sanitary latrines114 The situation of slum dwellers is also
positively effected by MFIs Directly through their services in poor urban communities
and indirectly by creating jobs in rural areas and therefore easing the pressure on urban
labor markets
38 Develop a global Partnership for Development
The eight MDG is about the means to achieve the other seven MDGs It calls for all
players involved in the endeavor of development and poverty eradication to work as
partners in a global context
Again MFIs are contributing to the eight MDG in many ways This is occurring through
international networks that provide funding and technical assistance through internet
information portals and specialized journals through social and for profit investors and
109 See Wimmer and Barua (2004) p 174110 Barua (2004) 111 See Martinot and Cabraal (2000) p 6112 See Pallen (1997) p 11 Lal (nd)113 See Varley (1995) pp 39 et sqq114 See Jalvaani (1999) pp 1 et sqq Varley (1995) pp 39 et sqq
22
specialized rating agencies The Bangladesh-based Grameen Trust is one of around 30
networks in operation Besides collaborating with over 200 MFIs around the world it
has directly operated three projects in Afghanistan Kosovo and Myanmar115 While the
ACCION network serves almost 12 million active clients in 19 countries throughout
America and sub-Saharan Africa116 FINCArsquos network operates in three different
continents where it serves more than 200000 customers117 In November 1997 the
MicroBanking Bulletin (MBB) was first published by the microfinance program at the
Economic Institute at the University of Colorado118 Its aim is to develop a database on
the financial performance of MFIs from all over the world which is now available
through the Mix Market an internet portal that also provides information about more
than 300 MFIs investors donor institutions and other related development
organizations119 Two years later the Marriott School at Brigham Young University
started to publish the Journal of Microfinance which has an editorial board of
microfinance experts from all over the world and offers the latest research on this
topic120 In the late 1990s a number of companies became attracted by the microfinance
market and started to invest in MFIs The German based Internationale Mikro
Investitionen Aktiengesellschaft (IMI) for example has already invested more than euro46
million in 19 MFIs in four different continents and plans to invest another euro27 million
before October 2004121 BlueOrchard Finance a microfinance investment consultancy
has channeled more than $60 million worth of private capital to some 40 MFIs
worldwide through investment funds and bond issues122 Big commercial banks like
Citigroup Deutsche Bank and ABN Amro also started to get involved in the
microfinance sector although this is mainly still perceived as a public relation activity
and not as a for-profit investment123 There are also several rating agencies specializing
in MFIs Dependent on their rating these institutions can help MFIs to receive money
from donors or investors Four of the most prominent rating agencies are PlanetFinance
115 See Grameen Trust (nd)116 See ACCION (nd)117 See FINCA (nd)118 See MicroBanking Bulletin (1997) p 5119 See The Mix (2004)120 See Woodworth and Woller (1999) p 6121 See IMI (2004)122 See BlueOrchard (2004b) p 3123 See Busch and Kort (2004) p 8 Fischer (2003) p 6
23
with headquarters in France M-Cril based in India Microfinanza in Italy and
MicroRate with offices in the USA and South Africa124
124 See Microfinance Rating and Assessment Fund (2004)
24
4 Microcredit Outreach
41 The Demand for Microcredit
Although it has been shown that microcredit is one of the most effective poverty
eradication tools that it is considered a human right by some of its advocates125 and it
can contribute considerably to the development of the financial sector in developing
countries an enormous gap still exists between supply and demand for microcredit
Estimates on the demand for microcredit vary greatly While USAID estimates the
number of potential microfinance clients is between 100 and 200 million126 the
Microcredit Summit Campaign states the total demand is more than 234 million
people127 CGAP recognizes some 500 million micro-entrepreneurs who have the
potential to become customers of MFIs128
Marguerite Robinson calculates the demand as follows ldquoAssuming five people to a
household among the 45 billion people living in low- and lower-middle-income
economies in 1999 (World Bank World Development Report 20002001) there are 900
million households in those economies If estimating conservatively we assume that
informal commercial moneylenders supply credit to 30 percent of these households at
least once a year this would mean that there are 270 million households borrowing
from informal moneylenders in a year Undoubtedly however many of these
households borrow multiple times within a yearrdquo129 Although this is a very rough
estimate assuming big differences in demand for microcredit in different countries the
number seems to be the most meaningful In contrast to the estimate of the Microcredit
Summit Campaign it does not include every single household living on less than $1 a
day but according to the definition presented in chapter 1 it counts everyone who has
no regular access to traditional financial institutions but demands such services
Obviously not all people who draw on moneylenders have financial needs that could be
matched through MFIs On the other hand interest rates charged by moneylenders tend
125 See Yunus (1998b) 126 See Christen et al (1995) p 15127 See Daley Harris (2003) p 22 128 See Robinson (2001) p 26129 See Robinson (2001) p 215
25
to be considerably higher than those of MFIs The former normally charge effective
monthly rates between ten and several hundred percent per month the latter generally
charge between 15 and five percent which enables them to attract additional clients130
42 The Supply of Microcredit
In spite of the impressive growth of MFIs around the world the demand for microcredit
is far from being met and this it is not likely to change in the near future The
Microcredit Summit Campaign reported that by the end of 2002 67606080 clients131
were reached through MFIs and that this number has increased by almost 40 percent
annually for the last five years132 It is likely that this tremendous speed of growth is at
least partly due to including MFIs which have not been reporting to the Campaign from
its start in 1997 although they have already existed at that time These institutions
contributed 22 percent to the growth in poorest clients in 2000 578 percent in 2001 and
338 percent in 2002 The growth of the poorest clients increased at least party because
of an expanded definition of the term ldquopoorestrdquo133 Since the contribution of MFIs
which previously have not been considered can be expected to decrease dramatically
the growth rate as stated by the Microcredit Summit Campaign can not be used to
predict the future development of the microfinance sector Another factor likely to slow
down the growth is the concentration of microfinance activities in some Asian countries
where almost 90 percent of the poorest microfinance clients live today134 Even if one
takes into consideration the relative size of Asiarsquos population and the fact that many
MFI customers in Latin America are relatively better off and therefore are not included
in this numbers the coverage of this part of the world far exceeds the others In
Bangladesh for example the microfinance market is close to saturation More than
eleven million households were served by several hundred MFIs in 2001135 Among
them are Grameen Bank and BRAC two of the best known MFIs in the world both
providing their services to more than three million customers With an average
household size of five it can be assumed that in Bangladesh the number of people
130 See Gibbons and Meehan (1999) pp 144 et sqq131 41594778 of them belonged to the poorest before they took their first loan The relative numbers in the following are for these poorest clients only since no other current data was available It can be assumed though that this works as a good proxy for the total number of clients 132 See Daley Harris (2003) p 3133 See Daley Harris (2003) p 17134 See Daley Harris (2003) p 21135 See Ahmed (2003)
26
benefiting from microcredit already surpasses the number of people living below the
poverty line which is estimated to be slightly higher than 50 million136 Therefore
Bangladesh will not contribute to the growth of the microfinance sector as much as it
has done in previous years This is also true for Vietnam Thailand and to a lesser
extent Indonesia Eight of the nine MFIs serving more than one million clients are based
in these countries while the ninth is based in India where due to its one billion
inhabitants the microfinance market is still far from saturation137 In contrast the
supply in Brazil meets less than two percent of the demand which is estimated to be
about 58 million potential clients138 For these reasons greater amount of future growth
must come from smaller or new MFIs in Latin America India China and especially
Africa where almost 30 percent of the worldrsquos poorest live139
43 Meeting the Demand
To fill the gap between the demand and supply for microcredit tremendous investments
are necessary to increase the loan funds of MFIs and build up their capacity through
upgrading existing institutions or building new ones Again estimates on how much
capital is needed vary greatly with the highest being at more than $300 billion140
In 1997 the Microcredit Summit Campaign estimated that $216 billion would be
needed to achieve their goal of providing microcredit to 100 million of the poorest
households This was calculated in the following way Since some 8 million people
already received microcredit in 1997 another 92 million needed to be reached
Assuming $200 ($150 for loan fund and $50 for capacity building) would be needed per
person for 88 million people in developing countries and $1000 ($500 for loan fund and
$500 for capacity building) would be needed for 4 million people in industrialized
countries the capital required ends up to be $216 billion141 For several reasons this
136 See CIA (2004)137 These institutions are The Grameen Bank BRAC Proshika and the Association for Social Advancement (ASA) in Bangladesh the Vietnam Bank for Agriculture and Rural Development (VBARD) and the Vietnam Bank for the Poor (VBA) in Vietnam BRI in Indonesia Bank for Agriculture and Agricultural Co-operatives (BAAC) in Thailand the National Bank for Agriculture and Rural Development (NABARD) in India See Ahmed (nd) p 1 Llanto (nd) p 337138 See Mezzera (2002) p 23139 See See Chen and Ravallion (2004) p 29140 See Clear Profit (2004) Prisma (2002)141 See The Microcredit Summit (1997)
27
number is not qualified to predict the total amount of capital needed to meet the demand
for microcredit On the one hand it focuses mainly on the low end of the market and
therefore underestimates the average loan fund needed On the other hand it does not
take the increasing capital demand from established MFIs into account A survey of 119
MFIs found that the average loan size to increased from $406 in 2002 to $498 in
2003142 This is mainly due to the fact that MFI clients once they have paid back their
loans usually demand larger ones for the continual development of their businesses
and therefore further increase the demand for capital of established MFIs The Grameen
Bank for example has a ceiling on its loans which increases or decreases depending on
the borrowers performance regarding repayments and savings143 While the maximum
amount for the first loan is fixed at approximately $75144 the largest loan disbursed so
far was $17195145 Thus if one estimates that by now 100 million people are borrowing
from MFIs146 another 170 million need to be reached to meet the estimated demand
Assuming an average of $600 ($400 for loan fund and $200 for capacity building) is
needed for every new client and another $200 is needed for every existing client to meet
the demand for larger loans a total of $122 billion is required This rough estimate
helps to convey the approximate amount of capital needed to meet the demand for
microcredit
So far the demand for funds is being partly met by donors which annually provide
between $500 million and $1 billion147 and through the mobilization of local savings
Obviously the amount of money provided by donors will not be able to meet the capital
demand for microcredit in the short term The mobilization of savings on the other hand
has been extremely successful in some cases with BRI probably being the most
prominent example After adapting commercial principals in October 1984 BRI was
able to raise its deposits from $161060 to more than $32 billion in 2003 which equals
almost two times its current loan portfolio148 Many other MFIs like BDB in Indonesia
142 Own calculations Without BRI the numbers would be $343 and $409 See Appendix 1143 See Grameen Bank (2003) p 13144 The accurate amount is 5000 Taka See Interview with Shaw Newaz145 Grameen Bank (2004)146 According to the data provided by the Daley Harris (2003) an annual increase in MFI clients ofapproximately 25 percent from 31122002 till the 3092004 would be needed to reach 100 million clients by now This rated is considerably below the average of the previous five years (38 percent) Therefore it can be assumed as realistic despite the growth hindering factors presented above147 See CGAP (2003) p 8148 See Robinson (2002) p 273 Mix Market (2004)
28
XacBank in Mongolia the Equity Building Society in Kenya or the Centenary Rural
Development Bank in Uganda also have managed to cover their loan portfolio fully
through internally mobilized resources149 The Grameen Bank is also expected to do so
in the first half of 2005150 In addition to raising much needed capital for on-lending the
provision of saving services can deliver notable social benefits itself151
Despite these impressive achievements even the combination of donor money and local
savings at their current levels will not be able to provide the capital needed to continue
the rapid growth of the microfinance sector Especially in their early years MFIs rely on
outside funding BRI for example needed six years before the amount of locally
mobilized savings surpassed the total amount of outstanding loans During this time
expenses and the loan portfolio were covered through a government grant worth $20
million and two World Bank loans of $5 and $97 million respectively152 It also
benefited from a network of more than 3600 branches which were established
throughout the country during the 1970s and early 80s in order to provide government
subsidized credit in rural areas153
The Grameen Bank also widely known as a best practice MFI has received about $175
million in direct and indirect subsidies between 1985 and 1996154 and continues to rely
on outside funding at below market interest rates This is made possible either through
special loans from the Bangladesh Bank or through offering bonds guaranteed by the
Bangladesh government155 - an option most MFIs do not have BDB might be one of the
very few examples which were able to finance their activities through savings and
commercial loans from the start but its outreach did not reach a large scale nor did it
serve the low end of the market In 2000 after 30 years of operation BDB provides
credit to only 10417 clients with an average loan balance of more than $5000156
approximately eight times the countries GDP per capita157
149 See Mix Market (2004)150 See Grameen Bank (2004)151 See Robinson (2001) pp 263 et sqq152 See Seibel and Schmidt (2000) p 4153 See Robinson (2002) p 180154 See Morduch (1999b) p 8155 See Morduch (1999ba) p 25 et sqq156 See Robinson (2002) p 387157 See CIA (2004)
29
Another problem keeping many MFIs from collecting savings is that they do not want
to become a regulated financial institution or do not meet the criteria in their respective
country and therefore they are simply not allowed to mobilize savings from the public
In summary the examples and numbers presented in this chapter support the argument
that the amount of capital that can be raised through donors and locally mobilized
savings is not enough for continuous rapid growth of the microfinance sector If this
lack of capital is not met through other sources the microfinance sector will fail to
contribute its full potential to the achievement of the MDGs
44 Microfinance and the Capital Markets
Regardless of whether the amount of capital needed for the development of the
microfinance sector is $20 or $300 billion it represents only a tiny fraction of the
worldwide capital markets which are estimated at $30 trillion158 Therefore if the
microfinance industry were able to tap the financial markets it would be able to grow
much faster and soon serve the millions of micro-entrepreneurs which currently can not
develop theirs businesses because of capital constrains Another advantage would be
that scarce donor money currently used for the development of the microfinance sector
could be used for other projects that do not have the potential to draw money from
commercial sources This view is shared by Michael Chu the former CEO of ACCION
who made the following statement in 1998 ldquoMicrofinance today stands at the threshold
of its next major stage the connection with the capital marketsrdquo159 Many attempts have
been made since that time Successful MFIs like BancoSol in Bolivia further
strengthened their ties to the capital markets which in some cases already provide the
majority of their funding160 Microfinance investment advisors like BlueOrchard
Finance have become middlemen for MFIs and the financial markets Nevertheless
these links are still far from reaching major scale Currently only approximately 20
percent of MFIs funding comes from commercial sources161 and the biggest bond issue
dedicated to fund MFIs totals only $40 million In addition these funds mainly end up
158 See Brynjolfsson (2004) 159 Chu (1998) quoted in Robinson (2001) p 23160 See Robinson (2001) p 69161 See Dominiceacute (2004)
30
in established institutions in Latin America or Eastern Europe162 while smaller
organizations only benefit indirectly if at all
162 See Clear Profit (2004) IMI (2004)
31
5 Credit Rationing
Until recently the predominant answer to why commercial banks or venture capital
companies did not invest in the microfinance sector was that the poor are not bankable
Besides lacking education and therefore not being able to deal with formal financial
institutions they were viewed as bad credit risk who were unable to invest the borrowed
money in a way that would allow them to repay the loan and interest at a commercial
rate163 Another reason that kept attention away from the idea of providing financial
services to low income people was the belief that informal moneylenders already met
this demand These skeptics felt affirmed through the poor performance of subsidized
credit programs as described in chapter 22 Although it is true that moneylenders
serve a huge number of people in the developing world they more often than not charge
usury interest rates of up to 20000 percent per month164 While the argument that poor
people are not able to participate in the formal financial market can be overcome by
adapting the services accordingly165 the claim of low returns on their investments is not
only proved wrong by empirical evidence but also contradicts economic theory as will
be shown in chapter 53
51 The imperfect Information Paradigm
A more elaborate explanation for the short supply of financial services to low income
people that can be derived from the imperfect information paradigm based
predominantly on the works of Akerlof166 and Stiglitz and Weiss167 After giving a brief
summary of their argument an adaptation of their findings to the microfinance market
will be presented and subsequently it will be shown how their conclusions can be
overcome
Behind the imperfect information paradigm lies the theory of asymmetric information
which simply states that if two parties conduct a transaction one is likely to have more
163 See Ghatak (1983) p 21 et sqq Yunus (1998) p 102 et sqq Robinson (2001) p 35 et sqq164 See Robinson (2001) p 17165 See Seibel (2003b) p 2 BRAC (2003) pp 15et sqq Yunus (1998) pp 151 et sqq 166 See Akerlof (1970) pp 488 et sqq167 See Stiglitz and Weiss (1981) pp 393 et sqq
32
information than the other and is trying to use that for its own advantage168 Applied to
the banking sector this means that a person applying for credit can better judge the
likelihood of repaying the loan than the bank This is because the borrower has better
knowledge of the market she wants to invest in her skills and her willingness to repay
Moreover the bank might not be able to observe if the borrower uses the loan for the
agreed purpose These occurrences can lead to what is known as adverse selection and
moral hazard In this case adverse selection refers to the problem that banks might
attract borrowers with a low probability of repayment if they can not distinguish
between high and low risk loan applicants Moral hazard occurs after the provision of
the loan when the borrower spends the money on a purpose different to the prescribed
purpose and therefore lowers the probability of repayment This can happen eg by
investing in a more risky project or through spending the money on consumption If the
bank is not able to find a cost effective way to avoid these problems it might raise its
interest rate in order to compensate for the increased risk
Figure 1 Expected Bank Return and the Interest Rate
Source Stiglitz and Weiss (1981) p 394
Since this might discourage low risk borrowers from applying for credit and encourage
borrowers who continue to take loans to invest in riskier projects the share of high risk
168 See Neus (1998) p 85 et sqq
INTEREST RATEI
EX
PE
CT
ED
RE
TU
RN
TO
TH
E B
AN
K
33
borrowers could increase and therefore reinforce the problems stated above Thus
increasing the interest rate beyond a certain point actually leads to a decrease in the
expected return to the lender This context is illustrated in figure 1 with I being the
interest rate which maximizes the expected returns to the bank Obviously the bank
would charge the interest rate I in order to maximize its expected return However this
price for capital was not determined through supply and demand as economic theory
would predict It is conceivable that at the interest rate I the demand for credit exceeds
the supply but even if loan applicants would offer to pay a higher interest rate the bank
would refuse because it associates such a loan with high risk As a result credit might
be rationed169
52 Adaptation to the Microfinance Sector
Through some adaptations this model can also help to explain the lack of funds
provided to low income people In the original model of Stiglitz and Weiss several
assumptions have been made that need to be suspended in order to compare the credit
markets for low and high income people and give an explanation why the latter is
widely neglected by institutional investors
Evidently the assumptions that the amount borrowed is equal for each loan applicant
and that transaction costs170 need not to be taken into account171 are not suitable for this
context While the average loan size of MFI customers is much smaller than that of
clients from traditional banks the transaction costs as a share of the loan are
considerably higher because the lenderrsquos costs for conscientious processing a credit
applications are only slightly smaller for a $50 loan than for a $100000 or a
$10000000 loan
In figure 2 the R(I)large curve represents the return to the bank for large loans with
regard to the interest rate I and the R(I)small curve describes the same correlation for
small loans It is shifts downwards to reflect the assertion that the imperfect information
169 See Stiglitz and Weiss (1981) p 394170 In this paper the term bdquotransaction costsldquo refers to the operating expense ratio as defined by MicroRate It ldquois calculated by dividing all expenses related to the operation of the institution (including all the administrative and salary expenses depreciation and board fees) by the period average gross portfoliordquo See MicroRate and Inter-American Development Bank (IADB) (2003) p 16 171 See Stiglitz and Weiss (1981) p 396
34
paradigm has a more severe effect on poor people than on the better off They are
expected to have less profitable investment opportunities at their disposal172 and
therefore are more likely to invest in riskier projects which increase the probability of
default and hence decrease the expected return to the bank Additionally one might
expect poor people to be more likely than others to spend borrowed money on
consumption instead of an income generating activity particularly if a crisis arises It
seems understandable that food or urgently needed medicine are given priority over
repaying a loan
The second shift downwards is due to transaction costs As stated above they are
relatively higher for smaller loans Obviously transaction costs are incurred in the
provision of a large loan as well but since they are much smaller with regard to the loan
amount they are not included in the diagram for reasons of clarity
Figure 2 The extended Model
Source Own diagram adapted from Stiglitz and Weiss (1981) p 394
172 See Khandker (1998) p 8
INTEREST RATE I
SmallLoans
LargeLoans
Transaction costs
Lack of investment opportunities
R(I)large
R(I)small
EX
PE
CT
ED
RE
TU
RN
TO
TH
E B
AN
K
35
53 Overcoming Credit Rationing for the Microfinance Sector
If the conclusions in chapter 51 hold it is rational for a profit maximizing investor to
neglect the microfinance sector as long as no surplus funds in the market for large loans
exist This finding can help to explain the small amount of money provided to the
microfinance sector from commercial investors On the other hand it has to be stated
that this theory is reflexive as defined by Soros173 It not only explains but also forms
reality since it has the potential to reinforce the view of potential investors that
microfinance is a less profitable business174 Therefore demonstrating under which
conditions microfinance can be profitable and in some cases be more profitable than
traditional businesses is of crucial importance
To provide a fairer view of the microfinance sector a further assumption of the Stiglitz
and Weiss model that needs to be suspended is that all investments made by the
borrowers have the same expected return175 As stated above this contradicts economic
theory which claims ceteris paribus capital productivity decreases while the amount of
fixed capital increases In combination with a low capital endowment micro-enterprises
are usually faced with an excess supply of unskilled labor especially in developing
countries176 Hence small enterprises use far less capital per employee than big business
and therefore their marginal productivity of capital is much higher177 This is intuitive if
one imagines an economic actor who wants to invest several packages of capital
Obviously she would invest the first package where she expects the highest return the
second package where she expects the second highest return and so on Each additional
investment opportunity would lead to lower or at best equal returns178 While this
simplified example has limitations it demonstrates how the marginal productivity of
capital can diminish Although it might actually increase until a certain point179 this can
be expected to be so low in this context that it has no influence on the correlation as
shown in figure 2
173 See Soros (1998) pp 14 et sqq174 See Goodwin-Groen (1999) p 8175 See Stiglitz and Weiss (1981) p 395176 See Perkins et al (2001) pp 95 et sqq177 See Tschach (2000) p 8178 See Rosenberg (2002) p 11179 See Rechard G Lipsey (1979) pp 211 et sqq
36
Figure 3 Marginal Productivity of Capital
Source Dornbusch and Fischer (1995) p 406
Even if good investment opportunities for poor people exist the question remains if it is
possible to distinguish between high and low risk borrowers The problem of adverse
selection is overcome in a cost effective way in many MFIs180 For the better off poor
for example institutions like BRI base their decision on whether or not to approve a
loan by assessing the repayment ability of potential borrowers from their current income
flows and not from the uncertain returns generated by the loan181 Additionally
collateral is used in some cases to attract low risk borrowers182 In contrast to
industrialized countries this is usually not done to cover the potential losses of the
lender but to punish the defaulter and therefore increase her willingness to repay183
Obviously this does not always work for the poorest since they often neither posses any
goods that could work as collateral nor do they have sufficient earnings prior to
obtaining a loan for starting an income generating activity Here the so called group-
lending model can help to identify creditworthy borrowers The most prominent
institution using this approach is the Grameen Bank which only provides credit to
180 See Farrington (2000) p 20181 See Robinson (2001) p 80 Robinson (2002) p 238182 See Bester (1985) p 850 et sqq183 See Schmidt and Tschach (2001) p 15 Robinson (2002) p 244
FIXED CAPITAL 0
MA
RG
INA
L P
RO
DU
CT
IVIT
Y
37
members of a group of five These groups are formed by their members without
interference of the Grameen Bank Although in this particular case no joint liability
exists for the members of the group nobody can receive a new loan if another member
of the group fails to repay on time184 Therefore the group formation work as a
screening process Since the borrowers do not want to risk their ability to obtain further
loans they carefully select with whom to form a group Usually the members know
each other for a long period of time and therefore they can make a meaningful judgment
of each othersrsquo ability to repay the loan Other MFIs even require the members of a
group to mutually guarantee each othersrsquo loans185 While this might further increase
borrowersrsquo efforts to search for trustworthy group members it might also keep potential
borrowers from applying for a loan since she does not want be held responsible for
defaulting members This mechanism enables MFIs to partly pass on the transaction
costs related to the selection of low risk borrowers to the borrowers themselves186
Many MFIs have also largely overcome the problem of moral hazard by creating
incentives to ensure a high repayment rate even among the poorest In some cases their
customers go hungry in order to pay back their loan even though no legal action would
be taken against them if they would refuse to do so187 One way to achieve this is to
build up peer pressure through the formation of groups as described above188 Another
and probably the most important is to limit access to future loans to those borrowers
who repay on time The demand for successive loans is extremely high In a 1996
survey 98 percent of BRI borrowers planed to apply for another loan189 and in 1993
less than 30 percent of Grameen Bank loans went to first time borrowers190 Especially
the poorest highly value the option to reborrow191 and many MFIs see this as their
primary incentive to ensure repayment192 According to Schmidt and Tschach ldquothe net
present value of future access to credit works out to be roughly half the value of the
economic advantage to be gained from the intended non-repaymentrdquo193 This can also
184 See Yunus (1998) p 135185 See Schmidt and Zeitinger (1997) p 6186 See Stiglitz (1990) p353187 Own observation at the Grameen Bank in Bangladesh (2003)188 See Hoff and Stiglitz (1990) p 249189 See Robinson (2002) p 251190 See Khandker Khalily and Khan (1995) p 93191 See Gibbons (2000) p 15 Hashemi and Schuler (1997) p 43192 See Gibbons and Meehan (1999) p 160193 See Schmidt and Tschach (2001) p 16
38
explain the occurrence of a drop in the repayment rate once a MFI is no longer seen as
viable and therefore is not expected to provide loans in the future194
With the help of the described mechanisms MFIs around the world are able to keep
repayment rates high A survey of 69 MFIs from 36 different countries each serving
more than 10000 clients in 2002 found the portfolio at risk (PAR)195 varied between
zero and 231 percent While the average was 36 percent the median was found to be
229 percent196 One of the MFIs included in this sample is BRIs whorsquos 12-month loss
ratio has never exceeded five percent since the start of its transformation in 1984 and
from 1997 to 1998 the ratio actually fell from 22 to 194 percent197 The latter deserves
special attention because the Asian financial crisis reached its peak at that time with
Indonesia being hardest hit as illustrated by a statement from The Economist in July
1998 Even with the fierce competition from its neighbors Indonesia would probably
walk away with the prize for Asias most desperate banking systemrdquo198
The findings that MFIs can adapt their services to low income people in order to ensure
a high repayment rate and that poor people do not lack profitable investment
opportunities are illustrated in figure 4 From this diagram it can be seen that under the
new assumptions the interest rate at which the bank maximizes its return differs for
large (I(l)) and small loans (I(s)) According to the assumption that micro-
entrepreneurs can realize a higher return on their investments the bank can charge them
a higher rate of interest without bearing an increased risk Nevertheless in this example
the bank would still serve the market for large loans first because of the higher
transaction costs for smaller loans
The view as described in figure 4 is shared among most traditional banks and investors
in industrialized as well as in developing countries In addition to neglecting the
possibility of generating profits by offering microcredit themselves199 they also hesitate
to lend to MFIs because they consider their business too risky
194 See Schreiner (1997) p 64195 ldquoPAR shows the real risk of the portfolio by comparing outstanding loan balances for loans with atleast one late payment to the outstanding loan portfoliordquo Gross and de Silva (2002) p 22196 Own calculations See Appendix 2197 See Seibel (2000) p 11198 The Economist (1998) pp 92 et sqq199 Busch and Kort (2004) p 8
39
Figure 4 The extended Model
Source Own diagram adapted from Stiglitz and Weiss (1981) p 394 Tschach (2000)
p 17
This attitude can be observed by comparing the ratio of equity to liabilities which is
considerably higher for MFIs than for conventional banks200 When it comes to MFI
start-ups and those MFIs serving the low end market in remote areas even experienced
microfinance practitioners are skeptical if interest rates that fully recover all costs can
be charged201
Theoretically there are two ways to adjust this model to arrive at a conclusion which is
more favorable with regard to the profitability of microcredit One is to cut the
transaction costs and therefore reduce the downward shift of the R(I)small curve the
other is to allow the bank to further raise the interest rate without experiencing a
decrease in its return This means to increase I(s) and the respective rate of return
While in 2000 Tschach stated that transaction costs vary between 10 and 20 percent for
loans provided through the group lending model and between 15 and 30 percent for
200 See MicroRate and IADB (2003) p 30201 See Volkery (2004) p 33 Gibbons (2000) p 15 Gibbons and Meehan (2002) p 29 Goodwin-Groen (1999) p 8
INTEREST RATE I(l)
SmallLoans
LargeLoans
Transaction costs
I(s)
R(i)large
R(i)small
EX
PE
CT
ED
RE
TU
RN
TO
TH
E B
AN
K
40
individual loans202 it was recommended in 1999 that MFIs should target a range
between 15 and 25 percent203 Some best practices on the other hand have already
achieved single digit numbers Currently BDB might be the most efficient MFI in the
world with transaction costs at just 47 percent in 2001204 Even though the low costs of
BDB have to be acknowledged its achievement has to be put in perspective As stated
above with an average loan balance of more than $5000 it does not serve the low end
market In addition it works in an environment with a high population density which
means that it can reach a relatively large group of borrowers per branch This is a
comparative advantage many Asian MFIs enjoy as can be illustrated by comparing
Bangladesh and Bolivia Both countries are at the forefront of the development of
microfinance in their respective continent but while in Bangladesh more than 1000
people are living per square kilometer the average for Bolivia is only eight205
Therefore it is consistent that the most efficient MFI in Latin America Fondo
Financiero Privado para el Fomento a Iniciativas Economicas has transaction costs of
114 percent206 With an average loan size greater than the annual GDP per Capita this
institution also does not serve the low end market207
Despite the impressive efficiency gains in the described examples most MFIs are far
from achieving these numbers and many are unlikely to reach them due to the
environment within which they work A survey of 67 MFIs from 31 countries found the
average transactions costs in 2002 to be 279 percent with a median of 206 percent208
However even if these institutions were to increase their efficiency to best practice
standards their transaction costs would still be significantly higher than those of
traditional banks providing much larger loans For these banks the respective costs vary
in a range between 05 and 3 percent209 According to this argument charging interest
rates considerably higher than conventional banks is the only way for MFIs to generate
higher returns and hence successfully compete for capital
202 See Tschach (2000) pp 100 et sqq203 See Gibbons and Meehan (1999) p 149204 See M-Cril (2001b) p 4205 See CIA (2004)206 See MicroRate (2004)207 In this paper the term ldquolow endrdquo refers to the definition of the MBB (2003) p 54 Loans worth less than 20 percent of the respective countryrsquos GDP per capita are described that way 208 Own calculations See Appendix 3209 See M-Cril (2004a) p 16
41
6 Interest Rates
61 Setting the right Interest Rate
Before addressing the questions to what extend MFIs can raise their interest rates
without putting the repayment rate or the social benefits of their customers at risk a
basic model will be presented This model will illustrate how a MFI should set their
rates in order to not only cover their costs but also to generate an appropriate profit to
finance further growth and attract additional capital
In 2002 CGAP revised its 1996 paper ldquoMicrocredit Interest Ratesrdquo210 which outlines
the standard method of setting sustainable interest rates for commercially oriented
MFIs According to this model the annual effective interest rate (I) should be calculated
as shown below
(1) I = LL
IIKCFLLTA
minusminus+++
1
With each variable being a decimal fraction of the average outstanding loan portfolio
whereby TA stands for the transaction costs as described above LL represents the
annual loan loss and II stands for investment income eg on liquid assets The cost of
funds (CF) consist of the interest and administrative costs needed to obtain deposits and
commercial loans as well as of the imputed costs on equity due to inflation K stands for
the capitalization rate which represents the net real profit Keeping this rate high is
important to finance the future growth of the loan portfolio This can be either done
through investors attracted by high profitability or through borrowing For the latter an
increase in equity is inevitable since it is required as a safety cushion by lenders
Since this model ignores the timing of cash flows and does not take taxes into account
it has to be regarded as fairly imprecise and hence should not be used for business
planning Nevertheless it can be used for an approximation of the interest rate that a
MFI would need to charge to provide its services as planned In the following I will
210 See Rosenberg (2002) pp 1 et sqq
42
apply this model on a fictitious MFI working in a rural area of Latin America with low
end customers In this setting it seems realistic to estimate transaction costs of 35
percent and loan loss rate of two percent211 If funds were borrowed at commercial
terms their costs can be assumed to equal at least 15 percent of the average outstanding
loan portfolio212 Estimating the capitalization rate is more challenging First the
targeted portfolio growth rate is set at 75 percent This is slightly below the 751 percent
average annual portfolio growth between 2000 and 2002 found by a survey of 25
different MFIs based in Central and South America213 If the extend to which the MFI
can leverage stays constant the loan portfolios growth would be limited by the growth
rate of the equity To express the capital needed for this growth as a share of the loan
portfolio it is necessary to estimate the ratio between the equity and the outstanding
loan amount According to the survey mentioned above the loan portfolios of the 25
Latin American MFIs equal on average 215 times their equity214 With this number the
capital needed to increase the equity by 75 percent would corresponds to approximately
35 percent of outstanding loan amount (075215) Finally the investment income has to
be estimated Since liquid assets that are available short term do not generate high
returns say five percent it does not seem advisable for the MFI to hold more than a
quarter of its loan portfolio in this form Hence the profit generated in this way would
equal 125 percent of the outstanding loan amount Using these numbers the equation to
calculate the annual effective interest rate reads as follows
(2) I = LL
IIKCFLLTA
minusminus+++
1 =
0201
01250350150020350
minusminus+++
= 0875
As a result the MFI would need to charge an annual effective interest rate of
approximately 875 percent on its loans in order to sustainable provide its services and
finance its growth without depending on donor money This rate might decrease once
the MFI matures the growth slows down and cheaper funds become available but it
will stay significantly higher than any rate charged by conventional banks
211 MicroRate and IADB (2004) pp 6 and 16212 See MicroRate and IADB (2004) p 616 and 28213 Own calculation See Appendix 4214 Own calculations See Appendix 5
43
62 Can Micro-Entrepreneurs bear these Rates
Although most MFIs charge rates significantly below 875 percent many critics have
strenuously argued against any rates exceeding those of traditional banks Rosanna
Barbero of Oxfam labeled an interest rate of 52 percent charged by a Cambodian MFI
ldquoludicrous evil and disgusting and stated that ldquo[n]o business in the world can make a
profit at these interest ratesldquo215 The former finance minister of Bangladesh Shah Kibria
even categorized the 20 percent effective rate charged by the Grameen Bank as to
high216 Many practitioners therefore believe in a strong negative correlation between
the interest rate and the demand for loans217 Others have argued more generally that
concentrating on profitability and therefore charging high interest rates diverts MFIs
from serving the poorest218
These views are still shared among many MFI managers donor agencies and especially
investors and politicians While the former are unwilling to charge interest rates for
funds they received ldquocheaplyrdquo (through grants or subsidized loans) and are worried
about undermining their social goals by charging higher rates of interest219 the latter are
reluctant to invest for reasons stated above or impose interest caps to catch the attention
of the public by pretending to protect the poor from usury rates220
In chapter 53 it has been described that micro-entrepreneurs due to their smaller
capital endowment have even better investment opportunities than big business The
extend to which this is true has not yet been answered An indication is the high
repayment rate observed within MFIs around the globe If their customers capital yield
did not exceed the charged interest rate how would they be able to repay According to
Gibbons and Meehan customers of MFIs can generally generate returns of more than
100 percent on their invested capital221 and ldquo[r]esearch in India Kenya and the
Philippines found that the average annual return on investments in microenterprises
215 See Kate and Roeun (2004)216 See Hodson (2001) min 1100217 See Morduch (1999a) p 1594218 See Prisma (2002) p 1219 See Schreiner (1997) p 60 Khandker (1998) p 106 220 See Gross and de Silva (2002) p 32 Jansson and Wenner (1997) p 36 et sqq Campion (2002) p 59221 See Gibbons and Meehan (1999) p 131
44
ranged from 117 to 847 percentrdquo222 Schmidt and Tschach found the marginal
productivity of capital to be as high as 1000 percent for the smallest loans provided by
the Bolivian MFI Caja Los Andes223 These findings are confirmed by the observation
of Rosenberg who found while working as a microfinance consultant for ten years he
never heard of a single MFI having problems to attract clients because interest rates
were too high224
To get a better understanding of the investment opportunities of low income people in
developing countries a typical example on how MFI clients invest their loans is as
follows
Zobair is working as a rickshaw puller in Bangladesh Like most of his colleagues he
does not own the rickshaw he is riding Therefore he has to pay a daily rent of about
$030 to the owner Since his average income of approximately $15 per day is hardly
enough to feed his family he is not able to save the $100 necessary to buy a rickshaw
on his own 225 If he could do so through obtaining a loan his income would increase by
$030 every day because he would not have to pay the rent for the rickshaw anymore
Assuming an average of six working days per week 226 and a life span of the rickshaw
of 5 years his internal rate of return would equal 15324 percent annually227
Consequently any interest rate charged by a MFI would be advantageous to him as long
as it would not exceed 15324 percent228
63 Should the Interest Rate be subsidized anyway
Despite the fact that numerous micro-entrepreneurs are able to generate tremendous
returns on their investment obviously not all are able to use capital in such a productive
way and therefore can not afford microcredit at commercial rates In order to reach
these people as well many MFIs continue to use donor money in order to keep their
interest rates low But even if the problems related to subsidized credit as described in
222 See Helms and Reille (2004) p 3223 See Schmidt and Tschach (2001) p 6224 See Rosenberg (2002) p 10225 This examples draws on observations made by the author in Dhaka (Bangladesh) during 2003226 Obviously extended holidays are not a viable option in this surrounding 227 Own calculation See Appendix 6228 This result is only valid if the loan is repaid in daily instalments For a weekly repayment schedule the interest rate charged by the MFI must not exceed 15119 percent in order to still be beneficial for Zobair
45
chapter 23 do not arise it might still not be the most effective tool to help poor people
as will be illustrated in the following example
A MFI faces two groups of potential clients one with businesses able to generate a
return of 125 percent on borrowed capital and another with a possible returns of 50
percent Assuming budget costs according to equation (2) the institution needs to
charge an interest rate of 875 percent and therefore only serves the former group
Supposed each group consists of 50 members demanding $100 loans the net gains to
society (NGS) could be calculated as follows
(3) NGS = 50 times ($125 ndash $875) = $1875
These gains would be due to the investments of the more profitable group which were
made possible through the loans provided by the MFI The less profitable group would
not borrow since their expected returns are not sufficient to pay for the interest If the
interest rate would be lowered to 30 percent both groups would be able to generate net
gains and therefore borrow from the MFI In order to provide loans at this rate the
institution would need to raise additional capital from non commercial sources The
NGS would be calculated as follows
(4) NGS = 50 times ($125 - $30) + 50 times ($50 - $30) + 100 times ($30 - $875) = 0
While the first terms represent the net gains to the respective groups the last describes
the costs incurred in providing the loans At a rate of 30 percent each loan would need
to be subsidized with $575 Hence the NGS actually fall after the introduction of the
subsidized loan This is due to the fact that the less profitable group is encouraged to
invest in relatively unproductive businesses In addition future growth of the MFI could
be jeopardized due to scarce donor money which is needed to finance the interest rate
subsidy Therefore it seems more advisable to continue to charge a rate of 875 percent
and spend the money used for subsidization on other programs such as health care or
education229
229 In Appendix 7 it will be shown that this result generally holds
46
7 Empirical verification
71 Setting up a Sample
To see if the findings of the previous chapters hold the effects which interest rates
charged by MFIs have on their performance will be analyzed in the following Up to
now such a study does not exist mainly because of a lack of adequate data Most MFIs
do not provide accurate information about the annual effective interest rate they charge
and therefore make an evaluation difficult
In 2002 Rosenberg distinguished eight different categories on how microcredit interest
rates are quoted230 These categories differ in several ways On the contrary to
traditional banks for example it is common for MFIs to state interest rates calculated on
a ldquoflatrdquo balance rather than on a declining one This means that the total loan amount is
used to determine the interest rate ignoring installments paid by the borrowers normally
on a weekly or monthly basis In addition many MFIs charge a certain upfront fee prior
to the loan disbursement require compulsory savings at a lower rate or state their
interest rate for semi annual terms only On the one hand this is done to provide
numbers that are more meaningful to MFI customers who often lack the necessary math
skills to deal with compound interest on the other hand it is done to circumvent interest
rate ceilings imposed by the government231 Another problem is that most MFIs offer
different loan products without itemizing their respective shares to their total loan
portfolio As a result it is not possible to calculate a weighted average even if the rate
stated by the respective MFI could be transformed into an effective interest rate
Usually the portfolio yield is used as a proxy in order to make statements about the
interest rate charged by a certain MFI232 It is generally ldquocalculated by dividing total
cash financial revenue (all income generated by the loan portfolio but not accrued
interest) by the period average gross portfoliordquo233 The advantage of this method is that
even the hidden costs are considered Nevertheless it also has a severe shortcoming by
not taking late or defaulted payments into account Therefore the portfolio yield does
230 See Rosenberg (2002) p 5231 MicroRate (2002) p 8232 See MicroRate (nd)233 MicroRate and IADB (2003) p 39
47
not allow to draw conclusions regarding the correlation between the interest rate
charged by a MFI and its PAR
72 Examining the Sample
Through the appearance of rating agencies specialized in the microfinance sector more
adequate information has become available in recent years While MicroRate only
publishes the portfolio yield of rated MFIs M-Cril Microfinanza Microserve and
Planet Rating actually provide information about the annual effective interest rate for at
least some of the MFIs they analyze Although it is labelled differently from all of the
four institutions234 the term describes what is ldquothe highest income or yield that an
organisation can earn from its portfolio based on the terms of its loansrdquo235
Currently236 reports of 39 different MFIs from 20 countries providing accurate
information about the effective annual interest rate are available to the public This
sample should be used to verify the findings of the previous chapters237 Since a
comparison is made between the performances of MFIs based in different countries and
the ratings have been carried out in different years several adjustments are necessary
First the inflation of the respective country and the respective year(s)238 has to be taken
into account in order to only compare the real rates239 In addition the average
outstanding loan amount per borrower is divided by the respective countryrsquos GDP per
capita Since it can be assumed that ldquoonly the poorer households will be willing to take
the smallest loansrdquo240 this number can be used as a proxy for the poverty level
Although the sample size is far to small to represent the microfinance sector as a whole
and the results are statistically not significant the findings can still be used to underline
the theoretical conclusions drawn in the previous chapters In figure 5 the connection
234 M-Cril uses the name ldquoannual percentage raterdquo See eg M-Cril (2004a) p 25 Microfinanza uses the name ldquoexpected portfolio yieldrdquo See eg Microfinanza (2002c) p 25 Planet Rating uses the name ldquoannual effective interest raterdquo See eg Planet Rating (2004d) p 1 Microserve uses the name ldquotheoretical yieldrdquo See Microserve (2003) p 62235 See M-Cril (2004a) p 25236 As of September 28th 2004237 See Appendix 8 For exchange rates see FXTOP (2004)238 Where necessary a weighted average of the annual inflation rate was used See Appendix 9239 This is done through the following formula ir = (I ndash F) (1 + F100) While ir represents the real annual effective interest rate F represents the inflation rate 240 Morduch (1998) p 1572
48
between the average loan size and the transaction costs as a share of the average loan
portfolio is illustrated
Figure 5 Loan Size vs Interest Rate241
Source Own diagram
000
1000
2000
3000
4000
5000
6000
7000
8000
9000
10000
0 100 200 300 400 500 600
Loan Size
Inte
res
t R
ate
It can be seen that the interest rate is negative correlated to the loans size This can be
explained by the relative higher transaction cost for smaller loans as described in
chapter 52 In order to cover their costs MFIs serving the low end market need to
charge higher rates to their customers than those organizations serving the better off
poor Obviously there are several assumptions to this general finding Especially
striking are the two MFIs with an average loan size of approximately five times their
countries GDP per capita which still high interest rates This occurrence can be
explained by taking a closer look to the respective organizations One was established
less than two years prior to its rating and therefore still bears a lot of start up costs242
241 The equation for the regression line reads as follows Y = -00219X + 365 The correlation coefficient is 014242 See Microfinanza (2002b) p 1
49
the other managed to stay profitable while it almost quadrupled its loan portfolio in the
last two years243
Figure 6 Interest Rate vs PAR244
Source Own diagram
0
5
10
15
20
25
30
35
0 20 40 60 80 100 120
Interest Rate
PA
R
In Figure 6 the crucial correlation between the interest rates charged by a MFIs and its
PAR245 is examined According to the given sample the view of traditional banks and
investors that a higher interest rate leads to a higher default rate does not hold
Obviously one has to avoid to draw the opposite conclusion namely that a high interest
rates decreases the PAR The connection illustrated in figure 6 has to be interpreted as
follows Since high interest rates are related to small loans the low PAR for MFIs
charging high interest rates can actually be explained by the tremendous profitability of
small size investments Despite the high rates their customers are even more likely to
repay
243 See Planet Rating (2003b)244 The equation for the regression line reads as follows Y = -00768X + 68433 The correlation coefficient is 0235245 M-Cril only publishes the PAR for overdues greater than 60 days Therefore these ratios are used as a proxy for the industry standard of 30 days for some Asian MFIs
50
Finally it has to be examined if charging high interest rates actually enables MFI to
generate higher returns Although it can be expected that the combination of a low PAR
and a high interest rate leads to a high profitability it still has to be checked if this is not
outdone by soaring transaction costs Figure 7 illustrates the correlation between the
interest rate charged by a MFI and its financial self-sufficiency (FSS) The latter is the
ldquo[r]atio of total income to total adjusted expenses for the year Adjustments are made
for subsidised cost of funds (relative to market interest rate) equity (with respect to
inflation) and in-kind donationsrdquo246 It can be seen that the regression line actually does
indicate a positive correlation between the interest rate and the profitability of a MFI
Figure 7 Interest Rate vs FSS247
Source Own diagram248
0
20
40
60
80
100
120
140
160
180
0 20 40 60 80 100
Interest Rate
FS
S
246 M-Cril (2004a) p 53247 The equation for the regression line reads as follows Y = 02839X + 8901 The correlation coefficient is 0174248 Since the interest rate the customers of the MFI Foccas have to pay includes fees which are not passed on to the institution its interest rate in this diagram is set at 723 percent instead of the 10715 percent used for figure 6 See Planet Rating (2003b) p 1
51
This result does not necessarily disprove the findings of Stiglitz and Weiss since it can
be argued that MFIs simply do no increase their interest rates to the point where they
would maximize their expected returns But if this would be true why do MFIs not
charge higher rates of interest given the demand described in chapter 41 and 43 In
mature markets competition normally ensures prices not to exceed a certain level but
since many MFIs still operate in a ldquosellerrsquos marketrdquo249 this can not explain the findings
as described in figure 7 Therefore it has to be assumed that a combination of the
unwillingness of many microfinance practitioners to burden their customers with high
interest rates and the plain disbelief of traditional investors that micro-entrepreneurs can
bear those rates is responsible for this occurrence
249 See MicroRate and IADB (2003) p 9
52
8 Conclusions
It has been shown that MFIs are not only contributing significantly to the development
of the financial sector in their respective countries but also that they play an important
role to eradicate poverty by providing much needed capital to low income people which
are able to generate tremendous returns on their investments
The fact that the demand for microcredit is not met is mainly due to the view of most
for profit investors and traditional banks that offering financial services to poor people
can not be done profitable Because of this conviction they hardly invest in the
microfinance sector This does not have to be the case according to the findings of this
paper Although faced with relatively high transaction costs MFIs are able to charge
interest rates at levels that fully recover their costs Elizabeth Rhynersquos claim ldquothat the
most financially viable programs differed from their less viable peers in their
willingness to set interest rates at levels that would fully recover costsrdquo250 is backed by
the findings of this paper that high profitability is correlated to high interest rates
Theoretical models based on the findings of Stiglitz and Weiss can not be used as a
justification to ration credit for the microfinance sector since the interest rate that
maximizes profits to the lender can be assumed to exceed 100 percent for many MFIs
Nevertheless this rate is hardly charged although it has been shown that it can be done
The Mexican MFI Compartamos for example manages to keep its PAR as low as one
percent while charging an effective interest rate of more than 100 percent to
approximately 160000 clients251 In combination with this case the conclusions drawn
from examining the sample of MFIs in chapter 7 the claim of Hulme and Mosley as
stated in the introduction can be considered as wrong MFIs are in fact able to finance
rapid growth stay profitable by charging corresponding interest rates and still have a
significantly positive impact on the poverty level of their clients In the long run gains
in efficiency economies of scale a slowdown in growth and competition will ensure
interest rates drop as it has already been the case in countries like Bangladesh and parts
of Bolivia252
250 See Rhyne (1998) p 7251 See MicroRate (2004)252 See Microrate and IADB (2003) p 9
53
According to a MicroRate survey many MFIs are more profitable than Citibank and also
generate a higher return on investment than commercial banks in their respective
countries253 Investments companies like IMI or Blue Orchard will soon be able to
present a meaningful track record of their microfinance investments to potential
investors Ultimately the capital markets can not ignore the facts proving that it actually
can be profitable to invest in the microfinance sector but in order to raise money
quickly microfinance practitioners will have to continue to intensively promote their
cause not only to for profit investors but also to donors and multilateral agencies like
the World Bank
253 See MicroRate (2002) p 10
54
Appendix
Appendix 1 Average loan balance
Source Data is available through the Mix Market (2004)
Organization
Loan Portfolio 2002 (US$)
Loan Portfolio 2003 (US$)
Number of borrowers 2002
Number of Borrowers 2003
2CM 1263602 1400438 3622 3708ACF 955503 1611401 285 370ACLEDA 26846703 39391301 82598 98905ACME 1460881 1714844 4283 4600ADIM 369065 407798 1122 1395AFK 933306 1706577 250 467AgroInvest 4684249 9697411 5208 9629Al Amana 15593277 28677666 78114 101610AMSSFMC 612167 1040756 6183 6886AREGAK 3285273 3987011 11841 14377AVFS 214331 269819 1883 2866BancoSol 83629049 91175000 42290 56707BESA 10563980 15114430 4488 5061BPR AK 613362 876130 1730 3879BPR BMMS 133949 237946 1755 1779BRI 1344006170 1720072773 3056103 3100358BZMF 1592508 1922097 1250 1331CBDIBA 216587 242465 5764 2877CCA 2146235 4582302 4070 6585CCCP 447534 851678 6265 9450CEP 3795400 5261957 32291 42132CERUDEB 25093643 34873228 34490 44796CMEDFI 227674 250244 3467 3781CMM - Bogota 4836000 8135968 15635 22038CMMB 34880 56964 42 190COAC Maquita Cushunchic
870084 1855718 6603 7732
CODES 280843 263091 60 60CODESARROLLO 6714007 12935951 4391 6896Constanta 2943822 3536047 16134 18588COOPEC CAMEC MN
7152 29821 92 77
Crear - Tacna 3891116 4636094 3671 4948CREDIT 642094 81838 7532 8097CRYSTAL FUND 366456 421403 1379 1061DBACD 3473701 3876526 12812 19606ECLOF - ECU 1154292 728312 860 416ECLOF - MAL 441734 407227 1118 1500EKI 11833244 19245751 8999 13323EMT 4481589 5765281 84781 92173ESED 8579460 6834742 22790 20035
55
Eshet 185741 462569 3308 6540Faulu - KEN 9027332 7206344 17463 15000FDL 12503027 16545332 21306 25106FIE 35818903 41597315 26468 33100FINADEV 5512586 9770323 12775 14709Finance Salone 211312 434298 2225 7159Finca - TAN 1293430 1854834 20648 27499Finca - UGA 2451703 2798869 35610 36912FINCORP 4761288 10236896 941 858FJN 5473563 8037662 8107 11133FMFB 308158 1188896 713 3558FMM -Bucaramanga
6355518 10227000 25814 42464
FODEM 739181 939824 1909 2501FundaciESPOIR
898561 1883446 5911 9464
FUNDESER 798907 1373113 4072 5065Gasha 323748 413742 5504 6423GGLS Save the Children
64235 137957 1291 2362
GK 56986 166971 951 2718HKL 1363365 1420357 6648 5372HOPE 402799 603488 1098 1562IAMD 42132 56550 2780 2772IDECE 21312 39453 150 232IDF 2031944 2626382 31003 36580IMCEC - Dakar 254759 688449 1018 2983IMCEC - Thies 199799 571122 1164 1261
ISSIA 221615 246792 1409 1698JMCC 1962355 2609723 1471 2333KAFC 21710638 29241051 24850 32097KAMURJ 1003935 1411258 5559 5691Kashf 2355965 6271498 29655 59389KMBI 721409 1626666 11973 27266KPSCA 109299 128063 362 794K-Rep 14490447 20699963 38739 45379KSCS 18978 43740 140 297KVT 44075 70621 241 373LAPO 922478 1194633 18740 19139MEC ADEFAP 27788 69248 198 202MEC Bosangani 14357 31086 364 540MEDF 104113 136257 1278 1184Meklit 233170 252232 2084 3577Metemamen 22123 57778 943 1501MFSC 109261 171090 511 687MIKRA 2951028 5008784 4145 6095MIKROFIN 9560502 18380263 5633 7426Miselini 737387 1026639 10182 11431MRFC 11475440 9133130 163000 180000Mushuc Runa 2089076 5418325 3139 6232Nirdhan 2886777 3016171 29589 27457OCSSC 5245186 7658413 42157 6215o
56
Otiv Diana 95992 638422 229 1073Otiv Sambava 188094 437974 2002 1442Otiv Tana 66465 673175 337 1269Partner 9976448 15321304 7139 11935PCA 6878257 6885926 63113 58147PEACE 420746 627295 4192 5428PEDF 164399 254233 2357 3340Piyeli 809447 1206656 8674 4745PRESTANIC 2827502 3540367 1477 2605PRIDE - MAL 991888 854631 5376 5601PRIZMA 3881581 6838978 8112 10968ProMujer -Nicaragua
1006871 1424437 10436 13047
PTF 891566 1068881 8500 9070RBST 818594 1058115 619 723REMECU 1381705 1483471 10330 13996
RUSCA 60887 100820 454 994
SCSCS 89423 157472 873 1007SFPI 709497 903556 7728 9552Sidama 934260 1011798 10267 11346SPBD 117807 186029 647 1740Sunlink 819138 1056823 3401 3833Sunrise 5412366 8782868 4560 7256TEBA 108032426 176300111 163021 157776TIAVO 281978 838905 2049 459TPC 1140429 2267148 22869 31668TSPI 4650989 5383755 49649 75617UNICECAM 3442843 5943804 16039 19031Wasasa 230657 274908 2850 3728Wisdom 1306066 1404463 10524 12054XacBank 4910098 9829503 11063 18610Zakoura 15907288 12444768 103720 118980
Appendix 2 Portfolio at Risk
Source Data is available through the Mix Market (2004)
Organization PAR 2002ABA 202ACEP 464ACLEDA 175ACODEP 452ACSI 209Al Amana 010Apoyo Integral
483
AREGAK 692Banco Solidario
500
BancoSol 660BASIX 1296
57
BRI 437BURO Tangail
350
CEP 200CERUDEB 103CMAC -Sullana
567
CMM -Bogota
176
Compartamos 111Constanta 304Credi Fe 212CREDIAMIGO 409DBACD 010EBS 847EMT 010ESED 1311FADES 2311Faulu - KEN 246Faulu - UGA 096FDL 212FECECAM 428FED 436FIE 598FINADEV 021Finamerica 1133Finca - TAN 000Finca - UGA 297FMM -Bucaramanga
094
FMM -Popayan
088
FONDEP 013FORA 064Genesis Empresarial
1197
IDF 017KAFC 106Kashf 000KMBI 128K-Rep 229MiBanco 309MRFC 1742Nirdhan 373
PADME 079PAMECAS 284PCA 379PRIDE - TAN 018ProMujer -Nicaragua
073
RCPB 600REMECU 157SHARE 000
58
Soluci 182Spandana 014TEBA 106TSPI 355UMU 125UNICECAM 405Urwego 290UWFT 363WAGES 736WWB -Medellin
235
XacBank 061Zakoura 095
Appendix 3 Transaction Costs
Source Data is available through the Mix Market (2004)
OrganizationTransaction Costs
Acci Rural 1154ACEP 858ACLEDA 2430ACODEP 2920ACSI 924Al Amana 2576AREGAK 2856AssEF 1919Banco Solidario
1826
BancoSol 1210BASIX 1317BRI 1353BURO Tangail
2053
CEP 1759CERUDEB 5109CMAC -Sullana
1784
CMM -Bogota
2089
Compartamos 3341Constanta 4597Credi Fe 1978CREDIAMIGO 2525DBACD 1742EBS 2377EMT 3220ESED 1343FADES 1673FAMA 2436
59
Faulu - KEN 2253Faulu - UGA 4962FDL 1726FECECAM 2587FED 4083FIE 1125Finamerica 1563Finca - TAN 10753Finca - UGA 9096FMM -Bucaramanga
1925
FMM -Popayan
1112
FONDEP 5477FORA 3481Genesis Empresarial
1626
IDF 1695
K-Rep 1909LAPO 3511MiBanco 2456Nirdhan 1325NWTF 3109OCSSC 1155PADME 1131PAMECAS 1705PCA 1670PRIDE - TAN 4273ProMujer -Nicaragua
5078
RCPB 2059SHARE 2308Sidama 2662Soluci 2906Spandana 641TEBA 1213TSPI 3898UMU 4023UNICECAM 10120Urwego 7437Wisdom 1906WWB -Medellin
1703
XacBank 4144Zakoura 1881
60
Appendix 4 Portfolio Growth
Source Data is available through the Mix Market (2004)
Organization
Total Loan Portfolio in 2000
Total Loan Portfolio in 2002
ACODEP 5889394 7258487Adelante 4327 88594ADRI 1514681 2591240AgroCapital 11100088 12018280Banco Solidario 39632165 103420000
BancoSol 78031172 83629049CMAC - Sullana 14596365 28055720
COAC Maquita Cushunchic
348443 870084
CODESARROLLO 1374801 6714007Compartamos 10804279 41825248Crear - Tacna 3778816 3891116
Credi Fe 781616 9393936ECLOF - ECU 179247 1154292
FADES 11948814 15501578FAMA 6201411 8835134FIE 22524645 35818903Finamerica 16575104 16097113FINCOMUN 3278938 5696556FMM - Popayan 6241821 12212867
FONDECO 3456625 5101801Genesis Empresarial
11154234 17746288
MiBanco 36964072 95873333Mushuc Runa 90737 2089076ProMujer -Nicaragua
426541 1006871
WWB - Medellin 2891207 4580998
Appendix 5 Portfolio vs Equity
Source Data is available through the Mix Market (2004)
OrganizationLoan Portfolio Equity
ACODEP 7258487 1921447Adelante 88594 72973
ADRI 2591240 781477AgroCapital 12018280 10766101Banco Solidario 103420000 12961000BancoSol 83629049 15299415CMAC - Sullana 28055720 6210291
61
COAC Maquita Cushunchic
870084 260331
CODESARROLLO 6714007 1285103
Compartamos 41825248 18350446
Crear - Tacna 3891116 1016912Credi Fe 9393936 863848ECLOF - ECU 1154292 459226FADES 15501578 4138972FAMA 8835134 6377663FIE 35818903 5360484Finamerica 16097113 3817960FINCOMUN 5696556 1042241FMM - Popayan 12212867 8510494FONDECO 5101801 1658075Genesis Empresarial
17746288 4765816
MiBanco 95873333 24261889Mushuc Runa 2089076 434311ProMujer -Nicaragua
1006871 1196015
WWB - Medellin 4580998 2213249
Appendix 6 Internal Rate of Return
Source Excel (German Version) calculation based on own data
A B C D E F
1 Date Cash Flow
Interest Rate Internal Rate of Return Balance Interest Principal
23 01012004 -100 15324 100 025489547 0045104534 02012004 03 999548955 025489547 0045104535 03012004 03 99909676 02547805 004521956 04012004 03 998643412 025466524 0045334767 05012004 03 998188909 025454968 0045450328 06012004 03 997733247 025443383 0045566179 08012004 03 999826083 050928361 -0209283610 09012004 03 999374595 025485114 004514886
hellip hellip hellip hellip hellip helliphellip hellip hellip hellip hellip hellip helliphellip hellip hellip hellip hellip hellip hellip1562 23122008 03 177951388 000528711 0294712891563 25122008 03 148859724 000908336 0290916641564 26122008 03 119239161 000379437 0296205631565 27122008 03 089543096 000303935 0296960651566 28122008 03 059771337 000228241 0297717591567 29122008 03 029923692 000152354 0298476461568 30122008 03 -3434E-07 000076274 029923726
62
The formula in the square C3 reads as follows
ldquoXINTZINSFUSS(B3B1568A3A156815)rdquo
Appendix 7 Subsidized Interest Rates and the Net Gains to Society
SourceOwn calculations
For simplicity only two groups of potential clients are distinguished This is possible
since using a continuum of potential clients would lead to the same results In addition it
is assumed that the amount of every loan (L) is equal and that all clients invest the
whole loan amount Group H consist of NH potential clients with a rate of return (rH) on
their invested capital higher than the cost recovering interest rate charged by the MFI
(iC) Group L consists of NL potential clients with a rate of return (rL) on their invested
capital lower than iC If the MFI charges iC the NGS can be calculated as follows
NGSC = NH times (rH - iC) times L
Since rH is bigger than iH (rH gt iC) according to the definition presented above the term
NGSH must be positive as long as NH does not equal zero If the MFI introduces a
subsidised interest rate (iS) lower than rL the NGS can be calculated as follows
(1) NGSS = NH times (rH - iS) times L + NLtimes (rL - iS) times L + (NH + NL) times (iS - iC) times L
(2) NGSS = NH times (rH- iC) times L + NLtimes (rL - iC) times L
The term (NH + NL) times (iS - iC) times L describes the amount of money that is needed in order
to subsidize the interest rate to the level iS By setting up an inequation it can be
examined under which conditions the NGSS are bigger than the NGSC
(3) NGSS gt NGSC
(4) NH times (rH- iC) times L + NLtimes (rL - iC) times L gt NH times (rH - iC) times L
(5) NLtimes (rL - iC) times L gt 0
(6) rL gt iC
63
So the NGSS could only be bigger than the NGSC if equation 6 holds This is
impossible since it violated the definitions presented above Therefore the introduction
of subsidized interest rates is always accompanied with a drop in the NGS
Appendix 8 Interest Rate vs Loan Size vs FSS vs PAR
Source Data is available through the Mix Market (2004)
Organization Country
Real Interest Rate
Loan Size (divided by the GDP per Capita) FSS PAR
BTFFKyrgyz Republic 3803 48260 1487 698
BesaFoundation Albania 2184 16076 684 260RFF Albania 1198 5783 4764 277PSHM Albania 2194 000 5758 198Mi-Bospo Bosnia 2974 5499 1261 020Prizma Bosnia 3474 3569 103 064Agroinvest Serbia 2201 4401 875 020KCLF Kazakhstan 5713 1713 865 090
Foccas Uganda10716 (723) 1550 584 29
ACEP Senegal 3280 20941 1643 1Padme Benin 2715 13575 1667 08Papme Benin 3086 53659 1405 24Vital Finance Benin 2676 9394 1015 17Finadev Benin 1738 14850 1024 21ABA Egypt 2579 1613 1168 88ASBA Egypt 2597 1702 1252 68DBACD Egypt 2490 1643 1073 0SBACD Egypt 2500 1734 982 67AMSSF Morocco 6926 787 1306 04Fondep Morocco 5199 650 889 071Zakoura Morocco 4414 900 98 006ENDA Tunisia 4008 1351 110 102BSFL India 1954 3269 856 99Share India 3426 1440 951 0Spandana India 2942 1618 1367 026SWC India 1864 2626 42 3036SKS India 2248 1912 578 0Grama Vidiya India 3176 1221 76 18Sneha India 3451 1433 933 0Buro Bangladesh 3206 1882 1093 17Upap Pakistan 2073 8183 757 03Seeds Sri Lanka 1004 1088 605 287EMT Cambodia 4324 1676 1016 01TPC Cambodia 4470 2035 832 27
64
WTF Phillippines 5816 1095 941 74TSKI Phillippines 5794 777 96 79Cacja Ecuador 862 6189 9460 897ACME Haiti 6043 6934 11685 450Grupo Cama Mexico 8961 267 10717 288
65
Appendix 9 Inflation vs GDP per Capita
Source IMF (2004)
Country Subject Description Units Scale 2000 2001 2002 2003 2004
Albania Gross domestic product per capita current prices US dollars Units 1083988 1238206 1396172 1757778 2229712
Albania Inflation annual percent change Percent 00 31 52 24 34
Bangladesh Gross domestic product per capita current prices US dollars Units 329310 327980 344494 369495 393717
Bangladesh Inflation annual percent change Percent 22 15 38 54 64
Benin Gross domestic product per capita current prices US dollars Units 361340 368213 405951 494725 560129
Benin Inflation annual percent change Percent 42 40 24 15 26
Bosnia and Herzegovina Gross domestic product per capita current prices US dollars Units 1255837 1321429 1466090 1807392 2070508
Bosnia and Herzegovina Inflation annual percent change Percent 50 32 03 02 09
Cambodia Gross domestic product per capita current prices US dollars Units 276413 280352 296577 305940 321247
Cambodia Inflation annual percent change Percent -08 02 33 12 20
Ecuador Gross domestic product per capita current prices US dollars Units 1227711 1590267 1804362 1957183 2082156
Ecuador Inflation annual percent change Percent -77 377 126 79 32
Egypt Gross domestic product per capita current prices US dollars Units 1550982 1461431 1278462 1188060 1083158
Egypt Inflation annual percent change Percent 28 24 24 32 52
India Gross domestic product per capita current prices US dollars Units 454206 458849 472915 542554 602625
India Inflation annual percent change Percent 40 38 43 38 47
Kazakhstan Gross domestic product per capita current prices US dollars Units 1236159 1490946 1655148 2000598 2579554
Kazakhstan Inflation annual percent change Percent 134 83 59 64 68
Kyrgyz Republic Gross domestic product per capita current prices US dollars Units 278256 306130 321079 349632 380637
Kyrgyz Republic Inflation annual percent change Percent 187 69 21 31 45
66
Mexico Gross domestic product per capita current prices US dollars Units 5957486 6274468 6425203 6111754 6377064
Mexico Inflation annual percent change Percent 95 64 50 45 44
Morocco Gross domestic product per capita current prices US dollars Units 1161302 1162154 1199584 1432725 1541041
Morocco Inflation annual percent change Percent 19 06 28 12 20
Pakistan Gross domestic product per capita current prices US dollars Units 437381 400356 440471 492913 538120
Pakistan Inflation annual percent change Percent 44 31 32 29 46
Philippines Gross domestic product per capita current prices US dollars Units 979423 900225 950707 963765 1018710
Philippines Inflation annual percent change Percent 43 61 31 30 54
Russia Inflation annual percent change Percent 208 215 158 137 103
Senegal Gross domestic product per capita current prices US dollars Units 478704 474460 507408 634171 714622
Senegal Inflation annual percent change Percent 09 30 23 -00 08
Serbia and Montenegro Gross domestic product per capita current prices US dollars Units 1031263 1389384 1882036 2491799 2795805
Serbia and Montenegro Inflation annual percent change Percent 699 911 212 113 79
Sri Lanka Gross domestic product per capita current prices US dollars Units 846811 796025 828256 904330 982466
Sri Lanka Inflation annual percent change Percent 62 142 96 63 64
Tunisia Gross domestic product per capita current prices US dollars Units 2034360 2065140 2149421 2534823 2881273
Tunisia Inflation annual percent change Percent 30 19 28 28 34
Uganda Gross domestic product per capita current prices US dollars Units 293404 249682 279587 280802 287204
Uganda Inflation annual percent change Percent 45 -20 57 51 35
67
References
Akerlof George A The Market for ldquoLemonsrdquo Qualitative Uncertainty and the Market Mechanism in Quarterly Journal of Economics Vol 84 (1970) pp 488-500
Amin Ruhul et al Integration of an Essential Service Package (ESP) in Child and Reproductive Health and Family Planning with a Micro-Credit Program for poor Women Experience from a Pilot Project in Rural Bangladesh in World Development Vol 29 (2001) No 9 pp 1611-1621
Bester Helmut Screening vs Rationing in Credit Markets with Imperfect Information in The American Economic Review Vol 75 (1985) No 4 pp 850855
Borst Dietmar Microfinance ndash Theoretische Grundlagen fuumlr den Einsatz sowie die Abschaumltzung des Potentials anhand einer Datenbankuntersuchung zur Verwundbarkeit der laumlndlichen Bevoumllkerung in Vietnam unpublished diploma thesis Karlsruhe 2004
BRAC Annual Report 2002 Dhaka 2003
Busch Alexander Kort Katharina Die Peanuts-Banker und ihre Kunden in Handelsblatt Nr 150 published August 5th 2004 p 8
Campion Anita Challenges to Microfinance Commercialization in Journal of Microfinance Vol 4 (1999) No 2 pp 57-65
Chu Michael Key Issues of Development Finance Somerville (MA) 1998
Dornbusch Ruumldiger Fischer Stanley Makrooumlkonomie Oldenburg 1995
Dunn Seth Flavin Christopher Moving the Climate Change Agenda Forward in State of the World New York London 2002 pp 24-50
Farrington Todd Efficiency in Microfinance Institutions in The MicroBanking Bulletin Issue No 4 pp 18-24
Gardner Gary The Challenge for Johannesburg Creating a More Secure World in State of the World New York London 2002 pp 3-23
Ghatak Subrata On Interregional Variations in Rural Interest Rates in Journal of Developing Areas Issue 18 pp 21-34
Gibbons David Serving the Poorest Sustainably in The MicroBanking Bulletin Issue No 5 (2000) pp 13-16
Gibbons David Meehan Jennifer W The Microcredit Summitrsquos Challenge WorkingToward Institutional Financial Self-Sufficiency While Maintaining a Commitment to Serving the Poorest Families in Journal of Microfinance Vol 1 (1999) No 1 pp 131-192
68
Goodwin-Groen Ruth Do Asian MFIs Access Funds from Commercial Banks inThe MicroBanking Bulletin Issue No 3 pp 8-10
Grameen Bank (ed) Grameen Generalized System Dhaka 2003
Gross Alexandra de Silva Samantha Social Fund Support of Microfinance A Reviewof Implementation Experience The World Bank Social Protection Discussion Paper No 0215 Washington DC 2002
Hashemi Syed M Schuler Sidney R Sustainable Banking with the Poor A Case Study of Grameen Bank Dhaka 1997
Helms Brigit Reille Xavier Interest Rate Ceilings and Microfinance The story so farConsultative Group to assist the Poor Occasional Paper No 9 September 2004 Washington DC 2004
Hoff Karla Stiglitz Joseph E Introduction Imperfect Information and Rural Credit Markets-Puzzles and Policy Perspectives in The World Bank Economic Review Vol 4 (1990) No 3 pp 235-250
Holcombe Susan Managing to Empower The Grameen Bankrsquos Experience of Poverty Allevation Dhaka 1995
Hulme David Mosley Paul Finance against Poverty London 1996
Jalvaani (ed) Flush with loans Micro credit for rural sanitation Vol 2 (1999) No 2 pp 1-2
Khandker Shahidur R Fighting Poverty with Microcredit Experience in Bangladesh Oxford et al 1998
Khandker Shahidur R Khalily Baqui Khan Zahed Grameen Bank Performance andSustainability The World Bank Discussion Paper No 306 Washington DC 1995
Lipsey Rechard G An Introduction to Positive Economics 5th edition London 1979
Littlefield Elizabeth Morduch Jonathan Hashemi Syed M Is Microfinance an Effective Strategy to Reach the Millennium Development Goals Consultative Group to Assist the Poorest Focus Note No 24 Washington DC 2003
Martinot Eric Cabraal Anil World Bank Solar Home Systems Projects Experience and Lessons Learned 1993-2000 in Renewable Energy Oxford 2000 pp 1-8
M-Cril Microfinance Review 2003 revised February 2004 Gurgaon 2004a
Mezzera Jaime Microcredit in Brazil The Gap Between Supply and Demand in The MicroBanking Bulletin Issue No 8 (2000) pp 22-24
The MicroBanking Bulletin (ed) Note to the Reader Vol 1 (1997) Issue No 1 pp 5-8
69
The MicroBanking Bulletin (ed) An Introduction to the Peer Groups and Tables Issue No 9 (2003) pp 53-60
MicroRate IADB Performance Indicators for Microfinance Institutions Technical Guide 3rd edition Washington DC 2003
MkNelly Barbara Dunford Christopher Impact of Credit with Education on Mothers and Their Young Childrenrsquos Nutrition Lower Pra Rural Bank Credit with Education Program in Ghana Freedom from Hunger Research Paper No 4 Davis (CA) 1998
MkNelly Barbara Dunford Christopher Impact of Credit with Education on Mothers and Their Young Childrenrsquos Nutrition CRECER Credit with Education Program in Bolivia Freedom from Hunger Research Paper No 5 Davis (CA) 1999
Morduch Jonathan The Microfinance Promise in Journal of Economic Literature Vol 37 (1999b) No 4 pp 1569-1614
Neus Werner Einfuumlhrung in die Betriebswirtschaftslehre Tuumlbingen 1998
Otero Maria Bringing Development Back into Microfinance Journal of Microfinance Vol 1 (1999) No 1 pp 8-19
Panjaitan-Drioadisuryo Rosintan D M Cloud Kathleen Gender self-employment and microcredit programs An Indonesian case study in The Quarterly Review of Economics and Finance Vol 39 (1999) pp 769ndash779
Perkins Dwight H et al Economics of Development 5th edition New York London 2001
Pitt Mark M Khandker Shahidur R Credit Programs for the Poor and the Health Status of Children in Rural Bangladesh in International Economic Review Vol 44 (2003) No 1 pp 87-118
Raiffeisen Friedrich W The Credit Unions 8th edition Neuwied 1966
Rhyne Elizabeth The Yin and Yang of Microfinance Reaching the Poor and Sustainability in The MicroBanking Bulletin Issue No 2 (1998) pp 6-9
Richardson David C Unorthodox Microfinance The Seven Doctrines of Success in The MicroBanking Bulletin Issue No 4 (2000) pp 3-7
Robinson Marguerite S The Microfinance Revolution Sustainable Finance for the Poor Washington DC 2001
Robinson Marguerite S The Microfinance Revolution Volume 2 Lessons from Indonesia Washington DC 2002
Rosenberg Richard Microcredit Interest Rates Consultative Group to assist the Poorest Occasional Paper No 1 revised November 2002 Washington DC 2002
70
Roth Michael Steinwand Dirk Mikrofinanz Weltweites Erfolgsmodell nur nicht inDeutschland Zur Uumlbertragbarkeit der Erfahrungen aus Entwicklungslaumlndern auf Deutschland Deutsche Gesellschaft fuumlr Technische Zusammenarbeit (ed) Eschborn2004
Schmidt Reinhard H Tschach Ingo Microfinance as a Nexus of Incentives Finance and Accounting Working Paper No 87A Frankfurt 2001
Schreiner Mark A Framework for the Analysis of the Performance and Sustainability of Subsidized Microfinance Organizations with Application to Banco Sol of Bolivia and Grameen Bank of Bangladesh unpublished PhD dissertation Columbus (O) 1997
Seibel Hans D Recent Developments in Microfinance Development Research Center Working Paper No 1998-5 Cologne 1998
Seibel Hans D History matters in microfinance in Small Enterprise Development ndashAn International Journal of Microfinance and Business Development Vol 14 (2003a) No 2 pp 10-12
Seibel Hans D Schmidt Petra How an Agricultural Development Bank Revolutionized Rural Finance The Case of Bank Rakyat Indonesia International Fund for Agricultural Development Rural Finance Working Paper B 5 Rome 2000
Sen Amartya Oumlkonomie fuumlr den Menschen ndash Wege zu Gerechtigkeit und Solidaritaumlt in der Marktwirtschaft Muumlnchen Wien 2000
Serageldin Ismail The View of the Chair in Consultative Group to Assist the Poorest Newsletter Issue No1 (1996) pp 1 11-12
Soros George Die Krise des globalen Kapitalismus Offene Gesellschaft in Gefahr Berlin 1998
Staschen Stefan Regulation and Supervision of Microfinance Institutions State of Knowledge Deutsche Gesellschaft fuumlr Technische Zusammenarbeit (ed) Eschborn 1999
Steinwand Dirk The Alchemy of Microfinance The Evolution of the IndonesianPeoples Credit Banks (BPR) to 1999 and a Contemporary Analysis Berlin 2001
Stiglitz Joseph E Peer Monitoring and Credit Markets in The World Bank Economic Review Vol 4 (1990) No 3 pp 351-366
Stiglitz Joseph E Weiss Andrew Credit Rationing in Markets with Imperfect Information in The American Economic Review Vol 71 (1981) No 3 pp 393-410
Tschach Ingo Theorie der Entwicklungsfinanzierung Mit Kleinkreditprogrammen Kredit- und Arbeitsmarktsegmentierung uumlberwinden Frankfurt 2000
UNDP Human Development Report 2004 New York 2004
71
UNFPA state of the world population 2004 New York 2004
UNICEF The State of the Worldrsquos Children 2002 NewYork Geneva 2002
Varley Robert C G Financial Services and Environmental Health Household Credit for Water and Sanitation Environmental Health Project Applied Study No 2 Washington DC 1995
Volkery Carsten Kampf um Straszligenhaumlndler in Die Zeit Nr 23 published May 27th
2004 p 33
Wardhana Ali Introduction in The Microfinance Revolution ndash Sustainable Finance for the Poor Washington DC 2001 pp XVII-XXVII
Woodworth Warner Woller Gary Greetings from the Editors Journal of Microfinance Vol 1 (1999) No 1 p 6
The World Bank Group World Development Indicators 2004 Washington DC 2004
Worldwatch Institute (2002) Vital Signs 2002 New York London 2002
Wimmer Nancy Barua Dipal Less is more Microfinance for solar energy in rural areas in Renewable Energy World Review Issue 2004-2005 Vol 7 (2004) No4 pp 170-179
Yunus Muhammad Grameen Bank II ndash Designed to Open new Possibilities Dhaka 2002
Yunus Muhammad Grameen ndash Eine Bank fuumlr die Armen dieser Welt Muumlnchen 1998a
Internet References
Abishek Lal (nd) An Overview of Microfinance and Environmental Management [http wwwgdrcorgicmenvironabhishekhtml] (availability date October 5 2004)
ACCION (nd) our history [httpwwwaccionorgabout_our_historyasp] (availability date October 5 2004)
ACCION (nd) key statistics [httpwwwaccionorgabout_key_statsasp] (availability date October 5 2004)
Ahmad Zulfiqar (nd) Forms of Regional Cooperation in Microfinance in South Asia [httpwwwbwtporgarcmpakistanIV_News_and_EventsBWTPworkshopZulfiqar20Ahmad20paper20(BWTP-PMN2029Jan04)pdf (availability date October 6 2004)
72
Ahmed Salehuddin (2003) Foreword [httpwwwpksf-bdorgaprm_summit_brochure htm] (availability date September 30 2004)
Annan Kofi (2002) Statement at The Microcredit Summit +5 [httpwww microcreditsummitorgenews2003-03_sp_chowdhuryhtml) (availability date October 5 2004)
Barnes Carolyn (2001) Microfinance Program Clients and Impact An Assessment of Zambuko Trust Zimbabwe [httpwwwmicrofinancegatewayorgfiles18553_Barnes_Zambuko_Trust_2001pdf] (availability date October 5 2004)
Barnes Carolyn Gaile Gary Kibombo Richard (2001) The Impact of Three Microfinance Programs in Uganda [httpwwwmicrofinancegatewayorgfiles2935_Barnes_2001pdf] (availability date October 5 2004)
Barua Dipal (2004) Success of Grameen Shakti in the Field of Renewable Energy Sector in Bangladesh [httpwwwrenewables2004depptPresentation1-SessionVA(14-1530h)-Baruapdf] (availability date September 30 2004)
Bhatt Ela (1997) In 1975 [httpwwwmicrocreditsummitorgdeclarationhtm] (availability date September 30 2004)
BlueOrchard (2004a) Microfinance [httpwwwblueorchardchenmicrofinance_institutions asp] (availability date October 5 2004)
BlueOrchard (2004b) January 2004 Newsletter [httpwwwblueorchardchmedialibrarywebsitenewsletter_jan_2004pdf] (availability date October 5 2004)
Brynjolfsson John (2004) John Brynjolfsson Discusses Recent Trends in TIPS Issuance [httpwwwpimcocomLeftNavPIMCO+Spotlight2004Spotlight_2_04htm] (availability date October 5 2004)
CGAP (2003) Report to the Board of Executive Directors [httpwww-wdsworldbankorgservletWDSContentServerWDSPIB20031208000012009_20031208101736RenderedPDF27441pdf] (availability date October 5 2004)
Chen Shaohua Ravallion Martin (2004) How have the worldrsquos poorest fared since the early 1980s [httpwwwworldbankorgresearchpovmonitorMartinPapersHow_have_the_poorest_fared_since_the_early_1980spdf] (availability date October 5 2004)
Cheston Susy Kuhn Lisa (2002) Empowering Women through Microfinance[httpwwwmicrofinancegatewayorgfiles3240_Cheston_2002doc] (availability date October 5 2004)
Christen Robert P et al (1995) Maximizing the Outreach of Microenterprise FinanceAn Analysis of Successful Microfinance Programs [httpwwwdecorgpdf_docsPNABS519 pdf] (availability date October 5 2004)
73
CIA (2004) The World Factbook [httpwwwciagovciapublicationsfactbook] (availability date October 5 2004)
Clear Profit (2004) Microfinance Bond Record May Double [httpwwwclear-profitcomissuescpsep04txt] (availability date September 30 2004)
Daley-Harris Sam (2003) State of the Microcredit Summit Campaign Report 2003 [httpwwwmicrocreditsummitorgpubsreportssocr2003SOCR03-E[txt]pdf] (availability date September 30 2004)
Dominiceacute Robert (2004) Interview in Microfinance Bond Record May Double [httpwwwclear-profitcomissuescpsep04txt] (availability date September 30 2004)
Donahue Jill Kabbucho Kamau Osinde Sylvia (2001) HIVAIDSmdashResponding To A Silent Economic Crisis Among Microfinance Clients In Kenya and Uganda [httpwwwmicrosave-africacomget_fileaspdownload_id=541] (availability date September 30 2004)
Donahue Jill Sussman Linda (1999) Building a Multi-Sectoral Response Follow-Up Assessment of Programming for Children and Families Affected by HIVAids in Kenya [httpwwwdecorgpdf_docspnacg778pdf] (availability date September 30 2004)
The Economist (1998) [httpwwweconomistcomdisplaystorycfmstory_id=S2629H3C28Q13F240A] (availability date September 30 2004)
Finca (nd) Introduction [httpvillagebankingorgwhereindexphp3] (availability date September 30 2004)
Fischer Stanley (2003) Statement at The Asia Society and Womens World BankingAnnual Microfinance Conference [httpwwwiiecomfischerpdffischer051303pdf] (availability date September 30 2004)
Friedman Milton (nd) Samuha [httpwwwsamuhaorgm-1htm] availability date September 30 2004)
FXTOP (2004) Historical Exchange Rates [httpfxtopcomdehistoratesphp3] (availability date September 30 2004)
Gibbons David Meehan Jennifer W (2002) Financing Microfinance for Poverty Reduction [httpwwwmicrocreditsummitorgpapersfinancing_finalpdf] (availability date September 30 2004)
Grameen Bank (2004) Grameen Bank At a Glance [httpwwwgrameen-infoorgbankcdshtml] (availability date September 30 2004)
Grameen Trust (nd) Grameen Bank Replication Program [httpwwwgrameen-infoorggrameengtrustreplicationhtml8721] (availability date September 30 2004)
74
Hossain Farhad (2004) Microfinance in Development [httpwwwvalthelsinkifi staff jkoponenb1104FarhadFeb2304pdf] (availability date October 5 2004)
IMF (2004) Data [httpwwwimforgexternalpubsftweo200402datadbginimcfm] (availability date October 5 2004)
IMI (2004) Investments [httpwwwimi-agcomoverviewindexhtml] (availability date September 30 2004)
IPCC (2001) Summary for Policymakers [httpwwwipccchpubspm22-01pdf] (availability date September 30 2004)
Jansson Tor Wenner Mark (1997) Financial Regulation and its Significance for Microfinance in Latin America and the Caribbean [httpwwwgdrcorgicmgoverniadb-janssonpdf] (availability date October 5 2004)
Ken Daniel Ten Roeun Van (2004) The Cycle of Debt - As Microcredit Institutions Grow Some Question Their Effect on Poverty [httpwwwcamnetcomkhcambodiadaily selected_featurescd-21-02-04htm] (availability date September 30 2004)
Kim Julia (2002) Social Interventions for HIVAIDS - Intervention with Microfinance for AIDS and Gender Equity [httpwwwwitsaczaradarPDF20filesIntervention_monograph_no_picspdfpdf] (availability date September 30 2004)
Llanto Gilberto (nd) Vietnam [httpwwwadborgDocumentsBooksCentral_Banks_MicrofinanceCountry_Studiesvietnampdf] (availability date September 30 2004)
The Microfinance Gateway (nd) Frequently Asked Questions [httpwwwmicrofinance gatewayorgsectionfaq1] (availability date October 5 2004)
Microfinance Rating and Assessment Fund (2004) Qualified Raters [httpwwwmfrating orgmfi_institutionsqualified_ratershtml] (availability date October 5 2004)
Microcredit Summit (1997) Declaration and Plan of Action [httpwwwmicrocreditsummit orgdeclarationhtm] (availability date September 30 2004)
MicroRate (nd) Performance Indicators and Ratios [httpwwwmicroratecomENGLISHsiteRATINGSindicatorshtml] (availability date September 30 2004)
MicroRate (2002) The Finance of Microfinance [httpwwwmicroratecomPDFFinance20of20Microfinancepdf] (availability date September 30 2004)
MicroRate (2004) Adjusted comparison table [httpwwwmicroratecomENGLISHsitePDFAdjusted20Comparison20Table060320engpdf] (availability date October 5 2004)
75
Mix Market (2004) The Mix Market [httpwwwmixmarketorg] (availability date October 5 2004)
Morduch Jonathan (1999b) The Grameen Bank A Financial Reckoning [httpwwwwwsprincetonedu~rpdsmacarthurdownloadsmorduch_grameen_bankpdf] (availability date September 30 2004)
Pallen Dean (1997) Environmental Sourcebook for Micro-Finance Institutions [httpwwwacdi-idagccaINETIMAGESNSFvLUImagesea20summaries$fileSOURC Epdf] (availability date September 30 2004)
Prisma (2002) The Case for Private Capital Market Creation in the Development Field of Microfinance [httpwwwsocialenterprisenetpdfsprivate_capital_marketpdf] (availability date September 30 2004)
Schmidt Reinhard H Zeitinger C-P (1997) Critical Issues in Microbusiness Finance and the Role of Donors No 6 [httpwwwgdrcorgicmmfi-donorpdf] (availability date September 30 2004)
Seibel Hans D (2003b) Commodity finance a commercial proposition Micro- and Mesofinance for Agricultural Commodity Production Processing and Trade [httpwwwuni-koelndeew-fakaef05-20042003-420Commodity20Financepdf] (availability date September 30 2004)
Simanowitz Anton Walter Alice (2002) Ensuring Impact Reaching the Poorest while Building Financially Self-sufficient Institutions and Showing Improvement in the Lives of the Poorest Families [httpwwwidsacukimpactPublicationsWorkingPapersOP3MCSSumdoc] (availability date September 30 2004)
Smith Stephen C Jain Sanjay (1999) Village Banking and Maternal and Child Health Theory and Evidence from Ecuador and Honduras[httphomegwuedu~scsmith healthrevwd801pdf] (availability date September 30 2004)
United Nations (1999) International Year of Microcredit 2005 [httpods-dds-nyunorgdoc UNDOCGENN9976933PDFN9976933 pdfOpenElement] (availability date October 5 2004)
United Nations (2000) United Nations Millennium Declaration [httpods-dds-nyunorgdocUNDOCGENN0055951PDFN0055951pdfOpenElement] (availability date October 5 2004)
US Census Bureau (2004) Total Midyear Population for the World 1950-2050 [httpwwwcensusgovipcwwwworldpophtml] (availability date October 5 2004)
WHO (2004) Making pregnancy safer [httpwwwwhointmediacentrefactsheets fs276en] (availability date September 30 2004)
WHO (2001) Child Health [httpwwwwhointmipfiles2082AAGChildHealthpdf] (availability date September 30 2004)
76
The World Bank Group (nd) Health Nutrition and Population and the Millennium Development Goals [www1worldbankorghnpMDGMDG20-20HNPbookletpdf] (availability date September 30 2004)
Yunus Muhammad (1998) Championing the Right to Credit for Poor Women Around the World [httpaspgrameencom dialoguedialogue34interviewhtml] (availability date September 30 2004)
UNAIDS (2004) [httpwwwunaidsorgbangkok2004GAR2004_pdfUNAIDSGlobalReport2004_enpdf] (availability date September 30 2004)
Ratings
M-Cril (2000) SPANDANA [httpwwwratingfundorgspanishdocsSPANDANA_RatingReportpdf] (availability date October 7 2004)
M-Cril (2001a) BASIX [httpwwwbasixindiacomMcrilasp] (availability date October 7 2004)
M-Cril (2001b) BDB [httpwwwratingfundorgspanishdocsRF_BDBpdf] (availability date October 7 2004)
M-Cril (2001c) SNEHA [httpwwwratingfundorgspanishdocsRF_Sneha-u1pdf] (availability date October 7 2004)
M-Cril (2002a) KCLF [httpwwwratingfundorgdocsRF-KCLF-risk20reportdoc] (availability date October 7 2004)
M-Cril (2002b) NWTF [httpwwwratingfundorgspanishdocsRF_NWTFpdf] (availability date October 7 2004)
M-Cril (2002c) SEEDS [httpwwwratingfundorgspanishdocsRF_SEEDS_2002_Ratingpdf] (availability date October 7 2004)
M-Cril (2002c) Share [httpwwwratingfundorgspanishdocsRF_SHAREpdf] (availability date October 7 2004)
M-Cril (2002d) TSKI [httpwwwratingfundorgspanishdocsRF_Tski_mcrilfinal(-) reportpdf] (availability date October 7 2004)
M-Cril (2003a) ASA [httpwwwratingfundorgdocsASA20updatepdf] (availability date October 7 2004)
M-Cril (2003b) BURO [httpwwwm-crilcomburopdf] (availability date October 7 2004)
M-Cril (2003c) EMT [httpwwwratingfundorgdocsEMTpdf] (availability date October 7 2004)
77
M-Cril (2003d) SKS [httpwwwmixmarketorgendemanddemandshowprofileaspett=25ampshowinfo=adjusted] (availability date October 7 2004)
M-Cril (2003d) TPC [httpwwwratingfundorgdocsTPC_Finalpdf] (availability date October 7 2004)
M-Cril (2004b) UPAP [httpwwwratingfundorgdocsUPAP_2004pdf] (availability date October 7 2004)
Microfinanza (2002a) ACME [httpwwwratingfundorgspanishdocsACME_finalpdf] (availability date October 7 2004)
Microfinanza (2002b) BTFF [httpwwwratingfundorgspanishdocsBTFF_RatingReportpdf] (availability date October 7 2004)
Microfinanza (2002c) BESA [httpwwwratingfundorgspanishdocsBESA_RatingReportpdf] (availability date October 7 2004)
Microfinanza (2002d) CAME [httpwwwratingfundorgdocsEvaluacionCAME(-) Finaldoc] (availability date October 7 2004)
Microfinanza (2002e) RFF [httpwwwratingfundorgdocsRFF20finalpdf] (availability date October 7 2004)
Microfinanza (2002f) PSHM [httpwwwratingfundorgspanishdocsPSHM_Reportpdf] (availability date October 7 2004)
Microfinanza (2003) CAJCA [httpwwwratingfundorgdocsCalificacion_Jardin_Azuayo_ratingpdf] (availability date October 7 2004)
Microserve (2003) ENDA [httpwwwmixmarketorgendemanddemandshowprofileaspett=865ampshowinfo=adjusted] (availability date October 7 2004)
Planet Rating (2002a) FONDEP [httpwwwmfratingorgRatingscompleted_ratingshtml] (availability date October 7 2004)
Planet Rating (2002b) PRIZMA [httpwwwmixmarketorgendemanddemandshowprofileaspett=111ampshowinfo=adjusted] (availability date October 7 2004)
Planet Rating (2002c) SWS [httpwwwratingfundorgspanishdocsSWC_reportpdf] (availability date October 7 2004)
Planet Rating (2002d) ZAKOURA [httpwwwratingfundorgspanishdocsRF_Zakourapdf] (availability date October 7 2004)
Planet Rating (2003a) AMSSF [httpwwwratingfundorgdocsPlanetRating_AMSSF_010803pdf] (availability date October 7 2004)
Planet Rating (2003b) FOCCAS [httpwwwratingfundorgdocsPlanetRatingFOCCAS120803pdf] (availability date October 7 2004)
78
Planet Rating (2003c) PADME [httpwwwmfratingorgdocsPlaNetRatingPADME070302_Englishpdf] (availability date October 7 2004)
Planet Rating (2003d) PAPME [httpwwwmfratingorgdocsPAPME_PlanetRating080903pdf] (availability date October 7 2004)
Planet Rating (2003e) VITAL FINANCE [httpwwwmfratingorgdocsVital20Finance_Sept202003pdf] (availability date October 7 2004)
Planet Rating (2004a) ABA [httpwwwratingfundorgdocsABA_April202004pdf] (availability date October 7 2004)
Planet Rating (2004b) ACEP [httpwwwmfratingorgdocsACEPSeacuteneacutegal_2004pdf] (availability date October 7 2004)
Planet Rating (2004c) AGROINVEST [httpwwwratingfundorgdocsAgroInvest_June202004pdf] (availability date October 7 2004)
Planet Rating (2004d) ASBA [httpwwwratingfundorgdocsASBA_April202004pdf] (availability date October 7 2004)
Planet Rating (2004e) DBACD [httpwwwratingfundorgdocsDBACD_April202004pdf] (availability date October 7 2004)
Planet Rating (2004f) FINADEV [httpwwwmfratingorgdocsFinadev_2004pdf] (availability date October 7 2004)
Planet Rating (2004g) MI-BOSPO [httpwwwratingfundorgdocsMIBOSPO_160404pdf] (availability date October 7 2004)
Planet Rating (2004h) SBACD [httpwwwratingfundorgdocsSBACD_PlanetRating300604pdf] (availability date October 7 2004)
Other Sources
Interview Shaw Newaz Deputy General Manager of the Grameen Bank October 30th
2003
Hodson Charles (2001) Your Business Your World Jim Boulden CNN (ed) Dhaka 2001
3
Figures
Figure 1 Expected Bank Return and the Interest Rate 32
Figure 2 The extended Model 34
Figure 3 Marginal Productivity of Capital 36
Figure 4 The extended Model 39
Figure 5 Loan Size vs Interest Rate 48
Figure 6 Interest Rate vs PAR 49
Figure 7 Interest Rate vs FSS 50
4
Acronyms
BDB Bank Dagan Bali
BRAC Bangladesh Rural Advancement Committee
BRI Bank Rakyat Indonesia
CF Cost of Funds
CGAP Consultative Group to Assist the Poor(est)
FSS Financial Self-Sufficiency
GDP Gross Domestic Product
GNP Gross National Product
I Interest Rate
IADB Inter-American Development Bank
II Investment Income
IMI Internationale Mikro Investitionen Aktiengesellschaft
IPCC Intergovernmental Panel on Climate Change
K Capitalization Rate
LL Loan Loss
MBB MikroBanking Bulletin
MDG Millennium Development Goal
MFI Microfinance Institution
NGO Non Governmental Organization
NGS Net Gains to Society
PAR Portfolio at Risk
TA Transaction Costs
UN United Nations
USA United States of America
5
1 Introduction
The poor stay poor not because they are lazy but because they have no access to
capital1 If this claim made by nobel laureate Milton Friedman actually holds will be
discussed in the initial part of this paper
First a short overview of the development of the microfinance sector will be given
showing that the concept of providing financial services to low income people is much
older than still believed by many development practitioners and bankers around the
world This is important since it underlines the contribution that microfinance
institutions (MFIs) can make to the development of the financial sector in their
respective countries Subsequently the various ways how such services can assist low
income people will be discussed demonstrating that even the poorest can benefit from
the provision of small loans This is a view that is still questioned in the academia
In the second part of this paper it will be shown that although some 10000
organizations are involved in microfinance already2 they are not even close to meet the
tremendous demand for low scale financial services This sector is still widely neglected
by for profit investors and traditional bankers After examining why these groups
continue to avoid investments in the microfinance industry it will be checked if the
assumptions that underline their arguments actually hold The possibility if MFIs could
raise their interest rates to an extend that would allow them generate profits sufficiently
high to attract for profit investors will be discussed
According to Hulme and Mosley MFIs ldquocan either go for growth and put their resources
into underpinning the success of established and rapidly growing institutions or go for
poverty impact and put their resources into poverty-focused operations with a higher
risk of failure and a lower expected returnrdquo3 If this is true will be examined in the third
part by checking if poor borrowers are able to bear interest rates significantly above
1 See Friedman (nd)2 See BlueOrchard (2004a)3 See Hulme and Mosley (1996) p 206
6
those charged by conventional banks Finally a sample of 39 MFIs will be used to verify
the drawn conclusions by examining the effects their interest rates have on their
financial performances and their repayment record
7
2 The Development of Microfinance
21 What is Microfinance
According to the Journal of Microfinance the term defines what ldquois arguably the most
innovative strategy to address the problems of global povertyldquo4 This view is shared by
the United Nations (UN) which declared that the year 2005 would be the international
year of microcredit5 while their General Secretary Kofi Annan stated in 2002 that
ldquo[m]icrocredit is a critical anti-poverty tool and a wise investment in human capitalrdquo6
Hossain describes microfinance as ldquothe practice of offering small collateral free loans
to members of cooperatives who otherwise would not have access to the capital
necessary to begin a small business or other income generating activitiesrdquo7 This view is
to narrow since it not only excludes such services as saving accounts and insurances8
but also ignores the possibility of collateral demanding MFIs Although it is true that
many MFIs do not take collateral especially if they are focusing on the poorest which
normally do not possess any collateral9 several MFIs in fact do require some form of
collateral10
Roth and Steinwand give a more general definition They describe microfinance as ldquothe
provision of a wide range of financial services like saving accounts loans payment
services and insurances for people with no regular access to financial services through
traditional financial institutionsrdquo11 Here it is important not to confuse the terms
traditional or conventional with the term formal If for example an illiterate beggar
takes a $10 loan from the Grameen Bank in Bangladesh she becomes a client of a
4 See Woodworth and Woller (1999) p 65 See United Nations (1999) p 16 Annan (2002)7 Hossain (2004)8 See The Microfinance Gateway (nd) Robinson (2001) p9 Otero (1999) p 89 See chapter 3 for a more detailed discussion on poverty10 See Robinson 2002 p 24311 See Roth and Steinwand (2004) p 2 ldquodie Bereitstellung einer breiten Palette von Finanzdiensteistungen wie Spareinlagen Kredite Zahlungsverkehr und Versicherungsleistungen fuumlr Wirtschaftsakteure die keinen regelmaumlszligigen Zugang zu Finanzdienstleistungen durch klassische Finanzinstitutionen habenldquo
8
formal financial institution (a registered bank) but obviously not of a traditional or
conventional one12
Although the other services have become more important in recent years microcredit is
still considered their central service by most MFIs In many countries it refers to loans
below $ 100013 however for significant cross country comparison it is more
meaningful to look at the ratio of the loan amount to the gross national product (GNP)
or gross domestic product (GDP) per capita for the respective countries While a loan of
$1000 is more than four times larger than the GNP per capita in Uganda it represents
less than 20 of the GNP per capita in Mexico The MicroBanking Bulletin (MBB) has
categorized the target market for MFIs by the average outstanding loan amount as a
percentage of the GNP per capita ranging from Low-end (less than 20) to Small
Business (more than 250)14 Especially for the latter category one must to look closely
at the condition of the financial service market where an institution is active Although
MFIs exist in industrialized countries15 one would definitely turn to a traditional
financial institution for a loan bigger than 250 of the GNP per capita and therefore not
to a MFI according to the definition presented above
22 The Origin of Microfinance
Although neither of the terms microcredit or microfinance were used in the academic
literature nor by development aid practitioners before the 1980s or 1990s16
respectively the concept of providing financial services to low income people is much
older
While the emergence of informal financial institutions in Nigeria dates back to the 15th
century17 they were first established in Europe during the 18th century as a response to
the enormous increase in poverty since the end of the extended European wars (1618 ndash
12 See Yunus (2002) p 19 for a more detailed description of the destitute member program of the Grameen Bank which focuses exclusively on persons with no regular income and no assets at all 13 See MicroBanking Bulletin (1997) p 614 See MicroBanking Bulletin (2003) p 5415 See Yunus (1998a) pp 229 et sqq16 See Robinson (2001) p XXX17 See Seibel (2003a) p 12
9
1648)18 In 1720 the first loan fund targeting poor people was founded in Ireland by the
author Jonathan Swift19 After a special law was passed in 1823 which allowed charity
institutions to become formal financial intermediaries a loan fund board was established
in 1836 and a big boom was initiated Their outreach peaked just before the government
introduced a cap on interest rates in 1843 At this time they provided financial services
to almost 20 of Irish households20
The credit cooperatives21 created in Germany in 1847 by Friedrich Wilhelm Raiffeisen
served 14 million people by 191022 He stated that the main objectives of these
cooperatives ldquoshould be to control the use made of money for economic improvements
and to improve the moral and physical values of people and also their will to act by
themselvesrdquo23
In the 1880s the British controlled government of Madras in South India tried to use the
German experience to address poverty which resulted in more than nine million poor
Indians belonging to credit cooperatives by 194624 During this same time the Dutch
colonial administrators constructed a cooperative rural banking system in Indonesia
based on the Raiffeisen model25 which eventually became Bank Rakyat Indonesia
(BRI) now known as the largest MFI in the world26
23 Microfinance after the Second World War
Because of further prudential regulation and effective supervision eg through bank
superintendencies the banking sector in the now developed world experienced
continuous growth Today the vast majority of the citizens of the industrialized
countries have access to financial services with many of them being customers of
former MFIs27
18 See Steinwand (2001) p 5119 See Robinson (2002) p 9620 See Seibel (2003a) p 1021 first known as Darlehnsvereine and now called Raiffeisenbanken22 See Morduch (1999a) p 157323 Raiffeisen (1966) quoted in Richardson (2000) p 324 See Morduch (1999a) p 157425 See Robinson (2002) p 9726 See Roth Steinwand (2004) p 327 See Seibel (2003a) p 11
10
This is not true for most developing countries where market penetration of financial
institutions is far from reaching the majority of the inhabitants (see chapter 4) A variety
of reasons is responsible for this including that the banking sector in the most
developing countries have developed in a very different way to than those in
industrialized countries
One of the most important reasons is that in contrast to the industrialized countries little
attention has been paid to the legal recognition prudential regulation and effective
supervision of informal financial institutions28 This insecure legal environment leads to
several problems Since the regulatory framework for mobilizing savings often does not
fit the needs of institutions targeting low income people many organizations are not
permitted to do so and are therefore missing funds to on-lend as credit29 An additional
problem is the lack of a deposit insurances This not only increases the risk of a bank
run but also keeps people from depositing their savings in a financial institution30 In
addition inappropriate interest rate ceilings prevail in many countries While politics
claim they are lowering the interest rates charged to the poor they de facto only limit
their access to financial services (see chapter 5)31
Another problem that retarded the growth of the financial sector in developing countries
was the supply-leading finance theory which dominated the development strategies of
many countries after the second world war32 This theory ldquo refers to the provision of
loans in advance of the demand for credit for the purpose of inducing economic
growthrdquo33 Since it was believed that poor people were neither able to save (and thus
dependent on outside funding) nor capable of paying commercial rates of interest
massive subsidized credit programs were established34 The results were alarming
Repayment rates often did not exceed 50 percent and some government financed
programs even had default rates of more than 90 percent35 The main reason being that
credit was not provided according to business management principles but instead
28 See Seibel (1998) p 829 See Robinson (2001) p 4930 See Staschen (1999) p 1431 See Gibbons (2000) p 1532 See Morduch (1999a) p 157033 Robinson (2001) p 14034 See Borst (2004) pp 33 et sqq35 See Yunus (1998a) p 154 Robinson (2001) p 145
11
according to political objectives Therefore receiving loans was seen as a reward for the
constituents rather than as a business transaction Most of the funds earmarked for the
poor also never reached them ending up instead in the hands of the local elites
Attracted by the below market interest rates and the possibility not to pay back at all
these groups lobbied to be treated privileged and often used the money received for
consumption or for on-lending at higher rates36 But subsidized credit not only
encouraged corruption it also discouraged sustainable financial institutions since they
could not compete with interest rates that were not aimed to cover all costs and were
sometimes even lower than the interest paid on savings37 The low or negative spread
also worked as a negative incentive to institutionsrsquo effort to mobilize savings which in
turn intensified the problem of credit rationing (see chapter 5)
24 Microfinance Today
In the 1970s a paradigm shift started to take place The failure of subsidized government
or donor driven institutions to meet the demand for financial services in developing
countries let to several new approaches Some of the most prominent ones are presented
below
Bank Dagan Bali (BDB) was established in September 1970 to serve low income people
in Indonesia without any subsidies and is now ldquowell-known as the earliest bank to
institute commercial microfinancerdquo38 While this is not true with regard to the
achievements made in Europe during the 19th century it still can be seen as a turning
point with an ever increasing impact on the view of politicians and development aid
practitioners throughout the world In 1973 ACCION International a United States of
America (USA) based non governmental organization (NGO) disbursed its first loan in
Brazil39 and in 1974 Professor Muhammad Yunus started what later became known as
the Grameen Bank by lending a total of $27 to 42 people in Bangladesh40 One year
later the Self-Employed Womenrsquos Association started to provide loans of about $15 to
36 See Robinson (2001) pp 144 et sqq37 Before BRI underwent a major transformation in 1983 a negative spread between interest rates on loans and savings existed While the bank lent at a 12 annual effective interest rate it paid 15 on savingsSee Robinson (2001) p 10638 Wardhana (2001) p XXVII39 See ACCION (nd)40 See Yunus (1998a) p 16 et sqq
12
poor women in India41 Although the latter examples still were subsidized projects they
used a more business oriented approach and showed the world that poor people can be
good credit risks with repayment rates exceeding 9542 even if the interest rate charged
is higher than that of traditional banks Another milestone was the transformation of
BRI starting in 1984 Once a loss making institution channeling government subsidized
credits to inhabitants of rural Indonesia it is now the largest MFI in the world being
profitable even during the Asian financial crisis of 1997 ndash 199843
In February 1997 more than 2900 policymakers microfinance practitioners and
representatives of various educational institutions and donor agencies from 137
different countries gathered in Washington DC for the first Micro Credit Summit This
was the start of a nine year long campaign to reach 100 million of the world poorest
households with credit for self employment by 200544 According to the Microcredit
Summit Campaign Report 67606080 clients have been reached through 2527 MFIs by
the end of 2002 with 41594778 of them being amongst the poorest before they took
their first loan45 Since the campaign started the average annual growth rate in reaching
clients has been almost 40 percent46 If it has continued at that speed more than 100
million people will have access to microcredit by now and by the end of 2005 the goal
of the microcredit summit campaign would be reached As the president of the World
Bank James Wolfensohn has pointed out providing financial services to 100 million of
the poorest households means helping as many as 500 ndash 600 million poor people47
41 See Bhatt (1997)42 See Yunus (1998a) p 143 et sqq43 See Robinson (2002) p 38044 See Daley-Harris (2003) p 345 ldquoThe Microcredit Summit Campaign defines ldquopoorestrdquo as those who are in the bottom half of those living below their nationrsquos poverty line or are living on less than $1 a day adjusted for purchasing power parity (PPP)rdquo See Daley-Harris (2003) p 3 This definition will also be used throughout this paper46 See Daley-Harris (2003) p 1847 See Morduch (1999a) p 1570
13
3 The Impact of Microcredit
31 Microcredit and the Millennium Development Goals
In 1996 Ismail Serageldin the then chair of the Consultative Group to Assist the Poorest
(CGAP)48 claimed that ldquo[m]icrofinance is a proven instrument to assist the very poorrdquo49
This view is also shared by the World Watch Institute50 and underlines what has been
stated above namely that microfinance can be used as a strong anti-poverty tool But
does microfinance actually meet these expectations and keep this promise51
The impact that microcredit has on the lives of poor people will be demonstrated by
showing how it contributes to each of the eight Millennium Development Goals
(MDGs)52 which are related to the reduction of poverty in all its forms These goals
were resolved in September 2000 by the General Assembly of the UN in their
Millennium Declaration53
32 The Eradication of extreme Poverty and Hunger
The aim of the first MDG is to halve the proportion of people who live on less than $1 a
day between 1990 and 2015 According to current population projections of the World
Bank54 this would equal 849 million people in 201555
48 The Consultative Group to Assist the Poorest is a consortium of 28 public and private development agencies working together to expand access to financial services for the poor in developing countries and was established by the World Bank in 1995 Recently it changed its name to Consultative Group to Assist the Poor49 See Serageldin (1996) p 1150 See Gardner (2002) p 1851 See Morduch (1999a) pp 1569 et sqq52 The Millennium Development Goals are (1) eradicate extreme poverty and hunger (2) achieve universal primary education (3) promote gender equality and empower women (4) reduce child mortality (5) improve maternal health (6) combat HIVAIDS malaria and other diseases (7) ensure environmental sustainability and (8) develop a global partnership for development53 See United Nations (2000)54 See World Bank (2004) p 38 et sqq55 Although it is not explicitly mentioned in the Millennium Declaration it is commonly assumed that the share of people living on less than $1 in low and middle income countries should be halved If the share would be calculated with regard to the worldrsquos total population the goal for 2015 would 818 million people For the worldrsquos total population in 1990 see US Census Bureau (2004)
14
Today almost 11 billion people live on less than $1 and more than 27 Billion live on
less than $2 per day56 The mean income for those living under $1 a day is $077 and it
is $125 for those living under $2 a day57 While the number of people living on less
than $1 per day is slowly decreasing and is expected to be 913 million in 2015 the
number of people living on less than $2 a day is actually increasing58 One of the
outcomes from this degree of poverty is that more than 27000 children die every day
from mostly preventable diseases many of them related to hunger59
Microcredit enables poor people to start new businesses or to diversify existing ones
which helps them to increase their income In addition to large amounts of anecdotal
evidence several studies have documented the positive economic impact microcredit
has on its clients Cloud and Panjaitan-Drioadisuryo have found that the average income
of a sample of BRI borrowers has increased by 112 percent and that 90 percent of their
families have crossed the poverty line60 Only 12 out of the 121 respondents of that
study reported that their income had not increased61 According to the Grameen Bank
website 5109 percent of their clients have crossed the poverty line since they took their
first loan62
A study conducted by Barnes showed that the program of the Zambuko Trust a local
MFI in Zambia had a considerable impact on the poorest clients consumption of meat
fish and chicken63 While 76 percent of the continuing clients of the MFI called Share in
India significantly increased their income and 50 percent have crossed the poverty line 64 Khandker discovered in his well known study ldquoFighting poverty with microcreditrdquo
that there is a connection between the microcredit programs of three Bangladeshi MFIs
and household per capita expenditure For every dollar borrowed by a Grameen Bank
member household consumption increases by $018 In addition he found that 5 percent
56 See Chen and Ravallion (2004) p 2957 In fact those people live on less than $108 and $215 respectively a day in 1993 PPP This means that the nominal dollar value of their income is considerably lower See Chen and Ravallion (2004) p 9 58Both numbers are decreasing in Asia but increasing in the rest of the world See Chen and Ravallion (2004) p 22 et sqq59 See UNICEF (2002) p 660 A consistent definition of the term ldquopoverty linerdquo does not exists among different nations Therefore the term will be used according to the definition of the respective country in this paper61 See Panjaitan-Drioadisuryo and Cloud (1999) p 77562 See Grameen Bank (2004) 63 See Barnes (2001) p 8664 See Simanowitz and Walter (2002) p 16
15
of Grameen Bank borrowers move out of poverty every year65 Supposing Khandkerrsquos
findings were correct for all MFIs worldwide and the Microcredit Summit Campaign
achieved its goal of reaching 100 million of the poorest households with microcredit by
2005 then 25 million people (assuming an average family size of five) would leave
poverty every year66 Although this number would have to be adjusted in order take into
consideration the MFI clients who have crossed the poverty line already and of course
the experiences made in Bangladesh can not be transferred precisely to other countries
it still demonstrates the enormous effect that microcredit can have on assisting the
poorest to move out of poverty
Although a 1996 study of Hulme and Mosley states that providing microcredit can also
have a negative impact on the income of the poorest households67 these findings can
be considered as disproved by the recent bulk of evidence drawing favorable
conclusions68
33 Achievement of universal primary Education
The aim of the second MDG is to ensure that all children will be able to complete
primary school by 2015
Currently more than 100 million children most of them girls are not in school69
Besides school fees poor households often can not afford to send their children to
school because they need them to help in the family business
Microcredit programs mainly contribute to the second MDG by increasing families
income and therefore enabling parents to send their children to school Barnes Gaile
and Kibombo found that clients of an MFI in Uganda spent significantly more on
childrenrsquos education than non-clients70 and in Zambia Barnes showed that ongoing
participation in the Zambuko Trustrsquos program had a positive impact on the members
65 See Khandker (1998) p 5666 See Daley-Harris (2003) p 2467 See Hulme and Mosley (1996) p 180 et sqq 68 See Gibbons and Meehan (1998) p 13669 See UNICEF (2002) p 2270 See Barnes Gaile and Kibombo (2001) p 64
16
children staying in school71 In Bangladesh the probability of girls enrolling in school
increased by 19 percent for every 1 percent increase in Grameen Bank loans to female
clients For boys this number was even higher with the mean being 24 percent72
34 Promote gender Equality and empower Women
The aim of the third MDG is to eliminate the disparity in the ratios of girls to boys in
primary secondary and tertiary education in the ratio of literate females to males and to
increase the share of women in the labor market and in parliament73
At present the literacy rate for women is lower than for man all over the world
According to the Human Development Report 2004 the average female literacy rate as
a percentage of male literacy rate is 759 in developing countries and is as low as 37 in
Niger74 But women are not only discriminated against in education but also in access to
medical services and therefore have a higher mortality rate than man75 The worldwide
tendency for women to be underrepresented in the labor market and in the parliaments is
even more severe in developing countries76 Although several women have become
heads of state in various Asian countries (eg Bangladesh India and Indonesia) this is
probably due to them being wives or daughters of former respected male politicians
Since women have a higher repayment rate than man77 and also tend to invest increases
in income on the household and on their children rather than on themselves78 most
MFIs prefer female clients79 Therefore they empower women in many ways Often
MFIs not only encourage women to become involved in financial transactions for the
first time but also to become independent active members of the economy and to
acquire assets in their own names Cheston and Kuhn found that 68 percent of the
women participating in an MFI program in Nepal ldquohellip experienced an increase their
71 See Barnes (2001) p 8472 See Khandker (1998) p 4973 See World Bank (2001) p 2074 See UNDP (2004) pp 225 et sqq75 See Sen (2000) p 23276 See Sen (2000) pp 242 et sqq77 See Littlefield Morduch and Hashemi (2003) p 778 See Yunus (1998a) pp 116 et sqq79 According to the Microcredit Summit Campaign Report 79 or 37677080 of the poorest clients were women See Daley-Harris (2003) p 3
17
decision-making roles in the areas of family planning childrenrsquos marriage buying and
selling property and sending their daughters to school - all areas of decision making
traditionally dominated by menrdquo80 The program of the Lower Pra Rural Bank in Ghana
had an positive impact on womenrsquos participation in the community81 which is true as
well for the CRECER program in Bolivia82 In Bangladesh the Grameen Bank and the
Bangladesh Rural Advancement Committee (BRAC) the two biggest MFIs of the
country had a significant positive effect on womenrsquos empowerment measured through
eight different indicators83 After joining Grameen Bank only 21 percent of the female
members considered themselves as unemployed while this number was 50 percent
before joining84 According to the Grameen Bank website 93 percent of the Bankrsquos
shares are owned by their borrowers which elect the members of the board every three
years They also get familiar with the election process by more frequently voting for
representatives at the lower level of the organizational structure Partly because of this
experience they are more likely to run for public office In the 2003 local government
elections Grameen Bank members constituted 24 of the seats reserved for women
while they represent less than 10 of Bangladeshi adult female population85 Female
clients of MFIs from countries like the Philippines Bolivia and Nepal have reported
similar occurrences86
35 Reduce Child Mortality and improve Maternal Health
The aim of the fourth MDG is to reduce the under-five mortality rate by two-thirds
between 1990 and 2015 and the fifth MDG strives for a three quarter reduction in the
maternal mortality ratio by the same date
As has been stated above more than 10 million children are dying annually in the
developing world of mostly preventable causes with malnutrition playing a role in over
80 See Cheston and Kuhn (2002) p 1881 See MkNelly and Dunford (1998) p 5482 See MkNelly and Dunford (1999) p 7183 The eight different indicators are ldquofreedom of movement economic security ability to make small and larger independent purchases participation in important family decisions relative freedom from domination by the family political and legal awareness and participation in political campaigning and public protestsrdquo Hashemi and Schuler (1998) p 3684 See Holcombe (1995) p 5185 See Grameen Bank (2004)and CIA (2004)86 See Littlefield Morduch and Hashemi (2003) p 8
18
half of the childrsquos deaths and in over 50 countries child mortality rates are greater than
100 deaths per 1000 live births87 Maternal mortality is also a significant problem in the
developing world with more than 500000 women dying every year from pregnancy
related causes88
MFIs are mainly contributing to the these MDGs by increasing families income and
therefore enabling the households to afford better nutrition and medical services
Furthermore they are often linked with microinsurance or health education programs
In addition to what has been showed in chapter 31 Pitt Khandker and Millimet
estimate that a 10 percent increase in the loan size of a female borrower in Bangladesh
increases the arm circumference of their daughters by 6389 Smith and Jain found that
village banking in Ecuador had a positive effect on child diarrhea90 which is responsible
for 15 of child deaths91 Since Sen argues that an improved status of women within
the family reduces child mortality92 the empowerment of women through MFIs is also
contributing to this cause
Although no study has been conducted so far on the direct impact of microcredit on
maternal health it can be assumed that an overall improvement of access to medical
services reduces maternal mortality as well A study of the Morgan State University for
example suggests that microcredit has a positive effect on the prevalence of
contraceptives93 which leads to a decrease of unwanted pregnancies and therefore
reduces maternal death
36 Combat HIVAIDS Malaria and other diseases
The aim of the sixth MDG is to halt and begin to reverse by 2015 the spread of
HIVAIDS malaria and other major diseases and to assist children orphaned by HIV
87 See World Bank (2001) p 888 See WHO (2004) 89 See Pitt Khandker and Millimet (2003) p 11390 See Smith and Jain (1999) p 3791 See WHO (2001) 92 See Sen (2000) p 23593 See Amin et al (2001) p 1614
19
In 2003 29 million people died because of HIV and about 48 million became infected
the greatest number since AIDS was discovered 23 years ago94 This pandemic has lead
to a tremendous decrease in the life expectancy in the hardest hit countries Botswana
for example one of the richest and most democratic countries in Africa has a
HIVAIDS adult prevalence rate of 388 and a life expectancy at birth of less than 31
years95
Malaria not only causes more than one million deaths annually it leads also to 300 ndash
500 million clinical cases a year Both numbers have been steadily increasing over the
past two decades96 More than two million people a year are killed by tuberculosis
another global health problem This curable disease is estimated to cost poor
communities about $12 billion every year since even those who survive normally lose
more than 3 month of work time while recovering97
MFIs contribute to the sixth MDG in several ways By increasing clientrsquos income they
help households affected by HIV or other diseases to better cope with the situation
Besides spending more money on health services and nutrition MFI clients also tend to
be more able and willing to support AIDS orphans than non clients98 In addition to the
already stated increase in the use of contraceptives99 several innovative approaches to
deal with disease related crisis have also arisen This is of course necessary not only to
counteract the devastating effect the above discussed epidemics can have on MFI
clients but also to not put the viability of the respective institution at risk One option is
to integrate education services in the MFI programs and encourage clients to form
solidarity groups100 It has been shown that these services do not necessarily decrease
the effectiveness of the institutionsrsquo employees101 Another way is to strengthen the ties
to NGOs specialize in dealing with the respective disease Synergies gained through this
cooperation can help clients to better deal with the situation and in the end increase their
94 See UNAIDS (2004) p 2395 See CIA (2004)96 See World Bank (2001) p 1697 See World Bank (2001) p 1298 See Barnes (2001) p 6499 See also Kim et al (2002) p 18100 See Donahue and Sussman (1999) p A 14101 See Donahue Kabbucho and Osinde (2001) p 25
20
repayment rates Various MFIs also have introduced loan and health insurance products
or cultivated linkages with organizations doing so102
It has to be stated that despite the benefits MFIs can provide to people effected by
HIVAIDS or other diseases microcredit can also be a burden for those who are already
chronically ill These people can still benefit through loans provided to members of the
family or the community or through one of the other services mentioned above
37 Ensure environmental Sustainability
The aims of the seventh MDG are to support and promote the principles of sustainable
development and put them into action and to improve the lives of slum dwellers and
people without sustainable access to safe drinking water and sanitation
Today climate change is considered as the major environmental problem103 The
Intergovernmental Panel on Climate Change (IPCC) states that human activities
contribute to most of the 06 degC increase in global average temperature over the 20th
century and the predicted increase of another 14 to 58 degC between 1990 and 2100104
Emission of carbon from fossil fuel is reported to have the dominant influence on this
development While the total emission was 16 billion tons in 1950 it was already 65
billion tons in 2000 and is expected to continue to grow105 This development would
lead to a rise in the average sea level of between 9 and 88 centimeters during the next
century106 Furthermore it is predicted that global warming increases the risk of extreme
events like cyclones or floods leads to an increase in the number of people infected by
diseases like malaria and decreases the potential crop harvest and water availability
especially in developing countries107 In 2000 already 11 billion people lacked access to
clean drinking water and 24 billion to basic sanitation108
102 See Barnes (2001) p 40 Barnes Gaile and Kibombo (2001) p 13 and Grameen Bank (2004)103 See Gardner (2002) p 5104 See IPCC (2001) pp 2 et sqq105 Worldwatch Institute (2002) p 52 et sqq106 See IPCC (2001) p 16107 See Dunn and Flavin p 29108 See UNFPA (2004) p 18
21
MFIs contribute to achieving the seventh MDG in several ways By providing loans for
the purchase of renewable energy technologies they help people in developing
countries to increase their per capita energy consumption without increasing the carbon
dioxide emission In a 2003 survey of 140 MFIs from 80 different countries 21 said
they provide credits for solar home systems and another 19 stated they are interested in
becoming engaged in this business109 While Grameen Shakti a rural energy service
company cooperating with the Grameen Bank in Bangladesh has already installed more
than 23000 solar home systems110 a 2000 World Bank study reports twelve projects
providing solar home systems to rural households with a target of 500000
installations111 It has also been suggested that MFIs should raise environmental
awareness among their clients112 but so far no data is available on how staff can cope
with this additional task Many MFIs also provide loans for improvements in sanitation
and the water supply of their clients Varley gives several examples from Africa Asia
and Latin America on how microcredit not only has helped to invest in rainwater
collection systems but also how it has enabled households to increase their water
supply through community water associations113 In addition many MFIs provide credit
for the construction of sanitary latrines114 The situation of slum dwellers is also
positively effected by MFIs Directly through their services in poor urban communities
and indirectly by creating jobs in rural areas and therefore easing the pressure on urban
labor markets
38 Develop a global Partnership for Development
The eight MDG is about the means to achieve the other seven MDGs It calls for all
players involved in the endeavor of development and poverty eradication to work as
partners in a global context
Again MFIs are contributing to the eight MDG in many ways This is occurring through
international networks that provide funding and technical assistance through internet
information portals and specialized journals through social and for profit investors and
109 See Wimmer and Barua (2004) p 174110 Barua (2004) 111 See Martinot and Cabraal (2000) p 6112 See Pallen (1997) p 11 Lal (nd)113 See Varley (1995) pp 39 et sqq114 See Jalvaani (1999) pp 1 et sqq Varley (1995) pp 39 et sqq
22
specialized rating agencies The Bangladesh-based Grameen Trust is one of around 30
networks in operation Besides collaborating with over 200 MFIs around the world it
has directly operated three projects in Afghanistan Kosovo and Myanmar115 While the
ACCION network serves almost 12 million active clients in 19 countries throughout
America and sub-Saharan Africa116 FINCArsquos network operates in three different
continents where it serves more than 200000 customers117 In November 1997 the
MicroBanking Bulletin (MBB) was first published by the microfinance program at the
Economic Institute at the University of Colorado118 Its aim is to develop a database on
the financial performance of MFIs from all over the world which is now available
through the Mix Market an internet portal that also provides information about more
than 300 MFIs investors donor institutions and other related development
organizations119 Two years later the Marriott School at Brigham Young University
started to publish the Journal of Microfinance which has an editorial board of
microfinance experts from all over the world and offers the latest research on this
topic120 In the late 1990s a number of companies became attracted by the microfinance
market and started to invest in MFIs The German based Internationale Mikro
Investitionen Aktiengesellschaft (IMI) for example has already invested more than euro46
million in 19 MFIs in four different continents and plans to invest another euro27 million
before October 2004121 BlueOrchard Finance a microfinance investment consultancy
has channeled more than $60 million worth of private capital to some 40 MFIs
worldwide through investment funds and bond issues122 Big commercial banks like
Citigroup Deutsche Bank and ABN Amro also started to get involved in the
microfinance sector although this is mainly still perceived as a public relation activity
and not as a for-profit investment123 There are also several rating agencies specializing
in MFIs Dependent on their rating these institutions can help MFIs to receive money
from donors or investors Four of the most prominent rating agencies are PlanetFinance
115 See Grameen Trust (nd)116 See ACCION (nd)117 See FINCA (nd)118 See MicroBanking Bulletin (1997) p 5119 See The Mix (2004)120 See Woodworth and Woller (1999) p 6121 See IMI (2004)122 See BlueOrchard (2004b) p 3123 See Busch and Kort (2004) p 8 Fischer (2003) p 6
23
with headquarters in France M-Cril based in India Microfinanza in Italy and
MicroRate with offices in the USA and South Africa124
124 See Microfinance Rating and Assessment Fund (2004)
24
4 Microcredit Outreach
41 The Demand for Microcredit
Although it has been shown that microcredit is one of the most effective poverty
eradication tools that it is considered a human right by some of its advocates125 and it
can contribute considerably to the development of the financial sector in developing
countries an enormous gap still exists between supply and demand for microcredit
Estimates on the demand for microcredit vary greatly While USAID estimates the
number of potential microfinance clients is between 100 and 200 million126 the
Microcredit Summit Campaign states the total demand is more than 234 million
people127 CGAP recognizes some 500 million micro-entrepreneurs who have the
potential to become customers of MFIs128
Marguerite Robinson calculates the demand as follows ldquoAssuming five people to a
household among the 45 billion people living in low- and lower-middle-income
economies in 1999 (World Bank World Development Report 20002001) there are 900
million households in those economies If estimating conservatively we assume that
informal commercial moneylenders supply credit to 30 percent of these households at
least once a year this would mean that there are 270 million households borrowing
from informal moneylenders in a year Undoubtedly however many of these
households borrow multiple times within a yearrdquo129 Although this is a very rough
estimate assuming big differences in demand for microcredit in different countries the
number seems to be the most meaningful In contrast to the estimate of the Microcredit
Summit Campaign it does not include every single household living on less than $1 a
day but according to the definition presented in chapter 1 it counts everyone who has
no regular access to traditional financial institutions but demands such services
Obviously not all people who draw on moneylenders have financial needs that could be
matched through MFIs On the other hand interest rates charged by moneylenders tend
125 See Yunus (1998b) 126 See Christen et al (1995) p 15127 See Daley Harris (2003) p 22 128 See Robinson (2001) p 26129 See Robinson (2001) p 215
25
to be considerably higher than those of MFIs The former normally charge effective
monthly rates between ten and several hundred percent per month the latter generally
charge between 15 and five percent which enables them to attract additional clients130
42 The Supply of Microcredit
In spite of the impressive growth of MFIs around the world the demand for microcredit
is far from being met and this it is not likely to change in the near future The
Microcredit Summit Campaign reported that by the end of 2002 67606080 clients131
were reached through MFIs and that this number has increased by almost 40 percent
annually for the last five years132 It is likely that this tremendous speed of growth is at
least partly due to including MFIs which have not been reporting to the Campaign from
its start in 1997 although they have already existed at that time These institutions
contributed 22 percent to the growth in poorest clients in 2000 578 percent in 2001 and
338 percent in 2002 The growth of the poorest clients increased at least party because
of an expanded definition of the term ldquopoorestrdquo133 Since the contribution of MFIs
which previously have not been considered can be expected to decrease dramatically
the growth rate as stated by the Microcredit Summit Campaign can not be used to
predict the future development of the microfinance sector Another factor likely to slow
down the growth is the concentration of microfinance activities in some Asian countries
where almost 90 percent of the poorest microfinance clients live today134 Even if one
takes into consideration the relative size of Asiarsquos population and the fact that many
MFI customers in Latin America are relatively better off and therefore are not included
in this numbers the coverage of this part of the world far exceeds the others In
Bangladesh for example the microfinance market is close to saturation More than
eleven million households were served by several hundred MFIs in 2001135 Among
them are Grameen Bank and BRAC two of the best known MFIs in the world both
providing their services to more than three million customers With an average
household size of five it can be assumed that in Bangladesh the number of people
130 See Gibbons and Meehan (1999) pp 144 et sqq131 41594778 of them belonged to the poorest before they took their first loan The relative numbers in the following are for these poorest clients only since no other current data was available It can be assumed though that this works as a good proxy for the total number of clients 132 See Daley Harris (2003) p 3133 See Daley Harris (2003) p 17134 See Daley Harris (2003) p 21135 See Ahmed (2003)
26
benefiting from microcredit already surpasses the number of people living below the
poverty line which is estimated to be slightly higher than 50 million136 Therefore
Bangladesh will not contribute to the growth of the microfinance sector as much as it
has done in previous years This is also true for Vietnam Thailand and to a lesser
extent Indonesia Eight of the nine MFIs serving more than one million clients are based
in these countries while the ninth is based in India where due to its one billion
inhabitants the microfinance market is still far from saturation137 In contrast the
supply in Brazil meets less than two percent of the demand which is estimated to be
about 58 million potential clients138 For these reasons greater amount of future growth
must come from smaller or new MFIs in Latin America India China and especially
Africa where almost 30 percent of the worldrsquos poorest live139
43 Meeting the Demand
To fill the gap between the demand and supply for microcredit tremendous investments
are necessary to increase the loan funds of MFIs and build up their capacity through
upgrading existing institutions or building new ones Again estimates on how much
capital is needed vary greatly with the highest being at more than $300 billion140
In 1997 the Microcredit Summit Campaign estimated that $216 billion would be
needed to achieve their goal of providing microcredit to 100 million of the poorest
households This was calculated in the following way Since some 8 million people
already received microcredit in 1997 another 92 million needed to be reached
Assuming $200 ($150 for loan fund and $50 for capacity building) would be needed per
person for 88 million people in developing countries and $1000 ($500 for loan fund and
$500 for capacity building) would be needed for 4 million people in industrialized
countries the capital required ends up to be $216 billion141 For several reasons this
136 See CIA (2004)137 These institutions are The Grameen Bank BRAC Proshika and the Association for Social Advancement (ASA) in Bangladesh the Vietnam Bank for Agriculture and Rural Development (VBARD) and the Vietnam Bank for the Poor (VBA) in Vietnam BRI in Indonesia Bank for Agriculture and Agricultural Co-operatives (BAAC) in Thailand the National Bank for Agriculture and Rural Development (NABARD) in India See Ahmed (nd) p 1 Llanto (nd) p 337138 See Mezzera (2002) p 23139 See See Chen and Ravallion (2004) p 29140 See Clear Profit (2004) Prisma (2002)141 See The Microcredit Summit (1997)
27
number is not qualified to predict the total amount of capital needed to meet the demand
for microcredit On the one hand it focuses mainly on the low end of the market and
therefore underestimates the average loan fund needed On the other hand it does not
take the increasing capital demand from established MFIs into account A survey of 119
MFIs found that the average loan size to increased from $406 in 2002 to $498 in
2003142 This is mainly due to the fact that MFI clients once they have paid back their
loans usually demand larger ones for the continual development of their businesses
and therefore further increase the demand for capital of established MFIs The Grameen
Bank for example has a ceiling on its loans which increases or decreases depending on
the borrowers performance regarding repayments and savings143 While the maximum
amount for the first loan is fixed at approximately $75144 the largest loan disbursed so
far was $17195145 Thus if one estimates that by now 100 million people are borrowing
from MFIs146 another 170 million need to be reached to meet the estimated demand
Assuming an average of $600 ($400 for loan fund and $200 for capacity building) is
needed for every new client and another $200 is needed for every existing client to meet
the demand for larger loans a total of $122 billion is required This rough estimate
helps to convey the approximate amount of capital needed to meet the demand for
microcredit
So far the demand for funds is being partly met by donors which annually provide
between $500 million and $1 billion147 and through the mobilization of local savings
Obviously the amount of money provided by donors will not be able to meet the capital
demand for microcredit in the short term The mobilization of savings on the other hand
has been extremely successful in some cases with BRI probably being the most
prominent example After adapting commercial principals in October 1984 BRI was
able to raise its deposits from $161060 to more than $32 billion in 2003 which equals
almost two times its current loan portfolio148 Many other MFIs like BDB in Indonesia
142 Own calculations Without BRI the numbers would be $343 and $409 See Appendix 1143 See Grameen Bank (2003) p 13144 The accurate amount is 5000 Taka See Interview with Shaw Newaz145 Grameen Bank (2004)146 According to the data provided by the Daley Harris (2003) an annual increase in MFI clients ofapproximately 25 percent from 31122002 till the 3092004 would be needed to reach 100 million clients by now This rated is considerably below the average of the previous five years (38 percent) Therefore it can be assumed as realistic despite the growth hindering factors presented above147 See CGAP (2003) p 8148 See Robinson (2002) p 273 Mix Market (2004)
28
XacBank in Mongolia the Equity Building Society in Kenya or the Centenary Rural
Development Bank in Uganda also have managed to cover their loan portfolio fully
through internally mobilized resources149 The Grameen Bank is also expected to do so
in the first half of 2005150 In addition to raising much needed capital for on-lending the
provision of saving services can deliver notable social benefits itself151
Despite these impressive achievements even the combination of donor money and local
savings at their current levels will not be able to provide the capital needed to continue
the rapid growth of the microfinance sector Especially in their early years MFIs rely on
outside funding BRI for example needed six years before the amount of locally
mobilized savings surpassed the total amount of outstanding loans During this time
expenses and the loan portfolio were covered through a government grant worth $20
million and two World Bank loans of $5 and $97 million respectively152 It also
benefited from a network of more than 3600 branches which were established
throughout the country during the 1970s and early 80s in order to provide government
subsidized credit in rural areas153
The Grameen Bank also widely known as a best practice MFI has received about $175
million in direct and indirect subsidies between 1985 and 1996154 and continues to rely
on outside funding at below market interest rates This is made possible either through
special loans from the Bangladesh Bank or through offering bonds guaranteed by the
Bangladesh government155 - an option most MFIs do not have BDB might be one of the
very few examples which were able to finance their activities through savings and
commercial loans from the start but its outreach did not reach a large scale nor did it
serve the low end of the market In 2000 after 30 years of operation BDB provides
credit to only 10417 clients with an average loan balance of more than $5000156
approximately eight times the countries GDP per capita157
149 See Mix Market (2004)150 See Grameen Bank (2004)151 See Robinson (2001) pp 263 et sqq152 See Seibel and Schmidt (2000) p 4153 See Robinson (2002) p 180154 See Morduch (1999b) p 8155 See Morduch (1999ba) p 25 et sqq156 See Robinson (2002) p 387157 See CIA (2004)
29
Another problem keeping many MFIs from collecting savings is that they do not want
to become a regulated financial institution or do not meet the criteria in their respective
country and therefore they are simply not allowed to mobilize savings from the public
In summary the examples and numbers presented in this chapter support the argument
that the amount of capital that can be raised through donors and locally mobilized
savings is not enough for continuous rapid growth of the microfinance sector If this
lack of capital is not met through other sources the microfinance sector will fail to
contribute its full potential to the achievement of the MDGs
44 Microfinance and the Capital Markets
Regardless of whether the amount of capital needed for the development of the
microfinance sector is $20 or $300 billion it represents only a tiny fraction of the
worldwide capital markets which are estimated at $30 trillion158 Therefore if the
microfinance industry were able to tap the financial markets it would be able to grow
much faster and soon serve the millions of micro-entrepreneurs which currently can not
develop theirs businesses because of capital constrains Another advantage would be
that scarce donor money currently used for the development of the microfinance sector
could be used for other projects that do not have the potential to draw money from
commercial sources This view is shared by Michael Chu the former CEO of ACCION
who made the following statement in 1998 ldquoMicrofinance today stands at the threshold
of its next major stage the connection with the capital marketsrdquo159 Many attempts have
been made since that time Successful MFIs like BancoSol in Bolivia further
strengthened their ties to the capital markets which in some cases already provide the
majority of their funding160 Microfinance investment advisors like BlueOrchard
Finance have become middlemen for MFIs and the financial markets Nevertheless
these links are still far from reaching major scale Currently only approximately 20
percent of MFIs funding comes from commercial sources161 and the biggest bond issue
dedicated to fund MFIs totals only $40 million In addition these funds mainly end up
158 See Brynjolfsson (2004) 159 Chu (1998) quoted in Robinson (2001) p 23160 See Robinson (2001) p 69161 See Dominiceacute (2004)
30
in established institutions in Latin America or Eastern Europe162 while smaller
organizations only benefit indirectly if at all
162 See Clear Profit (2004) IMI (2004)
31
5 Credit Rationing
Until recently the predominant answer to why commercial banks or venture capital
companies did not invest in the microfinance sector was that the poor are not bankable
Besides lacking education and therefore not being able to deal with formal financial
institutions they were viewed as bad credit risk who were unable to invest the borrowed
money in a way that would allow them to repay the loan and interest at a commercial
rate163 Another reason that kept attention away from the idea of providing financial
services to low income people was the belief that informal moneylenders already met
this demand These skeptics felt affirmed through the poor performance of subsidized
credit programs as described in chapter 22 Although it is true that moneylenders
serve a huge number of people in the developing world they more often than not charge
usury interest rates of up to 20000 percent per month164 While the argument that poor
people are not able to participate in the formal financial market can be overcome by
adapting the services accordingly165 the claim of low returns on their investments is not
only proved wrong by empirical evidence but also contradicts economic theory as will
be shown in chapter 53
51 The imperfect Information Paradigm
A more elaborate explanation for the short supply of financial services to low income
people that can be derived from the imperfect information paradigm based
predominantly on the works of Akerlof166 and Stiglitz and Weiss167 After giving a brief
summary of their argument an adaptation of their findings to the microfinance market
will be presented and subsequently it will be shown how their conclusions can be
overcome
Behind the imperfect information paradigm lies the theory of asymmetric information
which simply states that if two parties conduct a transaction one is likely to have more
163 See Ghatak (1983) p 21 et sqq Yunus (1998) p 102 et sqq Robinson (2001) p 35 et sqq164 See Robinson (2001) p 17165 See Seibel (2003b) p 2 BRAC (2003) pp 15et sqq Yunus (1998) pp 151 et sqq 166 See Akerlof (1970) pp 488 et sqq167 See Stiglitz and Weiss (1981) pp 393 et sqq
32
information than the other and is trying to use that for its own advantage168 Applied to
the banking sector this means that a person applying for credit can better judge the
likelihood of repaying the loan than the bank This is because the borrower has better
knowledge of the market she wants to invest in her skills and her willingness to repay
Moreover the bank might not be able to observe if the borrower uses the loan for the
agreed purpose These occurrences can lead to what is known as adverse selection and
moral hazard In this case adverse selection refers to the problem that banks might
attract borrowers with a low probability of repayment if they can not distinguish
between high and low risk loan applicants Moral hazard occurs after the provision of
the loan when the borrower spends the money on a purpose different to the prescribed
purpose and therefore lowers the probability of repayment This can happen eg by
investing in a more risky project or through spending the money on consumption If the
bank is not able to find a cost effective way to avoid these problems it might raise its
interest rate in order to compensate for the increased risk
Figure 1 Expected Bank Return and the Interest Rate
Source Stiglitz and Weiss (1981) p 394
Since this might discourage low risk borrowers from applying for credit and encourage
borrowers who continue to take loans to invest in riskier projects the share of high risk
168 See Neus (1998) p 85 et sqq
INTEREST RATEI
EX
PE
CT
ED
RE
TU
RN
TO
TH
E B
AN
K
33
borrowers could increase and therefore reinforce the problems stated above Thus
increasing the interest rate beyond a certain point actually leads to a decrease in the
expected return to the lender This context is illustrated in figure 1 with I being the
interest rate which maximizes the expected returns to the bank Obviously the bank
would charge the interest rate I in order to maximize its expected return However this
price for capital was not determined through supply and demand as economic theory
would predict It is conceivable that at the interest rate I the demand for credit exceeds
the supply but even if loan applicants would offer to pay a higher interest rate the bank
would refuse because it associates such a loan with high risk As a result credit might
be rationed169
52 Adaptation to the Microfinance Sector
Through some adaptations this model can also help to explain the lack of funds
provided to low income people In the original model of Stiglitz and Weiss several
assumptions have been made that need to be suspended in order to compare the credit
markets for low and high income people and give an explanation why the latter is
widely neglected by institutional investors
Evidently the assumptions that the amount borrowed is equal for each loan applicant
and that transaction costs170 need not to be taken into account171 are not suitable for this
context While the average loan size of MFI customers is much smaller than that of
clients from traditional banks the transaction costs as a share of the loan are
considerably higher because the lenderrsquos costs for conscientious processing a credit
applications are only slightly smaller for a $50 loan than for a $100000 or a
$10000000 loan
In figure 2 the R(I)large curve represents the return to the bank for large loans with
regard to the interest rate I and the R(I)small curve describes the same correlation for
small loans It is shifts downwards to reflect the assertion that the imperfect information
169 See Stiglitz and Weiss (1981) p 394170 In this paper the term bdquotransaction costsldquo refers to the operating expense ratio as defined by MicroRate It ldquois calculated by dividing all expenses related to the operation of the institution (including all the administrative and salary expenses depreciation and board fees) by the period average gross portfoliordquo See MicroRate and Inter-American Development Bank (IADB) (2003) p 16 171 See Stiglitz and Weiss (1981) p 396
34
paradigm has a more severe effect on poor people than on the better off They are
expected to have less profitable investment opportunities at their disposal172 and
therefore are more likely to invest in riskier projects which increase the probability of
default and hence decrease the expected return to the bank Additionally one might
expect poor people to be more likely than others to spend borrowed money on
consumption instead of an income generating activity particularly if a crisis arises It
seems understandable that food or urgently needed medicine are given priority over
repaying a loan
The second shift downwards is due to transaction costs As stated above they are
relatively higher for smaller loans Obviously transaction costs are incurred in the
provision of a large loan as well but since they are much smaller with regard to the loan
amount they are not included in the diagram for reasons of clarity
Figure 2 The extended Model
Source Own diagram adapted from Stiglitz and Weiss (1981) p 394
172 See Khandker (1998) p 8
INTEREST RATE I
SmallLoans
LargeLoans
Transaction costs
Lack of investment opportunities
R(I)large
R(I)small
EX
PE
CT
ED
RE
TU
RN
TO
TH
E B
AN
K
35
53 Overcoming Credit Rationing for the Microfinance Sector
If the conclusions in chapter 51 hold it is rational for a profit maximizing investor to
neglect the microfinance sector as long as no surplus funds in the market for large loans
exist This finding can help to explain the small amount of money provided to the
microfinance sector from commercial investors On the other hand it has to be stated
that this theory is reflexive as defined by Soros173 It not only explains but also forms
reality since it has the potential to reinforce the view of potential investors that
microfinance is a less profitable business174 Therefore demonstrating under which
conditions microfinance can be profitable and in some cases be more profitable than
traditional businesses is of crucial importance
To provide a fairer view of the microfinance sector a further assumption of the Stiglitz
and Weiss model that needs to be suspended is that all investments made by the
borrowers have the same expected return175 As stated above this contradicts economic
theory which claims ceteris paribus capital productivity decreases while the amount of
fixed capital increases In combination with a low capital endowment micro-enterprises
are usually faced with an excess supply of unskilled labor especially in developing
countries176 Hence small enterprises use far less capital per employee than big business
and therefore their marginal productivity of capital is much higher177 This is intuitive if
one imagines an economic actor who wants to invest several packages of capital
Obviously she would invest the first package where she expects the highest return the
second package where she expects the second highest return and so on Each additional
investment opportunity would lead to lower or at best equal returns178 While this
simplified example has limitations it demonstrates how the marginal productivity of
capital can diminish Although it might actually increase until a certain point179 this can
be expected to be so low in this context that it has no influence on the correlation as
shown in figure 2
173 See Soros (1998) pp 14 et sqq174 See Goodwin-Groen (1999) p 8175 See Stiglitz and Weiss (1981) p 395176 See Perkins et al (2001) pp 95 et sqq177 See Tschach (2000) p 8178 See Rosenberg (2002) p 11179 See Rechard G Lipsey (1979) pp 211 et sqq
36
Figure 3 Marginal Productivity of Capital
Source Dornbusch and Fischer (1995) p 406
Even if good investment opportunities for poor people exist the question remains if it is
possible to distinguish between high and low risk borrowers The problem of adverse
selection is overcome in a cost effective way in many MFIs180 For the better off poor
for example institutions like BRI base their decision on whether or not to approve a
loan by assessing the repayment ability of potential borrowers from their current income
flows and not from the uncertain returns generated by the loan181 Additionally
collateral is used in some cases to attract low risk borrowers182 In contrast to
industrialized countries this is usually not done to cover the potential losses of the
lender but to punish the defaulter and therefore increase her willingness to repay183
Obviously this does not always work for the poorest since they often neither posses any
goods that could work as collateral nor do they have sufficient earnings prior to
obtaining a loan for starting an income generating activity Here the so called group-
lending model can help to identify creditworthy borrowers The most prominent
institution using this approach is the Grameen Bank which only provides credit to
180 See Farrington (2000) p 20181 See Robinson (2001) p 80 Robinson (2002) p 238182 See Bester (1985) p 850 et sqq183 See Schmidt and Tschach (2001) p 15 Robinson (2002) p 244
FIXED CAPITAL 0
MA
RG
INA
L P
RO
DU
CT
IVIT
Y
37
members of a group of five These groups are formed by their members without
interference of the Grameen Bank Although in this particular case no joint liability
exists for the members of the group nobody can receive a new loan if another member
of the group fails to repay on time184 Therefore the group formation work as a
screening process Since the borrowers do not want to risk their ability to obtain further
loans they carefully select with whom to form a group Usually the members know
each other for a long period of time and therefore they can make a meaningful judgment
of each othersrsquo ability to repay the loan Other MFIs even require the members of a
group to mutually guarantee each othersrsquo loans185 While this might further increase
borrowersrsquo efforts to search for trustworthy group members it might also keep potential
borrowers from applying for a loan since she does not want be held responsible for
defaulting members This mechanism enables MFIs to partly pass on the transaction
costs related to the selection of low risk borrowers to the borrowers themselves186
Many MFIs have also largely overcome the problem of moral hazard by creating
incentives to ensure a high repayment rate even among the poorest In some cases their
customers go hungry in order to pay back their loan even though no legal action would
be taken against them if they would refuse to do so187 One way to achieve this is to
build up peer pressure through the formation of groups as described above188 Another
and probably the most important is to limit access to future loans to those borrowers
who repay on time The demand for successive loans is extremely high In a 1996
survey 98 percent of BRI borrowers planed to apply for another loan189 and in 1993
less than 30 percent of Grameen Bank loans went to first time borrowers190 Especially
the poorest highly value the option to reborrow191 and many MFIs see this as their
primary incentive to ensure repayment192 According to Schmidt and Tschach ldquothe net
present value of future access to credit works out to be roughly half the value of the
economic advantage to be gained from the intended non-repaymentrdquo193 This can also
184 See Yunus (1998) p 135185 See Schmidt and Zeitinger (1997) p 6186 See Stiglitz (1990) p353187 Own observation at the Grameen Bank in Bangladesh (2003)188 See Hoff and Stiglitz (1990) p 249189 See Robinson (2002) p 251190 See Khandker Khalily and Khan (1995) p 93191 See Gibbons (2000) p 15 Hashemi and Schuler (1997) p 43192 See Gibbons and Meehan (1999) p 160193 See Schmidt and Tschach (2001) p 16
38
explain the occurrence of a drop in the repayment rate once a MFI is no longer seen as
viable and therefore is not expected to provide loans in the future194
With the help of the described mechanisms MFIs around the world are able to keep
repayment rates high A survey of 69 MFIs from 36 different countries each serving
more than 10000 clients in 2002 found the portfolio at risk (PAR)195 varied between
zero and 231 percent While the average was 36 percent the median was found to be
229 percent196 One of the MFIs included in this sample is BRIs whorsquos 12-month loss
ratio has never exceeded five percent since the start of its transformation in 1984 and
from 1997 to 1998 the ratio actually fell from 22 to 194 percent197 The latter deserves
special attention because the Asian financial crisis reached its peak at that time with
Indonesia being hardest hit as illustrated by a statement from The Economist in July
1998 Even with the fierce competition from its neighbors Indonesia would probably
walk away with the prize for Asias most desperate banking systemrdquo198
The findings that MFIs can adapt their services to low income people in order to ensure
a high repayment rate and that poor people do not lack profitable investment
opportunities are illustrated in figure 4 From this diagram it can be seen that under the
new assumptions the interest rate at which the bank maximizes its return differs for
large (I(l)) and small loans (I(s)) According to the assumption that micro-
entrepreneurs can realize a higher return on their investments the bank can charge them
a higher rate of interest without bearing an increased risk Nevertheless in this example
the bank would still serve the market for large loans first because of the higher
transaction costs for smaller loans
The view as described in figure 4 is shared among most traditional banks and investors
in industrialized as well as in developing countries In addition to neglecting the
possibility of generating profits by offering microcredit themselves199 they also hesitate
to lend to MFIs because they consider their business too risky
194 See Schreiner (1997) p 64195 ldquoPAR shows the real risk of the portfolio by comparing outstanding loan balances for loans with atleast one late payment to the outstanding loan portfoliordquo Gross and de Silva (2002) p 22196 Own calculations See Appendix 2197 See Seibel (2000) p 11198 The Economist (1998) pp 92 et sqq199 Busch and Kort (2004) p 8
39
Figure 4 The extended Model
Source Own diagram adapted from Stiglitz and Weiss (1981) p 394 Tschach (2000)
p 17
This attitude can be observed by comparing the ratio of equity to liabilities which is
considerably higher for MFIs than for conventional banks200 When it comes to MFI
start-ups and those MFIs serving the low end market in remote areas even experienced
microfinance practitioners are skeptical if interest rates that fully recover all costs can
be charged201
Theoretically there are two ways to adjust this model to arrive at a conclusion which is
more favorable with regard to the profitability of microcredit One is to cut the
transaction costs and therefore reduce the downward shift of the R(I)small curve the
other is to allow the bank to further raise the interest rate without experiencing a
decrease in its return This means to increase I(s) and the respective rate of return
While in 2000 Tschach stated that transaction costs vary between 10 and 20 percent for
loans provided through the group lending model and between 15 and 30 percent for
200 See MicroRate and IADB (2003) p 30201 See Volkery (2004) p 33 Gibbons (2000) p 15 Gibbons and Meehan (2002) p 29 Goodwin-Groen (1999) p 8
INTEREST RATE I(l)
SmallLoans
LargeLoans
Transaction costs
I(s)
R(i)large
R(i)small
EX
PE
CT
ED
RE
TU
RN
TO
TH
E B
AN
K
40
individual loans202 it was recommended in 1999 that MFIs should target a range
between 15 and 25 percent203 Some best practices on the other hand have already
achieved single digit numbers Currently BDB might be the most efficient MFI in the
world with transaction costs at just 47 percent in 2001204 Even though the low costs of
BDB have to be acknowledged its achievement has to be put in perspective As stated
above with an average loan balance of more than $5000 it does not serve the low end
market In addition it works in an environment with a high population density which
means that it can reach a relatively large group of borrowers per branch This is a
comparative advantage many Asian MFIs enjoy as can be illustrated by comparing
Bangladesh and Bolivia Both countries are at the forefront of the development of
microfinance in their respective continent but while in Bangladesh more than 1000
people are living per square kilometer the average for Bolivia is only eight205
Therefore it is consistent that the most efficient MFI in Latin America Fondo
Financiero Privado para el Fomento a Iniciativas Economicas has transaction costs of
114 percent206 With an average loan size greater than the annual GDP per Capita this
institution also does not serve the low end market207
Despite the impressive efficiency gains in the described examples most MFIs are far
from achieving these numbers and many are unlikely to reach them due to the
environment within which they work A survey of 67 MFIs from 31 countries found the
average transactions costs in 2002 to be 279 percent with a median of 206 percent208
However even if these institutions were to increase their efficiency to best practice
standards their transaction costs would still be significantly higher than those of
traditional banks providing much larger loans For these banks the respective costs vary
in a range between 05 and 3 percent209 According to this argument charging interest
rates considerably higher than conventional banks is the only way for MFIs to generate
higher returns and hence successfully compete for capital
202 See Tschach (2000) pp 100 et sqq203 See Gibbons and Meehan (1999) p 149204 See M-Cril (2001b) p 4205 See CIA (2004)206 See MicroRate (2004)207 In this paper the term ldquolow endrdquo refers to the definition of the MBB (2003) p 54 Loans worth less than 20 percent of the respective countryrsquos GDP per capita are described that way 208 Own calculations See Appendix 3209 See M-Cril (2004a) p 16
41
6 Interest Rates
61 Setting the right Interest Rate
Before addressing the questions to what extend MFIs can raise their interest rates
without putting the repayment rate or the social benefits of their customers at risk a
basic model will be presented This model will illustrate how a MFI should set their
rates in order to not only cover their costs but also to generate an appropriate profit to
finance further growth and attract additional capital
In 2002 CGAP revised its 1996 paper ldquoMicrocredit Interest Ratesrdquo210 which outlines
the standard method of setting sustainable interest rates for commercially oriented
MFIs According to this model the annual effective interest rate (I) should be calculated
as shown below
(1) I = LL
IIKCFLLTA
minusminus+++
1
With each variable being a decimal fraction of the average outstanding loan portfolio
whereby TA stands for the transaction costs as described above LL represents the
annual loan loss and II stands for investment income eg on liquid assets The cost of
funds (CF) consist of the interest and administrative costs needed to obtain deposits and
commercial loans as well as of the imputed costs on equity due to inflation K stands for
the capitalization rate which represents the net real profit Keeping this rate high is
important to finance the future growth of the loan portfolio This can be either done
through investors attracted by high profitability or through borrowing For the latter an
increase in equity is inevitable since it is required as a safety cushion by lenders
Since this model ignores the timing of cash flows and does not take taxes into account
it has to be regarded as fairly imprecise and hence should not be used for business
planning Nevertheless it can be used for an approximation of the interest rate that a
MFI would need to charge to provide its services as planned In the following I will
210 See Rosenberg (2002) pp 1 et sqq
42
apply this model on a fictitious MFI working in a rural area of Latin America with low
end customers In this setting it seems realistic to estimate transaction costs of 35
percent and loan loss rate of two percent211 If funds were borrowed at commercial
terms their costs can be assumed to equal at least 15 percent of the average outstanding
loan portfolio212 Estimating the capitalization rate is more challenging First the
targeted portfolio growth rate is set at 75 percent This is slightly below the 751 percent
average annual portfolio growth between 2000 and 2002 found by a survey of 25
different MFIs based in Central and South America213 If the extend to which the MFI
can leverage stays constant the loan portfolios growth would be limited by the growth
rate of the equity To express the capital needed for this growth as a share of the loan
portfolio it is necessary to estimate the ratio between the equity and the outstanding
loan amount According to the survey mentioned above the loan portfolios of the 25
Latin American MFIs equal on average 215 times their equity214 With this number the
capital needed to increase the equity by 75 percent would corresponds to approximately
35 percent of outstanding loan amount (075215) Finally the investment income has to
be estimated Since liquid assets that are available short term do not generate high
returns say five percent it does not seem advisable for the MFI to hold more than a
quarter of its loan portfolio in this form Hence the profit generated in this way would
equal 125 percent of the outstanding loan amount Using these numbers the equation to
calculate the annual effective interest rate reads as follows
(2) I = LL
IIKCFLLTA
minusminus+++
1 =
0201
01250350150020350
minusminus+++
= 0875
As a result the MFI would need to charge an annual effective interest rate of
approximately 875 percent on its loans in order to sustainable provide its services and
finance its growth without depending on donor money This rate might decrease once
the MFI matures the growth slows down and cheaper funds become available but it
will stay significantly higher than any rate charged by conventional banks
211 MicroRate and IADB (2004) pp 6 and 16212 See MicroRate and IADB (2004) p 616 and 28213 Own calculation See Appendix 4214 Own calculations See Appendix 5
43
62 Can Micro-Entrepreneurs bear these Rates
Although most MFIs charge rates significantly below 875 percent many critics have
strenuously argued against any rates exceeding those of traditional banks Rosanna
Barbero of Oxfam labeled an interest rate of 52 percent charged by a Cambodian MFI
ldquoludicrous evil and disgusting and stated that ldquo[n]o business in the world can make a
profit at these interest ratesldquo215 The former finance minister of Bangladesh Shah Kibria
even categorized the 20 percent effective rate charged by the Grameen Bank as to
high216 Many practitioners therefore believe in a strong negative correlation between
the interest rate and the demand for loans217 Others have argued more generally that
concentrating on profitability and therefore charging high interest rates diverts MFIs
from serving the poorest218
These views are still shared among many MFI managers donor agencies and especially
investors and politicians While the former are unwilling to charge interest rates for
funds they received ldquocheaplyrdquo (through grants or subsidized loans) and are worried
about undermining their social goals by charging higher rates of interest219 the latter are
reluctant to invest for reasons stated above or impose interest caps to catch the attention
of the public by pretending to protect the poor from usury rates220
In chapter 53 it has been described that micro-entrepreneurs due to their smaller
capital endowment have even better investment opportunities than big business The
extend to which this is true has not yet been answered An indication is the high
repayment rate observed within MFIs around the globe If their customers capital yield
did not exceed the charged interest rate how would they be able to repay According to
Gibbons and Meehan customers of MFIs can generally generate returns of more than
100 percent on their invested capital221 and ldquo[r]esearch in India Kenya and the
Philippines found that the average annual return on investments in microenterprises
215 See Kate and Roeun (2004)216 See Hodson (2001) min 1100217 See Morduch (1999a) p 1594218 See Prisma (2002) p 1219 See Schreiner (1997) p 60 Khandker (1998) p 106 220 See Gross and de Silva (2002) p 32 Jansson and Wenner (1997) p 36 et sqq Campion (2002) p 59221 See Gibbons and Meehan (1999) p 131
44
ranged from 117 to 847 percentrdquo222 Schmidt and Tschach found the marginal
productivity of capital to be as high as 1000 percent for the smallest loans provided by
the Bolivian MFI Caja Los Andes223 These findings are confirmed by the observation
of Rosenberg who found while working as a microfinance consultant for ten years he
never heard of a single MFI having problems to attract clients because interest rates
were too high224
To get a better understanding of the investment opportunities of low income people in
developing countries a typical example on how MFI clients invest their loans is as
follows
Zobair is working as a rickshaw puller in Bangladesh Like most of his colleagues he
does not own the rickshaw he is riding Therefore he has to pay a daily rent of about
$030 to the owner Since his average income of approximately $15 per day is hardly
enough to feed his family he is not able to save the $100 necessary to buy a rickshaw
on his own 225 If he could do so through obtaining a loan his income would increase by
$030 every day because he would not have to pay the rent for the rickshaw anymore
Assuming an average of six working days per week 226 and a life span of the rickshaw
of 5 years his internal rate of return would equal 15324 percent annually227
Consequently any interest rate charged by a MFI would be advantageous to him as long
as it would not exceed 15324 percent228
63 Should the Interest Rate be subsidized anyway
Despite the fact that numerous micro-entrepreneurs are able to generate tremendous
returns on their investment obviously not all are able to use capital in such a productive
way and therefore can not afford microcredit at commercial rates In order to reach
these people as well many MFIs continue to use donor money in order to keep their
interest rates low But even if the problems related to subsidized credit as described in
222 See Helms and Reille (2004) p 3223 See Schmidt and Tschach (2001) p 6224 See Rosenberg (2002) p 10225 This examples draws on observations made by the author in Dhaka (Bangladesh) during 2003226 Obviously extended holidays are not a viable option in this surrounding 227 Own calculation See Appendix 6228 This result is only valid if the loan is repaid in daily instalments For a weekly repayment schedule the interest rate charged by the MFI must not exceed 15119 percent in order to still be beneficial for Zobair
45
chapter 23 do not arise it might still not be the most effective tool to help poor people
as will be illustrated in the following example
A MFI faces two groups of potential clients one with businesses able to generate a
return of 125 percent on borrowed capital and another with a possible returns of 50
percent Assuming budget costs according to equation (2) the institution needs to
charge an interest rate of 875 percent and therefore only serves the former group
Supposed each group consists of 50 members demanding $100 loans the net gains to
society (NGS) could be calculated as follows
(3) NGS = 50 times ($125 ndash $875) = $1875
These gains would be due to the investments of the more profitable group which were
made possible through the loans provided by the MFI The less profitable group would
not borrow since their expected returns are not sufficient to pay for the interest If the
interest rate would be lowered to 30 percent both groups would be able to generate net
gains and therefore borrow from the MFI In order to provide loans at this rate the
institution would need to raise additional capital from non commercial sources The
NGS would be calculated as follows
(4) NGS = 50 times ($125 - $30) + 50 times ($50 - $30) + 100 times ($30 - $875) = 0
While the first terms represent the net gains to the respective groups the last describes
the costs incurred in providing the loans At a rate of 30 percent each loan would need
to be subsidized with $575 Hence the NGS actually fall after the introduction of the
subsidized loan This is due to the fact that the less profitable group is encouraged to
invest in relatively unproductive businesses In addition future growth of the MFI could
be jeopardized due to scarce donor money which is needed to finance the interest rate
subsidy Therefore it seems more advisable to continue to charge a rate of 875 percent
and spend the money used for subsidization on other programs such as health care or
education229
229 In Appendix 7 it will be shown that this result generally holds
46
7 Empirical verification
71 Setting up a Sample
To see if the findings of the previous chapters hold the effects which interest rates
charged by MFIs have on their performance will be analyzed in the following Up to
now such a study does not exist mainly because of a lack of adequate data Most MFIs
do not provide accurate information about the annual effective interest rate they charge
and therefore make an evaluation difficult
In 2002 Rosenberg distinguished eight different categories on how microcredit interest
rates are quoted230 These categories differ in several ways On the contrary to
traditional banks for example it is common for MFIs to state interest rates calculated on
a ldquoflatrdquo balance rather than on a declining one This means that the total loan amount is
used to determine the interest rate ignoring installments paid by the borrowers normally
on a weekly or monthly basis In addition many MFIs charge a certain upfront fee prior
to the loan disbursement require compulsory savings at a lower rate or state their
interest rate for semi annual terms only On the one hand this is done to provide
numbers that are more meaningful to MFI customers who often lack the necessary math
skills to deal with compound interest on the other hand it is done to circumvent interest
rate ceilings imposed by the government231 Another problem is that most MFIs offer
different loan products without itemizing their respective shares to their total loan
portfolio As a result it is not possible to calculate a weighted average even if the rate
stated by the respective MFI could be transformed into an effective interest rate
Usually the portfolio yield is used as a proxy in order to make statements about the
interest rate charged by a certain MFI232 It is generally ldquocalculated by dividing total
cash financial revenue (all income generated by the loan portfolio but not accrued
interest) by the period average gross portfoliordquo233 The advantage of this method is that
even the hidden costs are considered Nevertheless it also has a severe shortcoming by
not taking late or defaulted payments into account Therefore the portfolio yield does
230 See Rosenberg (2002) p 5231 MicroRate (2002) p 8232 See MicroRate (nd)233 MicroRate and IADB (2003) p 39
47
not allow to draw conclusions regarding the correlation between the interest rate
charged by a MFI and its PAR
72 Examining the Sample
Through the appearance of rating agencies specialized in the microfinance sector more
adequate information has become available in recent years While MicroRate only
publishes the portfolio yield of rated MFIs M-Cril Microfinanza Microserve and
Planet Rating actually provide information about the annual effective interest rate for at
least some of the MFIs they analyze Although it is labelled differently from all of the
four institutions234 the term describes what is ldquothe highest income or yield that an
organisation can earn from its portfolio based on the terms of its loansrdquo235
Currently236 reports of 39 different MFIs from 20 countries providing accurate
information about the effective annual interest rate are available to the public This
sample should be used to verify the findings of the previous chapters237 Since a
comparison is made between the performances of MFIs based in different countries and
the ratings have been carried out in different years several adjustments are necessary
First the inflation of the respective country and the respective year(s)238 has to be taken
into account in order to only compare the real rates239 In addition the average
outstanding loan amount per borrower is divided by the respective countryrsquos GDP per
capita Since it can be assumed that ldquoonly the poorer households will be willing to take
the smallest loansrdquo240 this number can be used as a proxy for the poverty level
Although the sample size is far to small to represent the microfinance sector as a whole
and the results are statistically not significant the findings can still be used to underline
the theoretical conclusions drawn in the previous chapters In figure 5 the connection
234 M-Cril uses the name ldquoannual percentage raterdquo See eg M-Cril (2004a) p 25 Microfinanza uses the name ldquoexpected portfolio yieldrdquo See eg Microfinanza (2002c) p 25 Planet Rating uses the name ldquoannual effective interest raterdquo See eg Planet Rating (2004d) p 1 Microserve uses the name ldquotheoretical yieldrdquo See Microserve (2003) p 62235 See M-Cril (2004a) p 25236 As of September 28th 2004237 See Appendix 8 For exchange rates see FXTOP (2004)238 Where necessary a weighted average of the annual inflation rate was used See Appendix 9239 This is done through the following formula ir = (I ndash F) (1 + F100) While ir represents the real annual effective interest rate F represents the inflation rate 240 Morduch (1998) p 1572
48
between the average loan size and the transaction costs as a share of the average loan
portfolio is illustrated
Figure 5 Loan Size vs Interest Rate241
Source Own diagram
000
1000
2000
3000
4000
5000
6000
7000
8000
9000
10000
0 100 200 300 400 500 600
Loan Size
Inte
res
t R
ate
It can be seen that the interest rate is negative correlated to the loans size This can be
explained by the relative higher transaction cost for smaller loans as described in
chapter 52 In order to cover their costs MFIs serving the low end market need to
charge higher rates to their customers than those organizations serving the better off
poor Obviously there are several assumptions to this general finding Especially
striking are the two MFIs with an average loan size of approximately five times their
countries GDP per capita which still high interest rates This occurrence can be
explained by taking a closer look to the respective organizations One was established
less than two years prior to its rating and therefore still bears a lot of start up costs242
241 The equation for the regression line reads as follows Y = -00219X + 365 The correlation coefficient is 014242 See Microfinanza (2002b) p 1
49
the other managed to stay profitable while it almost quadrupled its loan portfolio in the
last two years243
Figure 6 Interest Rate vs PAR244
Source Own diagram
0
5
10
15
20
25
30
35
0 20 40 60 80 100 120
Interest Rate
PA
R
In Figure 6 the crucial correlation between the interest rates charged by a MFIs and its
PAR245 is examined According to the given sample the view of traditional banks and
investors that a higher interest rate leads to a higher default rate does not hold
Obviously one has to avoid to draw the opposite conclusion namely that a high interest
rates decreases the PAR The connection illustrated in figure 6 has to be interpreted as
follows Since high interest rates are related to small loans the low PAR for MFIs
charging high interest rates can actually be explained by the tremendous profitability of
small size investments Despite the high rates their customers are even more likely to
repay
243 See Planet Rating (2003b)244 The equation for the regression line reads as follows Y = -00768X + 68433 The correlation coefficient is 0235245 M-Cril only publishes the PAR for overdues greater than 60 days Therefore these ratios are used as a proxy for the industry standard of 30 days for some Asian MFIs
50
Finally it has to be examined if charging high interest rates actually enables MFI to
generate higher returns Although it can be expected that the combination of a low PAR
and a high interest rate leads to a high profitability it still has to be checked if this is not
outdone by soaring transaction costs Figure 7 illustrates the correlation between the
interest rate charged by a MFI and its financial self-sufficiency (FSS) The latter is the
ldquo[r]atio of total income to total adjusted expenses for the year Adjustments are made
for subsidised cost of funds (relative to market interest rate) equity (with respect to
inflation) and in-kind donationsrdquo246 It can be seen that the regression line actually does
indicate a positive correlation between the interest rate and the profitability of a MFI
Figure 7 Interest Rate vs FSS247
Source Own diagram248
0
20
40
60
80
100
120
140
160
180
0 20 40 60 80 100
Interest Rate
FS
S
246 M-Cril (2004a) p 53247 The equation for the regression line reads as follows Y = 02839X + 8901 The correlation coefficient is 0174248 Since the interest rate the customers of the MFI Foccas have to pay includes fees which are not passed on to the institution its interest rate in this diagram is set at 723 percent instead of the 10715 percent used for figure 6 See Planet Rating (2003b) p 1
51
This result does not necessarily disprove the findings of Stiglitz and Weiss since it can
be argued that MFIs simply do no increase their interest rates to the point where they
would maximize their expected returns But if this would be true why do MFIs not
charge higher rates of interest given the demand described in chapter 41 and 43 In
mature markets competition normally ensures prices not to exceed a certain level but
since many MFIs still operate in a ldquosellerrsquos marketrdquo249 this can not explain the findings
as described in figure 7 Therefore it has to be assumed that a combination of the
unwillingness of many microfinance practitioners to burden their customers with high
interest rates and the plain disbelief of traditional investors that micro-entrepreneurs can
bear those rates is responsible for this occurrence
249 See MicroRate and IADB (2003) p 9
52
8 Conclusions
It has been shown that MFIs are not only contributing significantly to the development
of the financial sector in their respective countries but also that they play an important
role to eradicate poverty by providing much needed capital to low income people which
are able to generate tremendous returns on their investments
The fact that the demand for microcredit is not met is mainly due to the view of most
for profit investors and traditional banks that offering financial services to poor people
can not be done profitable Because of this conviction they hardly invest in the
microfinance sector This does not have to be the case according to the findings of this
paper Although faced with relatively high transaction costs MFIs are able to charge
interest rates at levels that fully recover their costs Elizabeth Rhynersquos claim ldquothat the
most financially viable programs differed from their less viable peers in their
willingness to set interest rates at levels that would fully recover costsrdquo250 is backed by
the findings of this paper that high profitability is correlated to high interest rates
Theoretical models based on the findings of Stiglitz and Weiss can not be used as a
justification to ration credit for the microfinance sector since the interest rate that
maximizes profits to the lender can be assumed to exceed 100 percent for many MFIs
Nevertheless this rate is hardly charged although it has been shown that it can be done
The Mexican MFI Compartamos for example manages to keep its PAR as low as one
percent while charging an effective interest rate of more than 100 percent to
approximately 160000 clients251 In combination with this case the conclusions drawn
from examining the sample of MFIs in chapter 7 the claim of Hulme and Mosley as
stated in the introduction can be considered as wrong MFIs are in fact able to finance
rapid growth stay profitable by charging corresponding interest rates and still have a
significantly positive impact on the poverty level of their clients In the long run gains
in efficiency economies of scale a slowdown in growth and competition will ensure
interest rates drop as it has already been the case in countries like Bangladesh and parts
of Bolivia252
250 See Rhyne (1998) p 7251 See MicroRate (2004)252 See Microrate and IADB (2003) p 9
53
According to a MicroRate survey many MFIs are more profitable than Citibank and also
generate a higher return on investment than commercial banks in their respective
countries253 Investments companies like IMI or Blue Orchard will soon be able to
present a meaningful track record of their microfinance investments to potential
investors Ultimately the capital markets can not ignore the facts proving that it actually
can be profitable to invest in the microfinance sector but in order to raise money
quickly microfinance practitioners will have to continue to intensively promote their
cause not only to for profit investors but also to donors and multilateral agencies like
the World Bank
253 See MicroRate (2002) p 10
54
Appendix
Appendix 1 Average loan balance
Source Data is available through the Mix Market (2004)
Organization
Loan Portfolio 2002 (US$)
Loan Portfolio 2003 (US$)
Number of borrowers 2002
Number of Borrowers 2003
2CM 1263602 1400438 3622 3708ACF 955503 1611401 285 370ACLEDA 26846703 39391301 82598 98905ACME 1460881 1714844 4283 4600ADIM 369065 407798 1122 1395AFK 933306 1706577 250 467AgroInvest 4684249 9697411 5208 9629Al Amana 15593277 28677666 78114 101610AMSSFMC 612167 1040756 6183 6886AREGAK 3285273 3987011 11841 14377AVFS 214331 269819 1883 2866BancoSol 83629049 91175000 42290 56707BESA 10563980 15114430 4488 5061BPR AK 613362 876130 1730 3879BPR BMMS 133949 237946 1755 1779BRI 1344006170 1720072773 3056103 3100358BZMF 1592508 1922097 1250 1331CBDIBA 216587 242465 5764 2877CCA 2146235 4582302 4070 6585CCCP 447534 851678 6265 9450CEP 3795400 5261957 32291 42132CERUDEB 25093643 34873228 34490 44796CMEDFI 227674 250244 3467 3781CMM - Bogota 4836000 8135968 15635 22038CMMB 34880 56964 42 190COAC Maquita Cushunchic
870084 1855718 6603 7732
CODES 280843 263091 60 60CODESARROLLO 6714007 12935951 4391 6896Constanta 2943822 3536047 16134 18588COOPEC CAMEC MN
7152 29821 92 77
Crear - Tacna 3891116 4636094 3671 4948CREDIT 642094 81838 7532 8097CRYSTAL FUND 366456 421403 1379 1061DBACD 3473701 3876526 12812 19606ECLOF - ECU 1154292 728312 860 416ECLOF - MAL 441734 407227 1118 1500EKI 11833244 19245751 8999 13323EMT 4481589 5765281 84781 92173ESED 8579460 6834742 22790 20035
55
Eshet 185741 462569 3308 6540Faulu - KEN 9027332 7206344 17463 15000FDL 12503027 16545332 21306 25106FIE 35818903 41597315 26468 33100FINADEV 5512586 9770323 12775 14709Finance Salone 211312 434298 2225 7159Finca - TAN 1293430 1854834 20648 27499Finca - UGA 2451703 2798869 35610 36912FINCORP 4761288 10236896 941 858FJN 5473563 8037662 8107 11133FMFB 308158 1188896 713 3558FMM -Bucaramanga
6355518 10227000 25814 42464
FODEM 739181 939824 1909 2501FundaciESPOIR
898561 1883446 5911 9464
FUNDESER 798907 1373113 4072 5065Gasha 323748 413742 5504 6423GGLS Save the Children
64235 137957 1291 2362
GK 56986 166971 951 2718HKL 1363365 1420357 6648 5372HOPE 402799 603488 1098 1562IAMD 42132 56550 2780 2772IDECE 21312 39453 150 232IDF 2031944 2626382 31003 36580IMCEC - Dakar 254759 688449 1018 2983IMCEC - Thies 199799 571122 1164 1261
ISSIA 221615 246792 1409 1698JMCC 1962355 2609723 1471 2333KAFC 21710638 29241051 24850 32097KAMURJ 1003935 1411258 5559 5691Kashf 2355965 6271498 29655 59389KMBI 721409 1626666 11973 27266KPSCA 109299 128063 362 794K-Rep 14490447 20699963 38739 45379KSCS 18978 43740 140 297KVT 44075 70621 241 373LAPO 922478 1194633 18740 19139MEC ADEFAP 27788 69248 198 202MEC Bosangani 14357 31086 364 540MEDF 104113 136257 1278 1184Meklit 233170 252232 2084 3577Metemamen 22123 57778 943 1501MFSC 109261 171090 511 687MIKRA 2951028 5008784 4145 6095MIKROFIN 9560502 18380263 5633 7426Miselini 737387 1026639 10182 11431MRFC 11475440 9133130 163000 180000Mushuc Runa 2089076 5418325 3139 6232Nirdhan 2886777 3016171 29589 27457OCSSC 5245186 7658413 42157 6215o
56
Otiv Diana 95992 638422 229 1073Otiv Sambava 188094 437974 2002 1442Otiv Tana 66465 673175 337 1269Partner 9976448 15321304 7139 11935PCA 6878257 6885926 63113 58147PEACE 420746 627295 4192 5428PEDF 164399 254233 2357 3340Piyeli 809447 1206656 8674 4745PRESTANIC 2827502 3540367 1477 2605PRIDE - MAL 991888 854631 5376 5601PRIZMA 3881581 6838978 8112 10968ProMujer -Nicaragua
1006871 1424437 10436 13047
PTF 891566 1068881 8500 9070RBST 818594 1058115 619 723REMECU 1381705 1483471 10330 13996
RUSCA 60887 100820 454 994
SCSCS 89423 157472 873 1007SFPI 709497 903556 7728 9552Sidama 934260 1011798 10267 11346SPBD 117807 186029 647 1740Sunlink 819138 1056823 3401 3833Sunrise 5412366 8782868 4560 7256TEBA 108032426 176300111 163021 157776TIAVO 281978 838905 2049 459TPC 1140429 2267148 22869 31668TSPI 4650989 5383755 49649 75617UNICECAM 3442843 5943804 16039 19031Wasasa 230657 274908 2850 3728Wisdom 1306066 1404463 10524 12054XacBank 4910098 9829503 11063 18610Zakoura 15907288 12444768 103720 118980
Appendix 2 Portfolio at Risk
Source Data is available through the Mix Market (2004)
Organization PAR 2002ABA 202ACEP 464ACLEDA 175ACODEP 452ACSI 209Al Amana 010Apoyo Integral
483
AREGAK 692Banco Solidario
500
BancoSol 660BASIX 1296
57
BRI 437BURO Tangail
350
CEP 200CERUDEB 103CMAC -Sullana
567
CMM -Bogota
176
Compartamos 111Constanta 304Credi Fe 212CREDIAMIGO 409DBACD 010EBS 847EMT 010ESED 1311FADES 2311Faulu - KEN 246Faulu - UGA 096FDL 212FECECAM 428FED 436FIE 598FINADEV 021Finamerica 1133Finca - TAN 000Finca - UGA 297FMM -Bucaramanga
094
FMM -Popayan
088
FONDEP 013FORA 064Genesis Empresarial
1197
IDF 017KAFC 106Kashf 000KMBI 128K-Rep 229MiBanco 309MRFC 1742Nirdhan 373
PADME 079PAMECAS 284PCA 379PRIDE - TAN 018ProMujer -Nicaragua
073
RCPB 600REMECU 157SHARE 000
58
Soluci 182Spandana 014TEBA 106TSPI 355UMU 125UNICECAM 405Urwego 290UWFT 363WAGES 736WWB -Medellin
235
XacBank 061Zakoura 095
Appendix 3 Transaction Costs
Source Data is available through the Mix Market (2004)
OrganizationTransaction Costs
Acci Rural 1154ACEP 858ACLEDA 2430ACODEP 2920ACSI 924Al Amana 2576AREGAK 2856AssEF 1919Banco Solidario
1826
BancoSol 1210BASIX 1317BRI 1353BURO Tangail
2053
CEP 1759CERUDEB 5109CMAC -Sullana
1784
CMM -Bogota
2089
Compartamos 3341Constanta 4597Credi Fe 1978CREDIAMIGO 2525DBACD 1742EBS 2377EMT 3220ESED 1343FADES 1673FAMA 2436
59
Faulu - KEN 2253Faulu - UGA 4962FDL 1726FECECAM 2587FED 4083FIE 1125Finamerica 1563Finca - TAN 10753Finca - UGA 9096FMM -Bucaramanga
1925
FMM -Popayan
1112
FONDEP 5477FORA 3481Genesis Empresarial
1626
IDF 1695
K-Rep 1909LAPO 3511MiBanco 2456Nirdhan 1325NWTF 3109OCSSC 1155PADME 1131PAMECAS 1705PCA 1670PRIDE - TAN 4273ProMujer -Nicaragua
5078
RCPB 2059SHARE 2308Sidama 2662Soluci 2906Spandana 641TEBA 1213TSPI 3898UMU 4023UNICECAM 10120Urwego 7437Wisdom 1906WWB -Medellin
1703
XacBank 4144Zakoura 1881
60
Appendix 4 Portfolio Growth
Source Data is available through the Mix Market (2004)
Organization
Total Loan Portfolio in 2000
Total Loan Portfolio in 2002
ACODEP 5889394 7258487Adelante 4327 88594ADRI 1514681 2591240AgroCapital 11100088 12018280Banco Solidario 39632165 103420000
BancoSol 78031172 83629049CMAC - Sullana 14596365 28055720
COAC Maquita Cushunchic
348443 870084
CODESARROLLO 1374801 6714007Compartamos 10804279 41825248Crear - Tacna 3778816 3891116
Credi Fe 781616 9393936ECLOF - ECU 179247 1154292
FADES 11948814 15501578FAMA 6201411 8835134FIE 22524645 35818903Finamerica 16575104 16097113FINCOMUN 3278938 5696556FMM - Popayan 6241821 12212867
FONDECO 3456625 5101801Genesis Empresarial
11154234 17746288
MiBanco 36964072 95873333Mushuc Runa 90737 2089076ProMujer -Nicaragua
426541 1006871
WWB - Medellin 2891207 4580998
Appendix 5 Portfolio vs Equity
Source Data is available through the Mix Market (2004)
OrganizationLoan Portfolio Equity
ACODEP 7258487 1921447Adelante 88594 72973
ADRI 2591240 781477AgroCapital 12018280 10766101Banco Solidario 103420000 12961000BancoSol 83629049 15299415CMAC - Sullana 28055720 6210291
61
COAC Maquita Cushunchic
870084 260331
CODESARROLLO 6714007 1285103
Compartamos 41825248 18350446
Crear - Tacna 3891116 1016912Credi Fe 9393936 863848ECLOF - ECU 1154292 459226FADES 15501578 4138972FAMA 8835134 6377663FIE 35818903 5360484Finamerica 16097113 3817960FINCOMUN 5696556 1042241FMM - Popayan 12212867 8510494FONDECO 5101801 1658075Genesis Empresarial
17746288 4765816
MiBanco 95873333 24261889Mushuc Runa 2089076 434311ProMujer -Nicaragua
1006871 1196015
WWB - Medellin 4580998 2213249
Appendix 6 Internal Rate of Return
Source Excel (German Version) calculation based on own data
A B C D E F
1 Date Cash Flow
Interest Rate Internal Rate of Return Balance Interest Principal
23 01012004 -100 15324 100 025489547 0045104534 02012004 03 999548955 025489547 0045104535 03012004 03 99909676 02547805 004521956 04012004 03 998643412 025466524 0045334767 05012004 03 998188909 025454968 0045450328 06012004 03 997733247 025443383 0045566179 08012004 03 999826083 050928361 -0209283610 09012004 03 999374595 025485114 004514886
hellip hellip hellip hellip hellip helliphellip hellip hellip hellip hellip hellip helliphellip hellip hellip hellip hellip hellip hellip1562 23122008 03 177951388 000528711 0294712891563 25122008 03 148859724 000908336 0290916641564 26122008 03 119239161 000379437 0296205631565 27122008 03 089543096 000303935 0296960651566 28122008 03 059771337 000228241 0297717591567 29122008 03 029923692 000152354 0298476461568 30122008 03 -3434E-07 000076274 029923726
62
The formula in the square C3 reads as follows
ldquoXINTZINSFUSS(B3B1568A3A156815)rdquo
Appendix 7 Subsidized Interest Rates and the Net Gains to Society
SourceOwn calculations
For simplicity only two groups of potential clients are distinguished This is possible
since using a continuum of potential clients would lead to the same results In addition it
is assumed that the amount of every loan (L) is equal and that all clients invest the
whole loan amount Group H consist of NH potential clients with a rate of return (rH) on
their invested capital higher than the cost recovering interest rate charged by the MFI
(iC) Group L consists of NL potential clients with a rate of return (rL) on their invested
capital lower than iC If the MFI charges iC the NGS can be calculated as follows
NGSC = NH times (rH - iC) times L
Since rH is bigger than iH (rH gt iC) according to the definition presented above the term
NGSH must be positive as long as NH does not equal zero If the MFI introduces a
subsidised interest rate (iS) lower than rL the NGS can be calculated as follows
(1) NGSS = NH times (rH - iS) times L + NLtimes (rL - iS) times L + (NH + NL) times (iS - iC) times L
(2) NGSS = NH times (rH- iC) times L + NLtimes (rL - iC) times L
The term (NH + NL) times (iS - iC) times L describes the amount of money that is needed in order
to subsidize the interest rate to the level iS By setting up an inequation it can be
examined under which conditions the NGSS are bigger than the NGSC
(3) NGSS gt NGSC
(4) NH times (rH- iC) times L + NLtimes (rL - iC) times L gt NH times (rH - iC) times L
(5) NLtimes (rL - iC) times L gt 0
(6) rL gt iC
63
So the NGSS could only be bigger than the NGSC if equation 6 holds This is
impossible since it violated the definitions presented above Therefore the introduction
of subsidized interest rates is always accompanied with a drop in the NGS
Appendix 8 Interest Rate vs Loan Size vs FSS vs PAR
Source Data is available through the Mix Market (2004)
Organization Country
Real Interest Rate
Loan Size (divided by the GDP per Capita) FSS PAR
BTFFKyrgyz Republic 3803 48260 1487 698
BesaFoundation Albania 2184 16076 684 260RFF Albania 1198 5783 4764 277PSHM Albania 2194 000 5758 198Mi-Bospo Bosnia 2974 5499 1261 020Prizma Bosnia 3474 3569 103 064Agroinvest Serbia 2201 4401 875 020KCLF Kazakhstan 5713 1713 865 090
Foccas Uganda10716 (723) 1550 584 29
ACEP Senegal 3280 20941 1643 1Padme Benin 2715 13575 1667 08Papme Benin 3086 53659 1405 24Vital Finance Benin 2676 9394 1015 17Finadev Benin 1738 14850 1024 21ABA Egypt 2579 1613 1168 88ASBA Egypt 2597 1702 1252 68DBACD Egypt 2490 1643 1073 0SBACD Egypt 2500 1734 982 67AMSSF Morocco 6926 787 1306 04Fondep Morocco 5199 650 889 071Zakoura Morocco 4414 900 98 006ENDA Tunisia 4008 1351 110 102BSFL India 1954 3269 856 99Share India 3426 1440 951 0Spandana India 2942 1618 1367 026SWC India 1864 2626 42 3036SKS India 2248 1912 578 0Grama Vidiya India 3176 1221 76 18Sneha India 3451 1433 933 0Buro Bangladesh 3206 1882 1093 17Upap Pakistan 2073 8183 757 03Seeds Sri Lanka 1004 1088 605 287EMT Cambodia 4324 1676 1016 01TPC Cambodia 4470 2035 832 27
64
WTF Phillippines 5816 1095 941 74TSKI Phillippines 5794 777 96 79Cacja Ecuador 862 6189 9460 897ACME Haiti 6043 6934 11685 450Grupo Cama Mexico 8961 267 10717 288
65
Appendix 9 Inflation vs GDP per Capita
Source IMF (2004)
Country Subject Description Units Scale 2000 2001 2002 2003 2004
Albania Gross domestic product per capita current prices US dollars Units 1083988 1238206 1396172 1757778 2229712
Albania Inflation annual percent change Percent 00 31 52 24 34
Bangladesh Gross domestic product per capita current prices US dollars Units 329310 327980 344494 369495 393717
Bangladesh Inflation annual percent change Percent 22 15 38 54 64
Benin Gross domestic product per capita current prices US dollars Units 361340 368213 405951 494725 560129
Benin Inflation annual percent change Percent 42 40 24 15 26
Bosnia and Herzegovina Gross domestic product per capita current prices US dollars Units 1255837 1321429 1466090 1807392 2070508
Bosnia and Herzegovina Inflation annual percent change Percent 50 32 03 02 09
Cambodia Gross domestic product per capita current prices US dollars Units 276413 280352 296577 305940 321247
Cambodia Inflation annual percent change Percent -08 02 33 12 20
Ecuador Gross domestic product per capita current prices US dollars Units 1227711 1590267 1804362 1957183 2082156
Ecuador Inflation annual percent change Percent -77 377 126 79 32
Egypt Gross domestic product per capita current prices US dollars Units 1550982 1461431 1278462 1188060 1083158
Egypt Inflation annual percent change Percent 28 24 24 32 52
India Gross domestic product per capita current prices US dollars Units 454206 458849 472915 542554 602625
India Inflation annual percent change Percent 40 38 43 38 47
Kazakhstan Gross domestic product per capita current prices US dollars Units 1236159 1490946 1655148 2000598 2579554
Kazakhstan Inflation annual percent change Percent 134 83 59 64 68
Kyrgyz Republic Gross domestic product per capita current prices US dollars Units 278256 306130 321079 349632 380637
Kyrgyz Republic Inflation annual percent change Percent 187 69 21 31 45
66
Mexico Gross domestic product per capita current prices US dollars Units 5957486 6274468 6425203 6111754 6377064
Mexico Inflation annual percent change Percent 95 64 50 45 44
Morocco Gross domestic product per capita current prices US dollars Units 1161302 1162154 1199584 1432725 1541041
Morocco Inflation annual percent change Percent 19 06 28 12 20
Pakistan Gross domestic product per capita current prices US dollars Units 437381 400356 440471 492913 538120
Pakistan Inflation annual percent change Percent 44 31 32 29 46
Philippines Gross domestic product per capita current prices US dollars Units 979423 900225 950707 963765 1018710
Philippines Inflation annual percent change Percent 43 61 31 30 54
Russia Inflation annual percent change Percent 208 215 158 137 103
Senegal Gross domestic product per capita current prices US dollars Units 478704 474460 507408 634171 714622
Senegal Inflation annual percent change Percent 09 30 23 -00 08
Serbia and Montenegro Gross domestic product per capita current prices US dollars Units 1031263 1389384 1882036 2491799 2795805
Serbia and Montenegro Inflation annual percent change Percent 699 911 212 113 79
Sri Lanka Gross domestic product per capita current prices US dollars Units 846811 796025 828256 904330 982466
Sri Lanka Inflation annual percent change Percent 62 142 96 63 64
Tunisia Gross domestic product per capita current prices US dollars Units 2034360 2065140 2149421 2534823 2881273
Tunisia Inflation annual percent change Percent 30 19 28 28 34
Uganda Gross domestic product per capita current prices US dollars Units 293404 249682 279587 280802 287204
Uganda Inflation annual percent change Percent 45 -20 57 51 35
67
References
Akerlof George A The Market for ldquoLemonsrdquo Qualitative Uncertainty and the Market Mechanism in Quarterly Journal of Economics Vol 84 (1970) pp 488-500
Amin Ruhul et al Integration of an Essential Service Package (ESP) in Child and Reproductive Health and Family Planning with a Micro-Credit Program for poor Women Experience from a Pilot Project in Rural Bangladesh in World Development Vol 29 (2001) No 9 pp 1611-1621
Bester Helmut Screening vs Rationing in Credit Markets with Imperfect Information in The American Economic Review Vol 75 (1985) No 4 pp 850855
Borst Dietmar Microfinance ndash Theoretische Grundlagen fuumlr den Einsatz sowie die Abschaumltzung des Potentials anhand einer Datenbankuntersuchung zur Verwundbarkeit der laumlndlichen Bevoumllkerung in Vietnam unpublished diploma thesis Karlsruhe 2004
BRAC Annual Report 2002 Dhaka 2003
Busch Alexander Kort Katharina Die Peanuts-Banker und ihre Kunden in Handelsblatt Nr 150 published August 5th 2004 p 8
Campion Anita Challenges to Microfinance Commercialization in Journal of Microfinance Vol 4 (1999) No 2 pp 57-65
Chu Michael Key Issues of Development Finance Somerville (MA) 1998
Dornbusch Ruumldiger Fischer Stanley Makrooumlkonomie Oldenburg 1995
Dunn Seth Flavin Christopher Moving the Climate Change Agenda Forward in State of the World New York London 2002 pp 24-50
Farrington Todd Efficiency in Microfinance Institutions in The MicroBanking Bulletin Issue No 4 pp 18-24
Gardner Gary The Challenge for Johannesburg Creating a More Secure World in State of the World New York London 2002 pp 3-23
Ghatak Subrata On Interregional Variations in Rural Interest Rates in Journal of Developing Areas Issue 18 pp 21-34
Gibbons David Serving the Poorest Sustainably in The MicroBanking Bulletin Issue No 5 (2000) pp 13-16
Gibbons David Meehan Jennifer W The Microcredit Summitrsquos Challenge WorkingToward Institutional Financial Self-Sufficiency While Maintaining a Commitment to Serving the Poorest Families in Journal of Microfinance Vol 1 (1999) No 1 pp 131-192
68
Goodwin-Groen Ruth Do Asian MFIs Access Funds from Commercial Banks inThe MicroBanking Bulletin Issue No 3 pp 8-10
Grameen Bank (ed) Grameen Generalized System Dhaka 2003
Gross Alexandra de Silva Samantha Social Fund Support of Microfinance A Reviewof Implementation Experience The World Bank Social Protection Discussion Paper No 0215 Washington DC 2002
Hashemi Syed M Schuler Sidney R Sustainable Banking with the Poor A Case Study of Grameen Bank Dhaka 1997
Helms Brigit Reille Xavier Interest Rate Ceilings and Microfinance The story so farConsultative Group to assist the Poor Occasional Paper No 9 September 2004 Washington DC 2004
Hoff Karla Stiglitz Joseph E Introduction Imperfect Information and Rural Credit Markets-Puzzles and Policy Perspectives in The World Bank Economic Review Vol 4 (1990) No 3 pp 235-250
Holcombe Susan Managing to Empower The Grameen Bankrsquos Experience of Poverty Allevation Dhaka 1995
Hulme David Mosley Paul Finance against Poverty London 1996
Jalvaani (ed) Flush with loans Micro credit for rural sanitation Vol 2 (1999) No 2 pp 1-2
Khandker Shahidur R Fighting Poverty with Microcredit Experience in Bangladesh Oxford et al 1998
Khandker Shahidur R Khalily Baqui Khan Zahed Grameen Bank Performance andSustainability The World Bank Discussion Paper No 306 Washington DC 1995
Lipsey Rechard G An Introduction to Positive Economics 5th edition London 1979
Littlefield Elizabeth Morduch Jonathan Hashemi Syed M Is Microfinance an Effective Strategy to Reach the Millennium Development Goals Consultative Group to Assist the Poorest Focus Note No 24 Washington DC 2003
Martinot Eric Cabraal Anil World Bank Solar Home Systems Projects Experience and Lessons Learned 1993-2000 in Renewable Energy Oxford 2000 pp 1-8
M-Cril Microfinance Review 2003 revised February 2004 Gurgaon 2004a
Mezzera Jaime Microcredit in Brazil The Gap Between Supply and Demand in The MicroBanking Bulletin Issue No 8 (2000) pp 22-24
The MicroBanking Bulletin (ed) Note to the Reader Vol 1 (1997) Issue No 1 pp 5-8
69
The MicroBanking Bulletin (ed) An Introduction to the Peer Groups and Tables Issue No 9 (2003) pp 53-60
MicroRate IADB Performance Indicators for Microfinance Institutions Technical Guide 3rd edition Washington DC 2003
MkNelly Barbara Dunford Christopher Impact of Credit with Education on Mothers and Their Young Childrenrsquos Nutrition Lower Pra Rural Bank Credit with Education Program in Ghana Freedom from Hunger Research Paper No 4 Davis (CA) 1998
MkNelly Barbara Dunford Christopher Impact of Credit with Education on Mothers and Their Young Childrenrsquos Nutrition CRECER Credit with Education Program in Bolivia Freedom from Hunger Research Paper No 5 Davis (CA) 1999
Morduch Jonathan The Microfinance Promise in Journal of Economic Literature Vol 37 (1999b) No 4 pp 1569-1614
Neus Werner Einfuumlhrung in die Betriebswirtschaftslehre Tuumlbingen 1998
Otero Maria Bringing Development Back into Microfinance Journal of Microfinance Vol 1 (1999) No 1 pp 8-19
Panjaitan-Drioadisuryo Rosintan D M Cloud Kathleen Gender self-employment and microcredit programs An Indonesian case study in The Quarterly Review of Economics and Finance Vol 39 (1999) pp 769ndash779
Perkins Dwight H et al Economics of Development 5th edition New York London 2001
Pitt Mark M Khandker Shahidur R Credit Programs for the Poor and the Health Status of Children in Rural Bangladesh in International Economic Review Vol 44 (2003) No 1 pp 87-118
Raiffeisen Friedrich W The Credit Unions 8th edition Neuwied 1966
Rhyne Elizabeth The Yin and Yang of Microfinance Reaching the Poor and Sustainability in The MicroBanking Bulletin Issue No 2 (1998) pp 6-9
Richardson David C Unorthodox Microfinance The Seven Doctrines of Success in The MicroBanking Bulletin Issue No 4 (2000) pp 3-7
Robinson Marguerite S The Microfinance Revolution Sustainable Finance for the Poor Washington DC 2001
Robinson Marguerite S The Microfinance Revolution Volume 2 Lessons from Indonesia Washington DC 2002
Rosenberg Richard Microcredit Interest Rates Consultative Group to assist the Poorest Occasional Paper No 1 revised November 2002 Washington DC 2002
70
Roth Michael Steinwand Dirk Mikrofinanz Weltweites Erfolgsmodell nur nicht inDeutschland Zur Uumlbertragbarkeit der Erfahrungen aus Entwicklungslaumlndern auf Deutschland Deutsche Gesellschaft fuumlr Technische Zusammenarbeit (ed) Eschborn2004
Schmidt Reinhard H Tschach Ingo Microfinance as a Nexus of Incentives Finance and Accounting Working Paper No 87A Frankfurt 2001
Schreiner Mark A Framework for the Analysis of the Performance and Sustainability of Subsidized Microfinance Organizations with Application to Banco Sol of Bolivia and Grameen Bank of Bangladesh unpublished PhD dissertation Columbus (O) 1997
Seibel Hans D Recent Developments in Microfinance Development Research Center Working Paper No 1998-5 Cologne 1998
Seibel Hans D History matters in microfinance in Small Enterprise Development ndashAn International Journal of Microfinance and Business Development Vol 14 (2003a) No 2 pp 10-12
Seibel Hans D Schmidt Petra How an Agricultural Development Bank Revolutionized Rural Finance The Case of Bank Rakyat Indonesia International Fund for Agricultural Development Rural Finance Working Paper B 5 Rome 2000
Sen Amartya Oumlkonomie fuumlr den Menschen ndash Wege zu Gerechtigkeit und Solidaritaumlt in der Marktwirtschaft Muumlnchen Wien 2000
Serageldin Ismail The View of the Chair in Consultative Group to Assist the Poorest Newsletter Issue No1 (1996) pp 1 11-12
Soros George Die Krise des globalen Kapitalismus Offene Gesellschaft in Gefahr Berlin 1998
Staschen Stefan Regulation and Supervision of Microfinance Institutions State of Knowledge Deutsche Gesellschaft fuumlr Technische Zusammenarbeit (ed) Eschborn 1999
Steinwand Dirk The Alchemy of Microfinance The Evolution of the IndonesianPeoples Credit Banks (BPR) to 1999 and a Contemporary Analysis Berlin 2001
Stiglitz Joseph E Peer Monitoring and Credit Markets in The World Bank Economic Review Vol 4 (1990) No 3 pp 351-366
Stiglitz Joseph E Weiss Andrew Credit Rationing in Markets with Imperfect Information in The American Economic Review Vol 71 (1981) No 3 pp 393-410
Tschach Ingo Theorie der Entwicklungsfinanzierung Mit Kleinkreditprogrammen Kredit- und Arbeitsmarktsegmentierung uumlberwinden Frankfurt 2000
UNDP Human Development Report 2004 New York 2004
71
UNFPA state of the world population 2004 New York 2004
UNICEF The State of the Worldrsquos Children 2002 NewYork Geneva 2002
Varley Robert C G Financial Services and Environmental Health Household Credit for Water and Sanitation Environmental Health Project Applied Study No 2 Washington DC 1995
Volkery Carsten Kampf um Straszligenhaumlndler in Die Zeit Nr 23 published May 27th
2004 p 33
Wardhana Ali Introduction in The Microfinance Revolution ndash Sustainable Finance for the Poor Washington DC 2001 pp XVII-XXVII
Woodworth Warner Woller Gary Greetings from the Editors Journal of Microfinance Vol 1 (1999) No 1 p 6
The World Bank Group World Development Indicators 2004 Washington DC 2004
Worldwatch Institute (2002) Vital Signs 2002 New York London 2002
Wimmer Nancy Barua Dipal Less is more Microfinance for solar energy in rural areas in Renewable Energy World Review Issue 2004-2005 Vol 7 (2004) No4 pp 170-179
Yunus Muhammad Grameen Bank II ndash Designed to Open new Possibilities Dhaka 2002
Yunus Muhammad Grameen ndash Eine Bank fuumlr die Armen dieser Welt Muumlnchen 1998a
Internet References
Abishek Lal (nd) An Overview of Microfinance and Environmental Management [http wwwgdrcorgicmenvironabhishekhtml] (availability date October 5 2004)
ACCION (nd) our history [httpwwwaccionorgabout_our_historyasp] (availability date October 5 2004)
ACCION (nd) key statistics [httpwwwaccionorgabout_key_statsasp] (availability date October 5 2004)
Ahmad Zulfiqar (nd) Forms of Regional Cooperation in Microfinance in South Asia [httpwwwbwtporgarcmpakistanIV_News_and_EventsBWTPworkshopZulfiqar20Ahmad20paper20(BWTP-PMN2029Jan04)pdf (availability date October 6 2004)
72
Ahmed Salehuddin (2003) Foreword [httpwwwpksf-bdorgaprm_summit_brochure htm] (availability date September 30 2004)
Annan Kofi (2002) Statement at The Microcredit Summit +5 [httpwww microcreditsummitorgenews2003-03_sp_chowdhuryhtml) (availability date October 5 2004)
Barnes Carolyn (2001) Microfinance Program Clients and Impact An Assessment of Zambuko Trust Zimbabwe [httpwwwmicrofinancegatewayorgfiles18553_Barnes_Zambuko_Trust_2001pdf] (availability date October 5 2004)
Barnes Carolyn Gaile Gary Kibombo Richard (2001) The Impact of Three Microfinance Programs in Uganda [httpwwwmicrofinancegatewayorgfiles2935_Barnes_2001pdf] (availability date October 5 2004)
Barua Dipal (2004) Success of Grameen Shakti in the Field of Renewable Energy Sector in Bangladesh [httpwwwrenewables2004depptPresentation1-SessionVA(14-1530h)-Baruapdf] (availability date September 30 2004)
Bhatt Ela (1997) In 1975 [httpwwwmicrocreditsummitorgdeclarationhtm] (availability date September 30 2004)
BlueOrchard (2004a) Microfinance [httpwwwblueorchardchenmicrofinance_institutions asp] (availability date October 5 2004)
BlueOrchard (2004b) January 2004 Newsletter [httpwwwblueorchardchmedialibrarywebsitenewsletter_jan_2004pdf] (availability date October 5 2004)
Brynjolfsson John (2004) John Brynjolfsson Discusses Recent Trends in TIPS Issuance [httpwwwpimcocomLeftNavPIMCO+Spotlight2004Spotlight_2_04htm] (availability date October 5 2004)
CGAP (2003) Report to the Board of Executive Directors [httpwww-wdsworldbankorgservletWDSContentServerWDSPIB20031208000012009_20031208101736RenderedPDF27441pdf] (availability date October 5 2004)
Chen Shaohua Ravallion Martin (2004) How have the worldrsquos poorest fared since the early 1980s [httpwwwworldbankorgresearchpovmonitorMartinPapersHow_have_the_poorest_fared_since_the_early_1980spdf] (availability date October 5 2004)
Cheston Susy Kuhn Lisa (2002) Empowering Women through Microfinance[httpwwwmicrofinancegatewayorgfiles3240_Cheston_2002doc] (availability date October 5 2004)
Christen Robert P et al (1995) Maximizing the Outreach of Microenterprise FinanceAn Analysis of Successful Microfinance Programs [httpwwwdecorgpdf_docsPNABS519 pdf] (availability date October 5 2004)
73
CIA (2004) The World Factbook [httpwwwciagovciapublicationsfactbook] (availability date October 5 2004)
Clear Profit (2004) Microfinance Bond Record May Double [httpwwwclear-profitcomissuescpsep04txt] (availability date September 30 2004)
Daley-Harris Sam (2003) State of the Microcredit Summit Campaign Report 2003 [httpwwwmicrocreditsummitorgpubsreportssocr2003SOCR03-E[txt]pdf] (availability date September 30 2004)
Dominiceacute Robert (2004) Interview in Microfinance Bond Record May Double [httpwwwclear-profitcomissuescpsep04txt] (availability date September 30 2004)
Donahue Jill Kabbucho Kamau Osinde Sylvia (2001) HIVAIDSmdashResponding To A Silent Economic Crisis Among Microfinance Clients In Kenya and Uganda [httpwwwmicrosave-africacomget_fileaspdownload_id=541] (availability date September 30 2004)
Donahue Jill Sussman Linda (1999) Building a Multi-Sectoral Response Follow-Up Assessment of Programming for Children and Families Affected by HIVAids in Kenya [httpwwwdecorgpdf_docspnacg778pdf] (availability date September 30 2004)
The Economist (1998) [httpwwweconomistcomdisplaystorycfmstory_id=S2629H3C28Q13F240A] (availability date September 30 2004)
Finca (nd) Introduction [httpvillagebankingorgwhereindexphp3] (availability date September 30 2004)
Fischer Stanley (2003) Statement at The Asia Society and Womens World BankingAnnual Microfinance Conference [httpwwwiiecomfischerpdffischer051303pdf] (availability date September 30 2004)
Friedman Milton (nd) Samuha [httpwwwsamuhaorgm-1htm] availability date September 30 2004)
FXTOP (2004) Historical Exchange Rates [httpfxtopcomdehistoratesphp3] (availability date September 30 2004)
Gibbons David Meehan Jennifer W (2002) Financing Microfinance for Poverty Reduction [httpwwwmicrocreditsummitorgpapersfinancing_finalpdf] (availability date September 30 2004)
Grameen Bank (2004) Grameen Bank At a Glance [httpwwwgrameen-infoorgbankcdshtml] (availability date September 30 2004)
Grameen Trust (nd) Grameen Bank Replication Program [httpwwwgrameen-infoorggrameengtrustreplicationhtml8721] (availability date September 30 2004)
74
Hossain Farhad (2004) Microfinance in Development [httpwwwvalthelsinkifi staff jkoponenb1104FarhadFeb2304pdf] (availability date October 5 2004)
IMF (2004) Data [httpwwwimforgexternalpubsftweo200402datadbginimcfm] (availability date October 5 2004)
IMI (2004) Investments [httpwwwimi-agcomoverviewindexhtml] (availability date September 30 2004)
IPCC (2001) Summary for Policymakers [httpwwwipccchpubspm22-01pdf] (availability date September 30 2004)
Jansson Tor Wenner Mark (1997) Financial Regulation and its Significance for Microfinance in Latin America and the Caribbean [httpwwwgdrcorgicmgoverniadb-janssonpdf] (availability date October 5 2004)
Ken Daniel Ten Roeun Van (2004) The Cycle of Debt - As Microcredit Institutions Grow Some Question Their Effect on Poverty [httpwwwcamnetcomkhcambodiadaily selected_featurescd-21-02-04htm] (availability date September 30 2004)
Kim Julia (2002) Social Interventions for HIVAIDS - Intervention with Microfinance for AIDS and Gender Equity [httpwwwwitsaczaradarPDF20filesIntervention_monograph_no_picspdfpdf] (availability date September 30 2004)
Llanto Gilberto (nd) Vietnam [httpwwwadborgDocumentsBooksCentral_Banks_MicrofinanceCountry_Studiesvietnampdf] (availability date September 30 2004)
The Microfinance Gateway (nd) Frequently Asked Questions [httpwwwmicrofinance gatewayorgsectionfaq1] (availability date October 5 2004)
Microfinance Rating and Assessment Fund (2004) Qualified Raters [httpwwwmfrating orgmfi_institutionsqualified_ratershtml] (availability date October 5 2004)
Microcredit Summit (1997) Declaration and Plan of Action [httpwwwmicrocreditsummit orgdeclarationhtm] (availability date September 30 2004)
MicroRate (nd) Performance Indicators and Ratios [httpwwwmicroratecomENGLISHsiteRATINGSindicatorshtml] (availability date September 30 2004)
MicroRate (2002) The Finance of Microfinance [httpwwwmicroratecomPDFFinance20of20Microfinancepdf] (availability date September 30 2004)
MicroRate (2004) Adjusted comparison table [httpwwwmicroratecomENGLISHsitePDFAdjusted20Comparison20Table060320engpdf] (availability date October 5 2004)
75
Mix Market (2004) The Mix Market [httpwwwmixmarketorg] (availability date October 5 2004)
Morduch Jonathan (1999b) The Grameen Bank A Financial Reckoning [httpwwwwwsprincetonedu~rpdsmacarthurdownloadsmorduch_grameen_bankpdf] (availability date September 30 2004)
Pallen Dean (1997) Environmental Sourcebook for Micro-Finance Institutions [httpwwwacdi-idagccaINETIMAGESNSFvLUImagesea20summaries$fileSOURC Epdf] (availability date September 30 2004)
Prisma (2002) The Case for Private Capital Market Creation in the Development Field of Microfinance [httpwwwsocialenterprisenetpdfsprivate_capital_marketpdf] (availability date September 30 2004)
Schmidt Reinhard H Zeitinger C-P (1997) Critical Issues in Microbusiness Finance and the Role of Donors No 6 [httpwwwgdrcorgicmmfi-donorpdf] (availability date September 30 2004)
Seibel Hans D (2003b) Commodity finance a commercial proposition Micro- and Mesofinance for Agricultural Commodity Production Processing and Trade [httpwwwuni-koelndeew-fakaef05-20042003-420Commodity20Financepdf] (availability date September 30 2004)
Simanowitz Anton Walter Alice (2002) Ensuring Impact Reaching the Poorest while Building Financially Self-sufficient Institutions and Showing Improvement in the Lives of the Poorest Families [httpwwwidsacukimpactPublicationsWorkingPapersOP3MCSSumdoc] (availability date September 30 2004)
Smith Stephen C Jain Sanjay (1999) Village Banking and Maternal and Child Health Theory and Evidence from Ecuador and Honduras[httphomegwuedu~scsmith healthrevwd801pdf] (availability date September 30 2004)
United Nations (1999) International Year of Microcredit 2005 [httpods-dds-nyunorgdoc UNDOCGENN9976933PDFN9976933 pdfOpenElement] (availability date October 5 2004)
United Nations (2000) United Nations Millennium Declaration [httpods-dds-nyunorgdocUNDOCGENN0055951PDFN0055951pdfOpenElement] (availability date October 5 2004)
US Census Bureau (2004) Total Midyear Population for the World 1950-2050 [httpwwwcensusgovipcwwwworldpophtml] (availability date October 5 2004)
WHO (2004) Making pregnancy safer [httpwwwwhointmediacentrefactsheets fs276en] (availability date September 30 2004)
WHO (2001) Child Health [httpwwwwhointmipfiles2082AAGChildHealthpdf] (availability date September 30 2004)
76
The World Bank Group (nd) Health Nutrition and Population and the Millennium Development Goals [www1worldbankorghnpMDGMDG20-20HNPbookletpdf] (availability date September 30 2004)
Yunus Muhammad (1998) Championing the Right to Credit for Poor Women Around the World [httpaspgrameencom dialoguedialogue34interviewhtml] (availability date September 30 2004)
UNAIDS (2004) [httpwwwunaidsorgbangkok2004GAR2004_pdfUNAIDSGlobalReport2004_enpdf] (availability date September 30 2004)
Ratings
M-Cril (2000) SPANDANA [httpwwwratingfundorgspanishdocsSPANDANA_RatingReportpdf] (availability date October 7 2004)
M-Cril (2001a) BASIX [httpwwwbasixindiacomMcrilasp] (availability date October 7 2004)
M-Cril (2001b) BDB [httpwwwratingfundorgspanishdocsRF_BDBpdf] (availability date October 7 2004)
M-Cril (2001c) SNEHA [httpwwwratingfundorgspanishdocsRF_Sneha-u1pdf] (availability date October 7 2004)
M-Cril (2002a) KCLF [httpwwwratingfundorgdocsRF-KCLF-risk20reportdoc] (availability date October 7 2004)
M-Cril (2002b) NWTF [httpwwwratingfundorgspanishdocsRF_NWTFpdf] (availability date October 7 2004)
M-Cril (2002c) SEEDS [httpwwwratingfundorgspanishdocsRF_SEEDS_2002_Ratingpdf] (availability date October 7 2004)
M-Cril (2002c) Share [httpwwwratingfundorgspanishdocsRF_SHAREpdf] (availability date October 7 2004)
M-Cril (2002d) TSKI [httpwwwratingfundorgspanishdocsRF_Tski_mcrilfinal(-) reportpdf] (availability date October 7 2004)
M-Cril (2003a) ASA [httpwwwratingfundorgdocsASA20updatepdf] (availability date October 7 2004)
M-Cril (2003b) BURO [httpwwwm-crilcomburopdf] (availability date October 7 2004)
M-Cril (2003c) EMT [httpwwwratingfundorgdocsEMTpdf] (availability date October 7 2004)
77
M-Cril (2003d) SKS [httpwwwmixmarketorgendemanddemandshowprofileaspett=25ampshowinfo=adjusted] (availability date October 7 2004)
M-Cril (2003d) TPC [httpwwwratingfundorgdocsTPC_Finalpdf] (availability date October 7 2004)
M-Cril (2004b) UPAP [httpwwwratingfundorgdocsUPAP_2004pdf] (availability date October 7 2004)
Microfinanza (2002a) ACME [httpwwwratingfundorgspanishdocsACME_finalpdf] (availability date October 7 2004)
Microfinanza (2002b) BTFF [httpwwwratingfundorgspanishdocsBTFF_RatingReportpdf] (availability date October 7 2004)
Microfinanza (2002c) BESA [httpwwwratingfundorgspanishdocsBESA_RatingReportpdf] (availability date October 7 2004)
Microfinanza (2002d) CAME [httpwwwratingfundorgdocsEvaluacionCAME(-) Finaldoc] (availability date October 7 2004)
Microfinanza (2002e) RFF [httpwwwratingfundorgdocsRFF20finalpdf] (availability date October 7 2004)
Microfinanza (2002f) PSHM [httpwwwratingfundorgspanishdocsPSHM_Reportpdf] (availability date October 7 2004)
Microfinanza (2003) CAJCA [httpwwwratingfundorgdocsCalificacion_Jardin_Azuayo_ratingpdf] (availability date October 7 2004)
Microserve (2003) ENDA [httpwwwmixmarketorgendemanddemandshowprofileaspett=865ampshowinfo=adjusted] (availability date October 7 2004)
Planet Rating (2002a) FONDEP [httpwwwmfratingorgRatingscompleted_ratingshtml] (availability date October 7 2004)
Planet Rating (2002b) PRIZMA [httpwwwmixmarketorgendemanddemandshowprofileaspett=111ampshowinfo=adjusted] (availability date October 7 2004)
Planet Rating (2002c) SWS [httpwwwratingfundorgspanishdocsSWC_reportpdf] (availability date October 7 2004)
Planet Rating (2002d) ZAKOURA [httpwwwratingfundorgspanishdocsRF_Zakourapdf] (availability date October 7 2004)
Planet Rating (2003a) AMSSF [httpwwwratingfundorgdocsPlanetRating_AMSSF_010803pdf] (availability date October 7 2004)
Planet Rating (2003b) FOCCAS [httpwwwratingfundorgdocsPlanetRatingFOCCAS120803pdf] (availability date October 7 2004)
78
Planet Rating (2003c) PADME [httpwwwmfratingorgdocsPlaNetRatingPADME070302_Englishpdf] (availability date October 7 2004)
Planet Rating (2003d) PAPME [httpwwwmfratingorgdocsPAPME_PlanetRating080903pdf] (availability date October 7 2004)
Planet Rating (2003e) VITAL FINANCE [httpwwwmfratingorgdocsVital20Finance_Sept202003pdf] (availability date October 7 2004)
Planet Rating (2004a) ABA [httpwwwratingfundorgdocsABA_April202004pdf] (availability date October 7 2004)
Planet Rating (2004b) ACEP [httpwwwmfratingorgdocsACEPSeacuteneacutegal_2004pdf] (availability date October 7 2004)
Planet Rating (2004c) AGROINVEST [httpwwwratingfundorgdocsAgroInvest_June202004pdf] (availability date October 7 2004)
Planet Rating (2004d) ASBA [httpwwwratingfundorgdocsASBA_April202004pdf] (availability date October 7 2004)
Planet Rating (2004e) DBACD [httpwwwratingfundorgdocsDBACD_April202004pdf] (availability date October 7 2004)
Planet Rating (2004f) FINADEV [httpwwwmfratingorgdocsFinadev_2004pdf] (availability date October 7 2004)
Planet Rating (2004g) MI-BOSPO [httpwwwratingfundorgdocsMIBOSPO_160404pdf] (availability date October 7 2004)
Planet Rating (2004h) SBACD [httpwwwratingfundorgdocsSBACD_PlanetRating300604pdf] (availability date October 7 2004)
Other Sources
Interview Shaw Newaz Deputy General Manager of the Grameen Bank October 30th
2003
Hodson Charles (2001) Your Business Your World Jim Boulden CNN (ed) Dhaka 2001
4
Acronyms
BDB Bank Dagan Bali
BRAC Bangladesh Rural Advancement Committee
BRI Bank Rakyat Indonesia
CF Cost of Funds
CGAP Consultative Group to Assist the Poor(est)
FSS Financial Self-Sufficiency
GDP Gross Domestic Product
GNP Gross National Product
I Interest Rate
IADB Inter-American Development Bank
II Investment Income
IMI Internationale Mikro Investitionen Aktiengesellschaft
IPCC Intergovernmental Panel on Climate Change
K Capitalization Rate
LL Loan Loss
MBB MikroBanking Bulletin
MDG Millennium Development Goal
MFI Microfinance Institution
NGO Non Governmental Organization
NGS Net Gains to Society
PAR Portfolio at Risk
TA Transaction Costs
UN United Nations
USA United States of America
5
1 Introduction
The poor stay poor not because they are lazy but because they have no access to
capital1 If this claim made by nobel laureate Milton Friedman actually holds will be
discussed in the initial part of this paper
First a short overview of the development of the microfinance sector will be given
showing that the concept of providing financial services to low income people is much
older than still believed by many development practitioners and bankers around the
world This is important since it underlines the contribution that microfinance
institutions (MFIs) can make to the development of the financial sector in their
respective countries Subsequently the various ways how such services can assist low
income people will be discussed demonstrating that even the poorest can benefit from
the provision of small loans This is a view that is still questioned in the academia
In the second part of this paper it will be shown that although some 10000
organizations are involved in microfinance already2 they are not even close to meet the
tremendous demand for low scale financial services This sector is still widely neglected
by for profit investors and traditional bankers After examining why these groups
continue to avoid investments in the microfinance industry it will be checked if the
assumptions that underline their arguments actually hold The possibility if MFIs could
raise their interest rates to an extend that would allow them generate profits sufficiently
high to attract for profit investors will be discussed
According to Hulme and Mosley MFIs ldquocan either go for growth and put their resources
into underpinning the success of established and rapidly growing institutions or go for
poverty impact and put their resources into poverty-focused operations with a higher
risk of failure and a lower expected returnrdquo3 If this is true will be examined in the third
part by checking if poor borrowers are able to bear interest rates significantly above
1 See Friedman (nd)2 See BlueOrchard (2004a)3 See Hulme and Mosley (1996) p 206
6
those charged by conventional banks Finally a sample of 39 MFIs will be used to verify
the drawn conclusions by examining the effects their interest rates have on their
financial performances and their repayment record
7
2 The Development of Microfinance
21 What is Microfinance
According to the Journal of Microfinance the term defines what ldquois arguably the most
innovative strategy to address the problems of global povertyldquo4 This view is shared by
the United Nations (UN) which declared that the year 2005 would be the international
year of microcredit5 while their General Secretary Kofi Annan stated in 2002 that
ldquo[m]icrocredit is a critical anti-poverty tool and a wise investment in human capitalrdquo6
Hossain describes microfinance as ldquothe practice of offering small collateral free loans
to members of cooperatives who otherwise would not have access to the capital
necessary to begin a small business or other income generating activitiesrdquo7 This view is
to narrow since it not only excludes such services as saving accounts and insurances8
but also ignores the possibility of collateral demanding MFIs Although it is true that
many MFIs do not take collateral especially if they are focusing on the poorest which
normally do not possess any collateral9 several MFIs in fact do require some form of
collateral10
Roth and Steinwand give a more general definition They describe microfinance as ldquothe
provision of a wide range of financial services like saving accounts loans payment
services and insurances for people with no regular access to financial services through
traditional financial institutionsrdquo11 Here it is important not to confuse the terms
traditional or conventional with the term formal If for example an illiterate beggar
takes a $10 loan from the Grameen Bank in Bangladesh she becomes a client of a
4 See Woodworth and Woller (1999) p 65 See United Nations (1999) p 16 Annan (2002)7 Hossain (2004)8 See The Microfinance Gateway (nd) Robinson (2001) p9 Otero (1999) p 89 See chapter 3 for a more detailed discussion on poverty10 See Robinson 2002 p 24311 See Roth and Steinwand (2004) p 2 ldquodie Bereitstellung einer breiten Palette von Finanzdiensteistungen wie Spareinlagen Kredite Zahlungsverkehr und Versicherungsleistungen fuumlr Wirtschaftsakteure die keinen regelmaumlszligigen Zugang zu Finanzdienstleistungen durch klassische Finanzinstitutionen habenldquo
8
formal financial institution (a registered bank) but obviously not of a traditional or
conventional one12
Although the other services have become more important in recent years microcredit is
still considered their central service by most MFIs In many countries it refers to loans
below $ 100013 however for significant cross country comparison it is more
meaningful to look at the ratio of the loan amount to the gross national product (GNP)
or gross domestic product (GDP) per capita for the respective countries While a loan of
$1000 is more than four times larger than the GNP per capita in Uganda it represents
less than 20 of the GNP per capita in Mexico The MicroBanking Bulletin (MBB) has
categorized the target market for MFIs by the average outstanding loan amount as a
percentage of the GNP per capita ranging from Low-end (less than 20) to Small
Business (more than 250)14 Especially for the latter category one must to look closely
at the condition of the financial service market where an institution is active Although
MFIs exist in industrialized countries15 one would definitely turn to a traditional
financial institution for a loan bigger than 250 of the GNP per capita and therefore not
to a MFI according to the definition presented above
22 The Origin of Microfinance
Although neither of the terms microcredit or microfinance were used in the academic
literature nor by development aid practitioners before the 1980s or 1990s16
respectively the concept of providing financial services to low income people is much
older
While the emergence of informal financial institutions in Nigeria dates back to the 15th
century17 they were first established in Europe during the 18th century as a response to
the enormous increase in poverty since the end of the extended European wars (1618 ndash
12 See Yunus (2002) p 19 for a more detailed description of the destitute member program of the Grameen Bank which focuses exclusively on persons with no regular income and no assets at all 13 See MicroBanking Bulletin (1997) p 614 See MicroBanking Bulletin (2003) p 5415 See Yunus (1998a) pp 229 et sqq16 See Robinson (2001) p XXX17 See Seibel (2003a) p 12
9
1648)18 In 1720 the first loan fund targeting poor people was founded in Ireland by the
author Jonathan Swift19 After a special law was passed in 1823 which allowed charity
institutions to become formal financial intermediaries a loan fund board was established
in 1836 and a big boom was initiated Their outreach peaked just before the government
introduced a cap on interest rates in 1843 At this time they provided financial services
to almost 20 of Irish households20
The credit cooperatives21 created in Germany in 1847 by Friedrich Wilhelm Raiffeisen
served 14 million people by 191022 He stated that the main objectives of these
cooperatives ldquoshould be to control the use made of money for economic improvements
and to improve the moral and physical values of people and also their will to act by
themselvesrdquo23
In the 1880s the British controlled government of Madras in South India tried to use the
German experience to address poverty which resulted in more than nine million poor
Indians belonging to credit cooperatives by 194624 During this same time the Dutch
colonial administrators constructed a cooperative rural banking system in Indonesia
based on the Raiffeisen model25 which eventually became Bank Rakyat Indonesia
(BRI) now known as the largest MFI in the world26
23 Microfinance after the Second World War
Because of further prudential regulation and effective supervision eg through bank
superintendencies the banking sector in the now developed world experienced
continuous growth Today the vast majority of the citizens of the industrialized
countries have access to financial services with many of them being customers of
former MFIs27
18 See Steinwand (2001) p 5119 See Robinson (2002) p 9620 See Seibel (2003a) p 1021 first known as Darlehnsvereine and now called Raiffeisenbanken22 See Morduch (1999a) p 157323 Raiffeisen (1966) quoted in Richardson (2000) p 324 See Morduch (1999a) p 157425 See Robinson (2002) p 9726 See Roth Steinwand (2004) p 327 See Seibel (2003a) p 11
10
This is not true for most developing countries where market penetration of financial
institutions is far from reaching the majority of the inhabitants (see chapter 4) A variety
of reasons is responsible for this including that the banking sector in the most
developing countries have developed in a very different way to than those in
industrialized countries
One of the most important reasons is that in contrast to the industrialized countries little
attention has been paid to the legal recognition prudential regulation and effective
supervision of informal financial institutions28 This insecure legal environment leads to
several problems Since the regulatory framework for mobilizing savings often does not
fit the needs of institutions targeting low income people many organizations are not
permitted to do so and are therefore missing funds to on-lend as credit29 An additional
problem is the lack of a deposit insurances This not only increases the risk of a bank
run but also keeps people from depositing their savings in a financial institution30 In
addition inappropriate interest rate ceilings prevail in many countries While politics
claim they are lowering the interest rates charged to the poor they de facto only limit
their access to financial services (see chapter 5)31
Another problem that retarded the growth of the financial sector in developing countries
was the supply-leading finance theory which dominated the development strategies of
many countries after the second world war32 This theory ldquo refers to the provision of
loans in advance of the demand for credit for the purpose of inducing economic
growthrdquo33 Since it was believed that poor people were neither able to save (and thus
dependent on outside funding) nor capable of paying commercial rates of interest
massive subsidized credit programs were established34 The results were alarming
Repayment rates often did not exceed 50 percent and some government financed
programs even had default rates of more than 90 percent35 The main reason being that
credit was not provided according to business management principles but instead
28 See Seibel (1998) p 829 See Robinson (2001) p 4930 See Staschen (1999) p 1431 See Gibbons (2000) p 1532 See Morduch (1999a) p 157033 Robinson (2001) p 14034 See Borst (2004) pp 33 et sqq35 See Yunus (1998a) p 154 Robinson (2001) p 145
11
according to political objectives Therefore receiving loans was seen as a reward for the
constituents rather than as a business transaction Most of the funds earmarked for the
poor also never reached them ending up instead in the hands of the local elites
Attracted by the below market interest rates and the possibility not to pay back at all
these groups lobbied to be treated privileged and often used the money received for
consumption or for on-lending at higher rates36 But subsidized credit not only
encouraged corruption it also discouraged sustainable financial institutions since they
could not compete with interest rates that were not aimed to cover all costs and were
sometimes even lower than the interest paid on savings37 The low or negative spread
also worked as a negative incentive to institutionsrsquo effort to mobilize savings which in
turn intensified the problem of credit rationing (see chapter 5)
24 Microfinance Today
In the 1970s a paradigm shift started to take place The failure of subsidized government
or donor driven institutions to meet the demand for financial services in developing
countries let to several new approaches Some of the most prominent ones are presented
below
Bank Dagan Bali (BDB) was established in September 1970 to serve low income people
in Indonesia without any subsidies and is now ldquowell-known as the earliest bank to
institute commercial microfinancerdquo38 While this is not true with regard to the
achievements made in Europe during the 19th century it still can be seen as a turning
point with an ever increasing impact on the view of politicians and development aid
practitioners throughout the world In 1973 ACCION International a United States of
America (USA) based non governmental organization (NGO) disbursed its first loan in
Brazil39 and in 1974 Professor Muhammad Yunus started what later became known as
the Grameen Bank by lending a total of $27 to 42 people in Bangladesh40 One year
later the Self-Employed Womenrsquos Association started to provide loans of about $15 to
36 See Robinson (2001) pp 144 et sqq37 Before BRI underwent a major transformation in 1983 a negative spread between interest rates on loans and savings existed While the bank lent at a 12 annual effective interest rate it paid 15 on savingsSee Robinson (2001) p 10638 Wardhana (2001) p XXVII39 See ACCION (nd)40 See Yunus (1998a) p 16 et sqq
12
poor women in India41 Although the latter examples still were subsidized projects they
used a more business oriented approach and showed the world that poor people can be
good credit risks with repayment rates exceeding 9542 even if the interest rate charged
is higher than that of traditional banks Another milestone was the transformation of
BRI starting in 1984 Once a loss making institution channeling government subsidized
credits to inhabitants of rural Indonesia it is now the largest MFI in the world being
profitable even during the Asian financial crisis of 1997 ndash 199843
In February 1997 more than 2900 policymakers microfinance practitioners and
representatives of various educational institutions and donor agencies from 137
different countries gathered in Washington DC for the first Micro Credit Summit This
was the start of a nine year long campaign to reach 100 million of the world poorest
households with credit for self employment by 200544 According to the Microcredit
Summit Campaign Report 67606080 clients have been reached through 2527 MFIs by
the end of 2002 with 41594778 of them being amongst the poorest before they took
their first loan45 Since the campaign started the average annual growth rate in reaching
clients has been almost 40 percent46 If it has continued at that speed more than 100
million people will have access to microcredit by now and by the end of 2005 the goal
of the microcredit summit campaign would be reached As the president of the World
Bank James Wolfensohn has pointed out providing financial services to 100 million of
the poorest households means helping as many as 500 ndash 600 million poor people47
41 See Bhatt (1997)42 See Yunus (1998a) p 143 et sqq43 See Robinson (2002) p 38044 See Daley-Harris (2003) p 345 ldquoThe Microcredit Summit Campaign defines ldquopoorestrdquo as those who are in the bottom half of those living below their nationrsquos poverty line or are living on less than $1 a day adjusted for purchasing power parity (PPP)rdquo See Daley-Harris (2003) p 3 This definition will also be used throughout this paper46 See Daley-Harris (2003) p 1847 See Morduch (1999a) p 1570
13
3 The Impact of Microcredit
31 Microcredit and the Millennium Development Goals
In 1996 Ismail Serageldin the then chair of the Consultative Group to Assist the Poorest
(CGAP)48 claimed that ldquo[m]icrofinance is a proven instrument to assist the very poorrdquo49
This view is also shared by the World Watch Institute50 and underlines what has been
stated above namely that microfinance can be used as a strong anti-poverty tool But
does microfinance actually meet these expectations and keep this promise51
The impact that microcredit has on the lives of poor people will be demonstrated by
showing how it contributes to each of the eight Millennium Development Goals
(MDGs)52 which are related to the reduction of poverty in all its forms These goals
were resolved in September 2000 by the General Assembly of the UN in their
Millennium Declaration53
32 The Eradication of extreme Poverty and Hunger
The aim of the first MDG is to halve the proportion of people who live on less than $1 a
day between 1990 and 2015 According to current population projections of the World
Bank54 this would equal 849 million people in 201555
48 The Consultative Group to Assist the Poorest is a consortium of 28 public and private development agencies working together to expand access to financial services for the poor in developing countries and was established by the World Bank in 1995 Recently it changed its name to Consultative Group to Assist the Poor49 See Serageldin (1996) p 1150 See Gardner (2002) p 1851 See Morduch (1999a) pp 1569 et sqq52 The Millennium Development Goals are (1) eradicate extreme poverty and hunger (2) achieve universal primary education (3) promote gender equality and empower women (4) reduce child mortality (5) improve maternal health (6) combat HIVAIDS malaria and other diseases (7) ensure environmental sustainability and (8) develop a global partnership for development53 See United Nations (2000)54 See World Bank (2004) p 38 et sqq55 Although it is not explicitly mentioned in the Millennium Declaration it is commonly assumed that the share of people living on less than $1 in low and middle income countries should be halved If the share would be calculated with regard to the worldrsquos total population the goal for 2015 would 818 million people For the worldrsquos total population in 1990 see US Census Bureau (2004)
14
Today almost 11 billion people live on less than $1 and more than 27 Billion live on
less than $2 per day56 The mean income for those living under $1 a day is $077 and it
is $125 for those living under $2 a day57 While the number of people living on less
than $1 per day is slowly decreasing and is expected to be 913 million in 2015 the
number of people living on less than $2 a day is actually increasing58 One of the
outcomes from this degree of poverty is that more than 27000 children die every day
from mostly preventable diseases many of them related to hunger59
Microcredit enables poor people to start new businesses or to diversify existing ones
which helps them to increase their income In addition to large amounts of anecdotal
evidence several studies have documented the positive economic impact microcredit
has on its clients Cloud and Panjaitan-Drioadisuryo have found that the average income
of a sample of BRI borrowers has increased by 112 percent and that 90 percent of their
families have crossed the poverty line60 Only 12 out of the 121 respondents of that
study reported that their income had not increased61 According to the Grameen Bank
website 5109 percent of their clients have crossed the poverty line since they took their
first loan62
A study conducted by Barnes showed that the program of the Zambuko Trust a local
MFI in Zambia had a considerable impact on the poorest clients consumption of meat
fish and chicken63 While 76 percent of the continuing clients of the MFI called Share in
India significantly increased their income and 50 percent have crossed the poverty line 64 Khandker discovered in his well known study ldquoFighting poverty with microcreditrdquo
that there is a connection between the microcredit programs of three Bangladeshi MFIs
and household per capita expenditure For every dollar borrowed by a Grameen Bank
member household consumption increases by $018 In addition he found that 5 percent
56 See Chen and Ravallion (2004) p 2957 In fact those people live on less than $108 and $215 respectively a day in 1993 PPP This means that the nominal dollar value of their income is considerably lower See Chen and Ravallion (2004) p 9 58Both numbers are decreasing in Asia but increasing in the rest of the world See Chen and Ravallion (2004) p 22 et sqq59 See UNICEF (2002) p 660 A consistent definition of the term ldquopoverty linerdquo does not exists among different nations Therefore the term will be used according to the definition of the respective country in this paper61 See Panjaitan-Drioadisuryo and Cloud (1999) p 77562 See Grameen Bank (2004) 63 See Barnes (2001) p 8664 See Simanowitz and Walter (2002) p 16
15
of Grameen Bank borrowers move out of poverty every year65 Supposing Khandkerrsquos
findings were correct for all MFIs worldwide and the Microcredit Summit Campaign
achieved its goal of reaching 100 million of the poorest households with microcredit by
2005 then 25 million people (assuming an average family size of five) would leave
poverty every year66 Although this number would have to be adjusted in order take into
consideration the MFI clients who have crossed the poverty line already and of course
the experiences made in Bangladesh can not be transferred precisely to other countries
it still demonstrates the enormous effect that microcredit can have on assisting the
poorest to move out of poverty
Although a 1996 study of Hulme and Mosley states that providing microcredit can also
have a negative impact on the income of the poorest households67 these findings can
be considered as disproved by the recent bulk of evidence drawing favorable
conclusions68
33 Achievement of universal primary Education
The aim of the second MDG is to ensure that all children will be able to complete
primary school by 2015
Currently more than 100 million children most of them girls are not in school69
Besides school fees poor households often can not afford to send their children to
school because they need them to help in the family business
Microcredit programs mainly contribute to the second MDG by increasing families
income and therefore enabling parents to send their children to school Barnes Gaile
and Kibombo found that clients of an MFI in Uganda spent significantly more on
childrenrsquos education than non-clients70 and in Zambia Barnes showed that ongoing
participation in the Zambuko Trustrsquos program had a positive impact on the members
65 See Khandker (1998) p 5666 See Daley-Harris (2003) p 2467 See Hulme and Mosley (1996) p 180 et sqq 68 See Gibbons and Meehan (1998) p 13669 See UNICEF (2002) p 2270 See Barnes Gaile and Kibombo (2001) p 64
16
children staying in school71 In Bangladesh the probability of girls enrolling in school
increased by 19 percent for every 1 percent increase in Grameen Bank loans to female
clients For boys this number was even higher with the mean being 24 percent72
34 Promote gender Equality and empower Women
The aim of the third MDG is to eliminate the disparity in the ratios of girls to boys in
primary secondary and tertiary education in the ratio of literate females to males and to
increase the share of women in the labor market and in parliament73
At present the literacy rate for women is lower than for man all over the world
According to the Human Development Report 2004 the average female literacy rate as
a percentage of male literacy rate is 759 in developing countries and is as low as 37 in
Niger74 But women are not only discriminated against in education but also in access to
medical services and therefore have a higher mortality rate than man75 The worldwide
tendency for women to be underrepresented in the labor market and in the parliaments is
even more severe in developing countries76 Although several women have become
heads of state in various Asian countries (eg Bangladesh India and Indonesia) this is
probably due to them being wives or daughters of former respected male politicians
Since women have a higher repayment rate than man77 and also tend to invest increases
in income on the household and on their children rather than on themselves78 most
MFIs prefer female clients79 Therefore they empower women in many ways Often
MFIs not only encourage women to become involved in financial transactions for the
first time but also to become independent active members of the economy and to
acquire assets in their own names Cheston and Kuhn found that 68 percent of the
women participating in an MFI program in Nepal ldquohellip experienced an increase their
71 See Barnes (2001) p 8472 See Khandker (1998) p 4973 See World Bank (2001) p 2074 See UNDP (2004) pp 225 et sqq75 See Sen (2000) p 23276 See Sen (2000) pp 242 et sqq77 See Littlefield Morduch and Hashemi (2003) p 778 See Yunus (1998a) pp 116 et sqq79 According to the Microcredit Summit Campaign Report 79 or 37677080 of the poorest clients were women See Daley-Harris (2003) p 3
17
decision-making roles in the areas of family planning childrenrsquos marriage buying and
selling property and sending their daughters to school - all areas of decision making
traditionally dominated by menrdquo80 The program of the Lower Pra Rural Bank in Ghana
had an positive impact on womenrsquos participation in the community81 which is true as
well for the CRECER program in Bolivia82 In Bangladesh the Grameen Bank and the
Bangladesh Rural Advancement Committee (BRAC) the two biggest MFIs of the
country had a significant positive effect on womenrsquos empowerment measured through
eight different indicators83 After joining Grameen Bank only 21 percent of the female
members considered themselves as unemployed while this number was 50 percent
before joining84 According to the Grameen Bank website 93 percent of the Bankrsquos
shares are owned by their borrowers which elect the members of the board every three
years They also get familiar with the election process by more frequently voting for
representatives at the lower level of the organizational structure Partly because of this
experience they are more likely to run for public office In the 2003 local government
elections Grameen Bank members constituted 24 of the seats reserved for women
while they represent less than 10 of Bangladeshi adult female population85 Female
clients of MFIs from countries like the Philippines Bolivia and Nepal have reported
similar occurrences86
35 Reduce Child Mortality and improve Maternal Health
The aim of the fourth MDG is to reduce the under-five mortality rate by two-thirds
between 1990 and 2015 and the fifth MDG strives for a three quarter reduction in the
maternal mortality ratio by the same date
As has been stated above more than 10 million children are dying annually in the
developing world of mostly preventable causes with malnutrition playing a role in over
80 See Cheston and Kuhn (2002) p 1881 See MkNelly and Dunford (1998) p 5482 See MkNelly and Dunford (1999) p 7183 The eight different indicators are ldquofreedom of movement economic security ability to make small and larger independent purchases participation in important family decisions relative freedom from domination by the family political and legal awareness and participation in political campaigning and public protestsrdquo Hashemi and Schuler (1998) p 3684 See Holcombe (1995) p 5185 See Grameen Bank (2004)and CIA (2004)86 See Littlefield Morduch and Hashemi (2003) p 8
18
half of the childrsquos deaths and in over 50 countries child mortality rates are greater than
100 deaths per 1000 live births87 Maternal mortality is also a significant problem in the
developing world with more than 500000 women dying every year from pregnancy
related causes88
MFIs are mainly contributing to the these MDGs by increasing families income and
therefore enabling the households to afford better nutrition and medical services
Furthermore they are often linked with microinsurance or health education programs
In addition to what has been showed in chapter 31 Pitt Khandker and Millimet
estimate that a 10 percent increase in the loan size of a female borrower in Bangladesh
increases the arm circumference of their daughters by 6389 Smith and Jain found that
village banking in Ecuador had a positive effect on child diarrhea90 which is responsible
for 15 of child deaths91 Since Sen argues that an improved status of women within
the family reduces child mortality92 the empowerment of women through MFIs is also
contributing to this cause
Although no study has been conducted so far on the direct impact of microcredit on
maternal health it can be assumed that an overall improvement of access to medical
services reduces maternal mortality as well A study of the Morgan State University for
example suggests that microcredit has a positive effect on the prevalence of
contraceptives93 which leads to a decrease of unwanted pregnancies and therefore
reduces maternal death
36 Combat HIVAIDS Malaria and other diseases
The aim of the sixth MDG is to halt and begin to reverse by 2015 the spread of
HIVAIDS malaria and other major diseases and to assist children orphaned by HIV
87 See World Bank (2001) p 888 See WHO (2004) 89 See Pitt Khandker and Millimet (2003) p 11390 See Smith and Jain (1999) p 3791 See WHO (2001) 92 See Sen (2000) p 23593 See Amin et al (2001) p 1614
19
In 2003 29 million people died because of HIV and about 48 million became infected
the greatest number since AIDS was discovered 23 years ago94 This pandemic has lead
to a tremendous decrease in the life expectancy in the hardest hit countries Botswana
for example one of the richest and most democratic countries in Africa has a
HIVAIDS adult prevalence rate of 388 and a life expectancy at birth of less than 31
years95
Malaria not only causes more than one million deaths annually it leads also to 300 ndash
500 million clinical cases a year Both numbers have been steadily increasing over the
past two decades96 More than two million people a year are killed by tuberculosis
another global health problem This curable disease is estimated to cost poor
communities about $12 billion every year since even those who survive normally lose
more than 3 month of work time while recovering97
MFIs contribute to the sixth MDG in several ways By increasing clientrsquos income they
help households affected by HIV or other diseases to better cope with the situation
Besides spending more money on health services and nutrition MFI clients also tend to
be more able and willing to support AIDS orphans than non clients98 In addition to the
already stated increase in the use of contraceptives99 several innovative approaches to
deal with disease related crisis have also arisen This is of course necessary not only to
counteract the devastating effect the above discussed epidemics can have on MFI
clients but also to not put the viability of the respective institution at risk One option is
to integrate education services in the MFI programs and encourage clients to form
solidarity groups100 It has been shown that these services do not necessarily decrease
the effectiveness of the institutionsrsquo employees101 Another way is to strengthen the ties
to NGOs specialize in dealing with the respective disease Synergies gained through this
cooperation can help clients to better deal with the situation and in the end increase their
94 See UNAIDS (2004) p 2395 See CIA (2004)96 See World Bank (2001) p 1697 See World Bank (2001) p 1298 See Barnes (2001) p 6499 See also Kim et al (2002) p 18100 See Donahue and Sussman (1999) p A 14101 See Donahue Kabbucho and Osinde (2001) p 25
20
repayment rates Various MFIs also have introduced loan and health insurance products
or cultivated linkages with organizations doing so102
It has to be stated that despite the benefits MFIs can provide to people effected by
HIVAIDS or other diseases microcredit can also be a burden for those who are already
chronically ill These people can still benefit through loans provided to members of the
family or the community or through one of the other services mentioned above
37 Ensure environmental Sustainability
The aims of the seventh MDG are to support and promote the principles of sustainable
development and put them into action and to improve the lives of slum dwellers and
people without sustainable access to safe drinking water and sanitation
Today climate change is considered as the major environmental problem103 The
Intergovernmental Panel on Climate Change (IPCC) states that human activities
contribute to most of the 06 degC increase in global average temperature over the 20th
century and the predicted increase of another 14 to 58 degC between 1990 and 2100104
Emission of carbon from fossil fuel is reported to have the dominant influence on this
development While the total emission was 16 billion tons in 1950 it was already 65
billion tons in 2000 and is expected to continue to grow105 This development would
lead to a rise in the average sea level of between 9 and 88 centimeters during the next
century106 Furthermore it is predicted that global warming increases the risk of extreme
events like cyclones or floods leads to an increase in the number of people infected by
diseases like malaria and decreases the potential crop harvest and water availability
especially in developing countries107 In 2000 already 11 billion people lacked access to
clean drinking water and 24 billion to basic sanitation108
102 See Barnes (2001) p 40 Barnes Gaile and Kibombo (2001) p 13 and Grameen Bank (2004)103 See Gardner (2002) p 5104 See IPCC (2001) pp 2 et sqq105 Worldwatch Institute (2002) p 52 et sqq106 See IPCC (2001) p 16107 See Dunn and Flavin p 29108 See UNFPA (2004) p 18
21
MFIs contribute to achieving the seventh MDG in several ways By providing loans for
the purchase of renewable energy technologies they help people in developing
countries to increase their per capita energy consumption without increasing the carbon
dioxide emission In a 2003 survey of 140 MFIs from 80 different countries 21 said
they provide credits for solar home systems and another 19 stated they are interested in
becoming engaged in this business109 While Grameen Shakti a rural energy service
company cooperating with the Grameen Bank in Bangladesh has already installed more
than 23000 solar home systems110 a 2000 World Bank study reports twelve projects
providing solar home systems to rural households with a target of 500000
installations111 It has also been suggested that MFIs should raise environmental
awareness among their clients112 but so far no data is available on how staff can cope
with this additional task Many MFIs also provide loans for improvements in sanitation
and the water supply of their clients Varley gives several examples from Africa Asia
and Latin America on how microcredit not only has helped to invest in rainwater
collection systems but also how it has enabled households to increase their water
supply through community water associations113 In addition many MFIs provide credit
for the construction of sanitary latrines114 The situation of slum dwellers is also
positively effected by MFIs Directly through their services in poor urban communities
and indirectly by creating jobs in rural areas and therefore easing the pressure on urban
labor markets
38 Develop a global Partnership for Development
The eight MDG is about the means to achieve the other seven MDGs It calls for all
players involved in the endeavor of development and poverty eradication to work as
partners in a global context
Again MFIs are contributing to the eight MDG in many ways This is occurring through
international networks that provide funding and technical assistance through internet
information portals and specialized journals through social and for profit investors and
109 See Wimmer and Barua (2004) p 174110 Barua (2004) 111 See Martinot and Cabraal (2000) p 6112 See Pallen (1997) p 11 Lal (nd)113 See Varley (1995) pp 39 et sqq114 See Jalvaani (1999) pp 1 et sqq Varley (1995) pp 39 et sqq
22
specialized rating agencies The Bangladesh-based Grameen Trust is one of around 30
networks in operation Besides collaborating with over 200 MFIs around the world it
has directly operated three projects in Afghanistan Kosovo and Myanmar115 While the
ACCION network serves almost 12 million active clients in 19 countries throughout
America and sub-Saharan Africa116 FINCArsquos network operates in three different
continents where it serves more than 200000 customers117 In November 1997 the
MicroBanking Bulletin (MBB) was first published by the microfinance program at the
Economic Institute at the University of Colorado118 Its aim is to develop a database on
the financial performance of MFIs from all over the world which is now available
through the Mix Market an internet portal that also provides information about more
than 300 MFIs investors donor institutions and other related development
organizations119 Two years later the Marriott School at Brigham Young University
started to publish the Journal of Microfinance which has an editorial board of
microfinance experts from all over the world and offers the latest research on this
topic120 In the late 1990s a number of companies became attracted by the microfinance
market and started to invest in MFIs The German based Internationale Mikro
Investitionen Aktiengesellschaft (IMI) for example has already invested more than euro46
million in 19 MFIs in four different continents and plans to invest another euro27 million
before October 2004121 BlueOrchard Finance a microfinance investment consultancy
has channeled more than $60 million worth of private capital to some 40 MFIs
worldwide through investment funds and bond issues122 Big commercial banks like
Citigroup Deutsche Bank and ABN Amro also started to get involved in the
microfinance sector although this is mainly still perceived as a public relation activity
and not as a for-profit investment123 There are also several rating agencies specializing
in MFIs Dependent on their rating these institutions can help MFIs to receive money
from donors or investors Four of the most prominent rating agencies are PlanetFinance
115 See Grameen Trust (nd)116 See ACCION (nd)117 See FINCA (nd)118 See MicroBanking Bulletin (1997) p 5119 See The Mix (2004)120 See Woodworth and Woller (1999) p 6121 See IMI (2004)122 See BlueOrchard (2004b) p 3123 See Busch and Kort (2004) p 8 Fischer (2003) p 6
23
with headquarters in France M-Cril based in India Microfinanza in Italy and
MicroRate with offices in the USA and South Africa124
124 See Microfinance Rating and Assessment Fund (2004)
24
4 Microcredit Outreach
41 The Demand for Microcredit
Although it has been shown that microcredit is one of the most effective poverty
eradication tools that it is considered a human right by some of its advocates125 and it
can contribute considerably to the development of the financial sector in developing
countries an enormous gap still exists between supply and demand for microcredit
Estimates on the demand for microcredit vary greatly While USAID estimates the
number of potential microfinance clients is between 100 and 200 million126 the
Microcredit Summit Campaign states the total demand is more than 234 million
people127 CGAP recognizes some 500 million micro-entrepreneurs who have the
potential to become customers of MFIs128
Marguerite Robinson calculates the demand as follows ldquoAssuming five people to a
household among the 45 billion people living in low- and lower-middle-income
economies in 1999 (World Bank World Development Report 20002001) there are 900
million households in those economies If estimating conservatively we assume that
informal commercial moneylenders supply credit to 30 percent of these households at
least once a year this would mean that there are 270 million households borrowing
from informal moneylenders in a year Undoubtedly however many of these
households borrow multiple times within a yearrdquo129 Although this is a very rough
estimate assuming big differences in demand for microcredit in different countries the
number seems to be the most meaningful In contrast to the estimate of the Microcredit
Summit Campaign it does not include every single household living on less than $1 a
day but according to the definition presented in chapter 1 it counts everyone who has
no regular access to traditional financial institutions but demands such services
Obviously not all people who draw on moneylenders have financial needs that could be
matched through MFIs On the other hand interest rates charged by moneylenders tend
125 See Yunus (1998b) 126 See Christen et al (1995) p 15127 See Daley Harris (2003) p 22 128 See Robinson (2001) p 26129 See Robinson (2001) p 215
25
to be considerably higher than those of MFIs The former normally charge effective
monthly rates between ten and several hundred percent per month the latter generally
charge between 15 and five percent which enables them to attract additional clients130
42 The Supply of Microcredit
In spite of the impressive growth of MFIs around the world the demand for microcredit
is far from being met and this it is not likely to change in the near future The
Microcredit Summit Campaign reported that by the end of 2002 67606080 clients131
were reached through MFIs and that this number has increased by almost 40 percent
annually for the last five years132 It is likely that this tremendous speed of growth is at
least partly due to including MFIs which have not been reporting to the Campaign from
its start in 1997 although they have already existed at that time These institutions
contributed 22 percent to the growth in poorest clients in 2000 578 percent in 2001 and
338 percent in 2002 The growth of the poorest clients increased at least party because
of an expanded definition of the term ldquopoorestrdquo133 Since the contribution of MFIs
which previously have not been considered can be expected to decrease dramatically
the growth rate as stated by the Microcredit Summit Campaign can not be used to
predict the future development of the microfinance sector Another factor likely to slow
down the growth is the concentration of microfinance activities in some Asian countries
where almost 90 percent of the poorest microfinance clients live today134 Even if one
takes into consideration the relative size of Asiarsquos population and the fact that many
MFI customers in Latin America are relatively better off and therefore are not included
in this numbers the coverage of this part of the world far exceeds the others In
Bangladesh for example the microfinance market is close to saturation More than
eleven million households were served by several hundred MFIs in 2001135 Among
them are Grameen Bank and BRAC two of the best known MFIs in the world both
providing their services to more than three million customers With an average
household size of five it can be assumed that in Bangladesh the number of people
130 See Gibbons and Meehan (1999) pp 144 et sqq131 41594778 of them belonged to the poorest before they took their first loan The relative numbers in the following are for these poorest clients only since no other current data was available It can be assumed though that this works as a good proxy for the total number of clients 132 See Daley Harris (2003) p 3133 See Daley Harris (2003) p 17134 See Daley Harris (2003) p 21135 See Ahmed (2003)
26
benefiting from microcredit already surpasses the number of people living below the
poverty line which is estimated to be slightly higher than 50 million136 Therefore
Bangladesh will not contribute to the growth of the microfinance sector as much as it
has done in previous years This is also true for Vietnam Thailand and to a lesser
extent Indonesia Eight of the nine MFIs serving more than one million clients are based
in these countries while the ninth is based in India where due to its one billion
inhabitants the microfinance market is still far from saturation137 In contrast the
supply in Brazil meets less than two percent of the demand which is estimated to be
about 58 million potential clients138 For these reasons greater amount of future growth
must come from smaller or new MFIs in Latin America India China and especially
Africa where almost 30 percent of the worldrsquos poorest live139
43 Meeting the Demand
To fill the gap between the demand and supply for microcredit tremendous investments
are necessary to increase the loan funds of MFIs and build up their capacity through
upgrading existing institutions or building new ones Again estimates on how much
capital is needed vary greatly with the highest being at more than $300 billion140
In 1997 the Microcredit Summit Campaign estimated that $216 billion would be
needed to achieve their goal of providing microcredit to 100 million of the poorest
households This was calculated in the following way Since some 8 million people
already received microcredit in 1997 another 92 million needed to be reached
Assuming $200 ($150 for loan fund and $50 for capacity building) would be needed per
person for 88 million people in developing countries and $1000 ($500 for loan fund and
$500 for capacity building) would be needed for 4 million people in industrialized
countries the capital required ends up to be $216 billion141 For several reasons this
136 See CIA (2004)137 These institutions are The Grameen Bank BRAC Proshika and the Association for Social Advancement (ASA) in Bangladesh the Vietnam Bank for Agriculture and Rural Development (VBARD) and the Vietnam Bank for the Poor (VBA) in Vietnam BRI in Indonesia Bank for Agriculture and Agricultural Co-operatives (BAAC) in Thailand the National Bank for Agriculture and Rural Development (NABARD) in India See Ahmed (nd) p 1 Llanto (nd) p 337138 See Mezzera (2002) p 23139 See See Chen and Ravallion (2004) p 29140 See Clear Profit (2004) Prisma (2002)141 See The Microcredit Summit (1997)
27
number is not qualified to predict the total amount of capital needed to meet the demand
for microcredit On the one hand it focuses mainly on the low end of the market and
therefore underestimates the average loan fund needed On the other hand it does not
take the increasing capital demand from established MFIs into account A survey of 119
MFIs found that the average loan size to increased from $406 in 2002 to $498 in
2003142 This is mainly due to the fact that MFI clients once they have paid back their
loans usually demand larger ones for the continual development of their businesses
and therefore further increase the demand for capital of established MFIs The Grameen
Bank for example has a ceiling on its loans which increases or decreases depending on
the borrowers performance regarding repayments and savings143 While the maximum
amount for the first loan is fixed at approximately $75144 the largest loan disbursed so
far was $17195145 Thus if one estimates that by now 100 million people are borrowing
from MFIs146 another 170 million need to be reached to meet the estimated demand
Assuming an average of $600 ($400 for loan fund and $200 for capacity building) is
needed for every new client and another $200 is needed for every existing client to meet
the demand for larger loans a total of $122 billion is required This rough estimate
helps to convey the approximate amount of capital needed to meet the demand for
microcredit
So far the demand for funds is being partly met by donors which annually provide
between $500 million and $1 billion147 and through the mobilization of local savings
Obviously the amount of money provided by donors will not be able to meet the capital
demand for microcredit in the short term The mobilization of savings on the other hand
has been extremely successful in some cases with BRI probably being the most
prominent example After adapting commercial principals in October 1984 BRI was
able to raise its deposits from $161060 to more than $32 billion in 2003 which equals
almost two times its current loan portfolio148 Many other MFIs like BDB in Indonesia
142 Own calculations Without BRI the numbers would be $343 and $409 See Appendix 1143 See Grameen Bank (2003) p 13144 The accurate amount is 5000 Taka See Interview with Shaw Newaz145 Grameen Bank (2004)146 According to the data provided by the Daley Harris (2003) an annual increase in MFI clients ofapproximately 25 percent from 31122002 till the 3092004 would be needed to reach 100 million clients by now This rated is considerably below the average of the previous five years (38 percent) Therefore it can be assumed as realistic despite the growth hindering factors presented above147 See CGAP (2003) p 8148 See Robinson (2002) p 273 Mix Market (2004)
28
XacBank in Mongolia the Equity Building Society in Kenya or the Centenary Rural
Development Bank in Uganda also have managed to cover their loan portfolio fully
through internally mobilized resources149 The Grameen Bank is also expected to do so
in the first half of 2005150 In addition to raising much needed capital for on-lending the
provision of saving services can deliver notable social benefits itself151
Despite these impressive achievements even the combination of donor money and local
savings at their current levels will not be able to provide the capital needed to continue
the rapid growth of the microfinance sector Especially in their early years MFIs rely on
outside funding BRI for example needed six years before the amount of locally
mobilized savings surpassed the total amount of outstanding loans During this time
expenses and the loan portfolio were covered through a government grant worth $20
million and two World Bank loans of $5 and $97 million respectively152 It also
benefited from a network of more than 3600 branches which were established
throughout the country during the 1970s and early 80s in order to provide government
subsidized credit in rural areas153
The Grameen Bank also widely known as a best practice MFI has received about $175
million in direct and indirect subsidies between 1985 and 1996154 and continues to rely
on outside funding at below market interest rates This is made possible either through
special loans from the Bangladesh Bank or through offering bonds guaranteed by the
Bangladesh government155 - an option most MFIs do not have BDB might be one of the
very few examples which were able to finance their activities through savings and
commercial loans from the start but its outreach did not reach a large scale nor did it
serve the low end of the market In 2000 after 30 years of operation BDB provides
credit to only 10417 clients with an average loan balance of more than $5000156
approximately eight times the countries GDP per capita157
149 See Mix Market (2004)150 See Grameen Bank (2004)151 See Robinson (2001) pp 263 et sqq152 See Seibel and Schmidt (2000) p 4153 See Robinson (2002) p 180154 See Morduch (1999b) p 8155 See Morduch (1999ba) p 25 et sqq156 See Robinson (2002) p 387157 See CIA (2004)
29
Another problem keeping many MFIs from collecting savings is that they do not want
to become a regulated financial institution or do not meet the criteria in their respective
country and therefore they are simply not allowed to mobilize savings from the public
In summary the examples and numbers presented in this chapter support the argument
that the amount of capital that can be raised through donors and locally mobilized
savings is not enough for continuous rapid growth of the microfinance sector If this
lack of capital is not met through other sources the microfinance sector will fail to
contribute its full potential to the achievement of the MDGs
44 Microfinance and the Capital Markets
Regardless of whether the amount of capital needed for the development of the
microfinance sector is $20 or $300 billion it represents only a tiny fraction of the
worldwide capital markets which are estimated at $30 trillion158 Therefore if the
microfinance industry were able to tap the financial markets it would be able to grow
much faster and soon serve the millions of micro-entrepreneurs which currently can not
develop theirs businesses because of capital constrains Another advantage would be
that scarce donor money currently used for the development of the microfinance sector
could be used for other projects that do not have the potential to draw money from
commercial sources This view is shared by Michael Chu the former CEO of ACCION
who made the following statement in 1998 ldquoMicrofinance today stands at the threshold
of its next major stage the connection with the capital marketsrdquo159 Many attempts have
been made since that time Successful MFIs like BancoSol in Bolivia further
strengthened their ties to the capital markets which in some cases already provide the
majority of their funding160 Microfinance investment advisors like BlueOrchard
Finance have become middlemen for MFIs and the financial markets Nevertheless
these links are still far from reaching major scale Currently only approximately 20
percent of MFIs funding comes from commercial sources161 and the biggest bond issue
dedicated to fund MFIs totals only $40 million In addition these funds mainly end up
158 See Brynjolfsson (2004) 159 Chu (1998) quoted in Robinson (2001) p 23160 See Robinson (2001) p 69161 See Dominiceacute (2004)
30
in established institutions in Latin America or Eastern Europe162 while smaller
organizations only benefit indirectly if at all
162 See Clear Profit (2004) IMI (2004)
31
5 Credit Rationing
Until recently the predominant answer to why commercial banks or venture capital
companies did not invest in the microfinance sector was that the poor are not bankable
Besides lacking education and therefore not being able to deal with formal financial
institutions they were viewed as bad credit risk who were unable to invest the borrowed
money in a way that would allow them to repay the loan and interest at a commercial
rate163 Another reason that kept attention away from the idea of providing financial
services to low income people was the belief that informal moneylenders already met
this demand These skeptics felt affirmed through the poor performance of subsidized
credit programs as described in chapter 22 Although it is true that moneylenders
serve a huge number of people in the developing world they more often than not charge
usury interest rates of up to 20000 percent per month164 While the argument that poor
people are not able to participate in the formal financial market can be overcome by
adapting the services accordingly165 the claim of low returns on their investments is not
only proved wrong by empirical evidence but also contradicts economic theory as will
be shown in chapter 53
51 The imperfect Information Paradigm
A more elaborate explanation for the short supply of financial services to low income
people that can be derived from the imperfect information paradigm based
predominantly on the works of Akerlof166 and Stiglitz and Weiss167 After giving a brief
summary of their argument an adaptation of their findings to the microfinance market
will be presented and subsequently it will be shown how their conclusions can be
overcome
Behind the imperfect information paradigm lies the theory of asymmetric information
which simply states that if two parties conduct a transaction one is likely to have more
163 See Ghatak (1983) p 21 et sqq Yunus (1998) p 102 et sqq Robinson (2001) p 35 et sqq164 See Robinson (2001) p 17165 See Seibel (2003b) p 2 BRAC (2003) pp 15et sqq Yunus (1998) pp 151 et sqq 166 See Akerlof (1970) pp 488 et sqq167 See Stiglitz and Weiss (1981) pp 393 et sqq
32
information than the other and is trying to use that for its own advantage168 Applied to
the banking sector this means that a person applying for credit can better judge the
likelihood of repaying the loan than the bank This is because the borrower has better
knowledge of the market she wants to invest in her skills and her willingness to repay
Moreover the bank might not be able to observe if the borrower uses the loan for the
agreed purpose These occurrences can lead to what is known as adverse selection and
moral hazard In this case adverse selection refers to the problem that banks might
attract borrowers with a low probability of repayment if they can not distinguish
between high and low risk loan applicants Moral hazard occurs after the provision of
the loan when the borrower spends the money on a purpose different to the prescribed
purpose and therefore lowers the probability of repayment This can happen eg by
investing in a more risky project or through spending the money on consumption If the
bank is not able to find a cost effective way to avoid these problems it might raise its
interest rate in order to compensate for the increased risk
Figure 1 Expected Bank Return and the Interest Rate
Source Stiglitz and Weiss (1981) p 394
Since this might discourage low risk borrowers from applying for credit and encourage
borrowers who continue to take loans to invest in riskier projects the share of high risk
168 See Neus (1998) p 85 et sqq
INTEREST RATEI
EX
PE
CT
ED
RE
TU
RN
TO
TH
E B
AN
K
33
borrowers could increase and therefore reinforce the problems stated above Thus
increasing the interest rate beyond a certain point actually leads to a decrease in the
expected return to the lender This context is illustrated in figure 1 with I being the
interest rate which maximizes the expected returns to the bank Obviously the bank
would charge the interest rate I in order to maximize its expected return However this
price for capital was not determined through supply and demand as economic theory
would predict It is conceivable that at the interest rate I the demand for credit exceeds
the supply but even if loan applicants would offer to pay a higher interest rate the bank
would refuse because it associates such a loan with high risk As a result credit might
be rationed169
52 Adaptation to the Microfinance Sector
Through some adaptations this model can also help to explain the lack of funds
provided to low income people In the original model of Stiglitz and Weiss several
assumptions have been made that need to be suspended in order to compare the credit
markets for low and high income people and give an explanation why the latter is
widely neglected by institutional investors
Evidently the assumptions that the amount borrowed is equal for each loan applicant
and that transaction costs170 need not to be taken into account171 are not suitable for this
context While the average loan size of MFI customers is much smaller than that of
clients from traditional banks the transaction costs as a share of the loan are
considerably higher because the lenderrsquos costs for conscientious processing a credit
applications are only slightly smaller for a $50 loan than for a $100000 or a
$10000000 loan
In figure 2 the R(I)large curve represents the return to the bank for large loans with
regard to the interest rate I and the R(I)small curve describes the same correlation for
small loans It is shifts downwards to reflect the assertion that the imperfect information
169 See Stiglitz and Weiss (1981) p 394170 In this paper the term bdquotransaction costsldquo refers to the operating expense ratio as defined by MicroRate It ldquois calculated by dividing all expenses related to the operation of the institution (including all the administrative and salary expenses depreciation and board fees) by the period average gross portfoliordquo See MicroRate and Inter-American Development Bank (IADB) (2003) p 16 171 See Stiglitz and Weiss (1981) p 396
34
paradigm has a more severe effect on poor people than on the better off They are
expected to have less profitable investment opportunities at their disposal172 and
therefore are more likely to invest in riskier projects which increase the probability of
default and hence decrease the expected return to the bank Additionally one might
expect poor people to be more likely than others to spend borrowed money on
consumption instead of an income generating activity particularly if a crisis arises It
seems understandable that food or urgently needed medicine are given priority over
repaying a loan
The second shift downwards is due to transaction costs As stated above they are
relatively higher for smaller loans Obviously transaction costs are incurred in the
provision of a large loan as well but since they are much smaller with regard to the loan
amount they are not included in the diagram for reasons of clarity
Figure 2 The extended Model
Source Own diagram adapted from Stiglitz and Weiss (1981) p 394
172 See Khandker (1998) p 8
INTEREST RATE I
SmallLoans
LargeLoans
Transaction costs
Lack of investment opportunities
R(I)large
R(I)small
EX
PE
CT
ED
RE
TU
RN
TO
TH
E B
AN
K
35
53 Overcoming Credit Rationing for the Microfinance Sector
If the conclusions in chapter 51 hold it is rational for a profit maximizing investor to
neglect the microfinance sector as long as no surplus funds in the market for large loans
exist This finding can help to explain the small amount of money provided to the
microfinance sector from commercial investors On the other hand it has to be stated
that this theory is reflexive as defined by Soros173 It not only explains but also forms
reality since it has the potential to reinforce the view of potential investors that
microfinance is a less profitable business174 Therefore demonstrating under which
conditions microfinance can be profitable and in some cases be more profitable than
traditional businesses is of crucial importance
To provide a fairer view of the microfinance sector a further assumption of the Stiglitz
and Weiss model that needs to be suspended is that all investments made by the
borrowers have the same expected return175 As stated above this contradicts economic
theory which claims ceteris paribus capital productivity decreases while the amount of
fixed capital increases In combination with a low capital endowment micro-enterprises
are usually faced with an excess supply of unskilled labor especially in developing
countries176 Hence small enterprises use far less capital per employee than big business
and therefore their marginal productivity of capital is much higher177 This is intuitive if
one imagines an economic actor who wants to invest several packages of capital
Obviously she would invest the first package where she expects the highest return the
second package where she expects the second highest return and so on Each additional
investment opportunity would lead to lower or at best equal returns178 While this
simplified example has limitations it demonstrates how the marginal productivity of
capital can diminish Although it might actually increase until a certain point179 this can
be expected to be so low in this context that it has no influence on the correlation as
shown in figure 2
173 See Soros (1998) pp 14 et sqq174 See Goodwin-Groen (1999) p 8175 See Stiglitz and Weiss (1981) p 395176 See Perkins et al (2001) pp 95 et sqq177 See Tschach (2000) p 8178 See Rosenberg (2002) p 11179 See Rechard G Lipsey (1979) pp 211 et sqq
36
Figure 3 Marginal Productivity of Capital
Source Dornbusch and Fischer (1995) p 406
Even if good investment opportunities for poor people exist the question remains if it is
possible to distinguish between high and low risk borrowers The problem of adverse
selection is overcome in a cost effective way in many MFIs180 For the better off poor
for example institutions like BRI base their decision on whether or not to approve a
loan by assessing the repayment ability of potential borrowers from their current income
flows and not from the uncertain returns generated by the loan181 Additionally
collateral is used in some cases to attract low risk borrowers182 In contrast to
industrialized countries this is usually not done to cover the potential losses of the
lender but to punish the defaulter and therefore increase her willingness to repay183
Obviously this does not always work for the poorest since they often neither posses any
goods that could work as collateral nor do they have sufficient earnings prior to
obtaining a loan for starting an income generating activity Here the so called group-
lending model can help to identify creditworthy borrowers The most prominent
institution using this approach is the Grameen Bank which only provides credit to
180 See Farrington (2000) p 20181 See Robinson (2001) p 80 Robinson (2002) p 238182 See Bester (1985) p 850 et sqq183 See Schmidt and Tschach (2001) p 15 Robinson (2002) p 244
FIXED CAPITAL 0
MA
RG
INA
L P
RO
DU
CT
IVIT
Y
37
members of a group of five These groups are formed by their members without
interference of the Grameen Bank Although in this particular case no joint liability
exists for the members of the group nobody can receive a new loan if another member
of the group fails to repay on time184 Therefore the group formation work as a
screening process Since the borrowers do not want to risk their ability to obtain further
loans they carefully select with whom to form a group Usually the members know
each other for a long period of time and therefore they can make a meaningful judgment
of each othersrsquo ability to repay the loan Other MFIs even require the members of a
group to mutually guarantee each othersrsquo loans185 While this might further increase
borrowersrsquo efforts to search for trustworthy group members it might also keep potential
borrowers from applying for a loan since she does not want be held responsible for
defaulting members This mechanism enables MFIs to partly pass on the transaction
costs related to the selection of low risk borrowers to the borrowers themselves186
Many MFIs have also largely overcome the problem of moral hazard by creating
incentives to ensure a high repayment rate even among the poorest In some cases their
customers go hungry in order to pay back their loan even though no legal action would
be taken against them if they would refuse to do so187 One way to achieve this is to
build up peer pressure through the formation of groups as described above188 Another
and probably the most important is to limit access to future loans to those borrowers
who repay on time The demand for successive loans is extremely high In a 1996
survey 98 percent of BRI borrowers planed to apply for another loan189 and in 1993
less than 30 percent of Grameen Bank loans went to first time borrowers190 Especially
the poorest highly value the option to reborrow191 and many MFIs see this as their
primary incentive to ensure repayment192 According to Schmidt and Tschach ldquothe net
present value of future access to credit works out to be roughly half the value of the
economic advantage to be gained from the intended non-repaymentrdquo193 This can also
184 See Yunus (1998) p 135185 See Schmidt and Zeitinger (1997) p 6186 See Stiglitz (1990) p353187 Own observation at the Grameen Bank in Bangladesh (2003)188 See Hoff and Stiglitz (1990) p 249189 See Robinson (2002) p 251190 See Khandker Khalily and Khan (1995) p 93191 See Gibbons (2000) p 15 Hashemi and Schuler (1997) p 43192 See Gibbons and Meehan (1999) p 160193 See Schmidt and Tschach (2001) p 16
38
explain the occurrence of a drop in the repayment rate once a MFI is no longer seen as
viable and therefore is not expected to provide loans in the future194
With the help of the described mechanisms MFIs around the world are able to keep
repayment rates high A survey of 69 MFIs from 36 different countries each serving
more than 10000 clients in 2002 found the portfolio at risk (PAR)195 varied between
zero and 231 percent While the average was 36 percent the median was found to be
229 percent196 One of the MFIs included in this sample is BRIs whorsquos 12-month loss
ratio has never exceeded five percent since the start of its transformation in 1984 and
from 1997 to 1998 the ratio actually fell from 22 to 194 percent197 The latter deserves
special attention because the Asian financial crisis reached its peak at that time with
Indonesia being hardest hit as illustrated by a statement from The Economist in July
1998 Even with the fierce competition from its neighbors Indonesia would probably
walk away with the prize for Asias most desperate banking systemrdquo198
The findings that MFIs can adapt their services to low income people in order to ensure
a high repayment rate and that poor people do not lack profitable investment
opportunities are illustrated in figure 4 From this diagram it can be seen that under the
new assumptions the interest rate at which the bank maximizes its return differs for
large (I(l)) and small loans (I(s)) According to the assumption that micro-
entrepreneurs can realize a higher return on their investments the bank can charge them
a higher rate of interest without bearing an increased risk Nevertheless in this example
the bank would still serve the market for large loans first because of the higher
transaction costs for smaller loans
The view as described in figure 4 is shared among most traditional banks and investors
in industrialized as well as in developing countries In addition to neglecting the
possibility of generating profits by offering microcredit themselves199 they also hesitate
to lend to MFIs because they consider their business too risky
194 See Schreiner (1997) p 64195 ldquoPAR shows the real risk of the portfolio by comparing outstanding loan balances for loans with atleast one late payment to the outstanding loan portfoliordquo Gross and de Silva (2002) p 22196 Own calculations See Appendix 2197 See Seibel (2000) p 11198 The Economist (1998) pp 92 et sqq199 Busch and Kort (2004) p 8
39
Figure 4 The extended Model
Source Own diagram adapted from Stiglitz and Weiss (1981) p 394 Tschach (2000)
p 17
This attitude can be observed by comparing the ratio of equity to liabilities which is
considerably higher for MFIs than for conventional banks200 When it comes to MFI
start-ups and those MFIs serving the low end market in remote areas even experienced
microfinance practitioners are skeptical if interest rates that fully recover all costs can
be charged201
Theoretically there are two ways to adjust this model to arrive at a conclusion which is
more favorable with regard to the profitability of microcredit One is to cut the
transaction costs and therefore reduce the downward shift of the R(I)small curve the
other is to allow the bank to further raise the interest rate without experiencing a
decrease in its return This means to increase I(s) and the respective rate of return
While in 2000 Tschach stated that transaction costs vary between 10 and 20 percent for
loans provided through the group lending model and between 15 and 30 percent for
200 See MicroRate and IADB (2003) p 30201 See Volkery (2004) p 33 Gibbons (2000) p 15 Gibbons and Meehan (2002) p 29 Goodwin-Groen (1999) p 8
INTEREST RATE I(l)
SmallLoans
LargeLoans
Transaction costs
I(s)
R(i)large
R(i)small
EX
PE
CT
ED
RE
TU
RN
TO
TH
E B
AN
K
40
individual loans202 it was recommended in 1999 that MFIs should target a range
between 15 and 25 percent203 Some best practices on the other hand have already
achieved single digit numbers Currently BDB might be the most efficient MFI in the
world with transaction costs at just 47 percent in 2001204 Even though the low costs of
BDB have to be acknowledged its achievement has to be put in perspective As stated
above with an average loan balance of more than $5000 it does not serve the low end
market In addition it works in an environment with a high population density which
means that it can reach a relatively large group of borrowers per branch This is a
comparative advantage many Asian MFIs enjoy as can be illustrated by comparing
Bangladesh and Bolivia Both countries are at the forefront of the development of
microfinance in their respective continent but while in Bangladesh more than 1000
people are living per square kilometer the average for Bolivia is only eight205
Therefore it is consistent that the most efficient MFI in Latin America Fondo
Financiero Privado para el Fomento a Iniciativas Economicas has transaction costs of
114 percent206 With an average loan size greater than the annual GDP per Capita this
institution also does not serve the low end market207
Despite the impressive efficiency gains in the described examples most MFIs are far
from achieving these numbers and many are unlikely to reach them due to the
environment within which they work A survey of 67 MFIs from 31 countries found the
average transactions costs in 2002 to be 279 percent with a median of 206 percent208
However even if these institutions were to increase their efficiency to best practice
standards their transaction costs would still be significantly higher than those of
traditional banks providing much larger loans For these banks the respective costs vary
in a range between 05 and 3 percent209 According to this argument charging interest
rates considerably higher than conventional banks is the only way for MFIs to generate
higher returns and hence successfully compete for capital
202 See Tschach (2000) pp 100 et sqq203 See Gibbons and Meehan (1999) p 149204 See M-Cril (2001b) p 4205 See CIA (2004)206 See MicroRate (2004)207 In this paper the term ldquolow endrdquo refers to the definition of the MBB (2003) p 54 Loans worth less than 20 percent of the respective countryrsquos GDP per capita are described that way 208 Own calculations See Appendix 3209 See M-Cril (2004a) p 16
41
6 Interest Rates
61 Setting the right Interest Rate
Before addressing the questions to what extend MFIs can raise their interest rates
without putting the repayment rate or the social benefits of their customers at risk a
basic model will be presented This model will illustrate how a MFI should set their
rates in order to not only cover their costs but also to generate an appropriate profit to
finance further growth and attract additional capital
In 2002 CGAP revised its 1996 paper ldquoMicrocredit Interest Ratesrdquo210 which outlines
the standard method of setting sustainable interest rates for commercially oriented
MFIs According to this model the annual effective interest rate (I) should be calculated
as shown below
(1) I = LL
IIKCFLLTA
minusminus+++
1
With each variable being a decimal fraction of the average outstanding loan portfolio
whereby TA stands for the transaction costs as described above LL represents the
annual loan loss and II stands for investment income eg on liquid assets The cost of
funds (CF) consist of the interest and administrative costs needed to obtain deposits and
commercial loans as well as of the imputed costs on equity due to inflation K stands for
the capitalization rate which represents the net real profit Keeping this rate high is
important to finance the future growth of the loan portfolio This can be either done
through investors attracted by high profitability or through borrowing For the latter an
increase in equity is inevitable since it is required as a safety cushion by lenders
Since this model ignores the timing of cash flows and does not take taxes into account
it has to be regarded as fairly imprecise and hence should not be used for business
planning Nevertheless it can be used for an approximation of the interest rate that a
MFI would need to charge to provide its services as planned In the following I will
210 See Rosenberg (2002) pp 1 et sqq
42
apply this model on a fictitious MFI working in a rural area of Latin America with low
end customers In this setting it seems realistic to estimate transaction costs of 35
percent and loan loss rate of two percent211 If funds were borrowed at commercial
terms their costs can be assumed to equal at least 15 percent of the average outstanding
loan portfolio212 Estimating the capitalization rate is more challenging First the
targeted portfolio growth rate is set at 75 percent This is slightly below the 751 percent
average annual portfolio growth between 2000 and 2002 found by a survey of 25
different MFIs based in Central and South America213 If the extend to which the MFI
can leverage stays constant the loan portfolios growth would be limited by the growth
rate of the equity To express the capital needed for this growth as a share of the loan
portfolio it is necessary to estimate the ratio between the equity and the outstanding
loan amount According to the survey mentioned above the loan portfolios of the 25
Latin American MFIs equal on average 215 times their equity214 With this number the
capital needed to increase the equity by 75 percent would corresponds to approximately
35 percent of outstanding loan amount (075215) Finally the investment income has to
be estimated Since liquid assets that are available short term do not generate high
returns say five percent it does not seem advisable for the MFI to hold more than a
quarter of its loan portfolio in this form Hence the profit generated in this way would
equal 125 percent of the outstanding loan amount Using these numbers the equation to
calculate the annual effective interest rate reads as follows
(2) I = LL
IIKCFLLTA
minusminus+++
1 =
0201
01250350150020350
minusminus+++
= 0875
As a result the MFI would need to charge an annual effective interest rate of
approximately 875 percent on its loans in order to sustainable provide its services and
finance its growth without depending on donor money This rate might decrease once
the MFI matures the growth slows down and cheaper funds become available but it
will stay significantly higher than any rate charged by conventional banks
211 MicroRate and IADB (2004) pp 6 and 16212 See MicroRate and IADB (2004) p 616 and 28213 Own calculation See Appendix 4214 Own calculations See Appendix 5
43
62 Can Micro-Entrepreneurs bear these Rates
Although most MFIs charge rates significantly below 875 percent many critics have
strenuously argued against any rates exceeding those of traditional banks Rosanna
Barbero of Oxfam labeled an interest rate of 52 percent charged by a Cambodian MFI
ldquoludicrous evil and disgusting and stated that ldquo[n]o business in the world can make a
profit at these interest ratesldquo215 The former finance minister of Bangladesh Shah Kibria
even categorized the 20 percent effective rate charged by the Grameen Bank as to
high216 Many practitioners therefore believe in a strong negative correlation between
the interest rate and the demand for loans217 Others have argued more generally that
concentrating on profitability and therefore charging high interest rates diverts MFIs
from serving the poorest218
These views are still shared among many MFI managers donor agencies and especially
investors and politicians While the former are unwilling to charge interest rates for
funds they received ldquocheaplyrdquo (through grants or subsidized loans) and are worried
about undermining their social goals by charging higher rates of interest219 the latter are
reluctant to invest for reasons stated above or impose interest caps to catch the attention
of the public by pretending to protect the poor from usury rates220
In chapter 53 it has been described that micro-entrepreneurs due to their smaller
capital endowment have even better investment opportunities than big business The
extend to which this is true has not yet been answered An indication is the high
repayment rate observed within MFIs around the globe If their customers capital yield
did not exceed the charged interest rate how would they be able to repay According to
Gibbons and Meehan customers of MFIs can generally generate returns of more than
100 percent on their invested capital221 and ldquo[r]esearch in India Kenya and the
Philippines found that the average annual return on investments in microenterprises
215 See Kate and Roeun (2004)216 See Hodson (2001) min 1100217 See Morduch (1999a) p 1594218 See Prisma (2002) p 1219 See Schreiner (1997) p 60 Khandker (1998) p 106 220 See Gross and de Silva (2002) p 32 Jansson and Wenner (1997) p 36 et sqq Campion (2002) p 59221 See Gibbons and Meehan (1999) p 131
44
ranged from 117 to 847 percentrdquo222 Schmidt and Tschach found the marginal
productivity of capital to be as high as 1000 percent for the smallest loans provided by
the Bolivian MFI Caja Los Andes223 These findings are confirmed by the observation
of Rosenberg who found while working as a microfinance consultant for ten years he
never heard of a single MFI having problems to attract clients because interest rates
were too high224
To get a better understanding of the investment opportunities of low income people in
developing countries a typical example on how MFI clients invest their loans is as
follows
Zobair is working as a rickshaw puller in Bangladesh Like most of his colleagues he
does not own the rickshaw he is riding Therefore he has to pay a daily rent of about
$030 to the owner Since his average income of approximately $15 per day is hardly
enough to feed his family he is not able to save the $100 necessary to buy a rickshaw
on his own 225 If he could do so through obtaining a loan his income would increase by
$030 every day because he would not have to pay the rent for the rickshaw anymore
Assuming an average of six working days per week 226 and a life span of the rickshaw
of 5 years his internal rate of return would equal 15324 percent annually227
Consequently any interest rate charged by a MFI would be advantageous to him as long
as it would not exceed 15324 percent228
63 Should the Interest Rate be subsidized anyway
Despite the fact that numerous micro-entrepreneurs are able to generate tremendous
returns on their investment obviously not all are able to use capital in such a productive
way and therefore can not afford microcredit at commercial rates In order to reach
these people as well many MFIs continue to use donor money in order to keep their
interest rates low But even if the problems related to subsidized credit as described in
222 See Helms and Reille (2004) p 3223 See Schmidt and Tschach (2001) p 6224 See Rosenberg (2002) p 10225 This examples draws on observations made by the author in Dhaka (Bangladesh) during 2003226 Obviously extended holidays are not a viable option in this surrounding 227 Own calculation See Appendix 6228 This result is only valid if the loan is repaid in daily instalments For a weekly repayment schedule the interest rate charged by the MFI must not exceed 15119 percent in order to still be beneficial for Zobair
45
chapter 23 do not arise it might still not be the most effective tool to help poor people
as will be illustrated in the following example
A MFI faces two groups of potential clients one with businesses able to generate a
return of 125 percent on borrowed capital and another with a possible returns of 50
percent Assuming budget costs according to equation (2) the institution needs to
charge an interest rate of 875 percent and therefore only serves the former group
Supposed each group consists of 50 members demanding $100 loans the net gains to
society (NGS) could be calculated as follows
(3) NGS = 50 times ($125 ndash $875) = $1875
These gains would be due to the investments of the more profitable group which were
made possible through the loans provided by the MFI The less profitable group would
not borrow since their expected returns are not sufficient to pay for the interest If the
interest rate would be lowered to 30 percent both groups would be able to generate net
gains and therefore borrow from the MFI In order to provide loans at this rate the
institution would need to raise additional capital from non commercial sources The
NGS would be calculated as follows
(4) NGS = 50 times ($125 - $30) + 50 times ($50 - $30) + 100 times ($30 - $875) = 0
While the first terms represent the net gains to the respective groups the last describes
the costs incurred in providing the loans At a rate of 30 percent each loan would need
to be subsidized with $575 Hence the NGS actually fall after the introduction of the
subsidized loan This is due to the fact that the less profitable group is encouraged to
invest in relatively unproductive businesses In addition future growth of the MFI could
be jeopardized due to scarce donor money which is needed to finance the interest rate
subsidy Therefore it seems more advisable to continue to charge a rate of 875 percent
and spend the money used for subsidization on other programs such as health care or
education229
229 In Appendix 7 it will be shown that this result generally holds
46
7 Empirical verification
71 Setting up a Sample
To see if the findings of the previous chapters hold the effects which interest rates
charged by MFIs have on their performance will be analyzed in the following Up to
now such a study does not exist mainly because of a lack of adequate data Most MFIs
do not provide accurate information about the annual effective interest rate they charge
and therefore make an evaluation difficult
In 2002 Rosenberg distinguished eight different categories on how microcredit interest
rates are quoted230 These categories differ in several ways On the contrary to
traditional banks for example it is common for MFIs to state interest rates calculated on
a ldquoflatrdquo balance rather than on a declining one This means that the total loan amount is
used to determine the interest rate ignoring installments paid by the borrowers normally
on a weekly or monthly basis In addition many MFIs charge a certain upfront fee prior
to the loan disbursement require compulsory savings at a lower rate or state their
interest rate for semi annual terms only On the one hand this is done to provide
numbers that are more meaningful to MFI customers who often lack the necessary math
skills to deal with compound interest on the other hand it is done to circumvent interest
rate ceilings imposed by the government231 Another problem is that most MFIs offer
different loan products without itemizing their respective shares to their total loan
portfolio As a result it is not possible to calculate a weighted average even if the rate
stated by the respective MFI could be transformed into an effective interest rate
Usually the portfolio yield is used as a proxy in order to make statements about the
interest rate charged by a certain MFI232 It is generally ldquocalculated by dividing total
cash financial revenue (all income generated by the loan portfolio but not accrued
interest) by the period average gross portfoliordquo233 The advantage of this method is that
even the hidden costs are considered Nevertheless it also has a severe shortcoming by
not taking late or defaulted payments into account Therefore the portfolio yield does
230 See Rosenberg (2002) p 5231 MicroRate (2002) p 8232 See MicroRate (nd)233 MicroRate and IADB (2003) p 39
47
not allow to draw conclusions regarding the correlation between the interest rate
charged by a MFI and its PAR
72 Examining the Sample
Through the appearance of rating agencies specialized in the microfinance sector more
adequate information has become available in recent years While MicroRate only
publishes the portfolio yield of rated MFIs M-Cril Microfinanza Microserve and
Planet Rating actually provide information about the annual effective interest rate for at
least some of the MFIs they analyze Although it is labelled differently from all of the
four institutions234 the term describes what is ldquothe highest income or yield that an
organisation can earn from its portfolio based on the terms of its loansrdquo235
Currently236 reports of 39 different MFIs from 20 countries providing accurate
information about the effective annual interest rate are available to the public This
sample should be used to verify the findings of the previous chapters237 Since a
comparison is made between the performances of MFIs based in different countries and
the ratings have been carried out in different years several adjustments are necessary
First the inflation of the respective country and the respective year(s)238 has to be taken
into account in order to only compare the real rates239 In addition the average
outstanding loan amount per borrower is divided by the respective countryrsquos GDP per
capita Since it can be assumed that ldquoonly the poorer households will be willing to take
the smallest loansrdquo240 this number can be used as a proxy for the poverty level
Although the sample size is far to small to represent the microfinance sector as a whole
and the results are statistically not significant the findings can still be used to underline
the theoretical conclusions drawn in the previous chapters In figure 5 the connection
234 M-Cril uses the name ldquoannual percentage raterdquo See eg M-Cril (2004a) p 25 Microfinanza uses the name ldquoexpected portfolio yieldrdquo See eg Microfinanza (2002c) p 25 Planet Rating uses the name ldquoannual effective interest raterdquo See eg Planet Rating (2004d) p 1 Microserve uses the name ldquotheoretical yieldrdquo See Microserve (2003) p 62235 See M-Cril (2004a) p 25236 As of September 28th 2004237 See Appendix 8 For exchange rates see FXTOP (2004)238 Where necessary a weighted average of the annual inflation rate was used See Appendix 9239 This is done through the following formula ir = (I ndash F) (1 + F100) While ir represents the real annual effective interest rate F represents the inflation rate 240 Morduch (1998) p 1572
48
between the average loan size and the transaction costs as a share of the average loan
portfolio is illustrated
Figure 5 Loan Size vs Interest Rate241
Source Own diagram
000
1000
2000
3000
4000
5000
6000
7000
8000
9000
10000
0 100 200 300 400 500 600
Loan Size
Inte
res
t R
ate
It can be seen that the interest rate is negative correlated to the loans size This can be
explained by the relative higher transaction cost for smaller loans as described in
chapter 52 In order to cover their costs MFIs serving the low end market need to
charge higher rates to their customers than those organizations serving the better off
poor Obviously there are several assumptions to this general finding Especially
striking are the two MFIs with an average loan size of approximately five times their
countries GDP per capita which still high interest rates This occurrence can be
explained by taking a closer look to the respective organizations One was established
less than two years prior to its rating and therefore still bears a lot of start up costs242
241 The equation for the regression line reads as follows Y = -00219X + 365 The correlation coefficient is 014242 See Microfinanza (2002b) p 1
49
the other managed to stay profitable while it almost quadrupled its loan portfolio in the
last two years243
Figure 6 Interest Rate vs PAR244
Source Own diagram
0
5
10
15
20
25
30
35
0 20 40 60 80 100 120
Interest Rate
PA
R
In Figure 6 the crucial correlation between the interest rates charged by a MFIs and its
PAR245 is examined According to the given sample the view of traditional banks and
investors that a higher interest rate leads to a higher default rate does not hold
Obviously one has to avoid to draw the opposite conclusion namely that a high interest
rates decreases the PAR The connection illustrated in figure 6 has to be interpreted as
follows Since high interest rates are related to small loans the low PAR for MFIs
charging high interest rates can actually be explained by the tremendous profitability of
small size investments Despite the high rates their customers are even more likely to
repay
243 See Planet Rating (2003b)244 The equation for the regression line reads as follows Y = -00768X + 68433 The correlation coefficient is 0235245 M-Cril only publishes the PAR for overdues greater than 60 days Therefore these ratios are used as a proxy for the industry standard of 30 days for some Asian MFIs
50
Finally it has to be examined if charging high interest rates actually enables MFI to
generate higher returns Although it can be expected that the combination of a low PAR
and a high interest rate leads to a high profitability it still has to be checked if this is not
outdone by soaring transaction costs Figure 7 illustrates the correlation between the
interest rate charged by a MFI and its financial self-sufficiency (FSS) The latter is the
ldquo[r]atio of total income to total adjusted expenses for the year Adjustments are made
for subsidised cost of funds (relative to market interest rate) equity (with respect to
inflation) and in-kind donationsrdquo246 It can be seen that the regression line actually does
indicate a positive correlation between the interest rate and the profitability of a MFI
Figure 7 Interest Rate vs FSS247
Source Own diagram248
0
20
40
60
80
100
120
140
160
180
0 20 40 60 80 100
Interest Rate
FS
S
246 M-Cril (2004a) p 53247 The equation for the regression line reads as follows Y = 02839X + 8901 The correlation coefficient is 0174248 Since the interest rate the customers of the MFI Foccas have to pay includes fees which are not passed on to the institution its interest rate in this diagram is set at 723 percent instead of the 10715 percent used for figure 6 See Planet Rating (2003b) p 1
51
This result does not necessarily disprove the findings of Stiglitz and Weiss since it can
be argued that MFIs simply do no increase their interest rates to the point where they
would maximize their expected returns But if this would be true why do MFIs not
charge higher rates of interest given the demand described in chapter 41 and 43 In
mature markets competition normally ensures prices not to exceed a certain level but
since many MFIs still operate in a ldquosellerrsquos marketrdquo249 this can not explain the findings
as described in figure 7 Therefore it has to be assumed that a combination of the
unwillingness of many microfinance practitioners to burden their customers with high
interest rates and the plain disbelief of traditional investors that micro-entrepreneurs can
bear those rates is responsible for this occurrence
249 See MicroRate and IADB (2003) p 9
52
8 Conclusions
It has been shown that MFIs are not only contributing significantly to the development
of the financial sector in their respective countries but also that they play an important
role to eradicate poverty by providing much needed capital to low income people which
are able to generate tremendous returns on their investments
The fact that the demand for microcredit is not met is mainly due to the view of most
for profit investors and traditional banks that offering financial services to poor people
can not be done profitable Because of this conviction they hardly invest in the
microfinance sector This does not have to be the case according to the findings of this
paper Although faced with relatively high transaction costs MFIs are able to charge
interest rates at levels that fully recover their costs Elizabeth Rhynersquos claim ldquothat the
most financially viable programs differed from their less viable peers in their
willingness to set interest rates at levels that would fully recover costsrdquo250 is backed by
the findings of this paper that high profitability is correlated to high interest rates
Theoretical models based on the findings of Stiglitz and Weiss can not be used as a
justification to ration credit for the microfinance sector since the interest rate that
maximizes profits to the lender can be assumed to exceed 100 percent for many MFIs
Nevertheless this rate is hardly charged although it has been shown that it can be done
The Mexican MFI Compartamos for example manages to keep its PAR as low as one
percent while charging an effective interest rate of more than 100 percent to
approximately 160000 clients251 In combination with this case the conclusions drawn
from examining the sample of MFIs in chapter 7 the claim of Hulme and Mosley as
stated in the introduction can be considered as wrong MFIs are in fact able to finance
rapid growth stay profitable by charging corresponding interest rates and still have a
significantly positive impact on the poverty level of their clients In the long run gains
in efficiency economies of scale a slowdown in growth and competition will ensure
interest rates drop as it has already been the case in countries like Bangladesh and parts
of Bolivia252
250 See Rhyne (1998) p 7251 See MicroRate (2004)252 See Microrate and IADB (2003) p 9
53
According to a MicroRate survey many MFIs are more profitable than Citibank and also
generate a higher return on investment than commercial banks in their respective
countries253 Investments companies like IMI or Blue Orchard will soon be able to
present a meaningful track record of their microfinance investments to potential
investors Ultimately the capital markets can not ignore the facts proving that it actually
can be profitable to invest in the microfinance sector but in order to raise money
quickly microfinance practitioners will have to continue to intensively promote their
cause not only to for profit investors but also to donors and multilateral agencies like
the World Bank
253 See MicroRate (2002) p 10
54
Appendix
Appendix 1 Average loan balance
Source Data is available through the Mix Market (2004)
Organization
Loan Portfolio 2002 (US$)
Loan Portfolio 2003 (US$)
Number of borrowers 2002
Number of Borrowers 2003
2CM 1263602 1400438 3622 3708ACF 955503 1611401 285 370ACLEDA 26846703 39391301 82598 98905ACME 1460881 1714844 4283 4600ADIM 369065 407798 1122 1395AFK 933306 1706577 250 467AgroInvest 4684249 9697411 5208 9629Al Amana 15593277 28677666 78114 101610AMSSFMC 612167 1040756 6183 6886AREGAK 3285273 3987011 11841 14377AVFS 214331 269819 1883 2866BancoSol 83629049 91175000 42290 56707BESA 10563980 15114430 4488 5061BPR AK 613362 876130 1730 3879BPR BMMS 133949 237946 1755 1779BRI 1344006170 1720072773 3056103 3100358BZMF 1592508 1922097 1250 1331CBDIBA 216587 242465 5764 2877CCA 2146235 4582302 4070 6585CCCP 447534 851678 6265 9450CEP 3795400 5261957 32291 42132CERUDEB 25093643 34873228 34490 44796CMEDFI 227674 250244 3467 3781CMM - Bogota 4836000 8135968 15635 22038CMMB 34880 56964 42 190COAC Maquita Cushunchic
870084 1855718 6603 7732
CODES 280843 263091 60 60CODESARROLLO 6714007 12935951 4391 6896Constanta 2943822 3536047 16134 18588COOPEC CAMEC MN
7152 29821 92 77
Crear - Tacna 3891116 4636094 3671 4948CREDIT 642094 81838 7532 8097CRYSTAL FUND 366456 421403 1379 1061DBACD 3473701 3876526 12812 19606ECLOF - ECU 1154292 728312 860 416ECLOF - MAL 441734 407227 1118 1500EKI 11833244 19245751 8999 13323EMT 4481589 5765281 84781 92173ESED 8579460 6834742 22790 20035
55
Eshet 185741 462569 3308 6540Faulu - KEN 9027332 7206344 17463 15000FDL 12503027 16545332 21306 25106FIE 35818903 41597315 26468 33100FINADEV 5512586 9770323 12775 14709Finance Salone 211312 434298 2225 7159Finca - TAN 1293430 1854834 20648 27499Finca - UGA 2451703 2798869 35610 36912FINCORP 4761288 10236896 941 858FJN 5473563 8037662 8107 11133FMFB 308158 1188896 713 3558FMM -Bucaramanga
6355518 10227000 25814 42464
FODEM 739181 939824 1909 2501FundaciESPOIR
898561 1883446 5911 9464
FUNDESER 798907 1373113 4072 5065Gasha 323748 413742 5504 6423GGLS Save the Children
64235 137957 1291 2362
GK 56986 166971 951 2718HKL 1363365 1420357 6648 5372HOPE 402799 603488 1098 1562IAMD 42132 56550 2780 2772IDECE 21312 39453 150 232IDF 2031944 2626382 31003 36580IMCEC - Dakar 254759 688449 1018 2983IMCEC - Thies 199799 571122 1164 1261
ISSIA 221615 246792 1409 1698JMCC 1962355 2609723 1471 2333KAFC 21710638 29241051 24850 32097KAMURJ 1003935 1411258 5559 5691Kashf 2355965 6271498 29655 59389KMBI 721409 1626666 11973 27266KPSCA 109299 128063 362 794K-Rep 14490447 20699963 38739 45379KSCS 18978 43740 140 297KVT 44075 70621 241 373LAPO 922478 1194633 18740 19139MEC ADEFAP 27788 69248 198 202MEC Bosangani 14357 31086 364 540MEDF 104113 136257 1278 1184Meklit 233170 252232 2084 3577Metemamen 22123 57778 943 1501MFSC 109261 171090 511 687MIKRA 2951028 5008784 4145 6095MIKROFIN 9560502 18380263 5633 7426Miselini 737387 1026639 10182 11431MRFC 11475440 9133130 163000 180000Mushuc Runa 2089076 5418325 3139 6232Nirdhan 2886777 3016171 29589 27457OCSSC 5245186 7658413 42157 6215o
56
Otiv Diana 95992 638422 229 1073Otiv Sambava 188094 437974 2002 1442Otiv Tana 66465 673175 337 1269Partner 9976448 15321304 7139 11935PCA 6878257 6885926 63113 58147PEACE 420746 627295 4192 5428PEDF 164399 254233 2357 3340Piyeli 809447 1206656 8674 4745PRESTANIC 2827502 3540367 1477 2605PRIDE - MAL 991888 854631 5376 5601PRIZMA 3881581 6838978 8112 10968ProMujer -Nicaragua
1006871 1424437 10436 13047
PTF 891566 1068881 8500 9070RBST 818594 1058115 619 723REMECU 1381705 1483471 10330 13996
RUSCA 60887 100820 454 994
SCSCS 89423 157472 873 1007SFPI 709497 903556 7728 9552Sidama 934260 1011798 10267 11346SPBD 117807 186029 647 1740Sunlink 819138 1056823 3401 3833Sunrise 5412366 8782868 4560 7256TEBA 108032426 176300111 163021 157776TIAVO 281978 838905 2049 459TPC 1140429 2267148 22869 31668TSPI 4650989 5383755 49649 75617UNICECAM 3442843 5943804 16039 19031Wasasa 230657 274908 2850 3728Wisdom 1306066 1404463 10524 12054XacBank 4910098 9829503 11063 18610Zakoura 15907288 12444768 103720 118980
Appendix 2 Portfolio at Risk
Source Data is available through the Mix Market (2004)
Organization PAR 2002ABA 202ACEP 464ACLEDA 175ACODEP 452ACSI 209Al Amana 010Apoyo Integral
483
AREGAK 692Banco Solidario
500
BancoSol 660BASIX 1296
57
BRI 437BURO Tangail
350
CEP 200CERUDEB 103CMAC -Sullana
567
CMM -Bogota
176
Compartamos 111Constanta 304Credi Fe 212CREDIAMIGO 409DBACD 010EBS 847EMT 010ESED 1311FADES 2311Faulu - KEN 246Faulu - UGA 096FDL 212FECECAM 428FED 436FIE 598FINADEV 021Finamerica 1133Finca - TAN 000Finca - UGA 297FMM -Bucaramanga
094
FMM -Popayan
088
FONDEP 013FORA 064Genesis Empresarial
1197
IDF 017KAFC 106Kashf 000KMBI 128K-Rep 229MiBanco 309MRFC 1742Nirdhan 373
PADME 079PAMECAS 284PCA 379PRIDE - TAN 018ProMujer -Nicaragua
073
RCPB 600REMECU 157SHARE 000
58
Soluci 182Spandana 014TEBA 106TSPI 355UMU 125UNICECAM 405Urwego 290UWFT 363WAGES 736WWB -Medellin
235
XacBank 061Zakoura 095
Appendix 3 Transaction Costs
Source Data is available through the Mix Market (2004)
OrganizationTransaction Costs
Acci Rural 1154ACEP 858ACLEDA 2430ACODEP 2920ACSI 924Al Amana 2576AREGAK 2856AssEF 1919Banco Solidario
1826
BancoSol 1210BASIX 1317BRI 1353BURO Tangail
2053
CEP 1759CERUDEB 5109CMAC -Sullana
1784
CMM -Bogota
2089
Compartamos 3341Constanta 4597Credi Fe 1978CREDIAMIGO 2525DBACD 1742EBS 2377EMT 3220ESED 1343FADES 1673FAMA 2436
59
Faulu - KEN 2253Faulu - UGA 4962FDL 1726FECECAM 2587FED 4083FIE 1125Finamerica 1563Finca - TAN 10753Finca - UGA 9096FMM -Bucaramanga
1925
FMM -Popayan
1112
FONDEP 5477FORA 3481Genesis Empresarial
1626
IDF 1695
K-Rep 1909LAPO 3511MiBanco 2456Nirdhan 1325NWTF 3109OCSSC 1155PADME 1131PAMECAS 1705PCA 1670PRIDE - TAN 4273ProMujer -Nicaragua
5078
RCPB 2059SHARE 2308Sidama 2662Soluci 2906Spandana 641TEBA 1213TSPI 3898UMU 4023UNICECAM 10120Urwego 7437Wisdom 1906WWB -Medellin
1703
XacBank 4144Zakoura 1881
60
Appendix 4 Portfolio Growth
Source Data is available through the Mix Market (2004)
Organization
Total Loan Portfolio in 2000
Total Loan Portfolio in 2002
ACODEP 5889394 7258487Adelante 4327 88594ADRI 1514681 2591240AgroCapital 11100088 12018280Banco Solidario 39632165 103420000
BancoSol 78031172 83629049CMAC - Sullana 14596365 28055720
COAC Maquita Cushunchic
348443 870084
CODESARROLLO 1374801 6714007Compartamos 10804279 41825248Crear - Tacna 3778816 3891116
Credi Fe 781616 9393936ECLOF - ECU 179247 1154292
FADES 11948814 15501578FAMA 6201411 8835134FIE 22524645 35818903Finamerica 16575104 16097113FINCOMUN 3278938 5696556FMM - Popayan 6241821 12212867
FONDECO 3456625 5101801Genesis Empresarial
11154234 17746288
MiBanco 36964072 95873333Mushuc Runa 90737 2089076ProMujer -Nicaragua
426541 1006871
WWB - Medellin 2891207 4580998
Appendix 5 Portfolio vs Equity
Source Data is available through the Mix Market (2004)
OrganizationLoan Portfolio Equity
ACODEP 7258487 1921447Adelante 88594 72973
ADRI 2591240 781477AgroCapital 12018280 10766101Banco Solidario 103420000 12961000BancoSol 83629049 15299415CMAC - Sullana 28055720 6210291
61
COAC Maquita Cushunchic
870084 260331
CODESARROLLO 6714007 1285103
Compartamos 41825248 18350446
Crear - Tacna 3891116 1016912Credi Fe 9393936 863848ECLOF - ECU 1154292 459226FADES 15501578 4138972FAMA 8835134 6377663FIE 35818903 5360484Finamerica 16097113 3817960FINCOMUN 5696556 1042241FMM - Popayan 12212867 8510494FONDECO 5101801 1658075Genesis Empresarial
17746288 4765816
MiBanco 95873333 24261889Mushuc Runa 2089076 434311ProMujer -Nicaragua
1006871 1196015
WWB - Medellin 4580998 2213249
Appendix 6 Internal Rate of Return
Source Excel (German Version) calculation based on own data
A B C D E F
1 Date Cash Flow
Interest Rate Internal Rate of Return Balance Interest Principal
23 01012004 -100 15324 100 025489547 0045104534 02012004 03 999548955 025489547 0045104535 03012004 03 99909676 02547805 004521956 04012004 03 998643412 025466524 0045334767 05012004 03 998188909 025454968 0045450328 06012004 03 997733247 025443383 0045566179 08012004 03 999826083 050928361 -0209283610 09012004 03 999374595 025485114 004514886
hellip hellip hellip hellip hellip helliphellip hellip hellip hellip hellip hellip helliphellip hellip hellip hellip hellip hellip hellip1562 23122008 03 177951388 000528711 0294712891563 25122008 03 148859724 000908336 0290916641564 26122008 03 119239161 000379437 0296205631565 27122008 03 089543096 000303935 0296960651566 28122008 03 059771337 000228241 0297717591567 29122008 03 029923692 000152354 0298476461568 30122008 03 -3434E-07 000076274 029923726
62
The formula in the square C3 reads as follows
ldquoXINTZINSFUSS(B3B1568A3A156815)rdquo
Appendix 7 Subsidized Interest Rates and the Net Gains to Society
SourceOwn calculations
For simplicity only two groups of potential clients are distinguished This is possible
since using a continuum of potential clients would lead to the same results In addition it
is assumed that the amount of every loan (L) is equal and that all clients invest the
whole loan amount Group H consist of NH potential clients with a rate of return (rH) on
their invested capital higher than the cost recovering interest rate charged by the MFI
(iC) Group L consists of NL potential clients with a rate of return (rL) on their invested
capital lower than iC If the MFI charges iC the NGS can be calculated as follows
NGSC = NH times (rH - iC) times L
Since rH is bigger than iH (rH gt iC) according to the definition presented above the term
NGSH must be positive as long as NH does not equal zero If the MFI introduces a
subsidised interest rate (iS) lower than rL the NGS can be calculated as follows
(1) NGSS = NH times (rH - iS) times L + NLtimes (rL - iS) times L + (NH + NL) times (iS - iC) times L
(2) NGSS = NH times (rH- iC) times L + NLtimes (rL - iC) times L
The term (NH + NL) times (iS - iC) times L describes the amount of money that is needed in order
to subsidize the interest rate to the level iS By setting up an inequation it can be
examined under which conditions the NGSS are bigger than the NGSC
(3) NGSS gt NGSC
(4) NH times (rH- iC) times L + NLtimes (rL - iC) times L gt NH times (rH - iC) times L
(5) NLtimes (rL - iC) times L gt 0
(6) rL gt iC
63
So the NGSS could only be bigger than the NGSC if equation 6 holds This is
impossible since it violated the definitions presented above Therefore the introduction
of subsidized interest rates is always accompanied with a drop in the NGS
Appendix 8 Interest Rate vs Loan Size vs FSS vs PAR
Source Data is available through the Mix Market (2004)
Organization Country
Real Interest Rate
Loan Size (divided by the GDP per Capita) FSS PAR
BTFFKyrgyz Republic 3803 48260 1487 698
BesaFoundation Albania 2184 16076 684 260RFF Albania 1198 5783 4764 277PSHM Albania 2194 000 5758 198Mi-Bospo Bosnia 2974 5499 1261 020Prizma Bosnia 3474 3569 103 064Agroinvest Serbia 2201 4401 875 020KCLF Kazakhstan 5713 1713 865 090
Foccas Uganda10716 (723) 1550 584 29
ACEP Senegal 3280 20941 1643 1Padme Benin 2715 13575 1667 08Papme Benin 3086 53659 1405 24Vital Finance Benin 2676 9394 1015 17Finadev Benin 1738 14850 1024 21ABA Egypt 2579 1613 1168 88ASBA Egypt 2597 1702 1252 68DBACD Egypt 2490 1643 1073 0SBACD Egypt 2500 1734 982 67AMSSF Morocco 6926 787 1306 04Fondep Morocco 5199 650 889 071Zakoura Morocco 4414 900 98 006ENDA Tunisia 4008 1351 110 102BSFL India 1954 3269 856 99Share India 3426 1440 951 0Spandana India 2942 1618 1367 026SWC India 1864 2626 42 3036SKS India 2248 1912 578 0Grama Vidiya India 3176 1221 76 18Sneha India 3451 1433 933 0Buro Bangladesh 3206 1882 1093 17Upap Pakistan 2073 8183 757 03Seeds Sri Lanka 1004 1088 605 287EMT Cambodia 4324 1676 1016 01TPC Cambodia 4470 2035 832 27
64
WTF Phillippines 5816 1095 941 74TSKI Phillippines 5794 777 96 79Cacja Ecuador 862 6189 9460 897ACME Haiti 6043 6934 11685 450Grupo Cama Mexico 8961 267 10717 288
65
Appendix 9 Inflation vs GDP per Capita
Source IMF (2004)
Country Subject Description Units Scale 2000 2001 2002 2003 2004
Albania Gross domestic product per capita current prices US dollars Units 1083988 1238206 1396172 1757778 2229712
Albania Inflation annual percent change Percent 00 31 52 24 34
Bangladesh Gross domestic product per capita current prices US dollars Units 329310 327980 344494 369495 393717
Bangladesh Inflation annual percent change Percent 22 15 38 54 64
Benin Gross domestic product per capita current prices US dollars Units 361340 368213 405951 494725 560129
Benin Inflation annual percent change Percent 42 40 24 15 26
Bosnia and Herzegovina Gross domestic product per capita current prices US dollars Units 1255837 1321429 1466090 1807392 2070508
Bosnia and Herzegovina Inflation annual percent change Percent 50 32 03 02 09
Cambodia Gross domestic product per capita current prices US dollars Units 276413 280352 296577 305940 321247
Cambodia Inflation annual percent change Percent -08 02 33 12 20
Ecuador Gross domestic product per capita current prices US dollars Units 1227711 1590267 1804362 1957183 2082156
Ecuador Inflation annual percent change Percent -77 377 126 79 32
Egypt Gross domestic product per capita current prices US dollars Units 1550982 1461431 1278462 1188060 1083158
Egypt Inflation annual percent change Percent 28 24 24 32 52
India Gross domestic product per capita current prices US dollars Units 454206 458849 472915 542554 602625
India Inflation annual percent change Percent 40 38 43 38 47
Kazakhstan Gross domestic product per capita current prices US dollars Units 1236159 1490946 1655148 2000598 2579554
Kazakhstan Inflation annual percent change Percent 134 83 59 64 68
Kyrgyz Republic Gross domestic product per capita current prices US dollars Units 278256 306130 321079 349632 380637
Kyrgyz Republic Inflation annual percent change Percent 187 69 21 31 45
66
Mexico Gross domestic product per capita current prices US dollars Units 5957486 6274468 6425203 6111754 6377064
Mexico Inflation annual percent change Percent 95 64 50 45 44
Morocco Gross domestic product per capita current prices US dollars Units 1161302 1162154 1199584 1432725 1541041
Morocco Inflation annual percent change Percent 19 06 28 12 20
Pakistan Gross domestic product per capita current prices US dollars Units 437381 400356 440471 492913 538120
Pakistan Inflation annual percent change Percent 44 31 32 29 46
Philippines Gross domestic product per capita current prices US dollars Units 979423 900225 950707 963765 1018710
Philippines Inflation annual percent change Percent 43 61 31 30 54
Russia Inflation annual percent change Percent 208 215 158 137 103
Senegal Gross domestic product per capita current prices US dollars Units 478704 474460 507408 634171 714622
Senegal Inflation annual percent change Percent 09 30 23 -00 08
Serbia and Montenegro Gross domestic product per capita current prices US dollars Units 1031263 1389384 1882036 2491799 2795805
Serbia and Montenegro Inflation annual percent change Percent 699 911 212 113 79
Sri Lanka Gross domestic product per capita current prices US dollars Units 846811 796025 828256 904330 982466
Sri Lanka Inflation annual percent change Percent 62 142 96 63 64
Tunisia Gross domestic product per capita current prices US dollars Units 2034360 2065140 2149421 2534823 2881273
Tunisia Inflation annual percent change Percent 30 19 28 28 34
Uganda Gross domestic product per capita current prices US dollars Units 293404 249682 279587 280802 287204
Uganda Inflation annual percent change Percent 45 -20 57 51 35
67
References
Akerlof George A The Market for ldquoLemonsrdquo Qualitative Uncertainty and the Market Mechanism in Quarterly Journal of Economics Vol 84 (1970) pp 488-500
Amin Ruhul et al Integration of an Essential Service Package (ESP) in Child and Reproductive Health and Family Planning with a Micro-Credit Program for poor Women Experience from a Pilot Project in Rural Bangladesh in World Development Vol 29 (2001) No 9 pp 1611-1621
Bester Helmut Screening vs Rationing in Credit Markets with Imperfect Information in The American Economic Review Vol 75 (1985) No 4 pp 850855
Borst Dietmar Microfinance ndash Theoretische Grundlagen fuumlr den Einsatz sowie die Abschaumltzung des Potentials anhand einer Datenbankuntersuchung zur Verwundbarkeit der laumlndlichen Bevoumllkerung in Vietnam unpublished diploma thesis Karlsruhe 2004
BRAC Annual Report 2002 Dhaka 2003
Busch Alexander Kort Katharina Die Peanuts-Banker und ihre Kunden in Handelsblatt Nr 150 published August 5th 2004 p 8
Campion Anita Challenges to Microfinance Commercialization in Journal of Microfinance Vol 4 (1999) No 2 pp 57-65
Chu Michael Key Issues of Development Finance Somerville (MA) 1998
Dornbusch Ruumldiger Fischer Stanley Makrooumlkonomie Oldenburg 1995
Dunn Seth Flavin Christopher Moving the Climate Change Agenda Forward in State of the World New York London 2002 pp 24-50
Farrington Todd Efficiency in Microfinance Institutions in The MicroBanking Bulletin Issue No 4 pp 18-24
Gardner Gary The Challenge for Johannesburg Creating a More Secure World in State of the World New York London 2002 pp 3-23
Ghatak Subrata On Interregional Variations in Rural Interest Rates in Journal of Developing Areas Issue 18 pp 21-34
Gibbons David Serving the Poorest Sustainably in The MicroBanking Bulletin Issue No 5 (2000) pp 13-16
Gibbons David Meehan Jennifer W The Microcredit Summitrsquos Challenge WorkingToward Institutional Financial Self-Sufficiency While Maintaining a Commitment to Serving the Poorest Families in Journal of Microfinance Vol 1 (1999) No 1 pp 131-192
68
Goodwin-Groen Ruth Do Asian MFIs Access Funds from Commercial Banks inThe MicroBanking Bulletin Issue No 3 pp 8-10
Grameen Bank (ed) Grameen Generalized System Dhaka 2003
Gross Alexandra de Silva Samantha Social Fund Support of Microfinance A Reviewof Implementation Experience The World Bank Social Protection Discussion Paper No 0215 Washington DC 2002
Hashemi Syed M Schuler Sidney R Sustainable Banking with the Poor A Case Study of Grameen Bank Dhaka 1997
Helms Brigit Reille Xavier Interest Rate Ceilings and Microfinance The story so farConsultative Group to assist the Poor Occasional Paper No 9 September 2004 Washington DC 2004
Hoff Karla Stiglitz Joseph E Introduction Imperfect Information and Rural Credit Markets-Puzzles and Policy Perspectives in The World Bank Economic Review Vol 4 (1990) No 3 pp 235-250
Holcombe Susan Managing to Empower The Grameen Bankrsquos Experience of Poverty Allevation Dhaka 1995
Hulme David Mosley Paul Finance against Poverty London 1996
Jalvaani (ed) Flush with loans Micro credit for rural sanitation Vol 2 (1999) No 2 pp 1-2
Khandker Shahidur R Fighting Poverty with Microcredit Experience in Bangladesh Oxford et al 1998
Khandker Shahidur R Khalily Baqui Khan Zahed Grameen Bank Performance andSustainability The World Bank Discussion Paper No 306 Washington DC 1995
Lipsey Rechard G An Introduction to Positive Economics 5th edition London 1979
Littlefield Elizabeth Morduch Jonathan Hashemi Syed M Is Microfinance an Effective Strategy to Reach the Millennium Development Goals Consultative Group to Assist the Poorest Focus Note No 24 Washington DC 2003
Martinot Eric Cabraal Anil World Bank Solar Home Systems Projects Experience and Lessons Learned 1993-2000 in Renewable Energy Oxford 2000 pp 1-8
M-Cril Microfinance Review 2003 revised February 2004 Gurgaon 2004a
Mezzera Jaime Microcredit in Brazil The Gap Between Supply and Demand in The MicroBanking Bulletin Issue No 8 (2000) pp 22-24
The MicroBanking Bulletin (ed) Note to the Reader Vol 1 (1997) Issue No 1 pp 5-8
69
The MicroBanking Bulletin (ed) An Introduction to the Peer Groups and Tables Issue No 9 (2003) pp 53-60
MicroRate IADB Performance Indicators for Microfinance Institutions Technical Guide 3rd edition Washington DC 2003
MkNelly Barbara Dunford Christopher Impact of Credit with Education on Mothers and Their Young Childrenrsquos Nutrition Lower Pra Rural Bank Credit with Education Program in Ghana Freedom from Hunger Research Paper No 4 Davis (CA) 1998
MkNelly Barbara Dunford Christopher Impact of Credit with Education on Mothers and Their Young Childrenrsquos Nutrition CRECER Credit with Education Program in Bolivia Freedom from Hunger Research Paper No 5 Davis (CA) 1999
Morduch Jonathan The Microfinance Promise in Journal of Economic Literature Vol 37 (1999b) No 4 pp 1569-1614
Neus Werner Einfuumlhrung in die Betriebswirtschaftslehre Tuumlbingen 1998
Otero Maria Bringing Development Back into Microfinance Journal of Microfinance Vol 1 (1999) No 1 pp 8-19
Panjaitan-Drioadisuryo Rosintan D M Cloud Kathleen Gender self-employment and microcredit programs An Indonesian case study in The Quarterly Review of Economics and Finance Vol 39 (1999) pp 769ndash779
Perkins Dwight H et al Economics of Development 5th edition New York London 2001
Pitt Mark M Khandker Shahidur R Credit Programs for the Poor and the Health Status of Children in Rural Bangladesh in International Economic Review Vol 44 (2003) No 1 pp 87-118
Raiffeisen Friedrich W The Credit Unions 8th edition Neuwied 1966
Rhyne Elizabeth The Yin and Yang of Microfinance Reaching the Poor and Sustainability in The MicroBanking Bulletin Issue No 2 (1998) pp 6-9
Richardson David C Unorthodox Microfinance The Seven Doctrines of Success in The MicroBanking Bulletin Issue No 4 (2000) pp 3-7
Robinson Marguerite S The Microfinance Revolution Sustainable Finance for the Poor Washington DC 2001
Robinson Marguerite S The Microfinance Revolution Volume 2 Lessons from Indonesia Washington DC 2002
Rosenberg Richard Microcredit Interest Rates Consultative Group to assist the Poorest Occasional Paper No 1 revised November 2002 Washington DC 2002
70
Roth Michael Steinwand Dirk Mikrofinanz Weltweites Erfolgsmodell nur nicht inDeutschland Zur Uumlbertragbarkeit der Erfahrungen aus Entwicklungslaumlndern auf Deutschland Deutsche Gesellschaft fuumlr Technische Zusammenarbeit (ed) Eschborn2004
Schmidt Reinhard H Tschach Ingo Microfinance as a Nexus of Incentives Finance and Accounting Working Paper No 87A Frankfurt 2001
Schreiner Mark A Framework for the Analysis of the Performance and Sustainability of Subsidized Microfinance Organizations with Application to Banco Sol of Bolivia and Grameen Bank of Bangladesh unpublished PhD dissertation Columbus (O) 1997
Seibel Hans D Recent Developments in Microfinance Development Research Center Working Paper No 1998-5 Cologne 1998
Seibel Hans D History matters in microfinance in Small Enterprise Development ndashAn International Journal of Microfinance and Business Development Vol 14 (2003a) No 2 pp 10-12
Seibel Hans D Schmidt Petra How an Agricultural Development Bank Revolutionized Rural Finance The Case of Bank Rakyat Indonesia International Fund for Agricultural Development Rural Finance Working Paper B 5 Rome 2000
Sen Amartya Oumlkonomie fuumlr den Menschen ndash Wege zu Gerechtigkeit und Solidaritaumlt in der Marktwirtschaft Muumlnchen Wien 2000
Serageldin Ismail The View of the Chair in Consultative Group to Assist the Poorest Newsletter Issue No1 (1996) pp 1 11-12
Soros George Die Krise des globalen Kapitalismus Offene Gesellschaft in Gefahr Berlin 1998
Staschen Stefan Regulation and Supervision of Microfinance Institutions State of Knowledge Deutsche Gesellschaft fuumlr Technische Zusammenarbeit (ed) Eschborn 1999
Steinwand Dirk The Alchemy of Microfinance The Evolution of the IndonesianPeoples Credit Banks (BPR) to 1999 and a Contemporary Analysis Berlin 2001
Stiglitz Joseph E Peer Monitoring and Credit Markets in The World Bank Economic Review Vol 4 (1990) No 3 pp 351-366
Stiglitz Joseph E Weiss Andrew Credit Rationing in Markets with Imperfect Information in The American Economic Review Vol 71 (1981) No 3 pp 393-410
Tschach Ingo Theorie der Entwicklungsfinanzierung Mit Kleinkreditprogrammen Kredit- und Arbeitsmarktsegmentierung uumlberwinden Frankfurt 2000
UNDP Human Development Report 2004 New York 2004
71
UNFPA state of the world population 2004 New York 2004
UNICEF The State of the Worldrsquos Children 2002 NewYork Geneva 2002
Varley Robert C G Financial Services and Environmental Health Household Credit for Water and Sanitation Environmental Health Project Applied Study No 2 Washington DC 1995
Volkery Carsten Kampf um Straszligenhaumlndler in Die Zeit Nr 23 published May 27th
2004 p 33
Wardhana Ali Introduction in The Microfinance Revolution ndash Sustainable Finance for the Poor Washington DC 2001 pp XVII-XXVII
Woodworth Warner Woller Gary Greetings from the Editors Journal of Microfinance Vol 1 (1999) No 1 p 6
The World Bank Group World Development Indicators 2004 Washington DC 2004
Worldwatch Institute (2002) Vital Signs 2002 New York London 2002
Wimmer Nancy Barua Dipal Less is more Microfinance for solar energy in rural areas in Renewable Energy World Review Issue 2004-2005 Vol 7 (2004) No4 pp 170-179
Yunus Muhammad Grameen Bank II ndash Designed to Open new Possibilities Dhaka 2002
Yunus Muhammad Grameen ndash Eine Bank fuumlr die Armen dieser Welt Muumlnchen 1998a
Internet References
Abishek Lal (nd) An Overview of Microfinance and Environmental Management [http wwwgdrcorgicmenvironabhishekhtml] (availability date October 5 2004)
ACCION (nd) our history [httpwwwaccionorgabout_our_historyasp] (availability date October 5 2004)
ACCION (nd) key statistics [httpwwwaccionorgabout_key_statsasp] (availability date October 5 2004)
Ahmad Zulfiqar (nd) Forms of Regional Cooperation in Microfinance in South Asia [httpwwwbwtporgarcmpakistanIV_News_and_EventsBWTPworkshopZulfiqar20Ahmad20paper20(BWTP-PMN2029Jan04)pdf (availability date October 6 2004)
72
Ahmed Salehuddin (2003) Foreword [httpwwwpksf-bdorgaprm_summit_brochure htm] (availability date September 30 2004)
Annan Kofi (2002) Statement at The Microcredit Summit +5 [httpwww microcreditsummitorgenews2003-03_sp_chowdhuryhtml) (availability date October 5 2004)
Barnes Carolyn (2001) Microfinance Program Clients and Impact An Assessment of Zambuko Trust Zimbabwe [httpwwwmicrofinancegatewayorgfiles18553_Barnes_Zambuko_Trust_2001pdf] (availability date October 5 2004)
Barnes Carolyn Gaile Gary Kibombo Richard (2001) The Impact of Three Microfinance Programs in Uganda [httpwwwmicrofinancegatewayorgfiles2935_Barnes_2001pdf] (availability date October 5 2004)
Barua Dipal (2004) Success of Grameen Shakti in the Field of Renewable Energy Sector in Bangladesh [httpwwwrenewables2004depptPresentation1-SessionVA(14-1530h)-Baruapdf] (availability date September 30 2004)
Bhatt Ela (1997) In 1975 [httpwwwmicrocreditsummitorgdeclarationhtm] (availability date September 30 2004)
BlueOrchard (2004a) Microfinance [httpwwwblueorchardchenmicrofinance_institutions asp] (availability date October 5 2004)
BlueOrchard (2004b) January 2004 Newsletter [httpwwwblueorchardchmedialibrarywebsitenewsletter_jan_2004pdf] (availability date October 5 2004)
Brynjolfsson John (2004) John Brynjolfsson Discusses Recent Trends in TIPS Issuance [httpwwwpimcocomLeftNavPIMCO+Spotlight2004Spotlight_2_04htm] (availability date October 5 2004)
CGAP (2003) Report to the Board of Executive Directors [httpwww-wdsworldbankorgservletWDSContentServerWDSPIB20031208000012009_20031208101736RenderedPDF27441pdf] (availability date October 5 2004)
Chen Shaohua Ravallion Martin (2004) How have the worldrsquos poorest fared since the early 1980s [httpwwwworldbankorgresearchpovmonitorMartinPapersHow_have_the_poorest_fared_since_the_early_1980spdf] (availability date October 5 2004)
Cheston Susy Kuhn Lisa (2002) Empowering Women through Microfinance[httpwwwmicrofinancegatewayorgfiles3240_Cheston_2002doc] (availability date October 5 2004)
Christen Robert P et al (1995) Maximizing the Outreach of Microenterprise FinanceAn Analysis of Successful Microfinance Programs [httpwwwdecorgpdf_docsPNABS519 pdf] (availability date October 5 2004)
73
CIA (2004) The World Factbook [httpwwwciagovciapublicationsfactbook] (availability date October 5 2004)
Clear Profit (2004) Microfinance Bond Record May Double [httpwwwclear-profitcomissuescpsep04txt] (availability date September 30 2004)
Daley-Harris Sam (2003) State of the Microcredit Summit Campaign Report 2003 [httpwwwmicrocreditsummitorgpubsreportssocr2003SOCR03-E[txt]pdf] (availability date September 30 2004)
Dominiceacute Robert (2004) Interview in Microfinance Bond Record May Double [httpwwwclear-profitcomissuescpsep04txt] (availability date September 30 2004)
Donahue Jill Kabbucho Kamau Osinde Sylvia (2001) HIVAIDSmdashResponding To A Silent Economic Crisis Among Microfinance Clients In Kenya and Uganda [httpwwwmicrosave-africacomget_fileaspdownload_id=541] (availability date September 30 2004)
Donahue Jill Sussman Linda (1999) Building a Multi-Sectoral Response Follow-Up Assessment of Programming for Children and Families Affected by HIVAids in Kenya [httpwwwdecorgpdf_docspnacg778pdf] (availability date September 30 2004)
The Economist (1998) [httpwwweconomistcomdisplaystorycfmstory_id=S2629H3C28Q13F240A] (availability date September 30 2004)
Finca (nd) Introduction [httpvillagebankingorgwhereindexphp3] (availability date September 30 2004)
Fischer Stanley (2003) Statement at The Asia Society and Womens World BankingAnnual Microfinance Conference [httpwwwiiecomfischerpdffischer051303pdf] (availability date September 30 2004)
Friedman Milton (nd) Samuha [httpwwwsamuhaorgm-1htm] availability date September 30 2004)
FXTOP (2004) Historical Exchange Rates [httpfxtopcomdehistoratesphp3] (availability date September 30 2004)
Gibbons David Meehan Jennifer W (2002) Financing Microfinance for Poverty Reduction [httpwwwmicrocreditsummitorgpapersfinancing_finalpdf] (availability date September 30 2004)
Grameen Bank (2004) Grameen Bank At a Glance [httpwwwgrameen-infoorgbankcdshtml] (availability date September 30 2004)
Grameen Trust (nd) Grameen Bank Replication Program [httpwwwgrameen-infoorggrameengtrustreplicationhtml8721] (availability date September 30 2004)
74
Hossain Farhad (2004) Microfinance in Development [httpwwwvalthelsinkifi staff jkoponenb1104FarhadFeb2304pdf] (availability date October 5 2004)
IMF (2004) Data [httpwwwimforgexternalpubsftweo200402datadbginimcfm] (availability date October 5 2004)
IMI (2004) Investments [httpwwwimi-agcomoverviewindexhtml] (availability date September 30 2004)
IPCC (2001) Summary for Policymakers [httpwwwipccchpubspm22-01pdf] (availability date September 30 2004)
Jansson Tor Wenner Mark (1997) Financial Regulation and its Significance for Microfinance in Latin America and the Caribbean [httpwwwgdrcorgicmgoverniadb-janssonpdf] (availability date October 5 2004)
Ken Daniel Ten Roeun Van (2004) The Cycle of Debt - As Microcredit Institutions Grow Some Question Their Effect on Poverty [httpwwwcamnetcomkhcambodiadaily selected_featurescd-21-02-04htm] (availability date September 30 2004)
Kim Julia (2002) Social Interventions for HIVAIDS - Intervention with Microfinance for AIDS and Gender Equity [httpwwwwitsaczaradarPDF20filesIntervention_monograph_no_picspdfpdf] (availability date September 30 2004)
Llanto Gilberto (nd) Vietnam [httpwwwadborgDocumentsBooksCentral_Banks_MicrofinanceCountry_Studiesvietnampdf] (availability date September 30 2004)
The Microfinance Gateway (nd) Frequently Asked Questions [httpwwwmicrofinance gatewayorgsectionfaq1] (availability date October 5 2004)
Microfinance Rating and Assessment Fund (2004) Qualified Raters [httpwwwmfrating orgmfi_institutionsqualified_ratershtml] (availability date October 5 2004)
Microcredit Summit (1997) Declaration and Plan of Action [httpwwwmicrocreditsummit orgdeclarationhtm] (availability date September 30 2004)
MicroRate (nd) Performance Indicators and Ratios [httpwwwmicroratecomENGLISHsiteRATINGSindicatorshtml] (availability date September 30 2004)
MicroRate (2002) The Finance of Microfinance [httpwwwmicroratecomPDFFinance20of20Microfinancepdf] (availability date September 30 2004)
MicroRate (2004) Adjusted comparison table [httpwwwmicroratecomENGLISHsitePDFAdjusted20Comparison20Table060320engpdf] (availability date October 5 2004)
75
Mix Market (2004) The Mix Market [httpwwwmixmarketorg] (availability date October 5 2004)
Morduch Jonathan (1999b) The Grameen Bank A Financial Reckoning [httpwwwwwsprincetonedu~rpdsmacarthurdownloadsmorduch_grameen_bankpdf] (availability date September 30 2004)
Pallen Dean (1997) Environmental Sourcebook for Micro-Finance Institutions [httpwwwacdi-idagccaINETIMAGESNSFvLUImagesea20summaries$fileSOURC Epdf] (availability date September 30 2004)
Prisma (2002) The Case for Private Capital Market Creation in the Development Field of Microfinance [httpwwwsocialenterprisenetpdfsprivate_capital_marketpdf] (availability date September 30 2004)
Schmidt Reinhard H Zeitinger C-P (1997) Critical Issues in Microbusiness Finance and the Role of Donors No 6 [httpwwwgdrcorgicmmfi-donorpdf] (availability date September 30 2004)
Seibel Hans D (2003b) Commodity finance a commercial proposition Micro- and Mesofinance for Agricultural Commodity Production Processing and Trade [httpwwwuni-koelndeew-fakaef05-20042003-420Commodity20Financepdf] (availability date September 30 2004)
Simanowitz Anton Walter Alice (2002) Ensuring Impact Reaching the Poorest while Building Financially Self-sufficient Institutions and Showing Improvement in the Lives of the Poorest Families [httpwwwidsacukimpactPublicationsWorkingPapersOP3MCSSumdoc] (availability date September 30 2004)
Smith Stephen C Jain Sanjay (1999) Village Banking and Maternal and Child Health Theory and Evidence from Ecuador and Honduras[httphomegwuedu~scsmith healthrevwd801pdf] (availability date September 30 2004)
United Nations (1999) International Year of Microcredit 2005 [httpods-dds-nyunorgdoc UNDOCGENN9976933PDFN9976933 pdfOpenElement] (availability date October 5 2004)
United Nations (2000) United Nations Millennium Declaration [httpods-dds-nyunorgdocUNDOCGENN0055951PDFN0055951pdfOpenElement] (availability date October 5 2004)
US Census Bureau (2004) Total Midyear Population for the World 1950-2050 [httpwwwcensusgovipcwwwworldpophtml] (availability date October 5 2004)
WHO (2004) Making pregnancy safer [httpwwwwhointmediacentrefactsheets fs276en] (availability date September 30 2004)
WHO (2001) Child Health [httpwwwwhointmipfiles2082AAGChildHealthpdf] (availability date September 30 2004)
76
The World Bank Group (nd) Health Nutrition and Population and the Millennium Development Goals [www1worldbankorghnpMDGMDG20-20HNPbookletpdf] (availability date September 30 2004)
Yunus Muhammad (1998) Championing the Right to Credit for Poor Women Around the World [httpaspgrameencom dialoguedialogue34interviewhtml] (availability date September 30 2004)
UNAIDS (2004) [httpwwwunaidsorgbangkok2004GAR2004_pdfUNAIDSGlobalReport2004_enpdf] (availability date September 30 2004)
Ratings
M-Cril (2000) SPANDANA [httpwwwratingfundorgspanishdocsSPANDANA_RatingReportpdf] (availability date October 7 2004)
M-Cril (2001a) BASIX [httpwwwbasixindiacomMcrilasp] (availability date October 7 2004)
M-Cril (2001b) BDB [httpwwwratingfundorgspanishdocsRF_BDBpdf] (availability date October 7 2004)
M-Cril (2001c) SNEHA [httpwwwratingfundorgspanishdocsRF_Sneha-u1pdf] (availability date October 7 2004)
M-Cril (2002a) KCLF [httpwwwratingfundorgdocsRF-KCLF-risk20reportdoc] (availability date October 7 2004)
M-Cril (2002b) NWTF [httpwwwratingfundorgspanishdocsRF_NWTFpdf] (availability date October 7 2004)
M-Cril (2002c) SEEDS [httpwwwratingfundorgspanishdocsRF_SEEDS_2002_Ratingpdf] (availability date October 7 2004)
M-Cril (2002c) Share [httpwwwratingfundorgspanishdocsRF_SHAREpdf] (availability date October 7 2004)
M-Cril (2002d) TSKI [httpwwwratingfundorgspanishdocsRF_Tski_mcrilfinal(-) reportpdf] (availability date October 7 2004)
M-Cril (2003a) ASA [httpwwwratingfundorgdocsASA20updatepdf] (availability date October 7 2004)
M-Cril (2003b) BURO [httpwwwm-crilcomburopdf] (availability date October 7 2004)
M-Cril (2003c) EMT [httpwwwratingfundorgdocsEMTpdf] (availability date October 7 2004)
77
M-Cril (2003d) SKS [httpwwwmixmarketorgendemanddemandshowprofileaspett=25ampshowinfo=adjusted] (availability date October 7 2004)
M-Cril (2003d) TPC [httpwwwratingfundorgdocsTPC_Finalpdf] (availability date October 7 2004)
M-Cril (2004b) UPAP [httpwwwratingfundorgdocsUPAP_2004pdf] (availability date October 7 2004)
Microfinanza (2002a) ACME [httpwwwratingfundorgspanishdocsACME_finalpdf] (availability date October 7 2004)
Microfinanza (2002b) BTFF [httpwwwratingfundorgspanishdocsBTFF_RatingReportpdf] (availability date October 7 2004)
Microfinanza (2002c) BESA [httpwwwratingfundorgspanishdocsBESA_RatingReportpdf] (availability date October 7 2004)
Microfinanza (2002d) CAME [httpwwwratingfundorgdocsEvaluacionCAME(-) Finaldoc] (availability date October 7 2004)
Microfinanza (2002e) RFF [httpwwwratingfundorgdocsRFF20finalpdf] (availability date October 7 2004)
Microfinanza (2002f) PSHM [httpwwwratingfundorgspanishdocsPSHM_Reportpdf] (availability date October 7 2004)
Microfinanza (2003) CAJCA [httpwwwratingfundorgdocsCalificacion_Jardin_Azuayo_ratingpdf] (availability date October 7 2004)
Microserve (2003) ENDA [httpwwwmixmarketorgendemanddemandshowprofileaspett=865ampshowinfo=adjusted] (availability date October 7 2004)
Planet Rating (2002a) FONDEP [httpwwwmfratingorgRatingscompleted_ratingshtml] (availability date October 7 2004)
Planet Rating (2002b) PRIZMA [httpwwwmixmarketorgendemanddemandshowprofileaspett=111ampshowinfo=adjusted] (availability date October 7 2004)
Planet Rating (2002c) SWS [httpwwwratingfundorgspanishdocsSWC_reportpdf] (availability date October 7 2004)
Planet Rating (2002d) ZAKOURA [httpwwwratingfundorgspanishdocsRF_Zakourapdf] (availability date October 7 2004)
Planet Rating (2003a) AMSSF [httpwwwratingfundorgdocsPlanetRating_AMSSF_010803pdf] (availability date October 7 2004)
Planet Rating (2003b) FOCCAS [httpwwwratingfundorgdocsPlanetRatingFOCCAS120803pdf] (availability date October 7 2004)
78
Planet Rating (2003c) PADME [httpwwwmfratingorgdocsPlaNetRatingPADME070302_Englishpdf] (availability date October 7 2004)
Planet Rating (2003d) PAPME [httpwwwmfratingorgdocsPAPME_PlanetRating080903pdf] (availability date October 7 2004)
Planet Rating (2003e) VITAL FINANCE [httpwwwmfratingorgdocsVital20Finance_Sept202003pdf] (availability date October 7 2004)
Planet Rating (2004a) ABA [httpwwwratingfundorgdocsABA_April202004pdf] (availability date October 7 2004)
Planet Rating (2004b) ACEP [httpwwwmfratingorgdocsACEPSeacuteneacutegal_2004pdf] (availability date October 7 2004)
Planet Rating (2004c) AGROINVEST [httpwwwratingfundorgdocsAgroInvest_June202004pdf] (availability date October 7 2004)
Planet Rating (2004d) ASBA [httpwwwratingfundorgdocsASBA_April202004pdf] (availability date October 7 2004)
Planet Rating (2004e) DBACD [httpwwwratingfundorgdocsDBACD_April202004pdf] (availability date October 7 2004)
Planet Rating (2004f) FINADEV [httpwwwmfratingorgdocsFinadev_2004pdf] (availability date October 7 2004)
Planet Rating (2004g) MI-BOSPO [httpwwwratingfundorgdocsMIBOSPO_160404pdf] (availability date October 7 2004)
Planet Rating (2004h) SBACD [httpwwwratingfundorgdocsSBACD_PlanetRating300604pdf] (availability date October 7 2004)
Other Sources
Interview Shaw Newaz Deputy General Manager of the Grameen Bank October 30th
2003
Hodson Charles (2001) Your Business Your World Jim Boulden CNN (ed) Dhaka 2001
5
1 Introduction
The poor stay poor not because they are lazy but because they have no access to
capital1 If this claim made by nobel laureate Milton Friedman actually holds will be
discussed in the initial part of this paper
First a short overview of the development of the microfinance sector will be given
showing that the concept of providing financial services to low income people is much
older than still believed by many development practitioners and bankers around the
world This is important since it underlines the contribution that microfinance
institutions (MFIs) can make to the development of the financial sector in their
respective countries Subsequently the various ways how such services can assist low
income people will be discussed demonstrating that even the poorest can benefit from
the provision of small loans This is a view that is still questioned in the academia
In the second part of this paper it will be shown that although some 10000
organizations are involved in microfinance already2 they are not even close to meet the
tremendous demand for low scale financial services This sector is still widely neglected
by for profit investors and traditional bankers After examining why these groups
continue to avoid investments in the microfinance industry it will be checked if the
assumptions that underline their arguments actually hold The possibility if MFIs could
raise their interest rates to an extend that would allow them generate profits sufficiently
high to attract for profit investors will be discussed
According to Hulme and Mosley MFIs ldquocan either go for growth and put their resources
into underpinning the success of established and rapidly growing institutions or go for
poverty impact and put their resources into poverty-focused operations with a higher
risk of failure and a lower expected returnrdquo3 If this is true will be examined in the third
part by checking if poor borrowers are able to bear interest rates significantly above
1 See Friedman (nd)2 See BlueOrchard (2004a)3 See Hulme and Mosley (1996) p 206
6
those charged by conventional banks Finally a sample of 39 MFIs will be used to verify
the drawn conclusions by examining the effects their interest rates have on their
financial performances and their repayment record
7
2 The Development of Microfinance
21 What is Microfinance
According to the Journal of Microfinance the term defines what ldquois arguably the most
innovative strategy to address the problems of global povertyldquo4 This view is shared by
the United Nations (UN) which declared that the year 2005 would be the international
year of microcredit5 while their General Secretary Kofi Annan stated in 2002 that
ldquo[m]icrocredit is a critical anti-poverty tool and a wise investment in human capitalrdquo6
Hossain describes microfinance as ldquothe practice of offering small collateral free loans
to members of cooperatives who otherwise would not have access to the capital
necessary to begin a small business or other income generating activitiesrdquo7 This view is
to narrow since it not only excludes such services as saving accounts and insurances8
but also ignores the possibility of collateral demanding MFIs Although it is true that
many MFIs do not take collateral especially if they are focusing on the poorest which
normally do not possess any collateral9 several MFIs in fact do require some form of
collateral10
Roth and Steinwand give a more general definition They describe microfinance as ldquothe
provision of a wide range of financial services like saving accounts loans payment
services and insurances for people with no regular access to financial services through
traditional financial institutionsrdquo11 Here it is important not to confuse the terms
traditional or conventional with the term formal If for example an illiterate beggar
takes a $10 loan from the Grameen Bank in Bangladesh she becomes a client of a
4 See Woodworth and Woller (1999) p 65 See United Nations (1999) p 16 Annan (2002)7 Hossain (2004)8 See The Microfinance Gateway (nd) Robinson (2001) p9 Otero (1999) p 89 See chapter 3 for a more detailed discussion on poverty10 See Robinson 2002 p 24311 See Roth and Steinwand (2004) p 2 ldquodie Bereitstellung einer breiten Palette von Finanzdiensteistungen wie Spareinlagen Kredite Zahlungsverkehr und Versicherungsleistungen fuumlr Wirtschaftsakteure die keinen regelmaumlszligigen Zugang zu Finanzdienstleistungen durch klassische Finanzinstitutionen habenldquo
8
formal financial institution (a registered bank) but obviously not of a traditional or
conventional one12
Although the other services have become more important in recent years microcredit is
still considered their central service by most MFIs In many countries it refers to loans
below $ 100013 however for significant cross country comparison it is more
meaningful to look at the ratio of the loan amount to the gross national product (GNP)
or gross domestic product (GDP) per capita for the respective countries While a loan of
$1000 is more than four times larger than the GNP per capita in Uganda it represents
less than 20 of the GNP per capita in Mexico The MicroBanking Bulletin (MBB) has
categorized the target market for MFIs by the average outstanding loan amount as a
percentage of the GNP per capita ranging from Low-end (less than 20) to Small
Business (more than 250)14 Especially for the latter category one must to look closely
at the condition of the financial service market where an institution is active Although
MFIs exist in industrialized countries15 one would definitely turn to a traditional
financial institution for a loan bigger than 250 of the GNP per capita and therefore not
to a MFI according to the definition presented above
22 The Origin of Microfinance
Although neither of the terms microcredit or microfinance were used in the academic
literature nor by development aid practitioners before the 1980s or 1990s16
respectively the concept of providing financial services to low income people is much
older
While the emergence of informal financial institutions in Nigeria dates back to the 15th
century17 they were first established in Europe during the 18th century as a response to
the enormous increase in poverty since the end of the extended European wars (1618 ndash
12 See Yunus (2002) p 19 for a more detailed description of the destitute member program of the Grameen Bank which focuses exclusively on persons with no regular income and no assets at all 13 See MicroBanking Bulletin (1997) p 614 See MicroBanking Bulletin (2003) p 5415 See Yunus (1998a) pp 229 et sqq16 See Robinson (2001) p XXX17 See Seibel (2003a) p 12
9
1648)18 In 1720 the first loan fund targeting poor people was founded in Ireland by the
author Jonathan Swift19 After a special law was passed in 1823 which allowed charity
institutions to become formal financial intermediaries a loan fund board was established
in 1836 and a big boom was initiated Their outreach peaked just before the government
introduced a cap on interest rates in 1843 At this time they provided financial services
to almost 20 of Irish households20
The credit cooperatives21 created in Germany in 1847 by Friedrich Wilhelm Raiffeisen
served 14 million people by 191022 He stated that the main objectives of these
cooperatives ldquoshould be to control the use made of money for economic improvements
and to improve the moral and physical values of people and also their will to act by
themselvesrdquo23
In the 1880s the British controlled government of Madras in South India tried to use the
German experience to address poverty which resulted in more than nine million poor
Indians belonging to credit cooperatives by 194624 During this same time the Dutch
colonial administrators constructed a cooperative rural banking system in Indonesia
based on the Raiffeisen model25 which eventually became Bank Rakyat Indonesia
(BRI) now known as the largest MFI in the world26
23 Microfinance after the Second World War
Because of further prudential regulation and effective supervision eg through bank
superintendencies the banking sector in the now developed world experienced
continuous growth Today the vast majority of the citizens of the industrialized
countries have access to financial services with many of them being customers of
former MFIs27
18 See Steinwand (2001) p 5119 See Robinson (2002) p 9620 See Seibel (2003a) p 1021 first known as Darlehnsvereine and now called Raiffeisenbanken22 See Morduch (1999a) p 157323 Raiffeisen (1966) quoted in Richardson (2000) p 324 See Morduch (1999a) p 157425 See Robinson (2002) p 9726 See Roth Steinwand (2004) p 327 See Seibel (2003a) p 11
10
This is not true for most developing countries where market penetration of financial
institutions is far from reaching the majority of the inhabitants (see chapter 4) A variety
of reasons is responsible for this including that the banking sector in the most
developing countries have developed in a very different way to than those in
industrialized countries
One of the most important reasons is that in contrast to the industrialized countries little
attention has been paid to the legal recognition prudential regulation and effective
supervision of informal financial institutions28 This insecure legal environment leads to
several problems Since the regulatory framework for mobilizing savings often does not
fit the needs of institutions targeting low income people many organizations are not
permitted to do so and are therefore missing funds to on-lend as credit29 An additional
problem is the lack of a deposit insurances This not only increases the risk of a bank
run but also keeps people from depositing their savings in a financial institution30 In
addition inappropriate interest rate ceilings prevail in many countries While politics
claim they are lowering the interest rates charged to the poor they de facto only limit
their access to financial services (see chapter 5)31
Another problem that retarded the growth of the financial sector in developing countries
was the supply-leading finance theory which dominated the development strategies of
many countries after the second world war32 This theory ldquo refers to the provision of
loans in advance of the demand for credit for the purpose of inducing economic
growthrdquo33 Since it was believed that poor people were neither able to save (and thus
dependent on outside funding) nor capable of paying commercial rates of interest
massive subsidized credit programs were established34 The results were alarming
Repayment rates often did not exceed 50 percent and some government financed
programs even had default rates of more than 90 percent35 The main reason being that
credit was not provided according to business management principles but instead
28 See Seibel (1998) p 829 See Robinson (2001) p 4930 See Staschen (1999) p 1431 See Gibbons (2000) p 1532 See Morduch (1999a) p 157033 Robinson (2001) p 14034 See Borst (2004) pp 33 et sqq35 See Yunus (1998a) p 154 Robinson (2001) p 145
11
according to political objectives Therefore receiving loans was seen as a reward for the
constituents rather than as a business transaction Most of the funds earmarked for the
poor also never reached them ending up instead in the hands of the local elites
Attracted by the below market interest rates and the possibility not to pay back at all
these groups lobbied to be treated privileged and often used the money received for
consumption or for on-lending at higher rates36 But subsidized credit not only
encouraged corruption it also discouraged sustainable financial institutions since they
could not compete with interest rates that were not aimed to cover all costs and were
sometimes even lower than the interest paid on savings37 The low or negative spread
also worked as a negative incentive to institutionsrsquo effort to mobilize savings which in
turn intensified the problem of credit rationing (see chapter 5)
24 Microfinance Today
In the 1970s a paradigm shift started to take place The failure of subsidized government
or donor driven institutions to meet the demand for financial services in developing
countries let to several new approaches Some of the most prominent ones are presented
below
Bank Dagan Bali (BDB) was established in September 1970 to serve low income people
in Indonesia without any subsidies and is now ldquowell-known as the earliest bank to
institute commercial microfinancerdquo38 While this is not true with regard to the
achievements made in Europe during the 19th century it still can be seen as a turning
point with an ever increasing impact on the view of politicians and development aid
practitioners throughout the world In 1973 ACCION International a United States of
America (USA) based non governmental organization (NGO) disbursed its first loan in
Brazil39 and in 1974 Professor Muhammad Yunus started what later became known as
the Grameen Bank by lending a total of $27 to 42 people in Bangladesh40 One year
later the Self-Employed Womenrsquos Association started to provide loans of about $15 to
36 See Robinson (2001) pp 144 et sqq37 Before BRI underwent a major transformation in 1983 a negative spread between interest rates on loans and savings existed While the bank lent at a 12 annual effective interest rate it paid 15 on savingsSee Robinson (2001) p 10638 Wardhana (2001) p XXVII39 See ACCION (nd)40 See Yunus (1998a) p 16 et sqq
12
poor women in India41 Although the latter examples still were subsidized projects they
used a more business oriented approach and showed the world that poor people can be
good credit risks with repayment rates exceeding 9542 even if the interest rate charged
is higher than that of traditional banks Another milestone was the transformation of
BRI starting in 1984 Once a loss making institution channeling government subsidized
credits to inhabitants of rural Indonesia it is now the largest MFI in the world being
profitable even during the Asian financial crisis of 1997 ndash 199843
In February 1997 more than 2900 policymakers microfinance practitioners and
representatives of various educational institutions and donor agencies from 137
different countries gathered in Washington DC for the first Micro Credit Summit This
was the start of a nine year long campaign to reach 100 million of the world poorest
households with credit for self employment by 200544 According to the Microcredit
Summit Campaign Report 67606080 clients have been reached through 2527 MFIs by
the end of 2002 with 41594778 of them being amongst the poorest before they took
their first loan45 Since the campaign started the average annual growth rate in reaching
clients has been almost 40 percent46 If it has continued at that speed more than 100
million people will have access to microcredit by now and by the end of 2005 the goal
of the microcredit summit campaign would be reached As the president of the World
Bank James Wolfensohn has pointed out providing financial services to 100 million of
the poorest households means helping as many as 500 ndash 600 million poor people47
41 See Bhatt (1997)42 See Yunus (1998a) p 143 et sqq43 See Robinson (2002) p 38044 See Daley-Harris (2003) p 345 ldquoThe Microcredit Summit Campaign defines ldquopoorestrdquo as those who are in the bottom half of those living below their nationrsquos poverty line or are living on less than $1 a day adjusted for purchasing power parity (PPP)rdquo See Daley-Harris (2003) p 3 This definition will also be used throughout this paper46 See Daley-Harris (2003) p 1847 See Morduch (1999a) p 1570
13
3 The Impact of Microcredit
31 Microcredit and the Millennium Development Goals
In 1996 Ismail Serageldin the then chair of the Consultative Group to Assist the Poorest
(CGAP)48 claimed that ldquo[m]icrofinance is a proven instrument to assist the very poorrdquo49
This view is also shared by the World Watch Institute50 and underlines what has been
stated above namely that microfinance can be used as a strong anti-poverty tool But
does microfinance actually meet these expectations and keep this promise51
The impact that microcredit has on the lives of poor people will be demonstrated by
showing how it contributes to each of the eight Millennium Development Goals
(MDGs)52 which are related to the reduction of poverty in all its forms These goals
were resolved in September 2000 by the General Assembly of the UN in their
Millennium Declaration53
32 The Eradication of extreme Poverty and Hunger
The aim of the first MDG is to halve the proportion of people who live on less than $1 a
day between 1990 and 2015 According to current population projections of the World
Bank54 this would equal 849 million people in 201555
48 The Consultative Group to Assist the Poorest is a consortium of 28 public and private development agencies working together to expand access to financial services for the poor in developing countries and was established by the World Bank in 1995 Recently it changed its name to Consultative Group to Assist the Poor49 See Serageldin (1996) p 1150 See Gardner (2002) p 1851 See Morduch (1999a) pp 1569 et sqq52 The Millennium Development Goals are (1) eradicate extreme poverty and hunger (2) achieve universal primary education (3) promote gender equality and empower women (4) reduce child mortality (5) improve maternal health (6) combat HIVAIDS malaria and other diseases (7) ensure environmental sustainability and (8) develop a global partnership for development53 See United Nations (2000)54 See World Bank (2004) p 38 et sqq55 Although it is not explicitly mentioned in the Millennium Declaration it is commonly assumed that the share of people living on less than $1 in low and middle income countries should be halved If the share would be calculated with regard to the worldrsquos total population the goal for 2015 would 818 million people For the worldrsquos total population in 1990 see US Census Bureau (2004)
14
Today almost 11 billion people live on less than $1 and more than 27 Billion live on
less than $2 per day56 The mean income for those living under $1 a day is $077 and it
is $125 for those living under $2 a day57 While the number of people living on less
than $1 per day is slowly decreasing and is expected to be 913 million in 2015 the
number of people living on less than $2 a day is actually increasing58 One of the
outcomes from this degree of poverty is that more than 27000 children die every day
from mostly preventable diseases many of them related to hunger59
Microcredit enables poor people to start new businesses or to diversify existing ones
which helps them to increase their income In addition to large amounts of anecdotal
evidence several studies have documented the positive economic impact microcredit
has on its clients Cloud and Panjaitan-Drioadisuryo have found that the average income
of a sample of BRI borrowers has increased by 112 percent and that 90 percent of their
families have crossed the poverty line60 Only 12 out of the 121 respondents of that
study reported that their income had not increased61 According to the Grameen Bank
website 5109 percent of their clients have crossed the poverty line since they took their
first loan62
A study conducted by Barnes showed that the program of the Zambuko Trust a local
MFI in Zambia had a considerable impact on the poorest clients consumption of meat
fish and chicken63 While 76 percent of the continuing clients of the MFI called Share in
India significantly increased their income and 50 percent have crossed the poverty line 64 Khandker discovered in his well known study ldquoFighting poverty with microcreditrdquo
that there is a connection between the microcredit programs of three Bangladeshi MFIs
and household per capita expenditure For every dollar borrowed by a Grameen Bank
member household consumption increases by $018 In addition he found that 5 percent
56 See Chen and Ravallion (2004) p 2957 In fact those people live on less than $108 and $215 respectively a day in 1993 PPP This means that the nominal dollar value of their income is considerably lower See Chen and Ravallion (2004) p 9 58Both numbers are decreasing in Asia but increasing in the rest of the world See Chen and Ravallion (2004) p 22 et sqq59 See UNICEF (2002) p 660 A consistent definition of the term ldquopoverty linerdquo does not exists among different nations Therefore the term will be used according to the definition of the respective country in this paper61 See Panjaitan-Drioadisuryo and Cloud (1999) p 77562 See Grameen Bank (2004) 63 See Barnes (2001) p 8664 See Simanowitz and Walter (2002) p 16
15
of Grameen Bank borrowers move out of poverty every year65 Supposing Khandkerrsquos
findings were correct for all MFIs worldwide and the Microcredit Summit Campaign
achieved its goal of reaching 100 million of the poorest households with microcredit by
2005 then 25 million people (assuming an average family size of five) would leave
poverty every year66 Although this number would have to be adjusted in order take into
consideration the MFI clients who have crossed the poverty line already and of course
the experiences made in Bangladesh can not be transferred precisely to other countries
it still demonstrates the enormous effect that microcredit can have on assisting the
poorest to move out of poverty
Although a 1996 study of Hulme and Mosley states that providing microcredit can also
have a negative impact on the income of the poorest households67 these findings can
be considered as disproved by the recent bulk of evidence drawing favorable
conclusions68
33 Achievement of universal primary Education
The aim of the second MDG is to ensure that all children will be able to complete
primary school by 2015
Currently more than 100 million children most of them girls are not in school69
Besides school fees poor households often can not afford to send their children to
school because they need them to help in the family business
Microcredit programs mainly contribute to the second MDG by increasing families
income and therefore enabling parents to send their children to school Barnes Gaile
and Kibombo found that clients of an MFI in Uganda spent significantly more on
childrenrsquos education than non-clients70 and in Zambia Barnes showed that ongoing
participation in the Zambuko Trustrsquos program had a positive impact on the members
65 See Khandker (1998) p 5666 See Daley-Harris (2003) p 2467 See Hulme and Mosley (1996) p 180 et sqq 68 See Gibbons and Meehan (1998) p 13669 See UNICEF (2002) p 2270 See Barnes Gaile and Kibombo (2001) p 64
16
children staying in school71 In Bangladesh the probability of girls enrolling in school
increased by 19 percent for every 1 percent increase in Grameen Bank loans to female
clients For boys this number was even higher with the mean being 24 percent72
34 Promote gender Equality and empower Women
The aim of the third MDG is to eliminate the disparity in the ratios of girls to boys in
primary secondary and tertiary education in the ratio of literate females to males and to
increase the share of women in the labor market and in parliament73
At present the literacy rate for women is lower than for man all over the world
According to the Human Development Report 2004 the average female literacy rate as
a percentage of male literacy rate is 759 in developing countries and is as low as 37 in
Niger74 But women are not only discriminated against in education but also in access to
medical services and therefore have a higher mortality rate than man75 The worldwide
tendency for women to be underrepresented in the labor market and in the parliaments is
even more severe in developing countries76 Although several women have become
heads of state in various Asian countries (eg Bangladesh India and Indonesia) this is
probably due to them being wives or daughters of former respected male politicians
Since women have a higher repayment rate than man77 and also tend to invest increases
in income on the household and on their children rather than on themselves78 most
MFIs prefer female clients79 Therefore they empower women in many ways Often
MFIs not only encourage women to become involved in financial transactions for the
first time but also to become independent active members of the economy and to
acquire assets in their own names Cheston and Kuhn found that 68 percent of the
women participating in an MFI program in Nepal ldquohellip experienced an increase their
71 See Barnes (2001) p 8472 See Khandker (1998) p 4973 See World Bank (2001) p 2074 See UNDP (2004) pp 225 et sqq75 See Sen (2000) p 23276 See Sen (2000) pp 242 et sqq77 See Littlefield Morduch and Hashemi (2003) p 778 See Yunus (1998a) pp 116 et sqq79 According to the Microcredit Summit Campaign Report 79 or 37677080 of the poorest clients were women See Daley-Harris (2003) p 3
17
decision-making roles in the areas of family planning childrenrsquos marriage buying and
selling property and sending their daughters to school - all areas of decision making
traditionally dominated by menrdquo80 The program of the Lower Pra Rural Bank in Ghana
had an positive impact on womenrsquos participation in the community81 which is true as
well for the CRECER program in Bolivia82 In Bangladesh the Grameen Bank and the
Bangladesh Rural Advancement Committee (BRAC) the two biggest MFIs of the
country had a significant positive effect on womenrsquos empowerment measured through
eight different indicators83 After joining Grameen Bank only 21 percent of the female
members considered themselves as unemployed while this number was 50 percent
before joining84 According to the Grameen Bank website 93 percent of the Bankrsquos
shares are owned by their borrowers which elect the members of the board every three
years They also get familiar with the election process by more frequently voting for
representatives at the lower level of the organizational structure Partly because of this
experience they are more likely to run for public office In the 2003 local government
elections Grameen Bank members constituted 24 of the seats reserved for women
while they represent less than 10 of Bangladeshi adult female population85 Female
clients of MFIs from countries like the Philippines Bolivia and Nepal have reported
similar occurrences86
35 Reduce Child Mortality and improve Maternal Health
The aim of the fourth MDG is to reduce the under-five mortality rate by two-thirds
between 1990 and 2015 and the fifth MDG strives for a three quarter reduction in the
maternal mortality ratio by the same date
As has been stated above more than 10 million children are dying annually in the
developing world of mostly preventable causes with malnutrition playing a role in over
80 See Cheston and Kuhn (2002) p 1881 See MkNelly and Dunford (1998) p 5482 See MkNelly and Dunford (1999) p 7183 The eight different indicators are ldquofreedom of movement economic security ability to make small and larger independent purchases participation in important family decisions relative freedom from domination by the family political and legal awareness and participation in political campaigning and public protestsrdquo Hashemi and Schuler (1998) p 3684 See Holcombe (1995) p 5185 See Grameen Bank (2004)and CIA (2004)86 See Littlefield Morduch and Hashemi (2003) p 8
18
half of the childrsquos deaths and in over 50 countries child mortality rates are greater than
100 deaths per 1000 live births87 Maternal mortality is also a significant problem in the
developing world with more than 500000 women dying every year from pregnancy
related causes88
MFIs are mainly contributing to the these MDGs by increasing families income and
therefore enabling the households to afford better nutrition and medical services
Furthermore they are often linked with microinsurance or health education programs
In addition to what has been showed in chapter 31 Pitt Khandker and Millimet
estimate that a 10 percent increase in the loan size of a female borrower in Bangladesh
increases the arm circumference of their daughters by 6389 Smith and Jain found that
village banking in Ecuador had a positive effect on child diarrhea90 which is responsible
for 15 of child deaths91 Since Sen argues that an improved status of women within
the family reduces child mortality92 the empowerment of women through MFIs is also
contributing to this cause
Although no study has been conducted so far on the direct impact of microcredit on
maternal health it can be assumed that an overall improvement of access to medical
services reduces maternal mortality as well A study of the Morgan State University for
example suggests that microcredit has a positive effect on the prevalence of
contraceptives93 which leads to a decrease of unwanted pregnancies and therefore
reduces maternal death
36 Combat HIVAIDS Malaria and other diseases
The aim of the sixth MDG is to halt and begin to reverse by 2015 the spread of
HIVAIDS malaria and other major diseases and to assist children orphaned by HIV
87 See World Bank (2001) p 888 See WHO (2004) 89 See Pitt Khandker and Millimet (2003) p 11390 See Smith and Jain (1999) p 3791 See WHO (2001) 92 See Sen (2000) p 23593 See Amin et al (2001) p 1614
19
In 2003 29 million people died because of HIV and about 48 million became infected
the greatest number since AIDS was discovered 23 years ago94 This pandemic has lead
to a tremendous decrease in the life expectancy in the hardest hit countries Botswana
for example one of the richest and most democratic countries in Africa has a
HIVAIDS adult prevalence rate of 388 and a life expectancy at birth of less than 31
years95
Malaria not only causes more than one million deaths annually it leads also to 300 ndash
500 million clinical cases a year Both numbers have been steadily increasing over the
past two decades96 More than two million people a year are killed by tuberculosis
another global health problem This curable disease is estimated to cost poor
communities about $12 billion every year since even those who survive normally lose
more than 3 month of work time while recovering97
MFIs contribute to the sixth MDG in several ways By increasing clientrsquos income they
help households affected by HIV or other diseases to better cope with the situation
Besides spending more money on health services and nutrition MFI clients also tend to
be more able and willing to support AIDS orphans than non clients98 In addition to the
already stated increase in the use of contraceptives99 several innovative approaches to
deal with disease related crisis have also arisen This is of course necessary not only to
counteract the devastating effect the above discussed epidemics can have on MFI
clients but also to not put the viability of the respective institution at risk One option is
to integrate education services in the MFI programs and encourage clients to form
solidarity groups100 It has been shown that these services do not necessarily decrease
the effectiveness of the institutionsrsquo employees101 Another way is to strengthen the ties
to NGOs specialize in dealing with the respective disease Synergies gained through this
cooperation can help clients to better deal with the situation and in the end increase their
94 See UNAIDS (2004) p 2395 See CIA (2004)96 See World Bank (2001) p 1697 See World Bank (2001) p 1298 See Barnes (2001) p 6499 See also Kim et al (2002) p 18100 See Donahue and Sussman (1999) p A 14101 See Donahue Kabbucho and Osinde (2001) p 25
20
repayment rates Various MFIs also have introduced loan and health insurance products
or cultivated linkages with organizations doing so102
It has to be stated that despite the benefits MFIs can provide to people effected by
HIVAIDS or other diseases microcredit can also be a burden for those who are already
chronically ill These people can still benefit through loans provided to members of the
family or the community or through one of the other services mentioned above
37 Ensure environmental Sustainability
The aims of the seventh MDG are to support and promote the principles of sustainable
development and put them into action and to improve the lives of slum dwellers and
people without sustainable access to safe drinking water and sanitation
Today climate change is considered as the major environmental problem103 The
Intergovernmental Panel on Climate Change (IPCC) states that human activities
contribute to most of the 06 degC increase in global average temperature over the 20th
century and the predicted increase of another 14 to 58 degC between 1990 and 2100104
Emission of carbon from fossil fuel is reported to have the dominant influence on this
development While the total emission was 16 billion tons in 1950 it was already 65
billion tons in 2000 and is expected to continue to grow105 This development would
lead to a rise in the average sea level of between 9 and 88 centimeters during the next
century106 Furthermore it is predicted that global warming increases the risk of extreme
events like cyclones or floods leads to an increase in the number of people infected by
diseases like malaria and decreases the potential crop harvest and water availability
especially in developing countries107 In 2000 already 11 billion people lacked access to
clean drinking water and 24 billion to basic sanitation108
102 See Barnes (2001) p 40 Barnes Gaile and Kibombo (2001) p 13 and Grameen Bank (2004)103 See Gardner (2002) p 5104 See IPCC (2001) pp 2 et sqq105 Worldwatch Institute (2002) p 52 et sqq106 See IPCC (2001) p 16107 See Dunn and Flavin p 29108 See UNFPA (2004) p 18
21
MFIs contribute to achieving the seventh MDG in several ways By providing loans for
the purchase of renewable energy technologies they help people in developing
countries to increase their per capita energy consumption without increasing the carbon
dioxide emission In a 2003 survey of 140 MFIs from 80 different countries 21 said
they provide credits for solar home systems and another 19 stated they are interested in
becoming engaged in this business109 While Grameen Shakti a rural energy service
company cooperating with the Grameen Bank in Bangladesh has already installed more
than 23000 solar home systems110 a 2000 World Bank study reports twelve projects
providing solar home systems to rural households with a target of 500000
installations111 It has also been suggested that MFIs should raise environmental
awareness among their clients112 but so far no data is available on how staff can cope
with this additional task Many MFIs also provide loans for improvements in sanitation
and the water supply of their clients Varley gives several examples from Africa Asia
and Latin America on how microcredit not only has helped to invest in rainwater
collection systems but also how it has enabled households to increase their water
supply through community water associations113 In addition many MFIs provide credit
for the construction of sanitary latrines114 The situation of slum dwellers is also
positively effected by MFIs Directly through their services in poor urban communities
and indirectly by creating jobs in rural areas and therefore easing the pressure on urban
labor markets
38 Develop a global Partnership for Development
The eight MDG is about the means to achieve the other seven MDGs It calls for all
players involved in the endeavor of development and poverty eradication to work as
partners in a global context
Again MFIs are contributing to the eight MDG in many ways This is occurring through
international networks that provide funding and technical assistance through internet
information portals and specialized journals through social and for profit investors and
109 See Wimmer and Barua (2004) p 174110 Barua (2004) 111 See Martinot and Cabraal (2000) p 6112 See Pallen (1997) p 11 Lal (nd)113 See Varley (1995) pp 39 et sqq114 See Jalvaani (1999) pp 1 et sqq Varley (1995) pp 39 et sqq
22
specialized rating agencies The Bangladesh-based Grameen Trust is one of around 30
networks in operation Besides collaborating with over 200 MFIs around the world it
has directly operated three projects in Afghanistan Kosovo and Myanmar115 While the
ACCION network serves almost 12 million active clients in 19 countries throughout
America and sub-Saharan Africa116 FINCArsquos network operates in three different
continents where it serves more than 200000 customers117 In November 1997 the
MicroBanking Bulletin (MBB) was first published by the microfinance program at the
Economic Institute at the University of Colorado118 Its aim is to develop a database on
the financial performance of MFIs from all over the world which is now available
through the Mix Market an internet portal that also provides information about more
than 300 MFIs investors donor institutions and other related development
organizations119 Two years later the Marriott School at Brigham Young University
started to publish the Journal of Microfinance which has an editorial board of
microfinance experts from all over the world and offers the latest research on this
topic120 In the late 1990s a number of companies became attracted by the microfinance
market and started to invest in MFIs The German based Internationale Mikro
Investitionen Aktiengesellschaft (IMI) for example has already invested more than euro46
million in 19 MFIs in four different continents and plans to invest another euro27 million
before October 2004121 BlueOrchard Finance a microfinance investment consultancy
has channeled more than $60 million worth of private capital to some 40 MFIs
worldwide through investment funds and bond issues122 Big commercial banks like
Citigroup Deutsche Bank and ABN Amro also started to get involved in the
microfinance sector although this is mainly still perceived as a public relation activity
and not as a for-profit investment123 There are also several rating agencies specializing
in MFIs Dependent on their rating these institutions can help MFIs to receive money
from donors or investors Four of the most prominent rating agencies are PlanetFinance
115 See Grameen Trust (nd)116 See ACCION (nd)117 See FINCA (nd)118 See MicroBanking Bulletin (1997) p 5119 See The Mix (2004)120 See Woodworth and Woller (1999) p 6121 See IMI (2004)122 See BlueOrchard (2004b) p 3123 See Busch and Kort (2004) p 8 Fischer (2003) p 6
23
with headquarters in France M-Cril based in India Microfinanza in Italy and
MicroRate with offices in the USA and South Africa124
124 See Microfinance Rating and Assessment Fund (2004)
24
4 Microcredit Outreach
41 The Demand for Microcredit
Although it has been shown that microcredit is one of the most effective poverty
eradication tools that it is considered a human right by some of its advocates125 and it
can contribute considerably to the development of the financial sector in developing
countries an enormous gap still exists between supply and demand for microcredit
Estimates on the demand for microcredit vary greatly While USAID estimates the
number of potential microfinance clients is between 100 and 200 million126 the
Microcredit Summit Campaign states the total demand is more than 234 million
people127 CGAP recognizes some 500 million micro-entrepreneurs who have the
potential to become customers of MFIs128
Marguerite Robinson calculates the demand as follows ldquoAssuming five people to a
household among the 45 billion people living in low- and lower-middle-income
economies in 1999 (World Bank World Development Report 20002001) there are 900
million households in those economies If estimating conservatively we assume that
informal commercial moneylenders supply credit to 30 percent of these households at
least once a year this would mean that there are 270 million households borrowing
from informal moneylenders in a year Undoubtedly however many of these
households borrow multiple times within a yearrdquo129 Although this is a very rough
estimate assuming big differences in demand for microcredit in different countries the
number seems to be the most meaningful In contrast to the estimate of the Microcredit
Summit Campaign it does not include every single household living on less than $1 a
day but according to the definition presented in chapter 1 it counts everyone who has
no regular access to traditional financial institutions but demands such services
Obviously not all people who draw on moneylenders have financial needs that could be
matched through MFIs On the other hand interest rates charged by moneylenders tend
125 See Yunus (1998b) 126 See Christen et al (1995) p 15127 See Daley Harris (2003) p 22 128 See Robinson (2001) p 26129 See Robinson (2001) p 215
25
to be considerably higher than those of MFIs The former normally charge effective
monthly rates between ten and several hundred percent per month the latter generally
charge between 15 and five percent which enables them to attract additional clients130
42 The Supply of Microcredit
In spite of the impressive growth of MFIs around the world the demand for microcredit
is far from being met and this it is not likely to change in the near future The
Microcredit Summit Campaign reported that by the end of 2002 67606080 clients131
were reached through MFIs and that this number has increased by almost 40 percent
annually for the last five years132 It is likely that this tremendous speed of growth is at
least partly due to including MFIs which have not been reporting to the Campaign from
its start in 1997 although they have already existed at that time These institutions
contributed 22 percent to the growth in poorest clients in 2000 578 percent in 2001 and
338 percent in 2002 The growth of the poorest clients increased at least party because
of an expanded definition of the term ldquopoorestrdquo133 Since the contribution of MFIs
which previously have not been considered can be expected to decrease dramatically
the growth rate as stated by the Microcredit Summit Campaign can not be used to
predict the future development of the microfinance sector Another factor likely to slow
down the growth is the concentration of microfinance activities in some Asian countries
where almost 90 percent of the poorest microfinance clients live today134 Even if one
takes into consideration the relative size of Asiarsquos population and the fact that many
MFI customers in Latin America are relatively better off and therefore are not included
in this numbers the coverage of this part of the world far exceeds the others In
Bangladesh for example the microfinance market is close to saturation More than
eleven million households were served by several hundred MFIs in 2001135 Among
them are Grameen Bank and BRAC two of the best known MFIs in the world both
providing their services to more than three million customers With an average
household size of five it can be assumed that in Bangladesh the number of people
130 See Gibbons and Meehan (1999) pp 144 et sqq131 41594778 of them belonged to the poorest before they took their first loan The relative numbers in the following are for these poorest clients only since no other current data was available It can be assumed though that this works as a good proxy for the total number of clients 132 See Daley Harris (2003) p 3133 See Daley Harris (2003) p 17134 See Daley Harris (2003) p 21135 See Ahmed (2003)
26
benefiting from microcredit already surpasses the number of people living below the
poverty line which is estimated to be slightly higher than 50 million136 Therefore
Bangladesh will not contribute to the growth of the microfinance sector as much as it
has done in previous years This is also true for Vietnam Thailand and to a lesser
extent Indonesia Eight of the nine MFIs serving more than one million clients are based
in these countries while the ninth is based in India where due to its one billion
inhabitants the microfinance market is still far from saturation137 In contrast the
supply in Brazil meets less than two percent of the demand which is estimated to be
about 58 million potential clients138 For these reasons greater amount of future growth
must come from smaller or new MFIs in Latin America India China and especially
Africa where almost 30 percent of the worldrsquos poorest live139
43 Meeting the Demand
To fill the gap between the demand and supply for microcredit tremendous investments
are necessary to increase the loan funds of MFIs and build up their capacity through
upgrading existing institutions or building new ones Again estimates on how much
capital is needed vary greatly with the highest being at more than $300 billion140
In 1997 the Microcredit Summit Campaign estimated that $216 billion would be
needed to achieve their goal of providing microcredit to 100 million of the poorest
households This was calculated in the following way Since some 8 million people
already received microcredit in 1997 another 92 million needed to be reached
Assuming $200 ($150 for loan fund and $50 for capacity building) would be needed per
person for 88 million people in developing countries and $1000 ($500 for loan fund and
$500 for capacity building) would be needed for 4 million people in industrialized
countries the capital required ends up to be $216 billion141 For several reasons this
136 See CIA (2004)137 These institutions are The Grameen Bank BRAC Proshika and the Association for Social Advancement (ASA) in Bangladesh the Vietnam Bank for Agriculture and Rural Development (VBARD) and the Vietnam Bank for the Poor (VBA) in Vietnam BRI in Indonesia Bank for Agriculture and Agricultural Co-operatives (BAAC) in Thailand the National Bank for Agriculture and Rural Development (NABARD) in India See Ahmed (nd) p 1 Llanto (nd) p 337138 See Mezzera (2002) p 23139 See See Chen and Ravallion (2004) p 29140 See Clear Profit (2004) Prisma (2002)141 See The Microcredit Summit (1997)
27
number is not qualified to predict the total amount of capital needed to meet the demand
for microcredit On the one hand it focuses mainly on the low end of the market and
therefore underestimates the average loan fund needed On the other hand it does not
take the increasing capital demand from established MFIs into account A survey of 119
MFIs found that the average loan size to increased from $406 in 2002 to $498 in
2003142 This is mainly due to the fact that MFI clients once they have paid back their
loans usually demand larger ones for the continual development of their businesses
and therefore further increase the demand for capital of established MFIs The Grameen
Bank for example has a ceiling on its loans which increases or decreases depending on
the borrowers performance regarding repayments and savings143 While the maximum
amount for the first loan is fixed at approximately $75144 the largest loan disbursed so
far was $17195145 Thus if one estimates that by now 100 million people are borrowing
from MFIs146 another 170 million need to be reached to meet the estimated demand
Assuming an average of $600 ($400 for loan fund and $200 for capacity building) is
needed for every new client and another $200 is needed for every existing client to meet
the demand for larger loans a total of $122 billion is required This rough estimate
helps to convey the approximate amount of capital needed to meet the demand for
microcredit
So far the demand for funds is being partly met by donors which annually provide
between $500 million and $1 billion147 and through the mobilization of local savings
Obviously the amount of money provided by donors will not be able to meet the capital
demand for microcredit in the short term The mobilization of savings on the other hand
has been extremely successful in some cases with BRI probably being the most
prominent example After adapting commercial principals in October 1984 BRI was
able to raise its deposits from $161060 to more than $32 billion in 2003 which equals
almost two times its current loan portfolio148 Many other MFIs like BDB in Indonesia
142 Own calculations Without BRI the numbers would be $343 and $409 See Appendix 1143 See Grameen Bank (2003) p 13144 The accurate amount is 5000 Taka See Interview with Shaw Newaz145 Grameen Bank (2004)146 According to the data provided by the Daley Harris (2003) an annual increase in MFI clients ofapproximately 25 percent from 31122002 till the 3092004 would be needed to reach 100 million clients by now This rated is considerably below the average of the previous five years (38 percent) Therefore it can be assumed as realistic despite the growth hindering factors presented above147 See CGAP (2003) p 8148 See Robinson (2002) p 273 Mix Market (2004)
28
XacBank in Mongolia the Equity Building Society in Kenya or the Centenary Rural
Development Bank in Uganda also have managed to cover their loan portfolio fully
through internally mobilized resources149 The Grameen Bank is also expected to do so
in the first half of 2005150 In addition to raising much needed capital for on-lending the
provision of saving services can deliver notable social benefits itself151
Despite these impressive achievements even the combination of donor money and local
savings at their current levels will not be able to provide the capital needed to continue
the rapid growth of the microfinance sector Especially in their early years MFIs rely on
outside funding BRI for example needed six years before the amount of locally
mobilized savings surpassed the total amount of outstanding loans During this time
expenses and the loan portfolio were covered through a government grant worth $20
million and two World Bank loans of $5 and $97 million respectively152 It also
benefited from a network of more than 3600 branches which were established
throughout the country during the 1970s and early 80s in order to provide government
subsidized credit in rural areas153
The Grameen Bank also widely known as a best practice MFI has received about $175
million in direct and indirect subsidies between 1985 and 1996154 and continues to rely
on outside funding at below market interest rates This is made possible either through
special loans from the Bangladesh Bank or through offering bonds guaranteed by the
Bangladesh government155 - an option most MFIs do not have BDB might be one of the
very few examples which were able to finance their activities through savings and
commercial loans from the start but its outreach did not reach a large scale nor did it
serve the low end of the market In 2000 after 30 years of operation BDB provides
credit to only 10417 clients with an average loan balance of more than $5000156
approximately eight times the countries GDP per capita157
149 See Mix Market (2004)150 See Grameen Bank (2004)151 See Robinson (2001) pp 263 et sqq152 See Seibel and Schmidt (2000) p 4153 See Robinson (2002) p 180154 See Morduch (1999b) p 8155 See Morduch (1999ba) p 25 et sqq156 See Robinson (2002) p 387157 See CIA (2004)
29
Another problem keeping many MFIs from collecting savings is that they do not want
to become a regulated financial institution or do not meet the criteria in their respective
country and therefore they are simply not allowed to mobilize savings from the public
In summary the examples and numbers presented in this chapter support the argument
that the amount of capital that can be raised through donors and locally mobilized
savings is not enough for continuous rapid growth of the microfinance sector If this
lack of capital is not met through other sources the microfinance sector will fail to
contribute its full potential to the achievement of the MDGs
44 Microfinance and the Capital Markets
Regardless of whether the amount of capital needed for the development of the
microfinance sector is $20 or $300 billion it represents only a tiny fraction of the
worldwide capital markets which are estimated at $30 trillion158 Therefore if the
microfinance industry were able to tap the financial markets it would be able to grow
much faster and soon serve the millions of micro-entrepreneurs which currently can not
develop theirs businesses because of capital constrains Another advantage would be
that scarce donor money currently used for the development of the microfinance sector
could be used for other projects that do not have the potential to draw money from
commercial sources This view is shared by Michael Chu the former CEO of ACCION
who made the following statement in 1998 ldquoMicrofinance today stands at the threshold
of its next major stage the connection with the capital marketsrdquo159 Many attempts have
been made since that time Successful MFIs like BancoSol in Bolivia further
strengthened their ties to the capital markets which in some cases already provide the
majority of their funding160 Microfinance investment advisors like BlueOrchard
Finance have become middlemen for MFIs and the financial markets Nevertheless
these links are still far from reaching major scale Currently only approximately 20
percent of MFIs funding comes from commercial sources161 and the biggest bond issue
dedicated to fund MFIs totals only $40 million In addition these funds mainly end up
158 See Brynjolfsson (2004) 159 Chu (1998) quoted in Robinson (2001) p 23160 See Robinson (2001) p 69161 See Dominiceacute (2004)
30
in established institutions in Latin America or Eastern Europe162 while smaller
organizations only benefit indirectly if at all
162 See Clear Profit (2004) IMI (2004)
31
5 Credit Rationing
Until recently the predominant answer to why commercial banks or venture capital
companies did not invest in the microfinance sector was that the poor are not bankable
Besides lacking education and therefore not being able to deal with formal financial
institutions they were viewed as bad credit risk who were unable to invest the borrowed
money in a way that would allow them to repay the loan and interest at a commercial
rate163 Another reason that kept attention away from the idea of providing financial
services to low income people was the belief that informal moneylenders already met
this demand These skeptics felt affirmed through the poor performance of subsidized
credit programs as described in chapter 22 Although it is true that moneylenders
serve a huge number of people in the developing world they more often than not charge
usury interest rates of up to 20000 percent per month164 While the argument that poor
people are not able to participate in the formal financial market can be overcome by
adapting the services accordingly165 the claim of low returns on their investments is not
only proved wrong by empirical evidence but also contradicts economic theory as will
be shown in chapter 53
51 The imperfect Information Paradigm
A more elaborate explanation for the short supply of financial services to low income
people that can be derived from the imperfect information paradigm based
predominantly on the works of Akerlof166 and Stiglitz and Weiss167 After giving a brief
summary of their argument an adaptation of their findings to the microfinance market
will be presented and subsequently it will be shown how their conclusions can be
overcome
Behind the imperfect information paradigm lies the theory of asymmetric information
which simply states that if two parties conduct a transaction one is likely to have more
163 See Ghatak (1983) p 21 et sqq Yunus (1998) p 102 et sqq Robinson (2001) p 35 et sqq164 See Robinson (2001) p 17165 See Seibel (2003b) p 2 BRAC (2003) pp 15et sqq Yunus (1998) pp 151 et sqq 166 See Akerlof (1970) pp 488 et sqq167 See Stiglitz and Weiss (1981) pp 393 et sqq
32
information than the other and is trying to use that for its own advantage168 Applied to
the banking sector this means that a person applying for credit can better judge the
likelihood of repaying the loan than the bank This is because the borrower has better
knowledge of the market she wants to invest in her skills and her willingness to repay
Moreover the bank might not be able to observe if the borrower uses the loan for the
agreed purpose These occurrences can lead to what is known as adverse selection and
moral hazard In this case adverse selection refers to the problem that banks might
attract borrowers with a low probability of repayment if they can not distinguish
between high and low risk loan applicants Moral hazard occurs after the provision of
the loan when the borrower spends the money on a purpose different to the prescribed
purpose and therefore lowers the probability of repayment This can happen eg by
investing in a more risky project or through spending the money on consumption If the
bank is not able to find a cost effective way to avoid these problems it might raise its
interest rate in order to compensate for the increased risk
Figure 1 Expected Bank Return and the Interest Rate
Source Stiglitz and Weiss (1981) p 394
Since this might discourage low risk borrowers from applying for credit and encourage
borrowers who continue to take loans to invest in riskier projects the share of high risk
168 See Neus (1998) p 85 et sqq
INTEREST RATEI
EX
PE
CT
ED
RE
TU
RN
TO
TH
E B
AN
K
33
borrowers could increase and therefore reinforce the problems stated above Thus
increasing the interest rate beyond a certain point actually leads to a decrease in the
expected return to the lender This context is illustrated in figure 1 with I being the
interest rate which maximizes the expected returns to the bank Obviously the bank
would charge the interest rate I in order to maximize its expected return However this
price for capital was not determined through supply and demand as economic theory
would predict It is conceivable that at the interest rate I the demand for credit exceeds
the supply but even if loan applicants would offer to pay a higher interest rate the bank
would refuse because it associates such a loan with high risk As a result credit might
be rationed169
52 Adaptation to the Microfinance Sector
Through some adaptations this model can also help to explain the lack of funds
provided to low income people In the original model of Stiglitz and Weiss several
assumptions have been made that need to be suspended in order to compare the credit
markets for low and high income people and give an explanation why the latter is
widely neglected by institutional investors
Evidently the assumptions that the amount borrowed is equal for each loan applicant
and that transaction costs170 need not to be taken into account171 are not suitable for this
context While the average loan size of MFI customers is much smaller than that of
clients from traditional banks the transaction costs as a share of the loan are
considerably higher because the lenderrsquos costs for conscientious processing a credit
applications are only slightly smaller for a $50 loan than for a $100000 or a
$10000000 loan
In figure 2 the R(I)large curve represents the return to the bank for large loans with
regard to the interest rate I and the R(I)small curve describes the same correlation for
small loans It is shifts downwards to reflect the assertion that the imperfect information
169 See Stiglitz and Weiss (1981) p 394170 In this paper the term bdquotransaction costsldquo refers to the operating expense ratio as defined by MicroRate It ldquois calculated by dividing all expenses related to the operation of the institution (including all the administrative and salary expenses depreciation and board fees) by the period average gross portfoliordquo See MicroRate and Inter-American Development Bank (IADB) (2003) p 16 171 See Stiglitz and Weiss (1981) p 396
34
paradigm has a more severe effect on poor people than on the better off They are
expected to have less profitable investment opportunities at their disposal172 and
therefore are more likely to invest in riskier projects which increase the probability of
default and hence decrease the expected return to the bank Additionally one might
expect poor people to be more likely than others to spend borrowed money on
consumption instead of an income generating activity particularly if a crisis arises It
seems understandable that food or urgently needed medicine are given priority over
repaying a loan
The second shift downwards is due to transaction costs As stated above they are
relatively higher for smaller loans Obviously transaction costs are incurred in the
provision of a large loan as well but since they are much smaller with regard to the loan
amount they are not included in the diagram for reasons of clarity
Figure 2 The extended Model
Source Own diagram adapted from Stiglitz and Weiss (1981) p 394
172 See Khandker (1998) p 8
INTEREST RATE I
SmallLoans
LargeLoans
Transaction costs
Lack of investment opportunities
R(I)large
R(I)small
EX
PE
CT
ED
RE
TU
RN
TO
TH
E B
AN
K
35
53 Overcoming Credit Rationing for the Microfinance Sector
If the conclusions in chapter 51 hold it is rational for a profit maximizing investor to
neglect the microfinance sector as long as no surplus funds in the market for large loans
exist This finding can help to explain the small amount of money provided to the
microfinance sector from commercial investors On the other hand it has to be stated
that this theory is reflexive as defined by Soros173 It not only explains but also forms
reality since it has the potential to reinforce the view of potential investors that
microfinance is a less profitable business174 Therefore demonstrating under which
conditions microfinance can be profitable and in some cases be more profitable than
traditional businesses is of crucial importance
To provide a fairer view of the microfinance sector a further assumption of the Stiglitz
and Weiss model that needs to be suspended is that all investments made by the
borrowers have the same expected return175 As stated above this contradicts economic
theory which claims ceteris paribus capital productivity decreases while the amount of
fixed capital increases In combination with a low capital endowment micro-enterprises
are usually faced with an excess supply of unskilled labor especially in developing
countries176 Hence small enterprises use far less capital per employee than big business
and therefore their marginal productivity of capital is much higher177 This is intuitive if
one imagines an economic actor who wants to invest several packages of capital
Obviously she would invest the first package where she expects the highest return the
second package where she expects the second highest return and so on Each additional
investment opportunity would lead to lower or at best equal returns178 While this
simplified example has limitations it demonstrates how the marginal productivity of
capital can diminish Although it might actually increase until a certain point179 this can
be expected to be so low in this context that it has no influence on the correlation as
shown in figure 2
173 See Soros (1998) pp 14 et sqq174 See Goodwin-Groen (1999) p 8175 See Stiglitz and Weiss (1981) p 395176 See Perkins et al (2001) pp 95 et sqq177 See Tschach (2000) p 8178 See Rosenberg (2002) p 11179 See Rechard G Lipsey (1979) pp 211 et sqq
36
Figure 3 Marginal Productivity of Capital
Source Dornbusch and Fischer (1995) p 406
Even if good investment opportunities for poor people exist the question remains if it is
possible to distinguish between high and low risk borrowers The problem of adverse
selection is overcome in a cost effective way in many MFIs180 For the better off poor
for example institutions like BRI base their decision on whether or not to approve a
loan by assessing the repayment ability of potential borrowers from their current income
flows and not from the uncertain returns generated by the loan181 Additionally
collateral is used in some cases to attract low risk borrowers182 In contrast to
industrialized countries this is usually not done to cover the potential losses of the
lender but to punish the defaulter and therefore increase her willingness to repay183
Obviously this does not always work for the poorest since they often neither posses any
goods that could work as collateral nor do they have sufficient earnings prior to
obtaining a loan for starting an income generating activity Here the so called group-
lending model can help to identify creditworthy borrowers The most prominent
institution using this approach is the Grameen Bank which only provides credit to
180 See Farrington (2000) p 20181 See Robinson (2001) p 80 Robinson (2002) p 238182 See Bester (1985) p 850 et sqq183 See Schmidt and Tschach (2001) p 15 Robinson (2002) p 244
FIXED CAPITAL 0
MA
RG
INA
L P
RO
DU
CT
IVIT
Y
37
members of a group of five These groups are formed by their members without
interference of the Grameen Bank Although in this particular case no joint liability
exists for the members of the group nobody can receive a new loan if another member
of the group fails to repay on time184 Therefore the group formation work as a
screening process Since the borrowers do not want to risk their ability to obtain further
loans they carefully select with whom to form a group Usually the members know
each other for a long period of time and therefore they can make a meaningful judgment
of each othersrsquo ability to repay the loan Other MFIs even require the members of a
group to mutually guarantee each othersrsquo loans185 While this might further increase
borrowersrsquo efforts to search for trustworthy group members it might also keep potential
borrowers from applying for a loan since she does not want be held responsible for
defaulting members This mechanism enables MFIs to partly pass on the transaction
costs related to the selection of low risk borrowers to the borrowers themselves186
Many MFIs have also largely overcome the problem of moral hazard by creating
incentives to ensure a high repayment rate even among the poorest In some cases their
customers go hungry in order to pay back their loan even though no legal action would
be taken against them if they would refuse to do so187 One way to achieve this is to
build up peer pressure through the formation of groups as described above188 Another
and probably the most important is to limit access to future loans to those borrowers
who repay on time The demand for successive loans is extremely high In a 1996
survey 98 percent of BRI borrowers planed to apply for another loan189 and in 1993
less than 30 percent of Grameen Bank loans went to first time borrowers190 Especially
the poorest highly value the option to reborrow191 and many MFIs see this as their
primary incentive to ensure repayment192 According to Schmidt and Tschach ldquothe net
present value of future access to credit works out to be roughly half the value of the
economic advantage to be gained from the intended non-repaymentrdquo193 This can also
184 See Yunus (1998) p 135185 See Schmidt and Zeitinger (1997) p 6186 See Stiglitz (1990) p353187 Own observation at the Grameen Bank in Bangladesh (2003)188 See Hoff and Stiglitz (1990) p 249189 See Robinson (2002) p 251190 See Khandker Khalily and Khan (1995) p 93191 See Gibbons (2000) p 15 Hashemi and Schuler (1997) p 43192 See Gibbons and Meehan (1999) p 160193 See Schmidt and Tschach (2001) p 16
38
explain the occurrence of a drop in the repayment rate once a MFI is no longer seen as
viable and therefore is not expected to provide loans in the future194
With the help of the described mechanisms MFIs around the world are able to keep
repayment rates high A survey of 69 MFIs from 36 different countries each serving
more than 10000 clients in 2002 found the portfolio at risk (PAR)195 varied between
zero and 231 percent While the average was 36 percent the median was found to be
229 percent196 One of the MFIs included in this sample is BRIs whorsquos 12-month loss
ratio has never exceeded five percent since the start of its transformation in 1984 and
from 1997 to 1998 the ratio actually fell from 22 to 194 percent197 The latter deserves
special attention because the Asian financial crisis reached its peak at that time with
Indonesia being hardest hit as illustrated by a statement from The Economist in July
1998 Even with the fierce competition from its neighbors Indonesia would probably
walk away with the prize for Asias most desperate banking systemrdquo198
The findings that MFIs can adapt their services to low income people in order to ensure
a high repayment rate and that poor people do not lack profitable investment
opportunities are illustrated in figure 4 From this diagram it can be seen that under the
new assumptions the interest rate at which the bank maximizes its return differs for
large (I(l)) and small loans (I(s)) According to the assumption that micro-
entrepreneurs can realize a higher return on their investments the bank can charge them
a higher rate of interest without bearing an increased risk Nevertheless in this example
the bank would still serve the market for large loans first because of the higher
transaction costs for smaller loans
The view as described in figure 4 is shared among most traditional banks and investors
in industrialized as well as in developing countries In addition to neglecting the
possibility of generating profits by offering microcredit themselves199 they also hesitate
to lend to MFIs because they consider their business too risky
194 See Schreiner (1997) p 64195 ldquoPAR shows the real risk of the portfolio by comparing outstanding loan balances for loans with atleast one late payment to the outstanding loan portfoliordquo Gross and de Silva (2002) p 22196 Own calculations See Appendix 2197 See Seibel (2000) p 11198 The Economist (1998) pp 92 et sqq199 Busch and Kort (2004) p 8
39
Figure 4 The extended Model
Source Own diagram adapted from Stiglitz and Weiss (1981) p 394 Tschach (2000)
p 17
This attitude can be observed by comparing the ratio of equity to liabilities which is
considerably higher for MFIs than for conventional banks200 When it comes to MFI
start-ups and those MFIs serving the low end market in remote areas even experienced
microfinance practitioners are skeptical if interest rates that fully recover all costs can
be charged201
Theoretically there are two ways to adjust this model to arrive at a conclusion which is
more favorable with regard to the profitability of microcredit One is to cut the
transaction costs and therefore reduce the downward shift of the R(I)small curve the
other is to allow the bank to further raise the interest rate without experiencing a
decrease in its return This means to increase I(s) and the respective rate of return
While in 2000 Tschach stated that transaction costs vary between 10 and 20 percent for
loans provided through the group lending model and between 15 and 30 percent for
200 See MicroRate and IADB (2003) p 30201 See Volkery (2004) p 33 Gibbons (2000) p 15 Gibbons and Meehan (2002) p 29 Goodwin-Groen (1999) p 8
INTEREST RATE I(l)
SmallLoans
LargeLoans
Transaction costs
I(s)
R(i)large
R(i)small
EX
PE
CT
ED
RE
TU
RN
TO
TH
E B
AN
K
40
individual loans202 it was recommended in 1999 that MFIs should target a range
between 15 and 25 percent203 Some best practices on the other hand have already
achieved single digit numbers Currently BDB might be the most efficient MFI in the
world with transaction costs at just 47 percent in 2001204 Even though the low costs of
BDB have to be acknowledged its achievement has to be put in perspective As stated
above with an average loan balance of more than $5000 it does not serve the low end
market In addition it works in an environment with a high population density which
means that it can reach a relatively large group of borrowers per branch This is a
comparative advantage many Asian MFIs enjoy as can be illustrated by comparing
Bangladesh and Bolivia Both countries are at the forefront of the development of
microfinance in their respective continent but while in Bangladesh more than 1000
people are living per square kilometer the average for Bolivia is only eight205
Therefore it is consistent that the most efficient MFI in Latin America Fondo
Financiero Privado para el Fomento a Iniciativas Economicas has transaction costs of
114 percent206 With an average loan size greater than the annual GDP per Capita this
institution also does not serve the low end market207
Despite the impressive efficiency gains in the described examples most MFIs are far
from achieving these numbers and many are unlikely to reach them due to the
environment within which they work A survey of 67 MFIs from 31 countries found the
average transactions costs in 2002 to be 279 percent with a median of 206 percent208
However even if these institutions were to increase their efficiency to best practice
standards their transaction costs would still be significantly higher than those of
traditional banks providing much larger loans For these banks the respective costs vary
in a range between 05 and 3 percent209 According to this argument charging interest
rates considerably higher than conventional banks is the only way for MFIs to generate
higher returns and hence successfully compete for capital
202 See Tschach (2000) pp 100 et sqq203 See Gibbons and Meehan (1999) p 149204 See M-Cril (2001b) p 4205 See CIA (2004)206 See MicroRate (2004)207 In this paper the term ldquolow endrdquo refers to the definition of the MBB (2003) p 54 Loans worth less than 20 percent of the respective countryrsquos GDP per capita are described that way 208 Own calculations See Appendix 3209 See M-Cril (2004a) p 16
41
6 Interest Rates
61 Setting the right Interest Rate
Before addressing the questions to what extend MFIs can raise their interest rates
without putting the repayment rate or the social benefits of their customers at risk a
basic model will be presented This model will illustrate how a MFI should set their
rates in order to not only cover their costs but also to generate an appropriate profit to
finance further growth and attract additional capital
In 2002 CGAP revised its 1996 paper ldquoMicrocredit Interest Ratesrdquo210 which outlines
the standard method of setting sustainable interest rates for commercially oriented
MFIs According to this model the annual effective interest rate (I) should be calculated
as shown below
(1) I = LL
IIKCFLLTA
minusminus+++
1
With each variable being a decimal fraction of the average outstanding loan portfolio
whereby TA stands for the transaction costs as described above LL represents the
annual loan loss and II stands for investment income eg on liquid assets The cost of
funds (CF) consist of the interest and administrative costs needed to obtain deposits and
commercial loans as well as of the imputed costs on equity due to inflation K stands for
the capitalization rate which represents the net real profit Keeping this rate high is
important to finance the future growth of the loan portfolio This can be either done
through investors attracted by high profitability or through borrowing For the latter an
increase in equity is inevitable since it is required as a safety cushion by lenders
Since this model ignores the timing of cash flows and does not take taxes into account
it has to be regarded as fairly imprecise and hence should not be used for business
planning Nevertheless it can be used for an approximation of the interest rate that a
MFI would need to charge to provide its services as planned In the following I will
210 See Rosenberg (2002) pp 1 et sqq
42
apply this model on a fictitious MFI working in a rural area of Latin America with low
end customers In this setting it seems realistic to estimate transaction costs of 35
percent and loan loss rate of two percent211 If funds were borrowed at commercial
terms their costs can be assumed to equal at least 15 percent of the average outstanding
loan portfolio212 Estimating the capitalization rate is more challenging First the
targeted portfolio growth rate is set at 75 percent This is slightly below the 751 percent
average annual portfolio growth between 2000 and 2002 found by a survey of 25
different MFIs based in Central and South America213 If the extend to which the MFI
can leverage stays constant the loan portfolios growth would be limited by the growth
rate of the equity To express the capital needed for this growth as a share of the loan
portfolio it is necessary to estimate the ratio between the equity and the outstanding
loan amount According to the survey mentioned above the loan portfolios of the 25
Latin American MFIs equal on average 215 times their equity214 With this number the
capital needed to increase the equity by 75 percent would corresponds to approximately
35 percent of outstanding loan amount (075215) Finally the investment income has to
be estimated Since liquid assets that are available short term do not generate high
returns say five percent it does not seem advisable for the MFI to hold more than a
quarter of its loan portfolio in this form Hence the profit generated in this way would
equal 125 percent of the outstanding loan amount Using these numbers the equation to
calculate the annual effective interest rate reads as follows
(2) I = LL
IIKCFLLTA
minusminus+++
1 =
0201
01250350150020350
minusminus+++
= 0875
As a result the MFI would need to charge an annual effective interest rate of
approximately 875 percent on its loans in order to sustainable provide its services and
finance its growth without depending on donor money This rate might decrease once
the MFI matures the growth slows down and cheaper funds become available but it
will stay significantly higher than any rate charged by conventional banks
211 MicroRate and IADB (2004) pp 6 and 16212 See MicroRate and IADB (2004) p 616 and 28213 Own calculation See Appendix 4214 Own calculations See Appendix 5
43
62 Can Micro-Entrepreneurs bear these Rates
Although most MFIs charge rates significantly below 875 percent many critics have
strenuously argued against any rates exceeding those of traditional banks Rosanna
Barbero of Oxfam labeled an interest rate of 52 percent charged by a Cambodian MFI
ldquoludicrous evil and disgusting and stated that ldquo[n]o business in the world can make a
profit at these interest ratesldquo215 The former finance minister of Bangladesh Shah Kibria
even categorized the 20 percent effective rate charged by the Grameen Bank as to
high216 Many practitioners therefore believe in a strong negative correlation between
the interest rate and the demand for loans217 Others have argued more generally that
concentrating on profitability and therefore charging high interest rates diverts MFIs
from serving the poorest218
These views are still shared among many MFI managers donor agencies and especially
investors and politicians While the former are unwilling to charge interest rates for
funds they received ldquocheaplyrdquo (through grants or subsidized loans) and are worried
about undermining their social goals by charging higher rates of interest219 the latter are
reluctant to invest for reasons stated above or impose interest caps to catch the attention
of the public by pretending to protect the poor from usury rates220
In chapter 53 it has been described that micro-entrepreneurs due to their smaller
capital endowment have even better investment opportunities than big business The
extend to which this is true has not yet been answered An indication is the high
repayment rate observed within MFIs around the globe If their customers capital yield
did not exceed the charged interest rate how would they be able to repay According to
Gibbons and Meehan customers of MFIs can generally generate returns of more than
100 percent on their invested capital221 and ldquo[r]esearch in India Kenya and the
Philippines found that the average annual return on investments in microenterprises
215 See Kate and Roeun (2004)216 See Hodson (2001) min 1100217 See Morduch (1999a) p 1594218 See Prisma (2002) p 1219 See Schreiner (1997) p 60 Khandker (1998) p 106 220 See Gross and de Silva (2002) p 32 Jansson and Wenner (1997) p 36 et sqq Campion (2002) p 59221 See Gibbons and Meehan (1999) p 131
44
ranged from 117 to 847 percentrdquo222 Schmidt and Tschach found the marginal
productivity of capital to be as high as 1000 percent for the smallest loans provided by
the Bolivian MFI Caja Los Andes223 These findings are confirmed by the observation
of Rosenberg who found while working as a microfinance consultant for ten years he
never heard of a single MFI having problems to attract clients because interest rates
were too high224
To get a better understanding of the investment opportunities of low income people in
developing countries a typical example on how MFI clients invest their loans is as
follows
Zobair is working as a rickshaw puller in Bangladesh Like most of his colleagues he
does not own the rickshaw he is riding Therefore he has to pay a daily rent of about
$030 to the owner Since his average income of approximately $15 per day is hardly
enough to feed his family he is not able to save the $100 necessary to buy a rickshaw
on his own 225 If he could do so through obtaining a loan his income would increase by
$030 every day because he would not have to pay the rent for the rickshaw anymore
Assuming an average of six working days per week 226 and a life span of the rickshaw
of 5 years his internal rate of return would equal 15324 percent annually227
Consequently any interest rate charged by a MFI would be advantageous to him as long
as it would not exceed 15324 percent228
63 Should the Interest Rate be subsidized anyway
Despite the fact that numerous micro-entrepreneurs are able to generate tremendous
returns on their investment obviously not all are able to use capital in such a productive
way and therefore can not afford microcredit at commercial rates In order to reach
these people as well many MFIs continue to use donor money in order to keep their
interest rates low But even if the problems related to subsidized credit as described in
222 See Helms and Reille (2004) p 3223 See Schmidt and Tschach (2001) p 6224 See Rosenberg (2002) p 10225 This examples draws on observations made by the author in Dhaka (Bangladesh) during 2003226 Obviously extended holidays are not a viable option in this surrounding 227 Own calculation See Appendix 6228 This result is only valid if the loan is repaid in daily instalments For a weekly repayment schedule the interest rate charged by the MFI must not exceed 15119 percent in order to still be beneficial for Zobair
45
chapter 23 do not arise it might still not be the most effective tool to help poor people
as will be illustrated in the following example
A MFI faces two groups of potential clients one with businesses able to generate a
return of 125 percent on borrowed capital and another with a possible returns of 50
percent Assuming budget costs according to equation (2) the institution needs to
charge an interest rate of 875 percent and therefore only serves the former group
Supposed each group consists of 50 members demanding $100 loans the net gains to
society (NGS) could be calculated as follows
(3) NGS = 50 times ($125 ndash $875) = $1875
These gains would be due to the investments of the more profitable group which were
made possible through the loans provided by the MFI The less profitable group would
not borrow since their expected returns are not sufficient to pay for the interest If the
interest rate would be lowered to 30 percent both groups would be able to generate net
gains and therefore borrow from the MFI In order to provide loans at this rate the
institution would need to raise additional capital from non commercial sources The
NGS would be calculated as follows
(4) NGS = 50 times ($125 - $30) + 50 times ($50 - $30) + 100 times ($30 - $875) = 0
While the first terms represent the net gains to the respective groups the last describes
the costs incurred in providing the loans At a rate of 30 percent each loan would need
to be subsidized with $575 Hence the NGS actually fall after the introduction of the
subsidized loan This is due to the fact that the less profitable group is encouraged to
invest in relatively unproductive businesses In addition future growth of the MFI could
be jeopardized due to scarce donor money which is needed to finance the interest rate
subsidy Therefore it seems more advisable to continue to charge a rate of 875 percent
and spend the money used for subsidization on other programs such as health care or
education229
229 In Appendix 7 it will be shown that this result generally holds
46
7 Empirical verification
71 Setting up a Sample
To see if the findings of the previous chapters hold the effects which interest rates
charged by MFIs have on their performance will be analyzed in the following Up to
now such a study does not exist mainly because of a lack of adequate data Most MFIs
do not provide accurate information about the annual effective interest rate they charge
and therefore make an evaluation difficult
In 2002 Rosenberg distinguished eight different categories on how microcredit interest
rates are quoted230 These categories differ in several ways On the contrary to
traditional banks for example it is common for MFIs to state interest rates calculated on
a ldquoflatrdquo balance rather than on a declining one This means that the total loan amount is
used to determine the interest rate ignoring installments paid by the borrowers normally
on a weekly or monthly basis In addition many MFIs charge a certain upfront fee prior
to the loan disbursement require compulsory savings at a lower rate or state their
interest rate for semi annual terms only On the one hand this is done to provide
numbers that are more meaningful to MFI customers who often lack the necessary math
skills to deal with compound interest on the other hand it is done to circumvent interest
rate ceilings imposed by the government231 Another problem is that most MFIs offer
different loan products without itemizing their respective shares to their total loan
portfolio As a result it is not possible to calculate a weighted average even if the rate
stated by the respective MFI could be transformed into an effective interest rate
Usually the portfolio yield is used as a proxy in order to make statements about the
interest rate charged by a certain MFI232 It is generally ldquocalculated by dividing total
cash financial revenue (all income generated by the loan portfolio but not accrued
interest) by the period average gross portfoliordquo233 The advantage of this method is that
even the hidden costs are considered Nevertheless it also has a severe shortcoming by
not taking late or defaulted payments into account Therefore the portfolio yield does
230 See Rosenberg (2002) p 5231 MicroRate (2002) p 8232 See MicroRate (nd)233 MicroRate and IADB (2003) p 39
47
not allow to draw conclusions regarding the correlation between the interest rate
charged by a MFI and its PAR
72 Examining the Sample
Through the appearance of rating agencies specialized in the microfinance sector more
adequate information has become available in recent years While MicroRate only
publishes the portfolio yield of rated MFIs M-Cril Microfinanza Microserve and
Planet Rating actually provide information about the annual effective interest rate for at
least some of the MFIs they analyze Although it is labelled differently from all of the
four institutions234 the term describes what is ldquothe highest income or yield that an
organisation can earn from its portfolio based on the terms of its loansrdquo235
Currently236 reports of 39 different MFIs from 20 countries providing accurate
information about the effective annual interest rate are available to the public This
sample should be used to verify the findings of the previous chapters237 Since a
comparison is made between the performances of MFIs based in different countries and
the ratings have been carried out in different years several adjustments are necessary
First the inflation of the respective country and the respective year(s)238 has to be taken
into account in order to only compare the real rates239 In addition the average
outstanding loan amount per borrower is divided by the respective countryrsquos GDP per
capita Since it can be assumed that ldquoonly the poorer households will be willing to take
the smallest loansrdquo240 this number can be used as a proxy for the poverty level
Although the sample size is far to small to represent the microfinance sector as a whole
and the results are statistically not significant the findings can still be used to underline
the theoretical conclusions drawn in the previous chapters In figure 5 the connection
234 M-Cril uses the name ldquoannual percentage raterdquo See eg M-Cril (2004a) p 25 Microfinanza uses the name ldquoexpected portfolio yieldrdquo See eg Microfinanza (2002c) p 25 Planet Rating uses the name ldquoannual effective interest raterdquo See eg Planet Rating (2004d) p 1 Microserve uses the name ldquotheoretical yieldrdquo See Microserve (2003) p 62235 See M-Cril (2004a) p 25236 As of September 28th 2004237 See Appendix 8 For exchange rates see FXTOP (2004)238 Where necessary a weighted average of the annual inflation rate was used See Appendix 9239 This is done through the following formula ir = (I ndash F) (1 + F100) While ir represents the real annual effective interest rate F represents the inflation rate 240 Morduch (1998) p 1572
48
between the average loan size and the transaction costs as a share of the average loan
portfolio is illustrated
Figure 5 Loan Size vs Interest Rate241
Source Own diagram
000
1000
2000
3000
4000
5000
6000
7000
8000
9000
10000
0 100 200 300 400 500 600
Loan Size
Inte
res
t R
ate
It can be seen that the interest rate is negative correlated to the loans size This can be
explained by the relative higher transaction cost for smaller loans as described in
chapter 52 In order to cover their costs MFIs serving the low end market need to
charge higher rates to their customers than those organizations serving the better off
poor Obviously there are several assumptions to this general finding Especially
striking are the two MFIs with an average loan size of approximately five times their
countries GDP per capita which still high interest rates This occurrence can be
explained by taking a closer look to the respective organizations One was established
less than two years prior to its rating and therefore still bears a lot of start up costs242
241 The equation for the regression line reads as follows Y = -00219X + 365 The correlation coefficient is 014242 See Microfinanza (2002b) p 1
49
the other managed to stay profitable while it almost quadrupled its loan portfolio in the
last two years243
Figure 6 Interest Rate vs PAR244
Source Own diagram
0
5
10
15
20
25
30
35
0 20 40 60 80 100 120
Interest Rate
PA
R
In Figure 6 the crucial correlation between the interest rates charged by a MFIs and its
PAR245 is examined According to the given sample the view of traditional banks and
investors that a higher interest rate leads to a higher default rate does not hold
Obviously one has to avoid to draw the opposite conclusion namely that a high interest
rates decreases the PAR The connection illustrated in figure 6 has to be interpreted as
follows Since high interest rates are related to small loans the low PAR for MFIs
charging high interest rates can actually be explained by the tremendous profitability of
small size investments Despite the high rates their customers are even more likely to
repay
243 See Planet Rating (2003b)244 The equation for the regression line reads as follows Y = -00768X + 68433 The correlation coefficient is 0235245 M-Cril only publishes the PAR for overdues greater than 60 days Therefore these ratios are used as a proxy for the industry standard of 30 days for some Asian MFIs
50
Finally it has to be examined if charging high interest rates actually enables MFI to
generate higher returns Although it can be expected that the combination of a low PAR
and a high interest rate leads to a high profitability it still has to be checked if this is not
outdone by soaring transaction costs Figure 7 illustrates the correlation between the
interest rate charged by a MFI and its financial self-sufficiency (FSS) The latter is the
ldquo[r]atio of total income to total adjusted expenses for the year Adjustments are made
for subsidised cost of funds (relative to market interest rate) equity (with respect to
inflation) and in-kind donationsrdquo246 It can be seen that the regression line actually does
indicate a positive correlation between the interest rate and the profitability of a MFI
Figure 7 Interest Rate vs FSS247
Source Own diagram248
0
20
40
60
80
100
120
140
160
180
0 20 40 60 80 100
Interest Rate
FS
S
246 M-Cril (2004a) p 53247 The equation for the regression line reads as follows Y = 02839X + 8901 The correlation coefficient is 0174248 Since the interest rate the customers of the MFI Foccas have to pay includes fees which are not passed on to the institution its interest rate in this diagram is set at 723 percent instead of the 10715 percent used for figure 6 See Planet Rating (2003b) p 1
51
This result does not necessarily disprove the findings of Stiglitz and Weiss since it can
be argued that MFIs simply do no increase their interest rates to the point where they
would maximize their expected returns But if this would be true why do MFIs not
charge higher rates of interest given the demand described in chapter 41 and 43 In
mature markets competition normally ensures prices not to exceed a certain level but
since many MFIs still operate in a ldquosellerrsquos marketrdquo249 this can not explain the findings
as described in figure 7 Therefore it has to be assumed that a combination of the
unwillingness of many microfinance practitioners to burden their customers with high
interest rates and the plain disbelief of traditional investors that micro-entrepreneurs can
bear those rates is responsible for this occurrence
249 See MicroRate and IADB (2003) p 9
52
8 Conclusions
It has been shown that MFIs are not only contributing significantly to the development
of the financial sector in their respective countries but also that they play an important
role to eradicate poverty by providing much needed capital to low income people which
are able to generate tremendous returns on their investments
The fact that the demand for microcredit is not met is mainly due to the view of most
for profit investors and traditional banks that offering financial services to poor people
can not be done profitable Because of this conviction they hardly invest in the
microfinance sector This does not have to be the case according to the findings of this
paper Although faced with relatively high transaction costs MFIs are able to charge
interest rates at levels that fully recover their costs Elizabeth Rhynersquos claim ldquothat the
most financially viable programs differed from their less viable peers in their
willingness to set interest rates at levels that would fully recover costsrdquo250 is backed by
the findings of this paper that high profitability is correlated to high interest rates
Theoretical models based on the findings of Stiglitz and Weiss can not be used as a
justification to ration credit for the microfinance sector since the interest rate that
maximizes profits to the lender can be assumed to exceed 100 percent for many MFIs
Nevertheless this rate is hardly charged although it has been shown that it can be done
The Mexican MFI Compartamos for example manages to keep its PAR as low as one
percent while charging an effective interest rate of more than 100 percent to
approximately 160000 clients251 In combination with this case the conclusions drawn
from examining the sample of MFIs in chapter 7 the claim of Hulme and Mosley as
stated in the introduction can be considered as wrong MFIs are in fact able to finance
rapid growth stay profitable by charging corresponding interest rates and still have a
significantly positive impact on the poverty level of their clients In the long run gains
in efficiency economies of scale a slowdown in growth and competition will ensure
interest rates drop as it has already been the case in countries like Bangladesh and parts
of Bolivia252
250 See Rhyne (1998) p 7251 See MicroRate (2004)252 See Microrate and IADB (2003) p 9
53
According to a MicroRate survey many MFIs are more profitable than Citibank and also
generate a higher return on investment than commercial banks in their respective
countries253 Investments companies like IMI or Blue Orchard will soon be able to
present a meaningful track record of their microfinance investments to potential
investors Ultimately the capital markets can not ignore the facts proving that it actually
can be profitable to invest in the microfinance sector but in order to raise money
quickly microfinance practitioners will have to continue to intensively promote their
cause not only to for profit investors but also to donors and multilateral agencies like
the World Bank
253 See MicroRate (2002) p 10
54
Appendix
Appendix 1 Average loan balance
Source Data is available through the Mix Market (2004)
Organization
Loan Portfolio 2002 (US$)
Loan Portfolio 2003 (US$)
Number of borrowers 2002
Number of Borrowers 2003
2CM 1263602 1400438 3622 3708ACF 955503 1611401 285 370ACLEDA 26846703 39391301 82598 98905ACME 1460881 1714844 4283 4600ADIM 369065 407798 1122 1395AFK 933306 1706577 250 467AgroInvest 4684249 9697411 5208 9629Al Amana 15593277 28677666 78114 101610AMSSFMC 612167 1040756 6183 6886AREGAK 3285273 3987011 11841 14377AVFS 214331 269819 1883 2866BancoSol 83629049 91175000 42290 56707BESA 10563980 15114430 4488 5061BPR AK 613362 876130 1730 3879BPR BMMS 133949 237946 1755 1779BRI 1344006170 1720072773 3056103 3100358BZMF 1592508 1922097 1250 1331CBDIBA 216587 242465 5764 2877CCA 2146235 4582302 4070 6585CCCP 447534 851678 6265 9450CEP 3795400 5261957 32291 42132CERUDEB 25093643 34873228 34490 44796CMEDFI 227674 250244 3467 3781CMM - Bogota 4836000 8135968 15635 22038CMMB 34880 56964 42 190COAC Maquita Cushunchic
870084 1855718 6603 7732
CODES 280843 263091 60 60CODESARROLLO 6714007 12935951 4391 6896Constanta 2943822 3536047 16134 18588COOPEC CAMEC MN
7152 29821 92 77
Crear - Tacna 3891116 4636094 3671 4948CREDIT 642094 81838 7532 8097CRYSTAL FUND 366456 421403 1379 1061DBACD 3473701 3876526 12812 19606ECLOF - ECU 1154292 728312 860 416ECLOF - MAL 441734 407227 1118 1500EKI 11833244 19245751 8999 13323EMT 4481589 5765281 84781 92173ESED 8579460 6834742 22790 20035
55
Eshet 185741 462569 3308 6540Faulu - KEN 9027332 7206344 17463 15000FDL 12503027 16545332 21306 25106FIE 35818903 41597315 26468 33100FINADEV 5512586 9770323 12775 14709Finance Salone 211312 434298 2225 7159Finca - TAN 1293430 1854834 20648 27499Finca - UGA 2451703 2798869 35610 36912FINCORP 4761288 10236896 941 858FJN 5473563 8037662 8107 11133FMFB 308158 1188896 713 3558FMM -Bucaramanga
6355518 10227000 25814 42464
FODEM 739181 939824 1909 2501FundaciESPOIR
898561 1883446 5911 9464
FUNDESER 798907 1373113 4072 5065Gasha 323748 413742 5504 6423GGLS Save the Children
64235 137957 1291 2362
GK 56986 166971 951 2718HKL 1363365 1420357 6648 5372HOPE 402799 603488 1098 1562IAMD 42132 56550 2780 2772IDECE 21312 39453 150 232IDF 2031944 2626382 31003 36580IMCEC - Dakar 254759 688449 1018 2983IMCEC - Thies 199799 571122 1164 1261
ISSIA 221615 246792 1409 1698JMCC 1962355 2609723 1471 2333KAFC 21710638 29241051 24850 32097KAMURJ 1003935 1411258 5559 5691Kashf 2355965 6271498 29655 59389KMBI 721409 1626666 11973 27266KPSCA 109299 128063 362 794K-Rep 14490447 20699963 38739 45379KSCS 18978 43740 140 297KVT 44075 70621 241 373LAPO 922478 1194633 18740 19139MEC ADEFAP 27788 69248 198 202MEC Bosangani 14357 31086 364 540MEDF 104113 136257 1278 1184Meklit 233170 252232 2084 3577Metemamen 22123 57778 943 1501MFSC 109261 171090 511 687MIKRA 2951028 5008784 4145 6095MIKROFIN 9560502 18380263 5633 7426Miselini 737387 1026639 10182 11431MRFC 11475440 9133130 163000 180000Mushuc Runa 2089076 5418325 3139 6232Nirdhan 2886777 3016171 29589 27457OCSSC 5245186 7658413 42157 6215o
56
Otiv Diana 95992 638422 229 1073Otiv Sambava 188094 437974 2002 1442Otiv Tana 66465 673175 337 1269Partner 9976448 15321304 7139 11935PCA 6878257 6885926 63113 58147PEACE 420746 627295 4192 5428PEDF 164399 254233 2357 3340Piyeli 809447 1206656 8674 4745PRESTANIC 2827502 3540367 1477 2605PRIDE - MAL 991888 854631 5376 5601PRIZMA 3881581 6838978 8112 10968ProMujer -Nicaragua
1006871 1424437 10436 13047
PTF 891566 1068881 8500 9070RBST 818594 1058115 619 723REMECU 1381705 1483471 10330 13996
RUSCA 60887 100820 454 994
SCSCS 89423 157472 873 1007SFPI 709497 903556 7728 9552Sidama 934260 1011798 10267 11346SPBD 117807 186029 647 1740Sunlink 819138 1056823 3401 3833Sunrise 5412366 8782868 4560 7256TEBA 108032426 176300111 163021 157776TIAVO 281978 838905 2049 459TPC 1140429 2267148 22869 31668TSPI 4650989 5383755 49649 75617UNICECAM 3442843 5943804 16039 19031Wasasa 230657 274908 2850 3728Wisdom 1306066 1404463 10524 12054XacBank 4910098 9829503 11063 18610Zakoura 15907288 12444768 103720 118980
Appendix 2 Portfolio at Risk
Source Data is available through the Mix Market (2004)
Organization PAR 2002ABA 202ACEP 464ACLEDA 175ACODEP 452ACSI 209Al Amana 010Apoyo Integral
483
AREGAK 692Banco Solidario
500
BancoSol 660BASIX 1296
57
BRI 437BURO Tangail
350
CEP 200CERUDEB 103CMAC -Sullana
567
CMM -Bogota
176
Compartamos 111Constanta 304Credi Fe 212CREDIAMIGO 409DBACD 010EBS 847EMT 010ESED 1311FADES 2311Faulu - KEN 246Faulu - UGA 096FDL 212FECECAM 428FED 436FIE 598FINADEV 021Finamerica 1133Finca - TAN 000Finca - UGA 297FMM -Bucaramanga
094
FMM -Popayan
088
FONDEP 013FORA 064Genesis Empresarial
1197
IDF 017KAFC 106Kashf 000KMBI 128K-Rep 229MiBanco 309MRFC 1742Nirdhan 373
PADME 079PAMECAS 284PCA 379PRIDE - TAN 018ProMujer -Nicaragua
073
RCPB 600REMECU 157SHARE 000
58
Soluci 182Spandana 014TEBA 106TSPI 355UMU 125UNICECAM 405Urwego 290UWFT 363WAGES 736WWB -Medellin
235
XacBank 061Zakoura 095
Appendix 3 Transaction Costs
Source Data is available through the Mix Market (2004)
OrganizationTransaction Costs
Acci Rural 1154ACEP 858ACLEDA 2430ACODEP 2920ACSI 924Al Amana 2576AREGAK 2856AssEF 1919Banco Solidario
1826
BancoSol 1210BASIX 1317BRI 1353BURO Tangail
2053
CEP 1759CERUDEB 5109CMAC -Sullana
1784
CMM -Bogota
2089
Compartamos 3341Constanta 4597Credi Fe 1978CREDIAMIGO 2525DBACD 1742EBS 2377EMT 3220ESED 1343FADES 1673FAMA 2436
59
Faulu - KEN 2253Faulu - UGA 4962FDL 1726FECECAM 2587FED 4083FIE 1125Finamerica 1563Finca - TAN 10753Finca - UGA 9096FMM -Bucaramanga
1925
FMM -Popayan
1112
FONDEP 5477FORA 3481Genesis Empresarial
1626
IDF 1695
K-Rep 1909LAPO 3511MiBanco 2456Nirdhan 1325NWTF 3109OCSSC 1155PADME 1131PAMECAS 1705PCA 1670PRIDE - TAN 4273ProMujer -Nicaragua
5078
RCPB 2059SHARE 2308Sidama 2662Soluci 2906Spandana 641TEBA 1213TSPI 3898UMU 4023UNICECAM 10120Urwego 7437Wisdom 1906WWB -Medellin
1703
XacBank 4144Zakoura 1881
60
Appendix 4 Portfolio Growth
Source Data is available through the Mix Market (2004)
Organization
Total Loan Portfolio in 2000
Total Loan Portfolio in 2002
ACODEP 5889394 7258487Adelante 4327 88594ADRI 1514681 2591240AgroCapital 11100088 12018280Banco Solidario 39632165 103420000
BancoSol 78031172 83629049CMAC - Sullana 14596365 28055720
COAC Maquita Cushunchic
348443 870084
CODESARROLLO 1374801 6714007Compartamos 10804279 41825248Crear - Tacna 3778816 3891116
Credi Fe 781616 9393936ECLOF - ECU 179247 1154292
FADES 11948814 15501578FAMA 6201411 8835134FIE 22524645 35818903Finamerica 16575104 16097113FINCOMUN 3278938 5696556FMM - Popayan 6241821 12212867
FONDECO 3456625 5101801Genesis Empresarial
11154234 17746288
MiBanco 36964072 95873333Mushuc Runa 90737 2089076ProMujer -Nicaragua
426541 1006871
WWB - Medellin 2891207 4580998
Appendix 5 Portfolio vs Equity
Source Data is available through the Mix Market (2004)
OrganizationLoan Portfolio Equity
ACODEP 7258487 1921447Adelante 88594 72973
ADRI 2591240 781477AgroCapital 12018280 10766101Banco Solidario 103420000 12961000BancoSol 83629049 15299415CMAC - Sullana 28055720 6210291
61
COAC Maquita Cushunchic
870084 260331
CODESARROLLO 6714007 1285103
Compartamos 41825248 18350446
Crear - Tacna 3891116 1016912Credi Fe 9393936 863848ECLOF - ECU 1154292 459226FADES 15501578 4138972FAMA 8835134 6377663FIE 35818903 5360484Finamerica 16097113 3817960FINCOMUN 5696556 1042241FMM - Popayan 12212867 8510494FONDECO 5101801 1658075Genesis Empresarial
17746288 4765816
MiBanco 95873333 24261889Mushuc Runa 2089076 434311ProMujer -Nicaragua
1006871 1196015
WWB - Medellin 4580998 2213249
Appendix 6 Internal Rate of Return
Source Excel (German Version) calculation based on own data
A B C D E F
1 Date Cash Flow
Interest Rate Internal Rate of Return Balance Interest Principal
23 01012004 -100 15324 100 025489547 0045104534 02012004 03 999548955 025489547 0045104535 03012004 03 99909676 02547805 004521956 04012004 03 998643412 025466524 0045334767 05012004 03 998188909 025454968 0045450328 06012004 03 997733247 025443383 0045566179 08012004 03 999826083 050928361 -0209283610 09012004 03 999374595 025485114 004514886
hellip hellip hellip hellip hellip helliphellip hellip hellip hellip hellip hellip helliphellip hellip hellip hellip hellip hellip hellip1562 23122008 03 177951388 000528711 0294712891563 25122008 03 148859724 000908336 0290916641564 26122008 03 119239161 000379437 0296205631565 27122008 03 089543096 000303935 0296960651566 28122008 03 059771337 000228241 0297717591567 29122008 03 029923692 000152354 0298476461568 30122008 03 -3434E-07 000076274 029923726
62
The formula in the square C3 reads as follows
ldquoXINTZINSFUSS(B3B1568A3A156815)rdquo
Appendix 7 Subsidized Interest Rates and the Net Gains to Society
SourceOwn calculations
For simplicity only two groups of potential clients are distinguished This is possible
since using a continuum of potential clients would lead to the same results In addition it
is assumed that the amount of every loan (L) is equal and that all clients invest the
whole loan amount Group H consist of NH potential clients with a rate of return (rH) on
their invested capital higher than the cost recovering interest rate charged by the MFI
(iC) Group L consists of NL potential clients with a rate of return (rL) on their invested
capital lower than iC If the MFI charges iC the NGS can be calculated as follows
NGSC = NH times (rH - iC) times L
Since rH is bigger than iH (rH gt iC) according to the definition presented above the term
NGSH must be positive as long as NH does not equal zero If the MFI introduces a
subsidised interest rate (iS) lower than rL the NGS can be calculated as follows
(1) NGSS = NH times (rH - iS) times L + NLtimes (rL - iS) times L + (NH + NL) times (iS - iC) times L
(2) NGSS = NH times (rH- iC) times L + NLtimes (rL - iC) times L
The term (NH + NL) times (iS - iC) times L describes the amount of money that is needed in order
to subsidize the interest rate to the level iS By setting up an inequation it can be
examined under which conditions the NGSS are bigger than the NGSC
(3) NGSS gt NGSC
(4) NH times (rH- iC) times L + NLtimes (rL - iC) times L gt NH times (rH - iC) times L
(5) NLtimes (rL - iC) times L gt 0
(6) rL gt iC
63
So the NGSS could only be bigger than the NGSC if equation 6 holds This is
impossible since it violated the definitions presented above Therefore the introduction
of subsidized interest rates is always accompanied with a drop in the NGS
Appendix 8 Interest Rate vs Loan Size vs FSS vs PAR
Source Data is available through the Mix Market (2004)
Organization Country
Real Interest Rate
Loan Size (divided by the GDP per Capita) FSS PAR
BTFFKyrgyz Republic 3803 48260 1487 698
BesaFoundation Albania 2184 16076 684 260RFF Albania 1198 5783 4764 277PSHM Albania 2194 000 5758 198Mi-Bospo Bosnia 2974 5499 1261 020Prizma Bosnia 3474 3569 103 064Agroinvest Serbia 2201 4401 875 020KCLF Kazakhstan 5713 1713 865 090
Foccas Uganda10716 (723) 1550 584 29
ACEP Senegal 3280 20941 1643 1Padme Benin 2715 13575 1667 08Papme Benin 3086 53659 1405 24Vital Finance Benin 2676 9394 1015 17Finadev Benin 1738 14850 1024 21ABA Egypt 2579 1613 1168 88ASBA Egypt 2597 1702 1252 68DBACD Egypt 2490 1643 1073 0SBACD Egypt 2500 1734 982 67AMSSF Morocco 6926 787 1306 04Fondep Morocco 5199 650 889 071Zakoura Morocco 4414 900 98 006ENDA Tunisia 4008 1351 110 102BSFL India 1954 3269 856 99Share India 3426 1440 951 0Spandana India 2942 1618 1367 026SWC India 1864 2626 42 3036SKS India 2248 1912 578 0Grama Vidiya India 3176 1221 76 18Sneha India 3451 1433 933 0Buro Bangladesh 3206 1882 1093 17Upap Pakistan 2073 8183 757 03Seeds Sri Lanka 1004 1088 605 287EMT Cambodia 4324 1676 1016 01TPC Cambodia 4470 2035 832 27
64
WTF Phillippines 5816 1095 941 74TSKI Phillippines 5794 777 96 79Cacja Ecuador 862 6189 9460 897ACME Haiti 6043 6934 11685 450Grupo Cama Mexico 8961 267 10717 288
65
Appendix 9 Inflation vs GDP per Capita
Source IMF (2004)
Country Subject Description Units Scale 2000 2001 2002 2003 2004
Albania Gross domestic product per capita current prices US dollars Units 1083988 1238206 1396172 1757778 2229712
Albania Inflation annual percent change Percent 00 31 52 24 34
Bangladesh Gross domestic product per capita current prices US dollars Units 329310 327980 344494 369495 393717
Bangladesh Inflation annual percent change Percent 22 15 38 54 64
Benin Gross domestic product per capita current prices US dollars Units 361340 368213 405951 494725 560129
Benin Inflation annual percent change Percent 42 40 24 15 26
Bosnia and Herzegovina Gross domestic product per capita current prices US dollars Units 1255837 1321429 1466090 1807392 2070508
Bosnia and Herzegovina Inflation annual percent change Percent 50 32 03 02 09
Cambodia Gross domestic product per capita current prices US dollars Units 276413 280352 296577 305940 321247
Cambodia Inflation annual percent change Percent -08 02 33 12 20
Ecuador Gross domestic product per capita current prices US dollars Units 1227711 1590267 1804362 1957183 2082156
Ecuador Inflation annual percent change Percent -77 377 126 79 32
Egypt Gross domestic product per capita current prices US dollars Units 1550982 1461431 1278462 1188060 1083158
Egypt Inflation annual percent change Percent 28 24 24 32 52
India Gross domestic product per capita current prices US dollars Units 454206 458849 472915 542554 602625
India Inflation annual percent change Percent 40 38 43 38 47
Kazakhstan Gross domestic product per capita current prices US dollars Units 1236159 1490946 1655148 2000598 2579554
Kazakhstan Inflation annual percent change Percent 134 83 59 64 68
Kyrgyz Republic Gross domestic product per capita current prices US dollars Units 278256 306130 321079 349632 380637
Kyrgyz Republic Inflation annual percent change Percent 187 69 21 31 45
66
Mexico Gross domestic product per capita current prices US dollars Units 5957486 6274468 6425203 6111754 6377064
Mexico Inflation annual percent change Percent 95 64 50 45 44
Morocco Gross domestic product per capita current prices US dollars Units 1161302 1162154 1199584 1432725 1541041
Morocco Inflation annual percent change Percent 19 06 28 12 20
Pakistan Gross domestic product per capita current prices US dollars Units 437381 400356 440471 492913 538120
Pakistan Inflation annual percent change Percent 44 31 32 29 46
Philippines Gross domestic product per capita current prices US dollars Units 979423 900225 950707 963765 1018710
Philippines Inflation annual percent change Percent 43 61 31 30 54
Russia Inflation annual percent change Percent 208 215 158 137 103
Senegal Gross domestic product per capita current prices US dollars Units 478704 474460 507408 634171 714622
Senegal Inflation annual percent change Percent 09 30 23 -00 08
Serbia and Montenegro Gross domestic product per capita current prices US dollars Units 1031263 1389384 1882036 2491799 2795805
Serbia and Montenegro Inflation annual percent change Percent 699 911 212 113 79
Sri Lanka Gross domestic product per capita current prices US dollars Units 846811 796025 828256 904330 982466
Sri Lanka Inflation annual percent change Percent 62 142 96 63 64
Tunisia Gross domestic product per capita current prices US dollars Units 2034360 2065140 2149421 2534823 2881273
Tunisia Inflation annual percent change Percent 30 19 28 28 34
Uganda Gross domestic product per capita current prices US dollars Units 293404 249682 279587 280802 287204
Uganda Inflation annual percent change Percent 45 -20 57 51 35
67
References
Akerlof George A The Market for ldquoLemonsrdquo Qualitative Uncertainty and the Market Mechanism in Quarterly Journal of Economics Vol 84 (1970) pp 488-500
Amin Ruhul et al Integration of an Essential Service Package (ESP) in Child and Reproductive Health and Family Planning with a Micro-Credit Program for poor Women Experience from a Pilot Project in Rural Bangladesh in World Development Vol 29 (2001) No 9 pp 1611-1621
Bester Helmut Screening vs Rationing in Credit Markets with Imperfect Information in The American Economic Review Vol 75 (1985) No 4 pp 850855
Borst Dietmar Microfinance ndash Theoretische Grundlagen fuumlr den Einsatz sowie die Abschaumltzung des Potentials anhand einer Datenbankuntersuchung zur Verwundbarkeit der laumlndlichen Bevoumllkerung in Vietnam unpublished diploma thesis Karlsruhe 2004
BRAC Annual Report 2002 Dhaka 2003
Busch Alexander Kort Katharina Die Peanuts-Banker und ihre Kunden in Handelsblatt Nr 150 published August 5th 2004 p 8
Campion Anita Challenges to Microfinance Commercialization in Journal of Microfinance Vol 4 (1999) No 2 pp 57-65
Chu Michael Key Issues of Development Finance Somerville (MA) 1998
Dornbusch Ruumldiger Fischer Stanley Makrooumlkonomie Oldenburg 1995
Dunn Seth Flavin Christopher Moving the Climate Change Agenda Forward in State of the World New York London 2002 pp 24-50
Farrington Todd Efficiency in Microfinance Institutions in The MicroBanking Bulletin Issue No 4 pp 18-24
Gardner Gary The Challenge for Johannesburg Creating a More Secure World in State of the World New York London 2002 pp 3-23
Ghatak Subrata On Interregional Variations in Rural Interest Rates in Journal of Developing Areas Issue 18 pp 21-34
Gibbons David Serving the Poorest Sustainably in The MicroBanking Bulletin Issue No 5 (2000) pp 13-16
Gibbons David Meehan Jennifer W The Microcredit Summitrsquos Challenge WorkingToward Institutional Financial Self-Sufficiency While Maintaining a Commitment to Serving the Poorest Families in Journal of Microfinance Vol 1 (1999) No 1 pp 131-192
68
Goodwin-Groen Ruth Do Asian MFIs Access Funds from Commercial Banks inThe MicroBanking Bulletin Issue No 3 pp 8-10
Grameen Bank (ed) Grameen Generalized System Dhaka 2003
Gross Alexandra de Silva Samantha Social Fund Support of Microfinance A Reviewof Implementation Experience The World Bank Social Protection Discussion Paper No 0215 Washington DC 2002
Hashemi Syed M Schuler Sidney R Sustainable Banking with the Poor A Case Study of Grameen Bank Dhaka 1997
Helms Brigit Reille Xavier Interest Rate Ceilings and Microfinance The story so farConsultative Group to assist the Poor Occasional Paper No 9 September 2004 Washington DC 2004
Hoff Karla Stiglitz Joseph E Introduction Imperfect Information and Rural Credit Markets-Puzzles and Policy Perspectives in The World Bank Economic Review Vol 4 (1990) No 3 pp 235-250
Holcombe Susan Managing to Empower The Grameen Bankrsquos Experience of Poverty Allevation Dhaka 1995
Hulme David Mosley Paul Finance against Poverty London 1996
Jalvaani (ed) Flush with loans Micro credit for rural sanitation Vol 2 (1999) No 2 pp 1-2
Khandker Shahidur R Fighting Poverty with Microcredit Experience in Bangladesh Oxford et al 1998
Khandker Shahidur R Khalily Baqui Khan Zahed Grameen Bank Performance andSustainability The World Bank Discussion Paper No 306 Washington DC 1995
Lipsey Rechard G An Introduction to Positive Economics 5th edition London 1979
Littlefield Elizabeth Morduch Jonathan Hashemi Syed M Is Microfinance an Effective Strategy to Reach the Millennium Development Goals Consultative Group to Assist the Poorest Focus Note No 24 Washington DC 2003
Martinot Eric Cabraal Anil World Bank Solar Home Systems Projects Experience and Lessons Learned 1993-2000 in Renewable Energy Oxford 2000 pp 1-8
M-Cril Microfinance Review 2003 revised February 2004 Gurgaon 2004a
Mezzera Jaime Microcredit in Brazil The Gap Between Supply and Demand in The MicroBanking Bulletin Issue No 8 (2000) pp 22-24
The MicroBanking Bulletin (ed) Note to the Reader Vol 1 (1997) Issue No 1 pp 5-8
69
The MicroBanking Bulletin (ed) An Introduction to the Peer Groups and Tables Issue No 9 (2003) pp 53-60
MicroRate IADB Performance Indicators for Microfinance Institutions Technical Guide 3rd edition Washington DC 2003
MkNelly Barbara Dunford Christopher Impact of Credit with Education on Mothers and Their Young Childrenrsquos Nutrition Lower Pra Rural Bank Credit with Education Program in Ghana Freedom from Hunger Research Paper No 4 Davis (CA) 1998
MkNelly Barbara Dunford Christopher Impact of Credit with Education on Mothers and Their Young Childrenrsquos Nutrition CRECER Credit with Education Program in Bolivia Freedom from Hunger Research Paper No 5 Davis (CA) 1999
Morduch Jonathan The Microfinance Promise in Journal of Economic Literature Vol 37 (1999b) No 4 pp 1569-1614
Neus Werner Einfuumlhrung in die Betriebswirtschaftslehre Tuumlbingen 1998
Otero Maria Bringing Development Back into Microfinance Journal of Microfinance Vol 1 (1999) No 1 pp 8-19
Panjaitan-Drioadisuryo Rosintan D M Cloud Kathleen Gender self-employment and microcredit programs An Indonesian case study in The Quarterly Review of Economics and Finance Vol 39 (1999) pp 769ndash779
Perkins Dwight H et al Economics of Development 5th edition New York London 2001
Pitt Mark M Khandker Shahidur R Credit Programs for the Poor and the Health Status of Children in Rural Bangladesh in International Economic Review Vol 44 (2003) No 1 pp 87-118
Raiffeisen Friedrich W The Credit Unions 8th edition Neuwied 1966
Rhyne Elizabeth The Yin and Yang of Microfinance Reaching the Poor and Sustainability in The MicroBanking Bulletin Issue No 2 (1998) pp 6-9
Richardson David C Unorthodox Microfinance The Seven Doctrines of Success in The MicroBanking Bulletin Issue No 4 (2000) pp 3-7
Robinson Marguerite S The Microfinance Revolution Sustainable Finance for the Poor Washington DC 2001
Robinson Marguerite S The Microfinance Revolution Volume 2 Lessons from Indonesia Washington DC 2002
Rosenberg Richard Microcredit Interest Rates Consultative Group to assist the Poorest Occasional Paper No 1 revised November 2002 Washington DC 2002
70
Roth Michael Steinwand Dirk Mikrofinanz Weltweites Erfolgsmodell nur nicht inDeutschland Zur Uumlbertragbarkeit der Erfahrungen aus Entwicklungslaumlndern auf Deutschland Deutsche Gesellschaft fuumlr Technische Zusammenarbeit (ed) Eschborn2004
Schmidt Reinhard H Tschach Ingo Microfinance as a Nexus of Incentives Finance and Accounting Working Paper No 87A Frankfurt 2001
Schreiner Mark A Framework for the Analysis of the Performance and Sustainability of Subsidized Microfinance Organizations with Application to Banco Sol of Bolivia and Grameen Bank of Bangladesh unpublished PhD dissertation Columbus (O) 1997
Seibel Hans D Recent Developments in Microfinance Development Research Center Working Paper No 1998-5 Cologne 1998
Seibel Hans D History matters in microfinance in Small Enterprise Development ndashAn International Journal of Microfinance and Business Development Vol 14 (2003a) No 2 pp 10-12
Seibel Hans D Schmidt Petra How an Agricultural Development Bank Revolutionized Rural Finance The Case of Bank Rakyat Indonesia International Fund for Agricultural Development Rural Finance Working Paper B 5 Rome 2000
Sen Amartya Oumlkonomie fuumlr den Menschen ndash Wege zu Gerechtigkeit und Solidaritaumlt in der Marktwirtschaft Muumlnchen Wien 2000
Serageldin Ismail The View of the Chair in Consultative Group to Assist the Poorest Newsletter Issue No1 (1996) pp 1 11-12
Soros George Die Krise des globalen Kapitalismus Offene Gesellschaft in Gefahr Berlin 1998
Staschen Stefan Regulation and Supervision of Microfinance Institutions State of Knowledge Deutsche Gesellschaft fuumlr Technische Zusammenarbeit (ed) Eschborn 1999
Steinwand Dirk The Alchemy of Microfinance The Evolution of the IndonesianPeoples Credit Banks (BPR) to 1999 and a Contemporary Analysis Berlin 2001
Stiglitz Joseph E Peer Monitoring and Credit Markets in The World Bank Economic Review Vol 4 (1990) No 3 pp 351-366
Stiglitz Joseph E Weiss Andrew Credit Rationing in Markets with Imperfect Information in The American Economic Review Vol 71 (1981) No 3 pp 393-410
Tschach Ingo Theorie der Entwicklungsfinanzierung Mit Kleinkreditprogrammen Kredit- und Arbeitsmarktsegmentierung uumlberwinden Frankfurt 2000
UNDP Human Development Report 2004 New York 2004
71
UNFPA state of the world population 2004 New York 2004
UNICEF The State of the Worldrsquos Children 2002 NewYork Geneva 2002
Varley Robert C G Financial Services and Environmental Health Household Credit for Water and Sanitation Environmental Health Project Applied Study No 2 Washington DC 1995
Volkery Carsten Kampf um Straszligenhaumlndler in Die Zeit Nr 23 published May 27th
2004 p 33
Wardhana Ali Introduction in The Microfinance Revolution ndash Sustainable Finance for the Poor Washington DC 2001 pp XVII-XXVII
Woodworth Warner Woller Gary Greetings from the Editors Journal of Microfinance Vol 1 (1999) No 1 p 6
The World Bank Group World Development Indicators 2004 Washington DC 2004
Worldwatch Institute (2002) Vital Signs 2002 New York London 2002
Wimmer Nancy Barua Dipal Less is more Microfinance for solar energy in rural areas in Renewable Energy World Review Issue 2004-2005 Vol 7 (2004) No4 pp 170-179
Yunus Muhammad Grameen Bank II ndash Designed to Open new Possibilities Dhaka 2002
Yunus Muhammad Grameen ndash Eine Bank fuumlr die Armen dieser Welt Muumlnchen 1998a
Internet References
Abishek Lal (nd) An Overview of Microfinance and Environmental Management [http wwwgdrcorgicmenvironabhishekhtml] (availability date October 5 2004)
ACCION (nd) our history [httpwwwaccionorgabout_our_historyasp] (availability date October 5 2004)
ACCION (nd) key statistics [httpwwwaccionorgabout_key_statsasp] (availability date October 5 2004)
Ahmad Zulfiqar (nd) Forms of Regional Cooperation in Microfinance in South Asia [httpwwwbwtporgarcmpakistanIV_News_and_EventsBWTPworkshopZulfiqar20Ahmad20paper20(BWTP-PMN2029Jan04)pdf (availability date October 6 2004)
72
Ahmed Salehuddin (2003) Foreword [httpwwwpksf-bdorgaprm_summit_brochure htm] (availability date September 30 2004)
Annan Kofi (2002) Statement at The Microcredit Summit +5 [httpwww microcreditsummitorgenews2003-03_sp_chowdhuryhtml) (availability date October 5 2004)
Barnes Carolyn (2001) Microfinance Program Clients and Impact An Assessment of Zambuko Trust Zimbabwe [httpwwwmicrofinancegatewayorgfiles18553_Barnes_Zambuko_Trust_2001pdf] (availability date October 5 2004)
Barnes Carolyn Gaile Gary Kibombo Richard (2001) The Impact of Three Microfinance Programs in Uganda [httpwwwmicrofinancegatewayorgfiles2935_Barnes_2001pdf] (availability date October 5 2004)
Barua Dipal (2004) Success of Grameen Shakti in the Field of Renewable Energy Sector in Bangladesh [httpwwwrenewables2004depptPresentation1-SessionVA(14-1530h)-Baruapdf] (availability date September 30 2004)
Bhatt Ela (1997) In 1975 [httpwwwmicrocreditsummitorgdeclarationhtm] (availability date September 30 2004)
BlueOrchard (2004a) Microfinance [httpwwwblueorchardchenmicrofinance_institutions asp] (availability date October 5 2004)
BlueOrchard (2004b) January 2004 Newsletter [httpwwwblueorchardchmedialibrarywebsitenewsletter_jan_2004pdf] (availability date October 5 2004)
Brynjolfsson John (2004) John Brynjolfsson Discusses Recent Trends in TIPS Issuance [httpwwwpimcocomLeftNavPIMCO+Spotlight2004Spotlight_2_04htm] (availability date October 5 2004)
CGAP (2003) Report to the Board of Executive Directors [httpwww-wdsworldbankorgservletWDSContentServerWDSPIB20031208000012009_20031208101736RenderedPDF27441pdf] (availability date October 5 2004)
Chen Shaohua Ravallion Martin (2004) How have the worldrsquos poorest fared since the early 1980s [httpwwwworldbankorgresearchpovmonitorMartinPapersHow_have_the_poorest_fared_since_the_early_1980spdf] (availability date October 5 2004)
Cheston Susy Kuhn Lisa (2002) Empowering Women through Microfinance[httpwwwmicrofinancegatewayorgfiles3240_Cheston_2002doc] (availability date October 5 2004)
Christen Robert P et al (1995) Maximizing the Outreach of Microenterprise FinanceAn Analysis of Successful Microfinance Programs [httpwwwdecorgpdf_docsPNABS519 pdf] (availability date October 5 2004)
73
CIA (2004) The World Factbook [httpwwwciagovciapublicationsfactbook] (availability date October 5 2004)
Clear Profit (2004) Microfinance Bond Record May Double [httpwwwclear-profitcomissuescpsep04txt] (availability date September 30 2004)
Daley-Harris Sam (2003) State of the Microcredit Summit Campaign Report 2003 [httpwwwmicrocreditsummitorgpubsreportssocr2003SOCR03-E[txt]pdf] (availability date September 30 2004)
Dominiceacute Robert (2004) Interview in Microfinance Bond Record May Double [httpwwwclear-profitcomissuescpsep04txt] (availability date September 30 2004)
Donahue Jill Kabbucho Kamau Osinde Sylvia (2001) HIVAIDSmdashResponding To A Silent Economic Crisis Among Microfinance Clients In Kenya and Uganda [httpwwwmicrosave-africacomget_fileaspdownload_id=541] (availability date September 30 2004)
Donahue Jill Sussman Linda (1999) Building a Multi-Sectoral Response Follow-Up Assessment of Programming for Children and Families Affected by HIVAids in Kenya [httpwwwdecorgpdf_docspnacg778pdf] (availability date September 30 2004)
The Economist (1998) [httpwwweconomistcomdisplaystorycfmstory_id=S2629H3C28Q13F240A] (availability date September 30 2004)
Finca (nd) Introduction [httpvillagebankingorgwhereindexphp3] (availability date September 30 2004)
Fischer Stanley (2003) Statement at The Asia Society and Womens World BankingAnnual Microfinance Conference [httpwwwiiecomfischerpdffischer051303pdf] (availability date September 30 2004)
Friedman Milton (nd) Samuha [httpwwwsamuhaorgm-1htm] availability date September 30 2004)
FXTOP (2004) Historical Exchange Rates [httpfxtopcomdehistoratesphp3] (availability date September 30 2004)
Gibbons David Meehan Jennifer W (2002) Financing Microfinance for Poverty Reduction [httpwwwmicrocreditsummitorgpapersfinancing_finalpdf] (availability date September 30 2004)
Grameen Bank (2004) Grameen Bank At a Glance [httpwwwgrameen-infoorgbankcdshtml] (availability date September 30 2004)
Grameen Trust (nd) Grameen Bank Replication Program [httpwwwgrameen-infoorggrameengtrustreplicationhtml8721] (availability date September 30 2004)
74
Hossain Farhad (2004) Microfinance in Development [httpwwwvalthelsinkifi staff jkoponenb1104FarhadFeb2304pdf] (availability date October 5 2004)
IMF (2004) Data [httpwwwimforgexternalpubsftweo200402datadbginimcfm] (availability date October 5 2004)
IMI (2004) Investments [httpwwwimi-agcomoverviewindexhtml] (availability date September 30 2004)
IPCC (2001) Summary for Policymakers [httpwwwipccchpubspm22-01pdf] (availability date September 30 2004)
Jansson Tor Wenner Mark (1997) Financial Regulation and its Significance for Microfinance in Latin America and the Caribbean [httpwwwgdrcorgicmgoverniadb-janssonpdf] (availability date October 5 2004)
Ken Daniel Ten Roeun Van (2004) The Cycle of Debt - As Microcredit Institutions Grow Some Question Their Effect on Poverty [httpwwwcamnetcomkhcambodiadaily selected_featurescd-21-02-04htm] (availability date September 30 2004)
Kim Julia (2002) Social Interventions for HIVAIDS - Intervention with Microfinance for AIDS and Gender Equity [httpwwwwitsaczaradarPDF20filesIntervention_monograph_no_picspdfpdf] (availability date September 30 2004)
Llanto Gilberto (nd) Vietnam [httpwwwadborgDocumentsBooksCentral_Banks_MicrofinanceCountry_Studiesvietnampdf] (availability date September 30 2004)
The Microfinance Gateway (nd) Frequently Asked Questions [httpwwwmicrofinance gatewayorgsectionfaq1] (availability date October 5 2004)
Microfinance Rating and Assessment Fund (2004) Qualified Raters [httpwwwmfrating orgmfi_institutionsqualified_ratershtml] (availability date October 5 2004)
Microcredit Summit (1997) Declaration and Plan of Action [httpwwwmicrocreditsummit orgdeclarationhtm] (availability date September 30 2004)
MicroRate (nd) Performance Indicators and Ratios [httpwwwmicroratecomENGLISHsiteRATINGSindicatorshtml] (availability date September 30 2004)
MicroRate (2002) The Finance of Microfinance [httpwwwmicroratecomPDFFinance20of20Microfinancepdf] (availability date September 30 2004)
MicroRate (2004) Adjusted comparison table [httpwwwmicroratecomENGLISHsitePDFAdjusted20Comparison20Table060320engpdf] (availability date October 5 2004)
75
Mix Market (2004) The Mix Market [httpwwwmixmarketorg] (availability date October 5 2004)
Morduch Jonathan (1999b) The Grameen Bank A Financial Reckoning [httpwwwwwsprincetonedu~rpdsmacarthurdownloadsmorduch_grameen_bankpdf] (availability date September 30 2004)
Pallen Dean (1997) Environmental Sourcebook for Micro-Finance Institutions [httpwwwacdi-idagccaINETIMAGESNSFvLUImagesea20summaries$fileSOURC Epdf] (availability date September 30 2004)
Prisma (2002) The Case for Private Capital Market Creation in the Development Field of Microfinance [httpwwwsocialenterprisenetpdfsprivate_capital_marketpdf] (availability date September 30 2004)
Schmidt Reinhard H Zeitinger C-P (1997) Critical Issues in Microbusiness Finance and the Role of Donors No 6 [httpwwwgdrcorgicmmfi-donorpdf] (availability date September 30 2004)
Seibel Hans D (2003b) Commodity finance a commercial proposition Micro- and Mesofinance for Agricultural Commodity Production Processing and Trade [httpwwwuni-koelndeew-fakaef05-20042003-420Commodity20Financepdf] (availability date September 30 2004)
Simanowitz Anton Walter Alice (2002) Ensuring Impact Reaching the Poorest while Building Financially Self-sufficient Institutions and Showing Improvement in the Lives of the Poorest Families [httpwwwidsacukimpactPublicationsWorkingPapersOP3MCSSumdoc] (availability date September 30 2004)
Smith Stephen C Jain Sanjay (1999) Village Banking and Maternal and Child Health Theory and Evidence from Ecuador and Honduras[httphomegwuedu~scsmith healthrevwd801pdf] (availability date September 30 2004)
United Nations (1999) International Year of Microcredit 2005 [httpods-dds-nyunorgdoc UNDOCGENN9976933PDFN9976933 pdfOpenElement] (availability date October 5 2004)
United Nations (2000) United Nations Millennium Declaration [httpods-dds-nyunorgdocUNDOCGENN0055951PDFN0055951pdfOpenElement] (availability date October 5 2004)
US Census Bureau (2004) Total Midyear Population for the World 1950-2050 [httpwwwcensusgovipcwwwworldpophtml] (availability date October 5 2004)
WHO (2004) Making pregnancy safer [httpwwwwhointmediacentrefactsheets fs276en] (availability date September 30 2004)
WHO (2001) Child Health [httpwwwwhointmipfiles2082AAGChildHealthpdf] (availability date September 30 2004)
76
The World Bank Group (nd) Health Nutrition and Population and the Millennium Development Goals [www1worldbankorghnpMDGMDG20-20HNPbookletpdf] (availability date September 30 2004)
Yunus Muhammad (1998) Championing the Right to Credit for Poor Women Around the World [httpaspgrameencom dialoguedialogue34interviewhtml] (availability date September 30 2004)
UNAIDS (2004) [httpwwwunaidsorgbangkok2004GAR2004_pdfUNAIDSGlobalReport2004_enpdf] (availability date September 30 2004)
Ratings
M-Cril (2000) SPANDANA [httpwwwratingfundorgspanishdocsSPANDANA_RatingReportpdf] (availability date October 7 2004)
M-Cril (2001a) BASIX [httpwwwbasixindiacomMcrilasp] (availability date October 7 2004)
M-Cril (2001b) BDB [httpwwwratingfundorgspanishdocsRF_BDBpdf] (availability date October 7 2004)
M-Cril (2001c) SNEHA [httpwwwratingfundorgspanishdocsRF_Sneha-u1pdf] (availability date October 7 2004)
M-Cril (2002a) KCLF [httpwwwratingfundorgdocsRF-KCLF-risk20reportdoc] (availability date October 7 2004)
M-Cril (2002b) NWTF [httpwwwratingfundorgspanishdocsRF_NWTFpdf] (availability date October 7 2004)
M-Cril (2002c) SEEDS [httpwwwratingfundorgspanishdocsRF_SEEDS_2002_Ratingpdf] (availability date October 7 2004)
M-Cril (2002c) Share [httpwwwratingfundorgspanishdocsRF_SHAREpdf] (availability date October 7 2004)
M-Cril (2002d) TSKI [httpwwwratingfundorgspanishdocsRF_Tski_mcrilfinal(-) reportpdf] (availability date October 7 2004)
M-Cril (2003a) ASA [httpwwwratingfundorgdocsASA20updatepdf] (availability date October 7 2004)
M-Cril (2003b) BURO [httpwwwm-crilcomburopdf] (availability date October 7 2004)
M-Cril (2003c) EMT [httpwwwratingfundorgdocsEMTpdf] (availability date October 7 2004)
77
M-Cril (2003d) SKS [httpwwwmixmarketorgendemanddemandshowprofileaspett=25ampshowinfo=adjusted] (availability date October 7 2004)
M-Cril (2003d) TPC [httpwwwratingfundorgdocsTPC_Finalpdf] (availability date October 7 2004)
M-Cril (2004b) UPAP [httpwwwratingfundorgdocsUPAP_2004pdf] (availability date October 7 2004)
Microfinanza (2002a) ACME [httpwwwratingfundorgspanishdocsACME_finalpdf] (availability date October 7 2004)
Microfinanza (2002b) BTFF [httpwwwratingfundorgspanishdocsBTFF_RatingReportpdf] (availability date October 7 2004)
Microfinanza (2002c) BESA [httpwwwratingfundorgspanishdocsBESA_RatingReportpdf] (availability date October 7 2004)
Microfinanza (2002d) CAME [httpwwwratingfundorgdocsEvaluacionCAME(-) Finaldoc] (availability date October 7 2004)
Microfinanza (2002e) RFF [httpwwwratingfundorgdocsRFF20finalpdf] (availability date October 7 2004)
Microfinanza (2002f) PSHM [httpwwwratingfundorgspanishdocsPSHM_Reportpdf] (availability date October 7 2004)
Microfinanza (2003) CAJCA [httpwwwratingfundorgdocsCalificacion_Jardin_Azuayo_ratingpdf] (availability date October 7 2004)
Microserve (2003) ENDA [httpwwwmixmarketorgendemanddemandshowprofileaspett=865ampshowinfo=adjusted] (availability date October 7 2004)
Planet Rating (2002a) FONDEP [httpwwwmfratingorgRatingscompleted_ratingshtml] (availability date October 7 2004)
Planet Rating (2002b) PRIZMA [httpwwwmixmarketorgendemanddemandshowprofileaspett=111ampshowinfo=adjusted] (availability date October 7 2004)
Planet Rating (2002c) SWS [httpwwwratingfundorgspanishdocsSWC_reportpdf] (availability date October 7 2004)
Planet Rating (2002d) ZAKOURA [httpwwwratingfundorgspanishdocsRF_Zakourapdf] (availability date October 7 2004)
Planet Rating (2003a) AMSSF [httpwwwratingfundorgdocsPlanetRating_AMSSF_010803pdf] (availability date October 7 2004)
Planet Rating (2003b) FOCCAS [httpwwwratingfundorgdocsPlanetRatingFOCCAS120803pdf] (availability date October 7 2004)
78
Planet Rating (2003c) PADME [httpwwwmfratingorgdocsPlaNetRatingPADME070302_Englishpdf] (availability date October 7 2004)
Planet Rating (2003d) PAPME [httpwwwmfratingorgdocsPAPME_PlanetRating080903pdf] (availability date October 7 2004)
Planet Rating (2003e) VITAL FINANCE [httpwwwmfratingorgdocsVital20Finance_Sept202003pdf] (availability date October 7 2004)
Planet Rating (2004a) ABA [httpwwwratingfundorgdocsABA_April202004pdf] (availability date October 7 2004)
Planet Rating (2004b) ACEP [httpwwwmfratingorgdocsACEPSeacuteneacutegal_2004pdf] (availability date October 7 2004)
Planet Rating (2004c) AGROINVEST [httpwwwratingfundorgdocsAgroInvest_June202004pdf] (availability date October 7 2004)
Planet Rating (2004d) ASBA [httpwwwratingfundorgdocsASBA_April202004pdf] (availability date October 7 2004)
Planet Rating (2004e) DBACD [httpwwwratingfundorgdocsDBACD_April202004pdf] (availability date October 7 2004)
Planet Rating (2004f) FINADEV [httpwwwmfratingorgdocsFinadev_2004pdf] (availability date October 7 2004)
Planet Rating (2004g) MI-BOSPO [httpwwwratingfundorgdocsMIBOSPO_160404pdf] (availability date October 7 2004)
Planet Rating (2004h) SBACD [httpwwwratingfundorgdocsSBACD_PlanetRating300604pdf] (availability date October 7 2004)
Other Sources
Interview Shaw Newaz Deputy General Manager of the Grameen Bank October 30th
2003
Hodson Charles (2001) Your Business Your World Jim Boulden CNN (ed) Dhaka 2001
6
those charged by conventional banks Finally a sample of 39 MFIs will be used to verify
the drawn conclusions by examining the effects their interest rates have on their
financial performances and their repayment record
7
2 The Development of Microfinance
21 What is Microfinance
According to the Journal of Microfinance the term defines what ldquois arguably the most
innovative strategy to address the problems of global povertyldquo4 This view is shared by
the United Nations (UN) which declared that the year 2005 would be the international
year of microcredit5 while their General Secretary Kofi Annan stated in 2002 that
ldquo[m]icrocredit is a critical anti-poverty tool and a wise investment in human capitalrdquo6
Hossain describes microfinance as ldquothe practice of offering small collateral free loans
to members of cooperatives who otherwise would not have access to the capital
necessary to begin a small business or other income generating activitiesrdquo7 This view is
to narrow since it not only excludes such services as saving accounts and insurances8
but also ignores the possibility of collateral demanding MFIs Although it is true that
many MFIs do not take collateral especially if they are focusing on the poorest which
normally do not possess any collateral9 several MFIs in fact do require some form of
collateral10
Roth and Steinwand give a more general definition They describe microfinance as ldquothe
provision of a wide range of financial services like saving accounts loans payment
services and insurances for people with no regular access to financial services through
traditional financial institutionsrdquo11 Here it is important not to confuse the terms
traditional or conventional with the term formal If for example an illiterate beggar
takes a $10 loan from the Grameen Bank in Bangladesh she becomes a client of a
4 See Woodworth and Woller (1999) p 65 See United Nations (1999) p 16 Annan (2002)7 Hossain (2004)8 See The Microfinance Gateway (nd) Robinson (2001) p9 Otero (1999) p 89 See chapter 3 for a more detailed discussion on poverty10 See Robinson 2002 p 24311 See Roth and Steinwand (2004) p 2 ldquodie Bereitstellung einer breiten Palette von Finanzdiensteistungen wie Spareinlagen Kredite Zahlungsverkehr und Versicherungsleistungen fuumlr Wirtschaftsakteure die keinen regelmaumlszligigen Zugang zu Finanzdienstleistungen durch klassische Finanzinstitutionen habenldquo
8
formal financial institution (a registered bank) but obviously not of a traditional or
conventional one12
Although the other services have become more important in recent years microcredit is
still considered their central service by most MFIs In many countries it refers to loans
below $ 100013 however for significant cross country comparison it is more
meaningful to look at the ratio of the loan amount to the gross national product (GNP)
or gross domestic product (GDP) per capita for the respective countries While a loan of
$1000 is more than four times larger than the GNP per capita in Uganda it represents
less than 20 of the GNP per capita in Mexico The MicroBanking Bulletin (MBB) has
categorized the target market for MFIs by the average outstanding loan amount as a
percentage of the GNP per capita ranging from Low-end (less than 20) to Small
Business (more than 250)14 Especially for the latter category one must to look closely
at the condition of the financial service market where an institution is active Although
MFIs exist in industrialized countries15 one would definitely turn to a traditional
financial institution for a loan bigger than 250 of the GNP per capita and therefore not
to a MFI according to the definition presented above
22 The Origin of Microfinance
Although neither of the terms microcredit or microfinance were used in the academic
literature nor by development aid practitioners before the 1980s or 1990s16
respectively the concept of providing financial services to low income people is much
older
While the emergence of informal financial institutions in Nigeria dates back to the 15th
century17 they were first established in Europe during the 18th century as a response to
the enormous increase in poverty since the end of the extended European wars (1618 ndash
12 See Yunus (2002) p 19 for a more detailed description of the destitute member program of the Grameen Bank which focuses exclusively on persons with no regular income and no assets at all 13 See MicroBanking Bulletin (1997) p 614 See MicroBanking Bulletin (2003) p 5415 See Yunus (1998a) pp 229 et sqq16 See Robinson (2001) p XXX17 See Seibel (2003a) p 12
9
1648)18 In 1720 the first loan fund targeting poor people was founded in Ireland by the
author Jonathan Swift19 After a special law was passed in 1823 which allowed charity
institutions to become formal financial intermediaries a loan fund board was established
in 1836 and a big boom was initiated Their outreach peaked just before the government
introduced a cap on interest rates in 1843 At this time they provided financial services
to almost 20 of Irish households20
The credit cooperatives21 created in Germany in 1847 by Friedrich Wilhelm Raiffeisen
served 14 million people by 191022 He stated that the main objectives of these
cooperatives ldquoshould be to control the use made of money for economic improvements
and to improve the moral and physical values of people and also their will to act by
themselvesrdquo23
In the 1880s the British controlled government of Madras in South India tried to use the
German experience to address poverty which resulted in more than nine million poor
Indians belonging to credit cooperatives by 194624 During this same time the Dutch
colonial administrators constructed a cooperative rural banking system in Indonesia
based on the Raiffeisen model25 which eventually became Bank Rakyat Indonesia
(BRI) now known as the largest MFI in the world26
23 Microfinance after the Second World War
Because of further prudential regulation and effective supervision eg through bank
superintendencies the banking sector in the now developed world experienced
continuous growth Today the vast majority of the citizens of the industrialized
countries have access to financial services with many of them being customers of
former MFIs27
18 See Steinwand (2001) p 5119 See Robinson (2002) p 9620 See Seibel (2003a) p 1021 first known as Darlehnsvereine and now called Raiffeisenbanken22 See Morduch (1999a) p 157323 Raiffeisen (1966) quoted in Richardson (2000) p 324 See Morduch (1999a) p 157425 See Robinson (2002) p 9726 See Roth Steinwand (2004) p 327 See Seibel (2003a) p 11
10
This is not true for most developing countries where market penetration of financial
institutions is far from reaching the majority of the inhabitants (see chapter 4) A variety
of reasons is responsible for this including that the banking sector in the most
developing countries have developed in a very different way to than those in
industrialized countries
One of the most important reasons is that in contrast to the industrialized countries little
attention has been paid to the legal recognition prudential regulation and effective
supervision of informal financial institutions28 This insecure legal environment leads to
several problems Since the regulatory framework for mobilizing savings often does not
fit the needs of institutions targeting low income people many organizations are not
permitted to do so and are therefore missing funds to on-lend as credit29 An additional
problem is the lack of a deposit insurances This not only increases the risk of a bank
run but also keeps people from depositing their savings in a financial institution30 In
addition inappropriate interest rate ceilings prevail in many countries While politics
claim they are lowering the interest rates charged to the poor they de facto only limit
their access to financial services (see chapter 5)31
Another problem that retarded the growth of the financial sector in developing countries
was the supply-leading finance theory which dominated the development strategies of
many countries after the second world war32 This theory ldquo refers to the provision of
loans in advance of the demand for credit for the purpose of inducing economic
growthrdquo33 Since it was believed that poor people were neither able to save (and thus
dependent on outside funding) nor capable of paying commercial rates of interest
massive subsidized credit programs were established34 The results were alarming
Repayment rates often did not exceed 50 percent and some government financed
programs even had default rates of more than 90 percent35 The main reason being that
credit was not provided according to business management principles but instead
28 See Seibel (1998) p 829 See Robinson (2001) p 4930 See Staschen (1999) p 1431 See Gibbons (2000) p 1532 See Morduch (1999a) p 157033 Robinson (2001) p 14034 See Borst (2004) pp 33 et sqq35 See Yunus (1998a) p 154 Robinson (2001) p 145
11
according to political objectives Therefore receiving loans was seen as a reward for the
constituents rather than as a business transaction Most of the funds earmarked for the
poor also never reached them ending up instead in the hands of the local elites
Attracted by the below market interest rates and the possibility not to pay back at all
these groups lobbied to be treated privileged and often used the money received for
consumption or for on-lending at higher rates36 But subsidized credit not only
encouraged corruption it also discouraged sustainable financial institutions since they
could not compete with interest rates that were not aimed to cover all costs and were
sometimes even lower than the interest paid on savings37 The low or negative spread
also worked as a negative incentive to institutionsrsquo effort to mobilize savings which in
turn intensified the problem of credit rationing (see chapter 5)
24 Microfinance Today
In the 1970s a paradigm shift started to take place The failure of subsidized government
or donor driven institutions to meet the demand for financial services in developing
countries let to several new approaches Some of the most prominent ones are presented
below
Bank Dagan Bali (BDB) was established in September 1970 to serve low income people
in Indonesia without any subsidies and is now ldquowell-known as the earliest bank to
institute commercial microfinancerdquo38 While this is not true with regard to the
achievements made in Europe during the 19th century it still can be seen as a turning
point with an ever increasing impact on the view of politicians and development aid
practitioners throughout the world In 1973 ACCION International a United States of
America (USA) based non governmental organization (NGO) disbursed its first loan in
Brazil39 and in 1974 Professor Muhammad Yunus started what later became known as
the Grameen Bank by lending a total of $27 to 42 people in Bangladesh40 One year
later the Self-Employed Womenrsquos Association started to provide loans of about $15 to
36 See Robinson (2001) pp 144 et sqq37 Before BRI underwent a major transformation in 1983 a negative spread between interest rates on loans and savings existed While the bank lent at a 12 annual effective interest rate it paid 15 on savingsSee Robinson (2001) p 10638 Wardhana (2001) p XXVII39 See ACCION (nd)40 See Yunus (1998a) p 16 et sqq
12
poor women in India41 Although the latter examples still were subsidized projects they
used a more business oriented approach and showed the world that poor people can be
good credit risks with repayment rates exceeding 9542 even if the interest rate charged
is higher than that of traditional banks Another milestone was the transformation of
BRI starting in 1984 Once a loss making institution channeling government subsidized
credits to inhabitants of rural Indonesia it is now the largest MFI in the world being
profitable even during the Asian financial crisis of 1997 ndash 199843
In February 1997 more than 2900 policymakers microfinance practitioners and
representatives of various educational institutions and donor agencies from 137
different countries gathered in Washington DC for the first Micro Credit Summit This
was the start of a nine year long campaign to reach 100 million of the world poorest
households with credit for self employment by 200544 According to the Microcredit
Summit Campaign Report 67606080 clients have been reached through 2527 MFIs by
the end of 2002 with 41594778 of them being amongst the poorest before they took
their first loan45 Since the campaign started the average annual growth rate in reaching
clients has been almost 40 percent46 If it has continued at that speed more than 100
million people will have access to microcredit by now and by the end of 2005 the goal
of the microcredit summit campaign would be reached As the president of the World
Bank James Wolfensohn has pointed out providing financial services to 100 million of
the poorest households means helping as many as 500 ndash 600 million poor people47
41 See Bhatt (1997)42 See Yunus (1998a) p 143 et sqq43 See Robinson (2002) p 38044 See Daley-Harris (2003) p 345 ldquoThe Microcredit Summit Campaign defines ldquopoorestrdquo as those who are in the bottom half of those living below their nationrsquos poverty line or are living on less than $1 a day adjusted for purchasing power parity (PPP)rdquo See Daley-Harris (2003) p 3 This definition will also be used throughout this paper46 See Daley-Harris (2003) p 1847 See Morduch (1999a) p 1570
13
3 The Impact of Microcredit
31 Microcredit and the Millennium Development Goals
In 1996 Ismail Serageldin the then chair of the Consultative Group to Assist the Poorest
(CGAP)48 claimed that ldquo[m]icrofinance is a proven instrument to assist the very poorrdquo49
This view is also shared by the World Watch Institute50 and underlines what has been
stated above namely that microfinance can be used as a strong anti-poverty tool But
does microfinance actually meet these expectations and keep this promise51
The impact that microcredit has on the lives of poor people will be demonstrated by
showing how it contributes to each of the eight Millennium Development Goals
(MDGs)52 which are related to the reduction of poverty in all its forms These goals
were resolved in September 2000 by the General Assembly of the UN in their
Millennium Declaration53
32 The Eradication of extreme Poverty and Hunger
The aim of the first MDG is to halve the proportion of people who live on less than $1 a
day between 1990 and 2015 According to current population projections of the World
Bank54 this would equal 849 million people in 201555
48 The Consultative Group to Assist the Poorest is a consortium of 28 public and private development agencies working together to expand access to financial services for the poor in developing countries and was established by the World Bank in 1995 Recently it changed its name to Consultative Group to Assist the Poor49 See Serageldin (1996) p 1150 See Gardner (2002) p 1851 See Morduch (1999a) pp 1569 et sqq52 The Millennium Development Goals are (1) eradicate extreme poverty and hunger (2) achieve universal primary education (3) promote gender equality and empower women (4) reduce child mortality (5) improve maternal health (6) combat HIVAIDS malaria and other diseases (7) ensure environmental sustainability and (8) develop a global partnership for development53 See United Nations (2000)54 See World Bank (2004) p 38 et sqq55 Although it is not explicitly mentioned in the Millennium Declaration it is commonly assumed that the share of people living on less than $1 in low and middle income countries should be halved If the share would be calculated with regard to the worldrsquos total population the goal for 2015 would 818 million people For the worldrsquos total population in 1990 see US Census Bureau (2004)
14
Today almost 11 billion people live on less than $1 and more than 27 Billion live on
less than $2 per day56 The mean income for those living under $1 a day is $077 and it
is $125 for those living under $2 a day57 While the number of people living on less
than $1 per day is slowly decreasing and is expected to be 913 million in 2015 the
number of people living on less than $2 a day is actually increasing58 One of the
outcomes from this degree of poverty is that more than 27000 children die every day
from mostly preventable diseases many of them related to hunger59
Microcredit enables poor people to start new businesses or to diversify existing ones
which helps them to increase their income In addition to large amounts of anecdotal
evidence several studies have documented the positive economic impact microcredit
has on its clients Cloud and Panjaitan-Drioadisuryo have found that the average income
of a sample of BRI borrowers has increased by 112 percent and that 90 percent of their
families have crossed the poverty line60 Only 12 out of the 121 respondents of that
study reported that their income had not increased61 According to the Grameen Bank
website 5109 percent of their clients have crossed the poverty line since they took their
first loan62
A study conducted by Barnes showed that the program of the Zambuko Trust a local
MFI in Zambia had a considerable impact on the poorest clients consumption of meat
fish and chicken63 While 76 percent of the continuing clients of the MFI called Share in
India significantly increased their income and 50 percent have crossed the poverty line 64 Khandker discovered in his well known study ldquoFighting poverty with microcreditrdquo
that there is a connection between the microcredit programs of three Bangladeshi MFIs
and household per capita expenditure For every dollar borrowed by a Grameen Bank
member household consumption increases by $018 In addition he found that 5 percent
56 See Chen and Ravallion (2004) p 2957 In fact those people live on less than $108 and $215 respectively a day in 1993 PPP This means that the nominal dollar value of their income is considerably lower See Chen and Ravallion (2004) p 9 58Both numbers are decreasing in Asia but increasing in the rest of the world See Chen and Ravallion (2004) p 22 et sqq59 See UNICEF (2002) p 660 A consistent definition of the term ldquopoverty linerdquo does not exists among different nations Therefore the term will be used according to the definition of the respective country in this paper61 See Panjaitan-Drioadisuryo and Cloud (1999) p 77562 See Grameen Bank (2004) 63 See Barnes (2001) p 8664 See Simanowitz and Walter (2002) p 16
15
of Grameen Bank borrowers move out of poverty every year65 Supposing Khandkerrsquos
findings were correct for all MFIs worldwide and the Microcredit Summit Campaign
achieved its goal of reaching 100 million of the poorest households with microcredit by
2005 then 25 million people (assuming an average family size of five) would leave
poverty every year66 Although this number would have to be adjusted in order take into
consideration the MFI clients who have crossed the poverty line already and of course
the experiences made in Bangladesh can not be transferred precisely to other countries
it still demonstrates the enormous effect that microcredit can have on assisting the
poorest to move out of poverty
Although a 1996 study of Hulme and Mosley states that providing microcredit can also
have a negative impact on the income of the poorest households67 these findings can
be considered as disproved by the recent bulk of evidence drawing favorable
conclusions68
33 Achievement of universal primary Education
The aim of the second MDG is to ensure that all children will be able to complete
primary school by 2015
Currently more than 100 million children most of them girls are not in school69
Besides school fees poor households often can not afford to send their children to
school because they need them to help in the family business
Microcredit programs mainly contribute to the second MDG by increasing families
income and therefore enabling parents to send their children to school Barnes Gaile
and Kibombo found that clients of an MFI in Uganda spent significantly more on
childrenrsquos education than non-clients70 and in Zambia Barnes showed that ongoing
participation in the Zambuko Trustrsquos program had a positive impact on the members
65 See Khandker (1998) p 5666 See Daley-Harris (2003) p 2467 See Hulme and Mosley (1996) p 180 et sqq 68 See Gibbons and Meehan (1998) p 13669 See UNICEF (2002) p 2270 See Barnes Gaile and Kibombo (2001) p 64
16
children staying in school71 In Bangladesh the probability of girls enrolling in school
increased by 19 percent for every 1 percent increase in Grameen Bank loans to female
clients For boys this number was even higher with the mean being 24 percent72
34 Promote gender Equality and empower Women
The aim of the third MDG is to eliminate the disparity in the ratios of girls to boys in
primary secondary and tertiary education in the ratio of literate females to males and to
increase the share of women in the labor market and in parliament73
At present the literacy rate for women is lower than for man all over the world
According to the Human Development Report 2004 the average female literacy rate as
a percentage of male literacy rate is 759 in developing countries and is as low as 37 in
Niger74 But women are not only discriminated against in education but also in access to
medical services and therefore have a higher mortality rate than man75 The worldwide
tendency for women to be underrepresented in the labor market and in the parliaments is
even more severe in developing countries76 Although several women have become
heads of state in various Asian countries (eg Bangladesh India and Indonesia) this is
probably due to them being wives or daughters of former respected male politicians
Since women have a higher repayment rate than man77 and also tend to invest increases
in income on the household and on their children rather than on themselves78 most
MFIs prefer female clients79 Therefore they empower women in many ways Often
MFIs not only encourage women to become involved in financial transactions for the
first time but also to become independent active members of the economy and to
acquire assets in their own names Cheston and Kuhn found that 68 percent of the
women participating in an MFI program in Nepal ldquohellip experienced an increase their
71 See Barnes (2001) p 8472 See Khandker (1998) p 4973 See World Bank (2001) p 2074 See UNDP (2004) pp 225 et sqq75 See Sen (2000) p 23276 See Sen (2000) pp 242 et sqq77 See Littlefield Morduch and Hashemi (2003) p 778 See Yunus (1998a) pp 116 et sqq79 According to the Microcredit Summit Campaign Report 79 or 37677080 of the poorest clients were women See Daley-Harris (2003) p 3
17
decision-making roles in the areas of family planning childrenrsquos marriage buying and
selling property and sending their daughters to school - all areas of decision making
traditionally dominated by menrdquo80 The program of the Lower Pra Rural Bank in Ghana
had an positive impact on womenrsquos participation in the community81 which is true as
well for the CRECER program in Bolivia82 In Bangladesh the Grameen Bank and the
Bangladesh Rural Advancement Committee (BRAC) the two biggest MFIs of the
country had a significant positive effect on womenrsquos empowerment measured through
eight different indicators83 After joining Grameen Bank only 21 percent of the female
members considered themselves as unemployed while this number was 50 percent
before joining84 According to the Grameen Bank website 93 percent of the Bankrsquos
shares are owned by their borrowers which elect the members of the board every three
years They also get familiar with the election process by more frequently voting for
representatives at the lower level of the organizational structure Partly because of this
experience they are more likely to run for public office In the 2003 local government
elections Grameen Bank members constituted 24 of the seats reserved for women
while they represent less than 10 of Bangladeshi adult female population85 Female
clients of MFIs from countries like the Philippines Bolivia and Nepal have reported
similar occurrences86
35 Reduce Child Mortality and improve Maternal Health
The aim of the fourth MDG is to reduce the under-five mortality rate by two-thirds
between 1990 and 2015 and the fifth MDG strives for a three quarter reduction in the
maternal mortality ratio by the same date
As has been stated above more than 10 million children are dying annually in the
developing world of mostly preventable causes with malnutrition playing a role in over
80 See Cheston and Kuhn (2002) p 1881 See MkNelly and Dunford (1998) p 5482 See MkNelly and Dunford (1999) p 7183 The eight different indicators are ldquofreedom of movement economic security ability to make small and larger independent purchases participation in important family decisions relative freedom from domination by the family political and legal awareness and participation in political campaigning and public protestsrdquo Hashemi and Schuler (1998) p 3684 See Holcombe (1995) p 5185 See Grameen Bank (2004)and CIA (2004)86 See Littlefield Morduch and Hashemi (2003) p 8
18
half of the childrsquos deaths and in over 50 countries child mortality rates are greater than
100 deaths per 1000 live births87 Maternal mortality is also a significant problem in the
developing world with more than 500000 women dying every year from pregnancy
related causes88
MFIs are mainly contributing to the these MDGs by increasing families income and
therefore enabling the households to afford better nutrition and medical services
Furthermore they are often linked with microinsurance or health education programs
In addition to what has been showed in chapter 31 Pitt Khandker and Millimet
estimate that a 10 percent increase in the loan size of a female borrower in Bangladesh
increases the arm circumference of their daughters by 6389 Smith and Jain found that
village banking in Ecuador had a positive effect on child diarrhea90 which is responsible
for 15 of child deaths91 Since Sen argues that an improved status of women within
the family reduces child mortality92 the empowerment of women through MFIs is also
contributing to this cause
Although no study has been conducted so far on the direct impact of microcredit on
maternal health it can be assumed that an overall improvement of access to medical
services reduces maternal mortality as well A study of the Morgan State University for
example suggests that microcredit has a positive effect on the prevalence of
contraceptives93 which leads to a decrease of unwanted pregnancies and therefore
reduces maternal death
36 Combat HIVAIDS Malaria and other diseases
The aim of the sixth MDG is to halt and begin to reverse by 2015 the spread of
HIVAIDS malaria and other major diseases and to assist children orphaned by HIV
87 See World Bank (2001) p 888 See WHO (2004) 89 See Pitt Khandker and Millimet (2003) p 11390 See Smith and Jain (1999) p 3791 See WHO (2001) 92 See Sen (2000) p 23593 See Amin et al (2001) p 1614
19
In 2003 29 million people died because of HIV and about 48 million became infected
the greatest number since AIDS was discovered 23 years ago94 This pandemic has lead
to a tremendous decrease in the life expectancy in the hardest hit countries Botswana
for example one of the richest and most democratic countries in Africa has a
HIVAIDS adult prevalence rate of 388 and a life expectancy at birth of less than 31
years95
Malaria not only causes more than one million deaths annually it leads also to 300 ndash
500 million clinical cases a year Both numbers have been steadily increasing over the
past two decades96 More than two million people a year are killed by tuberculosis
another global health problem This curable disease is estimated to cost poor
communities about $12 billion every year since even those who survive normally lose
more than 3 month of work time while recovering97
MFIs contribute to the sixth MDG in several ways By increasing clientrsquos income they
help households affected by HIV or other diseases to better cope with the situation
Besides spending more money on health services and nutrition MFI clients also tend to
be more able and willing to support AIDS orphans than non clients98 In addition to the
already stated increase in the use of contraceptives99 several innovative approaches to
deal with disease related crisis have also arisen This is of course necessary not only to
counteract the devastating effect the above discussed epidemics can have on MFI
clients but also to not put the viability of the respective institution at risk One option is
to integrate education services in the MFI programs and encourage clients to form
solidarity groups100 It has been shown that these services do not necessarily decrease
the effectiveness of the institutionsrsquo employees101 Another way is to strengthen the ties
to NGOs specialize in dealing with the respective disease Synergies gained through this
cooperation can help clients to better deal with the situation and in the end increase their
94 See UNAIDS (2004) p 2395 See CIA (2004)96 See World Bank (2001) p 1697 See World Bank (2001) p 1298 See Barnes (2001) p 6499 See also Kim et al (2002) p 18100 See Donahue and Sussman (1999) p A 14101 See Donahue Kabbucho and Osinde (2001) p 25
20
repayment rates Various MFIs also have introduced loan and health insurance products
or cultivated linkages with organizations doing so102
It has to be stated that despite the benefits MFIs can provide to people effected by
HIVAIDS or other diseases microcredit can also be a burden for those who are already
chronically ill These people can still benefit through loans provided to members of the
family or the community or through one of the other services mentioned above
37 Ensure environmental Sustainability
The aims of the seventh MDG are to support and promote the principles of sustainable
development and put them into action and to improve the lives of slum dwellers and
people without sustainable access to safe drinking water and sanitation
Today climate change is considered as the major environmental problem103 The
Intergovernmental Panel on Climate Change (IPCC) states that human activities
contribute to most of the 06 degC increase in global average temperature over the 20th
century and the predicted increase of another 14 to 58 degC between 1990 and 2100104
Emission of carbon from fossil fuel is reported to have the dominant influence on this
development While the total emission was 16 billion tons in 1950 it was already 65
billion tons in 2000 and is expected to continue to grow105 This development would
lead to a rise in the average sea level of between 9 and 88 centimeters during the next
century106 Furthermore it is predicted that global warming increases the risk of extreme
events like cyclones or floods leads to an increase in the number of people infected by
diseases like malaria and decreases the potential crop harvest and water availability
especially in developing countries107 In 2000 already 11 billion people lacked access to
clean drinking water and 24 billion to basic sanitation108
102 See Barnes (2001) p 40 Barnes Gaile and Kibombo (2001) p 13 and Grameen Bank (2004)103 See Gardner (2002) p 5104 See IPCC (2001) pp 2 et sqq105 Worldwatch Institute (2002) p 52 et sqq106 See IPCC (2001) p 16107 See Dunn and Flavin p 29108 See UNFPA (2004) p 18
21
MFIs contribute to achieving the seventh MDG in several ways By providing loans for
the purchase of renewable energy technologies they help people in developing
countries to increase their per capita energy consumption without increasing the carbon
dioxide emission In a 2003 survey of 140 MFIs from 80 different countries 21 said
they provide credits for solar home systems and another 19 stated they are interested in
becoming engaged in this business109 While Grameen Shakti a rural energy service
company cooperating with the Grameen Bank in Bangladesh has already installed more
than 23000 solar home systems110 a 2000 World Bank study reports twelve projects
providing solar home systems to rural households with a target of 500000
installations111 It has also been suggested that MFIs should raise environmental
awareness among their clients112 but so far no data is available on how staff can cope
with this additional task Many MFIs also provide loans for improvements in sanitation
and the water supply of their clients Varley gives several examples from Africa Asia
and Latin America on how microcredit not only has helped to invest in rainwater
collection systems but also how it has enabled households to increase their water
supply through community water associations113 In addition many MFIs provide credit
for the construction of sanitary latrines114 The situation of slum dwellers is also
positively effected by MFIs Directly through their services in poor urban communities
and indirectly by creating jobs in rural areas and therefore easing the pressure on urban
labor markets
38 Develop a global Partnership for Development
The eight MDG is about the means to achieve the other seven MDGs It calls for all
players involved in the endeavor of development and poverty eradication to work as
partners in a global context
Again MFIs are contributing to the eight MDG in many ways This is occurring through
international networks that provide funding and technical assistance through internet
information portals and specialized journals through social and for profit investors and
109 See Wimmer and Barua (2004) p 174110 Barua (2004) 111 See Martinot and Cabraal (2000) p 6112 See Pallen (1997) p 11 Lal (nd)113 See Varley (1995) pp 39 et sqq114 See Jalvaani (1999) pp 1 et sqq Varley (1995) pp 39 et sqq
22
specialized rating agencies The Bangladesh-based Grameen Trust is one of around 30
networks in operation Besides collaborating with over 200 MFIs around the world it
has directly operated three projects in Afghanistan Kosovo and Myanmar115 While the
ACCION network serves almost 12 million active clients in 19 countries throughout
America and sub-Saharan Africa116 FINCArsquos network operates in three different
continents where it serves more than 200000 customers117 In November 1997 the
MicroBanking Bulletin (MBB) was first published by the microfinance program at the
Economic Institute at the University of Colorado118 Its aim is to develop a database on
the financial performance of MFIs from all over the world which is now available
through the Mix Market an internet portal that also provides information about more
than 300 MFIs investors donor institutions and other related development
organizations119 Two years later the Marriott School at Brigham Young University
started to publish the Journal of Microfinance which has an editorial board of
microfinance experts from all over the world and offers the latest research on this
topic120 In the late 1990s a number of companies became attracted by the microfinance
market and started to invest in MFIs The German based Internationale Mikro
Investitionen Aktiengesellschaft (IMI) for example has already invested more than euro46
million in 19 MFIs in four different continents and plans to invest another euro27 million
before October 2004121 BlueOrchard Finance a microfinance investment consultancy
has channeled more than $60 million worth of private capital to some 40 MFIs
worldwide through investment funds and bond issues122 Big commercial banks like
Citigroup Deutsche Bank and ABN Amro also started to get involved in the
microfinance sector although this is mainly still perceived as a public relation activity
and not as a for-profit investment123 There are also several rating agencies specializing
in MFIs Dependent on their rating these institutions can help MFIs to receive money
from donors or investors Four of the most prominent rating agencies are PlanetFinance
115 See Grameen Trust (nd)116 See ACCION (nd)117 See FINCA (nd)118 See MicroBanking Bulletin (1997) p 5119 See The Mix (2004)120 See Woodworth and Woller (1999) p 6121 See IMI (2004)122 See BlueOrchard (2004b) p 3123 See Busch and Kort (2004) p 8 Fischer (2003) p 6
23
with headquarters in France M-Cril based in India Microfinanza in Italy and
MicroRate with offices in the USA and South Africa124
124 See Microfinance Rating and Assessment Fund (2004)
24
4 Microcredit Outreach
41 The Demand for Microcredit
Although it has been shown that microcredit is one of the most effective poverty
eradication tools that it is considered a human right by some of its advocates125 and it
can contribute considerably to the development of the financial sector in developing
countries an enormous gap still exists between supply and demand for microcredit
Estimates on the demand for microcredit vary greatly While USAID estimates the
number of potential microfinance clients is between 100 and 200 million126 the
Microcredit Summit Campaign states the total demand is more than 234 million
people127 CGAP recognizes some 500 million micro-entrepreneurs who have the
potential to become customers of MFIs128
Marguerite Robinson calculates the demand as follows ldquoAssuming five people to a
household among the 45 billion people living in low- and lower-middle-income
economies in 1999 (World Bank World Development Report 20002001) there are 900
million households in those economies If estimating conservatively we assume that
informal commercial moneylenders supply credit to 30 percent of these households at
least once a year this would mean that there are 270 million households borrowing
from informal moneylenders in a year Undoubtedly however many of these
households borrow multiple times within a yearrdquo129 Although this is a very rough
estimate assuming big differences in demand for microcredit in different countries the
number seems to be the most meaningful In contrast to the estimate of the Microcredit
Summit Campaign it does not include every single household living on less than $1 a
day but according to the definition presented in chapter 1 it counts everyone who has
no regular access to traditional financial institutions but demands such services
Obviously not all people who draw on moneylenders have financial needs that could be
matched through MFIs On the other hand interest rates charged by moneylenders tend
125 See Yunus (1998b) 126 See Christen et al (1995) p 15127 See Daley Harris (2003) p 22 128 See Robinson (2001) p 26129 See Robinson (2001) p 215
25
to be considerably higher than those of MFIs The former normally charge effective
monthly rates between ten and several hundred percent per month the latter generally
charge between 15 and five percent which enables them to attract additional clients130
42 The Supply of Microcredit
In spite of the impressive growth of MFIs around the world the demand for microcredit
is far from being met and this it is not likely to change in the near future The
Microcredit Summit Campaign reported that by the end of 2002 67606080 clients131
were reached through MFIs and that this number has increased by almost 40 percent
annually for the last five years132 It is likely that this tremendous speed of growth is at
least partly due to including MFIs which have not been reporting to the Campaign from
its start in 1997 although they have already existed at that time These institutions
contributed 22 percent to the growth in poorest clients in 2000 578 percent in 2001 and
338 percent in 2002 The growth of the poorest clients increased at least party because
of an expanded definition of the term ldquopoorestrdquo133 Since the contribution of MFIs
which previously have not been considered can be expected to decrease dramatically
the growth rate as stated by the Microcredit Summit Campaign can not be used to
predict the future development of the microfinance sector Another factor likely to slow
down the growth is the concentration of microfinance activities in some Asian countries
where almost 90 percent of the poorest microfinance clients live today134 Even if one
takes into consideration the relative size of Asiarsquos population and the fact that many
MFI customers in Latin America are relatively better off and therefore are not included
in this numbers the coverage of this part of the world far exceeds the others In
Bangladesh for example the microfinance market is close to saturation More than
eleven million households were served by several hundred MFIs in 2001135 Among
them are Grameen Bank and BRAC two of the best known MFIs in the world both
providing their services to more than three million customers With an average
household size of five it can be assumed that in Bangladesh the number of people
130 See Gibbons and Meehan (1999) pp 144 et sqq131 41594778 of them belonged to the poorest before they took their first loan The relative numbers in the following are for these poorest clients only since no other current data was available It can be assumed though that this works as a good proxy for the total number of clients 132 See Daley Harris (2003) p 3133 See Daley Harris (2003) p 17134 See Daley Harris (2003) p 21135 See Ahmed (2003)
26
benefiting from microcredit already surpasses the number of people living below the
poverty line which is estimated to be slightly higher than 50 million136 Therefore
Bangladesh will not contribute to the growth of the microfinance sector as much as it
has done in previous years This is also true for Vietnam Thailand and to a lesser
extent Indonesia Eight of the nine MFIs serving more than one million clients are based
in these countries while the ninth is based in India where due to its one billion
inhabitants the microfinance market is still far from saturation137 In contrast the
supply in Brazil meets less than two percent of the demand which is estimated to be
about 58 million potential clients138 For these reasons greater amount of future growth
must come from smaller or new MFIs in Latin America India China and especially
Africa where almost 30 percent of the worldrsquos poorest live139
43 Meeting the Demand
To fill the gap between the demand and supply for microcredit tremendous investments
are necessary to increase the loan funds of MFIs and build up their capacity through
upgrading existing institutions or building new ones Again estimates on how much
capital is needed vary greatly with the highest being at more than $300 billion140
In 1997 the Microcredit Summit Campaign estimated that $216 billion would be
needed to achieve their goal of providing microcredit to 100 million of the poorest
households This was calculated in the following way Since some 8 million people
already received microcredit in 1997 another 92 million needed to be reached
Assuming $200 ($150 for loan fund and $50 for capacity building) would be needed per
person for 88 million people in developing countries and $1000 ($500 for loan fund and
$500 for capacity building) would be needed for 4 million people in industrialized
countries the capital required ends up to be $216 billion141 For several reasons this
136 See CIA (2004)137 These institutions are The Grameen Bank BRAC Proshika and the Association for Social Advancement (ASA) in Bangladesh the Vietnam Bank for Agriculture and Rural Development (VBARD) and the Vietnam Bank for the Poor (VBA) in Vietnam BRI in Indonesia Bank for Agriculture and Agricultural Co-operatives (BAAC) in Thailand the National Bank for Agriculture and Rural Development (NABARD) in India See Ahmed (nd) p 1 Llanto (nd) p 337138 See Mezzera (2002) p 23139 See See Chen and Ravallion (2004) p 29140 See Clear Profit (2004) Prisma (2002)141 See The Microcredit Summit (1997)
27
number is not qualified to predict the total amount of capital needed to meet the demand
for microcredit On the one hand it focuses mainly on the low end of the market and
therefore underestimates the average loan fund needed On the other hand it does not
take the increasing capital demand from established MFIs into account A survey of 119
MFIs found that the average loan size to increased from $406 in 2002 to $498 in
2003142 This is mainly due to the fact that MFI clients once they have paid back their
loans usually demand larger ones for the continual development of their businesses
and therefore further increase the demand for capital of established MFIs The Grameen
Bank for example has a ceiling on its loans which increases or decreases depending on
the borrowers performance regarding repayments and savings143 While the maximum
amount for the first loan is fixed at approximately $75144 the largest loan disbursed so
far was $17195145 Thus if one estimates that by now 100 million people are borrowing
from MFIs146 another 170 million need to be reached to meet the estimated demand
Assuming an average of $600 ($400 for loan fund and $200 for capacity building) is
needed for every new client and another $200 is needed for every existing client to meet
the demand for larger loans a total of $122 billion is required This rough estimate
helps to convey the approximate amount of capital needed to meet the demand for
microcredit
So far the demand for funds is being partly met by donors which annually provide
between $500 million and $1 billion147 and through the mobilization of local savings
Obviously the amount of money provided by donors will not be able to meet the capital
demand for microcredit in the short term The mobilization of savings on the other hand
has been extremely successful in some cases with BRI probably being the most
prominent example After adapting commercial principals in October 1984 BRI was
able to raise its deposits from $161060 to more than $32 billion in 2003 which equals
almost two times its current loan portfolio148 Many other MFIs like BDB in Indonesia
142 Own calculations Without BRI the numbers would be $343 and $409 See Appendix 1143 See Grameen Bank (2003) p 13144 The accurate amount is 5000 Taka See Interview with Shaw Newaz145 Grameen Bank (2004)146 According to the data provided by the Daley Harris (2003) an annual increase in MFI clients ofapproximately 25 percent from 31122002 till the 3092004 would be needed to reach 100 million clients by now This rated is considerably below the average of the previous five years (38 percent) Therefore it can be assumed as realistic despite the growth hindering factors presented above147 See CGAP (2003) p 8148 See Robinson (2002) p 273 Mix Market (2004)
28
XacBank in Mongolia the Equity Building Society in Kenya or the Centenary Rural
Development Bank in Uganda also have managed to cover their loan portfolio fully
through internally mobilized resources149 The Grameen Bank is also expected to do so
in the first half of 2005150 In addition to raising much needed capital for on-lending the
provision of saving services can deliver notable social benefits itself151
Despite these impressive achievements even the combination of donor money and local
savings at their current levels will not be able to provide the capital needed to continue
the rapid growth of the microfinance sector Especially in their early years MFIs rely on
outside funding BRI for example needed six years before the amount of locally
mobilized savings surpassed the total amount of outstanding loans During this time
expenses and the loan portfolio were covered through a government grant worth $20
million and two World Bank loans of $5 and $97 million respectively152 It also
benefited from a network of more than 3600 branches which were established
throughout the country during the 1970s and early 80s in order to provide government
subsidized credit in rural areas153
The Grameen Bank also widely known as a best practice MFI has received about $175
million in direct and indirect subsidies between 1985 and 1996154 and continues to rely
on outside funding at below market interest rates This is made possible either through
special loans from the Bangladesh Bank or through offering bonds guaranteed by the
Bangladesh government155 - an option most MFIs do not have BDB might be one of the
very few examples which were able to finance their activities through savings and
commercial loans from the start but its outreach did not reach a large scale nor did it
serve the low end of the market In 2000 after 30 years of operation BDB provides
credit to only 10417 clients with an average loan balance of more than $5000156
approximately eight times the countries GDP per capita157
149 See Mix Market (2004)150 See Grameen Bank (2004)151 See Robinson (2001) pp 263 et sqq152 See Seibel and Schmidt (2000) p 4153 See Robinson (2002) p 180154 See Morduch (1999b) p 8155 See Morduch (1999ba) p 25 et sqq156 See Robinson (2002) p 387157 See CIA (2004)
29
Another problem keeping many MFIs from collecting savings is that they do not want
to become a regulated financial institution or do not meet the criteria in their respective
country and therefore they are simply not allowed to mobilize savings from the public
In summary the examples and numbers presented in this chapter support the argument
that the amount of capital that can be raised through donors and locally mobilized
savings is not enough for continuous rapid growth of the microfinance sector If this
lack of capital is not met through other sources the microfinance sector will fail to
contribute its full potential to the achievement of the MDGs
44 Microfinance and the Capital Markets
Regardless of whether the amount of capital needed for the development of the
microfinance sector is $20 or $300 billion it represents only a tiny fraction of the
worldwide capital markets which are estimated at $30 trillion158 Therefore if the
microfinance industry were able to tap the financial markets it would be able to grow
much faster and soon serve the millions of micro-entrepreneurs which currently can not
develop theirs businesses because of capital constrains Another advantage would be
that scarce donor money currently used for the development of the microfinance sector
could be used for other projects that do not have the potential to draw money from
commercial sources This view is shared by Michael Chu the former CEO of ACCION
who made the following statement in 1998 ldquoMicrofinance today stands at the threshold
of its next major stage the connection with the capital marketsrdquo159 Many attempts have
been made since that time Successful MFIs like BancoSol in Bolivia further
strengthened their ties to the capital markets which in some cases already provide the
majority of their funding160 Microfinance investment advisors like BlueOrchard
Finance have become middlemen for MFIs and the financial markets Nevertheless
these links are still far from reaching major scale Currently only approximately 20
percent of MFIs funding comes from commercial sources161 and the biggest bond issue
dedicated to fund MFIs totals only $40 million In addition these funds mainly end up
158 See Brynjolfsson (2004) 159 Chu (1998) quoted in Robinson (2001) p 23160 See Robinson (2001) p 69161 See Dominiceacute (2004)
30
in established institutions in Latin America or Eastern Europe162 while smaller
organizations only benefit indirectly if at all
162 See Clear Profit (2004) IMI (2004)
31
5 Credit Rationing
Until recently the predominant answer to why commercial banks or venture capital
companies did not invest in the microfinance sector was that the poor are not bankable
Besides lacking education and therefore not being able to deal with formal financial
institutions they were viewed as bad credit risk who were unable to invest the borrowed
money in a way that would allow them to repay the loan and interest at a commercial
rate163 Another reason that kept attention away from the idea of providing financial
services to low income people was the belief that informal moneylenders already met
this demand These skeptics felt affirmed through the poor performance of subsidized
credit programs as described in chapter 22 Although it is true that moneylenders
serve a huge number of people in the developing world they more often than not charge
usury interest rates of up to 20000 percent per month164 While the argument that poor
people are not able to participate in the formal financial market can be overcome by
adapting the services accordingly165 the claim of low returns on their investments is not
only proved wrong by empirical evidence but also contradicts economic theory as will
be shown in chapter 53
51 The imperfect Information Paradigm
A more elaborate explanation for the short supply of financial services to low income
people that can be derived from the imperfect information paradigm based
predominantly on the works of Akerlof166 and Stiglitz and Weiss167 After giving a brief
summary of their argument an adaptation of their findings to the microfinance market
will be presented and subsequently it will be shown how their conclusions can be
overcome
Behind the imperfect information paradigm lies the theory of asymmetric information
which simply states that if two parties conduct a transaction one is likely to have more
163 See Ghatak (1983) p 21 et sqq Yunus (1998) p 102 et sqq Robinson (2001) p 35 et sqq164 See Robinson (2001) p 17165 See Seibel (2003b) p 2 BRAC (2003) pp 15et sqq Yunus (1998) pp 151 et sqq 166 See Akerlof (1970) pp 488 et sqq167 See Stiglitz and Weiss (1981) pp 393 et sqq
32
information than the other and is trying to use that for its own advantage168 Applied to
the banking sector this means that a person applying for credit can better judge the
likelihood of repaying the loan than the bank This is because the borrower has better
knowledge of the market she wants to invest in her skills and her willingness to repay
Moreover the bank might not be able to observe if the borrower uses the loan for the
agreed purpose These occurrences can lead to what is known as adverse selection and
moral hazard In this case adverse selection refers to the problem that banks might
attract borrowers with a low probability of repayment if they can not distinguish
between high and low risk loan applicants Moral hazard occurs after the provision of
the loan when the borrower spends the money on a purpose different to the prescribed
purpose and therefore lowers the probability of repayment This can happen eg by
investing in a more risky project or through spending the money on consumption If the
bank is not able to find a cost effective way to avoid these problems it might raise its
interest rate in order to compensate for the increased risk
Figure 1 Expected Bank Return and the Interest Rate
Source Stiglitz and Weiss (1981) p 394
Since this might discourage low risk borrowers from applying for credit and encourage
borrowers who continue to take loans to invest in riskier projects the share of high risk
168 See Neus (1998) p 85 et sqq
INTEREST RATEI
EX
PE
CT
ED
RE
TU
RN
TO
TH
E B
AN
K
33
borrowers could increase and therefore reinforce the problems stated above Thus
increasing the interest rate beyond a certain point actually leads to a decrease in the
expected return to the lender This context is illustrated in figure 1 with I being the
interest rate which maximizes the expected returns to the bank Obviously the bank
would charge the interest rate I in order to maximize its expected return However this
price for capital was not determined through supply and demand as economic theory
would predict It is conceivable that at the interest rate I the demand for credit exceeds
the supply but even if loan applicants would offer to pay a higher interest rate the bank
would refuse because it associates such a loan with high risk As a result credit might
be rationed169
52 Adaptation to the Microfinance Sector
Through some adaptations this model can also help to explain the lack of funds
provided to low income people In the original model of Stiglitz and Weiss several
assumptions have been made that need to be suspended in order to compare the credit
markets for low and high income people and give an explanation why the latter is
widely neglected by institutional investors
Evidently the assumptions that the amount borrowed is equal for each loan applicant
and that transaction costs170 need not to be taken into account171 are not suitable for this
context While the average loan size of MFI customers is much smaller than that of
clients from traditional banks the transaction costs as a share of the loan are
considerably higher because the lenderrsquos costs for conscientious processing a credit
applications are only slightly smaller for a $50 loan than for a $100000 or a
$10000000 loan
In figure 2 the R(I)large curve represents the return to the bank for large loans with
regard to the interest rate I and the R(I)small curve describes the same correlation for
small loans It is shifts downwards to reflect the assertion that the imperfect information
169 See Stiglitz and Weiss (1981) p 394170 In this paper the term bdquotransaction costsldquo refers to the operating expense ratio as defined by MicroRate It ldquois calculated by dividing all expenses related to the operation of the institution (including all the administrative and salary expenses depreciation and board fees) by the period average gross portfoliordquo See MicroRate and Inter-American Development Bank (IADB) (2003) p 16 171 See Stiglitz and Weiss (1981) p 396
34
paradigm has a more severe effect on poor people than on the better off They are
expected to have less profitable investment opportunities at their disposal172 and
therefore are more likely to invest in riskier projects which increase the probability of
default and hence decrease the expected return to the bank Additionally one might
expect poor people to be more likely than others to spend borrowed money on
consumption instead of an income generating activity particularly if a crisis arises It
seems understandable that food or urgently needed medicine are given priority over
repaying a loan
The second shift downwards is due to transaction costs As stated above they are
relatively higher for smaller loans Obviously transaction costs are incurred in the
provision of a large loan as well but since they are much smaller with regard to the loan
amount they are not included in the diagram for reasons of clarity
Figure 2 The extended Model
Source Own diagram adapted from Stiglitz and Weiss (1981) p 394
172 See Khandker (1998) p 8
INTEREST RATE I
SmallLoans
LargeLoans
Transaction costs
Lack of investment opportunities
R(I)large
R(I)small
EX
PE
CT
ED
RE
TU
RN
TO
TH
E B
AN
K
35
53 Overcoming Credit Rationing for the Microfinance Sector
If the conclusions in chapter 51 hold it is rational for a profit maximizing investor to
neglect the microfinance sector as long as no surplus funds in the market for large loans
exist This finding can help to explain the small amount of money provided to the
microfinance sector from commercial investors On the other hand it has to be stated
that this theory is reflexive as defined by Soros173 It not only explains but also forms
reality since it has the potential to reinforce the view of potential investors that
microfinance is a less profitable business174 Therefore demonstrating under which
conditions microfinance can be profitable and in some cases be more profitable than
traditional businesses is of crucial importance
To provide a fairer view of the microfinance sector a further assumption of the Stiglitz
and Weiss model that needs to be suspended is that all investments made by the
borrowers have the same expected return175 As stated above this contradicts economic
theory which claims ceteris paribus capital productivity decreases while the amount of
fixed capital increases In combination with a low capital endowment micro-enterprises
are usually faced with an excess supply of unskilled labor especially in developing
countries176 Hence small enterprises use far less capital per employee than big business
and therefore their marginal productivity of capital is much higher177 This is intuitive if
one imagines an economic actor who wants to invest several packages of capital
Obviously she would invest the first package where she expects the highest return the
second package where she expects the second highest return and so on Each additional
investment opportunity would lead to lower or at best equal returns178 While this
simplified example has limitations it demonstrates how the marginal productivity of
capital can diminish Although it might actually increase until a certain point179 this can
be expected to be so low in this context that it has no influence on the correlation as
shown in figure 2
173 See Soros (1998) pp 14 et sqq174 See Goodwin-Groen (1999) p 8175 See Stiglitz and Weiss (1981) p 395176 See Perkins et al (2001) pp 95 et sqq177 See Tschach (2000) p 8178 See Rosenberg (2002) p 11179 See Rechard G Lipsey (1979) pp 211 et sqq
36
Figure 3 Marginal Productivity of Capital
Source Dornbusch and Fischer (1995) p 406
Even if good investment opportunities for poor people exist the question remains if it is
possible to distinguish between high and low risk borrowers The problem of adverse
selection is overcome in a cost effective way in many MFIs180 For the better off poor
for example institutions like BRI base their decision on whether or not to approve a
loan by assessing the repayment ability of potential borrowers from their current income
flows and not from the uncertain returns generated by the loan181 Additionally
collateral is used in some cases to attract low risk borrowers182 In contrast to
industrialized countries this is usually not done to cover the potential losses of the
lender but to punish the defaulter and therefore increase her willingness to repay183
Obviously this does not always work for the poorest since they often neither posses any
goods that could work as collateral nor do they have sufficient earnings prior to
obtaining a loan for starting an income generating activity Here the so called group-
lending model can help to identify creditworthy borrowers The most prominent
institution using this approach is the Grameen Bank which only provides credit to
180 See Farrington (2000) p 20181 See Robinson (2001) p 80 Robinson (2002) p 238182 See Bester (1985) p 850 et sqq183 See Schmidt and Tschach (2001) p 15 Robinson (2002) p 244
FIXED CAPITAL 0
MA
RG
INA
L P
RO
DU
CT
IVIT
Y
37
members of a group of five These groups are formed by their members without
interference of the Grameen Bank Although in this particular case no joint liability
exists for the members of the group nobody can receive a new loan if another member
of the group fails to repay on time184 Therefore the group formation work as a
screening process Since the borrowers do not want to risk their ability to obtain further
loans they carefully select with whom to form a group Usually the members know
each other for a long period of time and therefore they can make a meaningful judgment
of each othersrsquo ability to repay the loan Other MFIs even require the members of a
group to mutually guarantee each othersrsquo loans185 While this might further increase
borrowersrsquo efforts to search for trustworthy group members it might also keep potential
borrowers from applying for a loan since she does not want be held responsible for
defaulting members This mechanism enables MFIs to partly pass on the transaction
costs related to the selection of low risk borrowers to the borrowers themselves186
Many MFIs have also largely overcome the problem of moral hazard by creating
incentives to ensure a high repayment rate even among the poorest In some cases their
customers go hungry in order to pay back their loan even though no legal action would
be taken against them if they would refuse to do so187 One way to achieve this is to
build up peer pressure through the formation of groups as described above188 Another
and probably the most important is to limit access to future loans to those borrowers
who repay on time The demand for successive loans is extremely high In a 1996
survey 98 percent of BRI borrowers planed to apply for another loan189 and in 1993
less than 30 percent of Grameen Bank loans went to first time borrowers190 Especially
the poorest highly value the option to reborrow191 and many MFIs see this as their
primary incentive to ensure repayment192 According to Schmidt and Tschach ldquothe net
present value of future access to credit works out to be roughly half the value of the
economic advantage to be gained from the intended non-repaymentrdquo193 This can also
184 See Yunus (1998) p 135185 See Schmidt and Zeitinger (1997) p 6186 See Stiglitz (1990) p353187 Own observation at the Grameen Bank in Bangladesh (2003)188 See Hoff and Stiglitz (1990) p 249189 See Robinson (2002) p 251190 See Khandker Khalily and Khan (1995) p 93191 See Gibbons (2000) p 15 Hashemi and Schuler (1997) p 43192 See Gibbons and Meehan (1999) p 160193 See Schmidt and Tschach (2001) p 16
38
explain the occurrence of a drop in the repayment rate once a MFI is no longer seen as
viable and therefore is not expected to provide loans in the future194
With the help of the described mechanisms MFIs around the world are able to keep
repayment rates high A survey of 69 MFIs from 36 different countries each serving
more than 10000 clients in 2002 found the portfolio at risk (PAR)195 varied between
zero and 231 percent While the average was 36 percent the median was found to be
229 percent196 One of the MFIs included in this sample is BRIs whorsquos 12-month loss
ratio has never exceeded five percent since the start of its transformation in 1984 and
from 1997 to 1998 the ratio actually fell from 22 to 194 percent197 The latter deserves
special attention because the Asian financial crisis reached its peak at that time with
Indonesia being hardest hit as illustrated by a statement from The Economist in July
1998 Even with the fierce competition from its neighbors Indonesia would probably
walk away with the prize for Asias most desperate banking systemrdquo198
The findings that MFIs can adapt their services to low income people in order to ensure
a high repayment rate and that poor people do not lack profitable investment
opportunities are illustrated in figure 4 From this diagram it can be seen that under the
new assumptions the interest rate at which the bank maximizes its return differs for
large (I(l)) and small loans (I(s)) According to the assumption that micro-
entrepreneurs can realize a higher return on their investments the bank can charge them
a higher rate of interest without bearing an increased risk Nevertheless in this example
the bank would still serve the market for large loans first because of the higher
transaction costs for smaller loans
The view as described in figure 4 is shared among most traditional banks and investors
in industrialized as well as in developing countries In addition to neglecting the
possibility of generating profits by offering microcredit themselves199 they also hesitate
to lend to MFIs because they consider their business too risky
194 See Schreiner (1997) p 64195 ldquoPAR shows the real risk of the portfolio by comparing outstanding loan balances for loans with atleast one late payment to the outstanding loan portfoliordquo Gross and de Silva (2002) p 22196 Own calculations See Appendix 2197 See Seibel (2000) p 11198 The Economist (1998) pp 92 et sqq199 Busch and Kort (2004) p 8
39
Figure 4 The extended Model
Source Own diagram adapted from Stiglitz and Weiss (1981) p 394 Tschach (2000)
p 17
This attitude can be observed by comparing the ratio of equity to liabilities which is
considerably higher for MFIs than for conventional banks200 When it comes to MFI
start-ups and those MFIs serving the low end market in remote areas even experienced
microfinance practitioners are skeptical if interest rates that fully recover all costs can
be charged201
Theoretically there are two ways to adjust this model to arrive at a conclusion which is
more favorable with regard to the profitability of microcredit One is to cut the
transaction costs and therefore reduce the downward shift of the R(I)small curve the
other is to allow the bank to further raise the interest rate without experiencing a
decrease in its return This means to increase I(s) and the respective rate of return
While in 2000 Tschach stated that transaction costs vary between 10 and 20 percent for
loans provided through the group lending model and between 15 and 30 percent for
200 See MicroRate and IADB (2003) p 30201 See Volkery (2004) p 33 Gibbons (2000) p 15 Gibbons and Meehan (2002) p 29 Goodwin-Groen (1999) p 8
INTEREST RATE I(l)
SmallLoans
LargeLoans
Transaction costs
I(s)
R(i)large
R(i)small
EX
PE
CT
ED
RE
TU
RN
TO
TH
E B
AN
K
40
individual loans202 it was recommended in 1999 that MFIs should target a range
between 15 and 25 percent203 Some best practices on the other hand have already
achieved single digit numbers Currently BDB might be the most efficient MFI in the
world with transaction costs at just 47 percent in 2001204 Even though the low costs of
BDB have to be acknowledged its achievement has to be put in perspective As stated
above with an average loan balance of more than $5000 it does not serve the low end
market In addition it works in an environment with a high population density which
means that it can reach a relatively large group of borrowers per branch This is a
comparative advantage many Asian MFIs enjoy as can be illustrated by comparing
Bangladesh and Bolivia Both countries are at the forefront of the development of
microfinance in their respective continent but while in Bangladesh more than 1000
people are living per square kilometer the average for Bolivia is only eight205
Therefore it is consistent that the most efficient MFI in Latin America Fondo
Financiero Privado para el Fomento a Iniciativas Economicas has transaction costs of
114 percent206 With an average loan size greater than the annual GDP per Capita this
institution also does not serve the low end market207
Despite the impressive efficiency gains in the described examples most MFIs are far
from achieving these numbers and many are unlikely to reach them due to the
environment within which they work A survey of 67 MFIs from 31 countries found the
average transactions costs in 2002 to be 279 percent with a median of 206 percent208
However even if these institutions were to increase their efficiency to best practice
standards their transaction costs would still be significantly higher than those of
traditional banks providing much larger loans For these banks the respective costs vary
in a range between 05 and 3 percent209 According to this argument charging interest
rates considerably higher than conventional banks is the only way for MFIs to generate
higher returns and hence successfully compete for capital
202 See Tschach (2000) pp 100 et sqq203 See Gibbons and Meehan (1999) p 149204 See M-Cril (2001b) p 4205 See CIA (2004)206 See MicroRate (2004)207 In this paper the term ldquolow endrdquo refers to the definition of the MBB (2003) p 54 Loans worth less than 20 percent of the respective countryrsquos GDP per capita are described that way 208 Own calculations See Appendix 3209 See M-Cril (2004a) p 16
41
6 Interest Rates
61 Setting the right Interest Rate
Before addressing the questions to what extend MFIs can raise their interest rates
without putting the repayment rate or the social benefits of their customers at risk a
basic model will be presented This model will illustrate how a MFI should set their
rates in order to not only cover their costs but also to generate an appropriate profit to
finance further growth and attract additional capital
In 2002 CGAP revised its 1996 paper ldquoMicrocredit Interest Ratesrdquo210 which outlines
the standard method of setting sustainable interest rates for commercially oriented
MFIs According to this model the annual effective interest rate (I) should be calculated
as shown below
(1) I = LL
IIKCFLLTA
minusminus+++
1
With each variable being a decimal fraction of the average outstanding loan portfolio
whereby TA stands for the transaction costs as described above LL represents the
annual loan loss and II stands for investment income eg on liquid assets The cost of
funds (CF) consist of the interest and administrative costs needed to obtain deposits and
commercial loans as well as of the imputed costs on equity due to inflation K stands for
the capitalization rate which represents the net real profit Keeping this rate high is
important to finance the future growth of the loan portfolio This can be either done
through investors attracted by high profitability or through borrowing For the latter an
increase in equity is inevitable since it is required as a safety cushion by lenders
Since this model ignores the timing of cash flows and does not take taxes into account
it has to be regarded as fairly imprecise and hence should not be used for business
planning Nevertheless it can be used for an approximation of the interest rate that a
MFI would need to charge to provide its services as planned In the following I will
210 See Rosenberg (2002) pp 1 et sqq
42
apply this model on a fictitious MFI working in a rural area of Latin America with low
end customers In this setting it seems realistic to estimate transaction costs of 35
percent and loan loss rate of two percent211 If funds were borrowed at commercial
terms their costs can be assumed to equal at least 15 percent of the average outstanding
loan portfolio212 Estimating the capitalization rate is more challenging First the
targeted portfolio growth rate is set at 75 percent This is slightly below the 751 percent
average annual portfolio growth between 2000 and 2002 found by a survey of 25
different MFIs based in Central and South America213 If the extend to which the MFI
can leverage stays constant the loan portfolios growth would be limited by the growth
rate of the equity To express the capital needed for this growth as a share of the loan
portfolio it is necessary to estimate the ratio between the equity and the outstanding
loan amount According to the survey mentioned above the loan portfolios of the 25
Latin American MFIs equal on average 215 times their equity214 With this number the
capital needed to increase the equity by 75 percent would corresponds to approximately
35 percent of outstanding loan amount (075215) Finally the investment income has to
be estimated Since liquid assets that are available short term do not generate high
returns say five percent it does not seem advisable for the MFI to hold more than a
quarter of its loan portfolio in this form Hence the profit generated in this way would
equal 125 percent of the outstanding loan amount Using these numbers the equation to
calculate the annual effective interest rate reads as follows
(2) I = LL
IIKCFLLTA
minusminus+++
1 =
0201
01250350150020350
minusminus+++
= 0875
As a result the MFI would need to charge an annual effective interest rate of
approximately 875 percent on its loans in order to sustainable provide its services and
finance its growth without depending on donor money This rate might decrease once
the MFI matures the growth slows down and cheaper funds become available but it
will stay significantly higher than any rate charged by conventional banks
211 MicroRate and IADB (2004) pp 6 and 16212 See MicroRate and IADB (2004) p 616 and 28213 Own calculation See Appendix 4214 Own calculations See Appendix 5
43
62 Can Micro-Entrepreneurs bear these Rates
Although most MFIs charge rates significantly below 875 percent many critics have
strenuously argued against any rates exceeding those of traditional banks Rosanna
Barbero of Oxfam labeled an interest rate of 52 percent charged by a Cambodian MFI
ldquoludicrous evil and disgusting and stated that ldquo[n]o business in the world can make a
profit at these interest ratesldquo215 The former finance minister of Bangladesh Shah Kibria
even categorized the 20 percent effective rate charged by the Grameen Bank as to
high216 Many practitioners therefore believe in a strong negative correlation between
the interest rate and the demand for loans217 Others have argued more generally that
concentrating on profitability and therefore charging high interest rates diverts MFIs
from serving the poorest218
These views are still shared among many MFI managers donor agencies and especially
investors and politicians While the former are unwilling to charge interest rates for
funds they received ldquocheaplyrdquo (through grants or subsidized loans) and are worried
about undermining their social goals by charging higher rates of interest219 the latter are
reluctant to invest for reasons stated above or impose interest caps to catch the attention
of the public by pretending to protect the poor from usury rates220
In chapter 53 it has been described that micro-entrepreneurs due to their smaller
capital endowment have even better investment opportunities than big business The
extend to which this is true has not yet been answered An indication is the high
repayment rate observed within MFIs around the globe If their customers capital yield
did not exceed the charged interest rate how would they be able to repay According to
Gibbons and Meehan customers of MFIs can generally generate returns of more than
100 percent on their invested capital221 and ldquo[r]esearch in India Kenya and the
Philippines found that the average annual return on investments in microenterprises
215 See Kate and Roeun (2004)216 See Hodson (2001) min 1100217 See Morduch (1999a) p 1594218 See Prisma (2002) p 1219 See Schreiner (1997) p 60 Khandker (1998) p 106 220 See Gross and de Silva (2002) p 32 Jansson and Wenner (1997) p 36 et sqq Campion (2002) p 59221 See Gibbons and Meehan (1999) p 131
44
ranged from 117 to 847 percentrdquo222 Schmidt and Tschach found the marginal
productivity of capital to be as high as 1000 percent for the smallest loans provided by
the Bolivian MFI Caja Los Andes223 These findings are confirmed by the observation
of Rosenberg who found while working as a microfinance consultant for ten years he
never heard of a single MFI having problems to attract clients because interest rates
were too high224
To get a better understanding of the investment opportunities of low income people in
developing countries a typical example on how MFI clients invest their loans is as
follows
Zobair is working as a rickshaw puller in Bangladesh Like most of his colleagues he
does not own the rickshaw he is riding Therefore he has to pay a daily rent of about
$030 to the owner Since his average income of approximately $15 per day is hardly
enough to feed his family he is not able to save the $100 necessary to buy a rickshaw
on his own 225 If he could do so through obtaining a loan his income would increase by
$030 every day because he would not have to pay the rent for the rickshaw anymore
Assuming an average of six working days per week 226 and a life span of the rickshaw
of 5 years his internal rate of return would equal 15324 percent annually227
Consequently any interest rate charged by a MFI would be advantageous to him as long
as it would not exceed 15324 percent228
63 Should the Interest Rate be subsidized anyway
Despite the fact that numerous micro-entrepreneurs are able to generate tremendous
returns on their investment obviously not all are able to use capital in such a productive
way and therefore can not afford microcredit at commercial rates In order to reach
these people as well many MFIs continue to use donor money in order to keep their
interest rates low But even if the problems related to subsidized credit as described in
222 See Helms and Reille (2004) p 3223 See Schmidt and Tschach (2001) p 6224 See Rosenberg (2002) p 10225 This examples draws on observations made by the author in Dhaka (Bangladesh) during 2003226 Obviously extended holidays are not a viable option in this surrounding 227 Own calculation See Appendix 6228 This result is only valid if the loan is repaid in daily instalments For a weekly repayment schedule the interest rate charged by the MFI must not exceed 15119 percent in order to still be beneficial for Zobair
45
chapter 23 do not arise it might still not be the most effective tool to help poor people
as will be illustrated in the following example
A MFI faces two groups of potential clients one with businesses able to generate a
return of 125 percent on borrowed capital and another with a possible returns of 50
percent Assuming budget costs according to equation (2) the institution needs to
charge an interest rate of 875 percent and therefore only serves the former group
Supposed each group consists of 50 members demanding $100 loans the net gains to
society (NGS) could be calculated as follows
(3) NGS = 50 times ($125 ndash $875) = $1875
These gains would be due to the investments of the more profitable group which were
made possible through the loans provided by the MFI The less profitable group would
not borrow since their expected returns are not sufficient to pay for the interest If the
interest rate would be lowered to 30 percent both groups would be able to generate net
gains and therefore borrow from the MFI In order to provide loans at this rate the
institution would need to raise additional capital from non commercial sources The
NGS would be calculated as follows
(4) NGS = 50 times ($125 - $30) + 50 times ($50 - $30) + 100 times ($30 - $875) = 0
While the first terms represent the net gains to the respective groups the last describes
the costs incurred in providing the loans At a rate of 30 percent each loan would need
to be subsidized with $575 Hence the NGS actually fall after the introduction of the
subsidized loan This is due to the fact that the less profitable group is encouraged to
invest in relatively unproductive businesses In addition future growth of the MFI could
be jeopardized due to scarce donor money which is needed to finance the interest rate
subsidy Therefore it seems more advisable to continue to charge a rate of 875 percent
and spend the money used for subsidization on other programs such as health care or
education229
229 In Appendix 7 it will be shown that this result generally holds
46
7 Empirical verification
71 Setting up a Sample
To see if the findings of the previous chapters hold the effects which interest rates
charged by MFIs have on their performance will be analyzed in the following Up to
now such a study does not exist mainly because of a lack of adequate data Most MFIs
do not provide accurate information about the annual effective interest rate they charge
and therefore make an evaluation difficult
In 2002 Rosenberg distinguished eight different categories on how microcredit interest
rates are quoted230 These categories differ in several ways On the contrary to
traditional banks for example it is common for MFIs to state interest rates calculated on
a ldquoflatrdquo balance rather than on a declining one This means that the total loan amount is
used to determine the interest rate ignoring installments paid by the borrowers normally
on a weekly or monthly basis In addition many MFIs charge a certain upfront fee prior
to the loan disbursement require compulsory savings at a lower rate or state their
interest rate for semi annual terms only On the one hand this is done to provide
numbers that are more meaningful to MFI customers who often lack the necessary math
skills to deal with compound interest on the other hand it is done to circumvent interest
rate ceilings imposed by the government231 Another problem is that most MFIs offer
different loan products without itemizing their respective shares to their total loan
portfolio As a result it is not possible to calculate a weighted average even if the rate
stated by the respective MFI could be transformed into an effective interest rate
Usually the portfolio yield is used as a proxy in order to make statements about the
interest rate charged by a certain MFI232 It is generally ldquocalculated by dividing total
cash financial revenue (all income generated by the loan portfolio but not accrued
interest) by the period average gross portfoliordquo233 The advantage of this method is that
even the hidden costs are considered Nevertheless it also has a severe shortcoming by
not taking late or defaulted payments into account Therefore the portfolio yield does
230 See Rosenberg (2002) p 5231 MicroRate (2002) p 8232 See MicroRate (nd)233 MicroRate and IADB (2003) p 39
47
not allow to draw conclusions regarding the correlation between the interest rate
charged by a MFI and its PAR
72 Examining the Sample
Through the appearance of rating agencies specialized in the microfinance sector more
adequate information has become available in recent years While MicroRate only
publishes the portfolio yield of rated MFIs M-Cril Microfinanza Microserve and
Planet Rating actually provide information about the annual effective interest rate for at
least some of the MFIs they analyze Although it is labelled differently from all of the
four institutions234 the term describes what is ldquothe highest income or yield that an
organisation can earn from its portfolio based on the terms of its loansrdquo235
Currently236 reports of 39 different MFIs from 20 countries providing accurate
information about the effective annual interest rate are available to the public This
sample should be used to verify the findings of the previous chapters237 Since a
comparison is made between the performances of MFIs based in different countries and
the ratings have been carried out in different years several adjustments are necessary
First the inflation of the respective country and the respective year(s)238 has to be taken
into account in order to only compare the real rates239 In addition the average
outstanding loan amount per borrower is divided by the respective countryrsquos GDP per
capita Since it can be assumed that ldquoonly the poorer households will be willing to take
the smallest loansrdquo240 this number can be used as a proxy for the poverty level
Although the sample size is far to small to represent the microfinance sector as a whole
and the results are statistically not significant the findings can still be used to underline
the theoretical conclusions drawn in the previous chapters In figure 5 the connection
234 M-Cril uses the name ldquoannual percentage raterdquo See eg M-Cril (2004a) p 25 Microfinanza uses the name ldquoexpected portfolio yieldrdquo See eg Microfinanza (2002c) p 25 Planet Rating uses the name ldquoannual effective interest raterdquo See eg Planet Rating (2004d) p 1 Microserve uses the name ldquotheoretical yieldrdquo See Microserve (2003) p 62235 See M-Cril (2004a) p 25236 As of September 28th 2004237 See Appendix 8 For exchange rates see FXTOP (2004)238 Where necessary a weighted average of the annual inflation rate was used See Appendix 9239 This is done through the following formula ir = (I ndash F) (1 + F100) While ir represents the real annual effective interest rate F represents the inflation rate 240 Morduch (1998) p 1572
48
between the average loan size and the transaction costs as a share of the average loan
portfolio is illustrated
Figure 5 Loan Size vs Interest Rate241
Source Own diagram
000
1000
2000
3000
4000
5000
6000
7000
8000
9000
10000
0 100 200 300 400 500 600
Loan Size
Inte
res
t R
ate
It can be seen that the interest rate is negative correlated to the loans size This can be
explained by the relative higher transaction cost for smaller loans as described in
chapter 52 In order to cover their costs MFIs serving the low end market need to
charge higher rates to their customers than those organizations serving the better off
poor Obviously there are several assumptions to this general finding Especially
striking are the two MFIs with an average loan size of approximately five times their
countries GDP per capita which still high interest rates This occurrence can be
explained by taking a closer look to the respective organizations One was established
less than two years prior to its rating and therefore still bears a lot of start up costs242
241 The equation for the regression line reads as follows Y = -00219X + 365 The correlation coefficient is 014242 See Microfinanza (2002b) p 1
49
the other managed to stay profitable while it almost quadrupled its loan portfolio in the
last two years243
Figure 6 Interest Rate vs PAR244
Source Own diagram
0
5
10
15
20
25
30
35
0 20 40 60 80 100 120
Interest Rate
PA
R
In Figure 6 the crucial correlation between the interest rates charged by a MFIs and its
PAR245 is examined According to the given sample the view of traditional banks and
investors that a higher interest rate leads to a higher default rate does not hold
Obviously one has to avoid to draw the opposite conclusion namely that a high interest
rates decreases the PAR The connection illustrated in figure 6 has to be interpreted as
follows Since high interest rates are related to small loans the low PAR for MFIs
charging high interest rates can actually be explained by the tremendous profitability of
small size investments Despite the high rates their customers are even more likely to
repay
243 See Planet Rating (2003b)244 The equation for the regression line reads as follows Y = -00768X + 68433 The correlation coefficient is 0235245 M-Cril only publishes the PAR for overdues greater than 60 days Therefore these ratios are used as a proxy for the industry standard of 30 days for some Asian MFIs
50
Finally it has to be examined if charging high interest rates actually enables MFI to
generate higher returns Although it can be expected that the combination of a low PAR
and a high interest rate leads to a high profitability it still has to be checked if this is not
outdone by soaring transaction costs Figure 7 illustrates the correlation between the
interest rate charged by a MFI and its financial self-sufficiency (FSS) The latter is the
ldquo[r]atio of total income to total adjusted expenses for the year Adjustments are made
for subsidised cost of funds (relative to market interest rate) equity (with respect to
inflation) and in-kind donationsrdquo246 It can be seen that the regression line actually does
indicate a positive correlation between the interest rate and the profitability of a MFI
Figure 7 Interest Rate vs FSS247
Source Own diagram248
0
20
40
60
80
100
120
140
160
180
0 20 40 60 80 100
Interest Rate
FS
S
246 M-Cril (2004a) p 53247 The equation for the regression line reads as follows Y = 02839X + 8901 The correlation coefficient is 0174248 Since the interest rate the customers of the MFI Foccas have to pay includes fees which are not passed on to the institution its interest rate in this diagram is set at 723 percent instead of the 10715 percent used for figure 6 See Planet Rating (2003b) p 1
51
This result does not necessarily disprove the findings of Stiglitz and Weiss since it can
be argued that MFIs simply do no increase their interest rates to the point where they
would maximize their expected returns But if this would be true why do MFIs not
charge higher rates of interest given the demand described in chapter 41 and 43 In
mature markets competition normally ensures prices not to exceed a certain level but
since many MFIs still operate in a ldquosellerrsquos marketrdquo249 this can not explain the findings
as described in figure 7 Therefore it has to be assumed that a combination of the
unwillingness of many microfinance practitioners to burden their customers with high
interest rates and the plain disbelief of traditional investors that micro-entrepreneurs can
bear those rates is responsible for this occurrence
249 See MicroRate and IADB (2003) p 9
52
8 Conclusions
It has been shown that MFIs are not only contributing significantly to the development
of the financial sector in their respective countries but also that they play an important
role to eradicate poverty by providing much needed capital to low income people which
are able to generate tremendous returns on their investments
The fact that the demand for microcredit is not met is mainly due to the view of most
for profit investors and traditional banks that offering financial services to poor people
can not be done profitable Because of this conviction they hardly invest in the
microfinance sector This does not have to be the case according to the findings of this
paper Although faced with relatively high transaction costs MFIs are able to charge
interest rates at levels that fully recover their costs Elizabeth Rhynersquos claim ldquothat the
most financially viable programs differed from their less viable peers in their
willingness to set interest rates at levels that would fully recover costsrdquo250 is backed by
the findings of this paper that high profitability is correlated to high interest rates
Theoretical models based on the findings of Stiglitz and Weiss can not be used as a
justification to ration credit for the microfinance sector since the interest rate that
maximizes profits to the lender can be assumed to exceed 100 percent for many MFIs
Nevertheless this rate is hardly charged although it has been shown that it can be done
The Mexican MFI Compartamos for example manages to keep its PAR as low as one
percent while charging an effective interest rate of more than 100 percent to
approximately 160000 clients251 In combination with this case the conclusions drawn
from examining the sample of MFIs in chapter 7 the claim of Hulme and Mosley as
stated in the introduction can be considered as wrong MFIs are in fact able to finance
rapid growth stay profitable by charging corresponding interest rates and still have a
significantly positive impact on the poverty level of their clients In the long run gains
in efficiency economies of scale a slowdown in growth and competition will ensure
interest rates drop as it has already been the case in countries like Bangladesh and parts
of Bolivia252
250 See Rhyne (1998) p 7251 See MicroRate (2004)252 See Microrate and IADB (2003) p 9
53
According to a MicroRate survey many MFIs are more profitable than Citibank and also
generate a higher return on investment than commercial banks in their respective
countries253 Investments companies like IMI or Blue Orchard will soon be able to
present a meaningful track record of their microfinance investments to potential
investors Ultimately the capital markets can not ignore the facts proving that it actually
can be profitable to invest in the microfinance sector but in order to raise money
quickly microfinance practitioners will have to continue to intensively promote their
cause not only to for profit investors but also to donors and multilateral agencies like
the World Bank
253 See MicroRate (2002) p 10
54
Appendix
Appendix 1 Average loan balance
Source Data is available through the Mix Market (2004)
Organization
Loan Portfolio 2002 (US$)
Loan Portfolio 2003 (US$)
Number of borrowers 2002
Number of Borrowers 2003
2CM 1263602 1400438 3622 3708ACF 955503 1611401 285 370ACLEDA 26846703 39391301 82598 98905ACME 1460881 1714844 4283 4600ADIM 369065 407798 1122 1395AFK 933306 1706577 250 467AgroInvest 4684249 9697411 5208 9629Al Amana 15593277 28677666 78114 101610AMSSFMC 612167 1040756 6183 6886AREGAK 3285273 3987011 11841 14377AVFS 214331 269819 1883 2866BancoSol 83629049 91175000 42290 56707BESA 10563980 15114430 4488 5061BPR AK 613362 876130 1730 3879BPR BMMS 133949 237946 1755 1779BRI 1344006170 1720072773 3056103 3100358BZMF 1592508 1922097 1250 1331CBDIBA 216587 242465 5764 2877CCA 2146235 4582302 4070 6585CCCP 447534 851678 6265 9450CEP 3795400 5261957 32291 42132CERUDEB 25093643 34873228 34490 44796CMEDFI 227674 250244 3467 3781CMM - Bogota 4836000 8135968 15635 22038CMMB 34880 56964 42 190COAC Maquita Cushunchic
870084 1855718 6603 7732
CODES 280843 263091 60 60CODESARROLLO 6714007 12935951 4391 6896Constanta 2943822 3536047 16134 18588COOPEC CAMEC MN
7152 29821 92 77
Crear - Tacna 3891116 4636094 3671 4948CREDIT 642094 81838 7532 8097CRYSTAL FUND 366456 421403 1379 1061DBACD 3473701 3876526 12812 19606ECLOF - ECU 1154292 728312 860 416ECLOF - MAL 441734 407227 1118 1500EKI 11833244 19245751 8999 13323EMT 4481589 5765281 84781 92173ESED 8579460 6834742 22790 20035
55
Eshet 185741 462569 3308 6540Faulu - KEN 9027332 7206344 17463 15000FDL 12503027 16545332 21306 25106FIE 35818903 41597315 26468 33100FINADEV 5512586 9770323 12775 14709Finance Salone 211312 434298 2225 7159Finca - TAN 1293430 1854834 20648 27499Finca - UGA 2451703 2798869 35610 36912FINCORP 4761288 10236896 941 858FJN 5473563 8037662 8107 11133FMFB 308158 1188896 713 3558FMM -Bucaramanga
6355518 10227000 25814 42464
FODEM 739181 939824 1909 2501FundaciESPOIR
898561 1883446 5911 9464
FUNDESER 798907 1373113 4072 5065Gasha 323748 413742 5504 6423GGLS Save the Children
64235 137957 1291 2362
GK 56986 166971 951 2718HKL 1363365 1420357 6648 5372HOPE 402799 603488 1098 1562IAMD 42132 56550 2780 2772IDECE 21312 39453 150 232IDF 2031944 2626382 31003 36580IMCEC - Dakar 254759 688449 1018 2983IMCEC - Thies 199799 571122 1164 1261
ISSIA 221615 246792 1409 1698JMCC 1962355 2609723 1471 2333KAFC 21710638 29241051 24850 32097KAMURJ 1003935 1411258 5559 5691Kashf 2355965 6271498 29655 59389KMBI 721409 1626666 11973 27266KPSCA 109299 128063 362 794K-Rep 14490447 20699963 38739 45379KSCS 18978 43740 140 297KVT 44075 70621 241 373LAPO 922478 1194633 18740 19139MEC ADEFAP 27788 69248 198 202MEC Bosangani 14357 31086 364 540MEDF 104113 136257 1278 1184Meklit 233170 252232 2084 3577Metemamen 22123 57778 943 1501MFSC 109261 171090 511 687MIKRA 2951028 5008784 4145 6095MIKROFIN 9560502 18380263 5633 7426Miselini 737387 1026639 10182 11431MRFC 11475440 9133130 163000 180000Mushuc Runa 2089076 5418325 3139 6232Nirdhan 2886777 3016171 29589 27457OCSSC 5245186 7658413 42157 6215o
56
Otiv Diana 95992 638422 229 1073Otiv Sambava 188094 437974 2002 1442Otiv Tana 66465 673175 337 1269Partner 9976448 15321304 7139 11935PCA 6878257 6885926 63113 58147PEACE 420746 627295 4192 5428PEDF 164399 254233 2357 3340Piyeli 809447 1206656 8674 4745PRESTANIC 2827502 3540367 1477 2605PRIDE - MAL 991888 854631 5376 5601PRIZMA 3881581 6838978 8112 10968ProMujer -Nicaragua
1006871 1424437 10436 13047
PTF 891566 1068881 8500 9070RBST 818594 1058115 619 723REMECU 1381705 1483471 10330 13996
RUSCA 60887 100820 454 994
SCSCS 89423 157472 873 1007SFPI 709497 903556 7728 9552Sidama 934260 1011798 10267 11346SPBD 117807 186029 647 1740Sunlink 819138 1056823 3401 3833Sunrise 5412366 8782868 4560 7256TEBA 108032426 176300111 163021 157776TIAVO 281978 838905 2049 459TPC 1140429 2267148 22869 31668TSPI 4650989 5383755 49649 75617UNICECAM 3442843 5943804 16039 19031Wasasa 230657 274908 2850 3728Wisdom 1306066 1404463 10524 12054XacBank 4910098 9829503 11063 18610Zakoura 15907288 12444768 103720 118980
Appendix 2 Portfolio at Risk
Source Data is available through the Mix Market (2004)
Organization PAR 2002ABA 202ACEP 464ACLEDA 175ACODEP 452ACSI 209Al Amana 010Apoyo Integral
483
AREGAK 692Banco Solidario
500
BancoSol 660BASIX 1296
57
BRI 437BURO Tangail
350
CEP 200CERUDEB 103CMAC -Sullana
567
CMM -Bogota
176
Compartamos 111Constanta 304Credi Fe 212CREDIAMIGO 409DBACD 010EBS 847EMT 010ESED 1311FADES 2311Faulu - KEN 246Faulu - UGA 096FDL 212FECECAM 428FED 436FIE 598FINADEV 021Finamerica 1133Finca - TAN 000Finca - UGA 297FMM -Bucaramanga
094
FMM -Popayan
088
FONDEP 013FORA 064Genesis Empresarial
1197
IDF 017KAFC 106Kashf 000KMBI 128K-Rep 229MiBanco 309MRFC 1742Nirdhan 373
PADME 079PAMECAS 284PCA 379PRIDE - TAN 018ProMujer -Nicaragua
073
RCPB 600REMECU 157SHARE 000
58
Soluci 182Spandana 014TEBA 106TSPI 355UMU 125UNICECAM 405Urwego 290UWFT 363WAGES 736WWB -Medellin
235
XacBank 061Zakoura 095
Appendix 3 Transaction Costs
Source Data is available through the Mix Market (2004)
OrganizationTransaction Costs
Acci Rural 1154ACEP 858ACLEDA 2430ACODEP 2920ACSI 924Al Amana 2576AREGAK 2856AssEF 1919Banco Solidario
1826
BancoSol 1210BASIX 1317BRI 1353BURO Tangail
2053
CEP 1759CERUDEB 5109CMAC -Sullana
1784
CMM -Bogota
2089
Compartamos 3341Constanta 4597Credi Fe 1978CREDIAMIGO 2525DBACD 1742EBS 2377EMT 3220ESED 1343FADES 1673FAMA 2436
59
Faulu - KEN 2253Faulu - UGA 4962FDL 1726FECECAM 2587FED 4083FIE 1125Finamerica 1563Finca - TAN 10753Finca - UGA 9096FMM -Bucaramanga
1925
FMM -Popayan
1112
FONDEP 5477FORA 3481Genesis Empresarial
1626
IDF 1695
K-Rep 1909LAPO 3511MiBanco 2456Nirdhan 1325NWTF 3109OCSSC 1155PADME 1131PAMECAS 1705PCA 1670PRIDE - TAN 4273ProMujer -Nicaragua
5078
RCPB 2059SHARE 2308Sidama 2662Soluci 2906Spandana 641TEBA 1213TSPI 3898UMU 4023UNICECAM 10120Urwego 7437Wisdom 1906WWB -Medellin
1703
XacBank 4144Zakoura 1881
60
Appendix 4 Portfolio Growth
Source Data is available through the Mix Market (2004)
Organization
Total Loan Portfolio in 2000
Total Loan Portfolio in 2002
ACODEP 5889394 7258487Adelante 4327 88594ADRI 1514681 2591240AgroCapital 11100088 12018280Banco Solidario 39632165 103420000
BancoSol 78031172 83629049CMAC - Sullana 14596365 28055720
COAC Maquita Cushunchic
348443 870084
CODESARROLLO 1374801 6714007Compartamos 10804279 41825248Crear - Tacna 3778816 3891116
Credi Fe 781616 9393936ECLOF - ECU 179247 1154292
FADES 11948814 15501578FAMA 6201411 8835134FIE 22524645 35818903Finamerica 16575104 16097113FINCOMUN 3278938 5696556FMM - Popayan 6241821 12212867
FONDECO 3456625 5101801Genesis Empresarial
11154234 17746288
MiBanco 36964072 95873333Mushuc Runa 90737 2089076ProMujer -Nicaragua
426541 1006871
WWB - Medellin 2891207 4580998
Appendix 5 Portfolio vs Equity
Source Data is available through the Mix Market (2004)
OrganizationLoan Portfolio Equity
ACODEP 7258487 1921447Adelante 88594 72973
ADRI 2591240 781477AgroCapital 12018280 10766101Banco Solidario 103420000 12961000BancoSol 83629049 15299415CMAC - Sullana 28055720 6210291
61
COAC Maquita Cushunchic
870084 260331
CODESARROLLO 6714007 1285103
Compartamos 41825248 18350446
Crear - Tacna 3891116 1016912Credi Fe 9393936 863848ECLOF - ECU 1154292 459226FADES 15501578 4138972FAMA 8835134 6377663FIE 35818903 5360484Finamerica 16097113 3817960FINCOMUN 5696556 1042241FMM - Popayan 12212867 8510494FONDECO 5101801 1658075Genesis Empresarial
17746288 4765816
MiBanco 95873333 24261889Mushuc Runa 2089076 434311ProMujer -Nicaragua
1006871 1196015
WWB - Medellin 4580998 2213249
Appendix 6 Internal Rate of Return
Source Excel (German Version) calculation based on own data
A B C D E F
1 Date Cash Flow
Interest Rate Internal Rate of Return Balance Interest Principal
23 01012004 -100 15324 100 025489547 0045104534 02012004 03 999548955 025489547 0045104535 03012004 03 99909676 02547805 004521956 04012004 03 998643412 025466524 0045334767 05012004 03 998188909 025454968 0045450328 06012004 03 997733247 025443383 0045566179 08012004 03 999826083 050928361 -0209283610 09012004 03 999374595 025485114 004514886
hellip hellip hellip hellip hellip helliphellip hellip hellip hellip hellip hellip helliphellip hellip hellip hellip hellip hellip hellip1562 23122008 03 177951388 000528711 0294712891563 25122008 03 148859724 000908336 0290916641564 26122008 03 119239161 000379437 0296205631565 27122008 03 089543096 000303935 0296960651566 28122008 03 059771337 000228241 0297717591567 29122008 03 029923692 000152354 0298476461568 30122008 03 -3434E-07 000076274 029923726
62
The formula in the square C3 reads as follows
ldquoXINTZINSFUSS(B3B1568A3A156815)rdquo
Appendix 7 Subsidized Interest Rates and the Net Gains to Society
SourceOwn calculations
For simplicity only two groups of potential clients are distinguished This is possible
since using a continuum of potential clients would lead to the same results In addition it
is assumed that the amount of every loan (L) is equal and that all clients invest the
whole loan amount Group H consist of NH potential clients with a rate of return (rH) on
their invested capital higher than the cost recovering interest rate charged by the MFI
(iC) Group L consists of NL potential clients with a rate of return (rL) on their invested
capital lower than iC If the MFI charges iC the NGS can be calculated as follows
NGSC = NH times (rH - iC) times L
Since rH is bigger than iH (rH gt iC) according to the definition presented above the term
NGSH must be positive as long as NH does not equal zero If the MFI introduces a
subsidised interest rate (iS) lower than rL the NGS can be calculated as follows
(1) NGSS = NH times (rH - iS) times L + NLtimes (rL - iS) times L + (NH + NL) times (iS - iC) times L
(2) NGSS = NH times (rH- iC) times L + NLtimes (rL - iC) times L
The term (NH + NL) times (iS - iC) times L describes the amount of money that is needed in order
to subsidize the interest rate to the level iS By setting up an inequation it can be
examined under which conditions the NGSS are bigger than the NGSC
(3) NGSS gt NGSC
(4) NH times (rH- iC) times L + NLtimes (rL - iC) times L gt NH times (rH - iC) times L
(5) NLtimes (rL - iC) times L gt 0
(6) rL gt iC
63
So the NGSS could only be bigger than the NGSC if equation 6 holds This is
impossible since it violated the definitions presented above Therefore the introduction
of subsidized interest rates is always accompanied with a drop in the NGS
Appendix 8 Interest Rate vs Loan Size vs FSS vs PAR
Source Data is available through the Mix Market (2004)
Organization Country
Real Interest Rate
Loan Size (divided by the GDP per Capita) FSS PAR
BTFFKyrgyz Republic 3803 48260 1487 698
BesaFoundation Albania 2184 16076 684 260RFF Albania 1198 5783 4764 277PSHM Albania 2194 000 5758 198Mi-Bospo Bosnia 2974 5499 1261 020Prizma Bosnia 3474 3569 103 064Agroinvest Serbia 2201 4401 875 020KCLF Kazakhstan 5713 1713 865 090
Foccas Uganda10716 (723) 1550 584 29
ACEP Senegal 3280 20941 1643 1Padme Benin 2715 13575 1667 08Papme Benin 3086 53659 1405 24Vital Finance Benin 2676 9394 1015 17Finadev Benin 1738 14850 1024 21ABA Egypt 2579 1613 1168 88ASBA Egypt 2597 1702 1252 68DBACD Egypt 2490 1643 1073 0SBACD Egypt 2500 1734 982 67AMSSF Morocco 6926 787 1306 04Fondep Morocco 5199 650 889 071Zakoura Morocco 4414 900 98 006ENDA Tunisia 4008 1351 110 102BSFL India 1954 3269 856 99Share India 3426 1440 951 0Spandana India 2942 1618 1367 026SWC India 1864 2626 42 3036SKS India 2248 1912 578 0Grama Vidiya India 3176 1221 76 18Sneha India 3451 1433 933 0Buro Bangladesh 3206 1882 1093 17Upap Pakistan 2073 8183 757 03Seeds Sri Lanka 1004 1088 605 287EMT Cambodia 4324 1676 1016 01TPC Cambodia 4470 2035 832 27
64
WTF Phillippines 5816 1095 941 74TSKI Phillippines 5794 777 96 79Cacja Ecuador 862 6189 9460 897ACME Haiti 6043 6934 11685 450Grupo Cama Mexico 8961 267 10717 288
65
Appendix 9 Inflation vs GDP per Capita
Source IMF (2004)
Country Subject Description Units Scale 2000 2001 2002 2003 2004
Albania Gross domestic product per capita current prices US dollars Units 1083988 1238206 1396172 1757778 2229712
Albania Inflation annual percent change Percent 00 31 52 24 34
Bangladesh Gross domestic product per capita current prices US dollars Units 329310 327980 344494 369495 393717
Bangladesh Inflation annual percent change Percent 22 15 38 54 64
Benin Gross domestic product per capita current prices US dollars Units 361340 368213 405951 494725 560129
Benin Inflation annual percent change Percent 42 40 24 15 26
Bosnia and Herzegovina Gross domestic product per capita current prices US dollars Units 1255837 1321429 1466090 1807392 2070508
Bosnia and Herzegovina Inflation annual percent change Percent 50 32 03 02 09
Cambodia Gross domestic product per capita current prices US dollars Units 276413 280352 296577 305940 321247
Cambodia Inflation annual percent change Percent -08 02 33 12 20
Ecuador Gross domestic product per capita current prices US dollars Units 1227711 1590267 1804362 1957183 2082156
Ecuador Inflation annual percent change Percent -77 377 126 79 32
Egypt Gross domestic product per capita current prices US dollars Units 1550982 1461431 1278462 1188060 1083158
Egypt Inflation annual percent change Percent 28 24 24 32 52
India Gross domestic product per capita current prices US dollars Units 454206 458849 472915 542554 602625
India Inflation annual percent change Percent 40 38 43 38 47
Kazakhstan Gross domestic product per capita current prices US dollars Units 1236159 1490946 1655148 2000598 2579554
Kazakhstan Inflation annual percent change Percent 134 83 59 64 68
Kyrgyz Republic Gross domestic product per capita current prices US dollars Units 278256 306130 321079 349632 380637
Kyrgyz Republic Inflation annual percent change Percent 187 69 21 31 45
66
Mexico Gross domestic product per capita current prices US dollars Units 5957486 6274468 6425203 6111754 6377064
Mexico Inflation annual percent change Percent 95 64 50 45 44
Morocco Gross domestic product per capita current prices US dollars Units 1161302 1162154 1199584 1432725 1541041
Morocco Inflation annual percent change Percent 19 06 28 12 20
Pakistan Gross domestic product per capita current prices US dollars Units 437381 400356 440471 492913 538120
Pakistan Inflation annual percent change Percent 44 31 32 29 46
Philippines Gross domestic product per capita current prices US dollars Units 979423 900225 950707 963765 1018710
Philippines Inflation annual percent change Percent 43 61 31 30 54
Russia Inflation annual percent change Percent 208 215 158 137 103
Senegal Gross domestic product per capita current prices US dollars Units 478704 474460 507408 634171 714622
Senegal Inflation annual percent change Percent 09 30 23 -00 08
Serbia and Montenegro Gross domestic product per capita current prices US dollars Units 1031263 1389384 1882036 2491799 2795805
Serbia and Montenegro Inflation annual percent change Percent 699 911 212 113 79
Sri Lanka Gross domestic product per capita current prices US dollars Units 846811 796025 828256 904330 982466
Sri Lanka Inflation annual percent change Percent 62 142 96 63 64
Tunisia Gross domestic product per capita current prices US dollars Units 2034360 2065140 2149421 2534823 2881273
Tunisia Inflation annual percent change Percent 30 19 28 28 34
Uganda Gross domestic product per capita current prices US dollars Units 293404 249682 279587 280802 287204
Uganda Inflation annual percent change Percent 45 -20 57 51 35
67
References
Akerlof George A The Market for ldquoLemonsrdquo Qualitative Uncertainty and the Market Mechanism in Quarterly Journal of Economics Vol 84 (1970) pp 488-500
Amin Ruhul et al Integration of an Essential Service Package (ESP) in Child and Reproductive Health and Family Planning with a Micro-Credit Program for poor Women Experience from a Pilot Project in Rural Bangladesh in World Development Vol 29 (2001) No 9 pp 1611-1621
Bester Helmut Screening vs Rationing in Credit Markets with Imperfect Information in The American Economic Review Vol 75 (1985) No 4 pp 850855
Borst Dietmar Microfinance ndash Theoretische Grundlagen fuumlr den Einsatz sowie die Abschaumltzung des Potentials anhand einer Datenbankuntersuchung zur Verwundbarkeit der laumlndlichen Bevoumllkerung in Vietnam unpublished diploma thesis Karlsruhe 2004
BRAC Annual Report 2002 Dhaka 2003
Busch Alexander Kort Katharina Die Peanuts-Banker und ihre Kunden in Handelsblatt Nr 150 published August 5th 2004 p 8
Campion Anita Challenges to Microfinance Commercialization in Journal of Microfinance Vol 4 (1999) No 2 pp 57-65
Chu Michael Key Issues of Development Finance Somerville (MA) 1998
Dornbusch Ruumldiger Fischer Stanley Makrooumlkonomie Oldenburg 1995
Dunn Seth Flavin Christopher Moving the Climate Change Agenda Forward in State of the World New York London 2002 pp 24-50
Farrington Todd Efficiency in Microfinance Institutions in The MicroBanking Bulletin Issue No 4 pp 18-24
Gardner Gary The Challenge for Johannesburg Creating a More Secure World in State of the World New York London 2002 pp 3-23
Ghatak Subrata On Interregional Variations in Rural Interest Rates in Journal of Developing Areas Issue 18 pp 21-34
Gibbons David Serving the Poorest Sustainably in The MicroBanking Bulletin Issue No 5 (2000) pp 13-16
Gibbons David Meehan Jennifer W The Microcredit Summitrsquos Challenge WorkingToward Institutional Financial Self-Sufficiency While Maintaining a Commitment to Serving the Poorest Families in Journal of Microfinance Vol 1 (1999) No 1 pp 131-192
68
Goodwin-Groen Ruth Do Asian MFIs Access Funds from Commercial Banks inThe MicroBanking Bulletin Issue No 3 pp 8-10
Grameen Bank (ed) Grameen Generalized System Dhaka 2003
Gross Alexandra de Silva Samantha Social Fund Support of Microfinance A Reviewof Implementation Experience The World Bank Social Protection Discussion Paper No 0215 Washington DC 2002
Hashemi Syed M Schuler Sidney R Sustainable Banking with the Poor A Case Study of Grameen Bank Dhaka 1997
Helms Brigit Reille Xavier Interest Rate Ceilings and Microfinance The story so farConsultative Group to assist the Poor Occasional Paper No 9 September 2004 Washington DC 2004
Hoff Karla Stiglitz Joseph E Introduction Imperfect Information and Rural Credit Markets-Puzzles and Policy Perspectives in The World Bank Economic Review Vol 4 (1990) No 3 pp 235-250
Holcombe Susan Managing to Empower The Grameen Bankrsquos Experience of Poverty Allevation Dhaka 1995
Hulme David Mosley Paul Finance against Poverty London 1996
Jalvaani (ed) Flush with loans Micro credit for rural sanitation Vol 2 (1999) No 2 pp 1-2
Khandker Shahidur R Fighting Poverty with Microcredit Experience in Bangladesh Oxford et al 1998
Khandker Shahidur R Khalily Baqui Khan Zahed Grameen Bank Performance andSustainability The World Bank Discussion Paper No 306 Washington DC 1995
Lipsey Rechard G An Introduction to Positive Economics 5th edition London 1979
Littlefield Elizabeth Morduch Jonathan Hashemi Syed M Is Microfinance an Effective Strategy to Reach the Millennium Development Goals Consultative Group to Assist the Poorest Focus Note No 24 Washington DC 2003
Martinot Eric Cabraal Anil World Bank Solar Home Systems Projects Experience and Lessons Learned 1993-2000 in Renewable Energy Oxford 2000 pp 1-8
M-Cril Microfinance Review 2003 revised February 2004 Gurgaon 2004a
Mezzera Jaime Microcredit in Brazil The Gap Between Supply and Demand in The MicroBanking Bulletin Issue No 8 (2000) pp 22-24
The MicroBanking Bulletin (ed) Note to the Reader Vol 1 (1997) Issue No 1 pp 5-8
69
The MicroBanking Bulletin (ed) An Introduction to the Peer Groups and Tables Issue No 9 (2003) pp 53-60
MicroRate IADB Performance Indicators for Microfinance Institutions Technical Guide 3rd edition Washington DC 2003
MkNelly Barbara Dunford Christopher Impact of Credit with Education on Mothers and Their Young Childrenrsquos Nutrition Lower Pra Rural Bank Credit with Education Program in Ghana Freedom from Hunger Research Paper No 4 Davis (CA) 1998
MkNelly Barbara Dunford Christopher Impact of Credit with Education on Mothers and Their Young Childrenrsquos Nutrition CRECER Credit with Education Program in Bolivia Freedom from Hunger Research Paper No 5 Davis (CA) 1999
Morduch Jonathan The Microfinance Promise in Journal of Economic Literature Vol 37 (1999b) No 4 pp 1569-1614
Neus Werner Einfuumlhrung in die Betriebswirtschaftslehre Tuumlbingen 1998
Otero Maria Bringing Development Back into Microfinance Journal of Microfinance Vol 1 (1999) No 1 pp 8-19
Panjaitan-Drioadisuryo Rosintan D M Cloud Kathleen Gender self-employment and microcredit programs An Indonesian case study in The Quarterly Review of Economics and Finance Vol 39 (1999) pp 769ndash779
Perkins Dwight H et al Economics of Development 5th edition New York London 2001
Pitt Mark M Khandker Shahidur R Credit Programs for the Poor and the Health Status of Children in Rural Bangladesh in International Economic Review Vol 44 (2003) No 1 pp 87-118
Raiffeisen Friedrich W The Credit Unions 8th edition Neuwied 1966
Rhyne Elizabeth The Yin and Yang of Microfinance Reaching the Poor and Sustainability in The MicroBanking Bulletin Issue No 2 (1998) pp 6-9
Richardson David C Unorthodox Microfinance The Seven Doctrines of Success in The MicroBanking Bulletin Issue No 4 (2000) pp 3-7
Robinson Marguerite S The Microfinance Revolution Sustainable Finance for the Poor Washington DC 2001
Robinson Marguerite S The Microfinance Revolution Volume 2 Lessons from Indonesia Washington DC 2002
Rosenberg Richard Microcredit Interest Rates Consultative Group to assist the Poorest Occasional Paper No 1 revised November 2002 Washington DC 2002
70
Roth Michael Steinwand Dirk Mikrofinanz Weltweites Erfolgsmodell nur nicht inDeutschland Zur Uumlbertragbarkeit der Erfahrungen aus Entwicklungslaumlndern auf Deutschland Deutsche Gesellschaft fuumlr Technische Zusammenarbeit (ed) Eschborn2004
Schmidt Reinhard H Tschach Ingo Microfinance as a Nexus of Incentives Finance and Accounting Working Paper No 87A Frankfurt 2001
Schreiner Mark A Framework for the Analysis of the Performance and Sustainability of Subsidized Microfinance Organizations with Application to Banco Sol of Bolivia and Grameen Bank of Bangladesh unpublished PhD dissertation Columbus (O) 1997
Seibel Hans D Recent Developments in Microfinance Development Research Center Working Paper No 1998-5 Cologne 1998
Seibel Hans D History matters in microfinance in Small Enterprise Development ndashAn International Journal of Microfinance and Business Development Vol 14 (2003a) No 2 pp 10-12
Seibel Hans D Schmidt Petra How an Agricultural Development Bank Revolutionized Rural Finance The Case of Bank Rakyat Indonesia International Fund for Agricultural Development Rural Finance Working Paper B 5 Rome 2000
Sen Amartya Oumlkonomie fuumlr den Menschen ndash Wege zu Gerechtigkeit und Solidaritaumlt in der Marktwirtschaft Muumlnchen Wien 2000
Serageldin Ismail The View of the Chair in Consultative Group to Assist the Poorest Newsletter Issue No1 (1996) pp 1 11-12
Soros George Die Krise des globalen Kapitalismus Offene Gesellschaft in Gefahr Berlin 1998
Staschen Stefan Regulation and Supervision of Microfinance Institutions State of Knowledge Deutsche Gesellschaft fuumlr Technische Zusammenarbeit (ed) Eschborn 1999
Steinwand Dirk The Alchemy of Microfinance The Evolution of the IndonesianPeoples Credit Banks (BPR) to 1999 and a Contemporary Analysis Berlin 2001
Stiglitz Joseph E Peer Monitoring and Credit Markets in The World Bank Economic Review Vol 4 (1990) No 3 pp 351-366
Stiglitz Joseph E Weiss Andrew Credit Rationing in Markets with Imperfect Information in The American Economic Review Vol 71 (1981) No 3 pp 393-410
Tschach Ingo Theorie der Entwicklungsfinanzierung Mit Kleinkreditprogrammen Kredit- und Arbeitsmarktsegmentierung uumlberwinden Frankfurt 2000
UNDP Human Development Report 2004 New York 2004
71
UNFPA state of the world population 2004 New York 2004
UNICEF The State of the Worldrsquos Children 2002 NewYork Geneva 2002
Varley Robert C G Financial Services and Environmental Health Household Credit for Water and Sanitation Environmental Health Project Applied Study No 2 Washington DC 1995
Volkery Carsten Kampf um Straszligenhaumlndler in Die Zeit Nr 23 published May 27th
2004 p 33
Wardhana Ali Introduction in The Microfinance Revolution ndash Sustainable Finance for the Poor Washington DC 2001 pp XVII-XXVII
Woodworth Warner Woller Gary Greetings from the Editors Journal of Microfinance Vol 1 (1999) No 1 p 6
The World Bank Group World Development Indicators 2004 Washington DC 2004
Worldwatch Institute (2002) Vital Signs 2002 New York London 2002
Wimmer Nancy Barua Dipal Less is more Microfinance for solar energy in rural areas in Renewable Energy World Review Issue 2004-2005 Vol 7 (2004) No4 pp 170-179
Yunus Muhammad Grameen Bank II ndash Designed to Open new Possibilities Dhaka 2002
Yunus Muhammad Grameen ndash Eine Bank fuumlr die Armen dieser Welt Muumlnchen 1998a
Internet References
Abishek Lal (nd) An Overview of Microfinance and Environmental Management [http wwwgdrcorgicmenvironabhishekhtml] (availability date October 5 2004)
ACCION (nd) our history [httpwwwaccionorgabout_our_historyasp] (availability date October 5 2004)
ACCION (nd) key statistics [httpwwwaccionorgabout_key_statsasp] (availability date October 5 2004)
Ahmad Zulfiqar (nd) Forms of Regional Cooperation in Microfinance in South Asia [httpwwwbwtporgarcmpakistanIV_News_and_EventsBWTPworkshopZulfiqar20Ahmad20paper20(BWTP-PMN2029Jan04)pdf (availability date October 6 2004)
72
Ahmed Salehuddin (2003) Foreword [httpwwwpksf-bdorgaprm_summit_brochure htm] (availability date September 30 2004)
Annan Kofi (2002) Statement at The Microcredit Summit +5 [httpwww microcreditsummitorgenews2003-03_sp_chowdhuryhtml) (availability date October 5 2004)
Barnes Carolyn (2001) Microfinance Program Clients and Impact An Assessment of Zambuko Trust Zimbabwe [httpwwwmicrofinancegatewayorgfiles18553_Barnes_Zambuko_Trust_2001pdf] (availability date October 5 2004)
Barnes Carolyn Gaile Gary Kibombo Richard (2001) The Impact of Three Microfinance Programs in Uganda [httpwwwmicrofinancegatewayorgfiles2935_Barnes_2001pdf] (availability date October 5 2004)
Barua Dipal (2004) Success of Grameen Shakti in the Field of Renewable Energy Sector in Bangladesh [httpwwwrenewables2004depptPresentation1-SessionVA(14-1530h)-Baruapdf] (availability date September 30 2004)
Bhatt Ela (1997) In 1975 [httpwwwmicrocreditsummitorgdeclarationhtm] (availability date September 30 2004)
BlueOrchard (2004a) Microfinance [httpwwwblueorchardchenmicrofinance_institutions asp] (availability date October 5 2004)
BlueOrchard (2004b) January 2004 Newsletter [httpwwwblueorchardchmedialibrarywebsitenewsletter_jan_2004pdf] (availability date October 5 2004)
Brynjolfsson John (2004) John Brynjolfsson Discusses Recent Trends in TIPS Issuance [httpwwwpimcocomLeftNavPIMCO+Spotlight2004Spotlight_2_04htm] (availability date October 5 2004)
CGAP (2003) Report to the Board of Executive Directors [httpwww-wdsworldbankorgservletWDSContentServerWDSPIB20031208000012009_20031208101736RenderedPDF27441pdf] (availability date October 5 2004)
Chen Shaohua Ravallion Martin (2004) How have the worldrsquos poorest fared since the early 1980s [httpwwwworldbankorgresearchpovmonitorMartinPapersHow_have_the_poorest_fared_since_the_early_1980spdf] (availability date October 5 2004)
Cheston Susy Kuhn Lisa (2002) Empowering Women through Microfinance[httpwwwmicrofinancegatewayorgfiles3240_Cheston_2002doc] (availability date October 5 2004)
Christen Robert P et al (1995) Maximizing the Outreach of Microenterprise FinanceAn Analysis of Successful Microfinance Programs [httpwwwdecorgpdf_docsPNABS519 pdf] (availability date October 5 2004)
73
CIA (2004) The World Factbook [httpwwwciagovciapublicationsfactbook] (availability date October 5 2004)
Clear Profit (2004) Microfinance Bond Record May Double [httpwwwclear-profitcomissuescpsep04txt] (availability date September 30 2004)
Daley-Harris Sam (2003) State of the Microcredit Summit Campaign Report 2003 [httpwwwmicrocreditsummitorgpubsreportssocr2003SOCR03-E[txt]pdf] (availability date September 30 2004)
Dominiceacute Robert (2004) Interview in Microfinance Bond Record May Double [httpwwwclear-profitcomissuescpsep04txt] (availability date September 30 2004)
Donahue Jill Kabbucho Kamau Osinde Sylvia (2001) HIVAIDSmdashResponding To A Silent Economic Crisis Among Microfinance Clients In Kenya and Uganda [httpwwwmicrosave-africacomget_fileaspdownload_id=541] (availability date September 30 2004)
Donahue Jill Sussman Linda (1999) Building a Multi-Sectoral Response Follow-Up Assessment of Programming for Children and Families Affected by HIVAids in Kenya [httpwwwdecorgpdf_docspnacg778pdf] (availability date September 30 2004)
The Economist (1998) [httpwwweconomistcomdisplaystorycfmstory_id=S2629H3C28Q13F240A] (availability date September 30 2004)
Finca (nd) Introduction [httpvillagebankingorgwhereindexphp3] (availability date September 30 2004)
Fischer Stanley (2003) Statement at The Asia Society and Womens World BankingAnnual Microfinance Conference [httpwwwiiecomfischerpdffischer051303pdf] (availability date September 30 2004)
Friedman Milton (nd) Samuha [httpwwwsamuhaorgm-1htm] availability date September 30 2004)
FXTOP (2004) Historical Exchange Rates [httpfxtopcomdehistoratesphp3] (availability date September 30 2004)
Gibbons David Meehan Jennifer W (2002) Financing Microfinance for Poverty Reduction [httpwwwmicrocreditsummitorgpapersfinancing_finalpdf] (availability date September 30 2004)
Grameen Bank (2004) Grameen Bank At a Glance [httpwwwgrameen-infoorgbankcdshtml] (availability date September 30 2004)
Grameen Trust (nd) Grameen Bank Replication Program [httpwwwgrameen-infoorggrameengtrustreplicationhtml8721] (availability date September 30 2004)
74
Hossain Farhad (2004) Microfinance in Development [httpwwwvalthelsinkifi staff jkoponenb1104FarhadFeb2304pdf] (availability date October 5 2004)
IMF (2004) Data [httpwwwimforgexternalpubsftweo200402datadbginimcfm] (availability date October 5 2004)
IMI (2004) Investments [httpwwwimi-agcomoverviewindexhtml] (availability date September 30 2004)
IPCC (2001) Summary for Policymakers [httpwwwipccchpubspm22-01pdf] (availability date September 30 2004)
Jansson Tor Wenner Mark (1997) Financial Regulation and its Significance for Microfinance in Latin America and the Caribbean [httpwwwgdrcorgicmgoverniadb-janssonpdf] (availability date October 5 2004)
Ken Daniel Ten Roeun Van (2004) The Cycle of Debt - As Microcredit Institutions Grow Some Question Their Effect on Poverty [httpwwwcamnetcomkhcambodiadaily selected_featurescd-21-02-04htm] (availability date September 30 2004)
Kim Julia (2002) Social Interventions for HIVAIDS - Intervention with Microfinance for AIDS and Gender Equity [httpwwwwitsaczaradarPDF20filesIntervention_monograph_no_picspdfpdf] (availability date September 30 2004)
Llanto Gilberto (nd) Vietnam [httpwwwadborgDocumentsBooksCentral_Banks_MicrofinanceCountry_Studiesvietnampdf] (availability date September 30 2004)
The Microfinance Gateway (nd) Frequently Asked Questions [httpwwwmicrofinance gatewayorgsectionfaq1] (availability date October 5 2004)
Microfinance Rating and Assessment Fund (2004) Qualified Raters [httpwwwmfrating orgmfi_institutionsqualified_ratershtml] (availability date October 5 2004)
Microcredit Summit (1997) Declaration and Plan of Action [httpwwwmicrocreditsummit orgdeclarationhtm] (availability date September 30 2004)
MicroRate (nd) Performance Indicators and Ratios [httpwwwmicroratecomENGLISHsiteRATINGSindicatorshtml] (availability date September 30 2004)
MicroRate (2002) The Finance of Microfinance [httpwwwmicroratecomPDFFinance20of20Microfinancepdf] (availability date September 30 2004)
MicroRate (2004) Adjusted comparison table [httpwwwmicroratecomENGLISHsitePDFAdjusted20Comparison20Table060320engpdf] (availability date October 5 2004)
75
Mix Market (2004) The Mix Market [httpwwwmixmarketorg] (availability date October 5 2004)
Morduch Jonathan (1999b) The Grameen Bank A Financial Reckoning [httpwwwwwsprincetonedu~rpdsmacarthurdownloadsmorduch_grameen_bankpdf] (availability date September 30 2004)
Pallen Dean (1997) Environmental Sourcebook for Micro-Finance Institutions [httpwwwacdi-idagccaINETIMAGESNSFvLUImagesea20summaries$fileSOURC Epdf] (availability date September 30 2004)
Prisma (2002) The Case for Private Capital Market Creation in the Development Field of Microfinance [httpwwwsocialenterprisenetpdfsprivate_capital_marketpdf] (availability date September 30 2004)
Schmidt Reinhard H Zeitinger C-P (1997) Critical Issues in Microbusiness Finance and the Role of Donors No 6 [httpwwwgdrcorgicmmfi-donorpdf] (availability date September 30 2004)
Seibel Hans D (2003b) Commodity finance a commercial proposition Micro- and Mesofinance for Agricultural Commodity Production Processing and Trade [httpwwwuni-koelndeew-fakaef05-20042003-420Commodity20Financepdf] (availability date September 30 2004)
Simanowitz Anton Walter Alice (2002) Ensuring Impact Reaching the Poorest while Building Financially Self-sufficient Institutions and Showing Improvement in the Lives of the Poorest Families [httpwwwidsacukimpactPublicationsWorkingPapersOP3MCSSumdoc] (availability date September 30 2004)
Smith Stephen C Jain Sanjay (1999) Village Banking and Maternal and Child Health Theory and Evidence from Ecuador and Honduras[httphomegwuedu~scsmith healthrevwd801pdf] (availability date September 30 2004)
United Nations (1999) International Year of Microcredit 2005 [httpods-dds-nyunorgdoc UNDOCGENN9976933PDFN9976933 pdfOpenElement] (availability date October 5 2004)
United Nations (2000) United Nations Millennium Declaration [httpods-dds-nyunorgdocUNDOCGENN0055951PDFN0055951pdfOpenElement] (availability date October 5 2004)
US Census Bureau (2004) Total Midyear Population for the World 1950-2050 [httpwwwcensusgovipcwwwworldpophtml] (availability date October 5 2004)
WHO (2004) Making pregnancy safer [httpwwwwhointmediacentrefactsheets fs276en] (availability date September 30 2004)
WHO (2001) Child Health [httpwwwwhointmipfiles2082AAGChildHealthpdf] (availability date September 30 2004)
76
The World Bank Group (nd) Health Nutrition and Population and the Millennium Development Goals [www1worldbankorghnpMDGMDG20-20HNPbookletpdf] (availability date September 30 2004)
Yunus Muhammad (1998) Championing the Right to Credit for Poor Women Around the World [httpaspgrameencom dialoguedialogue34interviewhtml] (availability date September 30 2004)
UNAIDS (2004) [httpwwwunaidsorgbangkok2004GAR2004_pdfUNAIDSGlobalReport2004_enpdf] (availability date September 30 2004)
Ratings
M-Cril (2000) SPANDANA [httpwwwratingfundorgspanishdocsSPANDANA_RatingReportpdf] (availability date October 7 2004)
M-Cril (2001a) BASIX [httpwwwbasixindiacomMcrilasp] (availability date October 7 2004)
M-Cril (2001b) BDB [httpwwwratingfundorgspanishdocsRF_BDBpdf] (availability date October 7 2004)
M-Cril (2001c) SNEHA [httpwwwratingfundorgspanishdocsRF_Sneha-u1pdf] (availability date October 7 2004)
M-Cril (2002a) KCLF [httpwwwratingfundorgdocsRF-KCLF-risk20reportdoc] (availability date October 7 2004)
M-Cril (2002b) NWTF [httpwwwratingfundorgspanishdocsRF_NWTFpdf] (availability date October 7 2004)
M-Cril (2002c) SEEDS [httpwwwratingfundorgspanishdocsRF_SEEDS_2002_Ratingpdf] (availability date October 7 2004)
M-Cril (2002c) Share [httpwwwratingfundorgspanishdocsRF_SHAREpdf] (availability date October 7 2004)
M-Cril (2002d) TSKI [httpwwwratingfundorgspanishdocsRF_Tski_mcrilfinal(-) reportpdf] (availability date October 7 2004)
M-Cril (2003a) ASA [httpwwwratingfundorgdocsASA20updatepdf] (availability date October 7 2004)
M-Cril (2003b) BURO [httpwwwm-crilcomburopdf] (availability date October 7 2004)
M-Cril (2003c) EMT [httpwwwratingfundorgdocsEMTpdf] (availability date October 7 2004)
77
M-Cril (2003d) SKS [httpwwwmixmarketorgendemanddemandshowprofileaspett=25ampshowinfo=adjusted] (availability date October 7 2004)
M-Cril (2003d) TPC [httpwwwratingfundorgdocsTPC_Finalpdf] (availability date October 7 2004)
M-Cril (2004b) UPAP [httpwwwratingfundorgdocsUPAP_2004pdf] (availability date October 7 2004)
Microfinanza (2002a) ACME [httpwwwratingfundorgspanishdocsACME_finalpdf] (availability date October 7 2004)
Microfinanza (2002b) BTFF [httpwwwratingfundorgspanishdocsBTFF_RatingReportpdf] (availability date October 7 2004)
Microfinanza (2002c) BESA [httpwwwratingfundorgspanishdocsBESA_RatingReportpdf] (availability date October 7 2004)
Microfinanza (2002d) CAME [httpwwwratingfundorgdocsEvaluacionCAME(-) Finaldoc] (availability date October 7 2004)
Microfinanza (2002e) RFF [httpwwwratingfundorgdocsRFF20finalpdf] (availability date October 7 2004)
Microfinanza (2002f) PSHM [httpwwwratingfundorgspanishdocsPSHM_Reportpdf] (availability date October 7 2004)
Microfinanza (2003) CAJCA [httpwwwratingfundorgdocsCalificacion_Jardin_Azuayo_ratingpdf] (availability date October 7 2004)
Microserve (2003) ENDA [httpwwwmixmarketorgendemanddemandshowprofileaspett=865ampshowinfo=adjusted] (availability date October 7 2004)
Planet Rating (2002a) FONDEP [httpwwwmfratingorgRatingscompleted_ratingshtml] (availability date October 7 2004)
Planet Rating (2002b) PRIZMA [httpwwwmixmarketorgendemanddemandshowprofileaspett=111ampshowinfo=adjusted] (availability date October 7 2004)
Planet Rating (2002c) SWS [httpwwwratingfundorgspanishdocsSWC_reportpdf] (availability date October 7 2004)
Planet Rating (2002d) ZAKOURA [httpwwwratingfundorgspanishdocsRF_Zakourapdf] (availability date October 7 2004)
Planet Rating (2003a) AMSSF [httpwwwratingfundorgdocsPlanetRating_AMSSF_010803pdf] (availability date October 7 2004)
Planet Rating (2003b) FOCCAS [httpwwwratingfundorgdocsPlanetRatingFOCCAS120803pdf] (availability date October 7 2004)
78
Planet Rating (2003c) PADME [httpwwwmfratingorgdocsPlaNetRatingPADME070302_Englishpdf] (availability date October 7 2004)
Planet Rating (2003d) PAPME [httpwwwmfratingorgdocsPAPME_PlanetRating080903pdf] (availability date October 7 2004)
Planet Rating (2003e) VITAL FINANCE [httpwwwmfratingorgdocsVital20Finance_Sept202003pdf] (availability date October 7 2004)
Planet Rating (2004a) ABA [httpwwwratingfundorgdocsABA_April202004pdf] (availability date October 7 2004)
Planet Rating (2004b) ACEP [httpwwwmfratingorgdocsACEPSeacuteneacutegal_2004pdf] (availability date October 7 2004)
Planet Rating (2004c) AGROINVEST [httpwwwratingfundorgdocsAgroInvest_June202004pdf] (availability date October 7 2004)
Planet Rating (2004d) ASBA [httpwwwratingfundorgdocsASBA_April202004pdf] (availability date October 7 2004)
Planet Rating (2004e) DBACD [httpwwwratingfundorgdocsDBACD_April202004pdf] (availability date October 7 2004)
Planet Rating (2004f) FINADEV [httpwwwmfratingorgdocsFinadev_2004pdf] (availability date October 7 2004)
Planet Rating (2004g) MI-BOSPO [httpwwwratingfundorgdocsMIBOSPO_160404pdf] (availability date October 7 2004)
Planet Rating (2004h) SBACD [httpwwwratingfundorgdocsSBACD_PlanetRating300604pdf] (availability date October 7 2004)
Other Sources
Interview Shaw Newaz Deputy General Manager of the Grameen Bank October 30th
2003
Hodson Charles (2001) Your Business Your World Jim Boulden CNN (ed) Dhaka 2001
7
2 The Development of Microfinance
21 What is Microfinance
According to the Journal of Microfinance the term defines what ldquois arguably the most
innovative strategy to address the problems of global povertyldquo4 This view is shared by
the United Nations (UN) which declared that the year 2005 would be the international
year of microcredit5 while their General Secretary Kofi Annan stated in 2002 that
ldquo[m]icrocredit is a critical anti-poverty tool and a wise investment in human capitalrdquo6
Hossain describes microfinance as ldquothe practice of offering small collateral free loans
to members of cooperatives who otherwise would not have access to the capital
necessary to begin a small business or other income generating activitiesrdquo7 This view is
to narrow since it not only excludes such services as saving accounts and insurances8
but also ignores the possibility of collateral demanding MFIs Although it is true that
many MFIs do not take collateral especially if they are focusing on the poorest which
normally do not possess any collateral9 several MFIs in fact do require some form of
collateral10
Roth and Steinwand give a more general definition They describe microfinance as ldquothe
provision of a wide range of financial services like saving accounts loans payment
services and insurances for people with no regular access to financial services through
traditional financial institutionsrdquo11 Here it is important not to confuse the terms
traditional or conventional with the term formal If for example an illiterate beggar
takes a $10 loan from the Grameen Bank in Bangladesh she becomes a client of a
4 See Woodworth and Woller (1999) p 65 See United Nations (1999) p 16 Annan (2002)7 Hossain (2004)8 See The Microfinance Gateway (nd) Robinson (2001) p9 Otero (1999) p 89 See chapter 3 for a more detailed discussion on poverty10 See Robinson 2002 p 24311 See Roth and Steinwand (2004) p 2 ldquodie Bereitstellung einer breiten Palette von Finanzdiensteistungen wie Spareinlagen Kredite Zahlungsverkehr und Versicherungsleistungen fuumlr Wirtschaftsakteure die keinen regelmaumlszligigen Zugang zu Finanzdienstleistungen durch klassische Finanzinstitutionen habenldquo
8
formal financial institution (a registered bank) but obviously not of a traditional or
conventional one12
Although the other services have become more important in recent years microcredit is
still considered their central service by most MFIs In many countries it refers to loans
below $ 100013 however for significant cross country comparison it is more
meaningful to look at the ratio of the loan amount to the gross national product (GNP)
or gross domestic product (GDP) per capita for the respective countries While a loan of
$1000 is more than four times larger than the GNP per capita in Uganda it represents
less than 20 of the GNP per capita in Mexico The MicroBanking Bulletin (MBB) has
categorized the target market for MFIs by the average outstanding loan amount as a
percentage of the GNP per capita ranging from Low-end (less than 20) to Small
Business (more than 250)14 Especially for the latter category one must to look closely
at the condition of the financial service market where an institution is active Although
MFIs exist in industrialized countries15 one would definitely turn to a traditional
financial institution for a loan bigger than 250 of the GNP per capita and therefore not
to a MFI according to the definition presented above
22 The Origin of Microfinance
Although neither of the terms microcredit or microfinance were used in the academic
literature nor by development aid practitioners before the 1980s or 1990s16
respectively the concept of providing financial services to low income people is much
older
While the emergence of informal financial institutions in Nigeria dates back to the 15th
century17 they were first established in Europe during the 18th century as a response to
the enormous increase in poverty since the end of the extended European wars (1618 ndash
12 See Yunus (2002) p 19 for a more detailed description of the destitute member program of the Grameen Bank which focuses exclusively on persons with no regular income and no assets at all 13 See MicroBanking Bulletin (1997) p 614 See MicroBanking Bulletin (2003) p 5415 See Yunus (1998a) pp 229 et sqq16 See Robinson (2001) p XXX17 See Seibel (2003a) p 12
9
1648)18 In 1720 the first loan fund targeting poor people was founded in Ireland by the
author Jonathan Swift19 After a special law was passed in 1823 which allowed charity
institutions to become formal financial intermediaries a loan fund board was established
in 1836 and a big boom was initiated Their outreach peaked just before the government
introduced a cap on interest rates in 1843 At this time they provided financial services
to almost 20 of Irish households20
The credit cooperatives21 created in Germany in 1847 by Friedrich Wilhelm Raiffeisen
served 14 million people by 191022 He stated that the main objectives of these
cooperatives ldquoshould be to control the use made of money for economic improvements
and to improve the moral and physical values of people and also their will to act by
themselvesrdquo23
In the 1880s the British controlled government of Madras in South India tried to use the
German experience to address poverty which resulted in more than nine million poor
Indians belonging to credit cooperatives by 194624 During this same time the Dutch
colonial administrators constructed a cooperative rural banking system in Indonesia
based on the Raiffeisen model25 which eventually became Bank Rakyat Indonesia
(BRI) now known as the largest MFI in the world26
23 Microfinance after the Second World War
Because of further prudential regulation and effective supervision eg through bank
superintendencies the banking sector in the now developed world experienced
continuous growth Today the vast majority of the citizens of the industrialized
countries have access to financial services with many of them being customers of
former MFIs27
18 See Steinwand (2001) p 5119 See Robinson (2002) p 9620 See Seibel (2003a) p 1021 first known as Darlehnsvereine and now called Raiffeisenbanken22 See Morduch (1999a) p 157323 Raiffeisen (1966) quoted in Richardson (2000) p 324 See Morduch (1999a) p 157425 See Robinson (2002) p 9726 See Roth Steinwand (2004) p 327 See Seibel (2003a) p 11
10
This is not true for most developing countries where market penetration of financial
institutions is far from reaching the majority of the inhabitants (see chapter 4) A variety
of reasons is responsible for this including that the banking sector in the most
developing countries have developed in a very different way to than those in
industrialized countries
One of the most important reasons is that in contrast to the industrialized countries little
attention has been paid to the legal recognition prudential regulation and effective
supervision of informal financial institutions28 This insecure legal environment leads to
several problems Since the regulatory framework for mobilizing savings often does not
fit the needs of institutions targeting low income people many organizations are not
permitted to do so and are therefore missing funds to on-lend as credit29 An additional
problem is the lack of a deposit insurances This not only increases the risk of a bank
run but also keeps people from depositing their savings in a financial institution30 In
addition inappropriate interest rate ceilings prevail in many countries While politics
claim they are lowering the interest rates charged to the poor they de facto only limit
their access to financial services (see chapter 5)31
Another problem that retarded the growth of the financial sector in developing countries
was the supply-leading finance theory which dominated the development strategies of
many countries after the second world war32 This theory ldquo refers to the provision of
loans in advance of the demand for credit for the purpose of inducing economic
growthrdquo33 Since it was believed that poor people were neither able to save (and thus
dependent on outside funding) nor capable of paying commercial rates of interest
massive subsidized credit programs were established34 The results were alarming
Repayment rates often did not exceed 50 percent and some government financed
programs even had default rates of more than 90 percent35 The main reason being that
credit was not provided according to business management principles but instead
28 See Seibel (1998) p 829 See Robinson (2001) p 4930 See Staschen (1999) p 1431 See Gibbons (2000) p 1532 See Morduch (1999a) p 157033 Robinson (2001) p 14034 See Borst (2004) pp 33 et sqq35 See Yunus (1998a) p 154 Robinson (2001) p 145
11
according to political objectives Therefore receiving loans was seen as a reward for the
constituents rather than as a business transaction Most of the funds earmarked for the
poor also never reached them ending up instead in the hands of the local elites
Attracted by the below market interest rates and the possibility not to pay back at all
these groups lobbied to be treated privileged and often used the money received for
consumption or for on-lending at higher rates36 But subsidized credit not only
encouraged corruption it also discouraged sustainable financial institutions since they
could not compete with interest rates that were not aimed to cover all costs and were
sometimes even lower than the interest paid on savings37 The low or negative spread
also worked as a negative incentive to institutionsrsquo effort to mobilize savings which in
turn intensified the problem of credit rationing (see chapter 5)
24 Microfinance Today
In the 1970s a paradigm shift started to take place The failure of subsidized government
or donor driven institutions to meet the demand for financial services in developing
countries let to several new approaches Some of the most prominent ones are presented
below
Bank Dagan Bali (BDB) was established in September 1970 to serve low income people
in Indonesia without any subsidies and is now ldquowell-known as the earliest bank to
institute commercial microfinancerdquo38 While this is not true with regard to the
achievements made in Europe during the 19th century it still can be seen as a turning
point with an ever increasing impact on the view of politicians and development aid
practitioners throughout the world In 1973 ACCION International a United States of
America (USA) based non governmental organization (NGO) disbursed its first loan in
Brazil39 and in 1974 Professor Muhammad Yunus started what later became known as
the Grameen Bank by lending a total of $27 to 42 people in Bangladesh40 One year
later the Self-Employed Womenrsquos Association started to provide loans of about $15 to
36 See Robinson (2001) pp 144 et sqq37 Before BRI underwent a major transformation in 1983 a negative spread between interest rates on loans and savings existed While the bank lent at a 12 annual effective interest rate it paid 15 on savingsSee Robinson (2001) p 10638 Wardhana (2001) p XXVII39 See ACCION (nd)40 See Yunus (1998a) p 16 et sqq
12
poor women in India41 Although the latter examples still were subsidized projects they
used a more business oriented approach and showed the world that poor people can be
good credit risks with repayment rates exceeding 9542 even if the interest rate charged
is higher than that of traditional banks Another milestone was the transformation of
BRI starting in 1984 Once a loss making institution channeling government subsidized
credits to inhabitants of rural Indonesia it is now the largest MFI in the world being
profitable even during the Asian financial crisis of 1997 ndash 199843
In February 1997 more than 2900 policymakers microfinance practitioners and
representatives of various educational institutions and donor agencies from 137
different countries gathered in Washington DC for the first Micro Credit Summit This
was the start of a nine year long campaign to reach 100 million of the world poorest
households with credit for self employment by 200544 According to the Microcredit
Summit Campaign Report 67606080 clients have been reached through 2527 MFIs by
the end of 2002 with 41594778 of them being amongst the poorest before they took
their first loan45 Since the campaign started the average annual growth rate in reaching
clients has been almost 40 percent46 If it has continued at that speed more than 100
million people will have access to microcredit by now and by the end of 2005 the goal
of the microcredit summit campaign would be reached As the president of the World
Bank James Wolfensohn has pointed out providing financial services to 100 million of
the poorest households means helping as many as 500 ndash 600 million poor people47
41 See Bhatt (1997)42 See Yunus (1998a) p 143 et sqq43 See Robinson (2002) p 38044 See Daley-Harris (2003) p 345 ldquoThe Microcredit Summit Campaign defines ldquopoorestrdquo as those who are in the bottom half of those living below their nationrsquos poverty line or are living on less than $1 a day adjusted for purchasing power parity (PPP)rdquo See Daley-Harris (2003) p 3 This definition will also be used throughout this paper46 See Daley-Harris (2003) p 1847 See Morduch (1999a) p 1570
13
3 The Impact of Microcredit
31 Microcredit and the Millennium Development Goals
In 1996 Ismail Serageldin the then chair of the Consultative Group to Assist the Poorest
(CGAP)48 claimed that ldquo[m]icrofinance is a proven instrument to assist the very poorrdquo49
This view is also shared by the World Watch Institute50 and underlines what has been
stated above namely that microfinance can be used as a strong anti-poverty tool But
does microfinance actually meet these expectations and keep this promise51
The impact that microcredit has on the lives of poor people will be demonstrated by
showing how it contributes to each of the eight Millennium Development Goals
(MDGs)52 which are related to the reduction of poverty in all its forms These goals
were resolved in September 2000 by the General Assembly of the UN in their
Millennium Declaration53
32 The Eradication of extreme Poverty and Hunger
The aim of the first MDG is to halve the proportion of people who live on less than $1 a
day between 1990 and 2015 According to current population projections of the World
Bank54 this would equal 849 million people in 201555
48 The Consultative Group to Assist the Poorest is a consortium of 28 public and private development agencies working together to expand access to financial services for the poor in developing countries and was established by the World Bank in 1995 Recently it changed its name to Consultative Group to Assist the Poor49 See Serageldin (1996) p 1150 See Gardner (2002) p 1851 See Morduch (1999a) pp 1569 et sqq52 The Millennium Development Goals are (1) eradicate extreme poverty and hunger (2) achieve universal primary education (3) promote gender equality and empower women (4) reduce child mortality (5) improve maternal health (6) combat HIVAIDS malaria and other diseases (7) ensure environmental sustainability and (8) develop a global partnership for development53 See United Nations (2000)54 See World Bank (2004) p 38 et sqq55 Although it is not explicitly mentioned in the Millennium Declaration it is commonly assumed that the share of people living on less than $1 in low and middle income countries should be halved If the share would be calculated with regard to the worldrsquos total population the goal for 2015 would 818 million people For the worldrsquos total population in 1990 see US Census Bureau (2004)
14
Today almost 11 billion people live on less than $1 and more than 27 Billion live on
less than $2 per day56 The mean income for those living under $1 a day is $077 and it
is $125 for those living under $2 a day57 While the number of people living on less
than $1 per day is slowly decreasing and is expected to be 913 million in 2015 the
number of people living on less than $2 a day is actually increasing58 One of the
outcomes from this degree of poverty is that more than 27000 children die every day
from mostly preventable diseases many of them related to hunger59
Microcredit enables poor people to start new businesses or to diversify existing ones
which helps them to increase their income In addition to large amounts of anecdotal
evidence several studies have documented the positive economic impact microcredit
has on its clients Cloud and Panjaitan-Drioadisuryo have found that the average income
of a sample of BRI borrowers has increased by 112 percent and that 90 percent of their
families have crossed the poverty line60 Only 12 out of the 121 respondents of that
study reported that their income had not increased61 According to the Grameen Bank
website 5109 percent of their clients have crossed the poverty line since they took their
first loan62
A study conducted by Barnes showed that the program of the Zambuko Trust a local
MFI in Zambia had a considerable impact on the poorest clients consumption of meat
fish and chicken63 While 76 percent of the continuing clients of the MFI called Share in
India significantly increased their income and 50 percent have crossed the poverty line 64 Khandker discovered in his well known study ldquoFighting poverty with microcreditrdquo
that there is a connection between the microcredit programs of three Bangladeshi MFIs
and household per capita expenditure For every dollar borrowed by a Grameen Bank
member household consumption increases by $018 In addition he found that 5 percent
56 See Chen and Ravallion (2004) p 2957 In fact those people live on less than $108 and $215 respectively a day in 1993 PPP This means that the nominal dollar value of their income is considerably lower See Chen and Ravallion (2004) p 9 58Both numbers are decreasing in Asia but increasing in the rest of the world See Chen and Ravallion (2004) p 22 et sqq59 See UNICEF (2002) p 660 A consistent definition of the term ldquopoverty linerdquo does not exists among different nations Therefore the term will be used according to the definition of the respective country in this paper61 See Panjaitan-Drioadisuryo and Cloud (1999) p 77562 See Grameen Bank (2004) 63 See Barnes (2001) p 8664 See Simanowitz and Walter (2002) p 16
15
of Grameen Bank borrowers move out of poverty every year65 Supposing Khandkerrsquos
findings were correct for all MFIs worldwide and the Microcredit Summit Campaign
achieved its goal of reaching 100 million of the poorest households with microcredit by
2005 then 25 million people (assuming an average family size of five) would leave
poverty every year66 Although this number would have to be adjusted in order take into
consideration the MFI clients who have crossed the poverty line already and of course
the experiences made in Bangladesh can not be transferred precisely to other countries
it still demonstrates the enormous effect that microcredit can have on assisting the
poorest to move out of poverty
Although a 1996 study of Hulme and Mosley states that providing microcredit can also
have a negative impact on the income of the poorest households67 these findings can
be considered as disproved by the recent bulk of evidence drawing favorable
conclusions68
33 Achievement of universal primary Education
The aim of the second MDG is to ensure that all children will be able to complete
primary school by 2015
Currently more than 100 million children most of them girls are not in school69
Besides school fees poor households often can not afford to send their children to
school because they need them to help in the family business
Microcredit programs mainly contribute to the second MDG by increasing families
income and therefore enabling parents to send their children to school Barnes Gaile
and Kibombo found that clients of an MFI in Uganda spent significantly more on
childrenrsquos education than non-clients70 and in Zambia Barnes showed that ongoing
participation in the Zambuko Trustrsquos program had a positive impact on the members
65 See Khandker (1998) p 5666 See Daley-Harris (2003) p 2467 See Hulme and Mosley (1996) p 180 et sqq 68 See Gibbons and Meehan (1998) p 13669 See UNICEF (2002) p 2270 See Barnes Gaile and Kibombo (2001) p 64
16
children staying in school71 In Bangladesh the probability of girls enrolling in school
increased by 19 percent for every 1 percent increase in Grameen Bank loans to female
clients For boys this number was even higher with the mean being 24 percent72
34 Promote gender Equality and empower Women
The aim of the third MDG is to eliminate the disparity in the ratios of girls to boys in
primary secondary and tertiary education in the ratio of literate females to males and to
increase the share of women in the labor market and in parliament73
At present the literacy rate for women is lower than for man all over the world
According to the Human Development Report 2004 the average female literacy rate as
a percentage of male literacy rate is 759 in developing countries and is as low as 37 in
Niger74 But women are not only discriminated against in education but also in access to
medical services and therefore have a higher mortality rate than man75 The worldwide
tendency for women to be underrepresented in the labor market and in the parliaments is
even more severe in developing countries76 Although several women have become
heads of state in various Asian countries (eg Bangladesh India and Indonesia) this is
probably due to them being wives or daughters of former respected male politicians
Since women have a higher repayment rate than man77 and also tend to invest increases
in income on the household and on their children rather than on themselves78 most
MFIs prefer female clients79 Therefore they empower women in many ways Often
MFIs not only encourage women to become involved in financial transactions for the
first time but also to become independent active members of the economy and to
acquire assets in their own names Cheston and Kuhn found that 68 percent of the
women participating in an MFI program in Nepal ldquohellip experienced an increase their
71 See Barnes (2001) p 8472 See Khandker (1998) p 4973 See World Bank (2001) p 2074 See UNDP (2004) pp 225 et sqq75 See Sen (2000) p 23276 See Sen (2000) pp 242 et sqq77 See Littlefield Morduch and Hashemi (2003) p 778 See Yunus (1998a) pp 116 et sqq79 According to the Microcredit Summit Campaign Report 79 or 37677080 of the poorest clients were women See Daley-Harris (2003) p 3
17
decision-making roles in the areas of family planning childrenrsquos marriage buying and
selling property and sending their daughters to school - all areas of decision making
traditionally dominated by menrdquo80 The program of the Lower Pra Rural Bank in Ghana
had an positive impact on womenrsquos participation in the community81 which is true as
well for the CRECER program in Bolivia82 In Bangladesh the Grameen Bank and the
Bangladesh Rural Advancement Committee (BRAC) the two biggest MFIs of the
country had a significant positive effect on womenrsquos empowerment measured through
eight different indicators83 After joining Grameen Bank only 21 percent of the female
members considered themselves as unemployed while this number was 50 percent
before joining84 According to the Grameen Bank website 93 percent of the Bankrsquos
shares are owned by their borrowers which elect the members of the board every three
years They also get familiar with the election process by more frequently voting for
representatives at the lower level of the organizational structure Partly because of this
experience they are more likely to run for public office In the 2003 local government
elections Grameen Bank members constituted 24 of the seats reserved for women
while they represent less than 10 of Bangladeshi adult female population85 Female
clients of MFIs from countries like the Philippines Bolivia and Nepal have reported
similar occurrences86
35 Reduce Child Mortality and improve Maternal Health
The aim of the fourth MDG is to reduce the under-five mortality rate by two-thirds
between 1990 and 2015 and the fifth MDG strives for a three quarter reduction in the
maternal mortality ratio by the same date
As has been stated above more than 10 million children are dying annually in the
developing world of mostly preventable causes with malnutrition playing a role in over
80 See Cheston and Kuhn (2002) p 1881 See MkNelly and Dunford (1998) p 5482 See MkNelly and Dunford (1999) p 7183 The eight different indicators are ldquofreedom of movement economic security ability to make small and larger independent purchases participation in important family decisions relative freedom from domination by the family political and legal awareness and participation in political campaigning and public protestsrdquo Hashemi and Schuler (1998) p 3684 See Holcombe (1995) p 5185 See Grameen Bank (2004)and CIA (2004)86 See Littlefield Morduch and Hashemi (2003) p 8
18
half of the childrsquos deaths and in over 50 countries child mortality rates are greater than
100 deaths per 1000 live births87 Maternal mortality is also a significant problem in the
developing world with more than 500000 women dying every year from pregnancy
related causes88
MFIs are mainly contributing to the these MDGs by increasing families income and
therefore enabling the households to afford better nutrition and medical services
Furthermore they are often linked with microinsurance or health education programs
In addition to what has been showed in chapter 31 Pitt Khandker and Millimet
estimate that a 10 percent increase in the loan size of a female borrower in Bangladesh
increases the arm circumference of their daughters by 6389 Smith and Jain found that
village banking in Ecuador had a positive effect on child diarrhea90 which is responsible
for 15 of child deaths91 Since Sen argues that an improved status of women within
the family reduces child mortality92 the empowerment of women through MFIs is also
contributing to this cause
Although no study has been conducted so far on the direct impact of microcredit on
maternal health it can be assumed that an overall improvement of access to medical
services reduces maternal mortality as well A study of the Morgan State University for
example suggests that microcredit has a positive effect on the prevalence of
contraceptives93 which leads to a decrease of unwanted pregnancies and therefore
reduces maternal death
36 Combat HIVAIDS Malaria and other diseases
The aim of the sixth MDG is to halt and begin to reverse by 2015 the spread of
HIVAIDS malaria and other major diseases and to assist children orphaned by HIV
87 See World Bank (2001) p 888 See WHO (2004) 89 See Pitt Khandker and Millimet (2003) p 11390 See Smith and Jain (1999) p 3791 See WHO (2001) 92 See Sen (2000) p 23593 See Amin et al (2001) p 1614
19
In 2003 29 million people died because of HIV and about 48 million became infected
the greatest number since AIDS was discovered 23 years ago94 This pandemic has lead
to a tremendous decrease in the life expectancy in the hardest hit countries Botswana
for example one of the richest and most democratic countries in Africa has a
HIVAIDS adult prevalence rate of 388 and a life expectancy at birth of less than 31
years95
Malaria not only causes more than one million deaths annually it leads also to 300 ndash
500 million clinical cases a year Both numbers have been steadily increasing over the
past two decades96 More than two million people a year are killed by tuberculosis
another global health problem This curable disease is estimated to cost poor
communities about $12 billion every year since even those who survive normally lose
more than 3 month of work time while recovering97
MFIs contribute to the sixth MDG in several ways By increasing clientrsquos income they
help households affected by HIV or other diseases to better cope with the situation
Besides spending more money on health services and nutrition MFI clients also tend to
be more able and willing to support AIDS orphans than non clients98 In addition to the
already stated increase in the use of contraceptives99 several innovative approaches to
deal with disease related crisis have also arisen This is of course necessary not only to
counteract the devastating effect the above discussed epidemics can have on MFI
clients but also to not put the viability of the respective institution at risk One option is
to integrate education services in the MFI programs and encourage clients to form
solidarity groups100 It has been shown that these services do not necessarily decrease
the effectiveness of the institutionsrsquo employees101 Another way is to strengthen the ties
to NGOs specialize in dealing with the respective disease Synergies gained through this
cooperation can help clients to better deal with the situation and in the end increase their
94 See UNAIDS (2004) p 2395 See CIA (2004)96 See World Bank (2001) p 1697 See World Bank (2001) p 1298 See Barnes (2001) p 6499 See also Kim et al (2002) p 18100 See Donahue and Sussman (1999) p A 14101 See Donahue Kabbucho and Osinde (2001) p 25
20
repayment rates Various MFIs also have introduced loan and health insurance products
or cultivated linkages with organizations doing so102
It has to be stated that despite the benefits MFIs can provide to people effected by
HIVAIDS or other diseases microcredit can also be a burden for those who are already
chronically ill These people can still benefit through loans provided to members of the
family or the community or through one of the other services mentioned above
37 Ensure environmental Sustainability
The aims of the seventh MDG are to support and promote the principles of sustainable
development and put them into action and to improve the lives of slum dwellers and
people without sustainable access to safe drinking water and sanitation
Today climate change is considered as the major environmental problem103 The
Intergovernmental Panel on Climate Change (IPCC) states that human activities
contribute to most of the 06 degC increase in global average temperature over the 20th
century and the predicted increase of another 14 to 58 degC between 1990 and 2100104
Emission of carbon from fossil fuel is reported to have the dominant influence on this
development While the total emission was 16 billion tons in 1950 it was already 65
billion tons in 2000 and is expected to continue to grow105 This development would
lead to a rise in the average sea level of between 9 and 88 centimeters during the next
century106 Furthermore it is predicted that global warming increases the risk of extreme
events like cyclones or floods leads to an increase in the number of people infected by
diseases like malaria and decreases the potential crop harvest and water availability
especially in developing countries107 In 2000 already 11 billion people lacked access to
clean drinking water and 24 billion to basic sanitation108
102 See Barnes (2001) p 40 Barnes Gaile and Kibombo (2001) p 13 and Grameen Bank (2004)103 See Gardner (2002) p 5104 See IPCC (2001) pp 2 et sqq105 Worldwatch Institute (2002) p 52 et sqq106 See IPCC (2001) p 16107 See Dunn and Flavin p 29108 See UNFPA (2004) p 18
21
MFIs contribute to achieving the seventh MDG in several ways By providing loans for
the purchase of renewable energy technologies they help people in developing
countries to increase their per capita energy consumption without increasing the carbon
dioxide emission In a 2003 survey of 140 MFIs from 80 different countries 21 said
they provide credits for solar home systems and another 19 stated they are interested in
becoming engaged in this business109 While Grameen Shakti a rural energy service
company cooperating with the Grameen Bank in Bangladesh has already installed more
than 23000 solar home systems110 a 2000 World Bank study reports twelve projects
providing solar home systems to rural households with a target of 500000
installations111 It has also been suggested that MFIs should raise environmental
awareness among their clients112 but so far no data is available on how staff can cope
with this additional task Many MFIs also provide loans for improvements in sanitation
and the water supply of their clients Varley gives several examples from Africa Asia
and Latin America on how microcredit not only has helped to invest in rainwater
collection systems but also how it has enabled households to increase their water
supply through community water associations113 In addition many MFIs provide credit
for the construction of sanitary latrines114 The situation of slum dwellers is also
positively effected by MFIs Directly through their services in poor urban communities
and indirectly by creating jobs in rural areas and therefore easing the pressure on urban
labor markets
38 Develop a global Partnership for Development
The eight MDG is about the means to achieve the other seven MDGs It calls for all
players involved in the endeavor of development and poverty eradication to work as
partners in a global context
Again MFIs are contributing to the eight MDG in many ways This is occurring through
international networks that provide funding and technical assistance through internet
information portals and specialized journals through social and for profit investors and
109 See Wimmer and Barua (2004) p 174110 Barua (2004) 111 See Martinot and Cabraal (2000) p 6112 See Pallen (1997) p 11 Lal (nd)113 See Varley (1995) pp 39 et sqq114 See Jalvaani (1999) pp 1 et sqq Varley (1995) pp 39 et sqq
22
specialized rating agencies The Bangladesh-based Grameen Trust is one of around 30
networks in operation Besides collaborating with over 200 MFIs around the world it
has directly operated three projects in Afghanistan Kosovo and Myanmar115 While the
ACCION network serves almost 12 million active clients in 19 countries throughout
America and sub-Saharan Africa116 FINCArsquos network operates in three different
continents where it serves more than 200000 customers117 In November 1997 the
MicroBanking Bulletin (MBB) was first published by the microfinance program at the
Economic Institute at the University of Colorado118 Its aim is to develop a database on
the financial performance of MFIs from all over the world which is now available
through the Mix Market an internet portal that also provides information about more
than 300 MFIs investors donor institutions and other related development
organizations119 Two years later the Marriott School at Brigham Young University
started to publish the Journal of Microfinance which has an editorial board of
microfinance experts from all over the world and offers the latest research on this
topic120 In the late 1990s a number of companies became attracted by the microfinance
market and started to invest in MFIs The German based Internationale Mikro
Investitionen Aktiengesellschaft (IMI) for example has already invested more than euro46
million in 19 MFIs in four different continents and plans to invest another euro27 million
before October 2004121 BlueOrchard Finance a microfinance investment consultancy
has channeled more than $60 million worth of private capital to some 40 MFIs
worldwide through investment funds and bond issues122 Big commercial banks like
Citigroup Deutsche Bank and ABN Amro also started to get involved in the
microfinance sector although this is mainly still perceived as a public relation activity
and not as a for-profit investment123 There are also several rating agencies specializing
in MFIs Dependent on their rating these institutions can help MFIs to receive money
from donors or investors Four of the most prominent rating agencies are PlanetFinance
115 See Grameen Trust (nd)116 See ACCION (nd)117 See FINCA (nd)118 See MicroBanking Bulletin (1997) p 5119 See The Mix (2004)120 See Woodworth and Woller (1999) p 6121 See IMI (2004)122 See BlueOrchard (2004b) p 3123 See Busch and Kort (2004) p 8 Fischer (2003) p 6
23
with headquarters in France M-Cril based in India Microfinanza in Italy and
MicroRate with offices in the USA and South Africa124
124 See Microfinance Rating and Assessment Fund (2004)
24
4 Microcredit Outreach
41 The Demand for Microcredit
Although it has been shown that microcredit is one of the most effective poverty
eradication tools that it is considered a human right by some of its advocates125 and it
can contribute considerably to the development of the financial sector in developing
countries an enormous gap still exists between supply and demand for microcredit
Estimates on the demand for microcredit vary greatly While USAID estimates the
number of potential microfinance clients is between 100 and 200 million126 the
Microcredit Summit Campaign states the total demand is more than 234 million
people127 CGAP recognizes some 500 million micro-entrepreneurs who have the
potential to become customers of MFIs128
Marguerite Robinson calculates the demand as follows ldquoAssuming five people to a
household among the 45 billion people living in low- and lower-middle-income
economies in 1999 (World Bank World Development Report 20002001) there are 900
million households in those economies If estimating conservatively we assume that
informal commercial moneylenders supply credit to 30 percent of these households at
least once a year this would mean that there are 270 million households borrowing
from informal moneylenders in a year Undoubtedly however many of these
households borrow multiple times within a yearrdquo129 Although this is a very rough
estimate assuming big differences in demand for microcredit in different countries the
number seems to be the most meaningful In contrast to the estimate of the Microcredit
Summit Campaign it does not include every single household living on less than $1 a
day but according to the definition presented in chapter 1 it counts everyone who has
no regular access to traditional financial institutions but demands such services
Obviously not all people who draw on moneylenders have financial needs that could be
matched through MFIs On the other hand interest rates charged by moneylenders tend
125 See Yunus (1998b) 126 See Christen et al (1995) p 15127 See Daley Harris (2003) p 22 128 See Robinson (2001) p 26129 See Robinson (2001) p 215
25
to be considerably higher than those of MFIs The former normally charge effective
monthly rates between ten and several hundred percent per month the latter generally
charge between 15 and five percent which enables them to attract additional clients130
42 The Supply of Microcredit
In spite of the impressive growth of MFIs around the world the demand for microcredit
is far from being met and this it is not likely to change in the near future The
Microcredit Summit Campaign reported that by the end of 2002 67606080 clients131
were reached through MFIs and that this number has increased by almost 40 percent
annually for the last five years132 It is likely that this tremendous speed of growth is at
least partly due to including MFIs which have not been reporting to the Campaign from
its start in 1997 although they have already existed at that time These institutions
contributed 22 percent to the growth in poorest clients in 2000 578 percent in 2001 and
338 percent in 2002 The growth of the poorest clients increased at least party because
of an expanded definition of the term ldquopoorestrdquo133 Since the contribution of MFIs
which previously have not been considered can be expected to decrease dramatically
the growth rate as stated by the Microcredit Summit Campaign can not be used to
predict the future development of the microfinance sector Another factor likely to slow
down the growth is the concentration of microfinance activities in some Asian countries
where almost 90 percent of the poorest microfinance clients live today134 Even if one
takes into consideration the relative size of Asiarsquos population and the fact that many
MFI customers in Latin America are relatively better off and therefore are not included
in this numbers the coverage of this part of the world far exceeds the others In
Bangladesh for example the microfinance market is close to saturation More than
eleven million households were served by several hundred MFIs in 2001135 Among
them are Grameen Bank and BRAC two of the best known MFIs in the world both
providing their services to more than three million customers With an average
household size of five it can be assumed that in Bangladesh the number of people
130 See Gibbons and Meehan (1999) pp 144 et sqq131 41594778 of them belonged to the poorest before they took their first loan The relative numbers in the following are for these poorest clients only since no other current data was available It can be assumed though that this works as a good proxy for the total number of clients 132 See Daley Harris (2003) p 3133 See Daley Harris (2003) p 17134 See Daley Harris (2003) p 21135 See Ahmed (2003)
26
benefiting from microcredit already surpasses the number of people living below the
poverty line which is estimated to be slightly higher than 50 million136 Therefore
Bangladesh will not contribute to the growth of the microfinance sector as much as it
has done in previous years This is also true for Vietnam Thailand and to a lesser
extent Indonesia Eight of the nine MFIs serving more than one million clients are based
in these countries while the ninth is based in India where due to its one billion
inhabitants the microfinance market is still far from saturation137 In contrast the
supply in Brazil meets less than two percent of the demand which is estimated to be
about 58 million potential clients138 For these reasons greater amount of future growth
must come from smaller or new MFIs in Latin America India China and especially
Africa where almost 30 percent of the worldrsquos poorest live139
43 Meeting the Demand
To fill the gap between the demand and supply for microcredit tremendous investments
are necessary to increase the loan funds of MFIs and build up their capacity through
upgrading existing institutions or building new ones Again estimates on how much
capital is needed vary greatly with the highest being at more than $300 billion140
In 1997 the Microcredit Summit Campaign estimated that $216 billion would be
needed to achieve their goal of providing microcredit to 100 million of the poorest
households This was calculated in the following way Since some 8 million people
already received microcredit in 1997 another 92 million needed to be reached
Assuming $200 ($150 for loan fund and $50 for capacity building) would be needed per
person for 88 million people in developing countries and $1000 ($500 for loan fund and
$500 for capacity building) would be needed for 4 million people in industrialized
countries the capital required ends up to be $216 billion141 For several reasons this
136 See CIA (2004)137 These institutions are The Grameen Bank BRAC Proshika and the Association for Social Advancement (ASA) in Bangladesh the Vietnam Bank for Agriculture and Rural Development (VBARD) and the Vietnam Bank for the Poor (VBA) in Vietnam BRI in Indonesia Bank for Agriculture and Agricultural Co-operatives (BAAC) in Thailand the National Bank for Agriculture and Rural Development (NABARD) in India See Ahmed (nd) p 1 Llanto (nd) p 337138 See Mezzera (2002) p 23139 See See Chen and Ravallion (2004) p 29140 See Clear Profit (2004) Prisma (2002)141 See The Microcredit Summit (1997)
27
number is not qualified to predict the total amount of capital needed to meet the demand
for microcredit On the one hand it focuses mainly on the low end of the market and
therefore underestimates the average loan fund needed On the other hand it does not
take the increasing capital demand from established MFIs into account A survey of 119
MFIs found that the average loan size to increased from $406 in 2002 to $498 in
2003142 This is mainly due to the fact that MFI clients once they have paid back their
loans usually demand larger ones for the continual development of their businesses
and therefore further increase the demand for capital of established MFIs The Grameen
Bank for example has a ceiling on its loans which increases or decreases depending on
the borrowers performance regarding repayments and savings143 While the maximum
amount for the first loan is fixed at approximately $75144 the largest loan disbursed so
far was $17195145 Thus if one estimates that by now 100 million people are borrowing
from MFIs146 another 170 million need to be reached to meet the estimated demand
Assuming an average of $600 ($400 for loan fund and $200 for capacity building) is
needed for every new client and another $200 is needed for every existing client to meet
the demand for larger loans a total of $122 billion is required This rough estimate
helps to convey the approximate amount of capital needed to meet the demand for
microcredit
So far the demand for funds is being partly met by donors which annually provide
between $500 million and $1 billion147 and through the mobilization of local savings
Obviously the amount of money provided by donors will not be able to meet the capital
demand for microcredit in the short term The mobilization of savings on the other hand
has been extremely successful in some cases with BRI probably being the most
prominent example After adapting commercial principals in October 1984 BRI was
able to raise its deposits from $161060 to more than $32 billion in 2003 which equals
almost two times its current loan portfolio148 Many other MFIs like BDB in Indonesia
142 Own calculations Without BRI the numbers would be $343 and $409 See Appendix 1143 See Grameen Bank (2003) p 13144 The accurate amount is 5000 Taka See Interview with Shaw Newaz145 Grameen Bank (2004)146 According to the data provided by the Daley Harris (2003) an annual increase in MFI clients ofapproximately 25 percent from 31122002 till the 3092004 would be needed to reach 100 million clients by now This rated is considerably below the average of the previous five years (38 percent) Therefore it can be assumed as realistic despite the growth hindering factors presented above147 See CGAP (2003) p 8148 See Robinson (2002) p 273 Mix Market (2004)
28
XacBank in Mongolia the Equity Building Society in Kenya or the Centenary Rural
Development Bank in Uganda also have managed to cover their loan portfolio fully
through internally mobilized resources149 The Grameen Bank is also expected to do so
in the first half of 2005150 In addition to raising much needed capital for on-lending the
provision of saving services can deliver notable social benefits itself151
Despite these impressive achievements even the combination of donor money and local
savings at their current levels will not be able to provide the capital needed to continue
the rapid growth of the microfinance sector Especially in their early years MFIs rely on
outside funding BRI for example needed six years before the amount of locally
mobilized savings surpassed the total amount of outstanding loans During this time
expenses and the loan portfolio were covered through a government grant worth $20
million and two World Bank loans of $5 and $97 million respectively152 It also
benefited from a network of more than 3600 branches which were established
throughout the country during the 1970s and early 80s in order to provide government
subsidized credit in rural areas153
The Grameen Bank also widely known as a best practice MFI has received about $175
million in direct and indirect subsidies between 1985 and 1996154 and continues to rely
on outside funding at below market interest rates This is made possible either through
special loans from the Bangladesh Bank or through offering bonds guaranteed by the
Bangladesh government155 - an option most MFIs do not have BDB might be one of the
very few examples which were able to finance their activities through savings and
commercial loans from the start but its outreach did not reach a large scale nor did it
serve the low end of the market In 2000 after 30 years of operation BDB provides
credit to only 10417 clients with an average loan balance of more than $5000156
approximately eight times the countries GDP per capita157
149 See Mix Market (2004)150 See Grameen Bank (2004)151 See Robinson (2001) pp 263 et sqq152 See Seibel and Schmidt (2000) p 4153 See Robinson (2002) p 180154 See Morduch (1999b) p 8155 See Morduch (1999ba) p 25 et sqq156 See Robinson (2002) p 387157 See CIA (2004)
29
Another problem keeping many MFIs from collecting savings is that they do not want
to become a regulated financial institution or do not meet the criteria in their respective
country and therefore they are simply not allowed to mobilize savings from the public
In summary the examples and numbers presented in this chapter support the argument
that the amount of capital that can be raised through donors and locally mobilized
savings is not enough for continuous rapid growth of the microfinance sector If this
lack of capital is not met through other sources the microfinance sector will fail to
contribute its full potential to the achievement of the MDGs
44 Microfinance and the Capital Markets
Regardless of whether the amount of capital needed for the development of the
microfinance sector is $20 or $300 billion it represents only a tiny fraction of the
worldwide capital markets which are estimated at $30 trillion158 Therefore if the
microfinance industry were able to tap the financial markets it would be able to grow
much faster and soon serve the millions of micro-entrepreneurs which currently can not
develop theirs businesses because of capital constrains Another advantage would be
that scarce donor money currently used for the development of the microfinance sector
could be used for other projects that do not have the potential to draw money from
commercial sources This view is shared by Michael Chu the former CEO of ACCION
who made the following statement in 1998 ldquoMicrofinance today stands at the threshold
of its next major stage the connection with the capital marketsrdquo159 Many attempts have
been made since that time Successful MFIs like BancoSol in Bolivia further
strengthened their ties to the capital markets which in some cases already provide the
majority of their funding160 Microfinance investment advisors like BlueOrchard
Finance have become middlemen for MFIs and the financial markets Nevertheless
these links are still far from reaching major scale Currently only approximately 20
percent of MFIs funding comes from commercial sources161 and the biggest bond issue
dedicated to fund MFIs totals only $40 million In addition these funds mainly end up
158 See Brynjolfsson (2004) 159 Chu (1998) quoted in Robinson (2001) p 23160 See Robinson (2001) p 69161 See Dominiceacute (2004)
30
in established institutions in Latin America or Eastern Europe162 while smaller
organizations only benefit indirectly if at all
162 See Clear Profit (2004) IMI (2004)
31
5 Credit Rationing
Until recently the predominant answer to why commercial banks or venture capital
companies did not invest in the microfinance sector was that the poor are not bankable
Besides lacking education and therefore not being able to deal with formal financial
institutions they were viewed as bad credit risk who were unable to invest the borrowed
money in a way that would allow them to repay the loan and interest at a commercial
rate163 Another reason that kept attention away from the idea of providing financial
services to low income people was the belief that informal moneylenders already met
this demand These skeptics felt affirmed through the poor performance of subsidized
credit programs as described in chapter 22 Although it is true that moneylenders
serve a huge number of people in the developing world they more often than not charge
usury interest rates of up to 20000 percent per month164 While the argument that poor
people are not able to participate in the formal financial market can be overcome by
adapting the services accordingly165 the claim of low returns on their investments is not
only proved wrong by empirical evidence but also contradicts economic theory as will
be shown in chapter 53
51 The imperfect Information Paradigm
A more elaborate explanation for the short supply of financial services to low income
people that can be derived from the imperfect information paradigm based
predominantly on the works of Akerlof166 and Stiglitz and Weiss167 After giving a brief
summary of their argument an adaptation of their findings to the microfinance market
will be presented and subsequently it will be shown how their conclusions can be
overcome
Behind the imperfect information paradigm lies the theory of asymmetric information
which simply states that if two parties conduct a transaction one is likely to have more
163 See Ghatak (1983) p 21 et sqq Yunus (1998) p 102 et sqq Robinson (2001) p 35 et sqq164 See Robinson (2001) p 17165 See Seibel (2003b) p 2 BRAC (2003) pp 15et sqq Yunus (1998) pp 151 et sqq 166 See Akerlof (1970) pp 488 et sqq167 See Stiglitz and Weiss (1981) pp 393 et sqq
32
information than the other and is trying to use that for its own advantage168 Applied to
the banking sector this means that a person applying for credit can better judge the
likelihood of repaying the loan than the bank This is because the borrower has better
knowledge of the market she wants to invest in her skills and her willingness to repay
Moreover the bank might not be able to observe if the borrower uses the loan for the
agreed purpose These occurrences can lead to what is known as adverse selection and
moral hazard In this case adverse selection refers to the problem that banks might
attract borrowers with a low probability of repayment if they can not distinguish
between high and low risk loan applicants Moral hazard occurs after the provision of
the loan when the borrower spends the money on a purpose different to the prescribed
purpose and therefore lowers the probability of repayment This can happen eg by
investing in a more risky project or through spending the money on consumption If the
bank is not able to find a cost effective way to avoid these problems it might raise its
interest rate in order to compensate for the increased risk
Figure 1 Expected Bank Return and the Interest Rate
Source Stiglitz and Weiss (1981) p 394
Since this might discourage low risk borrowers from applying for credit and encourage
borrowers who continue to take loans to invest in riskier projects the share of high risk
168 See Neus (1998) p 85 et sqq
INTEREST RATEI
EX
PE
CT
ED
RE
TU
RN
TO
TH
E B
AN
K
33
borrowers could increase and therefore reinforce the problems stated above Thus
increasing the interest rate beyond a certain point actually leads to a decrease in the
expected return to the lender This context is illustrated in figure 1 with I being the
interest rate which maximizes the expected returns to the bank Obviously the bank
would charge the interest rate I in order to maximize its expected return However this
price for capital was not determined through supply and demand as economic theory
would predict It is conceivable that at the interest rate I the demand for credit exceeds
the supply but even if loan applicants would offer to pay a higher interest rate the bank
would refuse because it associates such a loan with high risk As a result credit might
be rationed169
52 Adaptation to the Microfinance Sector
Through some adaptations this model can also help to explain the lack of funds
provided to low income people In the original model of Stiglitz and Weiss several
assumptions have been made that need to be suspended in order to compare the credit
markets for low and high income people and give an explanation why the latter is
widely neglected by institutional investors
Evidently the assumptions that the amount borrowed is equal for each loan applicant
and that transaction costs170 need not to be taken into account171 are not suitable for this
context While the average loan size of MFI customers is much smaller than that of
clients from traditional banks the transaction costs as a share of the loan are
considerably higher because the lenderrsquos costs for conscientious processing a credit
applications are only slightly smaller for a $50 loan than for a $100000 or a
$10000000 loan
In figure 2 the R(I)large curve represents the return to the bank for large loans with
regard to the interest rate I and the R(I)small curve describes the same correlation for
small loans It is shifts downwards to reflect the assertion that the imperfect information
169 See Stiglitz and Weiss (1981) p 394170 In this paper the term bdquotransaction costsldquo refers to the operating expense ratio as defined by MicroRate It ldquois calculated by dividing all expenses related to the operation of the institution (including all the administrative and salary expenses depreciation and board fees) by the period average gross portfoliordquo See MicroRate and Inter-American Development Bank (IADB) (2003) p 16 171 See Stiglitz and Weiss (1981) p 396
34
paradigm has a more severe effect on poor people than on the better off They are
expected to have less profitable investment opportunities at their disposal172 and
therefore are more likely to invest in riskier projects which increase the probability of
default and hence decrease the expected return to the bank Additionally one might
expect poor people to be more likely than others to spend borrowed money on
consumption instead of an income generating activity particularly if a crisis arises It
seems understandable that food or urgently needed medicine are given priority over
repaying a loan
The second shift downwards is due to transaction costs As stated above they are
relatively higher for smaller loans Obviously transaction costs are incurred in the
provision of a large loan as well but since they are much smaller with regard to the loan
amount they are not included in the diagram for reasons of clarity
Figure 2 The extended Model
Source Own diagram adapted from Stiglitz and Weiss (1981) p 394
172 See Khandker (1998) p 8
INTEREST RATE I
SmallLoans
LargeLoans
Transaction costs
Lack of investment opportunities
R(I)large
R(I)small
EX
PE
CT
ED
RE
TU
RN
TO
TH
E B
AN
K
35
53 Overcoming Credit Rationing for the Microfinance Sector
If the conclusions in chapter 51 hold it is rational for a profit maximizing investor to
neglect the microfinance sector as long as no surplus funds in the market for large loans
exist This finding can help to explain the small amount of money provided to the
microfinance sector from commercial investors On the other hand it has to be stated
that this theory is reflexive as defined by Soros173 It not only explains but also forms
reality since it has the potential to reinforce the view of potential investors that
microfinance is a less profitable business174 Therefore demonstrating under which
conditions microfinance can be profitable and in some cases be more profitable than
traditional businesses is of crucial importance
To provide a fairer view of the microfinance sector a further assumption of the Stiglitz
and Weiss model that needs to be suspended is that all investments made by the
borrowers have the same expected return175 As stated above this contradicts economic
theory which claims ceteris paribus capital productivity decreases while the amount of
fixed capital increases In combination with a low capital endowment micro-enterprises
are usually faced with an excess supply of unskilled labor especially in developing
countries176 Hence small enterprises use far less capital per employee than big business
and therefore their marginal productivity of capital is much higher177 This is intuitive if
one imagines an economic actor who wants to invest several packages of capital
Obviously she would invest the first package where she expects the highest return the
second package where she expects the second highest return and so on Each additional
investment opportunity would lead to lower or at best equal returns178 While this
simplified example has limitations it demonstrates how the marginal productivity of
capital can diminish Although it might actually increase until a certain point179 this can
be expected to be so low in this context that it has no influence on the correlation as
shown in figure 2
173 See Soros (1998) pp 14 et sqq174 See Goodwin-Groen (1999) p 8175 See Stiglitz and Weiss (1981) p 395176 See Perkins et al (2001) pp 95 et sqq177 See Tschach (2000) p 8178 See Rosenberg (2002) p 11179 See Rechard G Lipsey (1979) pp 211 et sqq
36
Figure 3 Marginal Productivity of Capital
Source Dornbusch and Fischer (1995) p 406
Even if good investment opportunities for poor people exist the question remains if it is
possible to distinguish between high and low risk borrowers The problem of adverse
selection is overcome in a cost effective way in many MFIs180 For the better off poor
for example institutions like BRI base their decision on whether or not to approve a
loan by assessing the repayment ability of potential borrowers from their current income
flows and not from the uncertain returns generated by the loan181 Additionally
collateral is used in some cases to attract low risk borrowers182 In contrast to
industrialized countries this is usually not done to cover the potential losses of the
lender but to punish the defaulter and therefore increase her willingness to repay183
Obviously this does not always work for the poorest since they often neither posses any
goods that could work as collateral nor do they have sufficient earnings prior to
obtaining a loan for starting an income generating activity Here the so called group-
lending model can help to identify creditworthy borrowers The most prominent
institution using this approach is the Grameen Bank which only provides credit to
180 See Farrington (2000) p 20181 See Robinson (2001) p 80 Robinson (2002) p 238182 See Bester (1985) p 850 et sqq183 See Schmidt and Tschach (2001) p 15 Robinson (2002) p 244
FIXED CAPITAL 0
MA
RG
INA
L P
RO
DU
CT
IVIT
Y
37
members of a group of five These groups are formed by their members without
interference of the Grameen Bank Although in this particular case no joint liability
exists for the members of the group nobody can receive a new loan if another member
of the group fails to repay on time184 Therefore the group formation work as a
screening process Since the borrowers do not want to risk their ability to obtain further
loans they carefully select with whom to form a group Usually the members know
each other for a long period of time and therefore they can make a meaningful judgment
of each othersrsquo ability to repay the loan Other MFIs even require the members of a
group to mutually guarantee each othersrsquo loans185 While this might further increase
borrowersrsquo efforts to search for trustworthy group members it might also keep potential
borrowers from applying for a loan since she does not want be held responsible for
defaulting members This mechanism enables MFIs to partly pass on the transaction
costs related to the selection of low risk borrowers to the borrowers themselves186
Many MFIs have also largely overcome the problem of moral hazard by creating
incentives to ensure a high repayment rate even among the poorest In some cases their
customers go hungry in order to pay back their loan even though no legal action would
be taken against them if they would refuse to do so187 One way to achieve this is to
build up peer pressure through the formation of groups as described above188 Another
and probably the most important is to limit access to future loans to those borrowers
who repay on time The demand for successive loans is extremely high In a 1996
survey 98 percent of BRI borrowers planed to apply for another loan189 and in 1993
less than 30 percent of Grameen Bank loans went to first time borrowers190 Especially
the poorest highly value the option to reborrow191 and many MFIs see this as their
primary incentive to ensure repayment192 According to Schmidt and Tschach ldquothe net
present value of future access to credit works out to be roughly half the value of the
economic advantage to be gained from the intended non-repaymentrdquo193 This can also
184 See Yunus (1998) p 135185 See Schmidt and Zeitinger (1997) p 6186 See Stiglitz (1990) p353187 Own observation at the Grameen Bank in Bangladesh (2003)188 See Hoff and Stiglitz (1990) p 249189 See Robinson (2002) p 251190 See Khandker Khalily and Khan (1995) p 93191 See Gibbons (2000) p 15 Hashemi and Schuler (1997) p 43192 See Gibbons and Meehan (1999) p 160193 See Schmidt and Tschach (2001) p 16
38
explain the occurrence of a drop in the repayment rate once a MFI is no longer seen as
viable and therefore is not expected to provide loans in the future194
With the help of the described mechanisms MFIs around the world are able to keep
repayment rates high A survey of 69 MFIs from 36 different countries each serving
more than 10000 clients in 2002 found the portfolio at risk (PAR)195 varied between
zero and 231 percent While the average was 36 percent the median was found to be
229 percent196 One of the MFIs included in this sample is BRIs whorsquos 12-month loss
ratio has never exceeded five percent since the start of its transformation in 1984 and
from 1997 to 1998 the ratio actually fell from 22 to 194 percent197 The latter deserves
special attention because the Asian financial crisis reached its peak at that time with
Indonesia being hardest hit as illustrated by a statement from The Economist in July
1998 Even with the fierce competition from its neighbors Indonesia would probably
walk away with the prize for Asias most desperate banking systemrdquo198
The findings that MFIs can adapt their services to low income people in order to ensure
a high repayment rate and that poor people do not lack profitable investment
opportunities are illustrated in figure 4 From this diagram it can be seen that under the
new assumptions the interest rate at which the bank maximizes its return differs for
large (I(l)) and small loans (I(s)) According to the assumption that micro-
entrepreneurs can realize a higher return on their investments the bank can charge them
a higher rate of interest without bearing an increased risk Nevertheless in this example
the bank would still serve the market for large loans first because of the higher
transaction costs for smaller loans
The view as described in figure 4 is shared among most traditional banks and investors
in industrialized as well as in developing countries In addition to neglecting the
possibility of generating profits by offering microcredit themselves199 they also hesitate
to lend to MFIs because they consider their business too risky
194 See Schreiner (1997) p 64195 ldquoPAR shows the real risk of the portfolio by comparing outstanding loan balances for loans with atleast one late payment to the outstanding loan portfoliordquo Gross and de Silva (2002) p 22196 Own calculations See Appendix 2197 See Seibel (2000) p 11198 The Economist (1998) pp 92 et sqq199 Busch and Kort (2004) p 8
39
Figure 4 The extended Model
Source Own diagram adapted from Stiglitz and Weiss (1981) p 394 Tschach (2000)
p 17
This attitude can be observed by comparing the ratio of equity to liabilities which is
considerably higher for MFIs than for conventional banks200 When it comes to MFI
start-ups and those MFIs serving the low end market in remote areas even experienced
microfinance practitioners are skeptical if interest rates that fully recover all costs can
be charged201
Theoretically there are two ways to adjust this model to arrive at a conclusion which is
more favorable with regard to the profitability of microcredit One is to cut the
transaction costs and therefore reduce the downward shift of the R(I)small curve the
other is to allow the bank to further raise the interest rate without experiencing a
decrease in its return This means to increase I(s) and the respective rate of return
While in 2000 Tschach stated that transaction costs vary between 10 and 20 percent for
loans provided through the group lending model and between 15 and 30 percent for
200 See MicroRate and IADB (2003) p 30201 See Volkery (2004) p 33 Gibbons (2000) p 15 Gibbons and Meehan (2002) p 29 Goodwin-Groen (1999) p 8
INTEREST RATE I(l)
SmallLoans
LargeLoans
Transaction costs
I(s)
R(i)large
R(i)small
EX
PE
CT
ED
RE
TU
RN
TO
TH
E B
AN
K
40
individual loans202 it was recommended in 1999 that MFIs should target a range
between 15 and 25 percent203 Some best practices on the other hand have already
achieved single digit numbers Currently BDB might be the most efficient MFI in the
world with transaction costs at just 47 percent in 2001204 Even though the low costs of
BDB have to be acknowledged its achievement has to be put in perspective As stated
above with an average loan balance of more than $5000 it does not serve the low end
market In addition it works in an environment with a high population density which
means that it can reach a relatively large group of borrowers per branch This is a
comparative advantage many Asian MFIs enjoy as can be illustrated by comparing
Bangladesh and Bolivia Both countries are at the forefront of the development of
microfinance in their respective continent but while in Bangladesh more than 1000
people are living per square kilometer the average for Bolivia is only eight205
Therefore it is consistent that the most efficient MFI in Latin America Fondo
Financiero Privado para el Fomento a Iniciativas Economicas has transaction costs of
114 percent206 With an average loan size greater than the annual GDP per Capita this
institution also does not serve the low end market207
Despite the impressive efficiency gains in the described examples most MFIs are far
from achieving these numbers and many are unlikely to reach them due to the
environment within which they work A survey of 67 MFIs from 31 countries found the
average transactions costs in 2002 to be 279 percent with a median of 206 percent208
However even if these institutions were to increase their efficiency to best practice
standards their transaction costs would still be significantly higher than those of
traditional banks providing much larger loans For these banks the respective costs vary
in a range between 05 and 3 percent209 According to this argument charging interest
rates considerably higher than conventional banks is the only way for MFIs to generate
higher returns and hence successfully compete for capital
202 See Tschach (2000) pp 100 et sqq203 See Gibbons and Meehan (1999) p 149204 See M-Cril (2001b) p 4205 See CIA (2004)206 See MicroRate (2004)207 In this paper the term ldquolow endrdquo refers to the definition of the MBB (2003) p 54 Loans worth less than 20 percent of the respective countryrsquos GDP per capita are described that way 208 Own calculations See Appendix 3209 See M-Cril (2004a) p 16
41
6 Interest Rates
61 Setting the right Interest Rate
Before addressing the questions to what extend MFIs can raise their interest rates
without putting the repayment rate or the social benefits of their customers at risk a
basic model will be presented This model will illustrate how a MFI should set their
rates in order to not only cover their costs but also to generate an appropriate profit to
finance further growth and attract additional capital
In 2002 CGAP revised its 1996 paper ldquoMicrocredit Interest Ratesrdquo210 which outlines
the standard method of setting sustainable interest rates for commercially oriented
MFIs According to this model the annual effective interest rate (I) should be calculated
as shown below
(1) I = LL
IIKCFLLTA
minusminus+++
1
With each variable being a decimal fraction of the average outstanding loan portfolio
whereby TA stands for the transaction costs as described above LL represents the
annual loan loss and II stands for investment income eg on liquid assets The cost of
funds (CF) consist of the interest and administrative costs needed to obtain deposits and
commercial loans as well as of the imputed costs on equity due to inflation K stands for
the capitalization rate which represents the net real profit Keeping this rate high is
important to finance the future growth of the loan portfolio This can be either done
through investors attracted by high profitability or through borrowing For the latter an
increase in equity is inevitable since it is required as a safety cushion by lenders
Since this model ignores the timing of cash flows and does not take taxes into account
it has to be regarded as fairly imprecise and hence should not be used for business
planning Nevertheless it can be used for an approximation of the interest rate that a
MFI would need to charge to provide its services as planned In the following I will
210 See Rosenberg (2002) pp 1 et sqq
42
apply this model on a fictitious MFI working in a rural area of Latin America with low
end customers In this setting it seems realistic to estimate transaction costs of 35
percent and loan loss rate of two percent211 If funds were borrowed at commercial
terms their costs can be assumed to equal at least 15 percent of the average outstanding
loan portfolio212 Estimating the capitalization rate is more challenging First the
targeted portfolio growth rate is set at 75 percent This is slightly below the 751 percent
average annual portfolio growth between 2000 and 2002 found by a survey of 25
different MFIs based in Central and South America213 If the extend to which the MFI
can leverage stays constant the loan portfolios growth would be limited by the growth
rate of the equity To express the capital needed for this growth as a share of the loan
portfolio it is necessary to estimate the ratio between the equity and the outstanding
loan amount According to the survey mentioned above the loan portfolios of the 25
Latin American MFIs equal on average 215 times their equity214 With this number the
capital needed to increase the equity by 75 percent would corresponds to approximately
35 percent of outstanding loan amount (075215) Finally the investment income has to
be estimated Since liquid assets that are available short term do not generate high
returns say five percent it does not seem advisable for the MFI to hold more than a
quarter of its loan portfolio in this form Hence the profit generated in this way would
equal 125 percent of the outstanding loan amount Using these numbers the equation to
calculate the annual effective interest rate reads as follows
(2) I = LL
IIKCFLLTA
minusminus+++
1 =
0201
01250350150020350
minusminus+++
= 0875
As a result the MFI would need to charge an annual effective interest rate of
approximately 875 percent on its loans in order to sustainable provide its services and
finance its growth without depending on donor money This rate might decrease once
the MFI matures the growth slows down and cheaper funds become available but it
will stay significantly higher than any rate charged by conventional banks
211 MicroRate and IADB (2004) pp 6 and 16212 See MicroRate and IADB (2004) p 616 and 28213 Own calculation See Appendix 4214 Own calculations See Appendix 5
43
62 Can Micro-Entrepreneurs bear these Rates
Although most MFIs charge rates significantly below 875 percent many critics have
strenuously argued against any rates exceeding those of traditional banks Rosanna
Barbero of Oxfam labeled an interest rate of 52 percent charged by a Cambodian MFI
ldquoludicrous evil and disgusting and stated that ldquo[n]o business in the world can make a
profit at these interest ratesldquo215 The former finance minister of Bangladesh Shah Kibria
even categorized the 20 percent effective rate charged by the Grameen Bank as to
high216 Many practitioners therefore believe in a strong negative correlation between
the interest rate and the demand for loans217 Others have argued more generally that
concentrating on profitability and therefore charging high interest rates diverts MFIs
from serving the poorest218
These views are still shared among many MFI managers donor agencies and especially
investors and politicians While the former are unwilling to charge interest rates for
funds they received ldquocheaplyrdquo (through grants or subsidized loans) and are worried
about undermining their social goals by charging higher rates of interest219 the latter are
reluctant to invest for reasons stated above or impose interest caps to catch the attention
of the public by pretending to protect the poor from usury rates220
In chapter 53 it has been described that micro-entrepreneurs due to their smaller
capital endowment have even better investment opportunities than big business The
extend to which this is true has not yet been answered An indication is the high
repayment rate observed within MFIs around the globe If their customers capital yield
did not exceed the charged interest rate how would they be able to repay According to
Gibbons and Meehan customers of MFIs can generally generate returns of more than
100 percent on their invested capital221 and ldquo[r]esearch in India Kenya and the
Philippines found that the average annual return on investments in microenterprises
215 See Kate and Roeun (2004)216 See Hodson (2001) min 1100217 See Morduch (1999a) p 1594218 See Prisma (2002) p 1219 See Schreiner (1997) p 60 Khandker (1998) p 106 220 See Gross and de Silva (2002) p 32 Jansson and Wenner (1997) p 36 et sqq Campion (2002) p 59221 See Gibbons and Meehan (1999) p 131
44
ranged from 117 to 847 percentrdquo222 Schmidt and Tschach found the marginal
productivity of capital to be as high as 1000 percent for the smallest loans provided by
the Bolivian MFI Caja Los Andes223 These findings are confirmed by the observation
of Rosenberg who found while working as a microfinance consultant for ten years he
never heard of a single MFI having problems to attract clients because interest rates
were too high224
To get a better understanding of the investment opportunities of low income people in
developing countries a typical example on how MFI clients invest their loans is as
follows
Zobair is working as a rickshaw puller in Bangladesh Like most of his colleagues he
does not own the rickshaw he is riding Therefore he has to pay a daily rent of about
$030 to the owner Since his average income of approximately $15 per day is hardly
enough to feed his family he is not able to save the $100 necessary to buy a rickshaw
on his own 225 If he could do so through obtaining a loan his income would increase by
$030 every day because he would not have to pay the rent for the rickshaw anymore
Assuming an average of six working days per week 226 and a life span of the rickshaw
of 5 years his internal rate of return would equal 15324 percent annually227
Consequently any interest rate charged by a MFI would be advantageous to him as long
as it would not exceed 15324 percent228
63 Should the Interest Rate be subsidized anyway
Despite the fact that numerous micro-entrepreneurs are able to generate tremendous
returns on their investment obviously not all are able to use capital in such a productive
way and therefore can not afford microcredit at commercial rates In order to reach
these people as well many MFIs continue to use donor money in order to keep their
interest rates low But even if the problems related to subsidized credit as described in
222 See Helms and Reille (2004) p 3223 See Schmidt and Tschach (2001) p 6224 See Rosenberg (2002) p 10225 This examples draws on observations made by the author in Dhaka (Bangladesh) during 2003226 Obviously extended holidays are not a viable option in this surrounding 227 Own calculation See Appendix 6228 This result is only valid if the loan is repaid in daily instalments For a weekly repayment schedule the interest rate charged by the MFI must not exceed 15119 percent in order to still be beneficial for Zobair
45
chapter 23 do not arise it might still not be the most effective tool to help poor people
as will be illustrated in the following example
A MFI faces two groups of potential clients one with businesses able to generate a
return of 125 percent on borrowed capital and another with a possible returns of 50
percent Assuming budget costs according to equation (2) the institution needs to
charge an interest rate of 875 percent and therefore only serves the former group
Supposed each group consists of 50 members demanding $100 loans the net gains to
society (NGS) could be calculated as follows
(3) NGS = 50 times ($125 ndash $875) = $1875
These gains would be due to the investments of the more profitable group which were
made possible through the loans provided by the MFI The less profitable group would
not borrow since their expected returns are not sufficient to pay for the interest If the
interest rate would be lowered to 30 percent both groups would be able to generate net
gains and therefore borrow from the MFI In order to provide loans at this rate the
institution would need to raise additional capital from non commercial sources The
NGS would be calculated as follows
(4) NGS = 50 times ($125 - $30) + 50 times ($50 - $30) + 100 times ($30 - $875) = 0
While the first terms represent the net gains to the respective groups the last describes
the costs incurred in providing the loans At a rate of 30 percent each loan would need
to be subsidized with $575 Hence the NGS actually fall after the introduction of the
subsidized loan This is due to the fact that the less profitable group is encouraged to
invest in relatively unproductive businesses In addition future growth of the MFI could
be jeopardized due to scarce donor money which is needed to finance the interest rate
subsidy Therefore it seems more advisable to continue to charge a rate of 875 percent
and spend the money used for subsidization on other programs such as health care or
education229
229 In Appendix 7 it will be shown that this result generally holds
46
7 Empirical verification
71 Setting up a Sample
To see if the findings of the previous chapters hold the effects which interest rates
charged by MFIs have on their performance will be analyzed in the following Up to
now such a study does not exist mainly because of a lack of adequate data Most MFIs
do not provide accurate information about the annual effective interest rate they charge
and therefore make an evaluation difficult
In 2002 Rosenberg distinguished eight different categories on how microcredit interest
rates are quoted230 These categories differ in several ways On the contrary to
traditional banks for example it is common for MFIs to state interest rates calculated on
a ldquoflatrdquo balance rather than on a declining one This means that the total loan amount is
used to determine the interest rate ignoring installments paid by the borrowers normally
on a weekly or monthly basis In addition many MFIs charge a certain upfront fee prior
to the loan disbursement require compulsory savings at a lower rate or state their
interest rate for semi annual terms only On the one hand this is done to provide
numbers that are more meaningful to MFI customers who often lack the necessary math
skills to deal with compound interest on the other hand it is done to circumvent interest
rate ceilings imposed by the government231 Another problem is that most MFIs offer
different loan products without itemizing their respective shares to their total loan
portfolio As a result it is not possible to calculate a weighted average even if the rate
stated by the respective MFI could be transformed into an effective interest rate
Usually the portfolio yield is used as a proxy in order to make statements about the
interest rate charged by a certain MFI232 It is generally ldquocalculated by dividing total
cash financial revenue (all income generated by the loan portfolio but not accrued
interest) by the period average gross portfoliordquo233 The advantage of this method is that
even the hidden costs are considered Nevertheless it also has a severe shortcoming by
not taking late or defaulted payments into account Therefore the portfolio yield does
230 See Rosenberg (2002) p 5231 MicroRate (2002) p 8232 See MicroRate (nd)233 MicroRate and IADB (2003) p 39
47
not allow to draw conclusions regarding the correlation between the interest rate
charged by a MFI and its PAR
72 Examining the Sample
Through the appearance of rating agencies specialized in the microfinance sector more
adequate information has become available in recent years While MicroRate only
publishes the portfolio yield of rated MFIs M-Cril Microfinanza Microserve and
Planet Rating actually provide information about the annual effective interest rate for at
least some of the MFIs they analyze Although it is labelled differently from all of the
four institutions234 the term describes what is ldquothe highest income or yield that an
organisation can earn from its portfolio based on the terms of its loansrdquo235
Currently236 reports of 39 different MFIs from 20 countries providing accurate
information about the effective annual interest rate are available to the public This
sample should be used to verify the findings of the previous chapters237 Since a
comparison is made between the performances of MFIs based in different countries and
the ratings have been carried out in different years several adjustments are necessary
First the inflation of the respective country and the respective year(s)238 has to be taken
into account in order to only compare the real rates239 In addition the average
outstanding loan amount per borrower is divided by the respective countryrsquos GDP per
capita Since it can be assumed that ldquoonly the poorer households will be willing to take
the smallest loansrdquo240 this number can be used as a proxy for the poverty level
Although the sample size is far to small to represent the microfinance sector as a whole
and the results are statistically not significant the findings can still be used to underline
the theoretical conclusions drawn in the previous chapters In figure 5 the connection
234 M-Cril uses the name ldquoannual percentage raterdquo See eg M-Cril (2004a) p 25 Microfinanza uses the name ldquoexpected portfolio yieldrdquo See eg Microfinanza (2002c) p 25 Planet Rating uses the name ldquoannual effective interest raterdquo See eg Planet Rating (2004d) p 1 Microserve uses the name ldquotheoretical yieldrdquo See Microserve (2003) p 62235 See M-Cril (2004a) p 25236 As of September 28th 2004237 See Appendix 8 For exchange rates see FXTOP (2004)238 Where necessary a weighted average of the annual inflation rate was used See Appendix 9239 This is done through the following formula ir = (I ndash F) (1 + F100) While ir represents the real annual effective interest rate F represents the inflation rate 240 Morduch (1998) p 1572
48
between the average loan size and the transaction costs as a share of the average loan
portfolio is illustrated
Figure 5 Loan Size vs Interest Rate241
Source Own diagram
000
1000
2000
3000
4000
5000
6000
7000
8000
9000
10000
0 100 200 300 400 500 600
Loan Size
Inte
res
t R
ate
It can be seen that the interest rate is negative correlated to the loans size This can be
explained by the relative higher transaction cost for smaller loans as described in
chapter 52 In order to cover their costs MFIs serving the low end market need to
charge higher rates to their customers than those organizations serving the better off
poor Obviously there are several assumptions to this general finding Especially
striking are the two MFIs with an average loan size of approximately five times their
countries GDP per capita which still high interest rates This occurrence can be
explained by taking a closer look to the respective organizations One was established
less than two years prior to its rating and therefore still bears a lot of start up costs242
241 The equation for the regression line reads as follows Y = -00219X + 365 The correlation coefficient is 014242 See Microfinanza (2002b) p 1
49
the other managed to stay profitable while it almost quadrupled its loan portfolio in the
last two years243
Figure 6 Interest Rate vs PAR244
Source Own diagram
0
5
10
15
20
25
30
35
0 20 40 60 80 100 120
Interest Rate
PA
R
In Figure 6 the crucial correlation between the interest rates charged by a MFIs and its
PAR245 is examined According to the given sample the view of traditional banks and
investors that a higher interest rate leads to a higher default rate does not hold
Obviously one has to avoid to draw the opposite conclusion namely that a high interest
rates decreases the PAR The connection illustrated in figure 6 has to be interpreted as
follows Since high interest rates are related to small loans the low PAR for MFIs
charging high interest rates can actually be explained by the tremendous profitability of
small size investments Despite the high rates their customers are even more likely to
repay
243 See Planet Rating (2003b)244 The equation for the regression line reads as follows Y = -00768X + 68433 The correlation coefficient is 0235245 M-Cril only publishes the PAR for overdues greater than 60 days Therefore these ratios are used as a proxy for the industry standard of 30 days for some Asian MFIs
50
Finally it has to be examined if charging high interest rates actually enables MFI to
generate higher returns Although it can be expected that the combination of a low PAR
and a high interest rate leads to a high profitability it still has to be checked if this is not
outdone by soaring transaction costs Figure 7 illustrates the correlation between the
interest rate charged by a MFI and its financial self-sufficiency (FSS) The latter is the
ldquo[r]atio of total income to total adjusted expenses for the year Adjustments are made
for subsidised cost of funds (relative to market interest rate) equity (with respect to
inflation) and in-kind donationsrdquo246 It can be seen that the regression line actually does
indicate a positive correlation between the interest rate and the profitability of a MFI
Figure 7 Interest Rate vs FSS247
Source Own diagram248
0
20
40
60
80
100
120
140
160
180
0 20 40 60 80 100
Interest Rate
FS
S
246 M-Cril (2004a) p 53247 The equation for the regression line reads as follows Y = 02839X + 8901 The correlation coefficient is 0174248 Since the interest rate the customers of the MFI Foccas have to pay includes fees which are not passed on to the institution its interest rate in this diagram is set at 723 percent instead of the 10715 percent used for figure 6 See Planet Rating (2003b) p 1
51
This result does not necessarily disprove the findings of Stiglitz and Weiss since it can
be argued that MFIs simply do no increase their interest rates to the point where they
would maximize their expected returns But if this would be true why do MFIs not
charge higher rates of interest given the demand described in chapter 41 and 43 In
mature markets competition normally ensures prices not to exceed a certain level but
since many MFIs still operate in a ldquosellerrsquos marketrdquo249 this can not explain the findings
as described in figure 7 Therefore it has to be assumed that a combination of the
unwillingness of many microfinance practitioners to burden their customers with high
interest rates and the plain disbelief of traditional investors that micro-entrepreneurs can
bear those rates is responsible for this occurrence
249 See MicroRate and IADB (2003) p 9
52
8 Conclusions
It has been shown that MFIs are not only contributing significantly to the development
of the financial sector in their respective countries but also that they play an important
role to eradicate poverty by providing much needed capital to low income people which
are able to generate tremendous returns on their investments
The fact that the demand for microcredit is not met is mainly due to the view of most
for profit investors and traditional banks that offering financial services to poor people
can not be done profitable Because of this conviction they hardly invest in the
microfinance sector This does not have to be the case according to the findings of this
paper Although faced with relatively high transaction costs MFIs are able to charge
interest rates at levels that fully recover their costs Elizabeth Rhynersquos claim ldquothat the
most financially viable programs differed from their less viable peers in their
willingness to set interest rates at levels that would fully recover costsrdquo250 is backed by
the findings of this paper that high profitability is correlated to high interest rates
Theoretical models based on the findings of Stiglitz and Weiss can not be used as a
justification to ration credit for the microfinance sector since the interest rate that
maximizes profits to the lender can be assumed to exceed 100 percent for many MFIs
Nevertheless this rate is hardly charged although it has been shown that it can be done
The Mexican MFI Compartamos for example manages to keep its PAR as low as one
percent while charging an effective interest rate of more than 100 percent to
approximately 160000 clients251 In combination with this case the conclusions drawn
from examining the sample of MFIs in chapter 7 the claim of Hulme and Mosley as
stated in the introduction can be considered as wrong MFIs are in fact able to finance
rapid growth stay profitable by charging corresponding interest rates and still have a
significantly positive impact on the poverty level of their clients In the long run gains
in efficiency economies of scale a slowdown in growth and competition will ensure
interest rates drop as it has already been the case in countries like Bangladesh and parts
of Bolivia252
250 See Rhyne (1998) p 7251 See MicroRate (2004)252 See Microrate and IADB (2003) p 9
53
According to a MicroRate survey many MFIs are more profitable than Citibank and also
generate a higher return on investment than commercial banks in their respective
countries253 Investments companies like IMI or Blue Orchard will soon be able to
present a meaningful track record of their microfinance investments to potential
investors Ultimately the capital markets can not ignore the facts proving that it actually
can be profitable to invest in the microfinance sector but in order to raise money
quickly microfinance practitioners will have to continue to intensively promote their
cause not only to for profit investors but also to donors and multilateral agencies like
the World Bank
253 See MicroRate (2002) p 10
54
Appendix
Appendix 1 Average loan balance
Source Data is available through the Mix Market (2004)
Organization
Loan Portfolio 2002 (US$)
Loan Portfolio 2003 (US$)
Number of borrowers 2002
Number of Borrowers 2003
2CM 1263602 1400438 3622 3708ACF 955503 1611401 285 370ACLEDA 26846703 39391301 82598 98905ACME 1460881 1714844 4283 4600ADIM 369065 407798 1122 1395AFK 933306 1706577 250 467AgroInvest 4684249 9697411 5208 9629Al Amana 15593277 28677666 78114 101610AMSSFMC 612167 1040756 6183 6886AREGAK 3285273 3987011 11841 14377AVFS 214331 269819 1883 2866BancoSol 83629049 91175000 42290 56707BESA 10563980 15114430 4488 5061BPR AK 613362 876130 1730 3879BPR BMMS 133949 237946 1755 1779BRI 1344006170 1720072773 3056103 3100358BZMF 1592508 1922097 1250 1331CBDIBA 216587 242465 5764 2877CCA 2146235 4582302 4070 6585CCCP 447534 851678 6265 9450CEP 3795400 5261957 32291 42132CERUDEB 25093643 34873228 34490 44796CMEDFI 227674 250244 3467 3781CMM - Bogota 4836000 8135968 15635 22038CMMB 34880 56964 42 190COAC Maquita Cushunchic
870084 1855718 6603 7732
CODES 280843 263091 60 60CODESARROLLO 6714007 12935951 4391 6896Constanta 2943822 3536047 16134 18588COOPEC CAMEC MN
7152 29821 92 77
Crear - Tacna 3891116 4636094 3671 4948CREDIT 642094 81838 7532 8097CRYSTAL FUND 366456 421403 1379 1061DBACD 3473701 3876526 12812 19606ECLOF - ECU 1154292 728312 860 416ECLOF - MAL 441734 407227 1118 1500EKI 11833244 19245751 8999 13323EMT 4481589 5765281 84781 92173ESED 8579460 6834742 22790 20035
55
Eshet 185741 462569 3308 6540Faulu - KEN 9027332 7206344 17463 15000FDL 12503027 16545332 21306 25106FIE 35818903 41597315 26468 33100FINADEV 5512586 9770323 12775 14709Finance Salone 211312 434298 2225 7159Finca - TAN 1293430 1854834 20648 27499Finca - UGA 2451703 2798869 35610 36912FINCORP 4761288 10236896 941 858FJN 5473563 8037662 8107 11133FMFB 308158 1188896 713 3558FMM -Bucaramanga
6355518 10227000 25814 42464
FODEM 739181 939824 1909 2501FundaciESPOIR
898561 1883446 5911 9464
FUNDESER 798907 1373113 4072 5065Gasha 323748 413742 5504 6423GGLS Save the Children
64235 137957 1291 2362
GK 56986 166971 951 2718HKL 1363365 1420357 6648 5372HOPE 402799 603488 1098 1562IAMD 42132 56550 2780 2772IDECE 21312 39453 150 232IDF 2031944 2626382 31003 36580IMCEC - Dakar 254759 688449 1018 2983IMCEC - Thies 199799 571122 1164 1261
ISSIA 221615 246792 1409 1698JMCC 1962355 2609723 1471 2333KAFC 21710638 29241051 24850 32097KAMURJ 1003935 1411258 5559 5691Kashf 2355965 6271498 29655 59389KMBI 721409 1626666 11973 27266KPSCA 109299 128063 362 794K-Rep 14490447 20699963 38739 45379KSCS 18978 43740 140 297KVT 44075 70621 241 373LAPO 922478 1194633 18740 19139MEC ADEFAP 27788 69248 198 202MEC Bosangani 14357 31086 364 540MEDF 104113 136257 1278 1184Meklit 233170 252232 2084 3577Metemamen 22123 57778 943 1501MFSC 109261 171090 511 687MIKRA 2951028 5008784 4145 6095MIKROFIN 9560502 18380263 5633 7426Miselini 737387 1026639 10182 11431MRFC 11475440 9133130 163000 180000Mushuc Runa 2089076 5418325 3139 6232Nirdhan 2886777 3016171 29589 27457OCSSC 5245186 7658413 42157 6215o
56
Otiv Diana 95992 638422 229 1073Otiv Sambava 188094 437974 2002 1442Otiv Tana 66465 673175 337 1269Partner 9976448 15321304 7139 11935PCA 6878257 6885926 63113 58147PEACE 420746 627295 4192 5428PEDF 164399 254233 2357 3340Piyeli 809447 1206656 8674 4745PRESTANIC 2827502 3540367 1477 2605PRIDE - MAL 991888 854631 5376 5601PRIZMA 3881581 6838978 8112 10968ProMujer -Nicaragua
1006871 1424437 10436 13047
PTF 891566 1068881 8500 9070RBST 818594 1058115 619 723REMECU 1381705 1483471 10330 13996
RUSCA 60887 100820 454 994
SCSCS 89423 157472 873 1007SFPI 709497 903556 7728 9552Sidama 934260 1011798 10267 11346SPBD 117807 186029 647 1740Sunlink 819138 1056823 3401 3833Sunrise 5412366 8782868 4560 7256TEBA 108032426 176300111 163021 157776TIAVO 281978 838905 2049 459TPC 1140429 2267148 22869 31668TSPI 4650989 5383755 49649 75617UNICECAM 3442843 5943804 16039 19031Wasasa 230657 274908 2850 3728Wisdom 1306066 1404463 10524 12054XacBank 4910098 9829503 11063 18610Zakoura 15907288 12444768 103720 118980
Appendix 2 Portfolio at Risk
Source Data is available through the Mix Market (2004)
Organization PAR 2002ABA 202ACEP 464ACLEDA 175ACODEP 452ACSI 209Al Amana 010Apoyo Integral
483
AREGAK 692Banco Solidario
500
BancoSol 660BASIX 1296
57
BRI 437BURO Tangail
350
CEP 200CERUDEB 103CMAC -Sullana
567
CMM -Bogota
176
Compartamos 111Constanta 304Credi Fe 212CREDIAMIGO 409DBACD 010EBS 847EMT 010ESED 1311FADES 2311Faulu - KEN 246Faulu - UGA 096FDL 212FECECAM 428FED 436FIE 598FINADEV 021Finamerica 1133Finca - TAN 000Finca - UGA 297FMM -Bucaramanga
094
FMM -Popayan
088
FONDEP 013FORA 064Genesis Empresarial
1197
IDF 017KAFC 106Kashf 000KMBI 128K-Rep 229MiBanco 309MRFC 1742Nirdhan 373
PADME 079PAMECAS 284PCA 379PRIDE - TAN 018ProMujer -Nicaragua
073
RCPB 600REMECU 157SHARE 000
58
Soluci 182Spandana 014TEBA 106TSPI 355UMU 125UNICECAM 405Urwego 290UWFT 363WAGES 736WWB -Medellin
235
XacBank 061Zakoura 095
Appendix 3 Transaction Costs
Source Data is available through the Mix Market (2004)
OrganizationTransaction Costs
Acci Rural 1154ACEP 858ACLEDA 2430ACODEP 2920ACSI 924Al Amana 2576AREGAK 2856AssEF 1919Banco Solidario
1826
BancoSol 1210BASIX 1317BRI 1353BURO Tangail
2053
CEP 1759CERUDEB 5109CMAC -Sullana
1784
CMM -Bogota
2089
Compartamos 3341Constanta 4597Credi Fe 1978CREDIAMIGO 2525DBACD 1742EBS 2377EMT 3220ESED 1343FADES 1673FAMA 2436
59
Faulu - KEN 2253Faulu - UGA 4962FDL 1726FECECAM 2587FED 4083FIE 1125Finamerica 1563Finca - TAN 10753Finca - UGA 9096FMM -Bucaramanga
1925
FMM -Popayan
1112
FONDEP 5477FORA 3481Genesis Empresarial
1626
IDF 1695
K-Rep 1909LAPO 3511MiBanco 2456Nirdhan 1325NWTF 3109OCSSC 1155PADME 1131PAMECAS 1705PCA 1670PRIDE - TAN 4273ProMujer -Nicaragua
5078
RCPB 2059SHARE 2308Sidama 2662Soluci 2906Spandana 641TEBA 1213TSPI 3898UMU 4023UNICECAM 10120Urwego 7437Wisdom 1906WWB -Medellin
1703
XacBank 4144Zakoura 1881
60
Appendix 4 Portfolio Growth
Source Data is available through the Mix Market (2004)
Organization
Total Loan Portfolio in 2000
Total Loan Portfolio in 2002
ACODEP 5889394 7258487Adelante 4327 88594ADRI 1514681 2591240AgroCapital 11100088 12018280Banco Solidario 39632165 103420000
BancoSol 78031172 83629049CMAC - Sullana 14596365 28055720
COAC Maquita Cushunchic
348443 870084
CODESARROLLO 1374801 6714007Compartamos 10804279 41825248Crear - Tacna 3778816 3891116
Credi Fe 781616 9393936ECLOF - ECU 179247 1154292
FADES 11948814 15501578FAMA 6201411 8835134FIE 22524645 35818903Finamerica 16575104 16097113FINCOMUN 3278938 5696556FMM - Popayan 6241821 12212867
FONDECO 3456625 5101801Genesis Empresarial
11154234 17746288
MiBanco 36964072 95873333Mushuc Runa 90737 2089076ProMujer -Nicaragua
426541 1006871
WWB - Medellin 2891207 4580998
Appendix 5 Portfolio vs Equity
Source Data is available through the Mix Market (2004)
OrganizationLoan Portfolio Equity
ACODEP 7258487 1921447Adelante 88594 72973
ADRI 2591240 781477AgroCapital 12018280 10766101Banco Solidario 103420000 12961000BancoSol 83629049 15299415CMAC - Sullana 28055720 6210291
61
COAC Maquita Cushunchic
870084 260331
CODESARROLLO 6714007 1285103
Compartamos 41825248 18350446
Crear - Tacna 3891116 1016912Credi Fe 9393936 863848ECLOF - ECU 1154292 459226FADES 15501578 4138972FAMA 8835134 6377663FIE 35818903 5360484Finamerica 16097113 3817960FINCOMUN 5696556 1042241FMM - Popayan 12212867 8510494FONDECO 5101801 1658075Genesis Empresarial
17746288 4765816
MiBanco 95873333 24261889Mushuc Runa 2089076 434311ProMujer -Nicaragua
1006871 1196015
WWB - Medellin 4580998 2213249
Appendix 6 Internal Rate of Return
Source Excel (German Version) calculation based on own data
A B C D E F
1 Date Cash Flow
Interest Rate Internal Rate of Return Balance Interest Principal
23 01012004 -100 15324 100 025489547 0045104534 02012004 03 999548955 025489547 0045104535 03012004 03 99909676 02547805 004521956 04012004 03 998643412 025466524 0045334767 05012004 03 998188909 025454968 0045450328 06012004 03 997733247 025443383 0045566179 08012004 03 999826083 050928361 -0209283610 09012004 03 999374595 025485114 004514886
hellip hellip hellip hellip hellip helliphellip hellip hellip hellip hellip hellip helliphellip hellip hellip hellip hellip hellip hellip1562 23122008 03 177951388 000528711 0294712891563 25122008 03 148859724 000908336 0290916641564 26122008 03 119239161 000379437 0296205631565 27122008 03 089543096 000303935 0296960651566 28122008 03 059771337 000228241 0297717591567 29122008 03 029923692 000152354 0298476461568 30122008 03 -3434E-07 000076274 029923726
62
The formula in the square C3 reads as follows
ldquoXINTZINSFUSS(B3B1568A3A156815)rdquo
Appendix 7 Subsidized Interest Rates and the Net Gains to Society
SourceOwn calculations
For simplicity only two groups of potential clients are distinguished This is possible
since using a continuum of potential clients would lead to the same results In addition it
is assumed that the amount of every loan (L) is equal and that all clients invest the
whole loan amount Group H consist of NH potential clients with a rate of return (rH) on
their invested capital higher than the cost recovering interest rate charged by the MFI
(iC) Group L consists of NL potential clients with a rate of return (rL) on their invested
capital lower than iC If the MFI charges iC the NGS can be calculated as follows
NGSC = NH times (rH - iC) times L
Since rH is bigger than iH (rH gt iC) according to the definition presented above the term
NGSH must be positive as long as NH does not equal zero If the MFI introduces a
subsidised interest rate (iS) lower than rL the NGS can be calculated as follows
(1) NGSS = NH times (rH - iS) times L + NLtimes (rL - iS) times L + (NH + NL) times (iS - iC) times L
(2) NGSS = NH times (rH- iC) times L + NLtimes (rL - iC) times L
The term (NH + NL) times (iS - iC) times L describes the amount of money that is needed in order
to subsidize the interest rate to the level iS By setting up an inequation it can be
examined under which conditions the NGSS are bigger than the NGSC
(3) NGSS gt NGSC
(4) NH times (rH- iC) times L + NLtimes (rL - iC) times L gt NH times (rH - iC) times L
(5) NLtimes (rL - iC) times L gt 0
(6) rL gt iC
63
So the NGSS could only be bigger than the NGSC if equation 6 holds This is
impossible since it violated the definitions presented above Therefore the introduction
of subsidized interest rates is always accompanied with a drop in the NGS
Appendix 8 Interest Rate vs Loan Size vs FSS vs PAR
Source Data is available through the Mix Market (2004)
Organization Country
Real Interest Rate
Loan Size (divided by the GDP per Capita) FSS PAR
BTFFKyrgyz Republic 3803 48260 1487 698
BesaFoundation Albania 2184 16076 684 260RFF Albania 1198 5783 4764 277PSHM Albania 2194 000 5758 198Mi-Bospo Bosnia 2974 5499 1261 020Prizma Bosnia 3474 3569 103 064Agroinvest Serbia 2201 4401 875 020KCLF Kazakhstan 5713 1713 865 090
Foccas Uganda10716 (723) 1550 584 29
ACEP Senegal 3280 20941 1643 1Padme Benin 2715 13575 1667 08Papme Benin 3086 53659 1405 24Vital Finance Benin 2676 9394 1015 17Finadev Benin 1738 14850 1024 21ABA Egypt 2579 1613 1168 88ASBA Egypt 2597 1702 1252 68DBACD Egypt 2490 1643 1073 0SBACD Egypt 2500 1734 982 67AMSSF Morocco 6926 787 1306 04Fondep Morocco 5199 650 889 071Zakoura Morocco 4414 900 98 006ENDA Tunisia 4008 1351 110 102BSFL India 1954 3269 856 99Share India 3426 1440 951 0Spandana India 2942 1618 1367 026SWC India 1864 2626 42 3036SKS India 2248 1912 578 0Grama Vidiya India 3176 1221 76 18Sneha India 3451 1433 933 0Buro Bangladesh 3206 1882 1093 17Upap Pakistan 2073 8183 757 03Seeds Sri Lanka 1004 1088 605 287EMT Cambodia 4324 1676 1016 01TPC Cambodia 4470 2035 832 27
64
WTF Phillippines 5816 1095 941 74TSKI Phillippines 5794 777 96 79Cacja Ecuador 862 6189 9460 897ACME Haiti 6043 6934 11685 450Grupo Cama Mexico 8961 267 10717 288
65
Appendix 9 Inflation vs GDP per Capita
Source IMF (2004)
Country Subject Description Units Scale 2000 2001 2002 2003 2004
Albania Gross domestic product per capita current prices US dollars Units 1083988 1238206 1396172 1757778 2229712
Albania Inflation annual percent change Percent 00 31 52 24 34
Bangladesh Gross domestic product per capita current prices US dollars Units 329310 327980 344494 369495 393717
Bangladesh Inflation annual percent change Percent 22 15 38 54 64
Benin Gross domestic product per capita current prices US dollars Units 361340 368213 405951 494725 560129
Benin Inflation annual percent change Percent 42 40 24 15 26
Bosnia and Herzegovina Gross domestic product per capita current prices US dollars Units 1255837 1321429 1466090 1807392 2070508
Bosnia and Herzegovina Inflation annual percent change Percent 50 32 03 02 09
Cambodia Gross domestic product per capita current prices US dollars Units 276413 280352 296577 305940 321247
Cambodia Inflation annual percent change Percent -08 02 33 12 20
Ecuador Gross domestic product per capita current prices US dollars Units 1227711 1590267 1804362 1957183 2082156
Ecuador Inflation annual percent change Percent -77 377 126 79 32
Egypt Gross domestic product per capita current prices US dollars Units 1550982 1461431 1278462 1188060 1083158
Egypt Inflation annual percent change Percent 28 24 24 32 52
India Gross domestic product per capita current prices US dollars Units 454206 458849 472915 542554 602625
India Inflation annual percent change Percent 40 38 43 38 47
Kazakhstan Gross domestic product per capita current prices US dollars Units 1236159 1490946 1655148 2000598 2579554
Kazakhstan Inflation annual percent change Percent 134 83 59 64 68
Kyrgyz Republic Gross domestic product per capita current prices US dollars Units 278256 306130 321079 349632 380637
Kyrgyz Republic Inflation annual percent change Percent 187 69 21 31 45
66
Mexico Gross domestic product per capita current prices US dollars Units 5957486 6274468 6425203 6111754 6377064
Mexico Inflation annual percent change Percent 95 64 50 45 44
Morocco Gross domestic product per capita current prices US dollars Units 1161302 1162154 1199584 1432725 1541041
Morocco Inflation annual percent change Percent 19 06 28 12 20
Pakistan Gross domestic product per capita current prices US dollars Units 437381 400356 440471 492913 538120
Pakistan Inflation annual percent change Percent 44 31 32 29 46
Philippines Gross domestic product per capita current prices US dollars Units 979423 900225 950707 963765 1018710
Philippines Inflation annual percent change Percent 43 61 31 30 54
Russia Inflation annual percent change Percent 208 215 158 137 103
Senegal Gross domestic product per capita current prices US dollars Units 478704 474460 507408 634171 714622
Senegal Inflation annual percent change Percent 09 30 23 -00 08
Serbia and Montenegro Gross domestic product per capita current prices US dollars Units 1031263 1389384 1882036 2491799 2795805
Serbia and Montenegro Inflation annual percent change Percent 699 911 212 113 79
Sri Lanka Gross domestic product per capita current prices US dollars Units 846811 796025 828256 904330 982466
Sri Lanka Inflation annual percent change Percent 62 142 96 63 64
Tunisia Gross domestic product per capita current prices US dollars Units 2034360 2065140 2149421 2534823 2881273
Tunisia Inflation annual percent change Percent 30 19 28 28 34
Uganda Gross domestic product per capita current prices US dollars Units 293404 249682 279587 280802 287204
Uganda Inflation annual percent change Percent 45 -20 57 51 35
67
References
Akerlof George A The Market for ldquoLemonsrdquo Qualitative Uncertainty and the Market Mechanism in Quarterly Journal of Economics Vol 84 (1970) pp 488-500
Amin Ruhul et al Integration of an Essential Service Package (ESP) in Child and Reproductive Health and Family Planning with a Micro-Credit Program for poor Women Experience from a Pilot Project in Rural Bangladesh in World Development Vol 29 (2001) No 9 pp 1611-1621
Bester Helmut Screening vs Rationing in Credit Markets with Imperfect Information in The American Economic Review Vol 75 (1985) No 4 pp 850855
Borst Dietmar Microfinance ndash Theoretische Grundlagen fuumlr den Einsatz sowie die Abschaumltzung des Potentials anhand einer Datenbankuntersuchung zur Verwundbarkeit der laumlndlichen Bevoumllkerung in Vietnam unpublished diploma thesis Karlsruhe 2004
BRAC Annual Report 2002 Dhaka 2003
Busch Alexander Kort Katharina Die Peanuts-Banker und ihre Kunden in Handelsblatt Nr 150 published August 5th 2004 p 8
Campion Anita Challenges to Microfinance Commercialization in Journal of Microfinance Vol 4 (1999) No 2 pp 57-65
Chu Michael Key Issues of Development Finance Somerville (MA) 1998
Dornbusch Ruumldiger Fischer Stanley Makrooumlkonomie Oldenburg 1995
Dunn Seth Flavin Christopher Moving the Climate Change Agenda Forward in State of the World New York London 2002 pp 24-50
Farrington Todd Efficiency in Microfinance Institutions in The MicroBanking Bulletin Issue No 4 pp 18-24
Gardner Gary The Challenge for Johannesburg Creating a More Secure World in State of the World New York London 2002 pp 3-23
Ghatak Subrata On Interregional Variations in Rural Interest Rates in Journal of Developing Areas Issue 18 pp 21-34
Gibbons David Serving the Poorest Sustainably in The MicroBanking Bulletin Issue No 5 (2000) pp 13-16
Gibbons David Meehan Jennifer W The Microcredit Summitrsquos Challenge WorkingToward Institutional Financial Self-Sufficiency While Maintaining a Commitment to Serving the Poorest Families in Journal of Microfinance Vol 1 (1999) No 1 pp 131-192
68
Goodwin-Groen Ruth Do Asian MFIs Access Funds from Commercial Banks inThe MicroBanking Bulletin Issue No 3 pp 8-10
Grameen Bank (ed) Grameen Generalized System Dhaka 2003
Gross Alexandra de Silva Samantha Social Fund Support of Microfinance A Reviewof Implementation Experience The World Bank Social Protection Discussion Paper No 0215 Washington DC 2002
Hashemi Syed M Schuler Sidney R Sustainable Banking with the Poor A Case Study of Grameen Bank Dhaka 1997
Helms Brigit Reille Xavier Interest Rate Ceilings and Microfinance The story so farConsultative Group to assist the Poor Occasional Paper No 9 September 2004 Washington DC 2004
Hoff Karla Stiglitz Joseph E Introduction Imperfect Information and Rural Credit Markets-Puzzles and Policy Perspectives in The World Bank Economic Review Vol 4 (1990) No 3 pp 235-250
Holcombe Susan Managing to Empower The Grameen Bankrsquos Experience of Poverty Allevation Dhaka 1995
Hulme David Mosley Paul Finance against Poverty London 1996
Jalvaani (ed) Flush with loans Micro credit for rural sanitation Vol 2 (1999) No 2 pp 1-2
Khandker Shahidur R Fighting Poverty with Microcredit Experience in Bangladesh Oxford et al 1998
Khandker Shahidur R Khalily Baqui Khan Zahed Grameen Bank Performance andSustainability The World Bank Discussion Paper No 306 Washington DC 1995
Lipsey Rechard G An Introduction to Positive Economics 5th edition London 1979
Littlefield Elizabeth Morduch Jonathan Hashemi Syed M Is Microfinance an Effective Strategy to Reach the Millennium Development Goals Consultative Group to Assist the Poorest Focus Note No 24 Washington DC 2003
Martinot Eric Cabraal Anil World Bank Solar Home Systems Projects Experience and Lessons Learned 1993-2000 in Renewable Energy Oxford 2000 pp 1-8
M-Cril Microfinance Review 2003 revised February 2004 Gurgaon 2004a
Mezzera Jaime Microcredit in Brazil The Gap Between Supply and Demand in The MicroBanking Bulletin Issue No 8 (2000) pp 22-24
The MicroBanking Bulletin (ed) Note to the Reader Vol 1 (1997) Issue No 1 pp 5-8
69
The MicroBanking Bulletin (ed) An Introduction to the Peer Groups and Tables Issue No 9 (2003) pp 53-60
MicroRate IADB Performance Indicators for Microfinance Institutions Technical Guide 3rd edition Washington DC 2003
MkNelly Barbara Dunford Christopher Impact of Credit with Education on Mothers and Their Young Childrenrsquos Nutrition Lower Pra Rural Bank Credit with Education Program in Ghana Freedom from Hunger Research Paper No 4 Davis (CA) 1998
MkNelly Barbara Dunford Christopher Impact of Credit with Education on Mothers and Their Young Childrenrsquos Nutrition CRECER Credit with Education Program in Bolivia Freedom from Hunger Research Paper No 5 Davis (CA) 1999
Morduch Jonathan The Microfinance Promise in Journal of Economic Literature Vol 37 (1999b) No 4 pp 1569-1614
Neus Werner Einfuumlhrung in die Betriebswirtschaftslehre Tuumlbingen 1998
Otero Maria Bringing Development Back into Microfinance Journal of Microfinance Vol 1 (1999) No 1 pp 8-19
Panjaitan-Drioadisuryo Rosintan D M Cloud Kathleen Gender self-employment and microcredit programs An Indonesian case study in The Quarterly Review of Economics and Finance Vol 39 (1999) pp 769ndash779
Perkins Dwight H et al Economics of Development 5th edition New York London 2001
Pitt Mark M Khandker Shahidur R Credit Programs for the Poor and the Health Status of Children in Rural Bangladesh in International Economic Review Vol 44 (2003) No 1 pp 87-118
Raiffeisen Friedrich W The Credit Unions 8th edition Neuwied 1966
Rhyne Elizabeth The Yin and Yang of Microfinance Reaching the Poor and Sustainability in The MicroBanking Bulletin Issue No 2 (1998) pp 6-9
Richardson David C Unorthodox Microfinance The Seven Doctrines of Success in The MicroBanking Bulletin Issue No 4 (2000) pp 3-7
Robinson Marguerite S The Microfinance Revolution Sustainable Finance for the Poor Washington DC 2001
Robinson Marguerite S The Microfinance Revolution Volume 2 Lessons from Indonesia Washington DC 2002
Rosenberg Richard Microcredit Interest Rates Consultative Group to assist the Poorest Occasional Paper No 1 revised November 2002 Washington DC 2002
70
Roth Michael Steinwand Dirk Mikrofinanz Weltweites Erfolgsmodell nur nicht inDeutschland Zur Uumlbertragbarkeit der Erfahrungen aus Entwicklungslaumlndern auf Deutschland Deutsche Gesellschaft fuumlr Technische Zusammenarbeit (ed) Eschborn2004
Schmidt Reinhard H Tschach Ingo Microfinance as a Nexus of Incentives Finance and Accounting Working Paper No 87A Frankfurt 2001
Schreiner Mark A Framework for the Analysis of the Performance and Sustainability of Subsidized Microfinance Organizations with Application to Banco Sol of Bolivia and Grameen Bank of Bangladesh unpublished PhD dissertation Columbus (O) 1997
Seibel Hans D Recent Developments in Microfinance Development Research Center Working Paper No 1998-5 Cologne 1998
Seibel Hans D History matters in microfinance in Small Enterprise Development ndashAn International Journal of Microfinance and Business Development Vol 14 (2003a) No 2 pp 10-12
Seibel Hans D Schmidt Petra How an Agricultural Development Bank Revolutionized Rural Finance The Case of Bank Rakyat Indonesia International Fund for Agricultural Development Rural Finance Working Paper B 5 Rome 2000
Sen Amartya Oumlkonomie fuumlr den Menschen ndash Wege zu Gerechtigkeit und Solidaritaumlt in der Marktwirtschaft Muumlnchen Wien 2000
Serageldin Ismail The View of the Chair in Consultative Group to Assist the Poorest Newsletter Issue No1 (1996) pp 1 11-12
Soros George Die Krise des globalen Kapitalismus Offene Gesellschaft in Gefahr Berlin 1998
Staschen Stefan Regulation and Supervision of Microfinance Institutions State of Knowledge Deutsche Gesellschaft fuumlr Technische Zusammenarbeit (ed) Eschborn 1999
Steinwand Dirk The Alchemy of Microfinance The Evolution of the IndonesianPeoples Credit Banks (BPR) to 1999 and a Contemporary Analysis Berlin 2001
Stiglitz Joseph E Peer Monitoring and Credit Markets in The World Bank Economic Review Vol 4 (1990) No 3 pp 351-366
Stiglitz Joseph E Weiss Andrew Credit Rationing in Markets with Imperfect Information in The American Economic Review Vol 71 (1981) No 3 pp 393-410
Tschach Ingo Theorie der Entwicklungsfinanzierung Mit Kleinkreditprogrammen Kredit- und Arbeitsmarktsegmentierung uumlberwinden Frankfurt 2000
UNDP Human Development Report 2004 New York 2004
71
UNFPA state of the world population 2004 New York 2004
UNICEF The State of the Worldrsquos Children 2002 NewYork Geneva 2002
Varley Robert C G Financial Services and Environmental Health Household Credit for Water and Sanitation Environmental Health Project Applied Study No 2 Washington DC 1995
Volkery Carsten Kampf um Straszligenhaumlndler in Die Zeit Nr 23 published May 27th
2004 p 33
Wardhana Ali Introduction in The Microfinance Revolution ndash Sustainable Finance for the Poor Washington DC 2001 pp XVII-XXVII
Woodworth Warner Woller Gary Greetings from the Editors Journal of Microfinance Vol 1 (1999) No 1 p 6
The World Bank Group World Development Indicators 2004 Washington DC 2004
Worldwatch Institute (2002) Vital Signs 2002 New York London 2002
Wimmer Nancy Barua Dipal Less is more Microfinance for solar energy in rural areas in Renewable Energy World Review Issue 2004-2005 Vol 7 (2004) No4 pp 170-179
Yunus Muhammad Grameen Bank II ndash Designed to Open new Possibilities Dhaka 2002
Yunus Muhammad Grameen ndash Eine Bank fuumlr die Armen dieser Welt Muumlnchen 1998a
Internet References
Abishek Lal (nd) An Overview of Microfinance and Environmental Management [http wwwgdrcorgicmenvironabhishekhtml] (availability date October 5 2004)
ACCION (nd) our history [httpwwwaccionorgabout_our_historyasp] (availability date October 5 2004)
ACCION (nd) key statistics [httpwwwaccionorgabout_key_statsasp] (availability date October 5 2004)
Ahmad Zulfiqar (nd) Forms of Regional Cooperation in Microfinance in South Asia [httpwwwbwtporgarcmpakistanIV_News_and_EventsBWTPworkshopZulfiqar20Ahmad20paper20(BWTP-PMN2029Jan04)pdf (availability date October 6 2004)
72
Ahmed Salehuddin (2003) Foreword [httpwwwpksf-bdorgaprm_summit_brochure htm] (availability date September 30 2004)
Annan Kofi (2002) Statement at The Microcredit Summit +5 [httpwww microcreditsummitorgenews2003-03_sp_chowdhuryhtml) (availability date October 5 2004)
Barnes Carolyn (2001) Microfinance Program Clients and Impact An Assessment of Zambuko Trust Zimbabwe [httpwwwmicrofinancegatewayorgfiles18553_Barnes_Zambuko_Trust_2001pdf] (availability date October 5 2004)
Barnes Carolyn Gaile Gary Kibombo Richard (2001) The Impact of Three Microfinance Programs in Uganda [httpwwwmicrofinancegatewayorgfiles2935_Barnes_2001pdf] (availability date October 5 2004)
Barua Dipal (2004) Success of Grameen Shakti in the Field of Renewable Energy Sector in Bangladesh [httpwwwrenewables2004depptPresentation1-SessionVA(14-1530h)-Baruapdf] (availability date September 30 2004)
Bhatt Ela (1997) In 1975 [httpwwwmicrocreditsummitorgdeclarationhtm] (availability date September 30 2004)
BlueOrchard (2004a) Microfinance [httpwwwblueorchardchenmicrofinance_institutions asp] (availability date October 5 2004)
BlueOrchard (2004b) January 2004 Newsletter [httpwwwblueorchardchmedialibrarywebsitenewsletter_jan_2004pdf] (availability date October 5 2004)
Brynjolfsson John (2004) John Brynjolfsson Discusses Recent Trends in TIPS Issuance [httpwwwpimcocomLeftNavPIMCO+Spotlight2004Spotlight_2_04htm] (availability date October 5 2004)
CGAP (2003) Report to the Board of Executive Directors [httpwww-wdsworldbankorgservletWDSContentServerWDSPIB20031208000012009_20031208101736RenderedPDF27441pdf] (availability date October 5 2004)
Chen Shaohua Ravallion Martin (2004) How have the worldrsquos poorest fared since the early 1980s [httpwwwworldbankorgresearchpovmonitorMartinPapersHow_have_the_poorest_fared_since_the_early_1980spdf] (availability date October 5 2004)
Cheston Susy Kuhn Lisa (2002) Empowering Women through Microfinance[httpwwwmicrofinancegatewayorgfiles3240_Cheston_2002doc] (availability date October 5 2004)
Christen Robert P et al (1995) Maximizing the Outreach of Microenterprise FinanceAn Analysis of Successful Microfinance Programs [httpwwwdecorgpdf_docsPNABS519 pdf] (availability date October 5 2004)
73
CIA (2004) The World Factbook [httpwwwciagovciapublicationsfactbook] (availability date October 5 2004)
Clear Profit (2004) Microfinance Bond Record May Double [httpwwwclear-profitcomissuescpsep04txt] (availability date September 30 2004)
Daley-Harris Sam (2003) State of the Microcredit Summit Campaign Report 2003 [httpwwwmicrocreditsummitorgpubsreportssocr2003SOCR03-E[txt]pdf] (availability date September 30 2004)
Dominiceacute Robert (2004) Interview in Microfinance Bond Record May Double [httpwwwclear-profitcomissuescpsep04txt] (availability date September 30 2004)
Donahue Jill Kabbucho Kamau Osinde Sylvia (2001) HIVAIDSmdashResponding To A Silent Economic Crisis Among Microfinance Clients In Kenya and Uganda [httpwwwmicrosave-africacomget_fileaspdownload_id=541] (availability date September 30 2004)
Donahue Jill Sussman Linda (1999) Building a Multi-Sectoral Response Follow-Up Assessment of Programming for Children and Families Affected by HIVAids in Kenya [httpwwwdecorgpdf_docspnacg778pdf] (availability date September 30 2004)
The Economist (1998) [httpwwweconomistcomdisplaystorycfmstory_id=S2629H3C28Q13F240A] (availability date September 30 2004)
Finca (nd) Introduction [httpvillagebankingorgwhereindexphp3] (availability date September 30 2004)
Fischer Stanley (2003) Statement at The Asia Society and Womens World BankingAnnual Microfinance Conference [httpwwwiiecomfischerpdffischer051303pdf] (availability date September 30 2004)
Friedman Milton (nd) Samuha [httpwwwsamuhaorgm-1htm] availability date September 30 2004)
FXTOP (2004) Historical Exchange Rates [httpfxtopcomdehistoratesphp3] (availability date September 30 2004)
Gibbons David Meehan Jennifer W (2002) Financing Microfinance for Poverty Reduction [httpwwwmicrocreditsummitorgpapersfinancing_finalpdf] (availability date September 30 2004)
Grameen Bank (2004) Grameen Bank At a Glance [httpwwwgrameen-infoorgbankcdshtml] (availability date September 30 2004)
Grameen Trust (nd) Grameen Bank Replication Program [httpwwwgrameen-infoorggrameengtrustreplicationhtml8721] (availability date September 30 2004)
74
Hossain Farhad (2004) Microfinance in Development [httpwwwvalthelsinkifi staff jkoponenb1104FarhadFeb2304pdf] (availability date October 5 2004)
IMF (2004) Data [httpwwwimforgexternalpubsftweo200402datadbginimcfm] (availability date October 5 2004)
IMI (2004) Investments [httpwwwimi-agcomoverviewindexhtml] (availability date September 30 2004)
IPCC (2001) Summary for Policymakers [httpwwwipccchpubspm22-01pdf] (availability date September 30 2004)
Jansson Tor Wenner Mark (1997) Financial Regulation and its Significance for Microfinance in Latin America and the Caribbean [httpwwwgdrcorgicmgoverniadb-janssonpdf] (availability date October 5 2004)
Ken Daniel Ten Roeun Van (2004) The Cycle of Debt - As Microcredit Institutions Grow Some Question Their Effect on Poverty [httpwwwcamnetcomkhcambodiadaily selected_featurescd-21-02-04htm] (availability date September 30 2004)
Kim Julia (2002) Social Interventions for HIVAIDS - Intervention with Microfinance for AIDS and Gender Equity [httpwwwwitsaczaradarPDF20filesIntervention_monograph_no_picspdfpdf] (availability date September 30 2004)
Llanto Gilberto (nd) Vietnam [httpwwwadborgDocumentsBooksCentral_Banks_MicrofinanceCountry_Studiesvietnampdf] (availability date September 30 2004)
The Microfinance Gateway (nd) Frequently Asked Questions [httpwwwmicrofinance gatewayorgsectionfaq1] (availability date October 5 2004)
Microfinance Rating and Assessment Fund (2004) Qualified Raters [httpwwwmfrating orgmfi_institutionsqualified_ratershtml] (availability date October 5 2004)
Microcredit Summit (1997) Declaration and Plan of Action [httpwwwmicrocreditsummit orgdeclarationhtm] (availability date September 30 2004)
MicroRate (nd) Performance Indicators and Ratios [httpwwwmicroratecomENGLISHsiteRATINGSindicatorshtml] (availability date September 30 2004)
MicroRate (2002) The Finance of Microfinance [httpwwwmicroratecomPDFFinance20of20Microfinancepdf] (availability date September 30 2004)
MicroRate (2004) Adjusted comparison table [httpwwwmicroratecomENGLISHsitePDFAdjusted20Comparison20Table060320engpdf] (availability date October 5 2004)
75
Mix Market (2004) The Mix Market [httpwwwmixmarketorg] (availability date October 5 2004)
Morduch Jonathan (1999b) The Grameen Bank A Financial Reckoning [httpwwwwwsprincetonedu~rpdsmacarthurdownloadsmorduch_grameen_bankpdf] (availability date September 30 2004)
Pallen Dean (1997) Environmental Sourcebook for Micro-Finance Institutions [httpwwwacdi-idagccaINETIMAGESNSFvLUImagesea20summaries$fileSOURC Epdf] (availability date September 30 2004)
Prisma (2002) The Case for Private Capital Market Creation in the Development Field of Microfinance [httpwwwsocialenterprisenetpdfsprivate_capital_marketpdf] (availability date September 30 2004)
Schmidt Reinhard H Zeitinger C-P (1997) Critical Issues in Microbusiness Finance and the Role of Donors No 6 [httpwwwgdrcorgicmmfi-donorpdf] (availability date September 30 2004)
Seibel Hans D (2003b) Commodity finance a commercial proposition Micro- and Mesofinance for Agricultural Commodity Production Processing and Trade [httpwwwuni-koelndeew-fakaef05-20042003-420Commodity20Financepdf] (availability date September 30 2004)
Simanowitz Anton Walter Alice (2002) Ensuring Impact Reaching the Poorest while Building Financially Self-sufficient Institutions and Showing Improvement in the Lives of the Poorest Families [httpwwwidsacukimpactPublicationsWorkingPapersOP3MCSSumdoc] (availability date September 30 2004)
Smith Stephen C Jain Sanjay (1999) Village Banking and Maternal and Child Health Theory and Evidence from Ecuador and Honduras[httphomegwuedu~scsmith healthrevwd801pdf] (availability date September 30 2004)
United Nations (1999) International Year of Microcredit 2005 [httpods-dds-nyunorgdoc UNDOCGENN9976933PDFN9976933 pdfOpenElement] (availability date October 5 2004)
United Nations (2000) United Nations Millennium Declaration [httpods-dds-nyunorgdocUNDOCGENN0055951PDFN0055951pdfOpenElement] (availability date October 5 2004)
US Census Bureau (2004) Total Midyear Population for the World 1950-2050 [httpwwwcensusgovipcwwwworldpophtml] (availability date October 5 2004)
WHO (2004) Making pregnancy safer [httpwwwwhointmediacentrefactsheets fs276en] (availability date September 30 2004)
WHO (2001) Child Health [httpwwwwhointmipfiles2082AAGChildHealthpdf] (availability date September 30 2004)
76
The World Bank Group (nd) Health Nutrition and Population and the Millennium Development Goals [www1worldbankorghnpMDGMDG20-20HNPbookletpdf] (availability date September 30 2004)
Yunus Muhammad (1998) Championing the Right to Credit for Poor Women Around the World [httpaspgrameencom dialoguedialogue34interviewhtml] (availability date September 30 2004)
UNAIDS (2004) [httpwwwunaidsorgbangkok2004GAR2004_pdfUNAIDSGlobalReport2004_enpdf] (availability date September 30 2004)
Ratings
M-Cril (2000) SPANDANA [httpwwwratingfundorgspanishdocsSPANDANA_RatingReportpdf] (availability date October 7 2004)
M-Cril (2001a) BASIX [httpwwwbasixindiacomMcrilasp] (availability date October 7 2004)
M-Cril (2001b) BDB [httpwwwratingfundorgspanishdocsRF_BDBpdf] (availability date October 7 2004)
M-Cril (2001c) SNEHA [httpwwwratingfundorgspanishdocsRF_Sneha-u1pdf] (availability date October 7 2004)
M-Cril (2002a) KCLF [httpwwwratingfundorgdocsRF-KCLF-risk20reportdoc] (availability date October 7 2004)
M-Cril (2002b) NWTF [httpwwwratingfundorgspanishdocsRF_NWTFpdf] (availability date October 7 2004)
M-Cril (2002c) SEEDS [httpwwwratingfundorgspanishdocsRF_SEEDS_2002_Ratingpdf] (availability date October 7 2004)
M-Cril (2002c) Share [httpwwwratingfundorgspanishdocsRF_SHAREpdf] (availability date October 7 2004)
M-Cril (2002d) TSKI [httpwwwratingfundorgspanishdocsRF_Tski_mcrilfinal(-) reportpdf] (availability date October 7 2004)
M-Cril (2003a) ASA [httpwwwratingfundorgdocsASA20updatepdf] (availability date October 7 2004)
M-Cril (2003b) BURO [httpwwwm-crilcomburopdf] (availability date October 7 2004)
M-Cril (2003c) EMT [httpwwwratingfundorgdocsEMTpdf] (availability date October 7 2004)
77
M-Cril (2003d) SKS [httpwwwmixmarketorgendemanddemandshowprofileaspett=25ampshowinfo=adjusted] (availability date October 7 2004)
M-Cril (2003d) TPC [httpwwwratingfundorgdocsTPC_Finalpdf] (availability date October 7 2004)
M-Cril (2004b) UPAP [httpwwwratingfundorgdocsUPAP_2004pdf] (availability date October 7 2004)
Microfinanza (2002a) ACME [httpwwwratingfundorgspanishdocsACME_finalpdf] (availability date October 7 2004)
Microfinanza (2002b) BTFF [httpwwwratingfundorgspanishdocsBTFF_RatingReportpdf] (availability date October 7 2004)
Microfinanza (2002c) BESA [httpwwwratingfundorgspanishdocsBESA_RatingReportpdf] (availability date October 7 2004)
Microfinanza (2002d) CAME [httpwwwratingfundorgdocsEvaluacionCAME(-) Finaldoc] (availability date October 7 2004)
Microfinanza (2002e) RFF [httpwwwratingfundorgdocsRFF20finalpdf] (availability date October 7 2004)
Microfinanza (2002f) PSHM [httpwwwratingfundorgspanishdocsPSHM_Reportpdf] (availability date October 7 2004)
Microfinanza (2003) CAJCA [httpwwwratingfundorgdocsCalificacion_Jardin_Azuayo_ratingpdf] (availability date October 7 2004)
Microserve (2003) ENDA [httpwwwmixmarketorgendemanddemandshowprofileaspett=865ampshowinfo=adjusted] (availability date October 7 2004)
Planet Rating (2002a) FONDEP [httpwwwmfratingorgRatingscompleted_ratingshtml] (availability date October 7 2004)
Planet Rating (2002b) PRIZMA [httpwwwmixmarketorgendemanddemandshowprofileaspett=111ampshowinfo=adjusted] (availability date October 7 2004)
Planet Rating (2002c) SWS [httpwwwratingfundorgspanishdocsSWC_reportpdf] (availability date October 7 2004)
Planet Rating (2002d) ZAKOURA [httpwwwratingfundorgspanishdocsRF_Zakourapdf] (availability date October 7 2004)
Planet Rating (2003a) AMSSF [httpwwwratingfundorgdocsPlanetRating_AMSSF_010803pdf] (availability date October 7 2004)
Planet Rating (2003b) FOCCAS [httpwwwratingfundorgdocsPlanetRatingFOCCAS120803pdf] (availability date October 7 2004)
78
Planet Rating (2003c) PADME [httpwwwmfratingorgdocsPlaNetRatingPADME070302_Englishpdf] (availability date October 7 2004)
Planet Rating (2003d) PAPME [httpwwwmfratingorgdocsPAPME_PlanetRating080903pdf] (availability date October 7 2004)
Planet Rating (2003e) VITAL FINANCE [httpwwwmfratingorgdocsVital20Finance_Sept202003pdf] (availability date October 7 2004)
Planet Rating (2004a) ABA [httpwwwratingfundorgdocsABA_April202004pdf] (availability date October 7 2004)
Planet Rating (2004b) ACEP [httpwwwmfratingorgdocsACEPSeacuteneacutegal_2004pdf] (availability date October 7 2004)
Planet Rating (2004c) AGROINVEST [httpwwwratingfundorgdocsAgroInvest_June202004pdf] (availability date October 7 2004)
Planet Rating (2004d) ASBA [httpwwwratingfundorgdocsASBA_April202004pdf] (availability date October 7 2004)
Planet Rating (2004e) DBACD [httpwwwratingfundorgdocsDBACD_April202004pdf] (availability date October 7 2004)
Planet Rating (2004f) FINADEV [httpwwwmfratingorgdocsFinadev_2004pdf] (availability date October 7 2004)
Planet Rating (2004g) MI-BOSPO [httpwwwratingfundorgdocsMIBOSPO_160404pdf] (availability date October 7 2004)
Planet Rating (2004h) SBACD [httpwwwratingfundorgdocsSBACD_PlanetRating300604pdf] (availability date October 7 2004)
Other Sources
Interview Shaw Newaz Deputy General Manager of the Grameen Bank October 30th
2003
Hodson Charles (2001) Your Business Your World Jim Boulden CNN (ed) Dhaka 2001
8
formal financial institution (a registered bank) but obviously not of a traditional or
conventional one12
Although the other services have become more important in recent years microcredit is
still considered their central service by most MFIs In many countries it refers to loans
below $ 100013 however for significant cross country comparison it is more
meaningful to look at the ratio of the loan amount to the gross national product (GNP)
or gross domestic product (GDP) per capita for the respective countries While a loan of
$1000 is more than four times larger than the GNP per capita in Uganda it represents
less than 20 of the GNP per capita in Mexico The MicroBanking Bulletin (MBB) has
categorized the target market for MFIs by the average outstanding loan amount as a
percentage of the GNP per capita ranging from Low-end (less than 20) to Small
Business (more than 250)14 Especially for the latter category one must to look closely
at the condition of the financial service market where an institution is active Although
MFIs exist in industrialized countries15 one would definitely turn to a traditional
financial institution for a loan bigger than 250 of the GNP per capita and therefore not
to a MFI according to the definition presented above
22 The Origin of Microfinance
Although neither of the terms microcredit or microfinance were used in the academic
literature nor by development aid practitioners before the 1980s or 1990s16
respectively the concept of providing financial services to low income people is much
older
While the emergence of informal financial institutions in Nigeria dates back to the 15th
century17 they were first established in Europe during the 18th century as a response to
the enormous increase in poverty since the end of the extended European wars (1618 ndash
12 See Yunus (2002) p 19 for a more detailed description of the destitute member program of the Grameen Bank which focuses exclusively on persons with no regular income and no assets at all 13 See MicroBanking Bulletin (1997) p 614 See MicroBanking Bulletin (2003) p 5415 See Yunus (1998a) pp 229 et sqq16 See Robinson (2001) p XXX17 See Seibel (2003a) p 12
9
1648)18 In 1720 the first loan fund targeting poor people was founded in Ireland by the
author Jonathan Swift19 After a special law was passed in 1823 which allowed charity
institutions to become formal financial intermediaries a loan fund board was established
in 1836 and a big boom was initiated Their outreach peaked just before the government
introduced a cap on interest rates in 1843 At this time they provided financial services
to almost 20 of Irish households20
The credit cooperatives21 created in Germany in 1847 by Friedrich Wilhelm Raiffeisen
served 14 million people by 191022 He stated that the main objectives of these
cooperatives ldquoshould be to control the use made of money for economic improvements
and to improve the moral and physical values of people and also their will to act by
themselvesrdquo23
In the 1880s the British controlled government of Madras in South India tried to use the
German experience to address poverty which resulted in more than nine million poor
Indians belonging to credit cooperatives by 194624 During this same time the Dutch
colonial administrators constructed a cooperative rural banking system in Indonesia
based on the Raiffeisen model25 which eventually became Bank Rakyat Indonesia
(BRI) now known as the largest MFI in the world26
23 Microfinance after the Second World War
Because of further prudential regulation and effective supervision eg through bank
superintendencies the banking sector in the now developed world experienced
continuous growth Today the vast majority of the citizens of the industrialized
countries have access to financial services with many of them being customers of
former MFIs27
18 See Steinwand (2001) p 5119 See Robinson (2002) p 9620 See Seibel (2003a) p 1021 first known as Darlehnsvereine and now called Raiffeisenbanken22 See Morduch (1999a) p 157323 Raiffeisen (1966) quoted in Richardson (2000) p 324 See Morduch (1999a) p 157425 See Robinson (2002) p 9726 See Roth Steinwand (2004) p 327 See Seibel (2003a) p 11
10
This is not true for most developing countries where market penetration of financial
institutions is far from reaching the majority of the inhabitants (see chapter 4) A variety
of reasons is responsible for this including that the banking sector in the most
developing countries have developed in a very different way to than those in
industrialized countries
One of the most important reasons is that in contrast to the industrialized countries little
attention has been paid to the legal recognition prudential regulation and effective
supervision of informal financial institutions28 This insecure legal environment leads to
several problems Since the regulatory framework for mobilizing savings often does not
fit the needs of institutions targeting low income people many organizations are not
permitted to do so and are therefore missing funds to on-lend as credit29 An additional
problem is the lack of a deposit insurances This not only increases the risk of a bank
run but also keeps people from depositing their savings in a financial institution30 In
addition inappropriate interest rate ceilings prevail in many countries While politics
claim they are lowering the interest rates charged to the poor they de facto only limit
their access to financial services (see chapter 5)31
Another problem that retarded the growth of the financial sector in developing countries
was the supply-leading finance theory which dominated the development strategies of
many countries after the second world war32 This theory ldquo refers to the provision of
loans in advance of the demand for credit for the purpose of inducing economic
growthrdquo33 Since it was believed that poor people were neither able to save (and thus
dependent on outside funding) nor capable of paying commercial rates of interest
massive subsidized credit programs were established34 The results were alarming
Repayment rates often did not exceed 50 percent and some government financed
programs even had default rates of more than 90 percent35 The main reason being that
credit was not provided according to business management principles but instead
28 See Seibel (1998) p 829 See Robinson (2001) p 4930 See Staschen (1999) p 1431 See Gibbons (2000) p 1532 See Morduch (1999a) p 157033 Robinson (2001) p 14034 See Borst (2004) pp 33 et sqq35 See Yunus (1998a) p 154 Robinson (2001) p 145
11
according to political objectives Therefore receiving loans was seen as a reward for the
constituents rather than as a business transaction Most of the funds earmarked for the
poor also never reached them ending up instead in the hands of the local elites
Attracted by the below market interest rates and the possibility not to pay back at all
these groups lobbied to be treated privileged and often used the money received for
consumption or for on-lending at higher rates36 But subsidized credit not only
encouraged corruption it also discouraged sustainable financial institutions since they
could not compete with interest rates that were not aimed to cover all costs and were
sometimes even lower than the interest paid on savings37 The low or negative spread
also worked as a negative incentive to institutionsrsquo effort to mobilize savings which in
turn intensified the problem of credit rationing (see chapter 5)
24 Microfinance Today
In the 1970s a paradigm shift started to take place The failure of subsidized government
or donor driven institutions to meet the demand for financial services in developing
countries let to several new approaches Some of the most prominent ones are presented
below
Bank Dagan Bali (BDB) was established in September 1970 to serve low income people
in Indonesia without any subsidies and is now ldquowell-known as the earliest bank to
institute commercial microfinancerdquo38 While this is not true with regard to the
achievements made in Europe during the 19th century it still can be seen as a turning
point with an ever increasing impact on the view of politicians and development aid
practitioners throughout the world In 1973 ACCION International a United States of
America (USA) based non governmental organization (NGO) disbursed its first loan in
Brazil39 and in 1974 Professor Muhammad Yunus started what later became known as
the Grameen Bank by lending a total of $27 to 42 people in Bangladesh40 One year
later the Self-Employed Womenrsquos Association started to provide loans of about $15 to
36 See Robinson (2001) pp 144 et sqq37 Before BRI underwent a major transformation in 1983 a negative spread between interest rates on loans and savings existed While the bank lent at a 12 annual effective interest rate it paid 15 on savingsSee Robinson (2001) p 10638 Wardhana (2001) p XXVII39 See ACCION (nd)40 See Yunus (1998a) p 16 et sqq
12
poor women in India41 Although the latter examples still were subsidized projects they
used a more business oriented approach and showed the world that poor people can be
good credit risks with repayment rates exceeding 9542 even if the interest rate charged
is higher than that of traditional banks Another milestone was the transformation of
BRI starting in 1984 Once a loss making institution channeling government subsidized
credits to inhabitants of rural Indonesia it is now the largest MFI in the world being
profitable even during the Asian financial crisis of 1997 ndash 199843
In February 1997 more than 2900 policymakers microfinance practitioners and
representatives of various educational institutions and donor agencies from 137
different countries gathered in Washington DC for the first Micro Credit Summit This
was the start of a nine year long campaign to reach 100 million of the world poorest
households with credit for self employment by 200544 According to the Microcredit
Summit Campaign Report 67606080 clients have been reached through 2527 MFIs by
the end of 2002 with 41594778 of them being amongst the poorest before they took
their first loan45 Since the campaign started the average annual growth rate in reaching
clients has been almost 40 percent46 If it has continued at that speed more than 100
million people will have access to microcredit by now and by the end of 2005 the goal
of the microcredit summit campaign would be reached As the president of the World
Bank James Wolfensohn has pointed out providing financial services to 100 million of
the poorest households means helping as many as 500 ndash 600 million poor people47
41 See Bhatt (1997)42 See Yunus (1998a) p 143 et sqq43 See Robinson (2002) p 38044 See Daley-Harris (2003) p 345 ldquoThe Microcredit Summit Campaign defines ldquopoorestrdquo as those who are in the bottom half of those living below their nationrsquos poverty line or are living on less than $1 a day adjusted for purchasing power parity (PPP)rdquo See Daley-Harris (2003) p 3 This definition will also be used throughout this paper46 See Daley-Harris (2003) p 1847 See Morduch (1999a) p 1570
13
3 The Impact of Microcredit
31 Microcredit and the Millennium Development Goals
In 1996 Ismail Serageldin the then chair of the Consultative Group to Assist the Poorest
(CGAP)48 claimed that ldquo[m]icrofinance is a proven instrument to assist the very poorrdquo49
This view is also shared by the World Watch Institute50 and underlines what has been
stated above namely that microfinance can be used as a strong anti-poverty tool But
does microfinance actually meet these expectations and keep this promise51
The impact that microcredit has on the lives of poor people will be demonstrated by
showing how it contributes to each of the eight Millennium Development Goals
(MDGs)52 which are related to the reduction of poverty in all its forms These goals
were resolved in September 2000 by the General Assembly of the UN in their
Millennium Declaration53
32 The Eradication of extreme Poverty and Hunger
The aim of the first MDG is to halve the proportion of people who live on less than $1 a
day between 1990 and 2015 According to current population projections of the World
Bank54 this would equal 849 million people in 201555
48 The Consultative Group to Assist the Poorest is a consortium of 28 public and private development agencies working together to expand access to financial services for the poor in developing countries and was established by the World Bank in 1995 Recently it changed its name to Consultative Group to Assist the Poor49 See Serageldin (1996) p 1150 See Gardner (2002) p 1851 See Morduch (1999a) pp 1569 et sqq52 The Millennium Development Goals are (1) eradicate extreme poverty and hunger (2) achieve universal primary education (3) promote gender equality and empower women (4) reduce child mortality (5) improve maternal health (6) combat HIVAIDS malaria and other diseases (7) ensure environmental sustainability and (8) develop a global partnership for development53 See United Nations (2000)54 See World Bank (2004) p 38 et sqq55 Although it is not explicitly mentioned in the Millennium Declaration it is commonly assumed that the share of people living on less than $1 in low and middle income countries should be halved If the share would be calculated with regard to the worldrsquos total population the goal for 2015 would 818 million people For the worldrsquos total population in 1990 see US Census Bureau (2004)
14
Today almost 11 billion people live on less than $1 and more than 27 Billion live on
less than $2 per day56 The mean income for those living under $1 a day is $077 and it
is $125 for those living under $2 a day57 While the number of people living on less
than $1 per day is slowly decreasing and is expected to be 913 million in 2015 the
number of people living on less than $2 a day is actually increasing58 One of the
outcomes from this degree of poverty is that more than 27000 children die every day
from mostly preventable diseases many of them related to hunger59
Microcredit enables poor people to start new businesses or to diversify existing ones
which helps them to increase their income In addition to large amounts of anecdotal
evidence several studies have documented the positive economic impact microcredit
has on its clients Cloud and Panjaitan-Drioadisuryo have found that the average income
of a sample of BRI borrowers has increased by 112 percent and that 90 percent of their
families have crossed the poverty line60 Only 12 out of the 121 respondents of that
study reported that their income had not increased61 According to the Grameen Bank
website 5109 percent of their clients have crossed the poverty line since they took their
first loan62
A study conducted by Barnes showed that the program of the Zambuko Trust a local
MFI in Zambia had a considerable impact on the poorest clients consumption of meat
fish and chicken63 While 76 percent of the continuing clients of the MFI called Share in
India significantly increased their income and 50 percent have crossed the poverty line 64 Khandker discovered in his well known study ldquoFighting poverty with microcreditrdquo
that there is a connection between the microcredit programs of three Bangladeshi MFIs
and household per capita expenditure For every dollar borrowed by a Grameen Bank
member household consumption increases by $018 In addition he found that 5 percent
56 See Chen and Ravallion (2004) p 2957 In fact those people live on less than $108 and $215 respectively a day in 1993 PPP This means that the nominal dollar value of their income is considerably lower See Chen and Ravallion (2004) p 9 58Both numbers are decreasing in Asia but increasing in the rest of the world See Chen and Ravallion (2004) p 22 et sqq59 See UNICEF (2002) p 660 A consistent definition of the term ldquopoverty linerdquo does not exists among different nations Therefore the term will be used according to the definition of the respective country in this paper61 See Panjaitan-Drioadisuryo and Cloud (1999) p 77562 See Grameen Bank (2004) 63 See Barnes (2001) p 8664 See Simanowitz and Walter (2002) p 16
15
of Grameen Bank borrowers move out of poverty every year65 Supposing Khandkerrsquos
findings were correct for all MFIs worldwide and the Microcredit Summit Campaign
achieved its goal of reaching 100 million of the poorest households with microcredit by
2005 then 25 million people (assuming an average family size of five) would leave
poverty every year66 Although this number would have to be adjusted in order take into
consideration the MFI clients who have crossed the poverty line already and of course
the experiences made in Bangladesh can not be transferred precisely to other countries
it still demonstrates the enormous effect that microcredit can have on assisting the
poorest to move out of poverty
Although a 1996 study of Hulme and Mosley states that providing microcredit can also
have a negative impact on the income of the poorest households67 these findings can
be considered as disproved by the recent bulk of evidence drawing favorable
conclusions68
33 Achievement of universal primary Education
The aim of the second MDG is to ensure that all children will be able to complete
primary school by 2015
Currently more than 100 million children most of them girls are not in school69
Besides school fees poor households often can not afford to send their children to
school because they need them to help in the family business
Microcredit programs mainly contribute to the second MDG by increasing families
income and therefore enabling parents to send their children to school Barnes Gaile
and Kibombo found that clients of an MFI in Uganda spent significantly more on
childrenrsquos education than non-clients70 and in Zambia Barnes showed that ongoing
participation in the Zambuko Trustrsquos program had a positive impact on the members
65 See Khandker (1998) p 5666 See Daley-Harris (2003) p 2467 See Hulme and Mosley (1996) p 180 et sqq 68 See Gibbons and Meehan (1998) p 13669 See UNICEF (2002) p 2270 See Barnes Gaile and Kibombo (2001) p 64
16
children staying in school71 In Bangladesh the probability of girls enrolling in school
increased by 19 percent for every 1 percent increase in Grameen Bank loans to female
clients For boys this number was even higher with the mean being 24 percent72
34 Promote gender Equality and empower Women
The aim of the third MDG is to eliminate the disparity in the ratios of girls to boys in
primary secondary and tertiary education in the ratio of literate females to males and to
increase the share of women in the labor market and in parliament73
At present the literacy rate for women is lower than for man all over the world
According to the Human Development Report 2004 the average female literacy rate as
a percentage of male literacy rate is 759 in developing countries and is as low as 37 in
Niger74 But women are not only discriminated against in education but also in access to
medical services and therefore have a higher mortality rate than man75 The worldwide
tendency for women to be underrepresented in the labor market and in the parliaments is
even more severe in developing countries76 Although several women have become
heads of state in various Asian countries (eg Bangladesh India and Indonesia) this is
probably due to them being wives or daughters of former respected male politicians
Since women have a higher repayment rate than man77 and also tend to invest increases
in income on the household and on their children rather than on themselves78 most
MFIs prefer female clients79 Therefore they empower women in many ways Often
MFIs not only encourage women to become involved in financial transactions for the
first time but also to become independent active members of the economy and to
acquire assets in their own names Cheston and Kuhn found that 68 percent of the
women participating in an MFI program in Nepal ldquohellip experienced an increase their
71 See Barnes (2001) p 8472 See Khandker (1998) p 4973 See World Bank (2001) p 2074 See UNDP (2004) pp 225 et sqq75 See Sen (2000) p 23276 See Sen (2000) pp 242 et sqq77 See Littlefield Morduch and Hashemi (2003) p 778 See Yunus (1998a) pp 116 et sqq79 According to the Microcredit Summit Campaign Report 79 or 37677080 of the poorest clients were women See Daley-Harris (2003) p 3
17
decision-making roles in the areas of family planning childrenrsquos marriage buying and
selling property and sending their daughters to school - all areas of decision making
traditionally dominated by menrdquo80 The program of the Lower Pra Rural Bank in Ghana
had an positive impact on womenrsquos participation in the community81 which is true as
well for the CRECER program in Bolivia82 In Bangladesh the Grameen Bank and the
Bangladesh Rural Advancement Committee (BRAC) the two biggest MFIs of the
country had a significant positive effect on womenrsquos empowerment measured through
eight different indicators83 After joining Grameen Bank only 21 percent of the female
members considered themselves as unemployed while this number was 50 percent
before joining84 According to the Grameen Bank website 93 percent of the Bankrsquos
shares are owned by their borrowers which elect the members of the board every three
years They also get familiar with the election process by more frequently voting for
representatives at the lower level of the organizational structure Partly because of this
experience they are more likely to run for public office In the 2003 local government
elections Grameen Bank members constituted 24 of the seats reserved for women
while they represent less than 10 of Bangladeshi adult female population85 Female
clients of MFIs from countries like the Philippines Bolivia and Nepal have reported
similar occurrences86
35 Reduce Child Mortality and improve Maternal Health
The aim of the fourth MDG is to reduce the under-five mortality rate by two-thirds
between 1990 and 2015 and the fifth MDG strives for a three quarter reduction in the
maternal mortality ratio by the same date
As has been stated above more than 10 million children are dying annually in the
developing world of mostly preventable causes with malnutrition playing a role in over
80 See Cheston and Kuhn (2002) p 1881 See MkNelly and Dunford (1998) p 5482 See MkNelly and Dunford (1999) p 7183 The eight different indicators are ldquofreedom of movement economic security ability to make small and larger independent purchases participation in important family decisions relative freedom from domination by the family political and legal awareness and participation in political campaigning and public protestsrdquo Hashemi and Schuler (1998) p 3684 See Holcombe (1995) p 5185 See Grameen Bank (2004)and CIA (2004)86 See Littlefield Morduch and Hashemi (2003) p 8
18
half of the childrsquos deaths and in over 50 countries child mortality rates are greater than
100 deaths per 1000 live births87 Maternal mortality is also a significant problem in the
developing world with more than 500000 women dying every year from pregnancy
related causes88
MFIs are mainly contributing to the these MDGs by increasing families income and
therefore enabling the households to afford better nutrition and medical services
Furthermore they are often linked with microinsurance or health education programs
In addition to what has been showed in chapter 31 Pitt Khandker and Millimet
estimate that a 10 percent increase in the loan size of a female borrower in Bangladesh
increases the arm circumference of their daughters by 6389 Smith and Jain found that
village banking in Ecuador had a positive effect on child diarrhea90 which is responsible
for 15 of child deaths91 Since Sen argues that an improved status of women within
the family reduces child mortality92 the empowerment of women through MFIs is also
contributing to this cause
Although no study has been conducted so far on the direct impact of microcredit on
maternal health it can be assumed that an overall improvement of access to medical
services reduces maternal mortality as well A study of the Morgan State University for
example suggests that microcredit has a positive effect on the prevalence of
contraceptives93 which leads to a decrease of unwanted pregnancies and therefore
reduces maternal death
36 Combat HIVAIDS Malaria and other diseases
The aim of the sixth MDG is to halt and begin to reverse by 2015 the spread of
HIVAIDS malaria and other major diseases and to assist children orphaned by HIV
87 See World Bank (2001) p 888 See WHO (2004) 89 See Pitt Khandker and Millimet (2003) p 11390 See Smith and Jain (1999) p 3791 See WHO (2001) 92 See Sen (2000) p 23593 See Amin et al (2001) p 1614
19
In 2003 29 million people died because of HIV and about 48 million became infected
the greatest number since AIDS was discovered 23 years ago94 This pandemic has lead
to a tremendous decrease in the life expectancy in the hardest hit countries Botswana
for example one of the richest and most democratic countries in Africa has a
HIVAIDS adult prevalence rate of 388 and a life expectancy at birth of less than 31
years95
Malaria not only causes more than one million deaths annually it leads also to 300 ndash
500 million clinical cases a year Both numbers have been steadily increasing over the
past two decades96 More than two million people a year are killed by tuberculosis
another global health problem This curable disease is estimated to cost poor
communities about $12 billion every year since even those who survive normally lose
more than 3 month of work time while recovering97
MFIs contribute to the sixth MDG in several ways By increasing clientrsquos income they
help households affected by HIV or other diseases to better cope with the situation
Besides spending more money on health services and nutrition MFI clients also tend to
be more able and willing to support AIDS orphans than non clients98 In addition to the
already stated increase in the use of contraceptives99 several innovative approaches to
deal with disease related crisis have also arisen This is of course necessary not only to
counteract the devastating effect the above discussed epidemics can have on MFI
clients but also to not put the viability of the respective institution at risk One option is
to integrate education services in the MFI programs and encourage clients to form
solidarity groups100 It has been shown that these services do not necessarily decrease
the effectiveness of the institutionsrsquo employees101 Another way is to strengthen the ties
to NGOs specialize in dealing with the respective disease Synergies gained through this
cooperation can help clients to better deal with the situation and in the end increase their
94 See UNAIDS (2004) p 2395 See CIA (2004)96 See World Bank (2001) p 1697 See World Bank (2001) p 1298 See Barnes (2001) p 6499 See also Kim et al (2002) p 18100 See Donahue and Sussman (1999) p A 14101 See Donahue Kabbucho and Osinde (2001) p 25
20
repayment rates Various MFIs also have introduced loan and health insurance products
or cultivated linkages with organizations doing so102
It has to be stated that despite the benefits MFIs can provide to people effected by
HIVAIDS or other diseases microcredit can also be a burden for those who are already
chronically ill These people can still benefit through loans provided to members of the
family or the community or through one of the other services mentioned above
37 Ensure environmental Sustainability
The aims of the seventh MDG are to support and promote the principles of sustainable
development and put them into action and to improve the lives of slum dwellers and
people without sustainable access to safe drinking water and sanitation
Today climate change is considered as the major environmental problem103 The
Intergovernmental Panel on Climate Change (IPCC) states that human activities
contribute to most of the 06 degC increase in global average temperature over the 20th
century and the predicted increase of another 14 to 58 degC between 1990 and 2100104
Emission of carbon from fossil fuel is reported to have the dominant influence on this
development While the total emission was 16 billion tons in 1950 it was already 65
billion tons in 2000 and is expected to continue to grow105 This development would
lead to a rise in the average sea level of between 9 and 88 centimeters during the next
century106 Furthermore it is predicted that global warming increases the risk of extreme
events like cyclones or floods leads to an increase in the number of people infected by
diseases like malaria and decreases the potential crop harvest and water availability
especially in developing countries107 In 2000 already 11 billion people lacked access to
clean drinking water and 24 billion to basic sanitation108
102 See Barnes (2001) p 40 Barnes Gaile and Kibombo (2001) p 13 and Grameen Bank (2004)103 See Gardner (2002) p 5104 See IPCC (2001) pp 2 et sqq105 Worldwatch Institute (2002) p 52 et sqq106 See IPCC (2001) p 16107 See Dunn and Flavin p 29108 See UNFPA (2004) p 18
21
MFIs contribute to achieving the seventh MDG in several ways By providing loans for
the purchase of renewable energy technologies they help people in developing
countries to increase their per capita energy consumption without increasing the carbon
dioxide emission In a 2003 survey of 140 MFIs from 80 different countries 21 said
they provide credits for solar home systems and another 19 stated they are interested in
becoming engaged in this business109 While Grameen Shakti a rural energy service
company cooperating with the Grameen Bank in Bangladesh has already installed more
than 23000 solar home systems110 a 2000 World Bank study reports twelve projects
providing solar home systems to rural households with a target of 500000
installations111 It has also been suggested that MFIs should raise environmental
awareness among their clients112 but so far no data is available on how staff can cope
with this additional task Many MFIs also provide loans for improvements in sanitation
and the water supply of their clients Varley gives several examples from Africa Asia
and Latin America on how microcredit not only has helped to invest in rainwater
collection systems but also how it has enabled households to increase their water
supply through community water associations113 In addition many MFIs provide credit
for the construction of sanitary latrines114 The situation of slum dwellers is also
positively effected by MFIs Directly through their services in poor urban communities
and indirectly by creating jobs in rural areas and therefore easing the pressure on urban
labor markets
38 Develop a global Partnership for Development
The eight MDG is about the means to achieve the other seven MDGs It calls for all
players involved in the endeavor of development and poverty eradication to work as
partners in a global context
Again MFIs are contributing to the eight MDG in many ways This is occurring through
international networks that provide funding and technical assistance through internet
information portals and specialized journals through social and for profit investors and
109 See Wimmer and Barua (2004) p 174110 Barua (2004) 111 See Martinot and Cabraal (2000) p 6112 See Pallen (1997) p 11 Lal (nd)113 See Varley (1995) pp 39 et sqq114 See Jalvaani (1999) pp 1 et sqq Varley (1995) pp 39 et sqq
22
specialized rating agencies The Bangladesh-based Grameen Trust is one of around 30
networks in operation Besides collaborating with over 200 MFIs around the world it
has directly operated three projects in Afghanistan Kosovo and Myanmar115 While the
ACCION network serves almost 12 million active clients in 19 countries throughout
America and sub-Saharan Africa116 FINCArsquos network operates in three different
continents where it serves more than 200000 customers117 In November 1997 the
MicroBanking Bulletin (MBB) was first published by the microfinance program at the
Economic Institute at the University of Colorado118 Its aim is to develop a database on
the financial performance of MFIs from all over the world which is now available
through the Mix Market an internet portal that also provides information about more
than 300 MFIs investors donor institutions and other related development
organizations119 Two years later the Marriott School at Brigham Young University
started to publish the Journal of Microfinance which has an editorial board of
microfinance experts from all over the world and offers the latest research on this
topic120 In the late 1990s a number of companies became attracted by the microfinance
market and started to invest in MFIs The German based Internationale Mikro
Investitionen Aktiengesellschaft (IMI) for example has already invested more than euro46
million in 19 MFIs in four different continents and plans to invest another euro27 million
before October 2004121 BlueOrchard Finance a microfinance investment consultancy
has channeled more than $60 million worth of private capital to some 40 MFIs
worldwide through investment funds and bond issues122 Big commercial banks like
Citigroup Deutsche Bank and ABN Amro also started to get involved in the
microfinance sector although this is mainly still perceived as a public relation activity
and not as a for-profit investment123 There are also several rating agencies specializing
in MFIs Dependent on their rating these institutions can help MFIs to receive money
from donors or investors Four of the most prominent rating agencies are PlanetFinance
115 See Grameen Trust (nd)116 See ACCION (nd)117 See FINCA (nd)118 See MicroBanking Bulletin (1997) p 5119 See The Mix (2004)120 See Woodworth and Woller (1999) p 6121 See IMI (2004)122 See BlueOrchard (2004b) p 3123 See Busch and Kort (2004) p 8 Fischer (2003) p 6
23
with headquarters in France M-Cril based in India Microfinanza in Italy and
MicroRate with offices in the USA and South Africa124
124 See Microfinance Rating and Assessment Fund (2004)
24
4 Microcredit Outreach
41 The Demand for Microcredit
Although it has been shown that microcredit is one of the most effective poverty
eradication tools that it is considered a human right by some of its advocates125 and it
can contribute considerably to the development of the financial sector in developing
countries an enormous gap still exists between supply and demand for microcredit
Estimates on the demand for microcredit vary greatly While USAID estimates the
number of potential microfinance clients is between 100 and 200 million126 the
Microcredit Summit Campaign states the total demand is more than 234 million
people127 CGAP recognizes some 500 million micro-entrepreneurs who have the
potential to become customers of MFIs128
Marguerite Robinson calculates the demand as follows ldquoAssuming five people to a
household among the 45 billion people living in low- and lower-middle-income
economies in 1999 (World Bank World Development Report 20002001) there are 900
million households in those economies If estimating conservatively we assume that
informal commercial moneylenders supply credit to 30 percent of these households at
least once a year this would mean that there are 270 million households borrowing
from informal moneylenders in a year Undoubtedly however many of these
households borrow multiple times within a yearrdquo129 Although this is a very rough
estimate assuming big differences in demand for microcredit in different countries the
number seems to be the most meaningful In contrast to the estimate of the Microcredit
Summit Campaign it does not include every single household living on less than $1 a
day but according to the definition presented in chapter 1 it counts everyone who has
no regular access to traditional financial institutions but demands such services
Obviously not all people who draw on moneylenders have financial needs that could be
matched through MFIs On the other hand interest rates charged by moneylenders tend
125 See Yunus (1998b) 126 See Christen et al (1995) p 15127 See Daley Harris (2003) p 22 128 See Robinson (2001) p 26129 See Robinson (2001) p 215
25
to be considerably higher than those of MFIs The former normally charge effective
monthly rates between ten and several hundred percent per month the latter generally
charge between 15 and five percent which enables them to attract additional clients130
42 The Supply of Microcredit
In spite of the impressive growth of MFIs around the world the demand for microcredit
is far from being met and this it is not likely to change in the near future The
Microcredit Summit Campaign reported that by the end of 2002 67606080 clients131
were reached through MFIs and that this number has increased by almost 40 percent
annually for the last five years132 It is likely that this tremendous speed of growth is at
least partly due to including MFIs which have not been reporting to the Campaign from
its start in 1997 although they have already existed at that time These institutions
contributed 22 percent to the growth in poorest clients in 2000 578 percent in 2001 and
338 percent in 2002 The growth of the poorest clients increased at least party because
of an expanded definition of the term ldquopoorestrdquo133 Since the contribution of MFIs
which previously have not been considered can be expected to decrease dramatically
the growth rate as stated by the Microcredit Summit Campaign can not be used to
predict the future development of the microfinance sector Another factor likely to slow
down the growth is the concentration of microfinance activities in some Asian countries
where almost 90 percent of the poorest microfinance clients live today134 Even if one
takes into consideration the relative size of Asiarsquos population and the fact that many
MFI customers in Latin America are relatively better off and therefore are not included
in this numbers the coverage of this part of the world far exceeds the others In
Bangladesh for example the microfinance market is close to saturation More than
eleven million households were served by several hundred MFIs in 2001135 Among
them are Grameen Bank and BRAC two of the best known MFIs in the world both
providing their services to more than three million customers With an average
household size of five it can be assumed that in Bangladesh the number of people
130 See Gibbons and Meehan (1999) pp 144 et sqq131 41594778 of them belonged to the poorest before they took their first loan The relative numbers in the following are for these poorest clients only since no other current data was available It can be assumed though that this works as a good proxy for the total number of clients 132 See Daley Harris (2003) p 3133 See Daley Harris (2003) p 17134 See Daley Harris (2003) p 21135 See Ahmed (2003)
26
benefiting from microcredit already surpasses the number of people living below the
poverty line which is estimated to be slightly higher than 50 million136 Therefore
Bangladesh will not contribute to the growth of the microfinance sector as much as it
has done in previous years This is also true for Vietnam Thailand and to a lesser
extent Indonesia Eight of the nine MFIs serving more than one million clients are based
in these countries while the ninth is based in India where due to its one billion
inhabitants the microfinance market is still far from saturation137 In contrast the
supply in Brazil meets less than two percent of the demand which is estimated to be
about 58 million potential clients138 For these reasons greater amount of future growth
must come from smaller or new MFIs in Latin America India China and especially
Africa where almost 30 percent of the worldrsquos poorest live139
43 Meeting the Demand
To fill the gap between the demand and supply for microcredit tremendous investments
are necessary to increase the loan funds of MFIs and build up their capacity through
upgrading existing institutions or building new ones Again estimates on how much
capital is needed vary greatly with the highest being at more than $300 billion140
In 1997 the Microcredit Summit Campaign estimated that $216 billion would be
needed to achieve their goal of providing microcredit to 100 million of the poorest
households This was calculated in the following way Since some 8 million people
already received microcredit in 1997 another 92 million needed to be reached
Assuming $200 ($150 for loan fund and $50 for capacity building) would be needed per
person for 88 million people in developing countries and $1000 ($500 for loan fund and
$500 for capacity building) would be needed for 4 million people in industrialized
countries the capital required ends up to be $216 billion141 For several reasons this
136 See CIA (2004)137 These institutions are The Grameen Bank BRAC Proshika and the Association for Social Advancement (ASA) in Bangladesh the Vietnam Bank for Agriculture and Rural Development (VBARD) and the Vietnam Bank for the Poor (VBA) in Vietnam BRI in Indonesia Bank for Agriculture and Agricultural Co-operatives (BAAC) in Thailand the National Bank for Agriculture and Rural Development (NABARD) in India See Ahmed (nd) p 1 Llanto (nd) p 337138 See Mezzera (2002) p 23139 See See Chen and Ravallion (2004) p 29140 See Clear Profit (2004) Prisma (2002)141 See The Microcredit Summit (1997)
27
number is not qualified to predict the total amount of capital needed to meet the demand
for microcredit On the one hand it focuses mainly on the low end of the market and
therefore underestimates the average loan fund needed On the other hand it does not
take the increasing capital demand from established MFIs into account A survey of 119
MFIs found that the average loan size to increased from $406 in 2002 to $498 in
2003142 This is mainly due to the fact that MFI clients once they have paid back their
loans usually demand larger ones for the continual development of their businesses
and therefore further increase the demand for capital of established MFIs The Grameen
Bank for example has a ceiling on its loans which increases or decreases depending on
the borrowers performance regarding repayments and savings143 While the maximum
amount for the first loan is fixed at approximately $75144 the largest loan disbursed so
far was $17195145 Thus if one estimates that by now 100 million people are borrowing
from MFIs146 another 170 million need to be reached to meet the estimated demand
Assuming an average of $600 ($400 for loan fund and $200 for capacity building) is
needed for every new client and another $200 is needed for every existing client to meet
the demand for larger loans a total of $122 billion is required This rough estimate
helps to convey the approximate amount of capital needed to meet the demand for
microcredit
So far the demand for funds is being partly met by donors which annually provide
between $500 million and $1 billion147 and through the mobilization of local savings
Obviously the amount of money provided by donors will not be able to meet the capital
demand for microcredit in the short term The mobilization of savings on the other hand
has been extremely successful in some cases with BRI probably being the most
prominent example After adapting commercial principals in October 1984 BRI was
able to raise its deposits from $161060 to more than $32 billion in 2003 which equals
almost two times its current loan portfolio148 Many other MFIs like BDB in Indonesia
142 Own calculations Without BRI the numbers would be $343 and $409 See Appendix 1143 See Grameen Bank (2003) p 13144 The accurate amount is 5000 Taka See Interview with Shaw Newaz145 Grameen Bank (2004)146 According to the data provided by the Daley Harris (2003) an annual increase in MFI clients ofapproximately 25 percent from 31122002 till the 3092004 would be needed to reach 100 million clients by now This rated is considerably below the average of the previous five years (38 percent) Therefore it can be assumed as realistic despite the growth hindering factors presented above147 See CGAP (2003) p 8148 See Robinson (2002) p 273 Mix Market (2004)
28
XacBank in Mongolia the Equity Building Society in Kenya or the Centenary Rural
Development Bank in Uganda also have managed to cover their loan portfolio fully
through internally mobilized resources149 The Grameen Bank is also expected to do so
in the first half of 2005150 In addition to raising much needed capital for on-lending the
provision of saving services can deliver notable social benefits itself151
Despite these impressive achievements even the combination of donor money and local
savings at their current levels will not be able to provide the capital needed to continue
the rapid growth of the microfinance sector Especially in their early years MFIs rely on
outside funding BRI for example needed six years before the amount of locally
mobilized savings surpassed the total amount of outstanding loans During this time
expenses and the loan portfolio were covered through a government grant worth $20
million and two World Bank loans of $5 and $97 million respectively152 It also
benefited from a network of more than 3600 branches which were established
throughout the country during the 1970s and early 80s in order to provide government
subsidized credit in rural areas153
The Grameen Bank also widely known as a best practice MFI has received about $175
million in direct and indirect subsidies between 1985 and 1996154 and continues to rely
on outside funding at below market interest rates This is made possible either through
special loans from the Bangladesh Bank or through offering bonds guaranteed by the
Bangladesh government155 - an option most MFIs do not have BDB might be one of the
very few examples which were able to finance their activities through savings and
commercial loans from the start but its outreach did not reach a large scale nor did it
serve the low end of the market In 2000 after 30 years of operation BDB provides
credit to only 10417 clients with an average loan balance of more than $5000156
approximately eight times the countries GDP per capita157
149 See Mix Market (2004)150 See Grameen Bank (2004)151 See Robinson (2001) pp 263 et sqq152 See Seibel and Schmidt (2000) p 4153 See Robinson (2002) p 180154 See Morduch (1999b) p 8155 See Morduch (1999ba) p 25 et sqq156 See Robinson (2002) p 387157 See CIA (2004)
29
Another problem keeping many MFIs from collecting savings is that they do not want
to become a regulated financial institution or do not meet the criteria in their respective
country and therefore they are simply not allowed to mobilize savings from the public
In summary the examples and numbers presented in this chapter support the argument
that the amount of capital that can be raised through donors and locally mobilized
savings is not enough for continuous rapid growth of the microfinance sector If this
lack of capital is not met through other sources the microfinance sector will fail to
contribute its full potential to the achievement of the MDGs
44 Microfinance and the Capital Markets
Regardless of whether the amount of capital needed for the development of the
microfinance sector is $20 or $300 billion it represents only a tiny fraction of the
worldwide capital markets which are estimated at $30 trillion158 Therefore if the
microfinance industry were able to tap the financial markets it would be able to grow
much faster and soon serve the millions of micro-entrepreneurs which currently can not
develop theirs businesses because of capital constrains Another advantage would be
that scarce donor money currently used for the development of the microfinance sector
could be used for other projects that do not have the potential to draw money from
commercial sources This view is shared by Michael Chu the former CEO of ACCION
who made the following statement in 1998 ldquoMicrofinance today stands at the threshold
of its next major stage the connection with the capital marketsrdquo159 Many attempts have
been made since that time Successful MFIs like BancoSol in Bolivia further
strengthened their ties to the capital markets which in some cases already provide the
majority of their funding160 Microfinance investment advisors like BlueOrchard
Finance have become middlemen for MFIs and the financial markets Nevertheless
these links are still far from reaching major scale Currently only approximately 20
percent of MFIs funding comes from commercial sources161 and the biggest bond issue
dedicated to fund MFIs totals only $40 million In addition these funds mainly end up
158 See Brynjolfsson (2004) 159 Chu (1998) quoted in Robinson (2001) p 23160 See Robinson (2001) p 69161 See Dominiceacute (2004)
30
in established institutions in Latin America or Eastern Europe162 while smaller
organizations only benefit indirectly if at all
162 See Clear Profit (2004) IMI (2004)
31
5 Credit Rationing
Until recently the predominant answer to why commercial banks or venture capital
companies did not invest in the microfinance sector was that the poor are not bankable
Besides lacking education and therefore not being able to deal with formal financial
institutions they were viewed as bad credit risk who were unable to invest the borrowed
money in a way that would allow them to repay the loan and interest at a commercial
rate163 Another reason that kept attention away from the idea of providing financial
services to low income people was the belief that informal moneylenders already met
this demand These skeptics felt affirmed through the poor performance of subsidized
credit programs as described in chapter 22 Although it is true that moneylenders
serve a huge number of people in the developing world they more often than not charge
usury interest rates of up to 20000 percent per month164 While the argument that poor
people are not able to participate in the formal financial market can be overcome by
adapting the services accordingly165 the claim of low returns on their investments is not
only proved wrong by empirical evidence but also contradicts economic theory as will
be shown in chapter 53
51 The imperfect Information Paradigm
A more elaborate explanation for the short supply of financial services to low income
people that can be derived from the imperfect information paradigm based
predominantly on the works of Akerlof166 and Stiglitz and Weiss167 After giving a brief
summary of their argument an adaptation of their findings to the microfinance market
will be presented and subsequently it will be shown how their conclusions can be
overcome
Behind the imperfect information paradigm lies the theory of asymmetric information
which simply states that if two parties conduct a transaction one is likely to have more
163 See Ghatak (1983) p 21 et sqq Yunus (1998) p 102 et sqq Robinson (2001) p 35 et sqq164 See Robinson (2001) p 17165 See Seibel (2003b) p 2 BRAC (2003) pp 15et sqq Yunus (1998) pp 151 et sqq 166 See Akerlof (1970) pp 488 et sqq167 See Stiglitz and Weiss (1981) pp 393 et sqq
32
information than the other and is trying to use that for its own advantage168 Applied to
the banking sector this means that a person applying for credit can better judge the
likelihood of repaying the loan than the bank This is because the borrower has better
knowledge of the market she wants to invest in her skills and her willingness to repay
Moreover the bank might not be able to observe if the borrower uses the loan for the
agreed purpose These occurrences can lead to what is known as adverse selection and
moral hazard In this case adverse selection refers to the problem that banks might
attract borrowers with a low probability of repayment if they can not distinguish
between high and low risk loan applicants Moral hazard occurs after the provision of
the loan when the borrower spends the money on a purpose different to the prescribed
purpose and therefore lowers the probability of repayment This can happen eg by
investing in a more risky project or through spending the money on consumption If the
bank is not able to find a cost effective way to avoid these problems it might raise its
interest rate in order to compensate for the increased risk
Figure 1 Expected Bank Return and the Interest Rate
Source Stiglitz and Weiss (1981) p 394
Since this might discourage low risk borrowers from applying for credit and encourage
borrowers who continue to take loans to invest in riskier projects the share of high risk
168 See Neus (1998) p 85 et sqq
INTEREST RATEI
EX
PE
CT
ED
RE
TU
RN
TO
TH
E B
AN
K
33
borrowers could increase and therefore reinforce the problems stated above Thus
increasing the interest rate beyond a certain point actually leads to a decrease in the
expected return to the lender This context is illustrated in figure 1 with I being the
interest rate which maximizes the expected returns to the bank Obviously the bank
would charge the interest rate I in order to maximize its expected return However this
price for capital was not determined through supply and demand as economic theory
would predict It is conceivable that at the interest rate I the demand for credit exceeds
the supply but even if loan applicants would offer to pay a higher interest rate the bank
would refuse because it associates such a loan with high risk As a result credit might
be rationed169
52 Adaptation to the Microfinance Sector
Through some adaptations this model can also help to explain the lack of funds
provided to low income people In the original model of Stiglitz and Weiss several
assumptions have been made that need to be suspended in order to compare the credit
markets for low and high income people and give an explanation why the latter is
widely neglected by institutional investors
Evidently the assumptions that the amount borrowed is equal for each loan applicant
and that transaction costs170 need not to be taken into account171 are not suitable for this
context While the average loan size of MFI customers is much smaller than that of
clients from traditional banks the transaction costs as a share of the loan are
considerably higher because the lenderrsquos costs for conscientious processing a credit
applications are only slightly smaller for a $50 loan than for a $100000 or a
$10000000 loan
In figure 2 the R(I)large curve represents the return to the bank for large loans with
regard to the interest rate I and the R(I)small curve describes the same correlation for
small loans It is shifts downwards to reflect the assertion that the imperfect information
169 See Stiglitz and Weiss (1981) p 394170 In this paper the term bdquotransaction costsldquo refers to the operating expense ratio as defined by MicroRate It ldquois calculated by dividing all expenses related to the operation of the institution (including all the administrative and salary expenses depreciation and board fees) by the period average gross portfoliordquo See MicroRate and Inter-American Development Bank (IADB) (2003) p 16 171 See Stiglitz and Weiss (1981) p 396
34
paradigm has a more severe effect on poor people than on the better off They are
expected to have less profitable investment opportunities at their disposal172 and
therefore are more likely to invest in riskier projects which increase the probability of
default and hence decrease the expected return to the bank Additionally one might
expect poor people to be more likely than others to spend borrowed money on
consumption instead of an income generating activity particularly if a crisis arises It
seems understandable that food or urgently needed medicine are given priority over
repaying a loan
The second shift downwards is due to transaction costs As stated above they are
relatively higher for smaller loans Obviously transaction costs are incurred in the
provision of a large loan as well but since they are much smaller with regard to the loan
amount they are not included in the diagram for reasons of clarity
Figure 2 The extended Model
Source Own diagram adapted from Stiglitz and Weiss (1981) p 394
172 See Khandker (1998) p 8
INTEREST RATE I
SmallLoans
LargeLoans
Transaction costs
Lack of investment opportunities
R(I)large
R(I)small
EX
PE
CT
ED
RE
TU
RN
TO
TH
E B
AN
K
35
53 Overcoming Credit Rationing for the Microfinance Sector
If the conclusions in chapter 51 hold it is rational for a profit maximizing investor to
neglect the microfinance sector as long as no surplus funds in the market for large loans
exist This finding can help to explain the small amount of money provided to the
microfinance sector from commercial investors On the other hand it has to be stated
that this theory is reflexive as defined by Soros173 It not only explains but also forms
reality since it has the potential to reinforce the view of potential investors that
microfinance is a less profitable business174 Therefore demonstrating under which
conditions microfinance can be profitable and in some cases be more profitable than
traditional businesses is of crucial importance
To provide a fairer view of the microfinance sector a further assumption of the Stiglitz
and Weiss model that needs to be suspended is that all investments made by the
borrowers have the same expected return175 As stated above this contradicts economic
theory which claims ceteris paribus capital productivity decreases while the amount of
fixed capital increases In combination with a low capital endowment micro-enterprises
are usually faced with an excess supply of unskilled labor especially in developing
countries176 Hence small enterprises use far less capital per employee than big business
and therefore their marginal productivity of capital is much higher177 This is intuitive if
one imagines an economic actor who wants to invest several packages of capital
Obviously she would invest the first package where she expects the highest return the
second package where she expects the second highest return and so on Each additional
investment opportunity would lead to lower or at best equal returns178 While this
simplified example has limitations it demonstrates how the marginal productivity of
capital can diminish Although it might actually increase until a certain point179 this can
be expected to be so low in this context that it has no influence on the correlation as
shown in figure 2
173 See Soros (1998) pp 14 et sqq174 See Goodwin-Groen (1999) p 8175 See Stiglitz and Weiss (1981) p 395176 See Perkins et al (2001) pp 95 et sqq177 See Tschach (2000) p 8178 See Rosenberg (2002) p 11179 See Rechard G Lipsey (1979) pp 211 et sqq
36
Figure 3 Marginal Productivity of Capital
Source Dornbusch and Fischer (1995) p 406
Even if good investment opportunities for poor people exist the question remains if it is
possible to distinguish between high and low risk borrowers The problem of adverse
selection is overcome in a cost effective way in many MFIs180 For the better off poor
for example institutions like BRI base their decision on whether or not to approve a
loan by assessing the repayment ability of potential borrowers from their current income
flows and not from the uncertain returns generated by the loan181 Additionally
collateral is used in some cases to attract low risk borrowers182 In contrast to
industrialized countries this is usually not done to cover the potential losses of the
lender but to punish the defaulter and therefore increase her willingness to repay183
Obviously this does not always work for the poorest since they often neither posses any
goods that could work as collateral nor do they have sufficient earnings prior to
obtaining a loan for starting an income generating activity Here the so called group-
lending model can help to identify creditworthy borrowers The most prominent
institution using this approach is the Grameen Bank which only provides credit to
180 See Farrington (2000) p 20181 See Robinson (2001) p 80 Robinson (2002) p 238182 See Bester (1985) p 850 et sqq183 See Schmidt and Tschach (2001) p 15 Robinson (2002) p 244
FIXED CAPITAL 0
MA
RG
INA
L P
RO
DU
CT
IVIT
Y
37
members of a group of five These groups are formed by their members without
interference of the Grameen Bank Although in this particular case no joint liability
exists for the members of the group nobody can receive a new loan if another member
of the group fails to repay on time184 Therefore the group formation work as a
screening process Since the borrowers do not want to risk their ability to obtain further
loans they carefully select with whom to form a group Usually the members know
each other for a long period of time and therefore they can make a meaningful judgment
of each othersrsquo ability to repay the loan Other MFIs even require the members of a
group to mutually guarantee each othersrsquo loans185 While this might further increase
borrowersrsquo efforts to search for trustworthy group members it might also keep potential
borrowers from applying for a loan since she does not want be held responsible for
defaulting members This mechanism enables MFIs to partly pass on the transaction
costs related to the selection of low risk borrowers to the borrowers themselves186
Many MFIs have also largely overcome the problem of moral hazard by creating
incentives to ensure a high repayment rate even among the poorest In some cases their
customers go hungry in order to pay back their loan even though no legal action would
be taken against them if they would refuse to do so187 One way to achieve this is to
build up peer pressure through the formation of groups as described above188 Another
and probably the most important is to limit access to future loans to those borrowers
who repay on time The demand for successive loans is extremely high In a 1996
survey 98 percent of BRI borrowers planed to apply for another loan189 and in 1993
less than 30 percent of Grameen Bank loans went to first time borrowers190 Especially
the poorest highly value the option to reborrow191 and many MFIs see this as their
primary incentive to ensure repayment192 According to Schmidt and Tschach ldquothe net
present value of future access to credit works out to be roughly half the value of the
economic advantage to be gained from the intended non-repaymentrdquo193 This can also
184 See Yunus (1998) p 135185 See Schmidt and Zeitinger (1997) p 6186 See Stiglitz (1990) p353187 Own observation at the Grameen Bank in Bangladesh (2003)188 See Hoff and Stiglitz (1990) p 249189 See Robinson (2002) p 251190 See Khandker Khalily and Khan (1995) p 93191 See Gibbons (2000) p 15 Hashemi and Schuler (1997) p 43192 See Gibbons and Meehan (1999) p 160193 See Schmidt and Tschach (2001) p 16
38
explain the occurrence of a drop in the repayment rate once a MFI is no longer seen as
viable and therefore is not expected to provide loans in the future194
With the help of the described mechanisms MFIs around the world are able to keep
repayment rates high A survey of 69 MFIs from 36 different countries each serving
more than 10000 clients in 2002 found the portfolio at risk (PAR)195 varied between
zero and 231 percent While the average was 36 percent the median was found to be
229 percent196 One of the MFIs included in this sample is BRIs whorsquos 12-month loss
ratio has never exceeded five percent since the start of its transformation in 1984 and
from 1997 to 1998 the ratio actually fell from 22 to 194 percent197 The latter deserves
special attention because the Asian financial crisis reached its peak at that time with
Indonesia being hardest hit as illustrated by a statement from The Economist in July
1998 Even with the fierce competition from its neighbors Indonesia would probably
walk away with the prize for Asias most desperate banking systemrdquo198
The findings that MFIs can adapt their services to low income people in order to ensure
a high repayment rate and that poor people do not lack profitable investment
opportunities are illustrated in figure 4 From this diagram it can be seen that under the
new assumptions the interest rate at which the bank maximizes its return differs for
large (I(l)) and small loans (I(s)) According to the assumption that micro-
entrepreneurs can realize a higher return on their investments the bank can charge them
a higher rate of interest without bearing an increased risk Nevertheless in this example
the bank would still serve the market for large loans first because of the higher
transaction costs for smaller loans
The view as described in figure 4 is shared among most traditional banks and investors
in industrialized as well as in developing countries In addition to neglecting the
possibility of generating profits by offering microcredit themselves199 they also hesitate
to lend to MFIs because they consider their business too risky
194 See Schreiner (1997) p 64195 ldquoPAR shows the real risk of the portfolio by comparing outstanding loan balances for loans with atleast one late payment to the outstanding loan portfoliordquo Gross and de Silva (2002) p 22196 Own calculations See Appendix 2197 See Seibel (2000) p 11198 The Economist (1998) pp 92 et sqq199 Busch and Kort (2004) p 8
39
Figure 4 The extended Model
Source Own diagram adapted from Stiglitz and Weiss (1981) p 394 Tschach (2000)
p 17
This attitude can be observed by comparing the ratio of equity to liabilities which is
considerably higher for MFIs than for conventional banks200 When it comes to MFI
start-ups and those MFIs serving the low end market in remote areas even experienced
microfinance practitioners are skeptical if interest rates that fully recover all costs can
be charged201
Theoretically there are two ways to adjust this model to arrive at a conclusion which is
more favorable with regard to the profitability of microcredit One is to cut the
transaction costs and therefore reduce the downward shift of the R(I)small curve the
other is to allow the bank to further raise the interest rate without experiencing a
decrease in its return This means to increase I(s) and the respective rate of return
While in 2000 Tschach stated that transaction costs vary between 10 and 20 percent for
loans provided through the group lending model and between 15 and 30 percent for
200 See MicroRate and IADB (2003) p 30201 See Volkery (2004) p 33 Gibbons (2000) p 15 Gibbons and Meehan (2002) p 29 Goodwin-Groen (1999) p 8
INTEREST RATE I(l)
SmallLoans
LargeLoans
Transaction costs
I(s)
R(i)large
R(i)small
EX
PE
CT
ED
RE
TU
RN
TO
TH
E B
AN
K
40
individual loans202 it was recommended in 1999 that MFIs should target a range
between 15 and 25 percent203 Some best practices on the other hand have already
achieved single digit numbers Currently BDB might be the most efficient MFI in the
world with transaction costs at just 47 percent in 2001204 Even though the low costs of
BDB have to be acknowledged its achievement has to be put in perspective As stated
above with an average loan balance of more than $5000 it does not serve the low end
market In addition it works in an environment with a high population density which
means that it can reach a relatively large group of borrowers per branch This is a
comparative advantage many Asian MFIs enjoy as can be illustrated by comparing
Bangladesh and Bolivia Both countries are at the forefront of the development of
microfinance in their respective continent but while in Bangladesh more than 1000
people are living per square kilometer the average for Bolivia is only eight205
Therefore it is consistent that the most efficient MFI in Latin America Fondo
Financiero Privado para el Fomento a Iniciativas Economicas has transaction costs of
114 percent206 With an average loan size greater than the annual GDP per Capita this
institution also does not serve the low end market207
Despite the impressive efficiency gains in the described examples most MFIs are far
from achieving these numbers and many are unlikely to reach them due to the
environment within which they work A survey of 67 MFIs from 31 countries found the
average transactions costs in 2002 to be 279 percent with a median of 206 percent208
However even if these institutions were to increase their efficiency to best practice
standards their transaction costs would still be significantly higher than those of
traditional banks providing much larger loans For these banks the respective costs vary
in a range between 05 and 3 percent209 According to this argument charging interest
rates considerably higher than conventional banks is the only way for MFIs to generate
higher returns and hence successfully compete for capital
202 See Tschach (2000) pp 100 et sqq203 See Gibbons and Meehan (1999) p 149204 See M-Cril (2001b) p 4205 See CIA (2004)206 See MicroRate (2004)207 In this paper the term ldquolow endrdquo refers to the definition of the MBB (2003) p 54 Loans worth less than 20 percent of the respective countryrsquos GDP per capita are described that way 208 Own calculations See Appendix 3209 See M-Cril (2004a) p 16
41
6 Interest Rates
61 Setting the right Interest Rate
Before addressing the questions to what extend MFIs can raise their interest rates
without putting the repayment rate or the social benefits of their customers at risk a
basic model will be presented This model will illustrate how a MFI should set their
rates in order to not only cover their costs but also to generate an appropriate profit to
finance further growth and attract additional capital
In 2002 CGAP revised its 1996 paper ldquoMicrocredit Interest Ratesrdquo210 which outlines
the standard method of setting sustainable interest rates for commercially oriented
MFIs According to this model the annual effective interest rate (I) should be calculated
as shown below
(1) I = LL
IIKCFLLTA
minusminus+++
1
With each variable being a decimal fraction of the average outstanding loan portfolio
whereby TA stands for the transaction costs as described above LL represents the
annual loan loss and II stands for investment income eg on liquid assets The cost of
funds (CF) consist of the interest and administrative costs needed to obtain deposits and
commercial loans as well as of the imputed costs on equity due to inflation K stands for
the capitalization rate which represents the net real profit Keeping this rate high is
important to finance the future growth of the loan portfolio This can be either done
through investors attracted by high profitability or through borrowing For the latter an
increase in equity is inevitable since it is required as a safety cushion by lenders
Since this model ignores the timing of cash flows and does not take taxes into account
it has to be regarded as fairly imprecise and hence should not be used for business
planning Nevertheless it can be used for an approximation of the interest rate that a
MFI would need to charge to provide its services as planned In the following I will
210 See Rosenberg (2002) pp 1 et sqq
42
apply this model on a fictitious MFI working in a rural area of Latin America with low
end customers In this setting it seems realistic to estimate transaction costs of 35
percent and loan loss rate of two percent211 If funds were borrowed at commercial
terms their costs can be assumed to equal at least 15 percent of the average outstanding
loan portfolio212 Estimating the capitalization rate is more challenging First the
targeted portfolio growth rate is set at 75 percent This is slightly below the 751 percent
average annual portfolio growth between 2000 and 2002 found by a survey of 25
different MFIs based in Central and South America213 If the extend to which the MFI
can leverage stays constant the loan portfolios growth would be limited by the growth
rate of the equity To express the capital needed for this growth as a share of the loan
portfolio it is necessary to estimate the ratio between the equity and the outstanding
loan amount According to the survey mentioned above the loan portfolios of the 25
Latin American MFIs equal on average 215 times their equity214 With this number the
capital needed to increase the equity by 75 percent would corresponds to approximately
35 percent of outstanding loan amount (075215) Finally the investment income has to
be estimated Since liquid assets that are available short term do not generate high
returns say five percent it does not seem advisable for the MFI to hold more than a
quarter of its loan portfolio in this form Hence the profit generated in this way would
equal 125 percent of the outstanding loan amount Using these numbers the equation to
calculate the annual effective interest rate reads as follows
(2) I = LL
IIKCFLLTA
minusminus+++
1 =
0201
01250350150020350
minusminus+++
= 0875
As a result the MFI would need to charge an annual effective interest rate of
approximately 875 percent on its loans in order to sustainable provide its services and
finance its growth without depending on donor money This rate might decrease once
the MFI matures the growth slows down and cheaper funds become available but it
will stay significantly higher than any rate charged by conventional banks
211 MicroRate and IADB (2004) pp 6 and 16212 See MicroRate and IADB (2004) p 616 and 28213 Own calculation See Appendix 4214 Own calculations See Appendix 5
43
62 Can Micro-Entrepreneurs bear these Rates
Although most MFIs charge rates significantly below 875 percent many critics have
strenuously argued against any rates exceeding those of traditional banks Rosanna
Barbero of Oxfam labeled an interest rate of 52 percent charged by a Cambodian MFI
ldquoludicrous evil and disgusting and stated that ldquo[n]o business in the world can make a
profit at these interest ratesldquo215 The former finance minister of Bangladesh Shah Kibria
even categorized the 20 percent effective rate charged by the Grameen Bank as to
high216 Many practitioners therefore believe in a strong negative correlation between
the interest rate and the demand for loans217 Others have argued more generally that
concentrating on profitability and therefore charging high interest rates diverts MFIs
from serving the poorest218
These views are still shared among many MFI managers donor agencies and especially
investors and politicians While the former are unwilling to charge interest rates for
funds they received ldquocheaplyrdquo (through grants or subsidized loans) and are worried
about undermining their social goals by charging higher rates of interest219 the latter are
reluctant to invest for reasons stated above or impose interest caps to catch the attention
of the public by pretending to protect the poor from usury rates220
In chapter 53 it has been described that micro-entrepreneurs due to their smaller
capital endowment have even better investment opportunities than big business The
extend to which this is true has not yet been answered An indication is the high
repayment rate observed within MFIs around the globe If their customers capital yield
did not exceed the charged interest rate how would they be able to repay According to
Gibbons and Meehan customers of MFIs can generally generate returns of more than
100 percent on their invested capital221 and ldquo[r]esearch in India Kenya and the
Philippines found that the average annual return on investments in microenterprises
215 See Kate and Roeun (2004)216 See Hodson (2001) min 1100217 See Morduch (1999a) p 1594218 See Prisma (2002) p 1219 See Schreiner (1997) p 60 Khandker (1998) p 106 220 See Gross and de Silva (2002) p 32 Jansson and Wenner (1997) p 36 et sqq Campion (2002) p 59221 See Gibbons and Meehan (1999) p 131
44
ranged from 117 to 847 percentrdquo222 Schmidt and Tschach found the marginal
productivity of capital to be as high as 1000 percent for the smallest loans provided by
the Bolivian MFI Caja Los Andes223 These findings are confirmed by the observation
of Rosenberg who found while working as a microfinance consultant for ten years he
never heard of a single MFI having problems to attract clients because interest rates
were too high224
To get a better understanding of the investment opportunities of low income people in
developing countries a typical example on how MFI clients invest their loans is as
follows
Zobair is working as a rickshaw puller in Bangladesh Like most of his colleagues he
does not own the rickshaw he is riding Therefore he has to pay a daily rent of about
$030 to the owner Since his average income of approximately $15 per day is hardly
enough to feed his family he is not able to save the $100 necessary to buy a rickshaw
on his own 225 If he could do so through obtaining a loan his income would increase by
$030 every day because he would not have to pay the rent for the rickshaw anymore
Assuming an average of six working days per week 226 and a life span of the rickshaw
of 5 years his internal rate of return would equal 15324 percent annually227
Consequently any interest rate charged by a MFI would be advantageous to him as long
as it would not exceed 15324 percent228
63 Should the Interest Rate be subsidized anyway
Despite the fact that numerous micro-entrepreneurs are able to generate tremendous
returns on their investment obviously not all are able to use capital in such a productive
way and therefore can not afford microcredit at commercial rates In order to reach
these people as well many MFIs continue to use donor money in order to keep their
interest rates low But even if the problems related to subsidized credit as described in
222 See Helms and Reille (2004) p 3223 See Schmidt and Tschach (2001) p 6224 See Rosenberg (2002) p 10225 This examples draws on observations made by the author in Dhaka (Bangladesh) during 2003226 Obviously extended holidays are not a viable option in this surrounding 227 Own calculation See Appendix 6228 This result is only valid if the loan is repaid in daily instalments For a weekly repayment schedule the interest rate charged by the MFI must not exceed 15119 percent in order to still be beneficial for Zobair
45
chapter 23 do not arise it might still not be the most effective tool to help poor people
as will be illustrated in the following example
A MFI faces two groups of potential clients one with businesses able to generate a
return of 125 percent on borrowed capital and another with a possible returns of 50
percent Assuming budget costs according to equation (2) the institution needs to
charge an interest rate of 875 percent and therefore only serves the former group
Supposed each group consists of 50 members demanding $100 loans the net gains to
society (NGS) could be calculated as follows
(3) NGS = 50 times ($125 ndash $875) = $1875
These gains would be due to the investments of the more profitable group which were
made possible through the loans provided by the MFI The less profitable group would
not borrow since their expected returns are not sufficient to pay for the interest If the
interest rate would be lowered to 30 percent both groups would be able to generate net
gains and therefore borrow from the MFI In order to provide loans at this rate the
institution would need to raise additional capital from non commercial sources The
NGS would be calculated as follows
(4) NGS = 50 times ($125 - $30) + 50 times ($50 - $30) + 100 times ($30 - $875) = 0
While the first terms represent the net gains to the respective groups the last describes
the costs incurred in providing the loans At a rate of 30 percent each loan would need
to be subsidized with $575 Hence the NGS actually fall after the introduction of the
subsidized loan This is due to the fact that the less profitable group is encouraged to
invest in relatively unproductive businesses In addition future growth of the MFI could
be jeopardized due to scarce donor money which is needed to finance the interest rate
subsidy Therefore it seems more advisable to continue to charge a rate of 875 percent
and spend the money used for subsidization on other programs such as health care or
education229
229 In Appendix 7 it will be shown that this result generally holds
46
7 Empirical verification
71 Setting up a Sample
To see if the findings of the previous chapters hold the effects which interest rates
charged by MFIs have on their performance will be analyzed in the following Up to
now such a study does not exist mainly because of a lack of adequate data Most MFIs
do not provide accurate information about the annual effective interest rate they charge
and therefore make an evaluation difficult
In 2002 Rosenberg distinguished eight different categories on how microcredit interest
rates are quoted230 These categories differ in several ways On the contrary to
traditional banks for example it is common for MFIs to state interest rates calculated on
a ldquoflatrdquo balance rather than on a declining one This means that the total loan amount is
used to determine the interest rate ignoring installments paid by the borrowers normally
on a weekly or monthly basis In addition many MFIs charge a certain upfront fee prior
to the loan disbursement require compulsory savings at a lower rate or state their
interest rate for semi annual terms only On the one hand this is done to provide
numbers that are more meaningful to MFI customers who often lack the necessary math
skills to deal with compound interest on the other hand it is done to circumvent interest
rate ceilings imposed by the government231 Another problem is that most MFIs offer
different loan products without itemizing their respective shares to their total loan
portfolio As a result it is not possible to calculate a weighted average even if the rate
stated by the respective MFI could be transformed into an effective interest rate
Usually the portfolio yield is used as a proxy in order to make statements about the
interest rate charged by a certain MFI232 It is generally ldquocalculated by dividing total
cash financial revenue (all income generated by the loan portfolio but not accrued
interest) by the period average gross portfoliordquo233 The advantage of this method is that
even the hidden costs are considered Nevertheless it also has a severe shortcoming by
not taking late or defaulted payments into account Therefore the portfolio yield does
230 See Rosenberg (2002) p 5231 MicroRate (2002) p 8232 See MicroRate (nd)233 MicroRate and IADB (2003) p 39
47
not allow to draw conclusions regarding the correlation between the interest rate
charged by a MFI and its PAR
72 Examining the Sample
Through the appearance of rating agencies specialized in the microfinance sector more
adequate information has become available in recent years While MicroRate only
publishes the portfolio yield of rated MFIs M-Cril Microfinanza Microserve and
Planet Rating actually provide information about the annual effective interest rate for at
least some of the MFIs they analyze Although it is labelled differently from all of the
four institutions234 the term describes what is ldquothe highest income or yield that an
organisation can earn from its portfolio based on the terms of its loansrdquo235
Currently236 reports of 39 different MFIs from 20 countries providing accurate
information about the effective annual interest rate are available to the public This
sample should be used to verify the findings of the previous chapters237 Since a
comparison is made between the performances of MFIs based in different countries and
the ratings have been carried out in different years several adjustments are necessary
First the inflation of the respective country and the respective year(s)238 has to be taken
into account in order to only compare the real rates239 In addition the average
outstanding loan amount per borrower is divided by the respective countryrsquos GDP per
capita Since it can be assumed that ldquoonly the poorer households will be willing to take
the smallest loansrdquo240 this number can be used as a proxy for the poverty level
Although the sample size is far to small to represent the microfinance sector as a whole
and the results are statistically not significant the findings can still be used to underline
the theoretical conclusions drawn in the previous chapters In figure 5 the connection
234 M-Cril uses the name ldquoannual percentage raterdquo See eg M-Cril (2004a) p 25 Microfinanza uses the name ldquoexpected portfolio yieldrdquo See eg Microfinanza (2002c) p 25 Planet Rating uses the name ldquoannual effective interest raterdquo See eg Planet Rating (2004d) p 1 Microserve uses the name ldquotheoretical yieldrdquo See Microserve (2003) p 62235 See M-Cril (2004a) p 25236 As of September 28th 2004237 See Appendix 8 For exchange rates see FXTOP (2004)238 Where necessary a weighted average of the annual inflation rate was used See Appendix 9239 This is done through the following formula ir = (I ndash F) (1 + F100) While ir represents the real annual effective interest rate F represents the inflation rate 240 Morduch (1998) p 1572
48
between the average loan size and the transaction costs as a share of the average loan
portfolio is illustrated
Figure 5 Loan Size vs Interest Rate241
Source Own diagram
000
1000
2000
3000
4000
5000
6000
7000
8000
9000
10000
0 100 200 300 400 500 600
Loan Size
Inte
res
t R
ate
It can be seen that the interest rate is negative correlated to the loans size This can be
explained by the relative higher transaction cost for smaller loans as described in
chapter 52 In order to cover their costs MFIs serving the low end market need to
charge higher rates to their customers than those organizations serving the better off
poor Obviously there are several assumptions to this general finding Especially
striking are the two MFIs with an average loan size of approximately five times their
countries GDP per capita which still high interest rates This occurrence can be
explained by taking a closer look to the respective organizations One was established
less than two years prior to its rating and therefore still bears a lot of start up costs242
241 The equation for the regression line reads as follows Y = -00219X + 365 The correlation coefficient is 014242 See Microfinanza (2002b) p 1
49
the other managed to stay profitable while it almost quadrupled its loan portfolio in the
last two years243
Figure 6 Interest Rate vs PAR244
Source Own diagram
0
5
10
15
20
25
30
35
0 20 40 60 80 100 120
Interest Rate
PA
R
In Figure 6 the crucial correlation between the interest rates charged by a MFIs and its
PAR245 is examined According to the given sample the view of traditional banks and
investors that a higher interest rate leads to a higher default rate does not hold
Obviously one has to avoid to draw the opposite conclusion namely that a high interest
rates decreases the PAR The connection illustrated in figure 6 has to be interpreted as
follows Since high interest rates are related to small loans the low PAR for MFIs
charging high interest rates can actually be explained by the tremendous profitability of
small size investments Despite the high rates their customers are even more likely to
repay
243 See Planet Rating (2003b)244 The equation for the regression line reads as follows Y = -00768X + 68433 The correlation coefficient is 0235245 M-Cril only publishes the PAR for overdues greater than 60 days Therefore these ratios are used as a proxy for the industry standard of 30 days for some Asian MFIs
50
Finally it has to be examined if charging high interest rates actually enables MFI to
generate higher returns Although it can be expected that the combination of a low PAR
and a high interest rate leads to a high profitability it still has to be checked if this is not
outdone by soaring transaction costs Figure 7 illustrates the correlation between the
interest rate charged by a MFI and its financial self-sufficiency (FSS) The latter is the
ldquo[r]atio of total income to total adjusted expenses for the year Adjustments are made
for subsidised cost of funds (relative to market interest rate) equity (with respect to
inflation) and in-kind donationsrdquo246 It can be seen that the regression line actually does
indicate a positive correlation between the interest rate and the profitability of a MFI
Figure 7 Interest Rate vs FSS247
Source Own diagram248
0
20
40
60
80
100
120
140
160
180
0 20 40 60 80 100
Interest Rate
FS
S
246 M-Cril (2004a) p 53247 The equation for the regression line reads as follows Y = 02839X + 8901 The correlation coefficient is 0174248 Since the interest rate the customers of the MFI Foccas have to pay includes fees which are not passed on to the institution its interest rate in this diagram is set at 723 percent instead of the 10715 percent used for figure 6 See Planet Rating (2003b) p 1
51
This result does not necessarily disprove the findings of Stiglitz and Weiss since it can
be argued that MFIs simply do no increase their interest rates to the point where they
would maximize their expected returns But if this would be true why do MFIs not
charge higher rates of interest given the demand described in chapter 41 and 43 In
mature markets competition normally ensures prices not to exceed a certain level but
since many MFIs still operate in a ldquosellerrsquos marketrdquo249 this can not explain the findings
as described in figure 7 Therefore it has to be assumed that a combination of the
unwillingness of many microfinance practitioners to burden their customers with high
interest rates and the plain disbelief of traditional investors that micro-entrepreneurs can
bear those rates is responsible for this occurrence
249 See MicroRate and IADB (2003) p 9
52
8 Conclusions
It has been shown that MFIs are not only contributing significantly to the development
of the financial sector in their respective countries but also that they play an important
role to eradicate poverty by providing much needed capital to low income people which
are able to generate tremendous returns on their investments
The fact that the demand for microcredit is not met is mainly due to the view of most
for profit investors and traditional banks that offering financial services to poor people
can not be done profitable Because of this conviction they hardly invest in the
microfinance sector This does not have to be the case according to the findings of this
paper Although faced with relatively high transaction costs MFIs are able to charge
interest rates at levels that fully recover their costs Elizabeth Rhynersquos claim ldquothat the
most financially viable programs differed from their less viable peers in their
willingness to set interest rates at levels that would fully recover costsrdquo250 is backed by
the findings of this paper that high profitability is correlated to high interest rates
Theoretical models based on the findings of Stiglitz and Weiss can not be used as a
justification to ration credit for the microfinance sector since the interest rate that
maximizes profits to the lender can be assumed to exceed 100 percent for many MFIs
Nevertheless this rate is hardly charged although it has been shown that it can be done
The Mexican MFI Compartamos for example manages to keep its PAR as low as one
percent while charging an effective interest rate of more than 100 percent to
approximately 160000 clients251 In combination with this case the conclusions drawn
from examining the sample of MFIs in chapter 7 the claim of Hulme and Mosley as
stated in the introduction can be considered as wrong MFIs are in fact able to finance
rapid growth stay profitable by charging corresponding interest rates and still have a
significantly positive impact on the poverty level of their clients In the long run gains
in efficiency economies of scale a slowdown in growth and competition will ensure
interest rates drop as it has already been the case in countries like Bangladesh and parts
of Bolivia252
250 See Rhyne (1998) p 7251 See MicroRate (2004)252 See Microrate and IADB (2003) p 9
53
According to a MicroRate survey many MFIs are more profitable than Citibank and also
generate a higher return on investment than commercial banks in their respective
countries253 Investments companies like IMI or Blue Orchard will soon be able to
present a meaningful track record of their microfinance investments to potential
investors Ultimately the capital markets can not ignore the facts proving that it actually
can be profitable to invest in the microfinance sector but in order to raise money
quickly microfinance practitioners will have to continue to intensively promote their
cause not only to for profit investors but also to donors and multilateral agencies like
the World Bank
253 See MicroRate (2002) p 10
54
Appendix
Appendix 1 Average loan balance
Source Data is available through the Mix Market (2004)
Organization
Loan Portfolio 2002 (US$)
Loan Portfolio 2003 (US$)
Number of borrowers 2002
Number of Borrowers 2003
2CM 1263602 1400438 3622 3708ACF 955503 1611401 285 370ACLEDA 26846703 39391301 82598 98905ACME 1460881 1714844 4283 4600ADIM 369065 407798 1122 1395AFK 933306 1706577 250 467AgroInvest 4684249 9697411 5208 9629Al Amana 15593277 28677666 78114 101610AMSSFMC 612167 1040756 6183 6886AREGAK 3285273 3987011 11841 14377AVFS 214331 269819 1883 2866BancoSol 83629049 91175000 42290 56707BESA 10563980 15114430 4488 5061BPR AK 613362 876130 1730 3879BPR BMMS 133949 237946 1755 1779BRI 1344006170 1720072773 3056103 3100358BZMF 1592508 1922097 1250 1331CBDIBA 216587 242465 5764 2877CCA 2146235 4582302 4070 6585CCCP 447534 851678 6265 9450CEP 3795400 5261957 32291 42132CERUDEB 25093643 34873228 34490 44796CMEDFI 227674 250244 3467 3781CMM - Bogota 4836000 8135968 15635 22038CMMB 34880 56964 42 190COAC Maquita Cushunchic
870084 1855718 6603 7732
CODES 280843 263091 60 60CODESARROLLO 6714007 12935951 4391 6896Constanta 2943822 3536047 16134 18588COOPEC CAMEC MN
7152 29821 92 77
Crear - Tacna 3891116 4636094 3671 4948CREDIT 642094 81838 7532 8097CRYSTAL FUND 366456 421403 1379 1061DBACD 3473701 3876526 12812 19606ECLOF - ECU 1154292 728312 860 416ECLOF - MAL 441734 407227 1118 1500EKI 11833244 19245751 8999 13323EMT 4481589 5765281 84781 92173ESED 8579460 6834742 22790 20035
55
Eshet 185741 462569 3308 6540Faulu - KEN 9027332 7206344 17463 15000FDL 12503027 16545332 21306 25106FIE 35818903 41597315 26468 33100FINADEV 5512586 9770323 12775 14709Finance Salone 211312 434298 2225 7159Finca - TAN 1293430 1854834 20648 27499Finca - UGA 2451703 2798869 35610 36912FINCORP 4761288 10236896 941 858FJN 5473563 8037662 8107 11133FMFB 308158 1188896 713 3558FMM -Bucaramanga
6355518 10227000 25814 42464
FODEM 739181 939824 1909 2501FundaciESPOIR
898561 1883446 5911 9464
FUNDESER 798907 1373113 4072 5065Gasha 323748 413742 5504 6423GGLS Save the Children
64235 137957 1291 2362
GK 56986 166971 951 2718HKL 1363365 1420357 6648 5372HOPE 402799 603488 1098 1562IAMD 42132 56550 2780 2772IDECE 21312 39453 150 232IDF 2031944 2626382 31003 36580IMCEC - Dakar 254759 688449 1018 2983IMCEC - Thies 199799 571122 1164 1261
ISSIA 221615 246792 1409 1698JMCC 1962355 2609723 1471 2333KAFC 21710638 29241051 24850 32097KAMURJ 1003935 1411258 5559 5691Kashf 2355965 6271498 29655 59389KMBI 721409 1626666 11973 27266KPSCA 109299 128063 362 794K-Rep 14490447 20699963 38739 45379KSCS 18978 43740 140 297KVT 44075 70621 241 373LAPO 922478 1194633 18740 19139MEC ADEFAP 27788 69248 198 202MEC Bosangani 14357 31086 364 540MEDF 104113 136257 1278 1184Meklit 233170 252232 2084 3577Metemamen 22123 57778 943 1501MFSC 109261 171090 511 687MIKRA 2951028 5008784 4145 6095MIKROFIN 9560502 18380263 5633 7426Miselini 737387 1026639 10182 11431MRFC 11475440 9133130 163000 180000Mushuc Runa 2089076 5418325 3139 6232Nirdhan 2886777 3016171 29589 27457OCSSC 5245186 7658413 42157 6215o
56
Otiv Diana 95992 638422 229 1073Otiv Sambava 188094 437974 2002 1442Otiv Tana 66465 673175 337 1269Partner 9976448 15321304 7139 11935PCA 6878257 6885926 63113 58147PEACE 420746 627295 4192 5428PEDF 164399 254233 2357 3340Piyeli 809447 1206656 8674 4745PRESTANIC 2827502 3540367 1477 2605PRIDE - MAL 991888 854631 5376 5601PRIZMA 3881581 6838978 8112 10968ProMujer -Nicaragua
1006871 1424437 10436 13047
PTF 891566 1068881 8500 9070RBST 818594 1058115 619 723REMECU 1381705 1483471 10330 13996
RUSCA 60887 100820 454 994
SCSCS 89423 157472 873 1007SFPI 709497 903556 7728 9552Sidama 934260 1011798 10267 11346SPBD 117807 186029 647 1740Sunlink 819138 1056823 3401 3833Sunrise 5412366 8782868 4560 7256TEBA 108032426 176300111 163021 157776TIAVO 281978 838905 2049 459TPC 1140429 2267148 22869 31668TSPI 4650989 5383755 49649 75617UNICECAM 3442843 5943804 16039 19031Wasasa 230657 274908 2850 3728Wisdom 1306066 1404463 10524 12054XacBank 4910098 9829503 11063 18610Zakoura 15907288 12444768 103720 118980
Appendix 2 Portfolio at Risk
Source Data is available through the Mix Market (2004)
Organization PAR 2002ABA 202ACEP 464ACLEDA 175ACODEP 452ACSI 209Al Amana 010Apoyo Integral
483
AREGAK 692Banco Solidario
500
BancoSol 660BASIX 1296
57
BRI 437BURO Tangail
350
CEP 200CERUDEB 103CMAC -Sullana
567
CMM -Bogota
176
Compartamos 111Constanta 304Credi Fe 212CREDIAMIGO 409DBACD 010EBS 847EMT 010ESED 1311FADES 2311Faulu - KEN 246Faulu - UGA 096FDL 212FECECAM 428FED 436FIE 598FINADEV 021Finamerica 1133Finca - TAN 000Finca - UGA 297FMM -Bucaramanga
094
FMM -Popayan
088
FONDEP 013FORA 064Genesis Empresarial
1197
IDF 017KAFC 106Kashf 000KMBI 128K-Rep 229MiBanco 309MRFC 1742Nirdhan 373
PADME 079PAMECAS 284PCA 379PRIDE - TAN 018ProMujer -Nicaragua
073
RCPB 600REMECU 157SHARE 000
58
Soluci 182Spandana 014TEBA 106TSPI 355UMU 125UNICECAM 405Urwego 290UWFT 363WAGES 736WWB -Medellin
235
XacBank 061Zakoura 095
Appendix 3 Transaction Costs
Source Data is available through the Mix Market (2004)
OrganizationTransaction Costs
Acci Rural 1154ACEP 858ACLEDA 2430ACODEP 2920ACSI 924Al Amana 2576AREGAK 2856AssEF 1919Banco Solidario
1826
BancoSol 1210BASIX 1317BRI 1353BURO Tangail
2053
CEP 1759CERUDEB 5109CMAC -Sullana
1784
CMM -Bogota
2089
Compartamos 3341Constanta 4597Credi Fe 1978CREDIAMIGO 2525DBACD 1742EBS 2377EMT 3220ESED 1343FADES 1673FAMA 2436
59
Faulu - KEN 2253Faulu - UGA 4962FDL 1726FECECAM 2587FED 4083FIE 1125Finamerica 1563Finca - TAN 10753Finca - UGA 9096FMM -Bucaramanga
1925
FMM -Popayan
1112
FONDEP 5477FORA 3481Genesis Empresarial
1626
IDF 1695
K-Rep 1909LAPO 3511MiBanco 2456Nirdhan 1325NWTF 3109OCSSC 1155PADME 1131PAMECAS 1705PCA 1670PRIDE - TAN 4273ProMujer -Nicaragua
5078
RCPB 2059SHARE 2308Sidama 2662Soluci 2906Spandana 641TEBA 1213TSPI 3898UMU 4023UNICECAM 10120Urwego 7437Wisdom 1906WWB -Medellin
1703
XacBank 4144Zakoura 1881
60
Appendix 4 Portfolio Growth
Source Data is available through the Mix Market (2004)
Organization
Total Loan Portfolio in 2000
Total Loan Portfolio in 2002
ACODEP 5889394 7258487Adelante 4327 88594ADRI 1514681 2591240AgroCapital 11100088 12018280Banco Solidario 39632165 103420000
BancoSol 78031172 83629049CMAC - Sullana 14596365 28055720
COAC Maquita Cushunchic
348443 870084
CODESARROLLO 1374801 6714007Compartamos 10804279 41825248Crear - Tacna 3778816 3891116
Credi Fe 781616 9393936ECLOF - ECU 179247 1154292
FADES 11948814 15501578FAMA 6201411 8835134FIE 22524645 35818903Finamerica 16575104 16097113FINCOMUN 3278938 5696556FMM - Popayan 6241821 12212867
FONDECO 3456625 5101801Genesis Empresarial
11154234 17746288
MiBanco 36964072 95873333Mushuc Runa 90737 2089076ProMujer -Nicaragua
426541 1006871
WWB - Medellin 2891207 4580998
Appendix 5 Portfolio vs Equity
Source Data is available through the Mix Market (2004)
OrganizationLoan Portfolio Equity
ACODEP 7258487 1921447Adelante 88594 72973
ADRI 2591240 781477AgroCapital 12018280 10766101Banco Solidario 103420000 12961000BancoSol 83629049 15299415CMAC - Sullana 28055720 6210291
61
COAC Maquita Cushunchic
870084 260331
CODESARROLLO 6714007 1285103
Compartamos 41825248 18350446
Crear - Tacna 3891116 1016912Credi Fe 9393936 863848ECLOF - ECU 1154292 459226FADES 15501578 4138972FAMA 8835134 6377663FIE 35818903 5360484Finamerica 16097113 3817960FINCOMUN 5696556 1042241FMM - Popayan 12212867 8510494FONDECO 5101801 1658075Genesis Empresarial
17746288 4765816
MiBanco 95873333 24261889Mushuc Runa 2089076 434311ProMujer -Nicaragua
1006871 1196015
WWB - Medellin 4580998 2213249
Appendix 6 Internal Rate of Return
Source Excel (German Version) calculation based on own data
A B C D E F
1 Date Cash Flow
Interest Rate Internal Rate of Return Balance Interest Principal
23 01012004 -100 15324 100 025489547 0045104534 02012004 03 999548955 025489547 0045104535 03012004 03 99909676 02547805 004521956 04012004 03 998643412 025466524 0045334767 05012004 03 998188909 025454968 0045450328 06012004 03 997733247 025443383 0045566179 08012004 03 999826083 050928361 -0209283610 09012004 03 999374595 025485114 004514886
hellip hellip hellip hellip hellip helliphellip hellip hellip hellip hellip hellip helliphellip hellip hellip hellip hellip hellip hellip1562 23122008 03 177951388 000528711 0294712891563 25122008 03 148859724 000908336 0290916641564 26122008 03 119239161 000379437 0296205631565 27122008 03 089543096 000303935 0296960651566 28122008 03 059771337 000228241 0297717591567 29122008 03 029923692 000152354 0298476461568 30122008 03 -3434E-07 000076274 029923726
62
The formula in the square C3 reads as follows
ldquoXINTZINSFUSS(B3B1568A3A156815)rdquo
Appendix 7 Subsidized Interest Rates and the Net Gains to Society
SourceOwn calculations
For simplicity only two groups of potential clients are distinguished This is possible
since using a continuum of potential clients would lead to the same results In addition it
is assumed that the amount of every loan (L) is equal and that all clients invest the
whole loan amount Group H consist of NH potential clients with a rate of return (rH) on
their invested capital higher than the cost recovering interest rate charged by the MFI
(iC) Group L consists of NL potential clients with a rate of return (rL) on their invested
capital lower than iC If the MFI charges iC the NGS can be calculated as follows
NGSC = NH times (rH - iC) times L
Since rH is bigger than iH (rH gt iC) according to the definition presented above the term
NGSH must be positive as long as NH does not equal zero If the MFI introduces a
subsidised interest rate (iS) lower than rL the NGS can be calculated as follows
(1) NGSS = NH times (rH - iS) times L + NLtimes (rL - iS) times L + (NH + NL) times (iS - iC) times L
(2) NGSS = NH times (rH- iC) times L + NLtimes (rL - iC) times L
The term (NH + NL) times (iS - iC) times L describes the amount of money that is needed in order
to subsidize the interest rate to the level iS By setting up an inequation it can be
examined under which conditions the NGSS are bigger than the NGSC
(3) NGSS gt NGSC
(4) NH times (rH- iC) times L + NLtimes (rL - iC) times L gt NH times (rH - iC) times L
(5) NLtimes (rL - iC) times L gt 0
(6) rL gt iC
63
So the NGSS could only be bigger than the NGSC if equation 6 holds This is
impossible since it violated the definitions presented above Therefore the introduction
of subsidized interest rates is always accompanied with a drop in the NGS
Appendix 8 Interest Rate vs Loan Size vs FSS vs PAR
Source Data is available through the Mix Market (2004)
Organization Country
Real Interest Rate
Loan Size (divided by the GDP per Capita) FSS PAR
BTFFKyrgyz Republic 3803 48260 1487 698
BesaFoundation Albania 2184 16076 684 260RFF Albania 1198 5783 4764 277PSHM Albania 2194 000 5758 198Mi-Bospo Bosnia 2974 5499 1261 020Prizma Bosnia 3474 3569 103 064Agroinvest Serbia 2201 4401 875 020KCLF Kazakhstan 5713 1713 865 090
Foccas Uganda10716 (723) 1550 584 29
ACEP Senegal 3280 20941 1643 1Padme Benin 2715 13575 1667 08Papme Benin 3086 53659 1405 24Vital Finance Benin 2676 9394 1015 17Finadev Benin 1738 14850 1024 21ABA Egypt 2579 1613 1168 88ASBA Egypt 2597 1702 1252 68DBACD Egypt 2490 1643 1073 0SBACD Egypt 2500 1734 982 67AMSSF Morocco 6926 787 1306 04Fondep Morocco 5199 650 889 071Zakoura Morocco 4414 900 98 006ENDA Tunisia 4008 1351 110 102BSFL India 1954 3269 856 99Share India 3426 1440 951 0Spandana India 2942 1618 1367 026SWC India 1864 2626 42 3036SKS India 2248 1912 578 0Grama Vidiya India 3176 1221 76 18Sneha India 3451 1433 933 0Buro Bangladesh 3206 1882 1093 17Upap Pakistan 2073 8183 757 03Seeds Sri Lanka 1004 1088 605 287EMT Cambodia 4324 1676 1016 01TPC Cambodia 4470 2035 832 27
64
WTF Phillippines 5816 1095 941 74TSKI Phillippines 5794 777 96 79Cacja Ecuador 862 6189 9460 897ACME Haiti 6043 6934 11685 450Grupo Cama Mexico 8961 267 10717 288
65
Appendix 9 Inflation vs GDP per Capita
Source IMF (2004)
Country Subject Description Units Scale 2000 2001 2002 2003 2004
Albania Gross domestic product per capita current prices US dollars Units 1083988 1238206 1396172 1757778 2229712
Albania Inflation annual percent change Percent 00 31 52 24 34
Bangladesh Gross domestic product per capita current prices US dollars Units 329310 327980 344494 369495 393717
Bangladesh Inflation annual percent change Percent 22 15 38 54 64
Benin Gross domestic product per capita current prices US dollars Units 361340 368213 405951 494725 560129
Benin Inflation annual percent change Percent 42 40 24 15 26
Bosnia and Herzegovina Gross domestic product per capita current prices US dollars Units 1255837 1321429 1466090 1807392 2070508
Bosnia and Herzegovina Inflation annual percent change Percent 50 32 03 02 09
Cambodia Gross domestic product per capita current prices US dollars Units 276413 280352 296577 305940 321247
Cambodia Inflation annual percent change Percent -08 02 33 12 20
Ecuador Gross domestic product per capita current prices US dollars Units 1227711 1590267 1804362 1957183 2082156
Ecuador Inflation annual percent change Percent -77 377 126 79 32
Egypt Gross domestic product per capita current prices US dollars Units 1550982 1461431 1278462 1188060 1083158
Egypt Inflation annual percent change Percent 28 24 24 32 52
India Gross domestic product per capita current prices US dollars Units 454206 458849 472915 542554 602625
India Inflation annual percent change Percent 40 38 43 38 47
Kazakhstan Gross domestic product per capita current prices US dollars Units 1236159 1490946 1655148 2000598 2579554
Kazakhstan Inflation annual percent change Percent 134 83 59 64 68
Kyrgyz Republic Gross domestic product per capita current prices US dollars Units 278256 306130 321079 349632 380637
Kyrgyz Republic Inflation annual percent change Percent 187 69 21 31 45
66
Mexico Gross domestic product per capita current prices US dollars Units 5957486 6274468 6425203 6111754 6377064
Mexico Inflation annual percent change Percent 95 64 50 45 44
Morocco Gross domestic product per capita current prices US dollars Units 1161302 1162154 1199584 1432725 1541041
Morocco Inflation annual percent change Percent 19 06 28 12 20
Pakistan Gross domestic product per capita current prices US dollars Units 437381 400356 440471 492913 538120
Pakistan Inflation annual percent change Percent 44 31 32 29 46
Philippines Gross domestic product per capita current prices US dollars Units 979423 900225 950707 963765 1018710
Philippines Inflation annual percent change Percent 43 61 31 30 54
Russia Inflation annual percent change Percent 208 215 158 137 103
Senegal Gross domestic product per capita current prices US dollars Units 478704 474460 507408 634171 714622
Senegal Inflation annual percent change Percent 09 30 23 -00 08
Serbia and Montenegro Gross domestic product per capita current prices US dollars Units 1031263 1389384 1882036 2491799 2795805
Serbia and Montenegro Inflation annual percent change Percent 699 911 212 113 79
Sri Lanka Gross domestic product per capita current prices US dollars Units 846811 796025 828256 904330 982466
Sri Lanka Inflation annual percent change Percent 62 142 96 63 64
Tunisia Gross domestic product per capita current prices US dollars Units 2034360 2065140 2149421 2534823 2881273
Tunisia Inflation annual percent change Percent 30 19 28 28 34
Uganda Gross domestic product per capita current prices US dollars Units 293404 249682 279587 280802 287204
Uganda Inflation annual percent change Percent 45 -20 57 51 35
67
References
Akerlof George A The Market for ldquoLemonsrdquo Qualitative Uncertainty and the Market Mechanism in Quarterly Journal of Economics Vol 84 (1970) pp 488-500
Amin Ruhul et al Integration of an Essential Service Package (ESP) in Child and Reproductive Health and Family Planning with a Micro-Credit Program for poor Women Experience from a Pilot Project in Rural Bangladesh in World Development Vol 29 (2001) No 9 pp 1611-1621
Bester Helmut Screening vs Rationing in Credit Markets with Imperfect Information in The American Economic Review Vol 75 (1985) No 4 pp 850855
Borst Dietmar Microfinance ndash Theoretische Grundlagen fuumlr den Einsatz sowie die Abschaumltzung des Potentials anhand einer Datenbankuntersuchung zur Verwundbarkeit der laumlndlichen Bevoumllkerung in Vietnam unpublished diploma thesis Karlsruhe 2004
BRAC Annual Report 2002 Dhaka 2003
Busch Alexander Kort Katharina Die Peanuts-Banker und ihre Kunden in Handelsblatt Nr 150 published August 5th 2004 p 8
Campion Anita Challenges to Microfinance Commercialization in Journal of Microfinance Vol 4 (1999) No 2 pp 57-65
Chu Michael Key Issues of Development Finance Somerville (MA) 1998
Dornbusch Ruumldiger Fischer Stanley Makrooumlkonomie Oldenburg 1995
Dunn Seth Flavin Christopher Moving the Climate Change Agenda Forward in State of the World New York London 2002 pp 24-50
Farrington Todd Efficiency in Microfinance Institutions in The MicroBanking Bulletin Issue No 4 pp 18-24
Gardner Gary The Challenge for Johannesburg Creating a More Secure World in State of the World New York London 2002 pp 3-23
Ghatak Subrata On Interregional Variations in Rural Interest Rates in Journal of Developing Areas Issue 18 pp 21-34
Gibbons David Serving the Poorest Sustainably in The MicroBanking Bulletin Issue No 5 (2000) pp 13-16
Gibbons David Meehan Jennifer W The Microcredit Summitrsquos Challenge WorkingToward Institutional Financial Self-Sufficiency While Maintaining a Commitment to Serving the Poorest Families in Journal of Microfinance Vol 1 (1999) No 1 pp 131-192
68
Goodwin-Groen Ruth Do Asian MFIs Access Funds from Commercial Banks inThe MicroBanking Bulletin Issue No 3 pp 8-10
Grameen Bank (ed) Grameen Generalized System Dhaka 2003
Gross Alexandra de Silva Samantha Social Fund Support of Microfinance A Reviewof Implementation Experience The World Bank Social Protection Discussion Paper No 0215 Washington DC 2002
Hashemi Syed M Schuler Sidney R Sustainable Banking with the Poor A Case Study of Grameen Bank Dhaka 1997
Helms Brigit Reille Xavier Interest Rate Ceilings and Microfinance The story so farConsultative Group to assist the Poor Occasional Paper No 9 September 2004 Washington DC 2004
Hoff Karla Stiglitz Joseph E Introduction Imperfect Information and Rural Credit Markets-Puzzles and Policy Perspectives in The World Bank Economic Review Vol 4 (1990) No 3 pp 235-250
Holcombe Susan Managing to Empower The Grameen Bankrsquos Experience of Poverty Allevation Dhaka 1995
Hulme David Mosley Paul Finance against Poverty London 1996
Jalvaani (ed) Flush with loans Micro credit for rural sanitation Vol 2 (1999) No 2 pp 1-2
Khandker Shahidur R Fighting Poverty with Microcredit Experience in Bangladesh Oxford et al 1998
Khandker Shahidur R Khalily Baqui Khan Zahed Grameen Bank Performance andSustainability The World Bank Discussion Paper No 306 Washington DC 1995
Lipsey Rechard G An Introduction to Positive Economics 5th edition London 1979
Littlefield Elizabeth Morduch Jonathan Hashemi Syed M Is Microfinance an Effective Strategy to Reach the Millennium Development Goals Consultative Group to Assist the Poorest Focus Note No 24 Washington DC 2003
Martinot Eric Cabraal Anil World Bank Solar Home Systems Projects Experience and Lessons Learned 1993-2000 in Renewable Energy Oxford 2000 pp 1-8
M-Cril Microfinance Review 2003 revised February 2004 Gurgaon 2004a
Mezzera Jaime Microcredit in Brazil The Gap Between Supply and Demand in The MicroBanking Bulletin Issue No 8 (2000) pp 22-24
The MicroBanking Bulletin (ed) Note to the Reader Vol 1 (1997) Issue No 1 pp 5-8
69
The MicroBanking Bulletin (ed) An Introduction to the Peer Groups and Tables Issue No 9 (2003) pp 53-60
MicroRate IADB Performance Indicators for Microfinance Institutions Technical Guide 3rd edition Washington DC 2003
MkNelly Barbara Dunford Christopher Impact of Credit with Education on Mothers and Their Young Childrenrsquos Nutrition Lower Pra Rural Bank Credit with Education Program in Ghana Freedom from Hunger Research Paper No 4 Davis (CA) 1998
MkNelly Barbara Dunford Christopher Impact of Credit with Education on Mothers and Their Young Childrenrsquos Nutrition CRECER Credit with Education Program in Bolivia Freedom from Hunger Research Paper No 5 Davis (CA) 1999
Morduch Jonathan The Microfinance Promise in Journal of Economic Literature Vol 37 (1999b) No 4 pp 1569-1614
Neus Werner Einfuumlhrung in die Betriebswirtschaftslehre Tuumlbingen 1998
Otero Maria Bringing Development Back into Microfinance Journal of Microfinance Vol 1 (1999) No 1 pp 8-19
Panjaitan-Drioadisuryo Rosintan D M Cloud Kathleen Gender self-employment and microcredit programs An Indonesian case study in The Quarterly Review of Economics and Finance Vol 39 (1999) pp 769ndash779
Perkins Dwight H et al Economics of Development 5th edition New York London 2001
Pitt Mark M Khandker Shahidur R Credit Programs for the Poor and the Health Status of Children in Rural Bangladesh in International Economic Review Vol 44 (2003) No 1 pp 87-118
Raiffeisen Friedrich W The Credit Unions 8th edition Neuwied 1966
Rhyne Elizabeth The Yin and Yang of Microfinance Reaching the Poor and Sustainability in The MicroBanking Bulletin Issue No 2 (1998) pp 6-9
Richardson David C Unorthodox Microfinance The Seven Doctrines of Success in The MicroBanking Bulletin Issue No 4 (2000) pp 3-7
Robinson Marguerite S The Microfinance Revolution Sustainable Finance for the Poor Washington DC 2001
Robinson Marguerite S The Microfinance Revolution Volume 2 Lessons from Indonesia Washington DC 2002
Rosenberg Richard Microcredit Interest Rates Consultative Group to assist the Poorest Occasional Paper No 1 revised November 2002 Washington DC 2002
70
Roth Michael Steinwand Dirk Mikrofinanz Weltweites Erfolgsmodell nur nicht inDeutschland Zur Uumlbertragbarkeit der Erfahrungen aus Entwicklungslaumlndern auf Deutschland Deutsche Gesellschaft fuumlr Technische Zusammenarbeit (ed) Eschborn2004
Schmidt Reinhard H Tschach Ingo Microfinance as a Nexus of Incentives Finance and Accounting Working Paper No 87A Frankfurt 2001
Schreiner Mark A Framework for the Analysis of the Performance and Sustainability of Subsidized Microfinance Organizations with Application to Banco Sol of Bolivia and Grameen Bank of Bangladesh unpublished PhD dissertation Columbus (O) 1997
Seibel Hans D Recent Developments in Microfinance Development Research Center Working Paper No 1998-5 Cologne 1998
Seibel Hans D History matters in microfinance in Small Enterprise Development ndashAn International Journal of Microfinance and Business Development Vol 14 (2003a) No 2 pp 10-12
Seibel Hans D Schmidt Petra How an Agricultural Development Bank Revolutionized Rural Finance The Case of Bank Rakyat Indonesia International Fund for Agricultural Development Rural Finance Working Paper B 5 Rome 2000
Sen Amartya Oumlkonomie fuumlr den Menschen ndash Wege zu Gerechtigkeit und Solidaritaumlt in der Marktwirtschaft Muumlnchen Wien 2000
Serageldin Ismail The View of the Chair in Consultative Group to Assist the Poorest Newsletter Issue No1 (1996) pp 1 11-12
Soros George Die Krise des globalen Kapitalismus Offene Gesellschaft in Gefahr Berlin 1998
Staschen Stefan Regulation and Supervision of Microfinance Institutions State of Knowledge Deutsche Gesellschaft fuumlr Technische Zusammenarbeit (ed) Eschborn 1999
Steinwand Dirk The Alchemy of Microfinance The Evolution of the IndonesianPeoples Credit Banks (BPR) to 1999 and a Contemporary Analysis Berlin 2001
Stiglitz Joseph E Peer Monitoring and Credit Markets in The World Bank Economic Review Vol 4 (1990) No 3 pp 351-366
Stiglitz Joseph E Weiss Andrew Credit Rationing in Markets with Imperfect Information in The American Economic Review Vol 71 (1981) No 3 pp 393-410
Tschach Ingo Theorie der Entwicklungsfinanzierung Mit Kleinkreditprogrammen Kredit- und Arbeitsmarktsegmentierung uumlberwinden Frankfurt 2000
UNDP Human Development Report 2004 New York 2004
71
UNFPA state of the world population 2004 New York 2004
UNICEF The State of the Worldrsquos Children 2002 NewYork Geneva 2002
Varley Robert C G Financial Services and Environmental Health Household Credit for Water and Sanitation Environmental Health Project Applied Study No 2 Washington DC 1995
Volkery Carsten Kampf um Straszligenhaumlndler in Die Zeit Nr 23 published May 27th
2004 p 33
Wardhana Ali Introduction in The Microfinance Revolution ndash Sustainable Finance for the Poor Washington DC 2001 pp XVII-XXVII
Woodworth Warner Woller Gary Greetings from the Editors Journal of Microfinance Vol 1 (1999) No 1 p 6
The World Bank Group World Development Indicators 2004 Washington DC 2004
Worldwatch Institute (2002) Vital Signs 2002 New York London 2002
Wimmer Nancy Barua Dipal Less is more Microfinance for solar energy in rural areas in Renewable Energy World Review Issue 2004-2005 Vol 7 (2004) No4 pp 170-179
Yunus Muhammad Grameen Bank II ndash Designed to Open new Possibilities Dhaka 2002
Yunus Muhammad Grameen ndash Eine Bank fuumlr die Armen dieser Welt Muumlnchen 1998a
Internet References
Abishek Lal (nd) An Overview of Microfinance and Environmental Management [http wwwgdrcorgicmenvironabhishekhtml] (availability date October 5 2004)
ACCION (nd) our history [httpwwwaccionorgabout_our_historyasp] (availability date October 5 2004)
ACCION (nd) key statistics [httpwwwaccionorgabout_key_statsasp] (availability date October 5 2004)
Ahmad Zulfiqar (nd) Forms of Regional Cooperation in Microfinance in South Asia [httpwwwbwtporgarcmpakistanIV_News_and_EventsBWTPworkshopZulfiqar20Ahmad20paper20(BWTP-PMN2029Jan04)pdf (availability date October 6 2004)
72
Ahmed Salehuddin (2003) Foreword [httpwwwpksf-bdorgaprm_summit_brochure htm] (availability date September 30 2004)
Annan Kofi (2002) Statement at The Microcredit Summit +5 [httpwww microcreditsummitorgenews2003-03_sp_chowdhuryhtml) (availability date October 5 2004)
Barnes Carolyn (2001) Microfinance Program Clients and Impact An Assessment of Zambuko Trust Zimbabwe [httpwwwmicrofinancegatewayorgfiles18553_Barnes_Zambuko_Trust_2001pdf] (availability date October 5 2004)
Barnes Carolyn Gaile Gary Kibombo Richard (2001) The Impact of Three Microfinance Programs in Uganda [httpwwwmicrofinancegatewayorgfiles2935_Barnes_2001pdf] (availability date October 5 2004)
Barua Dipal (2004) Success of Grameen Shakti in the Field of Renewable Energy Sector in Bangladesh [httpwwwrenewables2004depptPresentation1-SessionVA(14-1530h)-Baruapdf] (availability date September 30 2004)
Bhatt Ela (1997) In 1975 [httpwwwmicrocreditsummitorgdeclarationhtm] (availability date September 30 2004)
BlueOrchard (2004a) Microfinance [httpwwwblueorchardchenmicrofinance_institutions asp] (availability date October 5 2004)
BlueOrchard (2004b) January 2004 Newsletter [httpwwwblueorchardchmedialibrarywebsitenewsletter_jan_2004pdf] (availability date October 5 2004)
Brynjolfsson John (2004) John Brynjolfsson Discusses Recent Trends in TIPS Issuance [httpwwwpimcocomLeftNavPIMCO+Spotlight2004Spotlight_2_04htm] (availability date October 5 2004)
CGAP (2003) Report to the Board of Executive Directors [httpwww-wdsworldbankorgservletWDSContentServerWDSPIB20031208000012009_20031208101736RenderedPDF27441pdf] (availability date October 5 2004)
Chen Shaohua Ravallion Martin (2004) How have the worldrsquos poorest fared since the early 1980s [httpwwwworldbankorgresearchpovmonitorMartinPapersHow_have_the_poorest_fared_since_the_early_1980spdf] (availability date October 5 2004)
Cheston Susy Kuhn Lisa (2002) Empowering Women through Microfinance[httpwwwmicrofinancegatewayorgfiles3240_Cheston_2002doc] (availability date October 5 2004)
Christen Robert P et al (1995) Maximizing the Outreach of Microenterprise FinanceAn Analysis of Successful Microfinance Programs [httpwwwdecorgpdf_docsPNABS519 pdf] (availability date October 5 2004)
73
CIA (2004) The World Factbook [httpwwwciagovciapublicationsfactbook] (availability date October 5 2004)
Clear Profit (2004) Microfinance Bond Record May Double [httpwwwclear-profitcomissuescpsep04txt] (availability date September 30 2004)
Daley-Harris Sam (2003) State of the Microcredit Summit Campaign Report 2003 [httpwwwmicrocreditsummitorgpubsreportssocr2003SOCR03-E[txt]pdf] (availability date September 30 2004)
Dominiceacute Robert (2004) Interview in Microfinance Bond Record May Double [httpwwwclear-profitcomissuescpsep04txt] (availability date September 30 2004)
Donahue Jill Kabbucho Kamau Osinde Sylvia (2001) HIVAIDSmdashResponding To A Silent Economic Crisis Among Microfinance Clients In Kenya and Uganda [httpwwwmicrosave-africacomget_fileaspdownload_id=541] (availability date September 30 2004)
Donahue Jill Sussman Linda (1999) Building a Multi-Sectoral Response Follow-Up Assessment of Programming for Children and Families Affected by HIVAids in Kenya [httpwwwdecorgpdf_docspnacg778pdf] (availability date September 30 2004)
The Economist (1998) [httpwwweconomistcomdisplaystorycfmstory_id=S2629H3C28Q13F240A] (availability date September 30 2004)
Finca (nd) Introduction [httpvillagebankingorgwhereindexphp3] (availability date September 30 2004)
Fischer Stanley (2003) Statement at The Asia Society and Womens World BankingAnnual Microfinance Conference [httpwwwiiecomfischerpdffischer051303pdf] (availability date September 30 2004)
Friedman Milton (nd) Samuha [httpwwwsamuhaorgm-1htm] availability date September 30 2004)
FXTOP (2004) Historical Exchange Rates [httpfxtopcomdehistoratesphp3] (availability date September 30 2004)
Gibbons David Meehan Jennifer W (2002) Financing Microfinance for Poverty Reduction [httpwwwmicrocreditsummitorgpapersfinancing_finalpdf] (availability date September 30 2004)
Grameen Bank (2004) Grameen Bank At a Glance [httpwwwgrameen-infoorgbankcdshtml] (availability date September 30 2004)
Grameen Trust (nd) Grameen Bank Replication Program [httpwwwgrameen-infoorggrameengtrustreplicationhtml8721] (availability date September 30 2004)
74
Hossain Farhad (2004) Microfinance in Development [httpwwwvalthelsinkifi staff jkoponenb1104FarhadFeb2304pdf] (availability date October 5 2004)
IMF (2004) Data [httpwwwimforgexternalpubsftweo200402datadbginimcfm] (availability date October 5 2004)
IMI (2004) Investments [httpwwwimi-agcomoverviewindexhtml] (availability date September 30 2004)
IPCC (2001) Summary for Policymakers [httpwwwipccchpubspm22-01pdf] (availability date September 30 2004)
Jansson Tor Wenner Mark (1997) Financial Regulation and its Significance for Microfinance in Latin America and the Caribbean [httpwwwgdrcorgicmgoverniadb-janssonpdf] (availability date October 5 2004)
Ken Daniel Ten Roeun Van (2004) The Cycle of Debt - As Microcredit Institutions Grow Some Question Their Effect on Poverty [httpwwwcamnetcomkhcambodiadaily selected_featurescd-21-02-04htm] (availability date September 30 2004)
Kim Julia (2002) Social Interventions for HIVAIDS - Intervention with Microfinance for AIDS and Gender Equity [httpwwwwitsaczaradarPDF20filesIntervention_monograph_no_picspdfpdf] (availability date September 30 2004)
Llanto Gilberto (nd) Vietnam [httpwwwadborgDocumentsBooksCentral_Banks_MicrofinanceCountry_Studiesvietnampdf] (availability date September 30 2004)
The Microfinance Gateway (nd) Frequently Asked Questions [httpwwwmicrofinance gatewayorgsectionfaq1] (availability date October 5 2004)
Microfinance Rating and Assessment Fund (2004) Qualified Raters [httpwwwmfrating orgmfi_institutionsqualified_ratershtml] (availability date October 5 2004)
Microcredit Summit (1997) Declaration and Plan of Action [httpwwwmicrocreditsummit orgdeclarationhtm] (availability date September 30 2004)
MicroRate (nd) Performance Indicators and Ratios [httpwwwmicroratecomENGLISHsiteRATINGSindicatorshtml] (availability date September 30 2004)
MicroRate (2002) The Finance of Microfinance [httpwwwmicroratecomPDFFinance20of20Microfinancepdf] (availability date September 30 2004)
MicroRate (2004) Adjusted comparison table [httpwwwmicroratecomENGLISHsitePDFAdjusted20Comparison20Table060320engpdf] (availability date October 5 2004)
75
Mix Market (2004) The Mix Market [httpwwwmixmarketorg] (availability date October 5 2004)
Morduch Jonathan (1999b) The Grameen Bank A Financial Reckoning [httpwwwwwsprincetonedu~rpdsmacarthurdownloadsmorduch_grameen_bankpdf] (availability date September 30 2004)
Pallen Dean (1997) Environmental Sourcebook for Micro-Finance Institutions [httpwwwacdi-idagccaINETIMAGESNSFvLUImagesea20summaries$fileSOURC Epdf] (availability date September 30 2004)
Prisma (2002) The Case for Private Capital Market Creation in the Development Field of Microfinance [httpwwwsocialenterprisenetpdfsprivate_capital_marketpdf] (availability date September 30 2004)
Schmidt Reinhard H Zeitinger C-P (1997) Critical Issues in Microbusiness Finance and the Role of Donors No 6 [httpwwwgdrcorgicmmfi-donorpdf] (availability date September 30 2004)
Seibel Hans D (2003b) Commodity finance a commercial proposition Micro- and Mesofinance for Agricultural Commodity Production Processing and Trade [httpwwwuni-koelndeew-fakaef05-20042003-420Commodity20Financepdf] (availability date September 30 2004)
Simanowitz Anton Walter Alice (2002) Ensuring Impact Reaching the Poorest while Building Financially Self-sufficient Institutions and Showing Improvement in the Lives of the Poorest Families [httpwwwidsacukimpactPublicationsWorkingPapersOP3MCSSumdoc] (availability date September 30 2004)
Smith Stephen C Jain Sanjay (1999) Village Banking and Maternal and Child Health Theory and Evidence from Ecuador and Honduras[httphomegwuedu~scsmith healthrevwd801pdf] (availability date September 30 2004)
United Nations (1999) International Year of Microcredit 2005 [httpods-dds-nyunorgdoc UNDOCGENN9976933PDFN9976933 pdfOpenElement] (availability date October 5 2004)
United Nations (2000) United Nations Millennium Declaration [httpods-dds-nyunorgdocUNDOCGENN0055951PDFN0055951pdfOpenElement] (availability date October 5 2004)
US Census Bureau (2004) Total Midyear Population for the World 1950-2050 [httpwwwcensusgovipcwwwworldpophtml] (availability date October 5 2004)
WHO (2004) Making pregnancy safer [httpwwwwhointmediacentrefactsheets fs276en] (availability date September 30 2004)
WHO (2001) Child Health [httpwwwwhointmipfiles2082AAGChildHealthpdf] (availability date September 30 2004)
76
The World Bank Group (nd) Health Nutrition and Population and the Millennium Development Goals [www1worldbankorghnpMDGMDG20-20HNPbookletpdf] (availability date September 30 2004)
Yunus Muhammad (1998) Championing the Right to Credit for Poor Women Around the World [httpaspgrameencom dialoguedialogue34interviewhtml] (availability date September 30 2004)
UNAIDS (2004) [httpwwwunaidsorgbangkok2004GAR2004_pdfUNAIDSGlobalReport2004_enpdf] (availability date September 30 2004)
Ratings
M-Cril (2000) SPANDANA [httpwwwratingfundorgspanishdocsSPANDANA_RatingReportpdf] (availability date October 7 2004)
M-Cril (2001a) BASIX [httpwwwbasixindiacomMcrilasp] (availability date October 7 2004)
M-Cril (2001b) BDB [httpwwwratingfundorgspanishdocsRF_BDBpdf] (availability date October 7 2004)
M-Cril (2001c) SNEHA [httpwwwratingfundorgspanishdocsRF_Sneha-u1pdf] (availability date October 7 2004)
M-Cril (2002a) KCLF [httpwwwratingfundorgdocsRF-KCLF-risk20reportdoc] (availability date October 7 2004)
M-Cril (2002b) NWTF [httpwwwratingfundorgspanishdocsRF_NWTFpdf] (availability date October 7 2004)
M-Cril (2002c) SEEDS [httpwwwratingfundorgspanishdocsRF_SEEDS_2002_Ratingpdf] (availability date October 7 2004)
M-Cril (2002c) Share [httpwwwratingfundorgspanishdocsRF_SHAREpdf] (availability date October 7 2004)
M-Cril (2002d) TSKI [httpwwwratingfundorgspanishdocsRF_Tski_mcrilfinal(-) reportpdf] (availability date October 7 2004)
M-Cril (2003a) ASA [httpwwwratingfundorgdocsASA20updatepdf] (availability date October 7 2004)
M-Cril (2003b) BURO [httpwwwm-crilcomburopdf] (availability date October 7 2004)
M-Cril (2003c) EMT [httpwwwratingfundorgdocsEMTpdf] (availability date October 7 2004)
77
M-Cril (2003d) SKS [httpwwwmixmarketorgendemanddemandshowprofileaspett=25ampshowinfo=adjusted] (availability date October 7 2004)
M-Cril (2003d) TPC [httpwwwratingfundorgdocsTPC_Finalpdf] (availability date October 7 2004)
M-Cril (2004b) UPAP [httpwwwratingfundorgdocsUPAP_2004pdf] (availability date October 7 2004)
Microfinanza (2002a) ACME [httpwwwratingfundorgspanishdocsACME_finalpdf] (availability date October 7 2004)
Microfinanza (2002b) BTFF [httpwwwratingfundorgspanishdocsBTFF_RatingReportpdf] (availability date October 7 2004)
Microfinanza (2002c) BESA [httpwwwratingfundorgspanishdocsBESA_RatingReportpdf] (availability date October 7 2004)
Microfinanza (2002d) CAME [httpwwwratingfundorgdocsEvaluacionCAME(-) Finaldoc] (availability date October 7 2004)
Microfinanza (2002e) RFF [httpwwwratingfundorgdocsRFF20finalpdf] (availability date October 7 2004)
Microfinanza (2002f) PSHM [httpwwwratingfundorgspanishdocsPSHM_Reportpdf] (availability date October 7 2004)
Microfinanza (2003) CAJCA [httpwwwratingfundorgdocsCalificacion_Jardin_Azuayo_ratingpdf] (availability date October 7 2004)
Microserve (2003) ENDA [httpwwwmixmarketorgendemanddemandshowprofileaspett=865ampshowinfo=adjusted] (availability date October 7 2004)
Planet Rating (2002a) FONDEP [httpwwwmfratingorgRatingscompleted_ratingshtml] (availability date October 7 2004)
Planet Rating (2002b) PRIZMA [httpwwwmixmarketorgendemanddemandshowprofileaspett=111ampshowinfo=adjusted] (availability date October 7 2004)
Planet Rating (2002c) SWS [httpwwwratingfundorgspanishdocsSWC_reportpdf] (availability date October 7 2004)
Planet Rating (2002d) ZAKOURA [httpwwwratingfundorgspanishdocsRF_Zakourapdf] (availability date October 7 2004)
Planet Rating (2003a) AMSSF [httpwwwratingfundorgdocsPlanetRating_AMSSF_010803pdf] (availability date October 7 2004)
Planet Rating (2003b) FOCCAS [httpwwwratingfundorgdocsPlanetRatingFOCCAS120803pdf] (availability date October 7 2004)
78
Planet Rating (2003c) PADME [httpwwwmfratingorgdocsPlaNetRatingPADME070302_Englishpdf] (availability date October 7 2004)
Planet Rating (2003d) PAPME [httpwwwmfratingorgdocsPAPME_PlanetRating080903pdf] (availability date October 7 2004)
Planet Rating (2003e) VITAL FINANCE [httpwwwmfratingorgdocsVital20Finance_Sept202003pdf] (availability date October 7 2004)
Planet Rating (2004a) ABA [httpwwwratingfundorgdocsABA_April202004pdf] (availability date October 7 2004)
Planet Rating (2004b) ACEP [httpwwwmfratingorgdocsACEPSeacuteneacutegal_2004pdf] (availability date October 7 2004)
Planet Rating (2004c) AGROINVEST [httpwwwratingfundorgdocsAgroInvest_June202004pdf] (availability date October 7 2004)
Planet Rating (2004d) ASBA [httpwwwratingfundorgdocsASBA_April202004pdf] (availability date October 7 2004)
Planet Rating (2004e) DBACD [httpwwwratingfundorgdocsDBACD_April202004pdf] (availability date October 7 2004)
Planet Rating (2004f) FINADEV [httpwwwmfratingorgdocsFinadev_2004pdf] (availability date October 7 2004)
Planet Rating (2004g) MI-BOSPO [httpwwwratingfundorgdocsMIBOSPO_160404pdf] (availability date October 7 2004)
Planet Rating (2004h) SBACD [httpwwwratingfundorgdocsSBACD_PlanetRating300604pdf] (availability date October 7 2004)
Other Sources
Interview Shaw Newaz Deputy General Manager of the Grameen Bank October 30th
2003
Hodson Charles (2001) Your Business Your World Jim Boulden CNN (ed) Dhaka 2001
9
1648)18 In 1720 the first loan fund targeting poor people was founded in Ireland by the
author Jonathan Swift19 After a special law was passed in 1823 which allowed charity
institutions to become formal financial intermediaries a loan fund board was established
in 1836 and a big boom was initiated Their outreach peaked just before the government
introduced a cap on interest rates in 1843 At this time they provided financial services
to almost 20 of Irish households20
The credit cooperatives21 created in Germany in 1847 by Friedrich Wilhelm Raiffeisen
served 14 million people by 191022 He stated that the main objectives of these
cooperatives ldquoshould be to control the use made of money for economic improvements
and to improve the moral and physical values of people and also their will to act by
themselvesrdquo23
In the 1880s the British controlled government of Madras in South India tried to use the
German experience to address poverty which resulted in more than nine million poor
Indians belonging to credit cooperatives by 194624 During this same time the Dutch
colonial administrators constructed a cooperative rural banking system in Indonesia
based on the Raiffeisen model25 which eventually became Bank Rakyat Indonesia
(BRI) now known as the largest MFI in the world26
23 Microfinance after the Second World War
Because of further prudential regulation and effective supervision eg through bank
superintendencies the banking sector in the now developed world experienced
continuous growth Today the vast majority of the citizens of the industrialized
countries have access to financial services with many of them being customers of
former MFIs27
18 See Steinwand (2001) p 5119 See Robinson (2002) p 9620 See Seibel (2003a) p 1021 first known as Darlehnsvereine and now called Raiffeisenbanken22 See Morduch (1999a) p 157323 Raiffeisen (1966) quoted in Richardson (2000) p 324 See Morduch (1999a) p 157425 See Robinson (2002) p 9726 See Roth Steinwand (2004) p 327 See Seibel (2003a) p 11
10
This is not true for most developing countries where market penetration of financial
institutions is far from reaching the majority of the inhabitants (see chapter 4) A variety
of reasons is responsible for this including that the banking sector in the most
developing countries have developed in a very different way to than those in
industrialized countries
One of the most important reasons is that in contrast to the industrialized countries little
attention has been paid to the legal recognition prudential regulation and effective
supervision of informal financial institutions28 This insecure legal environment leads to
several problems Since the regulatory framework for mobilizing savings often does not
fit the needs of institutions targeting low income people many organizations are not
permitted to do so and are therefore missing funds to on-lend as credit29 An additional
problem is the lack of a deposit insurances This not only increases the risk of a bank
run but also keeps people from depositing their savings in a financial institution30 In
addition inappropriate interest rate ceilings prevail in many countries While politics
claim they are lowering the interest rates charged to the poor they de facto only limit
their access to financial services (see chapter 5)31
Another problem that retarded the growth of the financial sector in developing countries
was the supply-leading finance theory which dominated the development strategies of
many countries after the second world war32 This theory ldquo refers to the provision of
loans in advance of the demand for credit for the purpose of inducing economic
growthrdquo33 Since it was believed that poor people were neither able to save (and thus
dependent on outside funding) nor capable of paying commercial rates of interest
massive subsidized credit programs were established34 The results were alarming
Repayment rates often did not exceed 50 percent and some government financed
programs even had default rates of more than 90 percent35 The main reason being that
credit was not provided according to business management principles but instead
28 See Seibel (1998) p 829 See Robinson (2001) p 4930 See Staschen (1999) p 1431 See Gibbons (2000) p 1532 See Morduch (1999a) p 157033 Robinson (2001) p 14034 See Borst (2004) pp 33 et sqq35 See Yunus (1998a) p 154 Robinson (2001) p 145
11
according to political objectives Therefore receiving loans was seen as a reward for the
constituents rather than as a business transaction Most of the funds earmarked for the
poor also never reached them ending up instead in the hands of the local elites
Attracted by the below market interest rates and the possibility not to pay back at all
these groups lobbied to be treated privileged and often used the money received for
consumption or for on-lending at higher rates36 But subsidized credit not only
encouraged corruption it also discouraged sustainable financial institutions since they
could not compete with interest rates that were not aimed to cover all costs and were
sometimes even lower than the interest paid on savings37 The low or negative spread
also worked as a negative incentive to institutionsrsquo effort to mobilize savings which in
turn intensified the problem of credit rationing (see chapter 5)
24 Microfinance Today
In the 1970s a paradigm shift started to take place The failure of subsidized government
or donor driven institutions to meet the demand for financial services in developing
countries let to several new approaches Some of the most prominent ones are presented
below
Bank Dagan Bali (BDB) was established in September 1970 to serve low income people
in Indonesia without any subsidies and is now ldquowell-known as the earliest bank to
institute commercial microfinancerdquo38 While this is not true with regard to the
achievements made in Europe during the 19th century it still can be seen as a turning
point with an ever increasing impact on the view of politicians and development aid
practitioners throughout the world In 1973 ACCION International a United States of
America (USA) based non governmental organization (NGO) disbursed its first loan in
Brazil39 and in 1974 Professor Muhammad Yunus started what later became known as
the Grameen Bank by lending a total of $27 to 42 people in Bangladesh40 One year
later the Self-Employed Womenrsquos Association started to provide loans of about $15 to
36 See Robinson (2001) pp 144 et sqq37 Before BRI underwent a major transformation in 1983 a negative spread between interest rates on loans and savings existed While the bank lent at a 12 annual effective interest rate it paid 15 on savingsSee Robinson (2001) p 10638 Wardhana (2001) p XXVII39 See ACCION (nd)40 See Yunus (1998a) p 16 et sqq
12
poor women in India41 Although the latter examples still were subsidized projects they
used a more business oriented approach and showed the world that poor people can be
good credit risks with repayment rates exceeding 9542 even if the interest rate charged
is higher than that of traditional banks Another milestone was the transformation of
BRI starting in 1984 Once a loss making institution channeling government subsidized
credits to inhabitants of rural Indonesia it is now the largest MFI in the world being
profitable even during the Asian financial crisis of 1997 ndash 199843
In February 1997 more than 2900 policymakers microfinance practitioners and
representatives of various educational institutions and donor agencies from 137
different countries gathered in Washington DC for the first Micro Credit Summit This
was the start of a nine year long campaign to reach 100 million of the world poorest
households with credit for self employment by 200544 According to the Microcredit
Summit Campaign Report 67606080 clients have been reached through 2527 MFIs by
the end of 2002 with 41594778 of them being amongst the poorest before they took
their first loan45 Since the campaign started the average annual growth rate in reaching
clients has been almost 40 percent46 If it has continued at that speed more than 100
million people will have access to microcredit by now and by the end of 2005 the goal
of the microcredit summit campaign would be reached As the president of the World
Bank James Wolfensohn has pointed out providing financial services to 100 million of
the poorest households means helping as many as 500 ndash 600 million poor people47
41 See Bhatt (1997)42 See Yunus (1998a) p 143 et sqq43 See Robinson (2002) p 38044 See Daley-Harris (2003) p 345 ldquoThe Microcredit Summit Campaign defines ldquopoorestrdquo as those who are in the bottom half of those living below their nationrsquos poverty line or are living on less than $1 a day adjusted for purchasing power parity (PPP)rdquo See Daley-Harris (2003) p 3 This definition will also be used throughout this paper46 See Daley-Harris (2003) p 1847 See Morduch (1999a) p 1570
13
3 The Impact of Microcredit
31 Microcredit and the Millennium Development Goals
In 1996 Ismail Serageldin the then chair of the Consultative Group to Assist the Poorest
(CGAP)48 claimed that ldquo[m]icrofinance is a proven instrument to assist the very poorrdquo49
This view is also shared by the World Watch Institute50 and underlines what has been
stated above namely that microfinance can be used as a strong anti-poverty tool But
does microfinance actually meet these expectations and keep this promise51
The impact that microcredit has on the lives of poor people will be demonstrated by
showing how it contributes to each of the eight Millennium Development Goals
(MDGs)52 which are related to the reduction of poverty in all its forms These goals
were resolved in September 2000 by the General Assembly of the UN in their
Millennium Declaration53
32 The Eradication of extreme Poverty and Hunger
The aim of the first MDG is to halve the proportion of people who live on less than $1 a
day between 1990 and 2015 According to current population projections of the World
Bank54 this would equal 849 million people in 201555
48 The Consultative Group to Assist the Poorest is a consortium of 28 public and private development agencies working together to expand access to financial services for the poor in developing countries and was established by the World Bank in 1995 Recently it changed its name to Consultative Group to Assist the Poor49 See Serageldin (1996) p 1150 See Gardner (2002) p 1851 See Morduch (1999a) pp 1569 et sqq52 The Millennium Development Goals are (1) eradicate extreme poverty and hunger (2) achieve universal primary education (3) promote gender equality and empower women (4) reduce child mortality (5) improve maternal health (6) combat HIVAIDS malaria and other diseases (7) ensure environmental sustainability and (8) develop a global partnership for development53 See United Nations (2000)54 See World Bank (2004) p 38 et sqq55 Although it is not explicitly mentioned in the Millennium Declaration it is commonly assumed that the share of people living on less than $1 in low and middle income countries should be halved If the share would be calculated with regard to the worldrsquos total population the goal for 2015 would 818 million people For the worldrsquos total population in 1990 see US Census Bureau (2004)
14
Today almost 11 billion people live on less than $1 and more than 27 Billion live on
less than $2 per day56 The mean income for those living under $1 a day is $077 and it
is $125 for those living under $2 a day57 While the number of people living on less
than $1 per day is slowly decreasing and is expected to be 913 million in 2015 the
number of people living on less than $2 a day is actually increasing58 One of the
outcomes from this degree of poverty is that more than 27000 children die every day
from mostly preventable diseases many of them related to hunger59
Microcredit enables poor people to start new businesses or to diversify existing ones
which helps them to increase their income In addition to large amounts of anecdotal
evidence several studies have documented the positive economic impact microcredit
has on its clients Cloud and Panjaitan-Drioadisuryo have found that the average income
of a sample of BRI borrowers has increased by 112 percent and that 90 percent of their
families have crossed the poverty line60 Only 12 out of the 121 respondents of that
study reported that their income had not increased61 According to the Grameen Bank
website 5109 percent of their clients have crossed the poverty line since they took their
first loan62
A study conducted by Barnes showed that the program of the Zambuko Trust a local
MFI in Zambia had a considerable impact on the poorest clients consumption of meat
fish and chicken63 While 76 percent of the continuing clients of the MFI called Share in
India significantly increased their income and 50 percent have crossed the poverty line 64 Khandker discovered in his well known study ldquoFighting poverty with microcreditrdquo
that there is a connection between the microcredit programs of three Bangladeshi MFIs
and household per capita expenditure For every dollar borrowed by a Grameen Bank
member household consumption increases by $018 In addition he found that 5 percent
56 See Chen and Ravallion (2004) p 2957 In fact those people live on less than $108 and $215 respectively a day in 1993 PPP This means that the nominal dollar value of their income is considerably lower See Chen and Ravallion (2004) p 9 58Both numbers are decreasing in Asia but increasing in the rest of the world See Chen and Ravallion (2004) p 22 et sqq59 See UNICEF (2002) p 660 A consistent definition of the term ldquopoverty linerdquo does not exists among different nations Therefore the term will be used according to the definition of the respective country in this paper61 See Panjaitan-Drioadisuryo and Cloud (1999) p 77562 See Grameen Bank (2004) 63 See Barnes (2001) p 8664 See Simanowitz and Walter (2002) p 16
15
of Grameen Bank borrowers move out of poverty every year65 Supposing Khandkerrsquos
findings were correct for all MFIs worldwide and the Microcredit Summit Campaign
achieved its goal of reaching 100 million of the poorest households with microcredit by
2005 then 25 million people (assuming an average family size of five) would leave
poverty every year66 Although this number would have to be adjusted in order take into
consideration the MFI clients who have crossed the poverty line already and of course
the experiences made in Bangladesh can not be transferred precisely to other countries
it still demonstrates the enormous effect that microcredit can have on assisting the
poorest to move out of poverty
Although a 1996 study of Hulme and Mosley states that providing microcredit can also
have a negative impact on the income of the poorest households67 these findings can
be considered as disproved by the recent bulk of evidence drawing favorable
conclusions68
33 Achievement of universal primary Education
The aim of the second MDG is to ensure that all children will be able to complete
primary school by 2015
Currently more than 100 million children most of them girls are not in school69
Besides school fees poor households often can not afford to send their children to
school because they need them to help in the family business
Microcredit programs mainly contribute to the second MDG by increasing families
income and therefore enabling parents to send their children to school Barnes Gaile
and Kibombo found that clients of an MFI in Uganda spent significantly more on
childrenrsquos education than non-clients70 and in Zambia Barnes showed that ongoing
participation in the Zambuko Trustrsquos program had a positive impact on the members
65 See Khandker (1998) p 5666 See Daley-Harris (2003) p 2467 See Hulme and Mosley (1996) p 180 et sqq 68 See Gibbons and Meehan (1998) p 13669 See UNICEF (2002) p 2270 See Barnes Gaile and Kibombo (2001) p 64
16
children staying in school71 In Bangladesh the probability of girls enrolling in school
increased by 19 percent for every 1 percent increase in Grameen Bank loans to female
clients For boys this number was even higher with the mean being 24 percent72
34 Promote gender Equality and empower Women
The aim of the third MDG is to eliminate the disparity in the ratios of girls to boys in
primary secondary and tertiary education in the ratio of literate females to males and to
increase the share of women in the labor market and in parliament73
At present the literacy rate for women is lower than for man all over the world
According to the Human Development Report 2004 the average female literacy rate as
a percentage of male literacy rate is 759 in developing countries and is as low as 37 in
Niger74 But women are not only discriminated against in education but also in access to
medical services and therefore have a higher mortality rate than man75 The worldwide
tendency for women to be underrepresented in the labor market and in the parliaments is
even more severe in developing countries76 Although several women have become
heads of state in various Asian countries (eg Bangladesh India and Indonesia) this is
probably due to them being wives or daughters of former respected male politicians
Since women have a higher repayment rate than man77 and also tend to invest increases
in income on the household and on their children rather than on themselves78 most
MFIs prefer female clients79 Therefore they empower women in many ways Often
MFIs not only encourage women to become involved in financial transactions for the
first time but also to become independent active members of the economy and to
acquire assets in their own names Cheston and Kuhn found that 68 percent of the
women participating in an MFI program in Nepal ldquohellip experienced an increase their
71 See Barnes (2001) p 8472 See Khandker (1998) p 4973 See World Bank (2001) p 2074 See UNDP (2004) pp 225 et sqq75 See Sen (2000) p 23276 See Sen (2000) pp 242 et sqq77 See Littlefield Morduch and Hashemi (2003) p 778 See Yunus (1998a) pp 116 et sqq79 According to the Microcredit Summit Campaign Report 79 or 37677080 of the poorest clients were women See Daley-Harris (2003) p 3
17
decision-making roles in the areas of family planning childrenrsquos marriage buying and
selling property and sending their daughters to school - all areas of decision making
traditionally dominated by menrdquo80 The program of the Lower Pra Rural Bank in Ghana
had an positive impact on womenrsquos participation in the community81 which is true as
well for the CRECER program in Bolivia82 In Bangladesh the Grameen Bank and the
Bangladesh Rural Advancement Committee (BRAC) the two biggest MFIs of the
country had a significant positive effect on womenrsquos empowerment measured through
eight different indicators83 After joining Grameen Bank only 21 percent of the female
members considered themselves as unemployed while this number was 50 percent
before joining84 According to the Grameen Bank website 93 percent of the Bankrsquos
shares are owned by their borrowers which elect the members of the board every three
years They also get familiar with the election process by more frequently voting for
representatives at the lower level of the organizational structure Partly because of this
experience they are more likely to run for public office In the 2003 local government
elections Grameen Bank members constituted 24 of the seats reserved for women
while they represent less than 10 of Bangladeshi adult female population85 Female
clients of MFIs from countries like the Philippines Bolivia and Nepal have reported
similar occurrences86
35 Reduce Child Mortality and improve Maternal Health
The aim of the fourth MDG is to reduce the under-five mortality rate by two-thirds
between 1990 and 2015 and the fifth MDG strives for a three quarter reduction in the
maternal mortality ratio by the same date
As has been stated above more than 10 million children are dying annually in the
developing world of mostly preventable causes with malnutrition playing a role in over
80 See Cheston and Kuhn (2002) p 1881 See MkNelly and Dunford (1998) p 5482 See MkNelly and Dunford (1999) p 7183 The eight different indicators are ldquofreedom of movement economic security ability to make small and larger independent purchases participation in important family decisions relative freedom from domination by the family political and legal awareness and participation in political campaigning and public protestsrdquo Hashemi and Schuler (1998) p 3684 See Holcombe (1995) p 5185 See Grameen Bank (2004)and CIA (2004)86 See Littlefield Morduch and Hashemi (2003) p 8
18
half of the childrsquos deaths and in over 50 countries child mortality rates are greater than
100 deaths per 1000 live births87 Maternal mortality is also a significant problem in the
developing world with more than 500000 women dying every year from pregnancy
related causes88
MFIs are mainly contributing to the these MDGs by increasing families income and
therefore enabling the households to afford better nutrition and medical services
Furthermore they are often linked with microinsurance or health education programs
In addition to what has been showed in chapter 31 Pitt Khandker and Millimet
estimate that a 10 percent increase in the loan size of a female borrower in Bangladesh
increases the arm circumference of their daughters by 6389 Smith and Jain found that
village banking in Ecuador had a positive effect on child diarrhea90 which is responsible
for 15 of child deaths91 Since Sen argues that an improved status of women within
the family reduces child mortality92 the empowerment of women through MFIs is also
contributing to this cause
Although no study has been conducted so far on the direct impact of microcredit on
maternal health it can be assumed that an overall improvement of access to medical
services reduces maternal mortality as well A study of the Morgan State University for
example suggests that microcredit has a positive effect on the prevalence of
contraceptives93 which leads to a decrease of unwanted pregnancies and therefore
reduces maternal death
36 Combat HIVAIDS Malaria and other diseases
The aim of the sixth MDG is to halt and begin to reverse by 2015 the spread of
HIVAIDS malaria and other major diseases and to assist children orphaned by HIV
87 See World Bank (2001) p 888 See WHO (2004) 89 See Pitt Khandker and Millimet (2003) p 11390 See Smith and Jain (1999) p 3791 See WHO (2001) 92 See Sen (2000) p 23593 See Amin et al (2001) p 1614
19
In 2003 29 million people died because of HIV and about 48 million became infected
the greatest number since AIDS was discovered 23 years ago94 This pandemic has lead
to a tremendous decrease in the life expectancy in the hardest hit countries Botswana
for example one of the richest and most democratic countries in Africa has a
HIVAIDS adult prevalence rate of 388 and a life expectancy at birth of less than 31
years95
Malaria not only causes more than one million deaths annually it leads also to 300 ndash
500 million clinical cases a year Both numbers have been steadily increasing over the
past two decades96 More than two million people a year are killed by tuberculosis
another global health problem This curable disease is estimated to cost poor
communities about $12 billion every year since even those who survive normally lose
more than 3 month of work time while recovering97
MFIs contribute to the sixth MDG in several ways By increasing clientrsquos income they
help households affected by HIV or other diseases to better cope with the situation
Besides spending more money on health services and nutrition MFI clients also tend to
be more able and willing to support AIDS orphans than non clients98 In addition to the
already stated increase in the use of contraceptives99 several innovative approaches to
deal with disease related crisis have also arisen This is of course necessary not only to
counteract the devastating effect the above discussed epidemics can have on MFI
clients but also to not put the viability of the respective institution at risk One option is
to integrate education services in the MFI programs and encourage clients to form
solidarity groups100 It has been shown that these services do not necessarily decrease
the effectiveness of the institutionsrsquo employees101 Another way is to strengthen the ties
to NGOs specialize in dealing with the respective disease Synergies gained through this
cooperation can help clients to better deal with the situation and in the end increase their
94 See UNAIDS (2004) p 2395 See CIA (2004)96 See World Bank (2001) p 1697 See World Bank (2001) p 1298 See Barnes (2001) p 6499 See also Kim et al (2002) p 18100 See Donahue and Sussman (1999) p A 14101 See Donahue Kabbucho and Osinde (2001) p 25
20
repayment rates Various MFIs also have introduced loan and health insurance products
or cultivated linkages with organizations doing so102
It has to be stated that despite the benefits MFIs can provide to people effected by
HIVAIDS or other diseases microcredit can also be a burden for those who are already
chronically ill These people can still benefit through loans provided to members of the
family or the community or through one of the other services mentioned above
37 Ensure environmental Sustainability
The aims of the seventh MDG are to support and promote the principles of sustainable
development and put them into action and to improve the lives of slum dwellers and
people without sustainable access to safe drinking water and sanitation
Today climate change is considered as the major environmental problem103 The
Intergovernmental Panel on Climate Change (IPCC) states that human activities
contribute to most of the 06 degC increase in global average temperature over the 20th
century and the predicted increase of another 14 to 58 degC between 1990 and 2100104
Emission of carbon from fossil fuel is reported to have the dominant influence on this
development While the total emission was 16 billion tons in 1950 it was already 65
billion tons in 2000 and is expected to continue to grow105 This development would
lead to a rise in the average sea level of between 9 and 88 centimeters during the next
century106 Furthermore it is predicted that global warming increases the risk of extreme
events like cyclones or floods leads to an increase in the number of people infected by
diseases like malaria and decreases the potential crop harvest and water availability
especially in developing countries107 In 2000 already 11 billion people lacked access to
clean drinking water and 24 billion to basic sanitation108
102 See Barnes (2001) p 40 Barnes Gaile and Kibombo (2001) p 13 and Grameen Bank (2004)103 See Gardner (2002) p 5104 See IPCC (2001) pp 2 et sqq105 Worldwatch Institute (2002) p 52 et sqq106 See IPCC (2001) p 16107 See Dunn and Flavin p 29108 See UNFPA (2004) p 18
21
MFIs contribute to achieving the seventh MDG in several ways By providing loans for
the purchase of renewable energy technologies they help people in developing
countries to increase their per capita energy consumption without increasing the carbon
dioxide emission In a 2003 survey of 140 MFIs from 80 different countries 21 said
they provide credits for solar home systems and another 19 stated they are interested in
becoming engaged in this business109 While Grameen Shakti a rural energy service
company cooperating with the Grameen Bank in Bangladesh has already installed more
than 23000 solar home systems110 a 2000 World Bank study reports twelve projects
providing solar home systems to rural households with a target of 500000
installations111 It has also been suggested that MFIs should raise environmental
awareness among their clients112 but so far no data is available on how staff can cope
with this additional task Many MFIs also provide loans for improvements in sanitation
and the water supply of their clients Varley gives several examples from Africa Asia
and Latin America on how microcredit not only has helped to invest in rainwater
collection systems but also how it has enabled households to increase their water
supply through community water associations113 In addition many MFIs provide credit
for the construction of sanitary latrines114 The situation of slum dwellers is also
positively effected by MFIs Directly through their services in poor urban communities
and indirectly by creating jobs in rural areas and therefore easing the pressure on urban
labor markets
38 Develop a global Partnership for Development
The eight MDG is about the means to achieve the other seven MDGs It calls for all
players involved in the endeavor of development and poverty eradication to work as
partners in a global context
Again MFIs are contributing to the eight MDG in many ways This is occurring through
international networks that provide funding and technical assistance through internet
information portals and specialized journals through social and for profit investors and
109 See Wimmer and Barua (2004) p 174110 Barua (2004) 111 See Martinot and Cabraal (2000) p 6112 See Pallen (1997) p 11 Lal (nd)113 See Varley (1995) pp 39 et sqq114 See Jalvaani (1999) pp 1 et sqq Varley (1995) pp 39 et sqq
22
specialized rating agencies The Bangladesh-based Grameen Trust is one of around 30
networks in operation Besides collaborating with over 200 MFIs around the world it
has directly operated three projects in Afghanistan Kosovo and Myanmar115 While the
ACCION network serves almost 12 million active clients in 19 countries throughout
America and sub-Saharan Africa116 FINCArsquos network operates in three different
continents where it serves more than 200000 customers117 In November 1997 the
MicroBanking Bulletin (MBB) was first published by the microfinance program at the
Economic Institute at the University of Colorado118 Its aim is to develop a database on
the financial performance of MFIs from all over the world which is now available
through the Mix Market an internet portal that also provides information about more
than 300 MFIs investors donor institutions and other related development
organizations119 Two years later the Marriott School at Brigham Young University
started to publish the Journal of Microfinance which has an editorial board of
microfinance experts from all over the world and offers the latest research on this
topic120 In the late 1990s a number of companies became attracted by the microfinance
market and started to invest in MFIs The German based Internationale Mikro
Investitionen Aktiengesellschaft (IMI) for example has already invested more than euro46
million in 19 MFIs in four different continents and plans to invest another euro27 million
before October 2004121 BlueOrchard Finance a microfinance investment consultancy
has channeled more than $60 million worth of private capital to some 40 MFIs
worldwide through investment funds and bond issues122 Big commercial banks like
Citigroup Deutsche Bank and ABN Amro also started to get involved in the
microfinance sector although this is mainly still perceived as a public relation activity
and not as a for-profit investment123 There are also several rating agencies specializing
in MFIs Dependent on their rating these institutions can help MFIs to receive money
from donors or investors Four of the most prominent rating agencies are PlanetFinance
115 See Grameen Trust (nd)116 See ACCION (nd)117 See FINCA (nd)118 See MicroBanking Bulletin (1997) p 5119 See The Mix (2004)120 See Woodworth and Woller (1999) p 6121 See IMI (2004)122 See BlueOrchard (2004b) p 3123 See Busch and Kort (2004) p 8 Fischer (2003) p 6
23
with headquarters in France M-Cril based in India Microfinanza in Italy and
MicroRate with offices in the USA and South Africa124
124 See Microfinance Rating and Assessment Fund (2004)
24
4 Microcredit Outreach
41 The Demand for Microcredit
Although it has been shown that microcredit is one of the most effective poverty
eradication tools that it is considered a human right by some of its advocates125 and it
can contribute considerably to the development of the financial sector in developing
countries an enormous gap still exists between supply and demand for microcredit
Estimates on the demand for microcredit vary greatly While USAID estimates the
number of potential microfinance clients is between 100 and 200 million126 the
Microcredit Summit Campaign states the total demand is more than 234 million
people127 CGAP recognizes some 500 million micro-entrepreneurs who have the
potential to become customers of MFIs128
Marguerite Robinson calculates the demand as follows ldquoAssuming five people to a
household among the 45 billion people living in low- and lower-middle-income
economies in 1999 (World Bank World Development Report 20002001) there are 900
million households in those economies If estimating conservatively we assume that
informal commercial moneylenders supply credit to 30 percent of these households at
least once a year this would mean that there are 270 million households borrowing
from informal moneylenders in a year Undoubtedly however many of these
households borrow multiple times within a yearrdquo129 Although this is a very rough
estimate assuming big differences in demand for microcredit in different countries the
number seems to be the most meaningful In contrast to the estimate of the Microcredit
Summit Campaign it does not include every single household living on less than $1 a
day but according to the definition presented in chapter 1 it counts everyone who has
no regular access to traditional financial institutions but demands such services
Obviously not all people who draw on moneylenders have financial needs that could be
matched through MFIs On the other hand interest rates charged by moneylenders tend
125 See Yunus (1998b) 126 See Christen et al (1995) p 15127 See Daley Harris (2003) p 22 128 See Robinson (2001) p 26129 See Robinson (2001) p 215
25
to be considerably higher than those of MFIs The former normally charge effective
monthly rates between ten and several hundred percent per month the latter generally
charge between 15 and five percent which enables them to attract additional clients130
42 The Supply of Microcredit
In spite of the impressive growth of MFIs around the world the demand for microcredit
is far from being met and this it is not likely to change in the near future The
Microcredit Summit Campaign reported that by the end of 2002 67606080 clients131
were reached through MFIs and that this number has increased by almost 40 percent
annually for the last five years132 It is likely that this tremendous speed of growth is at
least partly due to including MFIs which have not been reporting to the Campaign from
its start in 1997 although they have already existed at that time These institutions
contributed 22 percent to the growth in poorest clients in 2000 578 percent in 2001 and
338 percent in 2002 The growth of the poorest clients increased at least party because
of an expanded definition of the term ldquopoorestrdquo133 Since the contribution of MFIs
which previously have not been considered can be expected to decrease dramatically
the growth rate as stated by the Microcredit Summit Campaign can not be used to
predict the future development of the microfinance sector Another factor likely to slow
down the growth is the concentration of microfinance activities in some Asian countries
where almost 90 percent of the poorest microfinance clients live today134 Even if one
takes into consideration the relative size of Asiarsquos population and the fact that many
MFI customers in Latin America are relatively better off and therefore are not included
in this numbers the coverage of this part of the world far exceeds the others In
Bangladesh for example the microfinance market is close to saturation More than
eleven million households were served by several hundred MFIs in 2001135 Among
them are Grameen Bank and BRAC two of the best known MFIs in the world both
providing their services to more than three million customers With an average
household size of five it can be assumed that in Bangladesh the number of people
130 See Gibbons and Meehan (1999) pp 144 et sqq131 41594778 of them belonged to the poorest before they took their first loan The relative numbers in the following are for these poorest clients only since no other current data was available It can be assumed though that this works as a good proxy for the total number of clients 132 See Daley Harris (2003) p 3133 See Daley Harris (2003) p 17134 See Daley Harris (2003) p 21135 See Ahmed (2003)
26
benefiting from microcredit already surpasses the number of people living below the
poverty line which is estimated to be slightly higher than 50 million136 Therefore
Bangladesh will not contribute to the growth of the microfinance sector as much as it
has done in previous years This is also true for Vietnam Thailand and to a lesser
extent Indonesia Eight of the nine MFIs serving more than one million clients are based
in these countries while the ninth is based in India where due to its one billion
inhabitants the microfinance market is still far from saturation137 In contrast the
supply in Brazil meets less than two percent of the demand which is estimated to be
about 58 million potential clients138 For these reasons greater amount of future growth
must come from smaller or new MFIs in Latin America India China and especially
Africa where almost 30 percent of the worldrsquos poorest live139
43 Meeting the Demand
To fill the gap between the demand and supply for microcredit tremendous investments
are necessary to increase the loan funds of MFIs and build up their capacity through
upgrading existing institutions or building new ones Again estimates on how much
capital is needed vary greatly with the highest being at more than $300 billion140
In 1997 the Microcredit Summit Campaign estimated that $216 billion would be
needed to achieve their goal of providing microcredit to 100 million of the poorest
households This was calculated in the following way Since some 8 million people
already received microcredit in 1997 another 92 million needed to be reached
Assuming $200 ($150 for loan fund and $50 for capacity building) would be needed per
person for 88 million people in developing countries and $1000 ($500 for loan fund and
$500 for capacity building) would be needed for 4 million people in industrialized
countries the capital required ends up to be $216 billion141 For several reasons this
136 See CIA (2004)137 These institutions are The Grameen Bank BRAC Proshika and the Association for Social Advancement (ASA) in Bangladesh the Vietnam Bank for Agriculture and Rural Development (VBARD) and the Vietnam Bank for the Poor (VBA) in Vietnam BRI in Indonesia Bank for Agriculture and Agricultural Co-operatives (BAAC) in Thailand the National Bank for Agriculture and Rural Development (NABARD) in India See Ahmed (nd) p 1 Llanto (nd) p 337138 See Mezzera (2002) p 23139 See See Chen and Ravallion (2004) p 29140 See Clear Profit (2004) Prisma (2002)141 See The Microcredit Summit (1997)
27
number is not qualified to predict the total amount of capital needed to meet the demand
for microcredit On the one hand it focuses mainly on the low end of the market and
therefore underestimates the average loan fund needed On the other hand it does not
take the increasing capital demand from established MFIs into account A survey of 119
MFIs found that the average loan size to increased from $406 in 2002 to $498 in
2003142 This is mainly due to the fact that MFI clients once they have paid back their
loans usually demand larger ones for the continual development of their businesses
and therefore further increase the demand for capital of established MFIs The Grameen
Bank for example has a ceiling on its loans which increases or decreases depending on
the borrowers performance regarding repayments and savings143 While the maximum
amount for the first loan is fixed at approximately $75144 the largest loan disbursed so
far was $17195145 Thus if one estimates that by now 100 million people are borrowing
from MFIs146 another 170 million need to be reached to meet the estimated demand
Assuming an average of $600 ($400 for loan fund and $200 for capacity building) is
needed for every new client and another $200 is needed for every existing client to meet
the demand for larger loans a total of $122 billion is required This rough estimate
helps to convey the approximate amount of capital needed to meet the demand for
microcredit
So far the demand for funds is being partly met by donors which annually provide
between $500 million and $1 billion147 and through the mobilization of local savings
Obviously the amount of money provided by donors will not be able to meet the capital
demand for microcredit in the short term The mobilization of savings on the other hand
has been extremely successful in some cases with BRI probably being the most
prominent example After adapting commercial principals in October 1984 BRI was
able to raise its deposits from $161060 to more than $32 billion in 2003 which equals
almost two times its current loan portfolio148 Many other MFIs like BDB in Indonesia
142 Own calculations Without BRI the numbers would be $343 and $409 See Appendix 1143 See Grameen Bank (2003) p 13144 The accurate amount is 5000 Taka See Interview with Shaw Newaz145 Grameen Bank (2004)146 According to the data provided by the Daley Harris (2003) an annual increase in MFI clients ofapproximately 25 percent from 31122002 till the 3092004 would be needed to reach 100 million clients by now This rated is considerably below the average of the previous five years (38 percent) Therefore it can be assumed as realistic despite the growth hindering factors presented above147 See CGAP (2003) p 8148 See Robinson (2002) p 273 Mix Market (2004)
28
XacBank in Mongolia the Equity Building Society in Kenya or the Centenary Rural
Development Bank in Uganda also have managed to cover their loan portfolio fully
through internally mobilized resources149 The Grameen Bank is also expected to do so
in the first half of 2005150 In addition to raising much needed capital for on-lending the
provision of saving services can deliver notable social benefits itself151
Despite these impressive achievements even the combination of donor money and local
savings at their current levels will not be able to provide the capital needed to continue
the rapid growth of the microfinance sector Especially in their early years MFIs rely on
outside funding BRI for example needed six years before the amount of locally
mobilized savings surpassed the total amount of outstanding loans During this time
expenses and the loan portfolio were covered through a government grant worth $20
million and two World Bank loans of $5 and $97 million respectively152 It also
benefited from a network of more than 3600 branches which were established
throughout the country during the 1970s and early 80s in order to provide government
subsidized credit in rural areas153
The Grameen Bank also widely known as a best practice MFI has received about $175
million in direct and indirect subsidies between 1985 and 1996154 and continues to rely
on outside funding at below market interest rates This is made possible either through
special loans from the Bangladesh Bank or through offering bonds guaranteed by the
Bangladesh government155 - an option most MFIs do not have BDB might be one of the
very few examples which were able to finance their activities through savings and
commercial loans from the start but its outreach did not reach a large scale nor did it
serve the low end of the market In 2000 after 30 years of operation BDB provides
credit to only 10417 clients with an average loan balance of more than $5000156
approximately eight times the countries GDP per capita157
149 See Mix Market (2004)150 See Grameen Bank (2004)151 See Robinson (2001) pp 263 et sqq152 See Seibel and Schmidt (2000) p 4153 See Robinson (2002) p 180154 See Morduch (1999b) p 8155 See Morduch (1999ba) p 25 et sqq156 See Robinson (2002) p 387157 See CIA (2004)
29
Another problem keeping many MFIs from collecting savings is that they do not want
to become a regulated financial institution or do not meet the criteria in their respective
country and therefore they are simply not allowed to mobilize savings from the public
In summary the examples and numbers presented in this chapter support the argument
that the amount of capital that can be raised through donors and locally mobilized
savings is not enough for continuous rapid growth of the microfinance sector If this
lack of capital is not met through other sources the microfinance sector will fail to
contribute its full potential to the achievement of the MDGs
44 Microfinance and the Capital Markets
Regardless of whether the amount of capital needed for the development of the
microfinance sector is $20 or $300 billion it represents only a tiny fraction of the
worldwide capital markets which are estimated at $30 trillion158 Therefore if the
microfinance industry were able to tap the financial markets it would be able to grow
much faster and soon serve the millions of micro-entrepreneurs which currently can not
develop theirs businesses because of capital constrains Another advantage would be
that scarce donor money currently used for the development of the microfinance sector
could be used for other projects that do not have the potential to draw money from
commercial sources This view is shared by Michael Chu the former CEO of ACCION
who made the following statement in 1998 ldquoMicrofinance today stands at the threshold
of its next major stage the connection with the capital marketsrdquo159 Many attempts have
been made since that time Successful MFIs like BancoSol in Bolivia further
strengthened their ties to the capital markets which in some cases already provide the
majority of their funding160 Microfinance investment advisors like BlueOrchard
Finance have become middlemen for MFIs and the financial markets Nevertheless
these links are still far from reaching major scale Currently only approximately 20
percent of MFIs funding comes from commercial sources161 and the biggest bond issue
dedicated to fund MFIs totals only $40 million In addition these funds mainly end up
158 See Brynjolfsson (2004) 159 Chu (1998) quoted in Robinson (2001) p 23160 See Robinson (2001) p 69161 See Dominiceacute (2004)
30
in established institutions in Latin America or Eastern Europe162 while smaller
organizations only benefit indirectly if at all
162 See Clear Profit (2004) IMI (2004)
31
5 Credit Rationing
Until recently the predominant answer to why commercial banks or venture capital
companies did not invest in the microfinance sector was that the poor are not bankable
Besides lacking education and therefore not being able to deal with formal financial
institutions they were viewed as bad credit risk who were unable to invest the borrowed
money in a way that would allow them to repay the loan and interest at a commercial
rate163 Another reason that kept attention away from the idea of providing financial
services to low income people was the belief that informal moneylenders already met
this demand These skeptics felt affirmed through the poor performance of subsidized
credit programs as described in chapter 22 Although it is true that moneylenders
serve a huge number of people in the developing world they more often than not charge
usury interest rates of up to 20000 percent per month164 While the argument that poor
people are not able to participate in the formal financial market can be overcome by
adapting the services accordingly165 the claim of low returns on their investments is not
only proved wrong by empirical evidence but also contradicts economic theory as will
be shown in chapter 53
51 The imperfect Information Paradigm
A more elaborate explanation for the short supply of financial services to low income
people that can be derived from the imperfect information paradigm based
predominantly on the works of Akerlof166 and Stiglitz and Weiss167 After giving a brief
summary of their argument an adaptation of their findings to the microfinance market
will be presented and subsequently it will be shown how their conclusions can be
overcome
Behind the imperfect information paradigm lies the theory of asymmetric information
which simply states that if two parties conduct a transaction one is likely to have more
163 See Ghatak (1983) p 21 et sqq Yunus (1998) p 102 et sqq Robinson (2001) p 35 et sqq164 See Robinson (2001) p 17165 See Seibel (2003b) p 2 BRAC (2003) pp 15et sqq Yunus (1998) pp 151 et sqq 166 See Akerlof (1970) pp 488 et sqq167 See Stiglitz and Weiss (1981) pp 393 et sqq
32
information than the other and is trying to use that for its own advantage168 Applied to
the banking sector this means that a person applying for credit can better judge the
likelihood of repaying the loan than the bank This is because the borrower has better
knowledge of the market she wants to invest in her skills and her willingness to repay
Moreover the bank might not be able to observe if the borrower uses the loan for the
agreed purpose These occurrences can lead to what is known as adverse selection and
moral hazard In this case adverse selection refers to the problem that banks might
attract borrowers with a low probability of repayment if they can not distinguish
between high and low risk loan applicants Moral hazard occurs after the provision of
the loan when the borrower spends the money on a purpose different to the prescribed
purpose and therefore lowers the probability of repayment This can happen eg by
investing in a more risky project or through spending the money on consumption If the
bank is not able to find a cost effective way to avoid these problems it might raise its
interest rate in order to compensate for the increased risk
Figure 1 Expected Bank Return and the Interest Rate
Source Stiglitz and Weiss (1981) p 394
Since this might discourage low risk borrowers from applying for credit and encourage
borrowers who continue to take loans to invest in riskier projects the share of high risk
168 See Neus (1998) p 85 et sqq
INTEREST RATEI
EX
PE
CT
ED
RE
TU
RN
TO
TH
E B
AN
K
33
borrowers could increase and therefore reinforce the problems stated above Thus
increasing the interest rate beyond a certain point actually leads to a decrease in the
expected return to the lender This context is illustrated in figure 1 with I being the
interest rate which maximizes the expected returns to the bank Obviously the bank
would charge the interest rate I in order to maximize its expected return However this
price for capital was not determined through supply and demand as economic theory
would predict It is conceivable that at the interest rate I the demand for credit exceeds
the supply but even if loan applicants would offer to pay a higher interest rate the bank
would refuse because it associates such a loan with high risk As a result credit might
be rationed169
52 Adaptation to the Microfinance Sector
Through some adaptations this model can also help to explain the lack of funds
provided to low income people In the original model of Stiglitz and Weiss several
assumptions have been made that need to be suspended in order to compare the credit
markets for low and high income people and give an explanation why the latter is
widely neglected by institutional investors
Evidently the assumptions that the amount borrowed is equal for each loan applicant
and that transaction costs170 need not to be taken into account171 are not suitable for this
context While the average loan size of MFI customers is much smaller than that of
clients from traditional banks the transaction costs as a share of the loan are
considerably higher because the lenderrsquos costs for conscientious processing a credit
applications are only slightly smaller for a $50 loan than for a $100000 or a
$10000000 loan
In figure 2 the R(I)large curve represents the return to the bank for large loans with
regard to the interest rate I and the R(I)small curve describes the same correlation for
small loans It is shifts downwards to reflect the assertion that the imperfect information
169 See Stiglitz and Weiss (1981) p 394170 In this paper the term bdquotransaction costsldquo refers to the operating expense ratio as defined by MicroRate It ldquois calculated by dividing all expenses related to the operation of the institution (including all the administrative and salary expenses depreciation and board fees) by the period average gross portfoliordquo See MicroRate and Inter-American Development Bank (IADB) (2003) p 16 171 See Stiglitz and Weiss (1981) p 396
34
paradigm has a more severe effect on poor people than on the better off They are
expected to have less profitable investment opportunities at their disposal172 and
therefore are more likely to invest in riskier projects which increase the probability of
default and hence decrease the expected return to the bank Additionally one might
expect poor people to be more likely than others to spend borrowed money on
consumption instead of an income generating activity particularly if a crisis arises It
seems understandable that food or urgently needed medicine are given priority over
repaying a loan
The second shift downwards is due to transaction costs As stated above they are
relatively higher for smaller loans Obviously transaction costs are incurred in the
provision of a large loan as well but since they are much smaller with regard to the loan
amount they are not included in the diagram for reasons of clarity
Figure 2 The extended Model
Source Own diagram adapted from Stiglitz and Weiss (1981) p 394
172 See Khandker (1998) p 8
INTEREST RATE I
SmallLoans
LargeLoans
Transaction costs
Lack of investment opportunities
R(I)large
R(I)small
EX
PE
CT
ED
RE
TU
RN
TO
TH
E B
AN
K
35
53 Overcoming Credit Rationing for the Microfinance Sector
If the conclusions in chapter 51 hold it is rational for a profit maximizing investor to
neglect the microfinance sector as long as no surplus funds in the market for large loans
exist This finding can help to explain the small amount of money provided to the
microfinance sector from commercial investors On the other hand it has to be stated
that this theory is reflexive as defined by Soros173 It not only explains but also forms
reality since it has the potential to reinforce the view of potential investors that
microfinance is a less profitable business174 Therefore demonstrating under which
conditions microfinance can be profitable and in some cases be more profitable than
traditional businesses is of crucial importance
To provide a fairer view of the microfinance sector a further assumption of the Stiglitz
and Weiss model that needs to be suspended is that all investments made by the
borrowers have the same expected return175 As stated above this contradicts economic
theory which claims ceteris paribus capital productivity decreases while the amount of
fixed capital increases In combination with a low capital endowment micro-enterprises
are usually faced with an excess supply of unskilled labor especially in developing
countries176 Hence small enterprises use far less capital per employee than big business
and therefore their marginal productivity of capital is much higher177 This is intuitive if
one imagines an economic actor who wants to invest several packages of capital
Obviously she would invest the first package where she expects the highest return the
second package where she expects the second highest return and so on Each additional
investment opportunity would lead to lower or at best equal returns178 While this
simplified example has limitations it demonstrates how the marginal productivity of
capital can diminish Although it might actually increase until a certain point179 this can
be expected to be so low in this context that it has no influence on the correlation as
shown in figure 2
173 See Soros (1998) pp 14 et sqq174 See Goodwin-Groen (1999) p 8175 See Stiglitz and Weiss (1981) p 395176 See Perkins et al (2001) pp 95 et sqq177 See Tschach (2000) p 8178 See Rosenberg (2002) p 11179 See Rechard G Lipsey (1979) pp 211 et sqq
36
Figure 3 Marginal Productivity of Capital
Source Dornbusch and Fischer (1995) p 406
Even if good investment opportunities for poor people exist the question remains if it is
possible to distinguish between high and low risk borrowers The problem of adverse
selection is overcome in a cost effective way in many MFIs180 For the better off poor
for example institutions like BRI base their decision on whether or not to approve a
loan by assessing the repayment ability of potential borrowers from their current income
flows and not from the uncertain returns generated by the loan181 Additionally
collateral is used in some cases to attract low risk borrowers182 In contrast to
industrialized countries this is usually not done to cover the potential losses of the
lender but to punish the defaulter and therefore increase her willingness to repay183
Obviously this does not always work for the poorest since they often neither posses any
goods that could work as collateral nor do they have sufficient earnings prior to
obtaining a loan for starting an income generating activity Here the so called group-
lending model can help to identify creditworthy borrowers The most prominent
institution using this approach is the Grameen Bank which only provides credit to
180 See Farrington (2000) p 20181 See Robinson (2001) p 80 Robinson (2002) p 238182 See Bester (1985) p 850 et sqq183 See Schmidt and Tschach (2001) p 15 Robinson (2002) p 244
FIXED CAPITAL 0
MA
RG
INA
L P
RO
DU
CT
IVIT
Y
37
members of a group of five These groups are formed by their members without
interference of the Grameen Bank Although in this particular case no joint liability
exists for the members of the group nobody can receive a new loan if another member
of the group fails to repay on time184 Therefore the group formation work as a
screening process Since the borrowers do not want to risk their ability to obtain further
loans they carefully select with whom to form a group Usually the members know
each other for a long period of time and therefore they can make a meaningful judgment
of each othersrsquo ability to repay the loan Other MFIs even require the members of a
group to mutually guarantee each othersrsquo loans185 While this might further increase
borrowersrsquo efforts to search for trustworthy group members it might also keep potential
borrowers from applying for a loan since she does not want be held responsible for
defaulting members This mechanism enables MFIs to partly pass on the transaction
costs related to the selection of low risk borrowers to the borrowers themselves186
Many MFIs have also largely overcome the problem of moral hazard by creating
incentives to ensure a high repayment rate even among the poorest In some cases their
customers go hungry in order to pay back their loan even though no legal action would
be taken against them if they would refuse to do so187 One way to achieve this is to
build up peer pressure through the formation of groups as described above188 Another
and probably the most important is to limit access to future loans to those borrowers
who repay on time The demand for successive loans is extremely high In a 1996
survey 98 percent of BRI borrowers planed to apply for another loan189 and in 1993
less than 30 percent of Grameen Bank loans went to first time borrowers190 Especially
the poorest highly value the option to reborrow191 and many MFIs see this as their
primary incentive to ensure repayment192 According to Schmidt and Tschach ldquothe net
present value of future access to credit works out to be roughly half the value of the
economic advantage to be gained from the intended non-repaymentrdquo193 This can also
184 See Yunus (1998) p 135185 See Schmidt and Zeitinger (1997) p 6186 See Stiglitz (1990) p353187 Own observation at the Grameen Bank in Bangladesh (2003)188 See Hoff and Stiglitz (1990) p 249189 See Robinson (2002) p 251190 See Khandker Khalily and Khan (1995) p 93191 See Gibbons (2000) p 15 Hashemi and Schuler (1997) p 43192 See Gibbons and Meehan (1999) p 160193 See Schmidt and Tschach (2001) p 16
38
explain the occurrence of a drop in the repayment rate once a MFI is no longer seen as
viable and therefore is not expected to provide loans in the future194
With the help of the described mechanisms MFIs around the world are able to keep
repayment rates high A survey of 69 MFIs from 36 different countries each serving
more than 10000 clients in 2002 found the portfolio at risk (PAR)195 varied between
zero and 231 percent While the average was 36 percent the median was found to be
229 percent196 One of the MFIs included in this sample is BRIs whorsquos 12-month loss
ratio has never exceeded five percent since the start of its transformation in 1984 and
from 1997 to 1998 the ratio actually fell from 22 to 194 percent197 The latter deserves
special attention because the Asian financial crisis reached its peak at that time with
Indonesia being hardest hit as illustrated by a statement from The Economist in July
1998 Even with the fierce competition from its neighbors Indonesia would probably
walk away with the prize for Asias most desperate banking systemrdquo198
The findings that MFIs can adapt their services to low income people in order to ensure
a high repayment rate and that poor people do not lack profitable investment
opportunities are illustrated in figure 4 From this diagram it can be seen that under the
new assumptions the interest rate at which the bank maximizes its return differs for
large (I(l)) and small loans (I(s)) According to the assumption that micro-
entrepreneurs can realize a higher return on their investments the bank can charge them
a higher rate of interest without bearing an increased risk Nevertheless in this example
the bank would still serve the market for large loans first because of the higher
transaction costs for smaller loans
The view as described in figure 4 is shared among most traditional banks and investors
in industrialized as well as in developing countries In addition to neglecting the
possibility of generating profits by offering microcredit themselves199 they also hesitate
to lend to MFIs because they consider their business too risky
194 See Schreiner (1997) p 64195 ldquoPAR shows the real risk of the portfolio by comparing outstanding loan balances for loans with atleast one late payment to the outstanding loan portfoliordquo Gross and de Silva (2002) p 22196 Own calculations See Appendix 2197 See Seibel (2000) p 11198 The Economist (1998) pp 92 et sqq199 Busch and Kort (2004) p 8
39
Figure 4 The extended Model
Source Own diagram adapted from Stiglitz and Weiss (1981) p 394 Tschach (2000)
p 17
This attitude can be observed by comparing the ratio of equity to liabilities which is
considerably higher for MFIs than for conventional banks200 When it comes to MFI
start-ups and those MFIs serving the low end market in remote areas even experienced
microfinance practitioners are skeptical if interest rates that fully recover all costs can
be charged201
Theoretically there are two ways to adjust this model to arrive at a conclusion which is
more favorable with regard to the profitability of microcredit One is to cut the
transaction costs and therefore reduce the downward shift of the R(I)small curve the
other is to allow the bank to further raise the interest rate without experiencing a
decrease in its return This means to increase I(s) and the respective rate of return
While in 2000 Tschach stated that transaction costs vary between 10 and 20 percent for
loans provided through the group lending model and between 15 and 30 percent for
200 See MicroRate and IADB (2003) p 30201 See Volkery (2004) p 33 Gibbons (2000) p 15 Gibbons and Meehan (2002) p 29 Goodwin-Groen (1999) p 8
INTEREST RATE I(l)
SmallLoans
LargeLoans
Transaction costs
I(s)
R(i)large
R(i)small
EX
PE
CT
ED
RE
TU
RN
TO
TH
E B
AN
K
40
individual loans202 it was recommended in 1999 that MFIs should target a range
between 15 and 25 percent203 Some best practices on the other hand have already
achieved single digit numbers Currently BDB might be the most efficient MFI in the
world with transaction costs at just 47 percent in 2001204 Even though the low costs of
BDB have to be acknowledged its achievement has to be put in perspective As stated
above with an average loan balance of more than $5000 it does not serve the low end
market In addition it works in an environment with a high population density which
means that it can reach a relatively large group of borrowers per branch This is a
comparative advantage many Asian MFIs enjoy as can be illustrated by comparing
Bangladesh and Bolivia Both countries are at the forefront of the development of
microfinance in their respective continent but while in Bangladesh more than 1000
people are living per square kilometer the average for Bolivia is only eight205
Therefore it is consistent that the most efficient MFI in Latin America Fondo
Financiero Privado para el Fomento a Iniciativas Economicas has transaction costs of
114 percent206 With an average loan size greater than the annual GDP per Capita this
institution also does not serve the low end market207
Despite the impressive efficiency gains in the described examples most MFIs are far
from achieving these numbers and many are unlikely to reach them due to the
environment within which they work A survey of 67 MFIs from 31 countries found the
average transactions costs in 2002 to be 279 percent with a median of 206 percent208
However even if these institutions were to increase their efficiency to best practice
standards their transaction costs would still be significantly higher than those of
traditional banks providing much larger loans For these banks the respective costs vary
in a range between 05 and 3 percent209 According to this argument charging interest
rates considerably higher than conventional banks is the only way for MFIs to generate
higher returns and hence successfully compete for capital
202 See Tschach (2000) pp 100 et sqq203 See Gibbons and Meehan (1999) p 149204 See M-Cril (2001b) p 4205 See CIA (2004)206 See MicroRate (2004)207 In this paper the term ldquolow endrdquo refers to the definition of the MBB (2003) p 54 Loans worth less than 20 percent of the respective countryrsquos GDP per capita are described that way 208 Own calculations See Appendix 3209 See M-Cril (2004a) p 16
41
6 Interest Rates
61 Setting the right Interest Rate
Before addressing the questions to what extend MFIs can raise their interest rates
without putting the repayment rate or the social benefits of their customers at risk a
basic model will be presented This model will illustrate how a MFI should set their
rates in order to not only cover their costs but also to generate an appropriate profit to
finance further growth and attract additional capital
In 2002 CGAP revised its 1996 paper ldquoMicrocredit Interest Ratesrdquo210 which outlines
the standard method of setting sustainable interest rates for commercially oriented
MFIs According to this model the annual effective interest rate (I) should be calculated
as shown below
(1) I = LL
IIKCFLLTA
minusminus+++
1
With each variable being a decimal fraction of the average outstanding loan portfolio
whereby TA stands for the transaction costs as described above LL represents the
annual loan loss and II stands for investment income eg on liquid assets The cost of
funds (CF) consist of the interest and administrative costs needed to obtain deposits and
commercial loans as well as of the imputed costs on equity due to inflation K stands for
the capitalization rate which represents the net real profit Keeping this rate high is
important to finance the future growth of the loan portfolio This can be either done
through investors attracted by high profitability or through borrowing For the latter an
increase in equity is inevitable since it is required as a safety cushion by lenders
Since this model ignores the timing of cash flows and does not take taxes into account
it has to be regarded as fairly imprecise and hence should not be used for business
planning Nevertheless it can be used for an approximation of the interest rate that a
MFI would need to charge to provide its services as planned In the following I will
210 See Rosenberg (2002) pp 1 et sqq
42
apply this model on a fictitious MFI working in a rural area of Latin America with low
end customers In this setting it seems realistic to estimate transaction costs of 35
percent and loan loss rate of two percent211 If funds were borrowed at commercial
terms their costs can be assumed to equal at least 15 percent of the average outstanding
loan portfolio212 Estimating the capitalization rate is more challenging First the
targeted portfolio growth rate is set at 75 percent This is slightly below the 751 percent
average annual portfolio growth between 2000 and 2002 found by a survey of 25
different MFIs based in Central and South America213 If the extend to which the MFI
can leverage stays constant the loan portfolios growth would be limited by the growth
rate of the equity To express the capital needed for this growth as a share of the loan
portfolio it is necessary to estimate the ratio between the equity and the outstanding
loan amount According to the survey mentioned above the loan portfolios of the 25
Latin American MFIs equal on average 215 times their equity214 With this number the
capital needed to increase the equity by 75 percent would corresponds to approximately
35 percent of outstanding loan amount (075215) Finally the investment income has to
be estimated Since liquid assets that are available short term do not generate high
returns say five percent it does not seem advisable for the MFI to hold more than a
quarter of its loan portfolio in this form Hence the profit generated in this way would
equal 125 percent of the outstanding loan amount Using these numbers the equation to
calculate the annual effective interest rate reads as follows
(2) I = LL
IIKCFLLTA
minusminus+++
1 =
0201
01250350150020350
minusminus+++
= 0875
As a result the MFI would need to charge an annual effective interest rate of
approximately 875 percent on its loans in order to sustainable provide its services and
finance its growth without depending on donor money This rate might decrease once
the MFI matures the growth slows down and cheaper funds become available but it
will stay significantly higher than any rate charged by conventional banks
211 MicroRate and IADB (2004) pp 6 and 16212 See MicroRate and IADB (2004) p 616 and 28213 Own calculation See Appendix 4214 Own calculations See Appendix 5
43
62 Can Micro-Entrepreneurs bear these Rates
Although most MFIs charge rates significantly below 875 percent many critics have
strenuously argued against any rates exceeding those of traditional banks Rosanna
Barbero of Oxfam labeled an interest rate of 52 percent charged by a Cambodian MFI
ldquoludicrous evil and disgusting and stated that ldquo[n]o business in the world can make a
profit at these interest ratesldquo215 The former finance minister of Bangladesh Shah Kibria
even categorized the 20 percent effective rate charged by the Grameen Bank as to
high216 Many practitioners therefore believe in a strong negative correlation between
the interest rate and the demand for loans217 Others have argued more generally that
concentrating on profitability and therefore charging high interest rates diverts MFIs
from serving the poorest218
These views are still shared among many MFI managers donor agencies and especially
investors and politicians While the former are unwilling to charge interest rates for
funds they received ldquocheaplyrdquo (through grants or subsidized loans) and are worried
about undermining their social goals by charging higher rates of interest219 the latter are
reluctant to invest for reasons stated above or impose interest caps to catch the attention
of the public by pretending to protect the poor from usury rates220
In chapter 53 it has been described that micro-entrepreneurs due to their smaller
capital endowment have even better investment opportunities than big business The
extend to which this is true has not yet been answered An indication is the high
repayment rate observed within MFIs around the globe If their customers capital yield
did not exceed the charged interest rate how would they be able to repay According to
Gibbons and Meehan customers of MFIs can generally generate returns of more than
100 percent on their invested capital221 and ldquo[r]esearch in India Kenya and the
Philippines found that the average annual return on investments in microenterprises
215 See Kate and Roeun (2004)216 See Hodson (2001) min 1100217 See Morduch (1999a) p 1594218 See Prisma (2002) p 1219 See Schreiner (1997) p 60 Khandker (1998) p 106 220 See Gross and de Silva (2002) p 32 Jansson and Wenner (1997) p 36 et sqq Campion (2002) p 59221 See Gibbons and Meehan (1999) p 131
44
ranged from 117 to 847 percentrdquo222 Schmidt and Tschach found the marginal
productivity of capital to be as high as 1000 percent for the smallest loans provided by
the Bolivian MFI Caja Los Andes223 These findings are confirmed by the observation
of Rosenberg who found while working as a microfinance consultant for ten years he
never heard of a single MFI having problems to attract clients because interest rates
were too high224
To get a better understanding of the investment opportunities of low income people in
developing countries a typical example on how MFI clients invest their loans is as
follows
Zobair is working as a rickshaw puller in Bangladesh Like most of his colleagues he
does not own the rickshaw he is riding Therefore he has to pay a daily rent of about
$030 to the owner Since his average income of approximately $15 per day is hardly
enough to feed his family he is not able to save the $100 necessary to buy a rickshaw
on his own 225 If he could do so through obtaining a loan his income would increase by
$030 every day because he would not have to pay the rent for the rickshaw anymore
Assuming an average of six working days per week 226 and a life span of the rickshaw
of 5 years his internal rate of return would equal 15324 percent annually227
Consequently any interest rate charged by a MFI would be advantageous to him as long
as it would not exceed 15324 percent228
63 Should the Interest Rate be subsidized anyway
Despite the fact that numerous micro-entrepreneurs are able to generate tremendous
returns on their investment obviously not all are able to use capital in such a productive
way and therefore can not afford microcredit at commercial rates In order to reach
these people as well many MFIs continue to use donor money in order to keep their
interest rates low But even if the problems related to subsidized credit as described in
222 See Helms and Reille (2004) p 3223 See Schmidt and Tschach (2001) p 6224 See Rosenberg (2002) p 10225 This examples draws on observations made by the author in Dhaka (Bangladesh) during 2003226 Obviously extended holidays are not a viable option in this surrounding 227 Own calculation See Appendix 6228 This result is only valid if the loan is repaid in daily instalments For a weekly repayment schedule the interest rate charged by the MFI must not exceed 15119 percent in order to still be beneficial for Zobair
45
chapter 23 do not arise it might still not be the most effective tool to help poor people
as will be illustrated in the following example
A MFI faces two groups of potential clients one with businesses able to generate a
return of 125 percent on borrowed capital and another with a possible returns of 50
percent Assuming budget costs according to equation (2) the institution needs to
charge an interest rate of 875 percent and therefore only serves the former group
Supposed each group consists of 50 members demanding $100 loans the net gains to
society (NGS) could be calculated as follows
(3) NGS = 50 times ($125 ndash $875) = $1875
These gains would be due to the investments of the more profitable group which were
made possible through the loans provided by the MFI The less profitable group would
not borrow since their expected returns are not sufficient to pay for the interest If the
interest rate would be lowered to 30 percent both groups would be able to generate net
gains and therefore borrow from the MFI In order to provide loans at this rate the
institution would need to raise additional capital from non commercial sources The
NGS would be calculated as follows
(4) NGS = 50 times ($125 - $30) + 50 times ($50 - $30) + 100 times ($30 - $875) = 0
While the first terms represent the net gains to the respective groups the last describes
the costs incurred in providing the loans At a rate of 30 percent each loan would need
to be subsidized with $575 Hence the NGS actually fall after the introduction of the
subsidized loan This is due to the fact that the less profitable group is encouraged to
invest in relatively unproductive businesses In addition future growth of the MFI could
be jeopardized due to scarce donor money which is needed to finance the interest rate
subsidy Therefore it seems more advisable to continue to charge a rate of 875 percent
and spend the money used for subsidization on other programs such as health care or
education229
229 In Appendix 7 it will be shown that this result generally holds
46
7 Empirical verification
71 Setting up a Sample
To see if the findings of the previous chapters hold the effects which interest rates
charged by MFIs have on their performance will be analyzed in the following Up to
now such a study does not exist mainly because of a lack of adequate data Most MFIs
do not provide accurate information about the annual effective interest rate they charge
and therefore make an evaluation difficult
In 2002 Rosenberg distinguished eight different categories on how microcredit interest
rates are quoted230 These categories differ in several ways On the contrary to
traditional banks for example it is common for MFIs to state interest rates calculated on
a ldquoflatrdquo balance rather than on a declining one This means that the total loan amount is
used to determine the interest rate ignoring installments paid by the borrowers normally
on a weekly or monthly basis In addition many MFIs charge a certain upfront fee prior
to the loan disbursement require compulsory savings at a lower rate or state their
interest rate for semi annual terms only On the one hand this is done to provide
numbers that are more meaningful to MFI customers who often lack the necessary math
skills to deal with compound interest on the other hand it is done to circumvent interest
rate ceilings imposed by the government231 Another problem is that most MFIs offer
different loan products without itemizing their respective shares to their total loan
portfolio As a result it is not possible to calculate a weighted average even if the rate
stated by the respective MFI could be transformed into an effective interest rate
Usually the portfolio yield is used as a proxy in order to make statements about the
interest rate charged by a certain MFI232 It is generally ldquocalculated by dividing total
cash financial revenue (all income generated by the loan portfolio but not accrued
interest) by the period average gross portfoliordquo233 The advantage of this method is that
even the hidden costs are considered Nevertheless it also has a severe shortcoming by
not taking late or defaulted payments into account Therefore the portfolio yield does
230 See Rosenberg (2002) p 5231 MicroRate (2002) p 8232 See MicroRate (nd)233 MicroRate and IADB (2003) p 39
47
not allow to draw conclusions regarding the correlation between the interest rate
charged by a MFI and its PAR
72 Examining the Sample
Through the appearance of rating agencies specialized in the microfinance sector more
adequate information has become available in recent years While MicroRate only
publishes the portfolio yield of rated MFIs M-Cril Microfinanza Microserve and
Planet Rating actually provide information about the annual effective interest rate for at
least some of the MFIs they analyze Although it is labelled differently from all of the
four institutions234 the term describes what is ldquothe highest income or yield that an
organisation can earn from its portfolio based on the terms of its loansrdquo235
Currently236 reports of 39 different MFIs from 20 countries providing accurate
information about the effective annual interest rate are available to the public This
sample should be used to verify the findings of the previous chapters237 Since a
comparison is made between the performances of MFIs based in different countries and
the ratings have been carried out in different years several adjustments are necessary
First the inflation of the respective country and the respective year(s)238 has to be taken
into account in order to only compare the real rates239 In addition the average
outstanding loan amount per borrower is divided by the respective countryrsquos GDP per
capita Since it can be assumed that ldquoonly the poorer households will be willing to take
the smallest loansrdquo240 this number can be used as a proxy for the poverty level
Although the sample size is far to small to represent the microfinance sector as a whole
and the results are statistically not significant the findings can still be used to underline
the theoretical conclusions drawn in the previous chapters In figure 5 the connection
234 M-Cril uses the name ldquoannual percentage raterdquo See eg M-Cril (2004a) p 25 Microfinanza uses the name ldquoexpected portfolio yieldrdquo See eg Microfinanza (2002c) p 25 Planet Rating uses the name ldquoannual effective interest raterdquo See eg Planet Rating (2004d) p 1 Microserve uses the name ldquotheoretical yieldrdquo See Microserve (2003) p 62235 See M-Cril (2004a) p 25236 As of September 28th 2004237 See Appendix 8 For exchange rates see FXTOP (2004)238 Where necessary a weighted average of the annual inflation rate was used See Appendix 9239 This is done through the following formula ir = (I ndash F) (1 + F100) While ir represents the real annual effective interest rate F represents the inflation rate 240 Morduch (1998) p 1572
48
between the average loan size and the transaction costs as a share of the average loan
portfolio is illustrated
Figure 5 Loan Size vs Interest Rate241
Source Own diagram
000
1000
2000
3000
4000
5000
6000
7000
8000
9000
10000
0 100 200 300 400 500 600
Loan Size
Inte
res
t R
ate
It can be seen that the interest rate is negative correlated to the loans size This can be
explained by the relative higher transaction cost for smaller loans as described in
chapter 52 In order to cover their costs MFIs serving the low end market need to
charge higher rates to their customers than those organizations serving the better off
poor Obviously there are several assumptions to this general finding Especially
striking are the two MFIs with an average loan size of approximately five times their
countries GDP per capita which still high interest rates This occurrence can be
explained by taking a closer look to the respective organizations One was established
less than two years prior to its rating and therefore still bears a lot of start up costs242
241 The equation for the regression line reads as follows Y = -00219X + 365 The correlation coefficient is 014242 See Microfinanza (2002b) p 1
49
the other managed to stay profitable while it almost quadrupled its loan portfolio in the
last two years243
Figure 6 Interest Rate vs PAR244
Source Own diagram
0
5
10
15
20
25
30
35
0 20 40 60 80 100 120
Interest Rate
PA
R
In Figure 6 the crucial correlation between the interest rates charged by a MFIs and its
PAR245 is examined According to the given sample the view of traditional banks and
investors that a higher interest rate leads to a higher default rate does not hold
Obviously one has to avoid to draw the opposite conclusion namely that a high interest
rates decreases the PAR The connection illustrated in figure 6 has to be interpreted as
follows Since high interest rates are related to small loans the low PAR for MFIs
charging high interest rates can actually be explained by the tremendous profitability of
small size investments Despite the high rates their customers are even more likely to
repay
243 See Planet Rating (2003b)244 The equation for the regression line reads as follows Y = -00768X + 68433 The correlation coefficient is 0235245 M-Cril only publishes the PAR for overdues greater than 60 days Therefore these ratios are used as a proxy for the industry standard of 30 days for some Asian MFIs
50
Finally it has to be examined if charging high interest rates actually enables MFI to
generate higher returns Although it can be expected that the combination of a low PAR
and a high interest rate leads to a high profitability it still has to be checked if this is not
outdone by soaring transaction costs Figure 7 illustrates the correlation between the
interest rate charged by a MFI and its financial self-sufficiency (FSS) The latter is the
ldquo[r]atio of total income to total adjusted expenses for the year Adjustments are made
for subsidised cost of funds (relative to market interest rate) equity (with respect to
inflation) and in-kind donationsrdquo246 It can be seen that the regression line actually does
indicate a positive correlation between the interest rate and the profitability of a MFI
Figure 7 Interest Rate vs FSS247
Source Own diagram248
0
20
40
60
80
100
120
140
160
180
0 20 40 60 80 100
Interest Rate
FS
S
246 M-Cril (2004a) p 53247 The equation for the regression line reads as follows Y = 02839X + 8901 The correlation coefficient is 0174248 Since the interest rate the customers of the MFI Foccas have to pay includes fees which are not passed on to the institution its interest rate in this diagram is set at 723 percent instead of the 10715 percent used for figure 6 See Planet Rating (2003b) p 1
51
This result does not necessarily disprove the findings of Stiglitz and Weiss since it can
be argued that MFIs simply do no increase their interest rates to the point where they
would maximize their expected returns But if this would be true why do MFIs not
charge higher rates of interest given the demand described in chapter 41 and 43 In
mature markets competition normally ensures prices not to exceed a certain level but
since many MFIs still operate in a ldquosellerrsquos marketrdquo249 this can not explain the findings
as described in figure 7 Therefore it has to be assumed that a combination of the
unwillingness of many microfinance practitioners to burden their customers with high
interest rates and the plain disbelief of traditional investors that micro-entrepreneurs can
bear those rates is responsible for this occurrence
249 See MicroRate and IADB (2003) p 9
52
8 Conclusions
It has been shown that MFIs are not only contributing significantly to the development
of the financial sector in their respective countries but also that they play an important
role to eradicate poverty by providing much needed capital to low income people which
are able to generate tremendous returns on their investments
The fact that the demand for microcredit is not met is mainly due to the view of most
for profit investors and traditional banks that offering financial services to poor people
can not be done profitable Because of this conviction they hardly invest in the
microfinance sector This does not have to be the case according to the findings of this
paper Although faced with relatively high transaction costs MFIs are able to charge
interest rates at levels that fully recover their costs Elizabeth Rhynersquos claim ldquothat the
most financially viable programs differed from their less viable peers in their
willingness to set interest rates at levels that would fully recover costsrdquo250 is backed by
the findings of this paper that high profitability is correlated to high interest rates
Theoretical models based on the findings of Stiglitz and Weiss can not be used as a
justification to ration credit for the microfinance sector since the interest rate that
maximizes profits to the lender can be assumed to exceed 100 percent for many MFIs
Nevertheless this rate is hardly charged although it has been shown that it can be done
The Mexican MFI Compartamos for example manages to keep its PAR as low as one
percent while charging an effective interest rate of more than 100 percent to
approximately 160000 clients251 In combination with this case the conclusions drawn
from examining the sample of MFIs in chapter 7 the claim of Hulme and Mosley as
stated in the introduction can be considered as wrong MFIs are in fact able to finance
rapid growth stay profitable by charging corresponding interest rates and still have a
significantly positive impact on the poverty level of their clients In the long run gains
in efficiency economies of scale a slowdown in growth and competition will ensure
interest rates drop as it has already been the case in countries like Bangladesh and parts
of Bolivia252
250 See Rhyne (1998) p 7251 See MicroRate (2004)252 See Microrate and IADB (2003) p 9
53
According to a MicroRate survey many MFIs are more profitable than Citibank and also
generate a higher return on investment than commercial banks in their respective
countries253 Investments companies like IMI or Blue Orchard will soon be able to
present a meaningful track record of their microfinance investments to potential
investors Ultimately the capital markets can not ignore the facts proving that it actually
can be profitable to invest in the microfinance sector but in order to raise money
quickly microfinance practitioners will have to continue to intensively promote their
cause not only to for profit investors but also to donors and multilateral agencies like
the World Bank
253 See MicroRate (2002) p 10
54
Appendix
Appendix 1 Average loan balance
Source Data is available through the Mix Market (2004)
Organization
Loan Portfolio 2002 (US$)
Loan Portfolio 2003 (US$)
Number of borrowers 2002
Number of Borrowers 2003
2CM 1263602 1400438 3622 3708ACF 955503 1611401 285 370ACLEDA 26846703 39391301 82598 98905ACME 1460881 1714844 4283 4600ADIM 369065 407798 1122 1395AFK 933306 1706577 250 467AgroInvest 4684249 9697411 5208 9629Al Amana 15593277 28677666 78114 101610AMSSFMC 612167 1040756 6183 6886AREGAK 3285273 3987011 11841 14377AVFS 214331 269819 1883 2866BancoSol 83629049 91175000 42290 56707BESA 10563980 15114430 4488 5061BPR AK 613362 876130 1730 3879BPR BMMS 133949 237946 1755 1779BRI 1344006170 1720072773 3056103 3100358BZMF 1592508 1922097 1250 1331CBDIBA 216587 242465 5764 2877CCA 2146235 4582302 4070 6585CCCP 447534 851678 6265 9450CEP 3795400 5261957 32291 42132CERUDEB 25093643 34873228 34490 44796CMEDFI 227674 250244 3467 3781CMM - Bogota 4836000 8135968 15635 22038CMMB 34880 56964 42 190COAC Maquita Cushunchic
870084 1855718 6603 7732
CODES 280843 263091 60 60CODESARROLLO 6714007 12935951 4391 6896Constanta 2943822 3536047 16134 18588COOPEC CAMEC MN
7152 29821 92 77
Crear - Tacna 3891116 4636094 3671 4948CREDIT 642094 81838 7532 8097CRYSTAL FUND 366456 421403 1379 1061DBACD 3473701 3876526 12812 19606ECLOF - ECU 1154292 728312 860 416ECLOF - MAL 441734 407227 1118 1500EKI 11833244 19245751 8999 13323EMT 4481589 5765281 84781 92173ESED 8579460 6834742 22790 20035
55
Eshet 185741 462569 3308 6540Faulu - KEN 9027332 7206344 17463 15000FDL 12503027 16545332 21306 25106FIE 35818903 41597315 26468 33100FINADEV 5512586 9770323 12775 14709Finance Salone 211312 434298 2225 7159Finca - TAN 1293430 1854834 20648 27499Finca - UGA 2451703 2798869 35610 36912FINCORP 4761288 10236896 941 858FJN 5473563 8037662 8107 11133FMFB 308158 1188896 713 3558FMM -Bucaramanga
6355518 10227000 25814 42464
FODEM 739181 939824 1909 2501FundaciESPOIR
898561 1883446 5911 9464
FUNDESER 798907 1373113 4072 5065Gasha 323748 413742 5504 6423GGLS Save the Children
64235 137957 1291 2362
GK 56986 166971 951 2718HKL 1363365 1420357 6648 5372HOPE 402799 603488 1098 1562IAMD 42132 56550 2780 2772IDECE 21312 39453 150 232IDF 2031944 2626382 31003 36580IMCEC - Dakar 254759 688449 1018 2983IMCEC - Thies 199799 571122 1164 1261
ISSIA 221615 246792 1409 1698JMCC 1962355 2609723 1471 2333KAFC 21710638 29241051 24850 32097KAMURJ 1003935 1411258 5559 5691Kashf 2355965 6271498 29655 59389KMBI 721409 1626666 11973 27266KPSCA 109299 128063 362 794K-Rep 14490447 20699963 38739 45379KSCS 18978 43740 140 297KVT 44075 70621 241 373LAPO 922478 1194633 18740 19139MEC ADEFAP 27788 69248 198 202MEC Bosangani 14357 31086 364 540MEDF 104113 136257 1278 1184Meklit 233170 252232 2084 3577Metemamen 22123 57778 943 1501MFSC 109261 171090 511 687MIKRA 2951028 5008784 4145 6095MIKROFIN 9560502 18380263 5633 7426Miselini 737387 1026639 10182 11431MRFC 11475440 9133130 163000 180000Mushuc Runa 2089076 5418325 3139 6232Nirdhan 2886777 3016171 29589 27457OCSSC 5245186 7658413 42157 6215o
56
Otiv Diana 95992 638422 229 1073Otiv Sambava 188094 437974 2002 1442Otiv Tana 66465 673175 337 1269Partner 9976448 15321304 7139 11935PCA 6878257 6885926 63113 58147PEACE 420746 627295 4192 5428PEDF 164399 254233 2357 3340Piyeli 809447 1206656 8674 4745PRESTANIC 2827502 3540367 1477 2605PRIDE - MAL 991888 854631 5376 5601PRIZMA 3881581 6838978 8112 10968ProMujer -Nicaragua
1006871 1424437 10436 13047
PTF 891566 1068881 8500 9070RBST 818594 1058115 619 723REMECU 1381705 1483471 10330 13996
RUSCA 60887 100820 454 994
SCSCS 89423 157472 873 1007SFPI 709497 903556 7728 9552Sidama 934260 1011798 10267 11346SPBD 117807 186029 647 1740Sunlink 819138 1056823 3401 3833Sunrise 5412366 8782868 4560 7256TEBA 108032426 176300111 163021 157776TIAVO 281978 838905 2049 459TPC 1140429 2267148 22869 31668TSPI 4650989 5383755 49649 75617UNICECAM 3442843 5943804 16039 19031Wasasa 230657 274908 2850 3728Wisdom 1306066 1404463 10524 12054XacBank 4910098 9829503 11063 18610Zakoura 15907288 12444768 103720 118980
Appendix 2 Portfolio at Risk
Source Data is available through the Mix Market (2004)
Organization PAR 2002ABA 202ACEP 464ACLEDA 175ACODEP 452ACSI 209Al Amana 010Apoyo Integral
483
AREGAK 692Banco Solidario
500
BancoSol 660BASIX 1296
57
BRI 437BURO Tangail
350
CEP 200CERUDEB 103CMAC -Sullana
567
CMM -Bogota
176
Compartamos 111Constanta 304Credi Fe 212CREDIAMIGO 409DBACD 010EBS 847EMT 010ESED 1311FADES 2311Faulu - KEN 246Faulu - UGA 096FDL 212FECECAM 428FED 436FIE 598FINADEV 021Finamerica 1133Finca - TAN 000Finca - UGA 297FMM -Bucaramanga
094
FMM -Popayan
088
FONDEP 013FORA 064Genesis Empresarial
1197
IDF 017KAFC 106Kashf 000KMBI 128K-Rep 229MiBanco 309MRFC 1742Nirdhan 373
PADME 079PAMECAS 284PCA 379PRIDE - TAN 018ProMujer -Nicaragua
073
RCPB 600REMECU 157SHARE 000
58
Soluci 182Spandana 014TEBA 106TSPI 355UMU 125UNICECAM 405Urwego 290UWFT 363WAGES 736WWB -Medellin
235
XacBank 061Zakoura 095
Appendix 3 Transaction Costs
Source Data is available through the Mix Market (2004)
OrganizationTransaction Costs
Acci Rural 1154ACEP 858ACLEDA 2430ACODEP 2920ACSI 924Al Amana 2576AREGAK 2856AssEF 1919Banco Solidario
1826
BancoSol 1210BASIX 1317BRI 1353BURO Tangail
2053
CEP 1759CERUDEB 5109CMAC -Sullana
1784
CMM -Bogota
2089
Compartamos 3341Constanta 4597Credi Fe 1978CREDIAMIGO 2525DBACD 1742EBS 2377EMT 3220ESED 1343FADES 1673FAMA 2436
59
Faulu - KEN 2253Faulu - UGA 4962FDL 1726FECECAM 2587FED 4083FIE 1125Finamerica 1563Finca - TAN 10753Finca - UGA 9096FMM -Bucaramanga
1925
FMM -Popayan
1112
FONDEP 5477FORA 3481Genesis Empresarial
1626
IDF 1695
K-Rep 1909LAPO 3511MiBanco 2456Nirdhan 1325NWTF 3109OCSSC 1155PADME 1131PAMECAS 1705PCA 1670PRIDE - TAN 4273ProMujer -Nicaragua
5078
RCPB 2059SHARE 2308Sidama 2662Soluci 2906Spandana 641TEBA 1213TSPI 3898UMU 4023UNICECAM 10120Urwego 7437Wisdom 1906WWB -Medellin
1703
XacBank 4144Zakoura 1881
60
Appendix 4 Portfolio Growth
Source Data is available through the Mix Market (2004)
Organization
Total Loan Portfolio in 2000
Total Loan Portfolio in 2002
ACODEP 5889394 7258487Adelante 4327 88594ADRI 1514681 2591240AgroCapital 11100088 12018280Banco Solidario 39632165 103420000
BancoSol 78031172 83629049CMAC - Sullana 14596365 28055720
COAC Maquita Cushunchic
348443 870084
CODESARROLLO 1374801 6714007Compartamos 10804279 41825248Crear - Tacna 3778816 3891116
Credi Fe 781616 9393936ECLOF - ECU 179247 1154292
FADES 11948814 15501578FAMA 6201411 8835134FIE 22524645 35818903Finamerica 16575104 16097113FINCOMUN 3278938 5696556FMM - Popayan 6241821 12212867
FONDECO 3456625 5101801Genesis Empresarial
11154234 17746288
MiBanco 36964072 95873333Mushuc Runa 90737 2089076ProMujer -Nicaragua
426541 1006871
WWB - Medellin 2891207 4580998
Appendix 5 Portfolio vs Equity
Source Data is available through the Mix Market (2004)
OrganizationLoan Portfolio Equity
ACODEP 7258487 1921447Adelante 88594 72973
ADRI 2591240 781477AgroCapital 12018280 10766101Banco Solidario 103420000 12961000BancoSol 83629049 15299415CMAC - Sullana 28055720 6210291
61
COAC Maquita Cushunchic
870084 260331
CODESARROLLO 6714007 1285103
Compartamos 41825248 18350446
Crear - Tacna 3891116 1016912Credi Fe 9393936 863848ECLOF - ECU 1154292 459226FADES 15501578 4138972FAMA 8835134 6377663FIE 35818903 5360484Finamerica 16097113 3817960FINCOMUN 5696556 1042241FMM - Popayan 12212867 8510494FONDECO 5101801 1658075Genesis Empresarial
17746288 4765816
MiBanco 95873333 24261889Mushuc Runa 2089076 434311ProMujer -Nicaragua
1006871 1196015
WWB - Medellin 4580998 2213249
Appendix 6 Internal Rate of Return
Source Excel (German Version) calculation based on own data
A B C D E F
1 Date Cash Flow
Interest Rate Internal Rate of Return Balance Interest Principal
23 01012004 -100 15324 100 025489547 0045104534 02012004 03 999548955 025489547 0045104535 03012004 03 99909676 02547805 004521956 04012004 03 998643412 025466524 0045334767 05012004 03 998188909 025454968 0045450328 06012004 03 997733247 025443383 0045566179 08012004 03 999826083 050928361 -0209283610 09012004 03 999374595 025485114 004514886
hellip hellip hellip hellip hellip helliphellip hellip hellip hellip hellip hellip helliphellip hellip hellip hellip hellip hellip hellip1562 23122008 03 177951388 000528711 0294712891563 25122008 03 148859724 000908336 0290916641564 26122008 03 119239161 000379437 0296205631565 27122008 03 089543096 000303935 0296960651566 28122008 03 059771337 000228241 0297717591567 29122008 03 029923692 000152354 0298476461568 30122008 03 -3434E-07 000076274 029923726
62
The formula in the square C3 reads as follows
ldquoXINTZINSFUSS(B3B1568A3A156815)rdquo
Appendix 7 Subsidized Interest Rates and the Net Gains to Society
SourceOwn calculations
For simplicity only two groups of potential clients are distinguished This is possible
since using a continuum of potential clients would lead to the same results In addition it
is assumed that the amount of every loan (L) is equal and that all clients invest the
whole loan amount Group H consist of NH potential clients with a rate of return (rH) on
their invested capital higher than the cost recovering interest rate charged by the MFI
(iC) Group L consists of NL potential clients with a rate of return (rL) on their invested
capital lower than iC If the MFI charges iC the NGS can be calculated as follows
NGSC = NH times (rH - iC) times L
Since rH is bigger than iH (rH gt iC) according to the definition presented above the term
NGSH must be positive as long as NH does not equal zero If the MFI introduces a
subsidised interest rate (iS) lower than rL the NGS can be calculated as follows
(1) NGSS = NH times (rH - iS) times L + NLtimes (rL - iS) times L + (NH + NL) times (iS - iC) times L
(2) NGSS = NH times (rH- iC) times L + NLtimes (rL - iC) times L
The term (NH + NL) times (iS - iC) times L describes the amount of money that is needed in order
to subsidize the interest rate to the level iS By setting up an inequation it can be
examined under which conditions the NGSS are bigger than the NGSC
(3) NGSS gt NGSC
(4) NH times (rH- iC) times L + NLtimes (rL - iC) times L gt NH times (rH - iC) times L
(5) NLtimes (rL - iC) times L gt 0
(6) rL gt iC
63
So the NGSS could only be bigger than the NGSC if equation 6 holds This is
impossible since it violated the definitions presented above Therefore the introduction
of subsidized interest rates is always accompanied with a drop in the NGS
Appendix 8 Interest Rate vs Loan Size vs FSS vs PAR
Source Data is available through the Mix Market (2004)
Organization Country
Real Interest Rate
Loan Size (divided by the GDP per Capita) FSS PAR
BTFFKyrgyz Republic 3803 48260 1487 698
BesaFoundation Albania 2184 16076 684 260RFF Albania 1198 5783 4764 277PSHM Albania 2194 000 5758 198Mi-Bospo Bosnia 2974 5499 1261 020Prizma Bosnia 3474 3569 103 064Agroinvest Serbia 2201 4401 875 020KCLF Kazakhstan 5713 1713 865 090
Foccas Uganda10716 (723) 1550 584 29
ACEP Senegal 3280 20941 1643 1Padme Benin 2715 13575 1667 08Papme Benin 3086 53659 1405 24Vital Finance Benin 2676 9394 1015 17Finadev Benin 1738 14850 1024 21ABA Egypt 2579 1613 1168 88ASBA Egypt 2597 1702 1252 68DBACD Egypt 2490 1643 1073 0SBACD Egypt 2500 1734 982 67AMSSF Morocco 6926 787 1306 04Fondep Morocco 5199 650 889 071Zakoura Morocco 4414 900 98 006ENDA Tunisia 4008 1351 110 102BSFL India 1954 3269 856 99Share India 3426 1440 951 0Spandana India 2942 1618 1367 026SWC India 1864 2626 42 3036SKS India 2248 1912 578 0Grama Vidiya India 3176 1221 76 18Sneha India 3451 1433 933 0Buro Bangladesh 3206 1882 1093 17Upap Pakistan 2073 8183 757 03Seeds Sri Lanka 1004 1088 605 287EMT Cambodia 4324 1676 1016 01TPC Cambodia 4470 2035 832 27
64
WTF Phillippines 5816 1095 941 74TSKI Phillippines 5794 777 96 79Cacja Ecuador 862 6189 9460 897ACME Haiti 6043 6934 11685 450Grupo Cama Mexico 8961 267 10717 288
65
Appendix 9 Inflation vs GDP per Capita
Source IMF (2004)
Country Subject Description Units Scale 2000 2001 2002 2003 2004
Albania Gross domestic product per capita current prices US dollars Units 1083988 1238206 1396172 1757778 2229712
Albania Inflation annual percent change Percent 00 31 52 24 34
Bangladesh Gross domestic product per capita current prices US dollars Units 329310 327980 344494 369495 393717
Bangladesh Inflation annual percent change Percent 22 15 38 54 64
Benin Gross domestic product per capita current prices US dollars Units 361340 368213 405951 494725 560129
Benin Inflation annual percent change Percent 42 40 24 15 26
Bosnia and Herzegovina Gross domestic product per capita current prices US dollars Units 1255837 1321429 1466090 1807392 2070508
Bosnia and Herzegovina Inflation annual percent change Percent 50 32 03 02 09
Cambodia Gross domestic product per capita current prices US dollars Units 276413 280352 296577 305940 321247
Cambodia Inflation annual percent change Percent -08 02 33 12 20
Ecuador Gross domestic product per capita current prices US dollars Units 1227711 1590267 1804362 1957183 2082156
Ecuador Inflation annual percent change Percent -77 377 126 79 32
Egypt Gross domestic product per capita current prices US dollars Units 1550982 1461431 1278462 1188060 1083158
Egypt Inflation annual percent change Percent 28 24 24 32 52
India Gross domestic product per capita current prices US dollars Units 454206 458849 472915 542554 602625
India Inflation annual percent change Percent 40 38 43 38 47
Kazakhstan Gross domestic product per capita current prices US dollars Units 1236159 1490946 1655148 2000598 2579554
Kazakhstan Inflation annual percent change Percent 134 83 59 64 68
Kyrgyz Republic Gross domestic product per capita current prices US dollars Units 278256 306130 321079 349632 380637
Kyrgyz Republic Inflation annual percent change Percent 187 69 21 31 45
66
Mexico Gross domestic product per capita current prices US dollars Units 5957486 6274468 6425203 6111754 6377064
Mexico Inflation annual percent change Percent 95 64 50 45 44
Morocco Gross domestic product per capita current prices US dollars Units 1161302 1162154 1199584 1432725 1541041
Morocco Inflation annual percent change Percent 19 06 28 12 20
Pakistan Gross domestic product per capita current prices US dollars Units 437381 400356 440471 492913 538120
Pakistan Inflation annual percent change Percent 44 31 32 29 46
Philippines Gross domestic product per capita current prices US dollars Units 979423 900225 950707 963765 1018710
Philippines Inflation annual percent change Percent 43 61 31 30 54
Russia Inflation annual percent change Percent 208 215 158 137 103
Senegal Gross domestic product per capita current prices US dollars Units 478704 474460 507408 634171 714622
Senegal Inflation annual percent change Percent 09 30 23 -00 08
Serbia and Montenegro Gross domestic product per capita current prices US dollars Units 1031263 1389384 1882036 2491799 2795805
Serbia and Montenegro Inflation annual percent change Percent 699 911 212 113 79
Sri Lanka Gross domestic product per capita current prices US dollars Units 846811 796025 828256 904330 982466
Sri Lanka Inflation annual percent change Percent 62 142 96 63 64
Tunisia Gross domestic product per capita current prices US dollars Units 2034360 2065140 2149421 2534823 2881273
Tunisia Inflation annual percent change Percent 30 19 28 28 34
Uganda Gross domestic product per capita current prices US dollars Units 293404 249682 279587 280802 287204
Uganda Inflation annual percent change Percent 45 -20 57 51 35
67
References
Akerlof George A The Market for ldquoLemonsrdquo Qualitative Uncertainty and the Market Mechanism in Quarterly Journal of Economics Vol 84 (1970) pp 488-500
Amin Ruhul et al Integration of an Essential Service Package (ESP) in Child and Reproductive Health and Family Planning with a Micro-Credit Program for poor Women Experience from a Pilot Project in Rural Bangladesh in World Development Vol 29 (2001) No 9 pp 1611-1621
Bester Helmut Screening vs Rationing in Credit Markets with Imperfect Information in The American Economic Review Vol 75 (1985) No 4 pp 850855
Borst Dietmar Microfinance ndash Theoretische Grundlagen fuumlr den Einsatz sowie die Abschaumltzung des Potentials anhand einer Datenbankuntersuchung zur Verwundbarkeit der laumlndlichen Bevoumllkerung in Vietnam unpublished diploma thesis Karlsruhe 2004
BRAC Annual Report 2002 Dhaka 2003
Busch Alexander Kort Katharina Die Peanuts-Banker und ihre Kunden in Handelsblatt Nr 150 published August 5th 2004 p 8
Campion Anita Challenges to Microfinance Commercialization in Journal of Microfinance Vol 4 (1999) No 2 pp 57-65
Chu Michael Key Issues of Development Finance Somerville (MA) 1998
Dornbusch Ruumldiger Fischer Stanley Makrooumlkonomie Oldenburg 1995
Dunn Seth Flavin Christopher Moving the Climate Change Agenda Forward in State of the World New York London 2002 pp 24-50
Farrington Todd Efficiency in Microfinance Institutions in The MicroBanking Bulletin Issue No 4 pp 18-24
Gardner Gary The Challenge for Johannesburg Creating a More Secure World in State of the World New York London 2002 pp 3-23
Ghatak Subrata On Interregional Variations in Rural Interest Rates in Journal of Developing Areas Issue 18 pp 21-34
Gibbons David Serving the Poorest Sustainably in The MicroBanking Bulletin Issue No 5 (2000) pp 13-16
Gibbons David Meehan Jennifer W The Microcredit Summitrsquos Challenge WorkingToward Institutional Financial Self-Sufficiency While Maintaining a Commitment to Serving the Poorest Families in Journal of Microfinance Vol 1 (1999) No 1 pp 131-192
68
Goodwin-Groen Ruth Do Asian MFIs Access Funds from Commercial Banks inThe MicroBanking Bulletin Issue No 3 pp 8-10
Grameen Bank (ed) Grameen Generalized System Dhaka 2003
Gross Alexandra de Silva Samantha Social Fund Support of Microfinance A Reviewof Implementation Experience The World Bank Social Protection Discussion Paper No 0215 Washington DC 2002
Hashemi Syed M Schuler Sidney R Sustainable Banking with the Poor A Case Study of Grameen Bank Dhaka 1997
Helms Brigit Reille Xavier Interest Rate Ceilings and Microfinance The story so farConsultative Group to assist the Poor Occasional Paper No 9 September 2004 Washington DC 2004
Hoff Karla Stiglitz Joseph E Introduction Imperfect Information and Rural Credit Markets-Puzzles and Policy Perspectives in The World Bank Economic Review Vol 4 (1990) No 3 pp 235-250
Holcombe Susan Managing to Empower The Grameen Bankrsquos Experience of Poverty Allevation Dhaka 1995
Hulme David Mosley Paul Finance against Poverty London 1996
Jalvaani (ed) Flush with loans Micro credit for rural sanitation Vol 2 (1999) No 2 pp 1-2
Khandker Shahidur R Fighting Poverty with Microcredit Experience in Bangladesh Oxford et al 1998
Khandker Shahidur R Khalily Baqui Khan Zahed Grameen Bank Performance andSustainability The World Bank Discussion Paper No 306 Washington DC 1995
Lipsey Rechard G An Introduction to Positive Economics 5th edition London 1979
Littlefield Elizabeth Morduch Jonathan Hashemi Syed M Is Microfinance an Effective Strategy to Reach the Millennium Development Goals Consultative Group to Assist the Poorest Focus Note No 24 Washington DC 2003
Martinot Eric Cabraal Anil World Bank Solar Home Systems Projects Experience and Lessons Learned 1993-2000 in Renewable Energy Oxford 2000 pp 1-8
M-Cril Microfinance Review 2003 revised February 2004 Gurgaon 2004a
Mezzera Jaime Microcredit in Brazil The Gap Between Supply and Demand in The MicroBanking Bulletin Issue No 8 (2000) pp 22-24
The MicroBanking Bulletin (ed) Note to the Reader Vol 1 (1997) Issue No 1 pp 5-8
69
The MicroBanking Bulletin (ed) An Introduction to the Peer Groups and Tables Issue No 9 (2003) pp 53-60
MicroRate IADB Performance Indicators for Microfinance Institutions Technical Guide 3rd edition Washington DC 2003
MkNelly Barbara Dunford Christopher Impact of Credit with Education on Mothers and Their Young Childrenrsquos Nutrition Lower Pra Rural Bank Credit with Education Program in Ghana Freedom from Hunger Research Paper No 4 Davis (CA) 1998
MkNelly Barbara Dunford Christopher Impact of Credit with Education on Mothers and Their Young Childrenrsquos Nutrition CRECER Credit with Education Program in Bolivia Freedom from Hunger Research Paper No 5 Davis (CA) 1999
Morduch Jonathan The Microfinance Promise in Journal of Economic Literature Vol 37 (1999b) No 4 pp 1569-1614
Neus Werner Einfuumlhrung in die Betriebswirtschaftslehre Tuumlbingen 1998
Otero Maria Bringing Development Back into Microfinance Journal of Microfinance Vol 1 (1999) No 1 pp 8-19
Panjaitan-Drioadisuryo Rosintan D M Cloud Kathleen Gender self-employment and microcredit programs An Indonesian case study in The Quarterly Review of Economics and Finance Vol 39 (1999) pp 769ndash779
Perkins Dwight H et al Economics of Development 5th edition New York London 2001
Pitt Mark M Khandker Shahidur R Credit Programs for the Poor and the Health Status of Children in Rural Bangladesh in International Economic Review Vol 44 (2003) No 1 pp 87-118
Raiffeisen Friedrich W The Credit Unions 8th edition Neuwied 1966
Rhyne Elizabeth The Yin and Yang of Microfinance Reaching the Poor and Sustainability in The MicroBanking Bulletin Issue No 2 (1998) pp 6-9
Richardson David C Unorthodox Microfinance The Seven Doctrines of Success in The MicroBanking Bulletin Issue No 4 (2000) pp 3-7
Robinson Marguerite S The Microfinance Revolution Sustainable Finance for the Poor Washington DC 2001
Robinson Marguerite S The Microfinance Revolution Volume 2 Lessons from Indonesia Washington DC 2002
Rosenberg Richard Microcredit Interest Rates Consultative Group to assist the Poorest Occasional Paper No 1 revised November 2002 Washington DC 2002
70
Roth Michael Steinwand Dirk Mikrofinanz Weltweites Erfolgsmodell nur nicht inDeutschland Zur Uumlbertragbarkeit der Erfahrungen aus Entwicklungslaumlndern auf Deutschland Deutsche Gesellschaft fuumlr Technische Zusammenarbeit (ed) Eschborn2004
Schmidt Reinhard H Tschach Ingo Microfinance as a Nexus of Incentives Finance and Accounting Working Paper No 87A Frankfurt 2001
Schreiner Mark A Framework for the Analysis of the Performance and Sustainability of Subsidized Microfinance Organizations with Application to Banco Sol of Bolivia and Grameen Bank of Bangladesh unpublished PhD dissertation Columbus (O) 1997
Seibel Hans D Recent Developments in Microfinance Development Research Center Working Paper No 1998-5 Cologne 1998
Seibel Hans D History matters in microfinance in Small Enterprise Development ndashAn International Journal of Microfinance and Business Development Vol 14 (2003a) No 2 pp 10-12
Seibel Hans D Schmidt Petra How an Agricultural Development Bank Revolutionized Rural Finance The Case of Bank Rakyat Indonesia International Fund for Agricultural Development Rural Finance Working Paper B 5 Rome 2000
Sen Amartya Oumlkonomie fuumlr den Menschen ndash Wege zu Gerechtigkeit und Solidaritaumlt in der Marktwirtschaft Muumlnchen Wien 2000
Serageldin Ismail The View of the Chair in Consultative Group to Assist the Poorest Newsletter Issue No1 (1996) pp 1 11-12
Soros George Die Krise des globalen Kapitalismus Offene Gesellschaft in Gefahr Berlin 1998
Staschen Stefan Regulation and Supervision of Microfinance Institutions State of Knowledge Deutsche Gesellschaft fuumlr Technische Zusammenarbeit (ed) Eschborn 1999
Steinwand Dirk The Alchemy of Microfinance The Evolution of the IndonesianPeoples Credit Banks (BPR) to 1999 and a Contemporary Analysis Berlin 2001
Stiglitz Joseph E Peer Monitoring and Credit Markets in The World Bank Economic Review Vol 4 (1990) No 3 pp 351-366
Stiglitz Joseph E Weiss Andrew Credit Rationing in Markets with Imperfect Information in The American Economic Review Vol 71 (1981) No 3 pp 393-410
Tschach Ingo Theorie der Entwicklungsfinanzierung Mit Kleinkreditprogrammen Kredit- und Arbeitsmarktsegmentierung uumlberwinden Frankfurt 2000
UNDP Human Development Report 2004 New York 2004
71
UNFPA state of the world population 2004 New York 2004
UNICEF The State of the Worldrsquos Children 2002 NewYork Geneva 2002
Varley Robert C G Financial Services and Environmental Health Household Credit for Water and Sanitation Environmental Health Project Applied Study No 2 Washington DC 1995
Volkery Carsten Kampf um Straszligenhaumlndler in Die Zeit Nr 23 published May 27th
2004 p 33
Wardhana Ali Introduction in The Microfinance Revolution ndash Sustainable Finance for the Poor Washington DC 2001 pp XVII-XXVII
Woodworth Warner Woller Gary Greetings from the Editors Journal of Microfinance Vol 1 (1999) No 1 p 6
The World Bank Group World Development Indicators 2004 Washington DC 2004
Worldwatch Institute (2002) Vital Signs 2002 New York London 2002
Wimmer Nancy Barua Dipal Less is more Microfinance for solar energy in rural areas in Renewable Energy World Review Issue 2004-2005 Vol 7 (2004) No4 pp 170-179
Yunus Muhammad Grameen Bank II ndash Designed to Open new Possibilities Dhaka 2002
Yunus Muhammad Grameen ndash Eine Bank fuumlr die Armen dieser Welt Muumlnchen 1998a
Internet References
Abishek Lal (nd) An Overview of Microfinance and Environmental Management [http wwwgdrcorgicmenvironabhishekhtml] (availability date October 5 2004)
ACCION (nd) our history [httpwwwaccionorgabout_our_historyasp] (availability date October 5 2004)
ACCION (nd) key statistics [httpwwwaccionorgabout_key_statsasp] (availability date October 5 2004)
Ahmad Zulfiqar (nd) Forms of Regional Cooperation in Microfinance in South Asia [httpwwwbwtporgarcmpakistanIV_News_and_EventsBWTPworkshopZulfiqar20Ahmad20paper20(BWTP-PMN2029Jan04)pdf (availability date October 6 2004)
72
Ahmed Salehuddin (2003) Foreword [httpwwwpksf-bdorgaprm_summit_brochure htm] (availability date September 30 2004)
Annan Kofi (2002) Statement at The Microcredit Summit +5 [httpwww microcreditsummitorgenews2003-03_sp_chowdhuryhtml) (availability date October 5 2004)
Barnes Carolyn (2001) Microfinance Program Clients and Impact An Assessment of Zambuko Trust Zimbabwe [httpwwwmicrofinancegatewayorgfiles18553_Barnes_Zambuko_Trust_2001pdf] (availability date October 5 2004)
Barnes Carolyn Gaile Gary Kibombo Richard (2001) The Impact of Three Microfinance Programs in Uganda [httpwwwmicrofinancegatewayorgfiles2935_Barnes_2001pdf] (availability date October 5 2004)
Barua Dipal (2004) Success of Grameen Shakti in the Field of Renewable Energy Sector in Bangladesh [httpwwwrenewables2004depptPresentation1-SessionVA(14-1530h)-Baruapdf] (availability date September 30 2004)
Bhatt Ela (1997) In 1975 [httpwwwmicrocreditsummitorgdeclarationhtm] (availability date September 30 2004)
BlueOrchard (2004a) Microfinance [httpwwwblueorchardchenmicrofinance_institutions asp] (availability date October 5 2004)
BlueOrchard (2004b) January 2004 Newsletter [httpwwwblueorchardchmedialibrarywebsitenewsletter_jan_2004pdf] (availability date October 5 2004)
Brynjolfsson John (2004) John Brynjolfsson Discusses Recent Trends in TIPS Issuance [httpwwwpimcocomLeftNavPIMCO+Spotlight2004Spotlight_2_04htm] (availability date October 5 2004)
CGAP (2003) Report to the Board of Executive Directors [httpwww-wdsworldbankorgservletWDSContentServerWDSPIB20031208000012009_20031208101736RenderedPDF27441pdf] (availability date October 5 2004)
Chen Shaohua Ravallion Martin (2004) How have the worldrsquos poorest fared since the early 1980s [httpwwwworldbankorgresearchpovmonitorMartinPapersHow_have_the_poorest_fared_since_the_early_1980spdf] (availability date October 5 2004)
Cheston Susy Kuhn Lisa (2002) Empowering Women through Microfinance[httpwwwmicrofinancegatewayorgfiles3240_Cheston_2002doc] (availability date October 5 2004)
Christen Robert P et al (1995) Maximizing the Outreach of Microenterprise FinanceAn Analysis of Successful Microfinance Programs [httpwwwdecorgpdf_docsPNABS519 pdf] (availability date October 5 2004)
73
CIA (2004) The World Factbook [httpwwwciagovciapublicationsfactbook] (availability date October 5 2004)
Clear Profit (2004) Microfinance Bond Record May Double [httpwwwclear-profitcomissuescpsep04txt] (availability date September 30 2004)
Daley-Harris Sam (2003) State of the Microcredit Summit Campaign Report 2003 [httpwwwmicrocreditsummitorgpubsreportssocr2003SOCR03-E[txt]pdf] (availability date September 30 2004)
Dominiceacute Robert (2004) Interview in Microfinance Bond Record May Double [httpwwwclear-profitcomissuescpsep04txt] (availability date September 30 2004)
Donahue Jill Kabbucho Kamau Osinde Sylvia (2001) HIVAIDSmdashResponding To A Silent Economic Crisis Among Microfinance Clients In Kenya and Uganda [httpwwwmicrosave-africacomget_fileaspdownload_id=541] (availability date September 30 2004)
Donahue Jill Sussman Linda (1999) Building a Multi-Sectoral Response Follow-Up Assessment of Programming for Children and Families Affected by HIVAids in Kenya [httpwwwdecorgpdf_docspnacg778pdf] (availability date September 30 2004)
The Economist (1998) [httpwwweconomistcomdisplaystorycfmstory_id=S2629H3C28Q13F240A] (availability date September 30 2004)
Finca (nd) Introduction [httpvillagebankingorgwhereindexphp3] (availability date September 30 2004)
Fischer Stanley (2003) Statement at The Asia Society and Womens World BankingAnnual Microfinance Conference [httpwwwiiecomfischerpdffischer051303pdf] (availability date September 30 2004)
Friedman Milton (nd) Samuha [httpwwwsamuhaorgm-1htm] availability date September 30 2004)
FXTOP (2004) Historical Exchange Rates [httpfxtopcomdehistoratesphp3] (availability date September 30 2004)
Gibbons David Meehan Jennifer W (2002) Financing Microfinance for Poverty Reduction [httpwwwmicrocreditsummitorgpapersfinancing_finalpdf] (availability date September 30 2004)
Grameen Bank (2004) Grameen Bank At a Glance [httpwwwgrameen-infoorgbankcdshtml] (availability date September 30 2004)
Grameen Trust (nd) Grameen Bank Replication Program [httpwwwgrameen-infoorggrameengtrustreplicationhtml8721] (availability date September 30 2004)
74
Hossain Farhad (2004) Microfinance in Development [httpwwwvalthelsinkifi staff jkoponenb1104FarhadFeb2304pdf] (availability date October 5 2004)
IMF (2004) Data [httpwwwimforgexternalpubsftweo200402datadbginimcfm] (availability date October 5 2004)
IMI (2004) Investments [httpwwwimi-agcomoverviewindexhtml] (availability date September 30 2004)
IPCC (2001) Summary for Policymakers [httpwwwipccchpubspm22-01pdf] (availability date September 30 2004)
Jansson Tor Wenner Mark (1997) Financial Regulation and its Significance for Microfinance in Latin America and the Caribbean [httpwwwgdrcorgicmgoverniadb-janssonpdf] (availability date October 5 2004)
Ken Daniel Ten Roeun Van (2004) The Cycle of Debt - As Microcredit Institutions Grow Some Question Their Effect on Poverty [httpwwwcamnetcomkhcambodiadaily selected_featurescd-21-02-04htm] (availability date September 30 2004)
Kim Julia (2002) Social Interventions for HIVAIDS - Intervention with Microfinance for AIDS and Gender Equity [httpwwwwitsaczaradarPDF20filesIntervention_monograph_no_picspdfpdf] (availability date September 30 2004)
Llanto Gilberto (nd) Vietnam [httpwwwadborgDocumentsBooksCentral_Banks_MicrofinanceCountry_Studiesvietnampdf] (availability date September 30 2004)
The Microfinance Gateway (nd) Frequently Asked Questions [httpwwwmicrofinance gatewayorgsectionfaq1] (availability date October 5 2004)
Microfinance Rating and Assessment Fund (2004) Qualified Raters [httpwwwmfrating orgmfi_institutionsqualified_ratershtml] (availability date October 5 2004)
Microcredit Summit (1997) Declaration and Plan of Action [httpwwwmicrocreditsummit orgdeclarationhtm] (availability date September 30 2004)
MicroRate (nd) Performance Indicators and Ratios [httpwwwmicroratecomENGLISHsiteRATINGSindicatorshtml] (availability date September 30 2004)
MicroRate (2002) The Finance of Microfinance [httpwwwmicroratecomPDFFinance20of20Microfinancepdf] (availability date September 30 2004)
MicroRate (2004) Adjusted comparison table [httpwwwmicroratecomENGLISHsitePDFAdjusted20Comparison20Table060320engpdf] (availability date October 5 2004)
75
Mix Market (2004) The Mix Market [httpwwwmixmarketorg] (availability date October 5 2004)
Morduch Jonathan (1999b) The Grameen Bank A Financial Reckoning [httpwwwwwsprincetonedu~rpdsmacarthurdownloadsmorduch_grameen_bankpdf] (availability date September 30 2004)
Pallen Dean (1997) Environmental Sourcebook for Micro-Finance Institutions [httpwwwacdi-idagccaINETIMAGESNSFvLUImagesea20summaries$fileSOURC Epdf] (availability date September 30 2004)
Prisma (2002) The Case for Private Capital Market Creation in the Development Field of Microfinance [httpwwwsocialenterprisenetpdfsprivate_capital_marketpdf] (availability date September 30 2004)
Schmidt Reinhard H Zeitinger C-P (1997) Critical Issues in Microbusiness Finance and the Role of Donors No 6 [httpwwwgdrcorgicmmfi-donorpdf] (availability date September 30 2004)
Seibel Hans D (2003b) Commodity finance a commercial proposition Micro- and Mesofinance for Agricultural Commodity Production Processing and Trade [httpwwwuni-koelndeew-fakaef05-20042003-420Commodity20Financepdf] (availability date September 30 2004)
Simanowitz Anton Walter Alice (2002) Ensuring Impact Reaching the Poorest while Building Financially Self-sufficient Institutions and Showing Improvement in the Lives of the Poorest Families [httpwwwidsacukimpactPublicationsWorkingPapersOP3MCSSumdoc] (availability date September 30 2004)
Smith Stephen C Jain Sanjay (1999) Village Banking and Maternal and Child Health Theory and Evidence from Ecuador and Honduras[httphomegwuedu~scsmith healthrevwd801pdf] (availability date September 30 2004)
United Nations (1999) International Year of Microcredit 2005 [httpods-dds-nyunorgdoc UNDOCGENN9976933PDFN9976933 pdfOpenElement] (availability date October 5 2004)
United Nations (2000) United Nations Millennium Declaration [httpods-dds-nyunorgdocUNDOCGENN0055951PDFN0055951pdfOpenElement] (availability date October 5 2004)
US Census Bureau (2004) Total Midyear Population for the World 1950-2050 [httpwwwcensusgovipcwwwworldpophtml] (availability date October 5 2004)
WHO (2004) Making pregnancy safer [httpwwwwhointmediacentrefactsheets fs276en] (availability date September 30 2004)
WHO (2001) Child Health [httpwwwwhointmipfiles2082AAGChildHealthpdf] (availability date September 30 2004)
76
The World Bank Group (nd) Health Nutrition and Population and the Millennium Development Goals [www1worldbankorghnpMDGMDG20-20HNPbookletpdf] (availability date September 30 2004)
Yunus Muhammad (1998) Championing the Right to Credit for Poor Women Around the World [httpaspgrameencom dialoguedialogue34interviewhtml] (availability date September 30 2004)
UNAIDS (2004) [httpwwwunaidsorgbangkok2004GAR2004_pdfUNAIDSGlobalReport2004_enpdf] (availability date September 30 2004)
Ratings
M-Cril (2000) SPANDANA [httpwwwratingfundorgspanishdocsSPANDANA_RatingReportpdf] (availability date October 7 2004)
M-Cril (2001a) BASIX [httpwwwbasixindiacomMcrilasp] (availability date October 7 2004)
M-Cril (2001b) BDB [httpwwwratingfundorgspanishdocsRF_BDBpdf] (availability date October 7 2004)
M-Cril (2001c) SNEHA [httpwwwratingfundorgspanishdocsRF_Sneha-u1pdf] (availability date October 7 2004)
M-Cril (2002a) KCLF [httpwwwratingfundorgdocsRF-KCLF-risk20reportdoc] (availability date October 7 2004)
M-Cril (2002b) NWTF [httpwwwratingfundorgspanishdocsRF_NWTFpdf] (availability date October 7 2004)
M-Cril (2002c) SEEDS [httpwwwratingfundorgspanishdocsRF_SEEDS_2002_Ratingpdf] (availability date October 7 2004)
M-Cril (2002c) Share [httpwwwratingfundorgspanishdocsRF_SHAREpdf] (availability date October 7 2004)
M-Cril (2002d) TSKI [httpwwwratingfundorgspanishdocsRF_Tski_mcrilfinal(-) reportpdf] (availability date October 7 2004)
M-Cril (2003a) ASA [httpwwwratingfundorgdocsASA20updatepdf] (availability date October 7 2004)
M-Cril (2003b) BURO [httpwwwm-crilcomburopdf] (availability date October 7 2004)
M-Cril (2003c) EMT [httpwwwratingfundorgdocsEMTpdf] (availability date October 7 2004)
77
M-Cril (2003d) SKS [httpwwwmixmarketorgendemanddemandshowprofileaspett=25ampshowinfo=adjusted] (availability date October 7 2004)
M-Cril (2003d) TPC [httpwwwratingfundorgdocsTPC_Finalpdf] (availability date October 7 2004)
M-Cril (2004b) UPAP [httpwwwratingfundorgdocsUPAP_2004pdf] (availability date October 7 2004)
Microfinanza (2002a) ACME [httpwwwratingfundorgspanishdocsACME_finalpdf] (availability date October 7 2004)
Microfinanza (2002b) BTFF [httpwwwratingfundorgspanishdocsBTFF_RatingReportpdf] (availability date October 7 2004)
Microfinanza (2002c) BESA [httpwwwratingfundorgspanishdocsBESA_RatingReportpdf] (availability date October 7 2004)
Microfinanza (2002d) CAME [httpwwwratingfundorgdocsEvaluacionCAME(-) Finaldoc] (availability date October 7 2004)
Microfinanza (2002e) RFF [httpwwwratingfundorgdocsRFF20finalpdf] (availability date October 7 2004)
Microfinanza (2002f) PSHM [httpwwwratingfundorgspanishdocsPSHM_Reportpdf] (availability date October 7 2004)
Microfinanza (2003) CAJCA [httpwwwratingfundorgdocsCalificacion_Jardin_Azuayo_ratingpdf] (availability date October 7 2004)
Microserve (2003) ENDA [httpwwwmixmarketorgendemanddemandshowprofileaspett=865ampshowinfo=adjusted] (availability date October 7 2004)
Planet Rating (2002a) FONDEP [httpwwwmfratingorgRatingscompleted_ratingshtml] (availability date October 7 2004)
Planet Rating (2002b) PRIZMA [httpwwwmixmarketorgendemanddemandshowprofileaspett=111ampshowinfo=adjusted] (availability date October 7 2004)
Planet Rating (2002c) SWS [httpwwwratingfundorgspanishdocsSWC_reportpdf] (availability date October 7 2004)
Planet Rating (2002d) ZAKOURA [httpwwwratingfundorgspanishdocsRF_Zakourapdf] (availability date October 7 2004)
Planet Rating (2003a) AMSSF [httpwwwratingfundorgdocsPlanetRating_AMSSF_010803pdf] (availability date October 7 2004)
Planet Rating (2003b) FOCCAS [httpwwwratingfundorgdocsPlanetRatingFOCCAS120803pdf] (availability date October 7 2004)
78
Planet Rating (2003c) PADME [httpwwwmfratingorgdocsPlaNetRatingPADME070302_Englishpdf] (availability date October 7 2004)
Planet Rating (2003d) PAPME [httpwwwmfratingorgdocsPAPME_PlanetRating080903pdf] (availability date October 7 2004)
Planet Rating (2003e) VITAL FINANCE [httpwwwmfratingorgdocsVital20Finance_Sept202003pdf] (availability date October 7 2004)
Planet Rating (2004a) ABA [httpwwwratingfundorgdocsABA_April202004pdf] (availability date October 7 2004)
Planet Rating (2004b) ACEP [httpwwwmfratingorgdocsACEPSeacuteneacutegal_2004pdf] (availability date October 7 2004)
Planet Rating (2004c) AGROINVEST [httpwwwratingfundorgdocsAgroInvest_June202004pdf] (availability date October 7 2004)
Planet Rating (2004d) ASBA [httpwwwratingfundorgdocsASBA_April202004pdf] (availability date October 7 2004)
Planet Rating (2004e) DBACD [httpwwwratingfundorgdocsDBACD_April202004pdf] (availability date October 7 2004)
Planet Rating (2004f) FINADEV [httpwwwmfratingorgdocsFinadev_2004pdf] (availability date October 7 2004)
Planet Rating (2004g) MI-BOSPO [httpwwwratingfundorgdocsMIBOSPO_160404pdf] (availability date October 7 2004)
Planet Rating (2004h) SBACD [httpwwwratingfundorgdocsSBACD_PlanetRating300604pdf] (availability date October 7 2004)
Other Sources
Interview Shaw Newaz Deputy General Manager of the Grameen Bank October 30th
2003
Hodson Charles (2001) Your Business Your World Jim Boulden CNN (ed) Dhaka 2001
10
This is not true for most developing countries where market penetration of financial
institutions is far from reaching the majority of the inhabitants (see chapter 4) A variety
of reasons is responsible for this including that the banking sector in the most
developing countries have developed in a very different way to than those in
industrialized countries
One of the most important reasons is that in contrast to the industrialized countries little
attention has been paid to the legal recognition prudential regulation and effective
supervision of informal financial institutions28 This insecure legal environment leads to
several problems Since the regulatory framework for mobilizing savings often does not
fit the needs of institutions targeting low income people many organizations are not
permitted to do so and are therefore missing funds to on-lend as credit29 An additional
problem is the lack of a deposit insurances This not only increases the risk of a bank
run but also keeps people from depositing their savings in a financial institution30 In
addition inappropriate interest rate ceilings prevail in many countries While politics
claim they are lowering the interest rates charged to the poor they de facto only limit
their access to financial services (see chapter 5)31
Another problem that retarded the growth of the financial sector in developing countries
was the supply-leading finance theory which dominated the development strategies of
many countries after the second world war32 This theory ldquo refers to the provision of
loans in advance of the demand for credit for the purpose of inducing economic
growthrdquo33 Since it was believed that poor people were neither able to save (and thus
dependent on outside funding) nor capable of paying commercial rates of interest
massive subsidized credit programs were established34 The results were alarming
Repayment rates often did not exceed 50 percent and some government financed
programs even had default rates of more than 90 percent35 The main reason being that
credit was not provided according to business management principles but instead
28 See Seibel (1998) p 829 See Robinson (2001) p 4930 See Staschen (1999) p 1431 See Gibbons (2000) p 1532 See Morduch (1999a) p 157033 Robinson (2001) p 14034 See Borst (2004) pp 33 et sqq35 See Yunus (1998a) p 154 Robinson (2001) p 145
11
according to political objectives Therefore receiving loans was seen as a reward for the
constituents rather than as a business transaction Most of the funds earmarked for the
poor also never reached them ending up instead in the hands of the local elites
Attracted by the below market interest rates and the possibility not to pay back at all
these groups lobbied to be treated privileged and often used the money received for
consumption or for on-lending at higher rates36 But subsidized credit not only
encouraged corruption it also discouraged sustainable financial institutions since they
could not compete with interest rates that were not aimed to cover all costs and were
sometimes even lower than the interest paid on savings37 The low or negative spread
also worked as a negative incentive to institutionsrsquo effort to mobilize savings which in
turn intensified the problem of credit rationing (see chapter 5)
24 Microfinance Today
In the 1970s a paradigm shift started to take place The failure of subsidized government
or donor driven institutions to meet the demand for financial services in developing
countries let to several new approaches Some of the most prominent ones are presented
below
Bank Dagan Bali (BDB) was established in September 1970 to serve low income people
in Indonesia without any subsidies and is now ldquowell-known as the earliest bank to
institute commercial microfinancerdquo38 While this is not true with regard to the
achievements made in Europe during the 19th century it still can be seen as a turning
point with an ever increasing impact on the view of politicians and development aid
practitioners throughout the world In 1973 ACCION International a United States of
America (USA) based non governmental organization (NGO) disbursed its first loan in
Brazil39 and in 1974 Professor Muhammad Yunus started what later became known as
the Grameen Bank by lending a total of $27 to 42 people in Bangladesh40 One year
later the Self-Employed Womenrsquos Association started to provide loans of about $15 to
36 See Robinson (2001) pp 144 et sqq37 Before BRI underwent a major transformation in 1983 a negative spread between interest rates on loans and savings existed While the bank lent at a 12 annual effective interest rate it paid 15 on savingsSee Robinson (2001) p 10638 Wardhana (2001) p XXVII39 See ACCION (nd)40 See Yunus (1998a) p 16 et sqq
12
poor women in India41 Although the latter examples still were subsidized projects they
used a more business oriented approach and showed the world that poor people can be
good credit risks with repayment rates exceeding 9542 even if the interest rate charged
is higher than that of traditional banks Another milestone was the transformation of
BRI starting in 1984 Once a loss making institution channeling government subsidized
credits to inhabitants of rural Indonesia it is now the largest MFI in the world being
profitable even during the Asian financial crisis of 1997 ndash 199843
In February 1997 more than 2900 policymakers microfinance practitioners and
representatives of various educational institutions and donor agencies from 137
different countries gathered in Washington DC for the first Micro Credit Summit This
was the start of a nine year long campaign to reach 100 million of the world poorest
households with credit for self employment by 200544 According to the Microcredit
Summit Campaign Report 67606080 clients have been reached through 2527 MFIs by
the end of 2002 with 41594778 of them being amongst the poorest before they took
their first loan45 Since the campaign started the average annual growth rate in reaching
clients has been almost 40 percent46 If it has continued at that speed more than 100
million people will have access to microcredit by now and by the end of 2005 the goal
of the microcredit summit campaign would be reached As the president of the World
Bank James Wolfensohn has pointed out providing financial services to 100 million of
the poorest households means helping as many as 500 ndash 600 million poor people47
41 See Bhatt (1997)42 See Yunus (1998a) p 143 et sqq43 See Robinson (2002) p 38044 See Daley-Harris (2003) p 345 ldquoThe Microcredit Summit Campaign defines ldquopoorestrdquo as those who are in the bottom half of those living below their nationrsquos poverty line or are living on less than $1 a day adjusted for purchasing power parity (PPP)rdquo See Daley-Harris (2003) p 3 This definition will also be used throughout this paper46 See Daley-Harris (2003) p 1847 See Morduch (1999a) p 1570
13
3 The Impact of Microcredit
31 Microcredit and the Millennium Development Goals
In 1996 Ismail Serageldin the then chair of the Consultative Group to Assist the Poorest
(CGAP)48 claimed that ldquo[m]icrofinance is a proven instrument to assist the very poorrdquo49
This view is also shared by the World Watch Institute50 and underlines what has been
stated above namely that microfinance can be used as a strong anti-poverty tool But
does microfinance actually meet these expectations and keep this promise51
The impact that microcredit has on the lives of poor people will be demonstrated by
showing how it contributes to each of the eight Millennium Development Goals
(MDGs)52 which are related to the reduction of poverty in all its forms These goals
were resolved in September 2000 by the General Assembly of the UN in their
Millennium Declaration53
32 The Eradication of extreme Poverty and Hunger
The aim of the first MDG is to halve the proportion of people who live on less than $1 a
day between 1990 and 2015 According to current population projections of the World
Bank54 this would equal 849 million people in 201555
48 The Consultative Group to Assist the Poorest is a consortium of 28 public and private development agencies working together to expand access to financial services for the poor in developing countries and was established by the World Bank in 1995 Recently it changed its name to Consultative Group to Assist the Poor49 See Serageldin (1996) p 1150 See Gardner (2002) p 1851 See Morduch (1999a) pp 1569 et sqq52 The Millennium Development Goals are (1) eradicate extreme poverty and hunger (2) achieve universal primary education (3) promote gender equality and empower women (4) reduce child mortality (5) improve maternal health (6) combat HIVAIDS malaria and other diseases (7) ensure environmental sustainability and (8) develop a global partnership for development53 See United Nations (2000)54 See World Bank (2004) p 38 et sqq55 Although it is not explicitly mentioned in the Millennium Declaration it is commonly assumed that the share of people living on less than $1 in low and middle income countries should be halved If the share would be calculated with regard to the worldrsquos total population the goal for 2015 would 818 million people For the worldrsquos total population in 1990 see US Census Bureau (2004)
14
Today almost 11 billion people live on less than $1 and more than 27 Billion live on
less than $2 per day56 The mean income for those living under $1 a day is $077 and it
is $125 for those living under $2 a day57 While the number of people living on less
than $1 per day is slowly decreasing and is expected to be 913 million in 2015 the
number of people living on less than $2 a day is actually increasing58 One of the
outcomes from this degree of poverty is that more than 27000 children die every day
from mostly preventable diseases many of them related to hunger59
Microcredit enables poor people to start new businesses or to diversify existing ones
which helps them to increase their income In addition to large amounts of anecdotal
evidence several studies have documented the positive economic impact microcredit
has on its clients Cloud and Panjaitan-Drioadisuryo have found that the average income
of a sample of BRI borrowers has increased by 112 percent and that 90 percent of their
families have crossed the poverty line60 Only 12 out of the 121 respondents of that
study reported that their income had not increased61 According to the Grameen Bank
website 5109 percent of their clients have crossed the poverty line since they took their
first loan62
A study conducted by Barnes showed that the program of the Zambuko Trust a local
MFI in Zambia had a considerable impact on the poorest clients consumption of meat
fish and chicken63 While 76 percent of the continuing clients of the MFI called Share in
India significantly increased their income and 50 percent have crossed the poverty line 64 Khandker discovered in his well known study ldquoFighting poverty with microcreditrdquo
that there is a connection between the microcredit programs of three Bangladeshi MFIs
and household per capita expenditure For every dollar borrowed by a Grameen Bank
member household consumption increases by $018 In addition he found that 5 percent
56 See Chen and Ravallion (2004) p 2957 In fact those people live on less than $108 and $215 respectively a day in 1993 PPP This means that the nominal dollar value of their income is considerably lower See Chen and Ravallion (2004) p 9 58Both numbers are decreasing in Asia but increasing in the rest of the world See Chen and Ravallion (2004) p 22 et sqq59 See UNICEF (2002) p 660 A consistent definition of the term ldquopoverty linerdquo does not exists among different nations Therefore the term will be used according to the definition of the respective country in this paper61 See Panjaitan-Drioadisuryo and Cloud (1999) p 77562 See Grameen Bank (2004) 63 See Barnes (2001) p 8664 See Simanowitz and Walter (2002) p 16
15
of Grameen Bank borrowers move out of poverty every year65 Supposing Khandkerrsquos
findings were correct for all MFIs worldwide and the Microcredit Summit Campaign
achieved its goal of reaching 100 million of the poorest households with microcredit by
2005 then 25 million people (assuming an average family size of five) would leave
poverty every year66 Although this number would have to be adjusted in order take into
consideration the MFI clients who have crossed the poverty line already and of course
the experiences made in Bangladesh can not be transferred precisely to other countries
it still demonstrates the enormous effect that microcredit can have on assisting the
poorest to move out of poverty
Although a 1996 study of Hulme and Mosley states that providing microcredit can also
have a negative impact on the income of the poorest households67 these findings can
be considered as disproved by the recent bulk of evidence drawing favorable
conclusions68
33 Achievement of universal primary Education
The aim of the second MDG is to ensure that all children will be able to complete
primary school by 2015
Currently more than 100 million children most of them girls are not in school69
Besides school fees poor households often can not afford to send their children to
school because they need them to help in the family business
Microcredit programs mainly contribute to the second MDG by increasing families
income and therefore enabling parents to send their children to school Barnes Gaile
and Kibombo found that clients of an MFI in Uganda spent significantly more on
childrenrsquos education than non-clients70 and in Zambia Barnes showed that ongoing
participation in the Zambuko Trustrsquos program had a positive impact on the members
65 See Khandker (1998) p 5666 See Daley-Harris (2003) p 2467 See Hulme and Mosley (1996) p 180 et sqq 68 See Gibbons and Meehan (1998) p 13669 See UNICEF (2002) p 2270 See Barnes Gaile and Kibombo (2001) p 64
16
children staying in school71 In Bangladesh the probability of girls enrolling in school
increased by 19 percent for every 1 percent increase in Grameen Bank loans to female
clients For boys this number was even higher with the mean being 24 percent72
34 Promote gender Equality and empower Women
The aim of the third MDG is to eliminate the disparity in the ratios of girls to boys in
primary secondary and tertiary education in the ratio of literate females to males and to
increase the share of women in the labor market and in parliament73
At present the literacy rate for women is lower than for man all over the world
According to the Human Development Report 2004 the average female literacy rate as
a percentage of male literacy rate is 759 in developing countries and is as low as 37 in
Niger74 But women are not only discriminated against in education but also in access to
medical services and therefore have a higher mortality rate than man75 The worldwide
tendency for women to be underrepresented in the labor market and in the parliaments is
even more severe in developing countries76 Although several women have become
heads of state in various Asian countries (eg Bangladesh India and Indonesia) this is
probably due to them being wives or daughters of former respected male politicians
Since women have a higher repayment rate than man77 and also tend to invest increases
in income on the household and on their children rather than on themselves78 most
MFIs prefer female clients79 Therefore they empower women in many ways Often
MFIs not only encourage women to become involved in financial transactions for the
first time but also to become independent active members of the economy and to
acquire assets in their own names Cheston and Kuhn found that 68 percent of the
women participating in an MFI program in Nepal ldquohellip experienced an increase their
71 See Barnes (2001) p 8472 See Khandker (1998) p 4973 See World Bank (2001) p 2074 See UNDP (2004) pp 225 et sqq75 See Sen (2000) p 23276 See Sen (2000) pp 242 et sqq77 See Littlefield Morduch and Hashemi (2003) p 778 See Yunus (1998a) pp 116 et sqq79 According to the Microcredit Summit Campaign Report 79 or 37677080 of the poorest clients were women See Daley-Harris (2003) p 3
17
decision-making roles in the areas of family planning childrenrsquos marriage buying and
selling property and sending their daughters to school - all areas of decision making
traditionally dominated by menrdquo80 The program of the Lower Pra Rural Bank in Ghana
had an positive impact on womenrsquos participation in the community81 which is true as
well for the CRECER program in Bolivia82 In Bangladesh the Grameen Bank and the
Bangladesh Rural Advancement Committee (BRAC) the two biggest MFIs of the
country had a significant positive effect on womenrsquos empowerment measured through
eight different indicators83 After joining Grameen Bank only 21 percent of the female
members considered themselves as unemployed while this number was 50 percent
before joining84 According to the Grameen Bank website 93 percent of the Bankrsquos
shares are owned by their borrowers which elect the members of the board every three
years They also get familiar with the election process by more frequently voting for
representatives at the lower level of the organizational structure Partly because of this
experience they are more likely to run for public office In the 2003 local government
elections Grameen Bank members constituted 24 of the seats reserved for women
while they represent less than 10 of Bangladeshi adult female population85 Female
clients of MFIs from countries like the Philippines Bolivia and Nepal have reported
similar occurrences86
35 Reduce Child Mortality and improve Maternal Health
The aim of the fourth MDG is to reduce the under-five mortality rate by two-thirds
between 1990 and 2015 and the fifth MDG strives for a three quarter reduction in the
maternal mortality ratio by the same date
As has been stated above more than 10 million children are dying annually in the
developing world of mostly preventable causes with malnutrition playing a role in over
80 See Cheston and Kuhn (2002) p 1881 See MkNelly and Dunford (1998) p 5482 See MkNelly and Dunford (1999) p 7183 The eight different indicators are ldquofreedom of movement economic security ability to make small and larger independent purchases participation in important family decisions relative freedom from domination by the family political and legal awareness and participation in political campaigning and public protestsrdquo Hashemi and Schuler (1998) p 3684 See Holcombe (1995) p 5185 See Grameen Bank (2004)and CIA (2004)86 See Littlefield Morduch and Hashemi (2003) p 8
18
half of the childrsquos deaths and in over 50 countries child mortality rates are greater than
100 deaths per 1000 live births87 Maternal mortality is also a significant problem in the
developing world with more than 500000 women dying every year from pregnancy
related causes88
MFIs are mainly contributing to the these MDGs by increasing families income and
therefore enabling the households to afford better nutrition and medical services
Furthermore they are often linked with microinsurance or health education programs
In addition to what has been showed in chapter 31 Pitt Khandker and Millimet
estimate that a 10 percent increase in the loan size of a female borrower in Bangladesh
increases the arm circumference of their daughters by 6389 Smith and Jain found that
village banking in Ecuador had a positive effect on child diarrhea90 which is responsible
for 15 of child deaths91 Since Sen argues that an improved status of women within
the family reduces child mortality92 the empowerment of women through MFIs is also
contributing to this cause
Although no study has been conducted so far on the direct impact of microcredit on
maternal health it can be assumed that an overall improvement of access to medical
services reduces maternal mortality as well A study of the Morgan State University for
example suggests that microcredit has a positive effect on the prevalence of
contraceptives93 which leads to a decrease of unwanted pregnancies and therefore
reduces maternal death
36 Combat HIVAIDS Malaria and other diseases
The aim of the sixth MDG is to halt and begin to reverse by 2015 the spread of
HIVAIDS malaria and other major diseases and to assist children orphaned by HIV
87 See World Bank (2001) p 888 See WHO (2004) 89 See Pitt Khandker and Millimet (2003) p 11390 See Smith and Jain (1999) p 3791 See WHO (2001) 92 See Sen (2000) p 23593 See Amin et al (2001) p 1614
19
In 2003 29 million people died because of HIV and about 48 million became infected
the greatest number since AIDS was discovered 23 years ago94 This pandemic has lead
to a tremendous decrease in the life expectancy in the hardest hit countries Botswana
for example one of the richest and most democratic countries in Africa has a
HIVAIDS adult prevalence rate of 388 and a life expectancy at birth of less than 31
years95
Malaria not only causes more than one million deaths annually it leads also to 300 ndash
500 million clinical cases a year Both numbers have been steadily increasing over the
past two decades96 More than two million people a year are killed by tuberculosis
another global health problem This curable disease is estimated to cost poor
communities about $12 billion every year since even those who survive normally lose
more than 3 month of work time while recovering97
MFIs contribute to the sixth MDG in several ways By increasing clientrsquos income they
help households affected by HIV or other diseases to better cope with the situation
Besides spending more money on health services and nutrition MFI clients also tend to
be more able and willing to support AIDS orphans than non clients98 In addition to the
already stated increase in the use of contraceptives99 several innovative approaches to
deal with disease related crisis have also arisen This is of course necessary not only to
counteract the devastating effect the above discussed epidemics can have on MFI
clients but also to not put the viability of the respective institution at risk One option is
to integrate education services in the MFI programs and encourage clients to form
solidarity groups100 It has been shown that these services do not necessarily decrease
the effectiveness of the institutionsrsquo employees101 Another way is to strengthen the ties
to NGOs specialize in dealing with the respective disease Synergies gained through this
cooperation can help clients to better deal with the situation and in the end increase their
94 See UNAIDS (2004) p 2395 See CIA (2004)96 See World Bank (2001) p 1697 See World Bank (2001) p 1298 See Barnes (2001) p 6499 See also Kim et al (2002) p 18100 See Donahue and Sussman (1999) p A 14101 See Donahue Kabbucho and Osinde (2001) p 25
20
repayment rates Various MFIs also have introduced loan and health insurance products
or cultivated linkages with organizations doing so102
It has to be stated that despite the benefits MFIs can provide to people effected by
HIVAIDS or other diseases microcredit can also be a burden for those who are already
chronically ill These people can still benefit through loans provided to members of the
family or the community or through one of the other services mentioned above
37 Ensure environmental Sustainability
The aims of the seventh MDG are to support and promote the principles of sustainable
development and put them into action and to improve the lives of slum dwellers and
people without sustainable access to safe drinking water and sanitation
Today climate change is considered as the major environmental problem103 The
Intergovernmental Panel on Climate Change (IPCC) states that human activities
contribute to most of the 06 degC increase in global average temperature over the 20th
century and the predicted increase of another 14 to 58 degC between 1990 and 2100104
Emission of carbon from fossil fuel is reported to have the dominant influence on this
development While the total emission was 16 billion tons in 1950 it was already 65
billion tons in 2000 and is expected to continue to grow105 This development would
lead to a rise in the average sea level of between 9 and 88 centimeters during the next
century106 Furthermore it is predicted that global warming increases the risk of extreme
events like cyclones or floods leads to an increase in the number of people infected by
diseases like malaria and decreases the potential crop harvest and water availability
especially in developing countries107 In 2000 already 11 billion people lacked access to
clean drinking water and 24 billion to basic sanitation108
102 See Barnes (2001) p 40 Barnes Gaile and Kibombo (2001) p 13 and Grameen Bank (2004)103 See Gardner (2002) p 5104 See IPCC (2001) pp 2 et sqq105 Worldwatch Institute (2002) p 52 et sqq106 See IPCC (2001) p 16107 See Dunn and Flavin p 29108 See UNFPA (2004) p 18
21
MFIs contribute to achieving the seventh MDG in several ways By providing loans for
the purchase of renewable energy technologies they help people in developing
countries to increase their per capita energy consumption without increasing the carbon
dioxide emission In a 2003 survey of 140 MFIs from 80 different countries 21 said
they provide credits for solar home systems and another 19 stated they are interested in
becoming engaged in this business109 While Grameen Shakti a rural energy service
company cooperating with the Grameen Bank in Bangladesh has already installed more
than 23000 solar home systems110 a 2000 World Bank study reports twelve projects
providing solar home systems to rural households with a target of 500000
installations111 It has also been suggested that MFIs should raise environmental
awareness among their clients112 but so far no data is available on how staff can cope
with this additional task Many MFIs also provide loans for improvements in sanitation
and the water supply of their clients Varley gives several examples from Africa Asia
and Latin America on how microcredit not only has helped to invest in rainwater
collection systems but also how it has enabled households to increase their water
supply through community water associations113 In addition many MFIs provide credit
for the construction of sanitary latrines114 The situation of slum dwellers is also
positively effected by MFIs Directly through their services in poor urban communities
and indirectly by creating jobs in rural areas and therefore easing the pressure on urban
labor markets
38 Develop a global Partnership for Development
The eight MDG is about the means to achieve the other seven MDGs It calls for all
players involved in the endeavor of development and poverty eradication to work as
partners in a global context
Again MFIs are contributing to the eight MDG in many ways This is occurring through
international networks that provide funding and technical assistance through internet
information portals and specialized journals through social and for profit investors and
109 See Wimmer and Barua (2004) p 174110 Barua (2004) 111 See Martinot and Cabraal (2000) p 6112 See Pallen (1997) p 11 Lal (nd)113 See Varley (1995) pp 39 et sqq114 See Jalvaani (1999) pp 1 et sqq Varley (1995) pp 39 et sqq
22
specialized rating agencies The Bangladesh-based Grameen Trust is one of around 30
networks in operation Besides collaborating with over 200 MFIs around the world it
has directly operated three projects in Afghanistan Kosovo and Myanmar115 While the
ACCION network serves almost 12 million active clients in 19 countries throughout
America and sub-Saharan Africa116 FINCArsquos network operates in three different
continents where it serves more than 200000 customers117 In November 1997 the
MicroBanking Bulletin (MBB) was first published by the microfinance program at the
Economic Institute at the University of Colorado118 Its aim is to develop a database on
the financial performance of MFIs from all over the world which is now available
through the Mix Market an internet portal that also provides information about more
than 300 MFIs investors donor institutions and other related development
organizations119 Two years later the Marriott School at Brigham Young University
started to publish the Journal of Microfinance which has an editorial board of
microfinance experts from all over the world and offers the latest research on this
topic120 In the late 1990s a number of companies became attracted by the microfinance
market and started to invest in MFIs The German based Internationale Mikro
Investitionen Aktiengesellschaft (IMI) for example has already invested more than euro46
million in 19 MFIs in four different continents and plans to invest another euro27 million
before October 2004121 BlueOrchard Finance a microfinance investment consultancy
has channeled more than $60 million worth of private capital to some 40 MFIs
worldwide through investment funds and bond issues122 Big commercial banks like
Citigroup Deutsche Bank and ABN Amro also started to get involved in the
microfinance sector although this is mainly still perceived as a public relation activity
and not as a for-profit investment123 There are also several rating agencies specializing
in MFIs Dependent on their rating these institutions can help MFIs to receive money
from donors or investors Four of the most prominent rating agencies are PlanetFinance
115 See Grameen Trust (nd)116 See ACCION (nd)117 See FINCA (nd)118 See MicroBanking Bulletin (1997) p 5119 See The Mix (2004)120 See Woodworth and Woller (1999) p 6121 See IMI (2004)122 See BlueOrchard (2004b) p 3123 See Busch and Kort (2004) p 8 Fischer (2003) p 6
23
with headquarters in France M-Cril based in India Microfinanza in Italy and
MicroRate with offices in the USA and South Africa124
124 See Microfinance Rating and Assessment Fund (2004)
24
4 Microcredit Outreach
41 The Demand for Microcredit
Although it has been shown that microcredit is one of the most effective poverty
eradication tools that it is considered a human right by some of its advocates125 and it
can contribute considerably to the development of the financial sector in developing
countries an enormous gap still exists between supply and demand for microcredit
Estimates on the demand for microcredit vary greatly While USAID estimates the
number of potential microfinance clients is between 100 and 200 million126 the
Microcredit Summit Campaign states the total demand is more than 234 million
people127 CGAP recognizes some 500 million micro-entrepreneurs who have the
potential to become customers of MFIs128
Marguerite Robinson calculates the demand as follows ldquoAssuming five people to a
household among the 45 billion people living in low- and lower-middle-income
economies in 1999 (World Bank World Development Report 20002001) there are 900
million households in those economies If estimating conservatively we assume that
informal commercial moneylenders supply credit to 30 percent of these households at
least once a year this would mean that there are 270 million households borrowing
from informal moneylenders in a year Undoubtedly however many of these
households borrow multiple times within a yearrdquo129 Although this is a very rough
estimate assuming big differences in demand for microcredit in different countries the
number seems to be the most meaningful In contrast to the estimate of the Microcredit
Summit Campaign it does not include every single household living on less than $1 a
day but according to the definition presented in chapter 1 it counts everyone who has
no regular access to traditional financial institutions but demands such services
Obviously not all people who draw on moneylenders have financial needs that could be
matched through MFIs On the other hand interest rates charged by moneylenders tend
125 See Yunus (1998b) 126 See Christen et al (1995) p 15127 See Daley Harris (2003) p 22 128 See Robinson (2001) p 26129 See Robinson (2001) p 215
25
to be considerably higher than those of MFIs The former normally charge effective
monthly rates between ten and several hundred percent per month the latter generally
charge between 15 and five percent which enables them to attract additional clients130
42 The Supply of Microcredit
In spite of the impressive growth of MFIs around the world the demand for microcredit
is far from being met and this it is not likely to change in the near future The
Microcredit Summit Campaign reported that by the end of 2002 67606080 clients131
were reached through MFIs and that this number has increased by almost 40 percent
annually for the last five years132 It is likely that this tremendous speed of growth is at
least partly due to including MFIs which have not been reporting to the Campaign from
its start in 1997 although they have already existed at that time These institutions
contributed 22 percent to the growth in poorest clients in 2000 578 percent in 2001 and
338 percent in 2002 The growth of the poorest clients increased at least party because
of an expanded definition of the term ldquopoorestrdquo133 Since the contribution of MFIs
which previously have not been considered can be expected to decrease dramatically
the growth rate as stated by the Microcredit Summit Campaign can not be used to
predict the future development of the microfinance sector Another factor likely to slow
down the growth is the concentration of microfinance activities in some Asian countries
where almost 90 percent of the poorest microfinance clients live today134 Even if one
takes into consideration the relative size of Asiarsquos population and the fact that many
MFI customers in Latin America are relatively better off and therefore are not included
in this numbers the coverage of this part of the world far exceeds the others In
Bangladesh for example the microfinance market is close to saturation More than
eleven million households were served by several hundred MFIs in 2001135 Among
them are Grameen Bank and BRAC two of the best known MFIs in the world both
providing their services to more than three million customers With an average
household size of five it can be assumed that in Bangladesh the number of people
130 See Gibbons and Meehan (1999) pp 144 et sqq131 41594778 of them belonged to the poorest before they took their first loan The relative numbers in the following are for these poorest clients only since no other current data was available It can be assumed though that this works as a good proxy for the total number of clients 132 See Daley Harris (2003) p 3133 See Daley Harris (2003) p 17134 See Daley Harris (2003) p 21135 See Ahmed (2003)
26
benefiting from microcredit already surpasses the number of people living below the
poverty line which is estimated to be slightly higher than 50 million136 Therefore
Bangladesh will not contribute to the growth of the microfinance sector as much as it
has done in previous years This is also true for Vietnam Thailand and to a lesser
extent Indonesia Eight of the nine MFIs serving more than one million clients are based
in these countries while the ninth is based in India where due to its one billion
inhabitants the microfinance market is still far from saturation137 In contrast the
supply in Brazil meets less than two percent of the demand which is estimated to be
about 58 million potential clients138 For these reasons greater amount of future growth
must come from smaller or new MFIs in Latin America India China and especially
Africa where almost 30 percent of the worldrsquos poorest live139
43 Meeting the Demand
To fill the gap between the demand and supply for microcredit tremendous investments
are necessary to increase the loan funds of MFIs and build up their capacity through
upgrading existing institutions or building new ones Again estimates on how much
capital is needed vary greatly with the highest being at more than $300 billion140
In 1997 the Microcredit Summit Campaign estimated that $216 billion would be
needed to achieve their goal of providing microcredit to 100 million of the poorest
households This was calculated in the following way Since some 8 million people
already received microcredit in 1997 another 92 million needed to be reached
Assuming $200 ($150 for loan fund and $50 for capacity building) would be needed per
person for 88 million people in developing countries and $1000 ($500 for loan fund and
$500 for capacity building) would be needed for 4 million people in industrialized
countries the capital required ends up to be $216 billion141 For several reasons this
136 See CIA (2004)137 These institutions are The Grameen Bank BRAC Proshika and the Association for Social Advancement (ASA) in Bangladesh the Vietnam Bank for Agriculture and Rural Development (VBARD) and the Vietnam Bank for the Poor (VBA) in Vietnam BRI in Indonesia Bank for Agriculture and Agricultural Co-operatives (BAAC) in Thailand the National Bank for Agriculture and Rural Development (NABARD) in India See Ahmed (nd) p 1 Llanto (nd) p 337138 See Mezzera (2002) p 23139 See See Chen and Ravallion (2004) p 29140 See Clear Profit (2004) Prisma (2002)141 See The Microcredit Summit (1997)
27
number is not qualified to predict the total amount of capital needed to meet the demand
for microcredit On the one hand it focuses mainly on the low end of the market and
therefore underestimates the average loan fund needed On the other hand it does not
take the increasing capital demand from established MFIs into account A survey of 119
MFIs found that the average loan size to increased from $406 in 2002 to $498 in
2003142 This is mainly due to the fact that MFI clients once they have paid back their
loans usually demand larger ones for the continual development of their businesses
and therefore further increase the demand for capital of established MFIs The Grameen
Bank for example has a ceiling on its loans which increases or decreases depending on
the borrowers performance regarding repayments and savings143 While the maximum
amount for the first loan is fixed at approximately $75144 the largest loan disbursed so
far was $17195145 Thus if one estimates that by now 100 million people are borrowing
from MFIs146 another 170 million need to be reached to meet the estimated demand
Assuming an average of $600 ($400 for loan fund and $200 for capacity building) is
needed for every new client and another $200 is needed for every existing client to meet
the demand for larger loans a total of $122 billion is required This rough estimate
helps to convey the approximate amount of capital needed to meet the demand for
microcredit
So far the demand for funds is being partly met by donors which annually provide
between $500 million and $1 billion147 and through the mobilization of local savings
Obviously the amount of money provided by donors will not be able to meet the capital
demand for microcredit in the short term The mobilization of savings on the other hand
has been extremely successful in some cases with BRI probably being the most
prominent example After adapting commercial principals in October 1984 BRI was
able to raise its deposits from $161060 to more than $32 billion in 2003 which equals
almost two times its current loan portfolio148 Many other MFIs like BDB in Indonesia
142 Own calculations Without BRI the numbers would be $343 and $409 See Appendix 1143 See Grameen Bank (2003) p 13144 The accurate amount is 5000 Taka See Interview with Shaw Newaz145 Grameen Bank (2004)146 According to the data provided by the Daley Harris (2003) an annual increase in MFI clients ofapproximately 25 percent from 31122002 till the 3092004 would be needed to reach 100 million clients by now This rated is considerably below the average of the previous five years (38 percent) Therefore it can be assumed as realistic despite the growth hindering factors presented above147 See CGAP (2003) p 8148 See Robinson (2002) p 273 Mix Market (2004)
28
XacBank in Mongolia the Equity Building Society in Kenya or the Centenary Rural
Development Bank in Uganda also have managed to cover their loan portfolio fully
through internally mobilized resources149 The Grameen Bank is also expected to do so
in the first half of 2005150 In addition to raising much needed capital for on-lending the
provision of saving services can deliver notable social benefits itself151
Despite these impressive achievements even the combination of donor money and local
savings at their current levels will not be able to provide the capital needed to continue
the rapid growth of the microfinance sector Especially in their early years MFIs rely on
outside funding BRI for example needed six years before the amount of locally
mobilized savings surpassed the total amount of outstanding loans During this time
expenses and the loan portfolio were covered through a government grant worth $20
million and two World Bank loans of $5 and $97 million respectively152 It also
benefited from a network of more than 3600 branches which were established
throughout the country during the 1970s and early 80s in order to provide government
subsidized credit in rural areas153
The Grameen Bank also widely known as a best practice MFI has received about $175
million in direct and indirect subsidies between 1985 and 1996154 and continues to rely
on outside funding at below market interest rates This is made possible either through
special loans from the Bangladesh Bank or through offering bonds guaranteed by the
Bangladesh government155 - an option most MFIs do not have BDB might be one of the
very few examples which were able to finance their activities through savings and
commercial loans from the start but its outreach did not reach a large scale nor did it
serve the low end of the market In 2000 after 30 years of operation BDB provides
credit to only 10417 clients with an average loan balance of more than $5000156
approximately eight times the countries GDP per capita157
149 See Mix Market (2004)150 See Grameen Bank (2004)151 See Robinson (2001) pp 263 et sqq152 See Seibel and Schmidt (2000) p 4153 See Robinson (2002) p 180154 See Morduch (1999b) p 8155 See Morduch (1999ba) p 25 et sqq156 See Robinson (2002) p 387157 See CIA (2004)
29
Another problem keeping many MFIs from collecting savings is that they do not want
to become a regulated financial institution or do not meet the criteria in their respective
country and therefore they are simply not allowed to mobilize savings from the public
In summary the examples and numbers presented in this chapter support the argument
that the amount of capital that can be raised through donors and locally mobilized
savings is not enough for continuous rapid growth of the microfinance sector If this
lack of capital is not met through other sources the microfinance sector will fail to
contribute its full potential to the achievement of the MDGs
44 Microfinance and the Capital Markets
Regardless of whether the amount of capital needed for the development of the
microfinance sector is $20 or $300 billion it represents only a tiny fraction of the
worldwide capital markets which are estimated at $30 trillion158 Therefore if the
microfinance industry were able to tap the financial markets it would be able to grow
much faster and soon serve the millions of micro-entrepreneurs which currently can not
develop theirs businesses because of capital constrains Another advantage would be
that scarce donor money currently used for the development of the microfinance sector
could be used for other projects that do not have the potential to draw money from
commercial sources This view is shared by Michael Chu the former CEO of ACCION
who made the following statement in 1998 ldquoMicrofinance today stands at the threshold
of its next major stage the connection with the capital marketsrdquo159 Many attempts have
been made since that time Successful MFIs like BancoSol in Bolivia further
strengthened their ties to the capital markets which in some cases already provide the
majority of their funding160 Microfinance investment advisors like BlueOrchard
Finance have become middlemen for MFIs and the financial markets Nevertheless
these links are still far from reaching major scale Currently only approximately 20
percent of MFIs funding comes from commercial sources161 and the biggest bond issue
dedicated to fund MFIs totals only $40 million In addition these funds mainly end up
158 See Brynjolfsson (2004) 159 Chu (1998) quoted in Robinson (2001) p 23160 See Robinson (2001) p 69161 See Dominiceacute (2004)
30
in established institutions in Latin America or Eastern Europe162 while smaller
organizations only benefit indirectly if at all
162 See Clear Profit (2004) IMI (2004)
31
5 Credit Rationing
Until recently the predominant answer to why commercial banks or venture capital
companies did not invest in the microfinance sector was that the poor are not bankable
Besides lacking education and therefore not being able to deal with formal financial
institutions they were viewed as bad credit risk who were unable to invest the borrowed
money in a way that would allow them to repay the loan and interest at a commercial
rate163 Another reason that kept attention away from the idea of providing financial
services to low income people was the belief that informal moneylenders already met
this demand These skeptics felt affirmed through the poor performance of subsidized
credit programs as described in chapter 22 Although it is true that moneylenders
serve a huge number of people in the developing world they more often than not charge
usury interest rates of up to 20000 percent per month164 While the argument that poor
people are not able to participate in the formal financial market can be overcome by
adapting the services accordingly165 the claim of low returns on their investments is not
only proved wrong by empirical evidence but also contradicts economic theory as will
be shown in chapter 53
51 The imperfect Information Paradigm
A more elaborate explanation for the short supply of financial services to low income
people that can be derived from the imperfect information paradigm based
predominantly on the works of Akerlof166 and Stiglitz and Weiss167 After giving a brief
summary of their argument an adaptation of their findings to the microfinance market
will be presented and subsequently it will be shown how their conclusions can be
overcome
Behind the imperfect information paradigm lies the theory of asymmetric information
which simply states that if two parties conduct a transaction one is likely to have more
163 See Ghatak (1983) p 21 et sqq Yunus (1998) p 102 et sqq Robinson (2001) p 35 et sqq164 See Robinson (2001) p 17165 See Seibel (2003b) p 2 BRAC (2003) pp 15et sqq Yunus (1998) pp 151 et sqq 166 See Akerlof (1970) pp 488 et sqq167 See Stiglitz and Weiss (1981) pp 393 et sqq
32
information than the other and is trying to use that for its own advantage168 Applied to
the banking sector this means that a person applying for credit can better judge the
likelihood of repaying the loan than the bank This is because the borrower has better
knowledge of the market she wants to invest in her skills and her willingness to repay
Moreover the bank might not be able to observe if the borrower uses the loan for the
agreed purpose These occurrences can lead to what is known as adverse selection and
moral hazard In this case adverse selection refers to the problem that banks might
attract borrowers with a low probability of repayment if they can not distinguish
between high and low risk loan applicants Moral hazard occurs after the provision of
the loan when the borrower spends the money on a purpose different to the prescribed
purpose and therefore lowers the probability of repayment This can happen eg by
investing in a more risky project or through spending the money on consumption If the
bank is not able to find a cost effective way to avoid these problems it might raise its
interest rate in order to compensate for the increased risk
Figure 1 Expected Bank Return and the Interest Rate
Source Stiglitz and Weiss (1981) p 394
Since this might discourage low risk borrowers from applying for credit and encourage
borrowers who continue to take loans to invest in riskier projects the share of high risk
168 See Neus (1998) p 85 et sqq
INTEREST RATEI
EX
PE
CT
ED
RE
TU
RN
TO
TH
E B
AN
K
33
borrowers could increase and therefore reinforce the problems stated above Thus
increasing the interest rate beyond a certain point actually leads to a decrease in the
expected return to the lender This context is illustrated in figure 1 with I being the
interest rate which maximizes the expected returns to the bank Obviously the bank
would charge the interest rate I in order to maximize its expected return However this
price for capital was not determined through supply and demand as economic theory
would predict It is conceivable that at the interest rate I the demand for credit exceeds
the supply but even if loan applicants would offer to pay a higher interest rate the bank
would refuse because it associates such a loan with high risk As a result credit might
be rationed169
52 Adaptation to the Microfinance Sector
Through some adaptations this model can also help to explain the lack of funds
provided to low income people In the original model of Stiglitz and Weiss several
assumptions have been made that need to be suspended in order to compare the credit
markets for low and high income people and give an explanation why the latter is
widely neglected by institutional investors
Evidently the assumptions that the amount borrowed is equal for each loan applicant
and that transaction costs170 need not to be taken into account171 are not suitable for this
context While the average loan size of MFI customers is much smaller than that of
clients from traditional banks the transaction costs as a share of the loan are
considerably higher because the lenderrsquos costs for conscientious processing a credit
applications are only slightly smaller for a $50 loan than for a $100000 or a
$10000000 loan
In figure 2 the R(I)large curve represents the return to the bank for large loans with
regard to the interest rate I and the R(I)small curve describes the same correlation for
small loans It is shifts downwards to reflect the assertion that the imperfect information
169 See Stiglitz and Weiss (1981) p 394170 In this paper the term bdquotransaction costsldquo refers to the operating expense ratio as defined by MicroRate It ldquois calculated by dividing all expenses related to the operation of the institution (including all the administrative and salary expenses depreciation and board fees) by the period average gross portfoliordquo See MicroRate and Inter-American Development Bank (IADB) (2003) p 16 171 See Stiglitz and Weiss (1981) p 396
34
paradigm has a more severe effect on poor people than on the better off They are
expected to have less profitable investment opportunities at their disposal172 and
therefore are more likely to invest in riskier projects which increase the probability of
default and hence decrease the expected return to the bank Additionally one might
expect poor people to be more likely than others to spend borrowed money on
consumption instead of an income generating activity particularly if a crisis arises It
seems understandable that food or urgently needed medicine are given priority over
repaying a loan
The second shift downwards is due to transaction costs As stated above they are
relatively higher for smaller loans Obviously transaction costs are incurred in the
provision of a large loan as well but since they are much smaller with regard to the loan
amount they are not included in the diagram for reasons of clarity
Figure 2 The extended Model
Source Own diagram adapted from Stiglitz and Weiss (1981) p 394
172 See Khandker (1998) p 8
INTEREST RATE I
SmallLoans
LargeLoans
Transaction costs
Lack of investment opportunities
R(I)large
R(I)small
EX
PE
CT
ED
RE
TU
RN
TO
TH
E B
AN
K
35
53 Overcoming Credit Rationing for the Microfinance Sector
If the conclusions in chapter 51 hold it is rational for a profit maximizing investor to
neglect the microfinance sector as long as no surplus funds in the market for large loans
exist This finding can help to explain the small amount of money provided to the
microfinance sector from commercial investors On the other hand it has to be stated
that this theory is reflexive as defined by Soros173 It not only explains but also forms
reality since it has the potential to reinforce the view of potential investors that
microfinance is a less profitable business174 Therefore demonstrating under which
conditions microfinance can be profitable and in some cases be more profitable than
traditional businesses is of crucial importance
To provide a fairer view of the microfinance sector a further assumption of the Stiglitz
and Weiss model that needs to be suspended is that all investments made by the
borrowers have the same expected return175 As stated above this contradicts economic
theory which claims ceteris paribus capital productivity decreases while the amount of
fixed capital increases In combination with a low capital endowment micro-enterprises
are usually faced with an excess supply of unskilled labor especially in developing
countries176 Hence small enterprises use far less capital per employee than big business
and therefore their marginal productivity of capital is much higher177 This is intuitive if
one imagines an economic actor who wants to invest several packages of capital
Obviously she would invest the first package where she expects the highest return the
second package where she expects the second highest return and so on Each additional
investment opportunity would lead to lower or at best equal returns178 While this
simplified example has limitations it demonstrates how the marginal productivity of
capital can diminish Although it might actually increase until a certain point179 this can
be expected to be so low in this context that it has no influence on the correlation as
shown in figure 2
173 See Soros (1998) pp 14 et sqq174 See Goodwin-Groen (1999) p 8175 See Stiglitz and Weiss (1981) p 395176 See Perkins et al (2001) pp 95 et sqq177 See Tschach (2000) p 8178 See Rosenberg (2002) p 11179 See Rechard G Lipsey (1979) pp 211 et sqq
36
Figure 3 Marginal Productivity of Capital
Source Dornbusch and Fischer (1995) p 406
Even if good investment opportunities for poor people exist the question remains if it is
possible to distinguish between high and low risk borrowers The problem of adverse
selection is overcome in a cost effective way in many MFIs180 For the better off poor
for example institutions like BRI base their decision on whether or not to approve a
loan by assessing the repayment ability of potential borrowers from their current income
flows and not from the uncertain returns generated by the loan181 Additionally
collateral is used in some cases to attract low risk borrowers182 In contrast to
industrialized countries this is usually not done to cover the potential losses of the
lender but to punish the defaulter and therefore increase her willingness to repay183
Obviously this does not always work for the poorest since they often neither posses any
goods that could work as collateral nor do they have sufficient earnings prior to
obtaining a loan for starting an income generating activity Here the so called group-
lending model can help to identify creditworthy borrowers The most prominent
institution using this approach is the Grameen Bank which only provides credit to
180 See Farrington (2000) p 20181 See Robinson (2001) p 80 Robinson (2002) p 238182 See Bester (1985) p 850 et sqq183 See Schmidt and Tschach (2001) p 15 Robinson (2002) p 244
FIXED CAPITAL 0
MA
RG
INA
L P
RO
DU
CT
IVIT
Y
37
members of a group of five These groups are formed by their members without
interference of the Grameen Bank Although in this particular case no joint liability
exists for the members of the group nobody can receive a new loan if another member
of the group fails to repay on time184 Therefore the group formation work as a
screening process Since the borrowers do not want to risk their ability to obtain further
loans they carefully select with whom to form a group Usually the members know
each other for a long period of time and therefore they can make a meaningful judgment
of each othersrsquo ability to repay the loan Other MFIs even require the members of a
group to mutually guarantee each othersrsquo loans185 While this might further increase
borrowersrsquo efforts to search for trustworthy group members it might also keep potential
borrowers from applying for a loan since she does not want be held responsible for
defaulting members This mechanism enables MFIs to partly pass on the transaction
costs related to the selection of low risk borrowers to the borrowers themselves186
Many MFIs have also largely overcome the problem of moral hazard by creating
incentives to ensure a high repayment rate even among the poorest In some cases their
customers go hungry in order to pay back their loan even though no legal action would
be taken against them if they would refuse to do so187 One way to achieve this is to
build up peer pressure through the formation of groups as described above188 Another
and probably the most important is to limit access to future loans to those borrowers
who repay on time The demand for successive loans is extremely high In a 1996
survey 98 percent of BRI borrowers planed to apply for another loan189 and in 1993
less than 30 percent of Grameen Bank loans went to first time borrowers190 Especially
the poorest highly value the option to reborrow191 and many MFIs see this as their
primary incentive to ensure repayment192 According to Schmidt and Tschach ldquothe net
present value of future access to credit works out to be roughly half the value of the
economic advantage to be gained from the intended non-repaymentrdquo193 This can also
184 See Yunus (1998) p 135185 See Schmidt and Zeitinger (1997) p 6186 See Stiglitz (1990) p353187 Own observation at the Grameen Bank in Bangladesh (2003)188 See Hoff and Stiglitz (1990) p 249189 See Robinson (2002) p 251190 See Khandker Khalily and Khan (1995) p 93191 See Gibbons (2000) p 15 Hashemi and Schuler (1997) p 43192 See Gibbons and Meehan (1999) p 160193 See Schmidt and Tschach (2001) p 16
38
explain the occurrence of a drop in the repayment rate once a MFI is no longer seen as
viable and therefore is not expected to provide loans in the future194
With the help of the described mechanisms MFIs around the world are able to keep
repayment rates high A survey of 69 MFIs from 36 different countries each serving
more than 10000 clients in 2002 found the portfolio at risk (PAR)195 varied between
zero and 231 percent While the average was 36 percent the median was found to be
229 percent196 One of the MFIs included in this sample is BRIs whorsquos 12-month loss
ratio has never exceeded five percent since the start of its transformation in 1984 and
from 1997 to 1998 the ratio actually fell from 22 to 194 percent197 The latter deserves
special attention because the Asian financial crisis reached its peak at that time with
Indonesia being hardest hit as illustrated by a statement from The Economist in July
1998 Even with the fierce competition from its neighbors Indonesia would probably
walk away with the prize for Asias most desperate banking systemrdquo198
The findings that MFIs can adapt their services to low income people in order to ensure
a high repayment rate and that poor people do not lack profitable investment
opportunities are illustrated in figure 4 From this diagram it can be seen that under the
new assumptions the interest rate at which the bank maximizes its return differs for
large (I(l)) and small loans (I(s)) According to the assumption that micro-
entrepreneurs can realize a higher return on their investments the bank can charge them
a higher rate of interest without bearing an increased risk Nevertheless in this example
the bank would still serve the market for large loans first because of the higher
transaction costs for smaller loans
The view as described in figure 4 is shared among most traditional banks and investors
in industrialized as well as in developing countries In addition to neglecting the
possibility of generating profits by offering microcredit themselves199 they also hesitate
to lend to MFIs because they consider their business too risky
194 See Schreiner (1997) p 64195 ldquoPAR shows the real risk of the portfolio by comparing outstanding loan balances for loans with atleast one late payment to the outstanding loan portfoliordquo Gross and de Silva (2002) p 22196 Own calculations See Appendix 2197 See Seibel (2000) p 11198 The Economist (1998) pp 92 et sqq199 Busch and Kort (2004) p 8
39
Figure 4 The extended Model
Source Own diagram adapted from Stiglitz and Weiss (1981) p 394 Tschach (2000)
p 17
This attitude can be observed by comparing the ratio of equity to liabilities which is
considerably higher for MFIs than for conventional banks200 When it comes to MFI
start-ups and those MFIs serving the low end market in remote areas even experienced
microfinance practitioners are skeptical if interest rates that fully recover all costs can
be charged201
Theoretically there are two ways to adjust this model to arrive at a conclusion which is
more favorable with regard to the profitability of microcredit One is to cut the
transaction costs and therefore reduce the downward shift of the R(I)small curve the
other is to allow the bank to further raise the interest rate without experiencing a
decrease in its return This means to increase I(s) and the respective rate of return
While in 2000 Tschach stated that transaction costs vary between 10 and 20 percent for
loans provided through the group lending model and between 15 and 30 percent for
200 See MicroRate and IADB (2003) p 30201 See Volkery (2004) p 33 Gibbons (2000) p 15 Gibbons and Meehan (2002) p 29 Goodwin-Groen (1999) p 8
INTEREST RATE I(l)
SmallLoans
LargeLoans
Transaction costs
I(s)
R(i)large
R(i)small
EX
PE
CT
ED
RE
TU
RN
TO
TH
E B
AN
K
40
individual loans202 it was recommended in 1999 that MFIs should target a range
between 15 and 25 percent203 Some best practices on the other hand have already
achieved single digit numbers Currently BDB might be the most efficient MFI in the
world with transaction costs at just 47 percent in 2001204 Even though the low costs of
BDB have to be acknowledged its achievement has to be put in perspective As stated
above with an average loan balance of more than $5000 it does not serve the low end
market In addition it works in an environment with a high population density which
means that it can reach a relatively large group of borrowers per branch This is a
comparative advantage many Asian MFIs enjoy as can be illustrated by comparing
Bangladesh and Bolivia Both countries are at the forefront of the development of
microfinance in their respective continent but while in Bangladesh more than 1000
people are living per square kilometer the average for Bolivia is only eight205
Therefore it is consistent that the most efficient MFI in Latin America Fondo
Financiero Privado para el Fomento a Iniciativas Economicas has transaction costs of
114 percent206 With an average loan size greater than the annual GDP per Capita this
institution also does not serve the low end market207
Despite the impressive efficiency gains in the described examples most MFIs are far
from achieving these numbers and many are unlikely to reach them due to the
environment within which they work A survey of 67 MFIs from 31 countries found the
average transactions costs in 2002 to be 279 percent with a median of 206 percent208
However even if these institutions were to increase their efficiency to best practice
standards their transaction costs would still be significantly higher than those of
traditional banks providing much larger loans For these banks the respective costs vary
in a range between 05 and 3 percent209 According to this argument charging interest
rates considerably higher than conventional banks is the only way for MFIs to generate
higher returns and hence successfully compete for capital
202 See Tschach (2000) pp 100 et sqq203 See Gibbons and Meehan (1999) p 149204 See M-Cril (2001b) p 4205 See CIA (2004)206 See MicroRate (2004)207 In this paper the term ldquolow endrdquo refers to the definition of the MBB (2003) p 54 Loans worth less than 20 percent of the respective countryrsquos GDP per capita are described that way 208 Own calculations See Appendix 3209 See M-Cril (2004a) p 16
41
6 Interest Rates
61 Setting the right Interest Rate
Before addressing the questions to what extend MFIs can raise their interest rates
without putting the repayment rate or the social benefits of their customers at risk a
basic model will be presented This model will illustrate how a MFI should set their
rates in order to not only cover their costs but also to generate an appropriate profit to
finance further growth and attract additional capital
In 2002 CGAP revised its 1996 paper ldquoMicrocredit Interest Ratesrdquo210 which outlines
the standard method of setting sustainable interest rates for commercially oriented
MFIs According to this model the annual effective interest rate (I) should be calculated
as shown below
(1) I = LL
IIKCFLLTA
minusminus+++
1
With each variable being a decimal fraction of the average outstanding loan portfolio
whereby TA stands for the transaction costs as described above LL represents the
annual loan loss and II stands for investment income eg on liquid assets The cost of
funds (CF) consist of the interest and administrative costs needed to obtain deposits and
commercial loans as well as of the imputed costs on equity due to inflation K stands for
the capitalization rate which represents the net real profit Keeping this rate high is
important to finance the future growth of the loan portfolio This can be either done
through investors attracted by high profitability or through borrowing For the latter an
increase in equity is inevitable since it is required as a safety cushion by lenders
Since this model ignores the timing of cash flows and does not take taxes into account
it has to be regarded as fairly imprecise and hence should not be used for business
planning Nevertheless it can be used for an approximation of the interest rate that a
MFI would need to charge to provide its services as planned In the following I will
210 See Rosenberg (2002) pp 1 et sqq
42
apply this model on a fictitious MFI working in a rural area of Latin America with low
end customers In this setting it seems realistic to estimate transaction costs of 35
percent and loan loss rate of two percent211 If funds were borrowed at commercial
terms their costs can be assumed to equal at least 15 percent of the average outstanding
loan portfolio212 Estimating the capitalization rate is more challenging First the
targeted portfolio growth rate is set at 75 percent This is slightly below the 751 percent
average annual portfolio growth between 2000 and 2002 found by a survey of 25
different MFIs based in Central and South America213 If the extend to which the MFI
can leverage stays constant the loan portfolios growth would be limited by the growth
rate of the equity To express the capital needed for this growth as a share of the loan
portfolio it is necessary to estimate the ratio between the equity and the outstanding
loan amount According to the survey mentioned above the loan portfolios of the 25
Latin American MFIs equal on average 215 times their equity214 With this number the
capital needed to increase the equity by 75 percent would corresponds to approximately
35 percent of outstanding loan amount (075215) Finally the investment income has to
be estimated Since liquid assets that are available short term do not generate high
returns say five percent it does not seem advisable for the MFI to hold more than a
quarter of its loan portfolio in this form Hence the profit generated in this way would
equal 125 percent of the outstanding loan amount Using these numbers the equation to
calculate the annual effective interest rate reads as follows
(2) I = LL
IIKCFLLTA
minusminus+++
1 =
0201
01250350150020350
minusminus+++
= 0875
As a result the MFI would need to charge an annual effective interest rate of
approximately 875 percent on its loans in order to sustainable provide its services and
finance its growth without depending on donor money This rate might decrease once
the MFI matures the growth slows down and cheaper funds become available but it
will stay significantly higher than any rate charged by conventional banks
211 MicroRate and IADB (2004) pp 6 and 16212 See MicroRate and IADB (2004) p 616 and 28213 Own calculation See Appendix 4214 Own calculations See Appendix 5
43
62 Can Micro-Entrepreneurs bear these Rates
Although most MFIs charge rates significantly below 875 percent many critics have
strenuously argued against any rates exceeding those of traditional banks Rosanna
Barbero of Oxfam labeled an interest rate of 52 percent charged by a Cambodian MFI
ldquoludicrous evil and disgusting and stated that ldquo[n]o business in the world can make a
profit at these interest ratesldquo215 The former finance minister of Bangladesh Shah Kibria
even categorized the 20 percent effective rate charged by the Grameen Bank as to
high216 Many practitioners therefore believe in a strong negative correlation between
the interest rate and the demand for loans217 Others have argued more generally that
concentrating on profitability and therefore charging high interest rates diverts MFIs
from serving the poorest218
These views are still shared among many MFI managers donor agencies and especially
investors and politicians While the former are unwilling to charge interest rates for
funds they received ldquocheaplyrdquo (through grants or subsidized loans) and are worried
about undermining their social goals by charging higher rates of interest219 the latter are
reluctant to invest for reasons stated above or impose interest caps to catch the attention
of the public by pretending to protect the poor from usury rates220
In chapter 53 it has been described that micro-entrepreneurs due to their smaller
capital endowment have even better investment opportunities than big business The
extend to which this is true has not yet been answered An indication is the high
repayment rate observed within MFIs around the globe If their customers capital yield
did not exceed the charged interest rate how would they be able to repay According to
Gibbons and Meehan customers of MFIs can generally generate returns of more than
100 percent on their invested capital221 and ldquo[r]esearch in India Kenya and the
Philippines found that the average annual return on investments in microenterprises
215 See Kate and Roeun (2004)216 See Hodson (2001) min 1100217 See Morduch (1999a) p 1594218 See Prisma (2002) p 1219 See Schreiner (1997) p 60 Khandker (1998) p 106 220 See Gross and de Silva (2002) p 32 Jansson and Wenner (1997) p 36 et sqq Campion (2002) p 59221 See Gibbons and Meehan (1999) p 131
44
ranged from 117 to 847 percentrdquo222 Schmidt and Tschach found the marginal
productivity of capital to be as high as 1000 percent for the smallest loans provided by
the Bolivian MFI Caja Los Andes223 These findings are confirmed by the observation
of Rosenberg who found while working as a microfinance consultant for ten years he
never heard of a single MFI having problems to attract clients because interest rates
were too high224
To get a better understanding of the investment opportunities of low income people in
developing countries a typical example on how MFI clients invest their loans is as
follows
Zobair is working as a rickshaw puller in Bangladesh Like most of his colleagues he
does not own the rickshaw he is riding Therefore he has to pay a daily rent of about
$030 to the owner Since his average income of approximately $15 per day is hardly
enough to feed his family he is not able to save the $100 necessary to buy a rickshaw
on his own 225 If he could do so through obtaining a loan his income would increase by
$030 every day because he would not have to pay the rent for the rickshaw anymore
Assuming an average of six working days per week 226 and a life span of the rickshaw
of 5 years his internal rate of return would equal 15324 percent annually227
Consequently any interest rate charged by a MFI would be advantageous to him as long
as it would not exceed 15324 percent228
63 Should the Interest Rate be subsidized anyway
Despite the fact that numerous micro-entrepreneurs are able to generate tremendous
returns on their investment obviously not all are able to use capital in such a productive
way and therefore can not afford microcredit at commercial rates In order to reach
these people as well many MFIs continue to use donor money in order to keep their
interest rates low But even if the problems related to subsidized credit as described in
222 See Helms and Reille (2004) p 3223 See Schmidt and Tschach (2001) p 6224 See Rosenberg (2002) p 10225 This examples draws on observations made by the author in Dhaka (Bangladesh) during 2003226 Obviously extended holidays are not a viable option in this surrounding 227 Own calculation See Appendix 6228 This result is only valid if the loan is repaid in daily instalments For a weekly repayment schedule the interest rate charged by the MFI must not exceed 15119 percent in order to still be beneficial for Zobair
45
chapter 23 do not arise it might still not be the most effective tool to help poor people
as will be illustrated in the following example
A MFI faces two groups of potential clients one with businesses able to generate a
return of 125 percent on borrowed capital and another with a possible returns of 50
percent Assuming budget costs according to equation (2) the institution needs to
charge an interest rate of 875 percent and therefore only serves the former group
Supposed each group consists of 50 members demanding $100 loans the net gains to
society (NGS) could be calculated as follows
(3) NGS = 50 times ($125 ndash $875) = $1875
These gains would be due to the investments of the more profitable group which were
made possible through the loans provided by the MFI The less profitable group would
not borrow since their expected returns are not sufficient to pay for the interest If the
interest rate would be lowered to 30 percent both groups would be able to generate net
gains and therefore borrow from the MFI In order to provide loans at this rate the
institution would need to raise additional capital from non commercial sources The
NGS would be calculated as follows
(4) NGS = 50 times ($125 - $30) + 50 times ($50 - $30) + 100 times ($30 - $875) = 0
While the first terms represent the net gains to the respective groups the last describes
the costs incurred in providing the loans At a rate of 30 percent each loan would need
to be subsidized with $575 Hence the NGS actually fall after the introduction of the
subsidized loan This is due to the fact that the less profitable group is encouraged to
invest in relatively unproductive businesses In addition future growth of the MFI could
be jeopardized due to scarce donor money which is needed to finance the interest rate
subsidy Therefore it seems more advisable to continue to charge a rate of 875 percent
and spend the money used for subsidization on other programs such as health care or
education229
229 In Appendix 7 it will be shown that this result generally holds
46
7 Empirical verification
71 Setting up a Sample
To see if the findings of the previous chapters hold the effects which interest rates
charged by MFIs have on their performance will be analyzed in the following Up to
now such a study does not exist mainly because of a lack of adequate data Most MFIs
do not provide accurate information about the annual effective interest rate they charge
and therefore make an evaluation difficult
In 2002 Rosenberg distinguished eight different categories on how microcredit interest
rates are quoted230 These categories differ in several ways On the contrary to
traditional banks for example it is common for MFIs to state interest rates calculated on
a ldquoflatrdquo balance rather than on a declining one This means that the total loan amount is
used to determine the interest rate ignoring installments paid by the borrowers normally
on a weekly or monthly basis In addition many MFIs charge a certain upfront fee prior
to the loan disbursement require compulsory savings at a lower rate or state their
interest rate for semi annual terms only On the one hand this is done to provide
numbers that are more meaningful to MFI customers who often lack the necessary math
skills to deal with compound interest on the other hand it is done to circumvent interest
rate ceilings imposed by the government231 Another problem is that most MFIs offer
different loan products without itemizing their respective shares to their total loan
portfolio As a result it is not possible to calculate a weighted average even if the rate
stated by the respective MFI could be transformed into an effective interest rate
Usually the portfolio yield is used as a proxy in order to make statements about the
interest rate charged by a certain MFI232 It is generally ldquocalculated by dividing total
cash financial revenue (all income generated by the loan portfolio but not accrued
interest) by the period average gross portfoliordquo233 The advantage of this method is that
even the hidden costs are considered Nevertheless it also has a severe shortcoming by
not taking late or defaulted payments into account Therefore the portfolio yield does
230 See Rosenberg (2002) p 5231 MicroRate (2002) p 8232 See MicroRate (nd)233 MicroRate and IADB (2003) p 39
47
not allow to draw conclusions regarding the correlation between the interest rate
charged by a MFI and its PAR
72 Examining the Sample
Through the appearance of rating agencies specialized in the microfinance sector more
adequate information has become available in recent years While MicroRate only
publishes the portfolio yield of rated MFIs M-Cril Microfinanza Microserve and
Planet Rating actually provide information about the annual effective interest rate for at
least some of the MFIs they analyze Although it is labelled differently from all of the
four institutions234 the term describes what is ldquothe highest income or yield that an
organisation can earn from its portfolio based on the terms of its loansrdquo235
Currently236 reports of 39 different MFIs from 20 countries providing accurate
information about the effective annual interest rate are available to the public This
sample should be used to verify the findings of the previous chapters237 Since a
comparison is made between the performances of MFIs based in different countries and
the ratings have been carried out in different years several adjustments are necessary
First the inflation of the respective country and the respective year(s)238 has to be taken
into account in order to only compare the real rates239 In addition the average
outstanding loan amount per borrower is divided by the respective countryrsquos GDP per
capita Since it can be assumed that ldquoonly the poorer households will be willing to take
the smallest loansrdquo240 this number can be used as a proxy for the poverty level
Although the sample size is far to small to represent the microfinance sector as a whole
and the results are statistically not significant the findings can still be used to underline
the theoretical conclusions drawn in the previous chapters In figure 5 the connection
234 M-Cril uses the name ldquoannual percentage raterdquo See eg M-Cril (2004a) p 25 Microfinanza uses the name ldquoexpected portfolio yieldrdquo See eg Microfinanza (2002c) p 25 Planet Rating uses the name ldquoannual effective interest raterdquo See eg Planet Rating (2004d) p 1 Microserve uses the name ldquotheoretical yieldrdquo See Microserve (2003) p 62235 See M-Cril (2004a) p 25236 As of September 28th 2004237 See Appendix 8 For exchange rates see FXTOP (2004)238 Where necessary a weighted average of the annual inflation rate was used See Appendix 9239 This is done through the following formula ir = (I ndash F) (1 + F100) While ir represents the real annual effective interest rate F represents the inflation rate 240 Morduch (1998) p 1572
48
between the average loan size and the transaction costs as a share of the average loan
portfolio is illustrated
Figure 5 Loan Size vs Interest Rate241
Source Own diagram
000
1000
2000
3000
4000
5000
6000
7000
8000
9000
10000
0 100 200 300 400 500 600
Loan Size
Inte
res
t R
ate
It can be seen that the interest rate is negative correlated to the loans size This can be
explained by the relative higher transaction cost for smaller loans as described in
chapter 52 In order to cover their costs MFIs serving the low end market need to
charge higher rates to their customers than those organizations serving the better off
poor Obviously there are several assumptions to this general finding Especially
striking are the two MFIs with an average loan size of approximately five times their
countries GDP per capita which still high interest rates This occurrence can be
explained by taking a closer look to the respective organizations One was established
less than two years prior to its rating and therefore still bears a lot of start up costs242
241 The equation for the regression line reads as follows Y = -00219X + 365 The correlation coefficient is 014242 See Microfinanza (2002b) p 1
49
the other managed to stay profitable while it almost quadrupled its loan portfolio in the
last two years243
Figure 6 Interest Rate vs PAR244
Source Own diagram
0
5
10
15
20
25
30
35
0 20 40 60 80 100 120
Interest Rate
PA
R
In Figure 6 the crucial correlation between the interest rates charged by a MFIs and its
PAR245 is examined According to the given sample the view of traditional banks and
investors that a higher interest rate leads to a higher default rate does not hold
Obviously one has to avoid to draw the opposite conclusion namely that a high interest
rates decreases the PAR The connection illustrated in figure 6 has to be interpreted as
follows Since high interest rates are related to small loans the low PAR for MFIs
charging high interest rates can actually be explained by the tremendous profitability of
small size investments Despite the high rates their customers are even more likely to
repay
243 See Planet Rating (2003b)244 The equation for the regression line reads as follows Y = -00768X + 68433 The correlation coefficient is 0235245 M-Cril only publishes the PAR for overdues greater than 60 days Therefore these ratios are used as a proxy for the industry standard of 30 days for some Asian MFIs
50
Finally it has to be examined if charging high interest rates actually enables MFI to
generate higher returns Although it can be expected that the combination of a low PAR
and a high interest rate leads to a high profitability it still has to be checked if this is not
outdone by soaring transaction costs Figure 7 illustrates the correlation between the
interest rate charged by a MFI and its financial self-sufficiency (FSS) The latter is the
ldquo[r]atio of total income to total adjusted expenses for the year Adjustments are made
for subsidised cost of funds (relative to market interest rate) equity (with respect to
inflation) and in-kind donationsrdquo246 It can be seen that the regression line actually does
indicate a positive correlation between the interest rate and the profitability of a MFI
Figure 7 Interest Rate vs FSS247
Source Own diagram248
0
20
40
60
80
100
120
140
160
180
0 20 40 60 80 100
Interest Rate
FS
S
246 M-Cril (2004a) p 53247 The equation for the regression line reads as follows Y = 02839X + 8901 The correlation coefficient is 0174248 Since the interest rate the customers of the MFI Foccas have to pay includes fees which are not passed on to the institution its interest rate in this diagram is set at 723 percent instead of the 10715 percent used for figure 6 See Planet Rating (2003b) p 1
51
This result does not necessarily disprove the findings of Stiglitz and Weiss since it can
be argued that MFIs simply do no increase their interest rates to the point where they
would maximize their expected returns But if this would be true why do MFIs not
charge higher rates of interest given the demand described in chapter 41 and 43 In
mature markets competition normally ensures prices not to exceed a certain level but
since many MFIs still operate in a ldquosellerrsquos marketrdquo249 this can not explain the findings
as described in figure 7 Therefore it has to be assumed that a combination of the
unwillingness of many microfinance practitioners to burden their customers with high
interest rates and the plain disbelief of traditional investors that micro-entrepreneurs can
bear those rates is responsible for this occurrence
249 See MicroRate and IADB (2003) p 9
52
8 Conclusions
It has been shown that MFIs are not only contributing significantly to the development
of the financial sector in their respective countries but also that they play an important
role to eradicate poverty by providing much needed capital to low income people which
are able to generate tremendous returns on their investments
The fact that the demand for microcredit is not met is mainly due to the view of most
for profit investors and traditional banks that offering financial services to poor people
can not be done profitable Because of this conviction they hardly invest in the
microfinance sector This does not have to be the case according to the findings of this
paper Although faced with relatively high transaction costs MFIs are able to charge
interest rates at levels that fully recover their costs Elizabeth Rhynersquos claim ldquothat the
most financially viable programs differed from their less viable peers in their
willingness to set interest rates at levels that would fully recover costsrdquo250 is backed by
the findings of this paper that high profitability is correlated to high interest rates
Theoretical models based on the findings of Stiglitz and Weiss can not be used as a
justification to ration credit for the microfinance sector since the interest rate that
maximizes profits to the lender can be assumed to exceed 100 percent for many MFIs
Nevertheless this rate is hardly charged although it has been shown that it can be done
The Mexican MFI Compartamos for example manages to keep its PAR as low as one
percent while charging an effective interest rate of more than 100 percent to
approximately 160000 clients251 In combination with this case the conclusions drawn
from examining the sample of MFIs in chapter 7 the claim of Hulme and Mosley as
stated in the introduction can be considered as wrong MFIs are in fact able to finance
rapid growth stay profitable by charging corresponding interest rates and still have a
significantly positive impact on the poverty level of their clients In the long run gains
in efficiency economies of scale a slowdown in growth and competition will ensure
interest rates drop as it has already been the case in countries like Bangladesh and parts
of Bolivia252
250 See Rhyne (1998) p 7251 See MicroRate (2004)252 See Microrate and IADB (2003) p 9
53
According to a MicroRate survey many MFIs are more profitable than Citibank and also
generate a higher return on investment than commercial banks in their respective
countries253 Investments companies like IMI or Blue Orchard will soon be able to
present a meaningful track record of their microfinance investments to potential
investors Ultimately the capital markets can not ignore the facts proving that it actually
can be profitable to invest in the microfinance sector but in order to raise money
quickly microfinance practitioners will have to continue to intensively promote their
cause not only to for profit investors but also to donors and multilateral agencies like
the World Bank
253 See MicroRate (2002) p 10
54
Appendix
Appendix 1 Average loan balance
Source Data is available through the Mix Market (2004)
Organization
Loan Portfolio 2002 (US$)
Loan Portfolio 2003 (US$)
Number of borrowers 2002
Number of Borrowers 2003
2CM 1263602 1400438 3622 3708ACF 955503 1611401 285 370ACLEDA 26846703 39391301 82598 98905ACME 1460881 1714844 4283 4600ADIM 369065 407798 1122 1395AFK 933306 1706577 250 467AgroInvest 4684249 9697411 5208 9629Al Amana 15593277 28677666 78114 101610AMSSFMC 612167 1040756 6183 6886AREGAK 3285273 3987011 11841 14377AVFS 214331 269819 1883 2866BancoSol 83629049 91175000 42290 56707BESA 10563980 15114430 4488 5061BPR AK 613362 876130 1730 3879BPR BMMS 133949 237946 1755 1779BRI 1344006170 1720072773 3056103 3100358BZMF 1592508 1922097 1250 1331CBDIBA 216587 242465 5764 2877CCA 2146235 4582302 4070 6585CCCP 447534 851678 6265 9450CEP 3795400 5261957 32291 42132CERUDEB 25093643 34873228 34490 44796CMEDFI 227674 250244 3467 3781CMM - Bogota 4836000 8135968 15635 22038CMMB 34880 56964 42 190COAC Maquita Cushunchic
870084 1855718 6603 7732
CODES 280843 263091 60 60CODESARROLLO 6714007 12935951 4391 6896Constanta 2943822 3536047 16134 18588COOPEC CAMEC MN
7152 29821 92 77
Crear - Tacna 3891116 4636094 3671 4948CREDIT 642094 81838 7532 8097CRYSTAL FUND 366456 421403 1379 1061DBACD 3473701 3876526 12812 19606ECLOF - ECU 1154292 728312 860 416ECLOF - MAL 441734 407227 1118 1500EKI 11833244 19245751 8999 13323EMT 4481589 5765281 84781 92173ESED 8579460 6834742 22790 20035
55
Eshet 185741 462569 3308 6540Faulu - KEN 9027332 7206344 17463 15000FDL 12503027 16545332 21306 25106FIE 35818903 41597315 26468 33100FINADEV 5512586 9770323 12775 14709Finance Salone 211312 434298 2225 7159Finca - TAN 1293430 1854834 20648 27499Finca - UGA 2451703 2798869 35610 36912FINCORP 4761288 10236896 941 858FJN 5473563 8037662 8107 11133FMFB 308158 1188896 713 3558FMM -Bucaramanga
6355518 10227000 25814 42464
FODEM 739181 939824 1909 2501FundaciESPOIR
898561 1883446 5911 9464
FUNDESER 798907 1373113 4072 5065Gasha 323748 413742 5504 6423GGLS Save the Children
64235 137957 1291 2362
GK 56986 166971 951 2718HKL 1363365 1420357 6648 5372HOPE 402799 603488 1098 1562IAMD 42132 56550 2780 2772IDECE 21312 39453 150 232IDF 2031944 2626382 31003 36580IMCEC - Dakar 254759 688449 1018 2983IMCEC - Thies 199799 571122 1164 1261
ISSIA 221615 246792 1409 1698JMCC 1962355 2609723 1471 2333KAFC 21710638 29241051 24850 32097KAMURJ 1003935 1411258 5559 5691Kashf 2355965 6271498 29655 59389KMBI 721409 1626666 11973 27266KPSCA 109299 128063 362 794K-Rep 14490447 20699963 38739 45379KSCS 18978 43740 140 297KVT 44075 70621 241 373LAPO 922478 1194633 18740 19139MEC ADEFAP 27788 69248 198 202MEC Bosangani 14357 31086 364 540MEDF 104113 136257 1278 1184Meklit 233170 252232 2084 3577Metemamen 22123 57778 943 1501MFSC 109261 171090 511 687MIKRA 2951028 5008784 4145 6095MIKROFIN 9560502 18380263 5633 7426Miselini 737387 1026639 10182 11431MRFC 11475440 9133130 163000 180000Mushuc Runa 2089076 5418325 3139 6232Nirdhan 2886777 3016171 29589 27457OCSSC 5245186 7658413 42157 6215o
56
Otiv Diana 95992 638422 229 1073Otiv Sambava 188094 437974 2002 1442Otiv Tana 66465 673175 337 1269Partner 9976448 15321304 7139 11935PCA 6878257 6885926 63113 58147PEACE 420746 627295 4192 5428PEDF 164399 254233 2357 3340Piyeli 809447 1206656 8674 4745PRESTANIC 2827502 3540367 1477 2605PRIDE - MAL 991888 854631 5376 5601PRIZMA 3881581 6838978 8112 10968ProMujer -Nicaragua
1006871 1424437 10436 13047
PTF 891566 1068881 8500 9070RBST 818594 1058115 619 723REMECU 1381705 1483471 10330 13996
RUSCA 60887 100820 454 994
SCSCS 89423 157472 873 1007SFPI 709497 903556 7728 9552Sidama 934260 1011798 10267 11346SPBD 117807 186029 647 1740Sunlink 819138 1056823 3401 3833Sunrise 5412366 8782868 4560 7256TEBA 108032426 176300111 163021 157776TIAVO 281978 838905 2049 459TPC 1140429 2267148 22869 31668TSPI 4650989 5383755 49649 75617UNICECAM 3442843 5943804 16039 19031Wasasa 230657 274908 2850 3728Wisdom 1306066 1404463 10524 12054XacBank 4910098 9829503 11063 18610Zakoura 15907288 12444768 103720 118980
Appendix 2 Portfolio at Risk
Source Data is available through the Mix Market (2004)
Organization PAR 2002ABA 202ACEP 464ACLEDA 175ACODEP 452ACSI 209Al Amana 010Apoyo Integral
483
AREGAK 692Banco Solidario
500
BancoSol 660BASIX 1296
57
BRI 437BURO Tangail
350
CEP 200CERUDEB 103CMAC -Sullana
567
CMM -Bogota
176
Compartamos 111Constanta 304Credi Fe 212CREDIAMIGO 409DBACD 010EBS 847EMT 010ESED 1311FADES 2311Faulu - KEN 246Faulu - UGA 096FDL 212FECECAM 428FED 436FIE 598FINADEV 021Finamerica 1133Finca - TAN 000Finca - UGA 297FMM -Bucaramanga
094
FMM -Popayan
088
FONDEP 013FORA 064Genesis Empresarial
1197
IDF 017KAFC 106Kashf 000KMBI 128K-Rep 229MiBanco 309MRFC 1742Nirdhan 373
PADME 079PAMECAS 284PCA 379PRIDE - TAN 018ProMujer -Nicaragua
073
RCPB 600REMECU 157SHARE 000
58
Soluci 182Spandana 014TEBA 106TSPI 355UMU 125UNICECAM 405Urwego 290UWFT 363WAGES 736WWB -Medellin
235
XacBank 061Zakoura 095
Appendix 3 Transaction Costs
Source Data is available through the Mix Market (2004)
OrganizationTransaction Costs
Acci Rural 1154ACEP 858ACLEDA 2430ACODEP 2920ACSI 924Al Amana 2576AREGAK 2856AssEF 1919Banco Solidario
1826
BancoSol 1210BASIX 1317BRI 1353BURO Tangail
2053
CEP 1759CERUDEB 5109CMAC -Sullana
1784
CMM -Bogota
2089
Compartamos 3341Constanta 4597Credi Fe 1978CREDIAMIGO 2525DBACD 1742EBS 2377EMT 3220ESED 1343FADES 1673FAMA 2436
59
Faulu - KEN 2253Faulu - UGA 4962FDL 1726FECECAM 2587FED 4083FIE 1125Finamerica 1563Finca - TAN 10753Finca - UGA 9096FMM -Bucaramanga
1925
FMM -Popayan
1112
FONDEP 5477FORA 3481Genesis Empresarial
1626
IDF 1695
K-Rep 1909LAPO 3511MiBanco 2456Nirdhan 1325NWTF 3109OCSSC 1155PADME 1131PAMECAS 1705PCA 1670PRIDE - TAN 4273ProMujer -Nicaragua
5078
RCPB 2059SHARE 2308Sidama 2662Soluci 2906Spandana 641TEBA 1213TSPI 3898UMU 4023UNICECAM 10120Urwego 7437Wisdom 1906WWB -Medellin
1703
XacBank 4144Zakoura 1881
60
Appendix 4 Portfolio Growth
Source Data is available through the Mix Market (2004)
Organization
Total Loan Portfolio in 2000
Total Loan Portfolio in 2002
ACODEP 5889394 7258487Adelante 4327 88594ADRI 1514681 2591240AgroCapital 11100088 12018280Banco Solidario 39632165 103420000
BancoSol 78031172 83629049CMAC - Sullana 14596365 28055720
COAC Maquita Cushunchic
348443 870084
CODESARROLLO 1374801 6714007Compartamos 10804279 41825248Crear - Tacna 3778816 3891116
Credi Fe 781616 9393936ECLOF - ECU 179247 1154292
FADES 11948814 15501578FAMA 6201411 8835134FIE 22524645 35818903Finamerica 16575104 16097113FINCOMUN 3278938 5696556FMM - Popayan 6241821 12212867
FONDECO 3456625 5101801Genesis Empresarial
11154234 17746288
MiBanco 36964072 95873333Mushuc Runa 90737 2089076ProMujer -Nicaragua
426541 1006871
WWB - Medellin 2891207 4580998
Appendix 5 Portfolio vs Equity
Source Data is available through the Mix Market (2004)
OrganizationLoan Portfolio Equity
ACODEP 7258487 1921447Adelante 88594 72973
ADRI 2591240 781477AgroCapital 12018280 10766101Banco Solidario 103420000 12961000BancoSol 83629049 15299415CMAC - Sullana 28055720 6210291
61
COAC Maquita Cushunchic
870084 260331
CODESARROLLO 6714007 1285103
Compartamos 41825248 18350446
Crear - Tacna 3891116 1016912Credi Fe 9393936 863848ECLOF - ECU 1154292 459226FADES 15501578 4138972FAMA 8835134 6377663FIE 35818903 5360484Finamerica 16097113 3817960FINCOMUN 5696556 1042241FMM - Popayan 12212867 8510494FONDECO 5101801 1658075Genesis Empresarial
17746288 4765816
MiBanco 95873333 24261889Mushuc Runa 2089076 434311ProMujer -Nicaragua
1006871 1196015
WWB - Medellin 4580998 2213249
Appendix 6 Internal Rate of Return
Source Excel (German Version) calculation based on own data
A B C D E F
1 Date Cash Flow
Interest Rate Internal Rate of Return Balance Interest Principal
23 01012004 -100 15324 100 025489547 0045104534 02012004 03 999548955 025489547 0045104535 03012004 03 99909676 02547805 004521956 04012004 03 998643412 025466524 0045334767 05012004 03 998188909 025454968 0045450328 06012004 03 997733247 025443383 0045566179 08012004 03 999826083 050928361 -0209283610 09012004 03 999374595 025485114 004514886
hellip hellip hellip hellip hellip helliphellip hellip hellip hellip hellip hellip helliphellip hellip hellip hellip hellip hellip hellip1562 23122008 03 177951388 000528711 0294712891563 25122008 03 148859724 000908336 0290916641564 26122008 03 119239161 000379437 0296205631565 27122008 03 089543096 000303935 0296960651566 28122008 03 059771337 000228241 0297717591567 29122008 03 029923692 000152354 0298476461568 30122008 03 -3434E-07 000076274 029923726
62
The formula in the square C3 reads as follows
ldquoXINTZINSFUSS(B3B1568A3A156815)rdquo
Appendix 7 Subsidized Interest Rates and the Net Gains to Society
SourceOwn calculations
For simplicity only two groups of potential clients are distinguished This is possible
since using a continuum of potential clients would lead to the same results In addition it
is assumed that the amount of every loan (L) is equal and that all clients invest the
whole loan amount Group H consist of NH potential clients with a rate of return (rH) on
their invested capital higher than the cost recovering interest rate charged by the MFI
(iC) Group L consists of NL potential clients with a rate of return (rL) on their invested
capital lower than iC If the MFI charges iC the NGS can be calculated as follows
NGSC = NH times (rH - iC) times L
Since rH is bigger than iH (rH gt iC) according to the definition presented above the term
NGSH must be positive as long as NH does not equal zero If the MFI introduces a
subsidised interest rate (iS) lower than rL the NGS can be calculated as follows
(1) NGSS = NH times (rH - iS) times L + NLtimes (rL - iS) times L + (NH + NL) times (iS - iC) times L
(2) NGSS = NH times (rH- iC) times L + NLtimes (rL - iC) times L
The term (NH + NL) times (iS - iC) times L describes the amount of money that is needed in order
to subsidize the interest rate to the level iS By setting up an inequation it can be
examined under which conditions the NGSS are bigger than the NGSC
(3) NGSS gt NGSC
(4) NH times (rH- iC) times L + NLtimes (rL - iC) times L gt NH times (rH - iC) times L
(5) NLtimes (rL - iC) times L gt 0
(6) rL gt iC
63
So the NGSS could only be bigger than the NGSC if equation 6 holds This is
impossible since it violated the definitions presented above Therefore the introduction
of subsidized interest rates is always accompanied with a drop in the NGS
Appendix 8 Interest Rate vs Loan Size vs FSS vs PAR
Source Data is available through the Mix Market (2004)
Organization Country
Real Interest Rate
Loan Size (divided by the GDP per Capita) FSS PAR
BTFFKyrgyz Republic 3803 48260 1487 698
BesaFoundation Albania 2184 16076 684 260RFF Albania 1198 5783 4764 277PSHM Albania 2194 000 5758 198Mi-Bospo Bosnia 2974 5499 1261 020Prizma Bosnia 3474 3569 103 064Agroinvest Serbia 2201 4401 875 020KCLF Kazakhstan 5713 1713 865 090
Foccas Uganda10716 (723) 1550 584 29
ACEP Senegal 3280 20941 1643 1Padme Benin 2715 13575 1667 08Papme Benin 3086 53659 1405 24Vital Finance Benin 2676 9394 1015 17Finadev Benin 1738 14850 1024 21ABA Egypt 2579 1613 1168 88ASBA Egypt 2597 1702 1252 68DBACD Egypt 2490 1643 1073 0SBACD Egypt 2500 1734 982 67AMSSF Morocco 6926 787 1306 04Fondep Morocco 5199 650 889 071Zakoura Morocco 4414 900 98 006ENDA Tunisia 4008 1351 110 102BSFL India 1954 3269 856 99Share India 3426 1440 951 0Spandana India 2942 1618 1367 026SWC India 1864 2626 42 3036SKS India 2248 1912 578 0Grama Vidiya India 3176 1221 76 18Sneha India 3451 1433 933 0Buro Bangladesh 3206 1882 1093 17Upap Pakistan 2073 8183 757 03Seeds Sri Lanka 1004 1088 605 287EMT Cambodia 4324 1676 1016 01TPC Cambodia 4470 2035 832 27
64
WTF Phillippines 5816 1095 941 74TSKI Phillippines 5794 777 96 79Cacja Ecuador 862 6189 9460 897ACME Haiti 6043 6934 11685 450Grupo Cama Mexico 8961 267 10717 288
65
Appendix 9 Inflation vs GDP per Capita
Source IMF (2004)
Country Subject Description Units Scale 2000 2001 2002 2003 2004
Albania Gross domestic product per capita current prices US dollars Units 1083988 1238206 1396172 1757778 2229712
Albania Inflation annual percent change Percent 00 31 52 24 34
Bangladesh Gross domestic product per capita current prices US dollars Units 329310 327980 344494 369495 393717
Bangladesh Inflation annual percent change Percent 22 15 38 54 64
Benin Gross domestic product per capita current prices US dollars Units 361340 368213 405951 494725 560129
Benin Inflation annual percent change Percent 42 40 24 15 26
Bosnia and Herzegovina Gross domestic product per capita current prices US dollars Units 1255837 1321429 1466090 1807392 2070508
Bosnia and Herzegovina Inflation annual percent change Percent 50 32 03 02 09
Cambodia Gross domestic product per capita current prices US dollars Units 276413 280352 296577 305940 321247
Cambodia Inflation annual percent change Percent -08 02 33 12 20
Ecuador Gross domestic product per capita current prices US dollars Units 1227711 1590267 1804362 1957183 2082156
Ecuador Inflation annual percent change Percent -77 377 126 79 32
Egypt Gross domestic product per capita current prices US dollars Units 1550982 1461431 1278462 1188060 1083158
Egypt Inflation annual percent change Percent 28 24 24 32 52
India Gross domestic product per capita current prices US dollars Units 454206 458849 472915 542554 602625
India Inflation annual percent change Percent 40 38 43 38 47
Kazakhstan Gross domestic product per capita current prices US dollars Units 1236159 1490946 1655148 2000598 2579554
Kazakhstan Inflation annual percent change Percent 134 83 59 64 68
Kyrgyz Republic Gross domestic product per capita current prices US dollars Units 278256 306130 321079 349632 380637
Kyrgyz Republic Inflation annual percent change Percent 187 69 21 31 45
66
Mexico Gross domestic product per capita current prices US dollars Units 5957486 6274468 6425203 6111754 6377064
Mexico Inflation annual percent change Percent 95 64 50 45 44
Morocco Gross domestic product per capita current prices US dollars Units 1161302 1162154 1199584 1432725 1541041
Morocco Inflation annual percent change Percent 19 06 28 12 20
Pakistan Gross domestic product per capita current prices US dollars Units 437381 400356 440471 492913 538120
Pakistan Inflation annual percent change Percent 44 31 32 29 46
Philippines Gross domestic product per capita current prices US dollars Units 979423 900225 950707 963765 1018710
Philippines Inflation annual percent change Percent 43 61 31 30 54
Russia Inflation annual percent change Percent 208 215 158 137 103
Senegal Gross domestic product per capita current prices US dollars Units 478704 474460 507408 634171 714622
Senegal Inflation annual percent change Percent 09 30 23 -00 08
Serbia and Montenegro Gross domestic product per capita current prices US dollars Units 1031263 1389384 1882036 2491799 2795805
Serbia and Montenegro Inflation annual percent change Percent 699 911 212 113 79
Sri Lanka Gross domestic product per capita current prices US dollars Units 846811 796025 828256 904330 982466
Sri Lanka Inflation annual percent change Percent 62 142 96 63 64
Tunisia Gross domestic product per capita current prices US dollars Units 2034360 2065140 2149421 2534823 2881273
Tunisia Inflation annual percent change Percent 30 19 28 28 34
Uganda Gross domestic product per capita current prices US dollars Units 293404 249682 279587 280802 287204
Uganda Inflation annual percent change Percent 45 -20 57 51 35
67
References
Akerlof George A The Market for ldquoLemonsrdquo Qualitative Uncertainty and the Market Mechanism in Quarterly Journal of Economics Vol 84 (1970) pp 488-500
Amin Ruhul et al Integration of an Essential Service Package (ESP) in Child and Reproductive Health and Family Planning with a Micro-Credit Program for poor Women Experience from a Pilot Project in Rural Bangladesh in World Development Vol 29 (2001) No 9 pp 1611-1621
Bester Helmut Screening vs Rationing in Credit Markets with Imperfect Information in The American Economic Review Vol 75 (1985) No 4 pp 850855
Borst Dietmar Microfinance ndash Theoretische Grundlagen fuumlr den Einsatz sowie die Abschaumltzung des Potentials anhand einer Datenbankuntersuchung zur Verwundbarkeit der laumlndlichen Bevoumllkerung in Vietnam unpublished diploma thesis Karlsruhe 2004
BRAC Annual Report 2002 Dhaka 2003
Busch Alexander Kort Katharina Die Peanuts-Banker und ihre Kunden in Handelsblatt Nr 150 published August 5th 2004 p 8
Campion Anita Challenges to Microfinance Commercialization in Journal of Microfinance Vol 4 (1999) No 2 pp 57-65
Chu Michael Key Issues of Development Finance Somerville (MA) 1998
Dornbusch Ruumldiger Fischer Stanley Makrooumlkonomie Oldenburg 1995
Dunn Seth Flavin Christopher Moving the Climate Change Agenda Forward in State of the World New York London 2002 pp 24-50
Farrington Todd Efficiency in Microfinance Institutions in The MicroBanking Bulletin Issue No 4 pp 18-24
Gardner Gary The Challenge for Johannesburg Creating a More Secure World in State of the World New York London 2002 pp 3-23
Ghatak Subrata On Interregional Variations in Rural Interest Rates in Journal of Developing Areas Issue 18 pp 21-34
Gibbons David Serving the Poorest Sustainably in The MicroBanking Bulletin Issue No 5 (2000) pp 13-16
Gibbons David Meehan Jennifer W The Microcredit Summitrsquos Challenge WorkingToward Institutional Financial Self-Sufficiency While Maintaining a Commitment to Serving the Poorest Families in Journal of Microfinance Vol 1 (1999) No 1 pp 131-192
68
Goodwin-Groen Ruth Do Asian MFIs Access Funds from Commercial Banks inThe MicroBanking Bulletin Issue No 3 pp 8-10
Grameen Bank (ed) Grameen Generalized System Dhaka 2003
Gross Alexandra de Silva Samantha Social Fund Support of Microfinance A Reviewof Implementation Experience The World Bank Social Protection Discussion Paper No 0215 Washington DC 2002
Hashemi Syed M Schuler Sidney R Sustainable Banking with the Poor A Case Study of Grameen Bank Dhaka 1997
Helms Brigit Reille Xavier Interest Rate Ceilings and Microfinance The story so farConsultative Group to assist the Poor Occasional Paper No 9 September 2004 Washington DC 2004
Hoff Karla Stiglitz Joseph E Introduction Imperfect Information and Rural Credit Markets-Puzzles and Policy Perspectives in The World Bank Economic Review Vol 4 (1990) No 3 pp 235-250
Holcombe Susan Managing to Empower The Grameen Bankrsquos Experience of Poverty Allevation Dhaka 1995
Hulme David Mosley Paul Finance against Poverty London 1996
Jalvaani (ed) Flush with loans Micro credit for rural sanitation Vol 2 (1999) No 2 pp 1-2
Khandker Shahidur R Fighting Poverty with Microcredit Experience in Bangladesh Oxford et al 1998
Khandker Shahidur R Khalily Baqui Khan Zahed Grameen Bank Performance andSustainability The World Bank Discussion Paper No 306 Washington DC 1995
Lipsey Rechard G An Introduction to Positive Economics 5th edition London 1979
Littlefield Elizabeth Morduch Jonathan Hashemi Syed M Is Microfinance an Effective Strategy to Reach the Millennium Development Goals Consultative Group to Assist the Poorest Focus Note No 24 Washington DC 2003
Martinot Eric Cabraal Anil World Bank Solar Home Systems Projects Experience and Lessons Learned 1993-2000 in Renewable Energy Oxford 2000 pp 1-8
M-Cril Microfinance Review 2003 revised February 2004 Gurgaon 2004a
Mezzera Jaime Microcredit in Brazil The Gap Between Supply and Demand in The MicroBanking Bulletin Issue No 8 (2000) pp 22-24
The MicroBanking Bulletin (ed) Note to the Reader Vol 1 (1997) Issue No 1 pp 5-8
69
The MicroBanking Bulletin (ed) An Introduction to the Peer Groups and Tables Issue No 9 (2003) pp 53-60
MicroRate IADB Performance Indicators for Microfinance Institutions Technical Guide 3rd edition Washington DC 2003
MkNelly Barbara Dunford Christopher Impact of Credit with Education on Mothers and Their Young Childrenrsquos Nutrition Lower Pra Rural Bank Credit with Education Program in Ghana Freedom from Hunger Research Paper No 4 Davis (CA) 1998
MkNelly Barbara Dunford Christopher Impact of Credit with Education on Mothers and Their Young Childrenrsquos Nutrition CRECER Credit with Education Program in Bolivia Freedom from Hunger Research Paper No 5 Davis (CA) 1999
Morduch Jonathan The Microfinance Promise in Journal of Economic Literature Vol 37 (1999b) No 4 pp 1569-1614
Neus Werner Einfuumlhrung in die Betriebswirtschaftslehre Tuumlbingen 1998
Otero Maria Bringing Development Back into Microfinance Journal of Microfinance Vol 1 (1999) No 1 pp 8-19
Panjaitan-Drioadisuryo Rosintan D M Cloud Kathleen Gender self-employment and microcredit programs An Indonesian case study in The Quarterly Review of Economics and Finance Vol 39 (1999) pp 769ndash779
Perkins Dwight H et al Economics of Development 5th edition New York London 2001
Pitt Mark M Khandker Shahidur R Credit Programs for the Poor and the Health Status of Children in Rural Bangladesh in International Economic Review Vol 44 (2003) No 1 pp 87-118
Raiffeisen Friedrich W The Credit Unions 8th edition Neuwied 1966
Rhyne Elizabeth The Yin and Yang of Microfinance Reaching the Poor and Sustainability in The MicroBanking Bulletin Issue No 2 (1998) pp 6-9
Richardson David C Unorthodox Microfinance The Seven Doctrines of Success in The MicroBanking Bulletin Issue No 4 (2000) pp 3-7
Robinson Marguerite S The Microfinance Revolution Sustainable Finance for the Poor Washington DC 2001
Robinson Marguerite S The Microfinance Revolution Volume 2 Lessons from Indonesia Washington DC 2002
Rosenberg Richard Microcredit Interest Rates Consultative Group to assist the Poorest Occasional Paper No 1 revised November 2002 Washington DC 2002
70
Roth Michael Steinwand Dirk Mikrofinanz Weltweites Erfolgsmodell nur nicht inDeutschland Zur Uumlbertragbarkeit der Erfahrungen aus Entwicklungslaumlndern auf Deutschland Deutsche Gesellschaft fuumlr Technische Zusammenarbeit (ed) Eschborn2004
Schmidt Reinhard H Tschach Ingo Microfinance as a Nexus of Incentives Finance and Accounting Working Paper No 87A Frankfurt 2001
Schreiner Mark A Framework for the Analysis of the Performance and Sustainability of Subsidized Microfinance Organizations with Application to Banco Sol of Bolivia and Grameen Bank of Bangladesh unpublished PhD dissertation Columbus (O) 1997
Seibel Hans D Recent Developments in Microfinance Development Research Center Working Paper No 1998-5 Cologne 1998
Seibel Hans D History matters in microfinance in Small Enterprise Development ndashAn International Journal of Microfinance and Business Development Vol 14 (2003a) No 2 pp 10-12
Seibel Hans D Schmidt Petra How an Agricultural Development Bank Revolutionized Rural Finance The Case of Bank Rakyat Indonesia International Fund for Agricultural Development Rural Finance Working Paper B 5 Rome 2000
Sen Amartya Oumlkonomie fuumlr den Menschen ndash Wege zu Gerechtigkeit und Solidaritaumlt in der Marktwirtschaft Muumlnchen Wien 2000
Serageldin Ismail The View of the Chair in Consultative Group to Assist the Poorest Newsletter Issue No1 (1996) pp 1 11-12
Soros George Die Krise des globalen Kapitalismus Offene Gesellschaft in Gefahr Berlin 1998
Staschen Stefan Regulation and Supervision of Microfinance Institutions State of Knowledge Deutsche Gesellschaft fuumlr Technische Zusammenarbeit (ed) Eschborn 1999
Steinwand Dirk The Alchemy of Microfinance The Evolution of the IndonesianPeoples Credit Banks (BPR) to 1999 and a Contemporary Analysis Berlin 2001
Stiglitz Joseph E Peer Monitoring and Credit Markets in The World Bank Economic Review Vol 4 (1990) No 3 pp 351-366
Stiglitz Joseph E Weiss Andrew Credit Rationing in Markets with Imperfect Information in The American Economic Review Vol 71 (1981) No 3 pp 393-410
Tschach Ingo Theorie der Entwicklungsfinanzierung Mit Kleinkreditprogrammen Kredit- und Arbeitsmarktsegmentierung uumlberwinden Frankfurt 2000
UNDP Human Development Report 2004 New York 2004
71
UNFPA state of the world population 2004 New York 2004
UNICEF The State of the Worldrsquos Children 2002 NewYork Geneva 2002
Varley Robert C G Financial Services and Environmental Health Household Credit for Water and Sanitation Environmental Health Project Applied Study No 2 Washington DC 1995
Volkery Carsten Kampf um Straszligenhaumlndler in Die Zeit Nr 23 published May 27th
2004 p 33
Wardhana Ali Introduction in The Microfinance Revolution ndash Sustainable Finance for the Poor Washington DC 2001 pp XVII-XXVII
Woodworth Warner Woller Gary Greetings from the Editors Journal of Microfinance Vol 1 (1999) No 1 p 6
The World Bank Group World Development Indicators 2004 Washington DC 2004
Worldwatch Institute (2002) Vital Signs 2002 New York London 2002
Wimmer Nancy Barua Dipal Less is more Microfinance for solar energy in rural areas in Renewable Energy World Review Issue 2004-2005 Vol 7 (2004) No4 pp 170-179
Yunus Muhammad Grameen Bank II ndash Designed to Open new Possibilities Dhaka 2002
Yunus Muhammad Grameen ndash Eine Bank fuumlr die Armen dieser Welt Muumlnchen 1998a
Internet References
Abishek Lal (nd) An Overview of Microfinance and Environmental Management [http wwwgdrcorgicmenvironabhishekhtml] (availability date October 5 2004)
ACCION (nd) our history [httpwwwaccionorgabout_our_historyasp] (availability date October 5 2004)
ACCION (nd) key statistics [httpwwwaccionorgabout_key_statsasp] (availability date October 5 2004)
Ahmad Zulfiqar (nd) Forms of Regional Cooperation in Microfinance in South Asia [httpwwwbwtporgarcmpakistanIV_News_and_EventsBWTPworkshopZulfiqar20Ahmad20paper20(BWTP-PMN2029Jan04)pdf (availability date October 6 2004)
72
Ahmed Salehuddin (2003) Foreword [httpwwwpksf-bdorgaprm_summit_brochure htm] (availability date September 30 2004)
Annan Kofi (2002) Statement at The Microcredit Summit +5 [httpwww microcreditsummitorgenews2003-03_sp_chowdhuryhtml) (availability date October 5 2004)
Barnes Carolyn (2001) Microfinance Program Clients and Impact An Assessment of Zambuko Trust Zimbabwe [httpwwwmicrofinancegatewayorgfiles18553_Barnes_Zambuko_Trust_2001pdf] (availability date October 5 2004)
Barnes Carolyn Gaile Gary Kibombo Richard (2001) The Impact of Three Microfinance Programs in Uganda [httpwwwmicrofinancegatewayorgfiles2935_Barnes_2001pdf] (availability date October 5 2004)
Barua Dipal (2004) Success of Grameen Shakti in the Field of Renewable Energy Sector in Bangladesh [httpwwwrenewables2004depptPresentation1-SessionVA(14-1530h)-Baruapdf] (availability date September 30 2004)
Bhatt Ela (1997) In 1975 [httpwwwmicrocreditsummitorgdeclarationhtm] (availability date September 30 2004)
BlueOrchard (2004a) Microfinance [httpwwwblueorchardchenmicrofinance_institutions asp] (availability date October 5 2004)
BlueOrchard (2004b) January 2004 Newsletter [httpwwwblueorchardchmedialibrarywebsitenewsletter_jan_2004pdf] (availability date October 5 2004)
Brynjolfsson John (2004) John Brynjolfsson Discusses Recent Trends in TIPS Issuance [httpwwwpimcocomLeftNavPIMCO+Spotlight2004Spotlight_2_04htm] (availability date October 5 2004)
CGAP (2003) Report to the Board of Executive Directors [httpwww-wdsworldbankorgservletWDSContentServerWDSPIB20031208000012009_20031208101736RenderedPDF27441pdf] (availability date October 5 2004)
Chen Shaohua Ravallion Martin (2004) How have the worldrsquos poorest fared since the early 1980s [httpwwwworldbankorgresearchpovmonitorMartinPapersHow_have_the_poorest_fared_since_the_early_1980spdf] (availability date October 5 2004)
Cheston Susy Kuhn Lisa (2002) Empowering Women through Microfinance[httpwwwmicrofinancegatewayorgfiles3240_Cheston_2002doc] (availability date October 5 2004)
Christen Robert P et al (1995) Maximizing the Outreach of Microenterprise FinanceAn Analysis of Successful Microfinance Programs [httpwwwdecorgpdf_docsPNABS519 pdf] (availability date October 5 2004)
73
CIA (2004) The World Factbook [httpwwwciagovciapublicationsfactbook] (availability date October 5 2004)
Clear Profit (2004) Microfinance Bond Record May Double [httpwwwclear-profitcomissuescpsep04txt] (availability date September 30 2004)
Daley-Harris Sam (2003) State of the Microcredit Summit Campaign Report 2003 [httpwwwmicrocreditsummitorgpubsreportssocr2003SOCR03-E[txt]pdf] (availability date September 30 2004)
Dominiceacute Robert (2004) Interview in Microfinance Bond Record May Double [httpwwwclear-profitcomissuescpsep04txt] (availability date September 30 2004)
Donahue Jill Kabbucho Kamau Osinde Sylvia (2001) HIVAIDSmdashResponding To A Silent Economic Crisis Among Microfinance Clients In Kenya and Uganda [httpwwwmicrosave-africacomget_fileaspdownload_id=541] (availability date September 30 2004)
Donahue Jill Sussman Linda (1999) Building a Multi-Sectoral Response Follow-Up Assessment of Programming for Children and Families Affected by HIVAids in Kenya [httpwwwdecorgpdf_docspnacg778pdf] (availability date September 30 2004)
The Economist (1998) [httpwwweconomistcomdisplaystorycfmstory_id=S2629H3C28Q13F240A] (availability date September 30 2004)
Finca (nd) Introduction [httpvillagebankingorgwhereindexphp3] (availability date September 30 2004)
Fischer Stanley (2003) Statement at The Asia Society and Womens World BankingAnnual Microfinance Conference [httpwwwiiecomfischerpdffischer051303pdf] (availability date September 30 2004)
Friedman Milton (nd) Samuha [httpwwwsamuhaorgm-1htm] availability date September 30 2004)
FXTOP (2004) Historical Exchange Rates [httpfxtopcomdehistoratesphp3] (availability date September 30 2004)
Gibbons David Meehan Jennifer W (2002) Financing Microfinance for Poverty Reduction [httpwwwmicrocreditsummitorgpapersfinancing_finalpdf] (availability date September 30 2004)
Grameen Bank (2004) Grameen Bank At a Glance [httpwwwgrameen-infoorgbankcdshtml] (availability date September 30 2004)
Grameen Trust (nd) Grameen Bank Replication Program [httpwwwgrameen-infoorggrameengtrustreplicationhtml8721] (availability date September 30 2004)
74
Hossain Farhad (2004) Microfinance in Development [httpwwwvalthelsinkifi staff jkoponenb1104FarhadFeb2304pdf] (availability date October 5 2004)
IMF (2004) Data [httpwwwimforgexternalpubsftweo200402datadbginimcfm] (availability date October 5 2004)
IMI (2004) Investments [httpwwwimi-agcomoverviewindexhtml] (availability date September 30 2004)
IPCC (2001) Summary for Policymakers [httpwwwipccchpubspm22-01pdf] (availability date September 30 2004)
Jansson Tor Wenner Mark (1997) Financial Regulation and its Significance for Microfinance in Latin America and the Caribbean [httpwwwgdrcorgicmgoverniadb-janssonpdf] (availability date October 5 2004)
Ken Daniel Ten Roeun Van (2004) The Cycle of Debt - As Microcredit Institutions Grow Some Question Their Effect on Poverty [httpwwwcamnetcomkhcambodiadaily selected_featurescd-21-02-04htm] (availability date September 30 2004)
Kim Julia (2002) Social Interventions for HIVAIDS - Intervention with Microfinance for AIDS and Gender Equity [httpwwwwitsaczaradarPDF20filesIntervention_monograph_no_picspdfpdf] (availability date September 30 2004)
Llanto Gilberto (nd) Vietnam [httpwwwadborgDocumentsBooksCentral_Banks_MicrofinanceCountry_Studiesvietnampdf] (availability date September 30 2004)
The Microfinance Gateway (nd) Frequently Asked Questions [httpwwwmicrofinance gatewayorgsectionfaq1] (availability date October 5 2004)
Microfinance Rating and Assessment Fund (2004) Qualified Raters [httpwwwmfrating orgmfi_institutionsqualified_ratershtml] (availability date October 5 2004)
Microcredit Summit (1997) Declaration and Plan of Action [httpwwwmicrocreditsummit orgdeclarationhtm] (availability date September 30 2004)
MicroRate (nd) Performance Indicators and Ratios [httpwwwmicroratecomENGLISHsiteRATINGSindicatorshtml] (availability date September 30 2004)
MicroRate (2002) The Finance of Microfinance [httpwwwmicroratecomPDFFinance20of20Microfinancepdf] (availability date September 30 2004)
MicroRate (2004) Adjusted comparison table [httpwwwmicroratecomENGLISHsitePDFAdjusted20Comparison20Table060320engpdf] (availability date October 5 2004)
75
Mix Market (2004) The Mix Market [httpwwwmixmarketorg] (availability date October 5 2004)
Morduch Jonathan (1999b) The Grameen Bank A Financial Reckoning [httpwwwwwsprincetonedu~rpdsmacarthurdownloadsmorduch_grameen_bankpdf] (availability date September 30 2004)
Pallen Dean (1997) Environmental Sourcebook for Micro-Finance Institutions [httpwwwacdi-idagccaINETIMAGESNSFvLUImagesea20summaries$fileSOURC Epdf] (availability date September 30 2004)
Prisma (2002) The Case for Private Capital Market Creation in the Development Field of Microfinance [httpwwwsocialenterprisenetpdfsprivate_capital_marketpdf] (availability date September 30 2004)
Schmidt Reinhard H Zeitinger C-P (1997) Critical Issues in Microbusiness Finance and the Role of Donors No 6 [httpwwwgdrcorgicmmfi-donorpdf] (availability date September 30 2004)
Seibel Hans D (2003b) Commodity finance a commercial proposition Micro- and Mesofinance for Agricultural Commodity Production Processing and Trade [httpwwwuni-koelndeew-fakaef05-20042003-420Commodity20Financepdf] (availability date September 30 2004)
Simanowitz Anton Walter Alice (2002) Ensuring Impact Reaching the Poorest while Building Financially Self-sufficient Institutions and Showing Improvement in the Lives of the Poorest Families [httpwwwidsacukimpactPublicationsWorkingPapersOP3MCSSumdoc] (availability date September 30 2004)
Smith Stephen C Jain Sanjay (1999) Village Banking and Maternal and Child Health Theory and Evidence from Ecuador and Honduras[httphomegwuedu~scsmith healthrevwd801pdf] (availability date September 30 2004)
United Nations (1999) International Year of Microcredit 2005 [httpods-dds-nyunorgdoc UNDOCGENN9976933PDFN9976933 pdfOpenElement] (availability date October 5 2004)
United Nations (2000) United Nations Millennium Declaration [httpods-dds-nyunorgdocUNDOCGENN0055951PDFN0055951pdfOpenElement] (availability date October 5 2004)
US Census Bureau (2004) Total Midyear Population for the World 1950-2050 [httpwwwcensusgovipcwwwworldpophtml] (availability date October 5 2004)
WHO (2004) Making pregnancy safer [httpwwwwhointmediacentrefactsheets fs276en] (availability date September 30 2004)
WHO (2001) Child Health [httpwwwwhointmipfiles2082AAGChildHealthpdf] (availability date September 30 2004)
76
The World Bank Group (nd) Health Nutrition and Population and the Millennium Development Goals [www1worldbankorghnpMDGMDG20-20HNPbookletpdf] (availability date September 30 2004)
Yunus Muhammad (1998) Championing the Right to Credit for Poor Women Around the World [httpaspgrameencom dialoguedialogue34interviewhtml] (availability date September 30 2004)
UNAIDS (2004) [httpwwwunaidsorgbangkok2004GAR2004_pdfUNAIDSGlobalReport2004_enpdf] (availability date September 30 2004)
Ratings
M-Cril (2000) SPANDANA [httpwwwratingfundorgspanishdocsSPANDANA_RatingReportpdf] (availability date October 7 2004)
M-Cril (2001a) BASIX [httpwwwbasixindiacomMcrilasp] (availability date October 7 2004)
M-Cril (2001b) BDB [httpwwwratingfundorgspanishdocsRF_BDBpdf] (availability date October 7 2004)
M-Cril (2001c) SNEHA [httpwwwratingfundorgspanishdocsRF_Sneha-u1pdf] (availability date October 7 2004)
M-Cril (2002a) KCLF [httpwwwratingfundorgdocsRF-KCLF-risk20reportdoc] (availability date October 7 2004)
M-Cril (2002b) NWTF [httpwwwratingfundorgspanishdocsRF_NWTFpdf] (availability date October 7 2004)
M-Cril (2002c) SEEDS [httpwwwratingfundorgspanishdocsRF_SEEDS_2002_Ratingpdf] (availability date October 7 2004)
M-Cril (2002c) Share [httpwwwratingfundorgspanishdocsRF_SHAREpdf] (availability date October 7 2004)
M-Cril (2002d) TSKI [httpwwwratingfundorgspanishdocsRF_Tski_mcrilfinal(-) reportpdf] (availability date October 7 2004)
M-Cril (2003a) ASA [httpwwwratingfundorgdocsASA20updatepdf] (availability date October 7 2004)
M-Cril (2003b) BURO [httpwwwm-crilcomburopdf] (availability date October 7 2004)
M-Cril (2003c) EMT [httpwwwratingfundorgdocsEMTpdf] (availability date October 7 2004)
77
M-Cril (2003d) SKS [httpwwwmixmarketorgendemanddemandshowprofileaspett=25ampshowinfo=adjusted] (availability date October 7 2004)
M-Cril (2003d) TPC [httpwwwratingfundorgdocsTPC_Finalpdf] (availability date October 7 2004)
M-Cril (2004b) UPAP [httpwwwratingfundorgdocsUPAP_2004pdf] (availability date October 7 2004)
Microfinanza (2002a) ACME [httpwwwratingfundorgspanishdocsACME_finalpdf] (availability date October 7 2004)
Microfinanza (2002b) BTFF [httpwwwratingfundorgspanishdocsBTFF_RatingReportpdf] (availability date October 7 2004)
Microfinanza (2002c) BESA [httpwwwratingfundorgspanishdocsBESA_RatingReportpdf] (availability date October 7 2004)
Microfinanza (2002d) CAME [httpwwwratingfundorgdocsEvaluacionCAME(-) Finaldoc] (availability date October 7 2004)
Microfinanza (2002e) RFF [httpwwwratingfundorgdocsRFF20finalpdf] (availability date October 7 2004)
Microfinanza (2002f) PSHM [httpwwwratingfundorgspanishdocsPSHM_Reportpdf] (availability date October 7 2004)
Microfinanza (2003) CAJCA [httpwwwratingfundorgdocsCalificacion_Jardin_Azuayo_ratingpdf] (availability date October 7 2004)
Microserve (2003) ENDA [httpwwwmixmarketorgendemanddemandshowprofileaspett=865ampshowinfo=adjusted] (availability date October 7 2004)
Planet Rating (2002a) FONDEP [httpwwwmfratingorgRatingscompleted_ratingshtml] (availability date October 7 2004)
Planet Rating (2002b) PRIZMA [httpwwwmixmarketorgendemanddemandshowprofileaspett=111ampshowinfo=adjusted] (availability date October 7 2004)
Planet Rating (2002c) SWS [httpwwwratingfundorgspanishdocsSWC_reportpdf] (availability date October 7 2004)
Planet Rating (2002d) ZAKOURA [httpwwwratingfundorgspanishdocsRF_Zakourapdf] (availability date October 7 2004)
Planet Rating (2003a) AMSSF [httpwwwratingfundorgdocsPlanetRating_AMSSF_010803pdf] (availability date October 7 2004)
Planet Rating (2003b) FOCCAS [httpwwwratingfundorgdocsPlanetRatingFOCCAS120803pdf] (availability date October 7 2004)
78
Planet Rating (2003c) PADME [httpwwwmfratingorgdocsPlaNetRatingPADME070302_Englishpdf] (availability date October 7 2004)
Planet Rating (2003d) PAPME [httpwwwmfratingorgdocsPAPME_PlanetRating080903pdf] (availability date October 7 2004)
Planet Rating (2003e) VITAL FINANCE [httpwwwmfratingorgdocsVital20Finance_Sept202003pdf] (availability date October 7 2004)
Planet Rating (2004a) ABA [httpwwwratingfundorgdocsABA_April202004pdf] (availability date October 7 2004)
Planet Rating (2004b) ACEP [httpwwwmfratingorgdocsACEPSeacuteneacutegal_2004pdf] (availability date October 7 2004)
Planet Rating (2004c) AGROINVEST [httpwwwratingfundorgdocsAgroInvest_June202004pdf] (availability date October 7 2004)
Planet Rating (2004d) ASBA [httpwwwratingfundorgdocsASBA_April202004pdf] (availability date October 7 2004)
Planet Rating (2004e) DBACD [httpwwwratingfundorgdocsDBACD_April202004pdf] (availability date October 7 2004)
Planet Rating (2004f) FINADEV [httpwwwmfratingorgdocsFinadev_2004pdf] (availability date October 7 2004)
Planet Rating (2004g) MI-BOSPO [httpwwwratingfundorgdocsMIBOSPO_160404pdf] (availability date October 7 2004)
Planet Rating (2004h) SBACD [httpwwwratingfundorgdocsSBACD_PlanetRating300604pdf] (availability date October 7 2004)
Other Sources
Interview Shaw Newaz Deputy General Manager of the Grameen Bank October 30th
2003
Hodson Charles (2001) Your Business Your World Jim Boulden CNN (ed) Dhaka 2001
11
according to political objectives Therefore receiving loans was seen as a reward for the
constituents rather than as a business transaction Most of the funds earmarked for the
poor also never reached them ending up instead in the hands of the local elites
Attracted by the below market interest rates and the possibility not to pay back at all
these groups lobbied to be treated privileged and often used the money received for
consumption or for on-lending at higher rates36 But subsidized credit not only
encouraged corruption it also discouraged sustainable financial institutions since they
could not compete with interest rates that were not aimed to cover all costs and were
sometimes even lower than the interest paid on savings37 The low or negative spread
also worked as a negative incentive to institutionsrsquo effort to mobilize savings which in
turn intensified the problem of credit rationing (see chapter 5)
24 Microfinance Today
In the 1970s a paradigm shift started to take place The failure of subsidized government
or donor driven institutions to meet the demand for financial services in developing
countries let to several new approaches Some of the most prominent ones are presented
below
Bank Dagan Bali (BDB) was established in September 1970 to serve low income people
in Indonesia without any subsidies and is now ldquowell-known as the earliest bank to
institute commercial microfinancerdquo38 While this is not true with regard to the
achievements made in Europe during the 19th century it still can be seen as a turning
point with an ever increasing impact on the view of politicians and development aid
practitioners throughout the world In 1973 ACCION International a United States of
America (USA) based non governmental organization (NGO) disbursed its first loan in
Brazil39 and in 1974 Professor Muhammad Yunus started what later became known as
the Grameen Bank by lending a total of $27 to 42 people in Bangladesh40 One year
later the Self-Employed Womenrsquos Association started to provide loans of about $15 to
36 See Robinson (2001) pp 144 et sqq37 Before BRI underwent a major transformation in 1983 a negative spread between interest rates on loans and savings existed While the bank lent at a 12 annual effective interest rate it paid 15 on savingsSee Robinson (2001) p 10638 Wardhana (2001) p XXVII39 See ACCION (nd)40 See Yunus (1998a) p 16 et sqq
12
poor women in India41 Although the latter examples still were subsidized projects they
used a more business oriented approach and showed the world that poor people can be
good credit risks with repayment rates exceeding 9542 even if the interest rate charged
is higher than that of traditional banks Another milestone was the transformation of
BRI starting in 1984 Once a loss making institution channeling government subsidized
credits to inhabitants of rural Indonesia it is now the largest MFI in the world being
profitable even during the Asian financial crisis of 1997 ndash 199843
In February 1997 more than 2900 policymakers microfinance practitioners and
representatives of various educational institutions and donor agencies from 137
different countries gathered in Washington DC for the first Micro Credit Summit This
was the start of a nine year long campaign to reach 100 million of the world poorest
households with credit for self employment by 200544 According to the Microcredit
Summit Campaign Report 67606080 clients have been reached through 2527 MFIs by
the end of 2002 with 41594778 of them being amongst the poorest before they took
their first loan45 Since the campaign started the average annual growth rate in reaching
clients has been almost 40 percent46 If it has continued at that speed more than 100
million people will have access to microcredit by now and by the end of 2005 the goal
of the microcredit summit campaign would be reached As the president of the World
Bank James Wolfensohn has pointed out providing financial services to 100 million of
the poorest households means helping as many as 500 ndash 600 million poor people47
41 See Bhatt (1997)42 See Yunus (1998a) p 143 et sqq43 See Robinson (2002) p 38044 See Daley-Harris (2003) p 345 ldquoThe Microcredit Summit Campaign defines ldquopoorestrdquo as those who are in the bottom half of those living below their nationrsquos poverty line or are living on less than $1 a day adjusted for purchasing power parity (PPP)rdquo See Daley-Harris (2003) p 3 This definition will also be used throughout this paper46 See Daley-Harris (2003) p 1847 See Morduch (1999a) p 1570
13
3 The Impact of Microcredit
31 Microcredit and the Millennium Development Goals
In 1996 Ismail Serageldin the then chair of the Consultative Group to Assist the Poorest
(CGAP)48 claimed that ldquo[m]icrofinance is a proven instrument to assist the very poorrdquo49
This view is also shared by the World Watch Institute50 and underlines what has been
stated above namely that microfinance can be used as a strong anti-poverty tool But
does microfinance actually meet these expectations and keep this promise51
The impact that microcredit has on the lives of poor people will be demonstrated by
showing how it contributes to each of the eight Millennium Development Goals
(MDGs)52 which are related to the reduction of poverty in all its forms These goals
were resolved in September 2000 by the General Assembly of the UN in their
Millennium Declaration53
32 The Eradication of extreme Poverty and Hunger
The aim of the first MDG is to halve the proportion of people who live on less than $1 a
day between 1990 and 2015 According to current population projections of the World
Bank54 this would equal 849 million people in 201555
48 The Consultative Group to Assist the Poorest is a consortium of 28 public and private development agencies working together to expand access to financial services for the poor in developing countries and was established by the World Bank in 1995 Recently it changed its name to Consultative Group to Assist the Poor49 See Serageldin (1996) p 1150 See Gardner (2002) p 1851 See Morduch (1999a) pp 1569 et sqq52 The Millennium Development Goals are (1) eradicate extreme poverty and hunger (2) achieve universal primary education (3) promote gender equality and empower women (4) reduce child mortality (5) improve maternal health (6) combat HIVAIDS malaria and other diseases (7) ensure environmental sustainability and (8) develop a global partnership for development53 See United Nations (2000)54 See World Bank (2004) p 38 et sqq55 Although it is not explicitly mentioned in the Millennium Declaration it is commonly assumed that the share of people living on less than $1 in low and middle income countries should be halved If the share would be calculated with regard to the worldrsquos total population the goal for 2015 would 818 million people For the worldrsquos total population in 1990 see US Census Bureau (2004)
14
Today almost 11 billion people live on less than $1 and more than 27 Billion live on
less than $2 per day56 The mean income for those living under $1 a day is $077 and it
is $125 for those living under $2 a day57 While the number of people living on less
than $1 per day is slowly decreasing and is expected to be 913 million in 2015 the
number of people living on less than $2 a day is actually increasing58 One of the
outcomes from this degree of poverty is that more than 27000 children die every day
from mostly preventable diseases many of them related to hunger59
Microcredit enables poor people to start new businesses or to diversify existing ones
which helps them to increase their income In addition to large amounts of anecdotal
evidence several studies have documented the positive economic impact microcredit
has on its clients Cloud and Panjaitan-Drioadisuryo have found that the average income
of a sample of BRI borrowers has increased by 112 percent and that 90 percent of their
families have crossed the poverty line60 Only 12 out of the 121 respondents of that
study reported that their income had not increased61 According to the Grameen Bank
website 5109 percent of their clients have crossed the poverty line since they took their
first loan62
A study conducted by Barnes showed that the program of the Zambuko Trust a local
MFI in Zambia had a considerable impact on the poorest clients consumption of meat
fish and chicken63 While 76 percent of the continuing clients of the MFI called Share in
India significantly increased their income and 50 percent have crossed the poverty line 64 Khandker discovered in his well known study ldquoFighting poverty with microcreditrdquo
that there is a connection between the microcredit programs of three Bangladeshi MFIs
and household per capita expenditure For every dollar borrowed by a Grameen Bank
member household consumption increases by $018 In addition he found that 5 percent
56 See Chen and Ravallion (2004) p 2957 In fact those people live on less than $108 and $215 respectively a day in 1993 PPP This means that the nominal dollar value of their income is considerably lower See Chen and Ravallion (2004) p 9 58Both numbers are decreasing in Asia but increasing in the rest of the world See Chen and Ravallion (2004) p 22 et sqq59 See UNICEF (2002) p 660 A consistent definition of the term ldquopoverty linerdquo does not exists among different nations Therefore the term will be used according to the definition of the respective country in this paper61 See Panjaitan-Drioadisuryo and Cloud (1999) p 77562 See Grameen Bank (2004) 63 See Barnes (2001) p 8664 See Simanowitz and Walter (2002) p 16
15
of Grameen Bank borrowers move out of poverty every year65 Supposing Khandkerrsquos
findings were correct for all MFIs worldwide and the Microcredit Summit Campaign
achieved its goal of reaching 100 million of the poorest households with microcredit by
2005 then 25 million people (assuming an average family size of five) would leave
poverty every year66 Although this number would have to be adjusted in order take into
consideration the MFI clients who have crossed the poverty line already and of course
the experiences made in Bangladesh can not be transferred precisely to other countries
it still demonstrates the enormous effect that microcredit can have on assisting the
poorest to move out of poverty
Although a 1996 study of Hulme and Mosley states that providing microcredit can also
have a negative impact on the income of the poorest households67 these findings can
be considered as disproved by the recent bulk of evidence drawing favorable
conclusions68
33 Achievement of universal primary Education
The aim of the second MDG is to ensure that all children will be able to complete
primary school by 2015
Currently more than 100 million children most of them girls are not in school69
Besides school fees poor households often can not afford to send their children to
school because they need them to help in the family business
Microcredit programs mainly contribute to the second MDG by increasing families
income and therefore enabling parents to send their children to school Barnes Gaile
and Kibombo found that clients of an MFI in Uganda spent significantly more on
childrenrsquos education than non-clients70 and in Zambia Barnes showed that ongoing
participation in the Zambuko Trustrsquos program had a positive impact on the members
65 See Khandker (1998) p 5666 See Daley-Harris (2003) p 2467 See Hulme and Mosley (1996) p 180 et sqq 68 See Gibbons and Meehan (1998) p 13669 See UNICEF (2002) p 2270 See Barnes Gaile and Kibombo (2001) p 64
16
children staying in school71 In Bangladesh the probability of girls enrolling in school
increased by 19 percent for every 1 percent increase in Grameen Bank loans to female
clients For boys this number was even higher with the mean being 24 percent72
34 Promote gender Equality and empower Women
The aim of the third MDG is to eliminate the disparity in the ratios of girls to boys in
primary secondary and tertiary education in the ratio of literate females to males and to
increase the share of women in the labor market and in parliament73
At present the literacy rate for women is lower than for man all over the world
According to the Human Development Report 2004 the average female literacy rate as
a percentage of male literacy rate is 759 in developing countries and is as low as 37 in
Niger74 But women are not only discriminated against in education but also in access to
medical services and therefore have a higher mortality rate than man75 The worldwide
tendency for women to be underrepresented in the labor market and in the parliaments is
even more severe in developing countries76 Although several women have become
heads of state in various Asian countries (eg Bangladesh India and Indonesia) this is
probably due to them being wives or daughters of former respected male politicians
Since women have a higher repayment rate than man77 and also tend to invest increases
in income on the household and on their children rather than on themselves78 most
MFIs prefer female clients79 Therefore they empower women in many ways Often
MFIs not only encourage women to become involved in financial transactions for the
first time but also to become independent active members of the economy and to
acquire assets in their own names Cheston and Kuhn found that 68 percent of the
women participating in an MFI program in Nepal ldquohellip experienced an increase their
71 See Barnes (2001) p 8472 See Khandker (1998) p 4973 See World Bank (2001) p 2074 See UNDP (2004) pp 225 et sqq75 See Sen (2000) p 23276 See Sen (2000) pp 242 et sqq77 See Littlefield Morduch and Hashemi (2003) p 778 See Yunus (1998a) pp 116 et sqq79 According to the Microcredit Summit Campaign Report 79 or 37677080 of the poorest clients were women See Daley-Harris (2003) p 3
17
decision-making roles in the areas of family planning childrenrsquos marriage buying and
selling property and sending their daughters to school - all areas of decision making
traditionally dominated by menrdquo80 The program of the Lower Pra Rural Bank in Ghana
had an positive impact on womenrsquos participation in the community81 which is true as
well for the CRECER program in Bolivia82 In Bangladesh the Grameen Bank and the
Bangladesh Rural Advancement Committee (BRAC) the two biggest MFIs of the
country had a significant positive effect on womenrsquos empowerment measured through
eight different indicators83 After joining Grameen Bank only 21 percent of the female
members considered themselves as unemployed while this number was 50 percent
before joining84 According to the Grameen Bank website 93 percent of the Bankrsquos
shares are owned by their borrowers which elect the members of the board every three
years They also get familiar with the election process by more frequently voting for
representatives at the lower level of the organizational structure Partly because of this
experience they are more likely to run for public office In the 2003 local government
elections Grameen Bank members constituted 24 of the seats reserved for women
while they represent less than 10 of Bangladeshi adult female population85 Female
clients of MFIs from countries like the Philippines Bolivia and Nepal have reported
similar occurrences86
35 Reduce Child Mortality and improve Maternal Health
The aim of the fourth MDG is to reduce the under-five mortality rate by two-thirds
between 1990 and 2015 and the fifth MDG strives for a three quarter reduction in the
maternal mortality ratio by the same date
As has been stated above more than 10 million children are dying annually in the
developing world of mostly preventable causes with malnutrition playing a role in over
80 See Cheston and Kuhn (2002) p 1881 See MkNelly and Dunford (1998) p 5482 See MkNelly and Dunford (1999) p 7183 The eight different indicators are ldquofreedom of movement economic security ability to make small and larger independent purchases participation in important family decisions relative freedom from domination by the family political and legal awareness and participation in political campaigning and public protestsrdquo Hashemi and Schuler (1998) p 3684 See Holcombe (1995) p 5185 See Grameen Bank (2004)and CIA (2004)86 See Littlefield Morduch and Hashemi (2003) p 8
18
half of the childrsquos deaths and in over 50 countries child mortality rates are greater than
100 deaths per 1000 live births87 Maternal mortality is also a significant problem in the
developing world with more than 500000 women dying every year from pregnancy
related causes88
MFIs are mainly contributing to the these MDGs by increasing families income and
therefore enabling the households to afford better nutrition and medical services
Furthermore they are often linked with microinsurance or health education programs
In addition to what has been showed in chapter 31 Pitt Khandker and Millimet
estimate that a 10 percent increase in the loan size of a female borrower in Bangladesh
increases the arm circumference of their daughters by 6389 Smith and Jain found that
village banking in Ecuador had a positive effect on child diarrhea90 which is responsible
for 15 of child deaths91 Since Sen argues that an improved status of women within
the family reduces child mortality92 the empowerment of women through MFIs is also
contributing to this cause
Although no study has been conducted so far on the direct impact of microcredit on
maternal health it can be assumed that an overall improvement of access to medical
services reduces maternal mortality as well A study of the Morgan State University for
example suggests that microcredit has a positive effect on the prevalence of
contraceptives93 which leads to a decrease of unwanted pregnancies and therefore
reduces maternal death
36 Combat HIVAIDS Malaria and other diseases
The aim of the sixth MDG is to halt and begin to reverse by 2015 the spread of
HIVAIDS malaria and other major diseases and to assist children orphaned by HIV
87 See World Bank (2001) p 888 See WHO (2004) 89 See Pitt Khandker and Millimet (2003) p 11390 See Smith and Jain (1999) p 3791 See WHO (2001) 92 See Sen (2000) p 23593 See Amin et al (2001) p 1614
19
In 2003 29 million people died because of HIV and about 48 million became infected
the greatest number since AIDS was discovered 23 years ago94 This pandemic has lead
to a tremendous decrease in the life expectancy in the hardest hit countries Botswana
for example one of the richest and most democratic countries in Africa has a
HIVAIDS adult prevalence rate of 388 and a life expectancy at birth of less than 31
years95
Malaria not only causes more than one million deaths annually it leads also to 300 ndash
500 million clinical cases a year Both numbers have been steadily increasing over the
past two decades96 More than two million people a year are killed by tuberculosis
another global health problem This curable disease is estimated to cost poor
communities about $12 billion every year since even those who survive normally lose
more than 3 month of work time while recovering97
MFIs contribute to the sixth MDG in several ways By increasing clientrsquos income they
help households affected by HIV or other diseases to better cope with the situation
Besides spending more money on health services and nutrition MFI clients also tend to
be more able and willing to support AIDS orphans than non clients98 In addition to the
already stated increase in the use of contraceptives99 several innovative approaches to
deal with disease related crisis have also arisen This is of course necessary not only to
counteract the devastating effect the above discussed epidemics can have on MFI
clients but also to not put the viability of the respective institution at risk One option is
to integrate education services in the MFI programs and encourage clients to form
solidarity groups100 It has been shown that these services do not necessarily decrease
the effectiveness of the institutionsrsquo employees101 Another way is to strengthen the ties
to NGOs specialize in dealing with the respective disease Synergies gained through this
cooperation can help clients to better deal with the situation and in the end increase their
94 See UNAIDS (2004) p 2395 See CIA (2004)96 See World Bank (2001) p 1697 See World Bank (2001) p 1298 See Barnes (2001) p 6499 See also Kim et al (2002) p 18100 See Donahue and Sussman (1999) p A 14101 See Donahue Kabbucho and Osinde (2001) p 25
20
repayment rates Various MFIs also have introduced loan and health insurance products
or cultivated linkages with organizations doing so102
It has to be stated that despite the benefits MFIs can provide to people effected by
HIVAIDS or other diseases microcredit can also be a burden for those who are already
chronically ill These people can still benefit through loans provided to members of the
family or the community or through one of the other services mentioned above
37 Ensure environmental Sustainability
The aims of the seventh MDG are to support and promote the principles of sustainable
development and put them into action and to improve the lives of slum dwellers and
people without sustainable access to safe drinking water and sanitation
Today climate change is considered as the major environmental problem103 The
Intergovernmental Panel on Climate Change (IPCC) states that human activities
contribute to most of the 06 degC increase in global average temperature over the 20th
century and the predicted increase of another 14 to 58 degC between 1990 and 2100104
Emission of carbon from fossil fuel is reported to have the dominant influence on this
development While the total emission was 16 billion tons in 1950 it was already 65
billion tons in 2000 and is expected to continue to grow105 This development would
lead to a rise in the average sea level of between 9 and 88 centimeters during the next
century106 Furthermore it is predicted that global warming increases the risk of extreme
events like cyclones or floods leads to an increase in the number of people infected by
diseases like malaria and decreases the potential crop harvest and water availability
especially in developing countries107 In 2000 already 11 billion people lacked access to
clean drinking water and 24 billion to basic sanitation108
102 See Barnes (2001) p 40 Barnes Gaile and Kibombo (2001) p 13 and Grameen Bank (2004)103 See Gardner (2002) p 5104 See IPCC (2001) pp 2 et sqq105 Worldwatch Institute (2002) p 52 et sqq106 See IPCC (2001) p 16107 See Dunn and Flavin p 29108 See UNFPA (2004) p 18
21
MFIs contribute to achieving the seventh MDG in several ways By providing loans for
the purchase of renewable energy technologies they help people in developing
countries to increase their per capita energy consumption without increasing the carbon
dioxide emission In a 2003 survey of 140 MFIs from 80 different countries 21 said
they provide credits for solar home systems and another 19 stated they are interested in
becoming engaged in this business109 While Grameen Shakti a rural energy service
company cooperating with the Grameen Bank in Bangladesh has already installed more
than 23000 solar home systems110 a 2000 World Bank study reports twelve projects
providing solar home systems to rural households with a target of 500000
installations111 It has also been suggested that MFIs should raise environmental
awareness among their clients112 but so far no data is available on how staff can cope
with this additional task Many MFIs also provide loans for improvements in sanitation
and the water supply of their clients Varley gives several examples from Africa Asia
and Latin America on how microcredit not only has helped to invest in rainwater
collection systems but also how it has enabled households to increase their water
supply through community water associations113 In addition many MFIs provide credit
for the construction of sanitary latrines114 The situation of slum dwellers is also
positively effected by MFIs Directly through their services in poor urban communities
and indirectly by creating jobs in rural areas and therefore easing the pressure on urban
labor markets
38 Develop a global Partnership for Development
The eight MDG is about the means to achieve the other seven MDGs It calls for all
players involved in the endeavor of development and poverty eradication to work as
partners in a global context
Again MFIs are contributing to the eight MDG in many ways This is occurring through
international networks that provide funding and technical assistance through internet
information portals and specialized journals through social and for profit investors and
109 See Wimmer and Barua (2004) p 174110 Barua (2004) 111 See Martinot and Cabraal (2000) p 6112 See Pallen (1997) p 11 Lal (nd)113 See Varley (1995) pp 39 et sqq114 See Jalvaani (1999) pp 1 et sqq Varley (1995) pp 39 et sqq
22
specialized rating agencies The Bangladesh-based Grameen Trust is one of around 30
networks in operation Besides collaborating with over 200 MFIs around the world it
has directly operated three projects in Afghanistan Kosovo and Myanmar115 While the
ACCION network serves almost 12 million active clients in 19 countries throughout
America and sub-Saharan Africa116 FINCArsquos network operates in three different
continents where it serves more than 200000 customers117 In November 1997 the
MicroBanking Bulletin (MBB) was first published by the microfinance program at the
Economic Institute at the University of Colorado118 Its aim is to develop a database on
the financial performance of MFIs from all over the world which is now available
through the Mix Market an internet portal that also provides information about more
than 300 MFIs investors donor institutions and other related development
organizations119 Two years later the Marriott School at Brigham Young University
started to publish the Journal of Microfinance which has an editorial board of
microfinance experts from all over the world and offers the latest research on this
topic120 In the late 1990s a number of companies became attracted by the microfinance
market and started to invest in MFIs The German based Internationale Mikro
Investitionen Aktiengesellschaft (IMI) for example has already invested more than euro46
million in 19 MFIs in four different continents and plans to invest another euro27 million
before October 2004121 BlueOrchard Finance a microfinance investment consultancy
has channeled more than $60 million worth of private capital to some 40 MFIs
worldwide through investment funds and bond issues122 Big commercial banks like
Citigroup Deutsche Bank and ABN Amro also started to get involved in the
microfinance sector although this is mainly still perceived as a public relation activity
and not as a for-profit investment123 There are also several rating agencies specializing
in MFIs Dependent on their rating these institutions can help MFIs to receive money
from donors or investors Four of the most prominent rating agencies are PlanetFinance
115 See Grameen Trust (nd)116 See ACCION (nd)117 See FINCA (nd)118 See MicroBanking Bulletin (1997) p 5119 See The Mix (2004)120 See Woodworth and Woller (1999) p 6121 See IMI (2004)122 See BlueOrchard (2004b) p 3123 See Busch and Kort (2004) p 8 Fischer (2003) p 6
23
with headquarters in France M-Cril based in India Microfinanza in Italy and
MicroRate with offices in the USA and South Africa124
124 See Microfinance Rating and Assessment Fund (2004)
24
4 Microcredit Outreach
41 The Demand for Microcredit
Although it has been shown that microcredit is one of the most effective poverty
eradication tools that it is considered a human right by some of its advocates125 and it
can contribute considerably to the development of the financial sector in developing
countries an enormous gap still exists between supply and demand for microcredit
Estimates on the demand for microcredit vary greatly While USAID estimates the
number of potential microfinance clients is between 100 and 200 million126 the
Microcredit Summit Campaign states the total demand is more than 234 million
people127 CGAP recognizes some 500 million micro-entrepreneurs who have the
potential to become customers of MFIs128
Marguerite Robinson calculates the demand as follows ldquoAssuming five people to a
household among the 45 billion people living in low- and lower-middle-income
economies in 1999 (World Bank World Development Report 20002001) there are 900
million households in those economies If estimating conservatively we assume that
informal commercial moneylenders supply credit to 30 percent of these households at
least once a year this would mean that there are 270 million households borrowing
from informal moneylenders in a year Undoubtedly however many of these
households borrow multiple times within a yearrdquo129 Although this is a very rough
estimate assuming big differences in demand for microcredit in different countries the
number seems to be the most meaningful In contrast to the estimate of the Microcredit
Summit Campaign it does not include every single household living on less than $1 a
day but according to the definition presented in chapter 1 it counts everyone who has
no regular access to traditional financial institutions but demands such services
Obviously not all people who draw on moneylenders have financial needs that could be
matched through MFIs On the other hand interest rates charged by moneylenders tend
125 See Yunus (1998b) 126 See Christen et al (1995) p 15127 See Daley Harris (2003) p 22 128 See Robinson (2001) p 26129 See Robinson (2001) p 215
25
to be considerably higher than those of MFIs The former normally charge effective
monthly rates between ten and several hundred percent per month the latter generally
charge between 15 and five percent which enables them to attract additional clients130
42 The Supply of Microcredit
In spite of the impressive growth of MFIs around the world the demand for microcredit
is far from being met and this it is not likely to change in the near future The
Microcredit Summit Campaign reported that by the end of 2002 67606080 clients131
were reached through MFIs and that this number has increased by almost 40 percent
annually for the last five years132 It is likely that this tremendous speed of growth is at
least partly due to including MFIs which have not been reporting to the Campaign from
its start in 1997 although they have already existed at that time These institutions
contributed 22 percent to the growth in poorest clients in 2000 578 percent in 2001 and
338 percent in 2002 The growth of the poorest clients increased at least party because
of an expanded definition of the term ldquopoorestrdquo133 Since the contribution of MFIs
which previously have not been considered can be expected to decrease dramatically
the growth rate as stated by the Microcredit Summit Campaign can not be used to
predict the future development of the microfinance sector Another factor likely to slow
down the growth is the concentration of microfinance activities in some Asian countries
where almost 90 percent of the poorest microfinance clients live today134 Even if one
takes into consideration the relative size of Asiarsquos population and the fact that many
MFI customers in Latin America are relatively better off and therefore are not included
in this numbers the coverage of this part of the world far exceeds the others In
Bangladesh for example the microfinance market is close to saturation More than
eleven million households were served by several hundred MFIs in 2001135 Among
them are Grameen Bank and BRAC two of the best known MFIs in the world both
providing their services to more than three million customers With an average
household size of five it can be assumed that in Bangladesh the number of people
130 See Gibbons and Meehan (1999) pp 144 et sqq131 41594778 of them belonged to the poorest before they took their first loan The relative numbers in the following are for these poorest clients only since no other current data was available It can be assumed though that this works as a good proxy for the total number of clients 132 See Daley Harris (2003) p 3133 See Daley Harris (2003) p 17134 See Daley Harris (2003) p 21135 See Ahmed (2003)
26
benefiting from microcredit already surpasses the number of people living below the
poverty line which is estimated to be slightly higher than 50 million136 Therefore
Bangladesh will not contribute to the growth of the microfinance sector as much as it
has done in previous years This is also true for Vietnam Thailand and to a lesser
extent Indonesia Eight of the nine MFIs serving more than one million clients are based
in these countries while the ninth is based in India where due to its one billion
inhabitants the microfinance market is still far from saturation137 In contrast the
supply in Brazil meets less than two percent of the demand which is estimated to be
about 58 million potential clients138 For these reasons greater amount of future growth
must come from smaller or new MFIs in Latin America India China and especially
Africa where almost 30 percent of the worldrsquos poorest live139
43 Meeting the Demand
To fill the gap between the demand and supply for microcredit tremendous investments
are necessary to increase the loan funds of MFIs and build up their capacity through
upgrading existing institutions or building new ones Again estimates on how much
capital is needed vary greatly with the highest being at more than $300 billion140
In 1997 the Microcredit Summit Campaign estimated that $216 billion would be
needed to achieve their goal of providing microcredit to 100 million of the poorest
households This was calculated in the following way Since some 8 million people
already received microcredit in 1997 another 92 million needed to be reached
Assuming $200 ($150 for loan fund and $50 for capacity building) would be needed per
person for 88 million people in developing countries and $1000 ($500 for loan fund and
$500 for capacity building) would be needed for 4 million people in industrialized
countries the capital required ends up to be $216 billion141 For several reasons this
136 See CIA (2004)137 These institutions are The Grameen Bank BRAC Proshika and the Association for Social Advancement (ASA) in Bangladesh the Vietnam Bank for Agriculture and Rural Development (VBARD) and the Vietnam Bank for the Poor (VBA) in Vietnam BRI in Indonesia Bank for Agriculture and Agricultural Co-operatives (BAAC) in Thailand the National Bank for Agriculture and Rural Development (NABARD) in India See Ahmed (nd) p 1 Llanto (nd) p 337138 See Mezzera (2002) p 23139 See See Chen and Ravallion (2004) p 29140 See Clear Profit (2004) Prisma (2002)141 See The Microcredit Summit (1997)
27
number is not qualified to predict the total amount of capital needed to meet the demand
for microcredit On the one hand it focuses mainly on the low end of the market and
therefore underestimates the average loan fund needed On the other hand it does not
take the increasing capital demand from established MFIs into account A survey of 119
MFIs found that the average loan size to increased from $406 in 2002 to $498 in
2003142 This is mainly due to the fact that MFI clients once they have paid back their
loans usually demand larger ones for the continual development of their businesses
and therefore further increase the demand for capital of established MFIs The Grameen
Bank for example has a ceiling on its loans which increases or decreases depending on
the borrowers performance regarding repayments and savings143 While the maximum
amount for the first loan is fixed at approximately $75144 the largest loan disbursed so
far was $17195145 Thus if one estimates that by now 100 million people are borrowing
from MFIs146 another 170 million need to be reached to meet the estimated demand
Assuming an average of $600 ($400 for loan fund and $200 for capacity building) is
needed for every new client and another $200 is needed for every existing client to meet
the demand for larger loans a total of $122 billion is required This rough estimate
helps to convey the approximate amount of capital needed to meet the demand for
microcredit
So far the demand for funds is being partly met by donors which annually provide
between $500 million and $1 billion147 and through the mobilization of local savings
Obviously the amount of money provided by donors will not be able to meet the capital
demand for microcredit in the short term The mobilization of savings on the other hand
has been extremely successful in some cases with BRI probably being the most
prominent example After adapting commercial principals in October 1984 BRI was
able to raise its deposits from $161060 to more than $32 billion in 2003 which equals
almost two times its current loan portfolio148 Many other MFIs like BDB in Indonesia
142 Own calculations Without BRI the numbers would be $343 and $409 See Appendix 1143 See Grameen Bank (2003) p 13144 The accurate amount is 5000 Taka See Interview with Shaw Newaz145 Grameen Bank (2004)146 According to the data provided by the Daley Harris (2003) an annual increase in MFI clients ofapproximately 25 percent from 31122002 till the 3092004 would be needed to reach 100 million clients by now This rated is considerably below the average of the previous five years (38 percent) Therefore it can be assumed as realistic despite the growth hindering factors presented above147 See CGAP (2003) p 8148 See Robinson (2002) p 273 Mix Market (2004)
28
XacBank in Mongolia the Equity Building Society in Kenya or the Centenary Rural
Development Bank in Uganda also have managed to cover their loan portfolio fully
through internally mobilized resources149 The Grameen Bank is also expected to do so
in the first half of 2005150 In addition to raising much needed capital for on-lending the
provision of saving services can deliver notable social benefits itself151
Despite these impressive achievements even the combination of donor money and local
savings at their current levels will not be able to provide the capital needed to continue
the rapid growth of the microfinance sector Especially in their early years MFIs rely on
outside funding BRI for example needed six years before the amount of locally
mobilized savings surpassed the total amount of outstanding loans During this time
expenses and the loan portfolio were covered through a government grant worth $20
million and two World Bank loans of $5 and $97 million respectively152 It also
benefited from a network of more than 3600 branches which were established
throughout the country during the 1970s and early 80s in order to provide government
subsidized credit in rural areas153
The Grameen Bank also widely known as a best practice MFI has received about $175
million in direct and indirect subsidies between 1985 and 1996154 and continues to rely
on outside funding at below market interest rates This is made possible either through
special loans from the Bangladesh Bank or through offering bonds guaranteed by the
Bangladesh government155 - an option most MFIs do not have BDB might be one of the
very few examples which were able to finance their activities through savings and
commercial loans from the start but its outreach did not reach a large scale nor did it
serve the low end of the market In 2000 after 30 years of operation BDB provides
credit to only 10417 clients with an average loan balance of more than $5000156
approximately eight times the countries GDP per capita157
149 See Mix Market (2004)150 See Grameen Bank (2004)151 See Robinson (2001) pp 263 et sqq152 See Seibel and Schmidt (2000) p 4153 See Robinson (2002) p 180154 See Morduch (1999b) p 8155 See Morduch (1999ba) p 25 et sqq156 See Robinson (2002) p 387157 See CIA (2004)
29
Another problem keeping many MFIs from collecting savings is that they do not want
to become a regulated financial institution or do not meet the criteria in their respective
country and therefore they are simply not allowed to mobilize savings from the public
In summary the examples and numbers presented in this chapter support the argument
that the amount of capital that can be raised through donors and locally mobilized
savings is not enough for continuous rapid growth of the microfinance sector If this
lack of capital is not met through other sources the microfinance sector will fail to
contribute its full potential to the achievement of the MDGs
44 Microfinance and the Capital Markets
Regardless of whether the amount of capital needed for the development of the
microfinance sector is $20 or $300 billion it represents only a tiny fraction of the
worldwide capital markets which are estimated at $30 trillion158 Therefore if the
microfinance industry were able to tap the financial markets it would be able to grow
much faster and soon serve the millions of micro-entrepreneurs which currently can not
develop theirs businesses because of capital constrains Another advantage would be
that scarce donor money currently used for the development of the microfinance sector
could be used for other projects that do not have the potential to draw money from
commercial sources This view is shared by Michael Chu the former CEO of ACCION
who made the following statement in 1998 ldquoMicrofinance today stands at the threshold
of its next major stage the connection with the capital marketsrdquo159 Many attempts have
been made since that time Successful MFIs like BancoSol in Bolivia further
strengthened their ties to the capital markets which in some cases already provide the
majority of their funding160 Microfinance investment advisors like BlueOrchard
Finance have become middlemen for MFIs and the financial markets Nevertheless
these links are still far from reaching major scale Currently only approximately 20
percent of MFIs funding comes from commercial sources161 and the biggest bond issue
dedicated to fund MFIs totals only $40 million In addition these funds mainly end up
158 See Brynjolfsson (2004) 159 Chu (1998) quoted in Robinson (2001) p 23160 See Robinson (2001) p 69161 See Dominiceacute (2004)
30
in established institutions in Latin America or Eastern Europe162 while smaller
organizations only benefit indirectly if at all
162 See Clear Profit (2004) IMI (2004)
31
5 Credit Rationing
Until recently the predominant answer to why commercial banks or venture capital
companies did not invest in the microfinance sector was that the poor are not bankable
Besides lacking education and therefore not being able to deal with formal financial
institutions they were viewed as bad credit risk who were unable to invest the borrowed
money in a way that would allow them to repay the loan and interest at a commercial
rate163 Another reason that kept attention away from the idea of providing financial
services to low income people was the belief that informal moneylenders already met
this demand These skeptics felt affirmed through the poor performance of subsidized
credit programs as described in chapter 22 Although it is true that moneylenders
serve a huge number of people in the developing world they more often than not charge
usury interest rates of up to 20000 percent per month164 While the argument that poor
people are not able to participate in the formal financial market can be overcome by
adapting the services accordingly165 the claim of low returns on their investments is not
only proved wrong by empirical evidence but also contradicts economic theory as will
be shown in chapter 53
51 The imperfect Information Paradigm
A more elaborate explanation for the short supply of financial services to low income
people that can be derived from the imperfect information paradigm based
predominantly on the works of Akerlof166 and Stiglitz and Weiss167 After giving a brief
summary of their argument an adaptation of their findings to the microfinance market
will be presented and subsequently it will be shown how their conclusions can be
overcome
Behind the imperfect information paradigm lies the theory of asymmetric information
which simply states that if two parties conduct a transaction one is likely to have more
163 See Ghatak (1983) p 21 et sqq Yunus (1998) p 102 et sqq Robinson (2001) p 35 et sqq164 See Robinson (2001) p 17165 See Seibel (2003b) p 2 BRAC (2003) pp 15et sqq Yunus (1998) pp 151 et sqq 166 See Akerlof (1970) pp 488 et sqq167 See Stiglitz and Weiss (1981) pp 393 et sqq
32
information than the other and is trying to use that for its own advantage168 Applied to
the banking sector this means that a person applying for credit can better judge the
likelihood of repaying the loan than the bank This is because the borrower has better
knowledge of the market she wants to invest in her skills and her willingness to repay
Moreover the bank might not be able to observe if the borrower uses the loan for the
agreed purpose These occurrences can lead to what is known as adverse selection and
moral hazard In this case adverse selection refers to the problem that banks might
attract borrowers with a low probability of repayment if they can not distinguish
between high and low risk loan applicants Moral hazard occurs after the provision of
the loan when the borrower spends the money on a purpose different to the prescribed
purpose and therefore lowers the probability of repayment This can happen eg by
investing in a more risky project or through spending the money on consumption If the
bank is not able to find a cost effective way to avoid these problems it might raise its
interest rate in order to compensate for the increased risk
Figure 1 Expected Bank Return and the Interest Rate
Source Stiglitz and Weiss (1981) p 394
Since this might discourage low risk borrowers from applying for credit and encourage
borrowers who continue to take loans to invest in riskier projects the share of high risk
168 See Neus (1998) p 85 et sqq
INTEREST RATEI
EX
PE
CT
ED
RE
TU
RN
TO
TH
E B
AN
K
33
borrowers could increase and therefore reinforce the problems stated above Thus
increasing the interest rate beyond a certain point actually leads to a decrease in the
expected return to the lender This context is illustrated in figure 1 with I being the
interest rate which maximizes the expected returns to the bank Obviously the bank
would charge the interest rate I in order to maximize its expected return However this
price for capital was not determined through supply and demand as economic theory
would predict It is conceivable that at the interest rate I the demand for credit exceeds
the supply but even if loan applicants would offer to pay a higher interest rate the bank
would refuse because it associates such a loan with high risk As a result credit might
be rationed169
52 Adaptation to the Microfinance Sector
Through some adaptations this model can also help to explain the lack of funds
provided to low income people In the original model of Stiglitz and Weiss several
assumptions have been made that need to be suspended in order to compare the credit
markets for low and high income people and give an explanation why the latter is
widely neglected by institutional investors
Evidently the assumptions that the amount borrowed is equal for each loan applicant
and that transaction costs170 need not to be taken into account171 are not suitable for this
context While the average loan size of MFI customers is much smaller than that of
clients from traditional banks the transaction costs as a share of the loan are
considerably higher because the lenderrsquos costs for conscientious processing a credit
applications are only slightly smaller for a $50 loan than for a $100000 or a
$10000000 loan
In figure 2 the R(I)large curve represents the return to the bank for large loans with
regard to the interest rate I and the R(I)small curve describes the same correlation for
small loans It is shifts downwards to reflect the assertion that the imperfect information
169 See Stiglitz and Weiss (1981) p 394170 In this paper the term bdquotransaction costsldquo refers to the operating expense ratio as defined by MicroRate It ldquois calculated by dividing all expenses related to the operation of the institution (including all the administrative and salary expenses depreciation and board fees) by the period average gross portfoliordquo See MicroRate and Inter-American Development Bank (IADB) (2003) p 16 171 See Stiglitz and Weiss (1981) p 396
34
paradigm has a more severe effect on poor people than on the better off They are
expected to have less profitable investment opportunities at their disposal172 and
therefore are more likely to invest in riskier projects which increase the probability of
default and hence decrease the expected return to the bank Additionally one might
expect poor people to be more likely than others to spend borrowed money on
consumption instead of an income generating activity particularly if a crisis arises It
seems understandable that food or urgently needed medicine are given priority over
repaying a loan
The second shift downwards is due to transaction costs As stated above they are
relatively higher for smaller loans Obviously transaction costs are incurred in the
provision of a large loan as well but since they are much smaller with regard to the loan
amount they are not included in the diagram for reasons of clarity
Figure 2 The extended Model
Source Own diagram adapted from Stiglitz and Weiss (1981) p 394
172 See Khandker (1998) p 8
INTEREST RATE I
SmallLoans
LargeLoans
Transaction costs
Lack of investment opportunities
R(I)large
R(I)small
EX
PE
CT
ED
RE
TU
RN
TO
TH
E B
AN
K
35
53 Overcoming Credit Rationing for the Microfinance Sector
If the conclusions in chapter 51 hold it is rational for a profit maximizing investor to
neglect the microfinance sector as long as no surplus funds in the market for large loans
exist This finding can help to explain the small amount of money provided to the
microfinance sector from commercial investors On the other hand it has to be stated
that this theory is reflexive as defined by Soros173 It not only explains but also forms
reality since it has the potential to reinforce the view of potential investors that
microfinance is a less profitable business174 Therefore demonstrating under which
conditions microfinance can be profitable and in some cases be more profitable than
traditional businesses is of crucial importance
To provide a fairer view of the microfinance sector a further assumption of the Stiglitz
and Weiss model that needs to be suspended is that all investments made by the
borrowers have the same expected return175 As stated above this contradicts economic
theory which claims ceteris paribus capital productivity decreases while the amount of
fixed capital increases In combination with a low capital endowment micro-enterprises
are usually faced with an excess supply of unskilled labor especially in developing
countries176 Hence small enterprises use far less capital per employee than big business
and therefore their marginal productivity of capital is much higher177 This is intuitive if
one imagines an economic actor who wants to invest several packages of capital
Obviously she would invest the first package where she expects the highest return the
second package where she expects the second highest return and so on Each additional
investment opportunity would lead to lower or at best equal returns178 While this
simplified example has limitations it demonstrates how the marginal productivity of
capital can diminish Although it might actually increase until a certain point179 this can
be expected to be so low in this context that it has no influence on the correlation as
shown in figure 2
173 See Soros (1998) pp 14 et sqq174 See Goodwin-Groen (1999) p 8175 See Stiglitz and Weiss (1981) p 395176 See Perkins et al (2001) pp 95 et sqq177 See Tschach (2000) p 8178 See Rosenberg (2002) p 11179 See Rechard G Lipsey (1979) pp 211 et sqq
36
Figure 3 Marginal Productivity of Capital
Source Dornbusch and Fischer (1995) p 406
Even if good investment opportunities for poor people exist the question remains if it is
possible to distinguish between high and low risk borrowers The problem of adverse
selection is overcome in a cost effective way in many MFIs180 For the better off poor
for example institutions like BRI base their decision on whether or not to approve a
loan by assessing the repayment ability of potential borrowers from their current income
flows and not from the uncertain returns generated by the loan181 Additionally
collateral is used in some cases to attract low risk borrowers182 In contrast to
industrialized countries this is usually not done to cover the potential losses of the
lender but to punish the defaulter and therefore increase her willingness to repay183
Obviously this does not always work for the poorest since they often neither posses any
goods that could work as collateral nor do they have sufficient earnings prior to
obtaining a loan for starting an income generating activity Here the so called group-
lending model can help to identify creditworthy borrowers The most prominent
institution using this approach is the Grameen Bank which only provides credit to
180 See Farrington (2000) p 20181 See Robinson (2001) p 80 Robinson (2002) p 238182 See Bester (1985) p 850 et sqq183 See Schmidt and Tschach (2001) p 15 Robinson (2002) p 244
FIXED CAPITAL 0
MA
RG
INA
L P
RO
DU
CT
IVIT
Y
37
members of a group of five These groups are formed by their members without
interference of the Grameen Bank Although in this particular case no joint liability
exists for the members of the group nobody can receive a new loan if another member
of the group fails to repay on time184 Therefore the group formation work as a
screening process Since the borrowers do not want to risk their ability to obtain further
loans they carefully select with whom to form a group Usually the members know
each other for a long period of time and therefore they can make a meaningful judgment
of each othersrsquo ability to repay the loan Other MFIs even require the members of a
group to mutually guarantee each othersrsquo loans185 While this might further increase
borrowersrsquo efforts to search for trustworthy group members it might also keep potential
borrowers from applying for a loan since she does not want be held responsible for
defaulting members This mechanism enables MFIs to partly pass on the transaction
costs related to the selection of low risk borrowers to the borrowers themselves186
Many MFIs have also largely overcome the problem of moral hazard by creating
incentives to ensure a high repayment rate even among the poorest In some cases their
customers go hungry in order to pay back their loan even though no legal action would
be taken against them if they would refuse to do so187 One way to achieve this is to
build up peer pressure through the formation of groups as described above188 Another
and probably the most important is to limit access to future loans to those borrowers
who repay on time The demand for successive loans is extremely high In a 1996
survey 98 percent of BRI borrowers planed to apply for another loan189 and in 1993
less than 30 percent of Grameen Bank loans went to first time borrowers190 Especially
the poorest highly value the option to reborrow191 and many MFIs see this as their
primary incentive to ensure repayment192 According to Schmidt and Tschach ldquothe net
present value of future access to credit works out to be roughly half the value of the
economic advantage to be gained from the intended non-repaymentrdquo193 This can also
184 See Yunus (1998) p 135185 See Schmidt and Zeitinger (1997) p 6186 See Stiglitz (1990) p353187 Own observation at the Grameen Bank in Bangladesh (2003)188 See Hoff and Stiglitz (1990) p 249189 See Robinson (2002) p 251190 See Khandker Khalily and Khan (1995) p 93191 See Gibbons (2000) p 15 Hashemi and Schuler (1997) p 43192 See Gibbons and Meehan (1999) p 160193 See Schmidt and Tschach (2001) p 16
38
explain the occurrence of a drop in the repayment rate once a MFI is no longer seen as
viable and therefore is not expected to provide loans in the future194
With the help of the described mechanisms MFIs around the world are able to keep
repayment rates high A survey of 69 MFIs from 36 different countries each serving
more than 10000 clients in 2002 found the portfolio at risk (PAR)195 varied between
zero and 231 percent While the average was 36 percent the median was found to be
229 percent196 One of the MFIs included in this sample is BRIs whorsquos 12-month loss
ratio has never exceeded five percent since the start of its transformation in 1984 and
from 1997 to 1998 the ratio actually fell from 22 to 194 percent197 The latter deserves
special attention because the Asian financial crisis reached its peak at that time with
Indonesia being hardest hit as illustrated by a statement from The Economist in July
1998 Even with the fierce competition from its neighbors Indonesia would probably
walk away with the prize for Asias most desperate banking systemrdquo198
The findings that MFIs can adapt their services to low income people in order to ensure
a high repayment rate and that poor people do not lack profitable investment
opportunities are illustrated in figure 4 From this diagram it can be seen that under the
new assumptions the interest rate at which the bank maximizes its return differs for
large (I(l)) and small loans (I(s)) According to the assumption that micro-
entrepreneurs can realize a higher return on their investments the bank can charge them
a higher rate of interest without bearing an increased risk Nevertheless in this example
the bank would still serve the market for large loans first because of the higher
transaction costs for smaller loans
The view as described in figure 4 is shared among most traditional banks and investors
in industrialized as well as in developing countries In addition to neglecting the
possibility of generating profits by offering microcredit themselves199 they also hesitate
to lend to MFIs because they consider their business too risky
194 See Schreiner (1997) p 64195 ldquoPAR shows the real risk of the portfolio by comparing outstanding loan balances for loans with atleast one late payment to the outstanding loan portfoliordquo Gross and de Silva (2002) p 22196 Own calculations See Appendix 2197 See Seibel (2000) p 11198 The Economist (1998) pp 92 et sqq199 Busch and Kort (2004) p 8
39
Figure 4 The extended Model
Source Own diagram adapted from Stiglitz and Weiss (1981) p 394 Tschach (2000)
p 17
This attitude can be observed by comparing the ratio of equity to liabilities which is
considerably higher for MFIs than for conventional banks200 When it comes to MFI
start-ups and those MFIs serving the low end market in remote areas even experienced
microfinance practitioners are skeptical if interest rates that fully recover all costs can
be charged201
Theoretically there are two ways to adjust this model to arrive at a conclusion which is
more favorable with regard to the profitability of microcredit One is to cut the
transaction costs and therefore reduce the downward shift of the R(I)small curve the
other is to allow the bank to further raise the interest rate without experiencing a
decrease in its return This means to increase I(s) and the respective rate of return
While in 2000 Tschach stated that transaction costs vary between 10 and 20 percent for
loans provided through the group lending model and between 15 and 30 percent for
200 See MicroRate and IADB (2003) p 30201 See Volkery (2004) p 33 Gibbons (2000) p 15 Gibbons and Meehan (2002) p 29 Goodwin-Groen (1999) p 8
INTEREST RATE I(l)
SmallLoans
LargeLoans
Transaction costs
I(s)
R(i)large
R(i)small
EX
PE
CT
ED
RE
TU
RN
TO
TH
E B
AN
K
40
individual loans202 it was recommended in 1999 that MFIs should target a range
between 15 and 25 percent203 Some best practices on the other hand have already
achieved single digit numbers Currently BDB might be the most efficient MFI in the
world with transaction costs at just 47 percent in 2001204 Even though the low costs of
BDB have to be acknowledged its achievement has to be put in perspective As stated
above with an average loan balance of more than $5000 it does not serve the low end
market In addition it works in an environment with a high population density which
means that it can reach a relatively large group of borrowers per branch This is a
comparative advantage many Asian MFIs enjoy as can be illustrated by comparing
Bangladesh and Bolivia Both countries are at the forefront of the development of
microfinance in their respective continent but while in Bangladesh more than 1000
people are living per square kilometer the average for Bolivia is only eight205
Therefore it is consistent that the most efficient MFI in Latin America Fondo
Financiero Privado para el Fomento a Iniciativas Economicas has transaction costs of
114 percent206 With an average loan size greater than the annual GDP per Capita this
institution also does not serve the low end market207
Despite the impressive efficiency gains in the described examples most MFIs are far
from achieving these numbers and many are unlikely to reach them due to the
environment within which they work A survey of 67 MFIs from 31 countries found the
average transactions costs in 2002 to be 279 percent with a median of 206 percent208
However even if these institutions were to increase their efficiency to best practice
standards their transaction costs would still be significantly higher than those of
traditional banks providing much larger loans For these banks the respective costs vary
in a range between 05 and 3 percent209 According to this argument charging interest
rates considerably higher than conventional banks is the only way for MFIs to generate
higher returns and hence successfully compete for capital
202 See Tschach (2000) pp 100 et sqq203 See Gibbons and Meehan (1999) p 149204 See M-Cril (2001b) p 4205 See CIA (2004)206 See MicroRate (2004)207 In this paper the term ldquolow endrdquo refers to the definition of the MBB (2003) p 54 Loans worth less than 20 percent of the respective countryrsquos GDP per capita are described that way 208 Own calculations See Appendix 3209 See M-Cril (2004a) p 16
41
6 Interest Rates
61 Setting the right Interest Rate
Before addressing the questions to what extend MFIs can raise their interest rates
without putting the repayment rate or the social benefits of their customers at risk a
basic model will be presented This model will illustrate how a MFI should set their
rates in order to not only cover their costs but also to generate an appropriate profit to
finance further growth and attract additional capital
In 2002 CGAP revised its 1996 paper ldquoMicrocredit Interest Ratesrdquo210 which outlines
the standard method of setting sustainable interest rates for commercially oriented
MFIs According to this model the annual effective interest rate (I) should be calculated
as shown below
(1) I = LL
IIKCFLLTA
minusminus+++
1
With each variable being a decimal fraction of the average outstanding loan portfolio
whereby TA stands for the transaction costs as described above LL represents the
annual loan loss and II stands for investment income eg on liquid assets The cost of
funds (CF) consist of the interest and administrative costs needed to obtain deposits and
commercial loans as well as of the imputed costs on equity due to inflation K stands for
the capitalization rate which represents the net real profit Keeping this rate high is
important to finance the future growth of the loan portfolio This can be either done
through investors attracted by high profitability or through borrowing For the latter an
increase in equity is inevitable since it is required as a safety cushion by lenders
Since this model ignores the timing of cash flows and does not take taxes into account
it has to be regarded as fairly imprecise and hence should not be used for business
planning Nevertheless it can be used for an approximation of the interest rate that a
MFI would need to charge to provide its services as planned In the following I will
210 See Rosenberg (2002) pp 1 et sqq
42
apply this model on a fictitious MFI working in a rural area of Latin America with low
end customers In this setting it seems realistic to estimate transaction costs of 35
percent and loan loss rate of two percent211 If funds were borrowed at commercial
terms their costs can be assumed to equal at least 15 percent of the average outstanding
loan portfolio212 Estimating the capitalization rate is more challenging First the
targeted portfolio growth rate is set at 75 percent This is slightly below the 751 percent
average annual portfolio growth between 2000 and 2002 found by a survey of 25
different MFIs based in Central and South America213 If the extend to which the MFI
can leverage stays constant the loan portfolios growth would be limited by the growth
rate of the equity To express the capital needed for this growth as a share of the loan
portfolio it is necessary to estimate the ratio between the equity and the outstanding
loan amount According to the survey mentioned above the loan portfolios of the 25
Latin American MFIs equal on average 215 times their equity214 With this number the
capital needed to increase the equity by 75 percent would corresponds to approximately
35 percent of outstanding loan amount (075215) Finally the investment income has to
be estimated Since liquid assets that are available short term do not generate high
returns say five percent it does not seem advisable for the MFI to hold more than a
quarter of its loan portfolio in this form Hence the profit generated in this way would
equal 125 percent of the outstanding loan amount Using these numbers the equation to
calculate the annual effective interest rate reads as follows
(2) I = LL
IIKCFLLTA
minusminus+++
1 =
0201
01250350150020350
minusminus+++
= 0875
As a result the MFI would need to charge an annual effective interest rate of
approximately 875 percent on its loans in order to sustainable provide its services and
finance its growth without depending on donor money This rate might decrease once
the MFI matures the growth slows down and cheaper funds become available but it
will stay significantly higher than any rate charged by conventional banks
211 MicroRate and IADB (2004) pp 6 and 16212 See MicroRate and IADB (2004) p 616 and 28213 Own calculation See Appendix 4214 Own calculations See Appendix 5
43
62 Can Micro-Entrepreneurs bear these Rates
Although most MFIs charge rates significantly below 875 percent many critics have
strenuously argued against any rates exceeding those of traditional banks Rosanna
Barbero of Oxfam labeled an interest rate of 52 percent charged by a Cambodian MFI
ldquoludicrous evil and disgusting and stated that ldquo[n]o business in the world can make a
profit at these interest ratesldquo215 The former finance minister of Bangladesh Shah Kibria
even categorized the 20 percent effective rate charged by the Grameen Bank as to
high216 Many practitioners therefore believe in a strong negative correlation between
the interest rate and the demand for loans217 Others have argued more generally that
concentrating on profitability and therefore charging high interest rates diverts MFIs
from serving the poorest218
These views are still shared among many MFI managers donor agencies and especially
investors and politicians While the former are unwilling to charge interest rates for
funds they received ldquocheaplyrdquo (through grants or subsidized loans) and are worried
about undermining their social goals by charging higher rates of interest219 the latter are
reluctant to invest for reasons stated above or impose interest caps to catch the attention
of the public by pretending to protect the poor from usury rates220
In chapter 53 it has been described that micro-entrepreneurs due to their smaller
capital endowment have even better investment opportunities than big business The
extend to which this is true has not yet been answered An indication is the high
repayment rate observed within MFIs around the globe If their customers capital yield
did not exceed the charged interest rate how would they be able to repay According to
Gibbons and Meehan customers of MFIs can generally generate returns of more than
100 percent on their invested capital221 and ldquo[r]esearch in India Kenya and the
Philippines found that the average annual return on investments in microenterprises
215 See Kate and Roeun (2004)216 See Hodson (2001) min 1100217 See Morduch (1999a) p 1594218 See Prisma (2002) p 1219 See Schreiner (1997) p 60 Khandker (1998) p 106 220 See Gross and de Silva (2002) p 32 Jansson and Wenner (1997) p 36 et sqq Campion (2002) p 59221 See Gibbons and Meehan (1999) p 131
44
ranged from 117 to 847 percentrdquo222 Schmidt and Tschach found the marginal
productivity of capital to be as high as 1000 percent for the smallest loans provided by
the Bolivian MFI Caja Los Andes223 These findings are confirmed by the observation
of Rosenberg who found while working as a microfinance consultant for ten years he
never heard of a single MFI having problems to attract clients because interest rates
were too high224
To get a better understanding of the investment opportunities of low income people in
developing countries a typical example on how MFI clients invest their loans is as
follows
Zobair is working as a rickshaw puller in Bangladesh Like most of his colleagues he
does not own the rickshaw he is riding Therefore he has to pay a daily rent of about
$030 to the owner Since his average income of approximately $15 per day is hardly
enough to feed his family he is not able to save the $100 necessary to buy a rickshaw
on his own 225 If he could do so through obtaining a loan his income would increase by
$030 every day because he would not have to pay the rent for the rickshaw anymore
Assuming an average of six working days per week 226 and a life span of the rickshaw
of 5 years his internal rate of return would equal 15324 percent annually227
Consequently any interest rate charged by a MFI would be advantageous to him as long
as it would not exceed 15324 percent228
63 Should the Interest Rate be subsidized anyway
Despite the fact that numerous micro-entrepreneurs are able to generate tremendous
returns on their investment obviously not all are able to use capital in such a productive
way and therefore can not afford microcredit at commercial rates In order to reach
these people as well many MFIs continue to use donor money in order to keep their
interest rates low But even if the problems related to subsidized credit as described in
222 See Helms and Reille (2004) p 3223 See Schmidt and Tschach (2001) p 6224 See Rosenberg (2002) p 10225 This examples draws on observations made by the author in Dhaka (Bangladesh) during 2003226 Obviously extended holidays are not a viable option in this surrounding 227 Own calculation See Appendix 6228 This result is only valid if the loan is repaid in daily instalments For a weekly repayment schedule the interest rate charged by the MFI must not exceed 15119 percent in order to still be beneficial for Zobair
45
chapter 23 do not arise it might still not be the most effective tool to help poor people
as will be illustrated in the following example
A MFI faces two groups of potential clients one with businesses able to generate a
return of 125 percent on borrowed capital and another with a possible returns of 50
percent Assuming budget costs according to equation (2) the institution needs to
charge an interest rate of 875 percent and therefore only serves the former group
Supposed each group consists of 50 members demanding $100 loans the net gains to
society (NGS) could be calculated as follows
(3) NGS = 50 times ($125 ndash $875) = $1875
These gains would be due to the investments of the more profitable group which were
made possible through the loans provided by the MFI The less profitable group would
not borrow since their expected returns are not sufficient to pay for the interest If the
interest rate would be lowered to 30 percent both groups would be able to generate net
gains and therefore borrow from the MFI In order to provide loans at this rate the
institution would need to raise additional capital from non commercial sources The
NGS would be calculated as follows
(4) NGS = 50 times ($125 - $30) + 50 times ($50 - $30) + 100 times ($30 - $875) = 0
While the first terms represent the net gains to the respective groups the last describes
the costs incurred in providing the loans At a rate of 30 percent each loan would need
to be subsidized with $575 Hence the NGS actually fall after the introduction of the
subsidized loan This is due to the fact that the less profitable group is encouraged to
invest in relatively unproductive businesses In addition future growth of the MFI could
be jeopardized due to scarce donor money which is needed to finance the interest rate
subsidy Therefore it seems more advisable to continue to charge a rate of 875 percent
and spend the money used for subsidization on other programs such as health care or
education229
229 In Appendix 7 it will be shown that this result generally holds
46
7 Empirical verification
71 Setting up a Sample
To see if the findings of the previous chapters hold the effects which interest rates
charged by MFIs have on their performance will be analyzed in the following Up to
now such a study does not exist mainly because of a lack of adequate data Most MFIs
do not provide accurate information about the annual effective interest rate they charge
and therefore make an evaluation difficult
In 2002 Rosenberg distinguished eight different categories on how microcredit interest
rates are quoted230 These categories differ in several ways On the contrary to
traditional banks for example it is common for MFIs to state interest rates calculated on
a ldquoflatrdquo balance rather than on a declining one This means that the total loan amount is
used to determine the interest rate ignoring installments paid by the borrowers normally
on a weekly or monthly basis In addition many MFIs charge a certain upfront fee prior
to the loan disbursement require compulsory savings at a lower rate or state their
interest rate for semi annual terms only On the one hand this is done to provide
numbers that are more meaningful to MFI customers who often lack the necessary math
skills to deal with compound interest on the other hand it is done to circumvent interest
rate ceilings imposed by the government231 Another problem is that most MFIs offer
different loan products without itemizing their respective shares to their total loan
portfolio As a result it is not possible to calculate a weighted average even if the rate
stated by the respective MFI could be transformed into an effective interest rate
Usually the portfolio yield is used as a proxy in order to make statements about the
interest rate charged by a certain MFI232 It is generally ldquocalculated by dividing total
cash financial revenue (all income generated by the loan portfolio but not accrued
interest) by the period average gross portfoliordquo233 The advantage of this method is that
even the hidden costs are considered Nevertheless it also has a severe shortcoming by
not taking late or defaulted payments into account Therefore the portfolio yield does
230 See Rosenberg (2002) p 5231 MicroRate (2002) p 8232 See MicroRate (nd)233 MicroRate and IADB (2003) p 39
47
not allow to draw conclusions regarding the correlation between the interest rate
charged by a MFI and its PAR
72 Examining the Sample
Through the appearance of rating agencies specialized in the microfinance sector more
adequate information has become available in recent years While MicroRate only
publishes the portfolio yield of rated MFIs M-Cril Microfinanza Microserve and
Planet Rating actually provide information about the annual effective interest rate for at
least some of the MFIs they analyze Although it is labelled differently from all of the
four institutions234 the term describes what is ldquothe highest income or yield that an
organisation can earn from its portfolio based on the terms of its loansrdquo235
Currently236 reports of 39 different MFIs from 20 countries providing accurate
information about the effective annual interest rate are available to the public This
sample should be used to verify the findings of the previous chapters237 Since a
comparison is made between the performances of MFIs based in different countries and
the ratings have been carried out in different years several adjustments are necessary
First the inflation of the respective country and the respective year(s)238 has to be taken
into account in order to only compare the real rates239 In addition the average
outstanding loan amount per borrower is divided by the respective countryrsquos GDP per
capita Since it can be assumed that ldquoonly the poorer households will be willing to take
the smallest loansrdquo240 this number can be used as a proxy for the poverty level
Although the sample size is far to small to represent the microfinance sector as a whole
and the results are statistically not significant the findings can still be used to underline
the theoretical conclusions drawn in the previous chapters In figure 5 the connection
234 M-Cril uses the name ldquoannual percentage raterdquo See eg M-Cril (2004a) p 25 Microfinanza uses the name ldquoexpected portfolio yieldrdquo See eg Microfinanza (2002c) p 25 Planet Rating uses the name ldquoannual effective interest raterdquo See eg Planet Rating (2004d) p 1 Microserve uses the name ldquotheoretical yieldrdquo See Microserve (2003) p 62235 See M-Cril (2004a) p 25236 As of September 28th 2004237 See Appendix 8 For exchange rates see FXTOP (2004)238 Where necessary a weighted average of the annual inflation rate was used See Appendix 9239 This is done through the following formula ir = (I ndash F) (1 + F100) While ir represents the real annual effective interest rate F represents the inflation rate 240 Morduch (1998) p 1572
48
between the average loan size and the transaction costs as a share of the average loan
portfolio is illustrated
Figure 5 Loan Size vs Interest Rate241
Source Own diagram
000
1000
2000
3000
4000
5000
6000
7000
8000
9000
10000
0 100 200 300 400 500 600
Loan Size
Inte
res
t R
ate
It can be seen that the interest rate is negative correlated to the loans size This can be
explained by the relative higher transaction cost for smaller loans as described in
chapter 52 In order to cover their costs MFIs serving the low end market need to
charge higher rates to their customers than those organizations serving the better off
poor Obviously there are several assumptions to this general finding Especially
striking are the two MFIs with an average loan size of approximately five times their
countries GDP per capita which still high interest rates This occurrence can be
explained by taking a closer look to the respective organizations One was established
less than two years prior to its rating and therefore still bears a lot of start up costs242
241 The equation for the regression line reads as follows Y = -00219X + 365 The correlation coefficient is 014242 See Microfinanza (2002b) p 1
49
the other managed to stay profitable while it almost quadrupled its loan portfolio in the
last two years243
Figure 6 Interest Rate vs PAR244
Source Own diagram
0
5
10
15
20
25
30
35
0 20 40 60 80 100 120
Interest Rate
PA
R
In Figure 6 the crucial correlation between the interest rates charged by a MFIs and its
PAR245 is examined According to the given sample the view of traditional banks and
investors that a higher interest rate leads to a higher default rate does not hold
Obviously one has to avoid to draw the opposite conclusion namely that a high interest
rates decreases the PAR The connection illustrated in figure 6 has to be interpreted as
follows Since high interest rates are related to small loans the low PAR for MFIs
charging high interest rates can actually be explained by the tremendous profitability of
small size investments Despite the high rates their customers are even more likely to
repay
243 See Planet Rating (2003b)244 The equation for the regression line reads as follows Y = -00768X + 68433 The correlation coefficient is 0235245 M-Cril only publishes the PAR for overdues greater than 60 days Therefore these ratios are used as a proxy for the industry standard of 30 days for some Asian MFIs
50
Finally it has to be examined if charging high interest rates actually enables MFI to
generate higher returns Although it can be expected that the combination of a low PAR
and a high interest rate leads to a high profitability it still has to be checked if this is not
outdone by soaring transaction costs Figure 7 illustrates the correlation between the
interest rate charged by a MFI and its financial self-sufficiency (FSS) The latter is the
ldquo[r]atio of total income to total adjusted expenses for the year Adjustments are made
for subsidised cost of funds (relative to market interest rate) equity (with respect to
inflation) and in-kind donationsrdquo246 It can be seen that the regression line actually does
indicate a positive correlation between the interest rate and the profitability of a MFI
Figure 7 Interest Rate vs FSS247
Source Own diagram248
0
20
40
60
80
100
120
140
160
180
0 20 40 60 80 100
Interest Rate
FS
S
246 M-Cril (2004a) p 53247 The equation for the regression line reads as follows Y = 02839X + 8901 The correlation coefficient is 0174248 Since the interest rate the customers of the MFI Foccas have to pay includes fees which are not passed on to the institution its interest rate in this diagram is set at 723 percent instead of the 10715 percent used for figure 6 See Planet Rating (2003b) p 1
51
This result does not necessarily disprove the findings of Stiglitz and Weiss since it can
be argued that MFIs simply do no increase their interest rates to the point where they
would maximize their expected returns But if this would be true why do MFIs not
charge higher rates of interest given the demand described in chapter 41 and 43 In
mature markets competition normally ensures prices not to exceed a certain level but
since many MFIs still operate in a ldquosellerrsquos marketrdquo249 this can not explain the findings
as described in figure 7 Therefore it has to be assumed that a combination of the
unwillingness of many microfinance practitioners to burden their customers with high
interest rates and the plain disbelief of traditional investors that micro-entrepreneurs can
bear those rates is responsible for this occurrence
249 See MicroRate and IADB (2003) p 9
52
8 Conclusions
It has been shown that MFIs are not only contributing significantly to the development
of the financial sector in their respective countries but also that they play an important
role to eradicate poverty by providing much needed capital to low income people which
are able to generate tremendous returns on their investments
The fact that the demand for microcredit is not met is mainly due to the view of most
for profit investors and traditional banks that offering financial services to poor people
can not be done profitable Because of this conviction they hardly invest in the
microfinance sector This does not have to be the case according to the findings of this
paper Although faced with relatively high transaction costs MFIs are able to charge
interest rates at levels that fully recover their costs Elizabeth Rhynersquos claim ldquothat the
most financially viable programs differed from their less viable peers in their
willingness to set interest rates at levels that would fully recover costsrdquo250 is backed by
the findings of this paper that high profitability is correlated to high interest rates
Theoretical models based on the findings of Stiglitz and Weiss can not be used as a
justification to ration credit for the microfinance sector since the interest rate that
maximizes profits to the lender can be assumed to exceed 100 percent for many MFIs
Nevertheless this rate is hardly charged although it has been shown that it can be done
The Mexican MFI Compartamos for example manages to keep its PAR as low as one
percent while charging an effective interest rate of more than 100 percent to
approximately 160000 clients251 In combination with this case the conclusions drawn
from examining the sample of MFIs in chapter 7 the claim of Hulme and Mosley as
stated in the introduction can be considered as wrong MFIs are in fact able to finance
rapid growth stay profitable by charging corresponding interest rates and still have a
significantly positive impact on the poverty level of their clients In the long run gains
in efficiency economies of scale a slowdown in growth and competition will ensure
interest rates drop as it has already been the case in countries like Bangladesh and parts
of Bolivia252
250 See Rhyne (1998) p 7251 See MicroRate (2004)252 See Microrate and IADB (2003) p 9
53
According to a MicroRate survey many MFIs are more profitable than Citibank and also
generate a higher return on investment than commercial banks in their respective
countries253 Investments companies like IMI or Blue Orchard will soon be able to
present a meaningful track record of their microfinance investments to potential
investors Ultimately the capital markets can not ignore the facts proving that it actually
can be profitable to invest in the microfinance sector but in order to raise money
quickly microfinance practitioners will have to continue to intensively promote their
cause not only to for profit investors but also to donors and multilateral agencies like
the World Bank
253 See MicroRate (2002) p 10
54
Appendix
Appendix 1 Average loan balance
Source Data is available through the Mix Market (2004)
Organization
Loan Portfolio 2002 (US$)
Loan Portfolio 2003 (US$)
Number of borrowers 2002
Number of Borrowers 2003
2CM 1263602 1400438 3622 3708ACF 955503 1611401 285 370ACLEDA 26846703 39391301 82598 98905ACME 1460881 1714844 4283 4600ADIM 369065 407798 1122 1395AFK 933306 1706577 250 467AgroInvest 4684249 9697411 5208 9629Al Amana 15593277 28677666 78114 101610AMSSFMC 612167 1040756 6183 6886AREGAK 3285273 3987011 11841 14377AVFS 214331 269819 1883 2866BancoSol 83629049 91175000 42290 56707BESA 10563980 15114430 4488 5061BPR AK 613362 876130 1730 3879BPR BMMS 133949 237946 1755 1779BRI 1344006170 1720072773 3056103 3100358BZMF 1592508 1922097 1250 1331CBDIBA 216587 242465 5764 2877CCA 2146235 4582302 4070 6585CCCP 447534 851678 6265 9450CEP 3795400 5261957 32291 42132CERUDEB 25093643 34873228 34490 44796CMEDFI 227674 250244 3467 3781CMM - Bogota 4836000 8135968 15635 22038CMMB 34880 56964 42 190COAC Maquita Cushunchic
870084 1855718 6603 7732
CODES 280843 263091 60 60CODESARROLLO 6714007 12935951 4391 6896Constanta 2943822 3536047 16134 18588COOPEC CAMEC MN
7152 29821 92 77
Crear - Tacna 3891116 4636094 3671 4948CREDIT 642094 81838 7532 8097CRYSTAL FUND 366456 421403 1379 1061DBACD 3473701 3876526 12812 19606ECLOF - ECU 1154292 728312 860 416ECLOF - MAL 441734 407227 1118 1500EKI 11833244 19245751 8999 13323EMT 4481589 5765281 84781 92173ESED 8579460 6834742 22790 20035
55
Eshet 185741 462569 3308 6540Faulu - KEN 9027332 7206344 17463 15000FDL 12503027 16545332 21306 25106FIE 35818903 41597315 26468 33100FINADEV 5512586 9770323 12775 14709Finance Salone 211312 434298 2225 7159Finca - TAN 1293430 1854834 20648 27499Finca - UGA 2451703 2798869 35610 36912FINCORP 4761288 10236896 941 858FJN 5473563 8037662 8107 11133FMFB 308158 1188896 713 3558FMM -Bucaramanga
6355518 10227000 25814 42464
FODEM 739181 939824 1909 2501FundaciESPOIR
898561 1883446 5911 9464
FUNDESER 798907 1373113 4072 5065Gasha 323748 413742 5504 6423GGLS Save the Children
64235 137957 1291 2362
GK 56986 166971 951 2718HKL 1363365 1420357 6648 5372HOPE 402799 603488 1098 1562IAMD 42132 56550 2780 2772IDECE 21312 39453 150 232IDF 2031944 2626382 31003 36580IMCEC - Dakar 254759 688449 1018 2983IMCEC - Thies 199799 571122 1164 1261
ISSIA 221615 246792 1409 1698JMCC 1962355 2609723 1471 2333KAFC 21710638 29241051 24850 32097KAMURJ 1003935 1411258 5559 5691Kashf 2355965 6271498 29655 59389KMBI 721409 1626666 11973 27266KPSCA 109299 128063 362 794K-Rep 14490447 20699963 38739 45379KSCS 18978 43740 140 297KVT 44075 70621 241 373LAPO 922478 1194633 18740 19139MEC ADEFAP 27788 69248 198 202MEC Bosangani 14357 31086 364 540MEDF 104113 136257 1278 1184Meklit 233170 252232 2084 3577Metemamen 22123 57778 943 1501MFSC 109261 171090 511 687MIKRA 2951028 5008784 4145 6095MIKROFIN 9560502 18380263 5633 7426Miselini 737387 1026639 10182 11431MRFC 11475440 9133130 163000 180000Mushuc Runa 2089076 5418325 3139 6232Nirdhan 2886777 3016171 29589 27457OCSSC 5245186 7658413 42157 6215o
56
Otiv Diana 95992 638422 229 1073Otiv Sambava 188094 437974 2002 1442Otiv Tana 66465 673175 337 1269Partner 9976448 15321304 7139 11935PCA 6878257 6885926 63113 58147PEACE 420746 627295 4192 5428PEDF 164399 254233 2357 3340Piyeli 809447 1206656 8674 4745PRESTANIC 2827502 3540367 1477 2605PRIDE - MAL 991888 854631 5376 5601PRIZMA 3881581 6838978 8112 10968ProMujer -Nicaragua
1006871 1424437 10436 13047
PTF 891566 1068881 8500 9070RBST 818594 1058115 619 723REMECU 1381705 1483471 10330 13996
RUSCA 60887 100820 454 994
SCSCS 89423 157472 873 1007SFPI 709497 903556 7728 9552Sidama 934260 1011798 10267 11346SPBD 117807 186029 647 1740Sunlink 819138 1056823 3401 3833Sunrise 5412366 8782868 4560 7256TEBA 108032426 176300111 163021 157776TIAVO 281978 838905 2049 459TPC 1140429 2267148 22869 31668TSPI 4650989 5383755 49649 75617UNICECAM 3442843 5943804 16039 19031Wasasa 230657 274908 2850 3728Wisdom 1306066 1404463 10524 12054XacBank 4910098 9829503 11063 18610Zakoura 15907288 12444768 103720 118980
Appendix 2 Portfolio at Risk
Source Data is available through the Mix Market (2004)
Organization PAR 2002ABA 202ACEP 464ACLEDA 175ACODEP 452ACSI 209Al Amana 010Apoyo Integral
483
AREGAK 692Banco Solidario
500
BancoSol 660BASIX 1296
57
BRI 437BURO Tangail
350
CEP 200CERUDEB 103CMAC -Sullana
567
CMM -Bogota
176
Compartamos 111Constanta 304Credi Fe 212CREDIAMIGO 409DBACD 010EBS 847EMT 010ESED 1311FADES 2311Faulu - KEN 246Faulu - UGA 096FDL 212FECECAM 428FED 436FIE 598FINADEV 021Finamerica 1133Finca - TAN 000Finca - UGA 297FMM -Bucaramanga
094
FMM -Popayan
088
FONDEP 013FORA 064Genesis Empresarial
1197
IDF 017KAFC 106Kashf 000KMBI 128K-Rep 229MiBanco 309MRFC 1742Nirdhan 373
PADME 079PAMECAS 284PCA 379PRIDE - TAN 018ProMujer -Nicaragua
073
RCPB 600REMECU 157SHARE 000
58
Soluci 182Spandana 014TEBA 106TSPI 355UMU 125UNICECAM 405Urwego 290UWFT 363WAGES 736WWB -Medellin
235
XacBank 061Zakoura 095
Appendix 3 Transaction Costs
Source Data is available through the Mix Market (2004)
OrganizationTransaction Costs
Acci Rural 1154ACEP 858ACLEDA 2430ACODEP 2920ACSI 924Al Amana 2576AREGAK 2856AssEF 1919Banco Solidario
1826
BancoSol 1210BASIX 1317BRI 1353BURO Tangail
2053
CEP 1759CERUDEB 5109CMAC -Sullana
1784
CMM -Bogota
2089
Compartamos 3341Constanta 4597Credi Fe 1978CREDIAMIGO 2525DBACD 1742EBS 2377EMT 3220ESED 1343FADES 1673FAMA 2436
59
Faulu - KEN 2253Faulu - UGA 4962FDL 1726FECECAM 2587FED 4083FIE 1125Finamerica 1563Finca - TAN 10753Finca - UGA 9096FMM -Bucaramanga
1925
FMM -Popayan
1112
FONDEP 5477FORA 3481Genesis Empresarial
1626
IDF 1695
K-Rep 1909LAPO 3511MiBanco 2456Nirdhan 1325NWTF 3109OCSSC 1155PADME 1131PAMECAS 1705PCA 1670PRIDE - TAN 4273ProMujer -Nicaragua
5078
RCPB 2059SHARE 2308Sidama 2662Soluci 2906Spandana 641TEBA 1213TSPI 3898UMU 4023UNICECAM 10120Urwego 7437Wisdom 1906WWB -Medellin
1703
XacBank 4144Zakoura 1881
60
Appendix 4 Portfolio Growth
Source Data is available through the Mix Market (2004)
Organization
Total Loan Portfolio in 2000
Total Loan Portfolio in 2002
ACODEP 5889394 7258487Adelante 4327 88594ADRI 1514681 2591240AgroCapital 11100088 12018280Banco Solidario 39632165 103420000
BancoSol 78031172 83629049CMAC - Sullana 14596365 28055720
COAC Maquita Cushunchic
348443 870084
CODESARROLLO 1374801 6714007Compartamos 10804279 41825248Crear - Tacna 3778816 3891116
Credi Fe 781616 9393936ECLOF - ECU 179247 1154292
FADES 11948814 15501578FAMA 6201411 8835134FIE 22524645 35818903Finamerica 16575104 16097113FINCOMUN 3278938 5696556FMM - Popayan 6241821 12212867
FONDECO 3456625 5101801Genesis Empresarial
11154234 17746288
MiBanco 36964072 95873333Mushuc Runa 90737 2089076ProMujer -Nicaragua
426541 1006871
WWB - Medellin 2891207 4580998
Appendix 5 Portfolio vs Equity
Source Data is available through the Mix Market (2004)
OrganizationLoan Portfolio Equity
ACODEP 7258487 1921447Adelante 88594 72973
ADRI 2591240 781477AgroCapital 12018280 10766101Banco Solidario 103420000 12961000BancoSol 83629049 15299415CMAC - Sullana 28055720 6210291
61
COAC Maquita Cushunchic
870084 260331
CODESARROLLO 6714007 1285103
Compartamos 41825248 18350446
Crear - Tacna 3891116 1016912Credi Fe 9393936 863848ECLOF - ECU 1154292 459226FADES 15501578 4138972FAMA 8835134 6377663FIE 35818903 5360484Finamerica 16097113 3817960FINCOMUN 5696556 1042241FMM - Popayan 12212867 8510494FONDECO 5101801 1658075Genesis Empresarial
17746288 4765816
MiBanco 95873333 24261889Mushuc Runa 2089076 434311ProMujer -Nicaragua
1006871 1196015
WWB - Medellin 4580998 2213249
Appendix 6 Internal Rate of Return
Source Excel (German Version) calculation based on own data
A B C D E F
1 Date Cash Flow
Interest Rate Internal Rate of Return Balance Interest Principal
23 01012004 -100 15324 100 025489547 0045104534 02012004 03 999548955 025489547 0045104535 03012004 03 99909676 02547805 004521956 04012004 03 998643412 025466524 0045334767 05012004 03 998188909 025454968 0045450328 06012004 03 997733247 025443383 0045566179 08012004 03 999826083 050928361 -0209283610 09012004 03 999374595 025485114 004514886
hellip hellip hellip hellip hellip helliphellip hellip hellip hellip hellip hellip helliphellip hellip hellip hellip hellip hellip hellip1562 23122008 03 177951388 000528711 0294712891563 25122008 03 148859724 000908336 0290916641564 26122008 03 119239161 000379437 0296205631565 27122008 03 089543096 000303935 0296960651566 28122008 03 059771337 000228241 0297717591567 29122008 03 029923692 000152354 0298476461568 30122008 03 -3434E-07 000076274 029923726
62
The formula in the square C3 reads as follows
ldquoXINTZINSFUSS(B3B1568A3A156815)rdquo
Appendix 7 Subsidized Interest Rates and the Net Gains to Society
SourceOwn calculations
For simplicity only two groups of potential clients are distinguished This is possible
since using a continuum of potential clients would lead to the same results In addition it
is assumed that the amount of every loan (L) is equal and that all clients invest the
whole loan amount Group H consist of NH potential clients with a rate of return (rH) on
their invested capital higher than the cost recovering interest rate charged by the MFI
(iC) Group L consists of NL potential clients with a rate of return (rL) on their invested
capital lower than iC If the MFI charges iC the NGS can be calculated as follows
NGSC = NH times (rH - iC) times L
Since rH is bigger than iH (rH gt iC) according to the definition presented above the term
NGSH must be positive as long as NH does not equal zero If the MFI introduces a
subsidised interest rate (iS) lower than rL the NGS can be calculated as follows
(1) NGSS = NH times (rH - iS) times L + NLtimes (rL - iS) times L + (NH + NL) times (iS - iC) times L
(2) NGSS = NH times (rH- iC) times L + NLtimes (rL - iC) times L
The term (NH + NL) times (iS - iC) times L describes the amount of money that is needed in order
to subsidize the interest rate to the level iS By setting up an inequation it can be
examined under which conditions the NGSS are bigger than the NGSC
(3) NGSS gt NGSC
(4) NH times (rH- iC) times L + NLtimes (rL - iC) times L gt NH times (rH - iC) times L
(5) NLtimes (rL - iC) times L gt 0
(6) rL gt iC
63
So the NGSS could only be bigger than the NGSC if equation 6 holds This is
impossible since it violated the definitions presented above Therefore the introduction
of subsidized interest rates is always accompanied with a drop in the NGS
Appendix 8 Interest Rate vs Loan Size vs FSS vs PAR
Source Data is available through the Mix Market (2004)
Organization Country
Real Interest Rate
Loan Size (divided by the GDP per Capita) FSS PAR
BTFFKyrgyz Republic 3803 48260 1487 698
BesaFoundation Albania 2184 16076 684 260RFF Albania 1198 5783 4764 277PSHM Albania 2194 000 5758 198Mi-Bospo Bosnia 2974 5499 1261 020Prizma Bosnia 3474 3569 103 064Agroinvest Serbia 2201 4401 875 020KCLF Kazakhstan 5713 1713 865 090
Foccas Uganda10716 (723) 1550 584 29
ACEP Senegal 3280 20941 1643 1Padme Benin 2715 13575 1667 08Papme Benin 3086 53659 1405 24Vital Finance Benin 2676 9394 1015 17Finadev Benin 1738 14850 1024 21ABA Egypt 2579 1613 1168 88ASBA Egypt 2597 1702 1252 68DBACD Egypt 2490 1643 1073 0SBACD Egypt 2500 1734 982 67AMSSF Morocco 6926 787 1306 04Fondep Morocco 5199 650 889 071Zakoura Morocco 4414 900 98 006ENDA Tunisia 4008 1351 110 102BSFL India 1954 3269 856 99Share India 3426 1440 951 0Spandana India 2942 1618 1367 026SWC India 1864 2626 42 3036SKS India 2248 1912 578 0Grama Vidiya India 3176 1221 76 18Sneha India 3451 1433 933 0Buro Bangladesh 3206 1882 1093 17Upap Pakistan 2073 8183 757 03Seeds Sri Lanka 1004 1088 605 287EMT Cambodia 4324 1676 1016 01TPC Cambodia 4470 2035 832 27
64
WTF Phillippines 5816 1095 941 74TSKI Phillippines 5794 777 96 79Cacja Ecuador 862 6189 9460 897ACME Haiti 6043 6934 11685 450Grupo Cama Mexico 8961 267 10717 288
65
Appendix 9 Inflation vs GDP per Capita
Source IMF (2004)
Country Subject Description Units Scale 2000 2001 2002 2003 2004
Albania Gross domestic product per capita current prices US dollars Units 1083988 1238206 1396172 1757778 2229712
Albania Inflation annual percent change Percent 00 31 52 24 34
Bangladesh Gross domestic product per capita current prices US dollars Units 329310 327980 344494 369495 393717
Bangladesh Inflation annual percent change Percent 22 15 38 54 64
Benin Gross domestic product per capita current prices US dollars Units 361340 368213 405951 494725 560129
Benin Inflation annual percent change Percent 42 40 24 15 26
Bosnia and Herzegovina Gross domestic product per capita current prices US dollars Units 1255837 1321429 1466090 1807392 2070508
Bosnia and Herzegovina Inflation annual percent change Percent 50 32 03 02 09
Cambodia Gross domestic product per capita current prices US dollars Units 276413 280352 296577 305940 321247
Cambodia Inflation annual percent change Percent -08 02 33 12 20
Ecuador Gross domestic product per capita current prices US dollars Units 1227711 1590267 1804362 1957183 2082156
Ecuador Inflation annual percent change Percent -77 377 126 79 32
Egypt Gross domestic product per capita current prices US dollars Units 1550982 1461431 1278462 1188060 1083158
Egypt Inflation annual percent change Percent 28 24 24 32 52
India Gross domestic product per capita current prices US dollars Units 454206 458849 472915 542554 602625
India Inflation annual percent change Percent 40 38 43 38 47
Kazakhstan Gross domestic product per capita current prices US dollars Units 1236159 1490946 1655148 2000598 2579554
Kazakhstan Inflation annual percent change Percent 134 83 59 64 68
Kyrgyz Republic Gross domestic product per capita current prices US dollars Units 278256 306130 321079 349632 380637
Kyrgyz Republic Inflation annual percent change Percent 187 69 21 31 45
66
Mexico Gross domestic product per capita current prices US dollars Units 5957486 6274468 6425203 6111754 6377064
Mexico Inflation annual percent change Percent 95 64 50 45 44
Morocco Gross domestic product per capita current prices US dollars Units 1161302 1162154 1199584 1432725 1541041
Morocco Inflation annual percent change Percent 19 06 28 12 20
Pakistan Gross domestic product per capita current prices US dollars Units 437381 400356 440471 492913 538120
Pakistan Inflation annual percent change Percent 44 31 32 29 46
Philippines Gross domestic product per capita current prices US dollars Units 979423 900225 950707 963765 1018710
Philippines Inflation annual percent change Percent 43 61 31 30 54
Russia Inflation annual percent change Percent 208 215 158 137 103
Senegal Gross domestic product per capita current prices US dollars Units 478704 474460 507408 634171 714622
Senegal Inflation annual percent change Percent 09 30 23 -00 08
Serbia and Montenegro Gross domestic product per capita current prices US dollars Units 1031263 1389384 1882036 2491799 2795805
Serbia and Montenegro Inflation annual percent change Percent 699 911 212 113 79
Sri Lanka Gross domestic product per capita current prices US dollars Units 846811 796025 828256 904330 982466
Sri Lanka Inflation annual percent change Percent 62 142 96 63 64
Tunisia Gross domestic product per capita current prices US dollars Units 2034360 2065140 2149421 2534823 2881273
Tunisia Inflation annual percent change Percent 30 19 28 28 34
Uganda Gross domestic product per capita current prices US dollars Units 293404 249682 279587 280802 287204
Uganda Inflation annual percent change Percent 45 -20 57 51 35
67
References
Akerlof George A The Market for ldquoLemonsrdquo Qualitative Uncertainty and the Market Mechanism in Quarterly Journal of Economics Vol 84 (1970) pp 488-500
Amin Ruhul et al Integration of an Essential Service Package (ESP) in Child and Reproductive Health and Family Planning with a Micro-Credit Program for poor Women Experience from a Pilot Project in Rural Bangladesh in World Development Vol 29 (2001) No 9 pp 1611-1621
Bester Helmut Screening vs Rationing in Credit Markets with Imperfect Information in The American Economic Review Vol 75 (1985) No 4 pp 850855
Borst Dietmar Microfinance ndash Theoretische Grundlagen fuumlr den Einsatz sowie die Abschaumltzung des Potentials anhand einer Datenbankuntersuchung zur Verwundbarkeit der laumlndlichen Bevoumllkerung in Vietnam unpublished diploma thesis Karlsruhe 2004
BRAC Annual Report 2002 Dhaka 2003
Busch Alexander Kort Katharina Die Peanuts-Banker und ihre Kunden in Handelsblatt Nr 150 published August 5th 2004 p 8
Campion Anita Challenges to Microfinance Commercialization in Journal of Microfinance Vol 4 (1999) No 2 pp 57-65
Chu Michael Key Issues of Development Finance Somerville (MA) 1998
Dornbusch Ruumldiger Fischer Stanley Makrooumlkonomie Oldenburg 1995
Dunn Seth Flavin Christopher Moving the Climate Change Agenda Forward in State of the World New York London 2002 pp 24-50
Farrington Todd Efficiency in Microfinance Institutions in The MicroBanking Bulletin Issue No 4 pp 18-24
Gardner Gary The Challenge for Johannesburg Creating a More Secure World in State of the World New York London 2002 pp 3-23
Ghatak Subrata On Interregional Variations in Rural Interest Rates in Journal of Developing Areas Issue 18 pp 21-34
Gibbons David Serving the Poorest Sustainably in The MicroBanking Bulletin Issue No 5 (2000) pp 13-16
Gibbons David Meehan Jennifer W The Microcredit Summitrsquos Challenge WorkingToward Institutional Financial Self-Sufficiency While Maintaining a Commitment to Serving the Poorest Families in Journal of Microfinance Vol 1 (1999) No 1 pp 131-192
68
Goodwin-Groen Ruth Do Asian MFIs Access Funds from Commercial Banks inThe MicroBanking Bulletin Issue No 3 pp 8-10
Grameen Bank (ed) Grameen Generalized System Dhaka 2003
Gross Alexandra de Silva Samantha Social Fund Support of Microfinance A Reviewof Implementation Experience The World Bank Social Protection Discussion Paper No 0215 Washington DC 2002
Hashemi Syed M Schuler Sidney R Sustainable Banking with the Poor A Case Study of Grameen Bank Dhaka 1997
Helms Brigit Reille Xavier Interest Rate Ceilings and Microfinance The story so farConsultative Group to assist the Poor Occasional Paper No 9 September 2004 Washington DC 2004
Hoff Karla Stiglitz Joseph E Introduction Imperfect Information and Rural Credit Markets-Puzzles and Policy Perspectives in The World Bank Economic Review Vol 4 (1990) No 3 pp 235-250
Holcombe Susan Managing to Empower The Grameen Bankrsquos Experience of Poverty Allevation Dhaka 1995
Hulme David Mosley Paul Finance against Poverty London 1996
Jalvaani (ed) Flush with loans Micro credit for rural sanitation Vol 2 (1999) No 2 pp 1-2
Khandker Shahidur R Fighting Poverty with Microcredit Experience in Bangladesh Oxford et al 1998
Khandker Shahidur R Khalily Baqui Khan Zahed Grameen Bank Performance andSustainability The World Bank Discussion Paper No 306 Washington DC 1995
Lipsey Rechard G An Introduction to Positive Economics 5th edition London 1979
Littlefield Elizabeth Morduch Jonathan Hashemi Syed M Is Microfinance an Effective Strategy to Reach the Millennium Development Goals Consultative Group to Assist the Poorest Focus Note No 24 Washington DC 2003
Martinot Eric Cabraal Anil World Bank Solar Home Systems Projects Experience and Lessons Learned 1993-2000 in Renewable Energy Oxford 2000 pp 1-8
M-Cril Microfinance Review 2003 revised February 2004 Gurgaon 2004a
Mezzera Jaime Microcredit in Brazil The Gap Between Supply and Demand in The MicroBanking Bulletin Issue No 8 (2000) pp 22-24
The MicroBanking Bulletin (ed) Note to the Reader Vol 1 (1997) Issue No 1 pp 5-8
69
The MicroBanking Bulletin (ed) An Introduction to the Peer Groups and Tables Issue No 9 (2003) pp 53-60
MicroRate IADB Performance Indicators for Microfinance Institutions Technical Guide 3rd edition Washington DC 2003
MkNelly Barbara Dunford Christopher Impact of Credit with Education on Mothers and Their Young Childrenrsquos Nutrition Lower Pra Rural Bank Credit with Education Program in Ghana Freedom from Hunger Research Paper No 4 Davis (CA) 1998
MkNelly Barbara Dunford Christopher Impact of Credit with Education on Mothers and Their Young Childrenrsquos Nutrition CRECER Credit with Education Program in Bolivia Freedom from Hunger Research Paper No 5 Davis (CA) 1999
Morduch Jonathan The Microfinance Promise in Journal of Economic Literature Vol 37 (1999b) No 4 pp 1569-1614
Neus Werner Einfuumlhrung in die Betriebswirtschaftslehre Tuumlbingen 1998
Otero Maria Bringing Development Back into Microfinance Journal of Microfinance Vol 1 (1999) No 1 pp 8-19
Panjaitan-Drioadisuryo Rosintan D M Cloud Kathleen Gender self-employment and microcredit programs An Indonesian case study in The Quarterly Review of Economics and Finance Vol 39 (1999) pp 769ndash779
Perkins Dwight H et al Economics of Development 5th edition New York London 2001
Pitt Mark M Khandker Shahidur R Credit Programs for the Poor and the Health Status of Children in Rural Bangladesh in International Economic Review Vol 44 (2003) No 1 pp 87-118
Raiffeisen Friedrich W The Credit Unions 8th edition Neuwied 1966
Rhyne Elizabeth The Yin and Yang of Microfinance Reaching the Poor and Sustainability in The MicroBanking Bulletin Issue No 2 (1998) pp 6-9
Richardson David C Unorthodox Microfinance The Seven Doctrines of Success in The MicroBanking Bulletin Issue No 4 (2000) pp 3-7
Robinson Marguerite S The Microfinance Revolution Sustainable Finance for the Poor Washington DC 2001
Robinson Marguerite S The Microfinance Revolution Volume 2 Lessons from Indonesia Washington DC 2002
Rosenberg Richard Microcredit Interest Rates Consultative Group to assist the Poorest Occasional Paper No 1 revised November 2002 Washington DC 2002
70
Roth Michael Steinwand Dirk Mikrofinanz Weltweites Erfolgsmodell nur nicht inDeutschland Zur Uumlbertragbarkeit der Erfahrungen aus Entwicklungslaumlndern auf Deutschland Deutsche Gesellschaft fuumlr Technische Zusammenarbeit (ed) Eschborn2004
Schmidt Reinhard H Tschach Ingo Microfinance as a Nexus of Incentives Finance and Accounting Working Paper No 87A Frankfurt 2001
Schreiner Mark A Framework for the Analysis of the Performance and Sustainability of Subsidized Microfinance Organizations with Application to Banco Sol of Bolivia and Grameen Bank of Bangladesh unpublished PhD dissertation Columbus (O) 1997
Seibel Hans D Recent Developments in Microfinance Development Research Center Working Paper No 1998-5 Cologne 1998
Seibel Hans D History matters in microfinance in Small Enterprise Development ndashAn International Journal of Microfinance and Business Development Vol 14 (2003a) No 2 pp 10-12
Seibel Hans D Schmidt Petra How an Agricultural Development Bank Revolutionized Rural Finance The Case of Bank Rakyat Indonesia International Fund for Agricultural Development Rural Finance Working Paper B 5 Rome 2000
Sen Amartya Oumlkonomie fuumlr den Menschen ndash Wege zu Gerechtigkeit und Solidaritaumlt in der Marktwirtschaft Muumlnchen Wien 2000
Serageldin Ismail The View of the Chair in Consultative Group to Assist the Poorest Newsletter Issue No1 (1996) pp 1 11-12
Soros George Die Krise des globalen Kapitalismus Offene Gesellschaft in Gefahr Berlin 1998
Staschen Stefan Regulation and Supervision of Microfinance Institutions State of Knowledge Deutsche Gesellschaft fuumlr Technische Zusammenarbeit (ed) Eschborn 1999
Steinwand Dirk The Alchemy of Microfinance The Evolution of the IndonesianPeoples Credit Banks (BPR) to 1999 and a Contemporary Analysis Berlin 2001
Stiglitz Joseph E Peer Monitoring and Credit Markets in The World Bank Economic Review Vol 4 (1990) No 3 pp 351-366
Stiglitz Joseph E Weiss Andrew Credit Rationing in Markets with Imperfect Information in The American Economic Review Vol 71 (1981) No 3 pp 393-410
Tschach Ingo Theorie der Entwicklungsfinanzierung Mit Kleinkreditprogrammen Kredit- und Arbeitsmarktsegmentierung uumlberwinden Frankfurt 2000
UNDP Human Development Report 2004 New York 2004
71
UNFPA state of the world population 2004 New York 2004
UNICEF The State of the Worldrsquos Children 2002 NewYork Geneva 2002
Varley Robert C G Financial Services and Environmental Health Household Credit for Water and Sanitation Environmental Health Project Applied Study No 2 Washington DC 1995
Volkery Carsten Kampf um Straszligenhaumlndler in Die Zeit Nr 23 published May 27th
2004 p 33
Wardhana Ali Introduction in The Microfinance Revolution ndash Sustainable Finance for the Poor Washington DC 2001 pp XVII-XXVII
Woodworth Warner Woller Gary Greetings from the Editors Journal of Microfinance Vol 1 (1999) No 1 p 6
The World Bank Group World Development Indicators 2004 Washington DC 2004
Worldwatch Institute (2002) Vital Signs 2002 New York London 2002
Wimmer Nancy Barua Dipal Less is more Microfinance for solar energy in rural areas in Renewable Energy World Review Issue 2004-2005 Vol 7 (2004) No4 pp 170-179
Yunus Muhammad Grameen Bank II ndash Designed to Open new Possibilities Dhaka 2002
Yunus Muhammad Grameen ndash Eine Bank fuumlr die Armen dieser Welt Muumlnchen 1998a
Internet References
Abishek Lal (nd) An Overview of Microfinance and Environmental Management [http wwwgdrcorgicmenvironabhishekhtml] (availability date October 5 2004)
ACCION (nd) our history [httpwwwaccionorgabout_our_historyasp] (availability date October 5 2004)
ACCION (nd) key statistics [httpwwwaccionorgabout_key_statsasp] (availability date October 5 2004)
Ahmad Zulfiqar (nd) Forms of Regional Cooperation in Microfinance in South Asia [httpwwwbwtporgarcmpakistanIV_News_and_EventsBWTPworkshopZulfiqar20Ahmad20paper20(BWTP-PMN2029Jan04)pdf (availability date October 6 2004)
72
Ahmed Salehuddin (2003) Foreword [httpwwwpksf-bdorgaprm_summit_brochure htm] (availability date September 30 2004)
Annan Kofi (2002) Statement at The Microcredit Summit +5 [httpwww microcreditsummitorgenews2003-03_sp_chowdhuryhtml) (availability date October 5 2004)
Barnes Carolyn (2001) Microfinance Program Clients and Impact An Assessment of Zambuko Trust Zimbabwe [httpwwwmicrofinancegatewayorgfiles18553_Barnes_Zambuko_Trust_2001pdf] (availability date October 5 2004)
Barnes Carolyn Gaile Gary Kibombo Richard (2001) The Impact of Three Microfinance Programs in Uganda [httpwwwmicrofinancegatewayorgfiles2935_Barnes_2001pdf] (availability date October 5 2004)
Barua Dipal (2004) Success of Grameen Shakti in the Field of Renewable Energy Sector in Bangladesh [httpwwwrenewables2004depptPresentation1-SessionVA(14-1530h)-Baruapdf] (availability date September 30 2004)
Bhatt Ela (1997) In 1975 [httpwwwmicrocreditsummitorgdeclarationhtm] (availability date September 30 2004)
BlueOrchard (2004a) Microfinance [httpwwwblueorchardchenmicrofinance_institutions asp] (availability date October 5 2004)
BlueOrchard (2004b) January 2004 Newsletter [httpwwwblueorchardchmedialibrarywebsitenewsletter_jan_2004pdf] (availability date October 5 2004)
Brynjolfsson John (2004) John Brynjolfsson Discusses Recent Trends in TIPS Issuance [httpwwwpimcocomLeftNavPIMCO+Spotlight2004Spotlight_2_04htm] (availability date October 5 2004)
CGAP (2003) Report to the Board of Executive Directors [httpwww-wdsworldbankorgservletWDSContentServerWDSPIB20031208000012009_20031208101736RenderedPDF27441pdf] (availability date October 5 2004)
Chen Shaohua Ravallion Martin (2004) How have the worldrsquos poorest fared since the early 1980s [httpwwwworldbankorgresearchpovmonitorMartinPapersHow_have_the_poorest_fared_since_the_early_1980spdf] (availability date October 5 2004)
Cheston Susy Kuhn Lisa (2002) Empowering Women through Microfinance[httpwwwmicrofinancegatewayorgfiles3240_Cheston_2002doc] (availability date October 5 2004)
Christen Robert P et al (1995) Maximizing the Outreach of Microenterprise FinanceAn Analysis of Successful Microfinance Programs [httpwwwdecorgpdf_docsPNABS519 pdf] (availability date October 5 2004)
73
CIA (2004) The World Factbook [httpwwwciagovciapublicationsfactbook] (availability date October 5 2004)
Clear Profit (2004) Microfinance Bond Record May Double [httpwwwclear-profitcomissuescpsep04txt] (availability date September 30 2004)
Daley-Harris Sam (2003) State of the Microcredit Summit Campaign Report 2003 [httpwwwmicrocreditsummitorgpubsreportssocr2003SOCR03-E[txt]pdf] (availability date September 30 2004)
Dominiceacute Robert (2004) Interview in Microfinance Bond Record May Double [httpwwwclear-profitcomissuescpsep04txt] (availability date September 30 2004)
Donahue Jill Kabbucho Kamau Osinde Sylvia (2001) HIVAIDSmdashResponding To A Silent Economic Crisis Among Microfinance Clients In Kenya and Uganda [httpwwwmicrosave-africacomget_fileaspdownload_id=541] (availability date September 30 2004)
Donahue Jill Sussman Linda (1999) Building a Multi-Sectoral Response Follow-Up Assessment of Programming for Children and Families Affected by HIVAids in Kenya [httpwwwdecorgpdf_docspnacg778pdf] (availability date September 30 2004)
The Economist (1998) [httpwwweconomistcomdisplaystorycfmstory_id=S2629H3C28Q13F240A] (availability date September 30 2004)
Finca (nd) Introduction [httpvillagebankingorgwhereindexphp3] (availability date September 30 2004)
Fischer Stanley (2003) Statement at The Asia Society and Womens World BankingAnnual Microfinance Conference [httpwwwiiecomfischerpdffischer051303pdf] (availability date September 30 2004)
Friedman Milton (nd) Samuha [httpwwwsamuhaorgm-1htm] availability date September 30 2004)
FXTOP (2004) Historical Exchange Rates [httpfxtopcomdehistoratesphp3] (availability date September 30 2004)
Gibbons David Meehan Jennifer W (2002) Financing Microfinance for Poverty Reduction [httpwwwmicrocreditsummitorgpapersfinancing_finalpdf] (availability date September 30 2004)
Grameen Bank (2004) Grameen Bank At a Glance [httpwwwgrameen-infoorgbankcdshtml] (availability date September 30 2004)
Grameen Trust (nd) Grameen Bank Replication Program [httpwwwgrameen-infoorggrameengtrustreplicationhtml8721] (availability date September 30 2004)
74
Hossain Farhad (2004) Microfinance in Development [httpwwwvalthelsinkifi staff jkoponenb1104FarhadFeb2304pdf] (availability date October 5 2004)
IMF (2004) Data [httpwwwimforgexternalpubsftweo200402datadbginimcfm] (availability date October 5 2004)
IMI (2004) Investments [httpwwwimi-agcomoverviewindexhtml] (availability date September 30 2004)
IPCC (2001) Summary for Policymakers [httpwwwipccchpubspm22-01pdf] (availability date September 30 2004)
Jansson Tor Wenner Mark (1997) Financial Regulation and its Significance for Microfinance in Latin America and the Caribbean [httpwwwgdrcorgicmgoverniadb-janssonpdf] (availability date October 5 2004)
Ken Daniel Ten Roeun Van (2004) The Cycle of Debt - As Microcredit Institutions Grow Some Question Their Effect on Poverty [httpwwwcamnetcomkhcambodiadaily selected_featurescd-21-02-04htm] (availability date September 30 2004)
Kim Julia (2002) Social Interventions for HIVAIDS - Intervention with Microfinance for AIDS and Gender Equity [httpwwwwitsaczaradarPDF20filesIntervention_monograph_no_picspdfpdf] (availability date September 30 2004)
Llanto Gilberto (nd) Vietnam [httpwwwadborgDocumentsBooksCentral_Banks_MicrofinanceCountry_Studiesvietnampdf] (availability date September 30 2004)
The Microfinance Gateway (nd) Frequently Asked Questions [httpwwwmicrofinance gatewayorgsectionfaq1] (availability date October 5 2004)
Microfinance Rating and Assessment Fund (2004) Qualified Raters [httpwwwmfrating orgmfi_institutionsqualified_ratershtml] (availability date October 5 2004)
Microcredit Summit (1997) Declaration and Plan of Action [httpwwwmicrocreditsummit orgdeclarationhtm] (availability date September 30 2004)
MicroRate (nd) Performance Indicators and Ratios [httpwwwmicroratecomENGLISHsiteRATINGSindicatorshtml] (availability date September 30 2004)
MicroRate (2002) The Finance of Microfinance [httpwwwmicroratecomPDFFinance20of20Microfinancepdf] (availability date September 30 2004)
MicroRate (2004) Adjusted comparison table [httpwwwmicroratecomENGLISHsitePDFAdjusted20Comparison20Table060320engpdf] (availability date October 5 2004)
75
Mix Market (2004) The Mix Market [httpwwwmixmarketorg] (availability date October 5 2004)
Morduch Jonathan (1999b) The Grameen Bank A Financial Reckoning [httpwwwwwsprincetonedu~rpdsmacarthurdownloadsmorduch_grameen_bankpdf] (availability date September 30 2004)
Pallen Dean (1997) Environmental Sourcebook for Micro-Finance Institutions [httpwwwacdi-idagccaINETIMAGESNSFvLUImagesea20summaries$fileSOURC Epdf] (availability date September 30 2004)
Prisma (2002) The Case for Private Capital Market Creation in the Development Field of Microfinance [httpwwwsocialenterprisenetpdfsprivate_capital_marketpdf] (availability date September 30 2004)
Schmidt Reinhard H Zeitinger C-P (1997) Critical Issues in Microbusiness Finance and the Role of Donors No 6 [httpwwwgdrcorgicmmfi-donorpdf] (availability date September 30 2004)
Seibel Hans D (2003b) Commodity finance a commercial proposition Micro- and Mesofinance for Agricultural Commodity Production Processing and Trade [httpwwwuni-koelndeew-fakaef05-20042003-420Commodity20Financepdf] (availability date September 30 2004)
Simanowitz Anton Walter Alice (2002) Ensuring Impact Reaching the Poorest while Building Financially Self-sufficient Institutions and Showing Improvement in the Lives of the Poorest Families [httpwwwidsacukimpactPublicationsWorkingPapersOP3MCSSumdoc] (availability date September 30 2004)
Smith Stephen C Jain Sanjay (1999) Village Banking and Maternal and Child Health Theory and Evidence from Ecuador and Honduras[httphomegwuedu~scsmith healthrevwd801pdf] (availability date September 30 2004)
United Nations (1999) International Year of Microcredit 2005 [httpods-dds-nyunorgdoc UNDOCGENN9976933PDFN9976933 pdfOpenElement] (availability date October 5 2004)
United Nations (2000) United Nations Millennium Declaration [httpods-dds-nyunorgdocUNDOCGENN0055951PDFN0055951pdfOpenElement] (availability date October 5 2004)
US Census Bureau (2004) Total Midyear Population for the World 1950-2050 [httpwwwcensusgovipcwwwworldpophtml] (availability date October 5 2004)
WHO (2004) Making pregnancy safer [httpwwwwhointmediacentrefactsheets fs276en] (availability date September 30 2004)
WHO (2001) Child Health [httpwwwwhointmipfiles2082AAGChildHealthpdf] (availability date September 30 2004)
76
The World Bank Group (nd) Health Nutrition and Population and the Millennium Development Goals [www1worldbankorghnpMDGMDG20-20HNPbookletpdf] (availability date September 30 2004)
Yunus Muhammad (1998) Championing the Right to Credit for Poor Women Around the World [httpaspgrameencom dialoguedialogue34interviewhtml] (availability date September 30 2004)
UNAIDS (2004) [httpwwwunaidsorgbangkok2004GAR2004_pdfUNAIDSGlobalReport2004_enpdf] (availability date September 30 2004)
Ratings
M-Cril (2000) SPANDANA [httpwwwratingfundorgspanishdocsSPANDANA_RatingReportpdf] (availability date October 7 2004)
M-Cril (2001a) BASIX [httpwwwbasixindiacomMcrilasp] (availability date October 7 2004)
M-Cril (2001b) BDB [httpwwwratingfundorgspanishdocsRF_BDBpdf] (availability date October 7 2004)
M-Cril (2001c) SNEHA [httpwwwratingfundorgspanishdocsRF_Sneha-u1pdf] (availability date October 7 2004)
M-Cril (2002a) KCLF [httpwwwratingfundorgdocsRF-KCLF-risk20reportdoc] (availability date October 7 2004)
M-Cril (2002b) NWTF [httpwwwratingfundorgspanishdocsRF_NWTFpdf] (availability date October 7 2004)
M-Cril (2002c) SEEDS [httpwwwratingfundorgspanishdocsRF_SEEDS_2002_Ratingpdf] (availability date October 7 2004)
M-Cril (2002c) Share [httpwwwratingfundorgspanishdocsRF_SHAREpdf] (availability date October 7 2004)
M-Cril (2002d) TSKI [httpwwwratingfundorgspanishdocsRF_Tski_mcrilfinal(-) reportpdf] (availability date October 7 2004)
M-Cril (2003a) ASA [httpwwwratingfundorgdocsASA20updatepdf] (availability date October 7 2004)
M-Cril (2003b) BURO [httpwwwm-crilcomburopdf] (availability date October 7 2004)
M-Cril (2003c) EMT [httpwwwratingfundorgdocsEMTpdf] (availability date October 7 2004)
77
M-Cril (2003d) SKS [httpwwwmixmarketorgendemanddemandshowprofileaspett=25ampshowinfo=adjusted] (availability date October 7 2004)
M-Cril (2003d) TPC [httpwwwratingfundorgdocsTPC_Finalpdf] (availability date October 7 2004)
M-Cril (2004b) UPAP [httpwwwratingfundorgdocsUPAP_2004pdf] (availability date October 7 2004)
Microfinanza (2002a) ACME [httpwwwratingfundorgspanishdocsACME_finalpdf] (availability date October 7 2004)
Microfinanza (2002b) BTFF [httpwwwratingfundorgspanishdocsBTFF_RatingReportpdf] (availability date October 7 2004)
Microfinanza (2002c) BESA [httpwwwratingfundorgspanishdocsBESA_RatingReportpdf] (availability date October 7 2004)
Microfinanza (2002d) CAME [httpwwwratingfundorgdocsEvaluacionCAME(-) Finaldoc] (availability date October 7 2004)
Microfinanza (2002e) RFF [httpwwwratingfundorgdocsRFF20finalpdf] (availability date October 7 2004)
Microfinanza (2002f) PSHM [httpwwwratingfundorgspanishdocsPSHM_Reportpdf] (availability date October 7 2004)
Microfinanza (2003) CAJCA [httpwwwratingfundorgdocsCalificacion_Jardin_Azuayo_ratingpdf] (availability date October 7 2004)
Microserve (2003) ENDA [httpwwwmixmarketorgendemanddemandshowprofileaspett=865ampshowinfo=adjusted] (availability date October 7 2004)
Planet Rating (2002a) FONDEP [httpwwwmfratingorgRatingscompleted_ratingshtml] (availability date October 7 2004)
Planet Rating (2002b) PRIZMA [httpwwwmixmarketorgendemanddemandshowprofileaspett=111ampshowinfo=adjusted] (availability date October 7 2004)
Planet Rating (2002c) SWS [httpwwwratingfundorgspanishdocsSWC_reportpdf] (availability date October 7 2004)
Planet Rating (2002d) ZAKOURA [httpwwwratingfundorgspanishdocsRF_Zakourapdf] (availability date October 7 2004)
Planet Rating (2003a) AMSSF [httpwwwratingfundorgdocsPlanetRating_AMSSF_010803pdf] (availability date October 7 2004)
Planet Rating (2003b) FOCCAS [httpwwwratingfundorgdocsPlanetRatingFOCCAS120803pdf] (availability date October 7 2004)
78
Planet Rating (2003c) PADME [httpwwwmfratingorgdocsPlaNetRatingPADME070302_Englishpdf] (availability date October 7 2004)
Planet Rating (2003d) PAPME [httpwwwmfratingorgdocsPAPME_PlanetRating080903pdf] (availability date October 7 2004)
Planet Rating (2003e) VITAL FINANCE [httpwwwmfratingorgdocsVital20Finance_Sept202003pdf] (availability date October 7 2004)
Planet Rating (2004a) ABA [httpwwwratingfundorgdocsABA_April202004pdf] (availability date October 7 2004)
Planet Rating (2004b) ACEP [httpwwwmfratingorgdocsACEPSeacuteneacutegal_2004pdf] (availability date October 7 2004)
Planet Rating (2004c) AGROINVEST [httpwwwratingfundorgdocsAgroInvest_June202004pdf] (availability date October 7 2004)
Planet Rating (2004d) ASBA [httpwwwratingfundorgdocsASBA_April202004pdf] (availability date October 7 2004)
Planet Rating (2004e) DBACD [httpwwwratingfundorgdocsDBACD_April202004pdf] (availability date October 7 2004)
Planet Rating (2004f) FINADEV [httpwwwmfratingorgdocsFinadev_2004pdf] (availability date October 7 2004)
Planet Rating (2004g) MI-BOSPO [httpwwwratingfundorgdocsMIBOSPO_160404pdf] (availability date October 7 2004)
Planet Rating (2004h) SBACD [httpwwwratingfundorgdocsSBACD_PlanetRating300604pdf] (availability date October 7 2004)
Other Sources
Interview Shaw Newaz Deputy General Manager of the Grameen Bank October 30th
2003
Hodson Charles (2001) Your Business Your World Jim Boulden CNN (ed) Dhaka 2001
12
poor women in India41 Although the latter examples still were subsidized projects they
used a more business oriented approach and showed the world that poor people can be
good credit risks with repayment rates exceeding 9542 even if the interest rate charged
is higher than that of traditional banks Another milestone was the transformation of
BRI starting in 1984 Once a loss making institution channeling government subsidized
credits to inhabitants of rural Indonesia it is now the largest MFI in the world being
profitable even during the Asian financial crisis of 1997 ndash 199843
In February 1997 more than 2900 policymakers microfinance practitioners and
representatives of various educational institutions and donor agencies from 137
different countries gathered in Washington DC for the first Micro Credit Summit This
was the start of a nine year long campaign to reach 100 million of the world poorest
households with credit for self employment by 200544 According to the Microcredit
Summit Campaign Report 67606080 clients have been reached through 2527 MFIs by
the end of 2002 with 41594778 of them being amongst the poorest before they took
their first loan45 Since the campaign started the average annual growth rate in reaching
clients has been almost 40 percent46 If it has continued at that speed more than 100
million people will have access to microcredit by now and by the end of 2005 the goal
of the microcredit summit campaign would be reached As the president of the World
Bank James Wolfensohn has pointed out providing financial services to 100 million of
the poorest households means helping as many as 500 ndash 600 million poor people47
41 See Bhatt (1997)42 See Yunus (1998a) p 143 et sqq43 See Robinson (2002) p 38044 See Daley-Harris (2003) p 345 ldquoThe Microcredit Summit Campaign defines ldquopoorestrdquo as those who are in the bottom half of those living below their nationrsquos poverty line or are living on less than $1 a day adjusted for purchasing power parity (PPP)rdquo See Daley-Harris (2003) p 3 This definition will also be used throughout this paper46 See Daley-Harris (2003) p 1847 See Morduch (1999a) p 1570
13
3 The Impact of Microcredit
31 Microcredit and the Millennium Development Goals
In 1996 Ismail Serageldin the then chair of the Consultative Group to Assist the Poorest
(CGAP)48 claimed that ldquo[m]icrofinance is a proven instrument to assist the very poorrdquo49
This view is also shared by the World Watch Institute50 and underlines what has been
stated above namely that microfinance can be used as a strong anti-poverty tool But
does microfinance actually meet these expectations and keep this promise51
The impact that microcredit has on the lives of poor people will be demonstrated by
showing how it contributes to each of the eight Millennium Development Goals
(MDGs)52 which are related to the reduction of poverty in all its forms These goals
were resolved in September 2000 by the General Assembly of the UN in their
Millennium Declaration53
32 The Eradication of extreme Poverty and Hunger
The aim of the first MDG is to halve the proportion of people who live on less than $1 a
day between 1990 and 2015 According to current population projections of the World
Bank54 this would equal 849 million people in 201555
48 The Consultative Group to Assist the Poorest is a consortium of 28 public and private development agencies working together to expand access to financial services for the poor in developing countries and was established by the World Bank in 1995 Recently it changed its name to Consultative Group to Assist the Poor49 See Serageldin (1996) p 1150 See Gardner (2002) p 1851 See Morduch (1999a) pp 1569 et sqq52 The Millennium Development Goals are (1) eradicate extreme poverty and hunger (2) achieve universal primary education (3) promote gender equality and empower women (4) reduce child mortality (5) improve maternal health (6) combat HIVAIDS malaria and other diseases (7) ensure environmental sustainability and (8) develop a global partnership for development53 See United Nations (2000)54 See World Bank (2004) p 38 et sqq55 Although it is not explicitly mentioned in the Millennium Declaration it is commonly assumed that the share of people living on less than $1 in low and middle income countries should be halved If the share would be calculated with regard to the worldrsquos total population the goal for 2015 would 818 million people For the worldrsquos total population in 1990 see US Census Bureau (2004)
14
Today almost 11 billion people live on less than $1 and more than 27 Billion live on
less than $2 per day56 The mean income for those living under $1 a day is $077 and it
is $125 for those living under $2 a day57 While the number of people living on less
than $1 per day is slowly decreasing and is expected to be 913 million in 2015 the
number of people living on less than $2 a day is actually increasing58 One of the
outcomes from this degree of poverty is that more than 27000 children die every day
from mostly preventable diseases many of them related to hunger59
Microcredit enables poor people to start new businesses or to diversify existing ones
which helps them to increase their income In addition to large amounts of anecdotal
evidence several studies have documented the positive economic impact microcredit
has on its clients Cloud and Panjaitan-Drioadisuryo have found that the average income
of a sample of BRI borrowers has increased by 112 percent and that 90 percent of their
families have crossed the poverty line60 Only 12 out of the 121 respondents of that
study reported that their income had not increased61 According to the Grameen Bank
website 5109 percent of their clients have crossed the poverty line since they took their
first loan62
A study conducted by Barnes showed that the program of the Zambuko Trust a local
MFI in Zambia had a considerable impact on the poorest clients consumption of meat
fish and chicken63 While 76 percent of the continuing clients of the MFI called Share in
India significantly increased their income and 50 percent have crossed the poverty line 64 Khandker discovered in his well known study ldquoFighting poverty with microcreditrdquo
that there is a connection between the microcredit programs of three Bangladeshi MFIs
and household per capita expenditure For every dollar borrowed by a Grameen Bank
member household consumption increases by $018 In addition he found that 5 percent
56 See Chen and Ravallion (2004) p 2957 In fact those people live on less than $108 and $215 respectively a day in 1993 PPP This means that the nominal dollar value of their income is considerably lower See Chen and Ravallion (2004) p 9 58Both numbers are decreasing in Asia but increasing in the rest of the world See Chen and Ravallion (2004) p 22 et sqq59 See UNICEF (2002) p 660 A consistent definition of the term ldquopoverty linerdquo does not exists among different nations Therefore the term will be used according to the definition of the respective country in this paper61 See Panjaitan-Drioadisuryo and Cloud (1999) p 77562 See Grameen Bank (2004) 63 See Barnes (2001) p 8664 See Simanowitz and Walter (2002) p 16
15
of Grameen Bank borrowers move out of poverty every year65 Supposing Khandkerrsquos
findings were correct for all MFIs worldwide and the Microcredit Summit Campaign
achieved its goal of reaching 100 million of the poorest households with microcredit by
2005 then 25 million people (assuming an average family size of five) would leave
poverty every year66 Although this number would have to be adjusted in order take into
consideration the MFI clients who have crossed the poverty line already and of course
the experiences made in Bangladesh can not be transferred precisely to other countries
it still demonstrates the enormous effect that microcredit can have on assisting the
poorest to move out of poverty
Although a 1996 study of Hulme and Mosley states that providing microcredit can also
have a negative impact on the income of the poorest households67 these findings can
be considered as disproved by the recent bulk of evidence drawing favorable
conclusions68
33 Achievement of universal primary Education
The aim of the second MDG is to ensure that all children will be able to complete
primary school by 2015
Currently more than 100 million children most of them girls are not in school69
Besides school fees poor households often can not afford to send their children to
school because they need them to help in the family business
Microcredit programs mainly contribute to the second MDG by increasing families
income and therefore enabling parents to send their children to school Barnes Gaile
and Kibombo found that clients of an MFI in Uganda spent significantly more on
childrenrsquos education than non-clients70 and in Zambia Barnes showed that ongoing
participation in the Zambuko Trustrsquos program had a positive impact on the members
65 See Khandker (1998) p 5666 See Daley-Harris (2003) p 2467 See Hulme and Mosley (1996) p 180 et sqq 68 See Gibbons and Meehan (1998) p 13669 See UNICEF (2002) p 2270 See Barnes Gaile and Kibombo (2001) p 64
16
children staying in school71 In Bangladesh the probability of girls enrolling in school
increased by 19 percent for every 1 percent increase in Grameen Bank loans to female
clients For boys this number was even higher with the mean being 24 percent72
34 Promote gender Equality and empower Women
The aim of the third MDG is to eliminate the disparity in the ratios of girls to boys in
primary secondary and tertiary education in the ratio of literate females to males and to
increase the share of women in the labor market and in parliament73
At present the literacy rate for women is lower than for man all over the world
According to the Human Development Report 2004 the average female literacy rate as
a percentage of male literacy rate is 759 in developing countries and is as low as 37 in
Niger74 But women are not only discriminated against in education but also in access to
medical services and therefore have a higher mortality rate than man75 The worldwide
tendency for women to be underrepresented in the labor market and in the parliaments is
even more severe in developing countries76 Although several women have become
heads of state in various Asian countries (eg Bangladesh India and Indonesia) this is
probably due to them being wives or daughters of former respected male politicians
Since women have a higher repayment rate than man77 and also tend to invest increases
in income on the household and on their children rather than on themselves78 most
MFIs prefer female clients79 Therefore they empower women in many ways Often
MFIs not only encourage women to become involved in financial transactions for the
first time but also to become independent active members of the economy and to
acquire assets in their own names Cheston and Kuhn found that 68 percent of the
women participating in an MFI program in Nepal ldquohellip experienced an increase their
71 See Barnes (2001) p 8472 See Khandker (1998) p 4973 See World Bank (2001) p 2074 See UNDP (2004) pp 225 et sqq75 See Sen (2000) p 23276 See Sen (2000) pp 242 et sqq77 See Littlefield Morduch and Hashemi (2003) p 778 See Yunus (1998a) pp 116 et sqq79 According to the Microcredit Summit Campaign Report 79 or 37677080 of the poorest clients were women See Daley-Harris (2003) p 3
17
decision-making roles in the areas of family planning childrenrsquos marriage buying and
selling property and sending their daughters to school - all areas of decision making
traditionally dominated by menrdquo80 The program of the Lower Pra Rural Bank in Ghana
had an positive impact on womenrsquos participation in the community81 which is true as
well for the CRECER program in Bolivia82 In Bangladesh the Grameen Bank and the
Bangladesh Rural Advancement Committee (BRAC) the two biggest MFIs of the
country had a significant positive effect on womenrsquos empowerment measured through
eight different indicators83 After joining Grameen Bank only 21 percent of the female
members considered themselves as unemployed while this number was 50 percent
before joining84 According to the Grameen Bank website 93 percent of the Bankrsquos
shares are owned by their borrowers which elect the members of the board every three
years They also get familiar with the election process by more frequently voting for
representatives at the lower level of the organizational structure Partly because of this
experience they are more likely to run for public office In the 2003 local government
elections Grameen Bank members constituted 24 of the seats reserved for women
while they represent less than 10 of Bangladeshi adult female population85 Female
clients of MFIs from countries like the Philippines Bolivia and Nepal have reported
similar occurrences86
35 Reduce Child Mortality and improve Maternal Health
The aim of the fourth MDG is to reduce the under-five mortality rate by two-thirds
between 1990 and 2015 and the fifth MDG strives for a three quarter reduction in the
maternal mortality ratio by the same date
As has been stated above more than 10 million children are dying annually in the
developing world of mostly preventable causes with malnutrition playing a role in over
80 See Cheston and Kuhn (2002) p 1881 See MkNelly and Dunford (1998) p 5482 See MkNelly and Dunford (1999) p 7183 The eight different indicators are ldquofreedom of movement economic security ability to make small and larger independent purchases participation in important family decisions relative freedom from domination by the family political and legal awareness and participation in political campaigning and public protestsrdquo Hashemi and Schuler (1998) p 3684 See Holcombe (1995) p 5185 See Grameen Bank (2004)and CIA (2004)86 See Littlefield Morduch and Hashemi (2003) p 8
18
half of the childrsquos deaths and in over 50 countries child mortality rates are greater than
100 deaths per 1000 live births87 Maternal mortality is also a significant problem in the
developing world with more than 500000 women dying every year from pregnancy
related causes88
MFIs are mainly contributing to the these MDGs by increasing families income and
therefore enabling the households to afford better nutrition and medical services
Furthermore they are often linked with microinsurance or health education programs
In addition to what has been showed in chapter 31 Pitt Khandker and Millimet
estimate that a 10 percent increase in the loan size of a female borrower in Bangladesh
increases the arm circumference of their daughters by 6389 Smith and Jain found that
village banking in Ecuador had a positive effect on child diarrhea90 which is responsible
for 15 of child deaths91 Since Sen argues that an improved status of women within
the family reduces child mortality92 the empowerment of women through MFIs is also
contributing to this cause
Although no study has been conducted so far on the direct impact of microcredit on
maternal health it can be assumed that an overall improvement of access to medical
services reduces maternal mortality as well A study of the Morgan State University for
example suggests that microcredit has a positive effect on the prevalence of
contraceptives93 which leads to a decrease of unwanted pregnancies and therefore
reduces maternal death
36 Combat HIVAIDS Malaria and other diseases
The aim of the sixth MDG is to halt and begin to reverse by 2015 the spread of
HIVAIDS malaria and other major diseases and to assist children orphaned by HIV
87 See World Bank (2001) p 888 See WHO (2004) 89 See Pitt Khandker and Millimet (2003) p 11390 See Smith and Jain (1999) p 3791 See WHO (2001) 92 See Sen (2000) p 23593 See Amin et al (2001) p 1614
19
In 2003 29 million people died because of HIV and about 48 million became infected
the greatest number since AIDS was discovered 23 years ago94 This pandemic has lead
to a tremendous decrease in the life expectancy in the hardest hit countries Botswana
for example one of the richest and most democratic countries in Africa has a
HIVAIDS adult prevalence rate of 388 and a life expectancy at birth of less than 31
years95
Malaria not only causes more than one million deaths annually it leads also to 300 ndash
500 million clinical cases a year Both numbers have been steadily increasing over the
past two decades96 More than two million people a year are killed by tuberculosis
another global health problem This curable disease is estimated to cost poor
communities about $12 billion every year since even those who survive normally lose
more than 3 month of work time while recovering97
MFIs contribute to the sixth MDG in several ways By increasing clientrsquos income they
help households affected by HIV or other diseases to better cope with the situation
Besides spending more money on health services and nutrition MFI clients also tend to
be more able and willing to support AIDS orphans than non clients98 In addition to the
already stated increase in the use of contraceptives99 several innovative approaches to
deal with disease related crisis have also arisen This is of course necessary not only to
counteract the devastating effect the above discussed epidemics can have on MFI
clients but also to not put the viability of the respective institution at risk One option is
to integrate education services in the MFI programs and encourage clients to form
solidarity groups100 It has been shown that these services do not necessarily decrease
the effectiveness of the institutionsrsquo employees101 Another way is to strengthen the ties
to NGOs specialize in dealing with the respective disease Synergies gained through this
cooperation can help clients to better deal with the situation and in the end increase their
94 See UNAIDS (2004) p 2395 See CIA (2004)96 See World Bank (2001) p 1697 See World Bank (2001) p 1298 See Barnes (2001) p 6499 See also Kim et al (2002) p 18100 See Donahue and Sussman (1999) p A 14101 See Donahue Kabbucho and Osinde (2001) p 25
20
repayment rates Various MFIs also have introduced loan and health insurance products
or cultivated linkages with organizations doing so102
It has to be stated that despite the benefits MFIs can provide to people effected by
HIVAIDS or other diseases microcredit can also be a burden for those who are already
chronically ill These people can still benefit through loans provided to members of the
family or the community or through one of the other services mentioned above
37 Ensure environmental Sustainability
The aims of the seventh MDG are to support and promote the principles of sustainable
development and put them into action and to improve the lives of slum dwellers and
people without sustainable access to safe drinking water and sanitation
Today climate change is considered as the major environmental problem103 The
Intergovernmental Panel on Climate Change (IPCC) states that human activities
contribute to most of the 06 degC increase in global average temperature over the 20th
century and the predicted increase of another 14 to 58 degC between 1990 and 2100104
Emission of carbon from fossil fuel is reported to have the dominant influence on this
development While the total emission was 16 billion tons in 1950 it was already 65
billion tons in 2000 and is expected to continue to grow105 This development would
lead to a rise in the average sea level of between 9 and 88 centimeters during the next
century106 Furthermore it is predicted that global warming increases the risk of extreme
events like cyclones or floods leads to an increase in the number of people infected by
diseases like malaria and decreases the potential crop harvest and water availability
especially in developing countries107 In 2000 already 11 billion people lacked access to
clean drinking water and 24 billion to basic sanitation108
102 See Barnes (2001) p 40 Barnes Gaile and Kibombo (2001) p 13 and Grameen Bank (2004)103 See Gardner (2002) p 5104 See IPCC (2001) pp 2 et sqq105 Worldwatch Institute (2002) p 52 et sqq106 See IPCC (2001) p 16107 See Dunn and Flavin p 29108 See UNFPA (2004) p 18
21
MFIs contribute to achieving the seventh MDG in several ways By providing loans for
the purchase of renewable energy technologies they help people in developing
countries to increase their per capita energy consumption without increasing the carbon
dioxide emission In a 2003 survey of 140 MFIs from 80 different countries 21 said
they provide credits for solar home systems and another 19 stated they are interested in
becoming engaged in this business109 While Grameen Shakti a rural energy service
company cooperating with the Grameen Bank in Bangladesh has already installed more
than 23000 solar home systems110 a 2000 World Bank study reports twelve projects
providing solar home systems to rural households with a target of 500000
installations111 It has also been suggested that MFIs should raise environmental
awareness among their clients112 but so far no data is available on how staff can cope
with this additional task Many MFIs also provide loans for improvements in sanitation
and the water supply of their clients Varley gives several examples from Africa Asia
and Latin America on how microcredit not only has helped to invest in rainwater
collection systems but also how it has enabled households to increase their water
supply through community water associations113 In addition many MFIs provide credit
for the construction of sanitary latrines114 The situation of slum dwellers is also
positively effected by MFIs Directly through their services in poor urban communities
and indirectly by creating jobs in rural areas and therefore easing the pressure on urban
labor markets
38 Develop a global Partnership for Development
The eight MDG is about the means to achieve the other seven MDGs It calls for all
players involved in the endeavor of development and poverty eradication to work as
partners in a global context
Again MFIs are contributing to the eight MDG in many ways This is occurring through
international networks that provide funding and technical assistance through internet
information portals and specialized journals through social and for profit investors and
109 See Wimmer and Barua (2004) p 174110 Barua (2004) 111 See Martinot and Cabraal (2000) p 6112 See Pallen (1997) p 11 Lal (nd)113 See Varley (1995) pp 39 et sqq114 See Jalvaani (1999) pp 1 et sqq Varley (1995) pp 39 et sqq
22
specialized rating agencies The Bangladesh-based Grameen Trust is one of around 30
networks in operation Besides collaborating with over 200 MFIs around the world it
has directly operated three projects in Afghanistan Kosovo and Myanmar115 While the
ACCION network serves almost 12 million active clients in 19 countries throughout
America and sub-Saharan Africa116 FINCArsquos network operates in three different
continents where it serves more than 200000 customers117 In November 1997 the
MicroBanking Bulletin (MBB) was first published by the microfinance program at the
Economic Institute at the University of Colorado118 Its aim is to develop a database on
the financial performance of MFIs from all over the world which is now available
through the Mix Market an internet portal that also provides information about more
than 300 MFIs investors donor institutions and other related development
organizations119 Two years later the Marriott School at Brigham Young University
started to publish the Journal of Microfinance which has an editorial board of
microfinance experts from all over the world and offers the latest research on this
topic120 In the late 1990s a number of companies became attracted by the microfinance
market and started to invest in MFIs The German based Internationale Mikro
Investitionen Aktiengesellschaft (IMI) for example has already invested more than euro46
million in 19 MFIs in four different continents and plans to invest another euro27 million
before October 2004121 BlueOrchard Finance a microfinance investment consultancy
has channeled more than $60 million worth of private capital to some 40 MFIs
worldwide through investment funds and bond issues122 Big commercial banks like
Citigroup Deutsche Bank and ABN Amro also started to get involved in the
microfinance sector although this is mainly still perceived as a public relation activity
and not as a for-profit investment123 There are also several rating agencies specializing
in MFIs Dependent on their rating these institutions can help MFIs to receive money
from donors or investors Four of the most prominent rating agencies are PlanetFinance
115 See Grameen Trust (nd)116 See ACCION (nd)117 See FINCA (nd)118 See MicroBanking Bulletin (1997) p 5119 See The Mix (2004)120 See Woodworth and Woller (1999) p 6121 See IMI (2004)122 See BlueOrchard (2004b) p 3123 See Busch and Kort (2004) p 8 Fischer (2003) p 6
23
with headquarters in France M-Cril based in India Microfinanza in Italy and
MicroRate with offices in the USA and South Africa124
124 See Microfinance Rating and Assessment Fund (2004)
24
4 Microcredit Outreach
41 The Demand for Microcredit
Although it has been shown that microcredit is one of the most effective poverty
eradication tools that it is considered a human right by some of its advocates125 and it
can contribute considerably to the development of the financial sector in developing
countries an enormous gap still exists between supply and demand for microcredit
Estimates on the demand for microcredit vary greatly While USAID estimates the
number of potential microfinance clients is between 100 and 200 million126 the
Microcredit Summit Campaign states the total demand is more than 234 million
people127 CGAP recognizes some 500 million micro-entrepreneurs who have the
potential to become customers of MFIs128
Marguerite Robinson calculates the demand as follows ldquoAssuming five people to a
household among the 45 billion people living in low- and lower-middle-income
economies in 1999 (World Bank World Development Report 20002001) there are 900
million households in those economies If estimating conservatively we assume that
informal commercial moneylenders supply credit to 30 percent of these households at
least once a year this would mean that there are 270 million households borrowing
from informal moneylenders in a year Undoubtedly however many of these
households borrow multiple times within a yearrdquo129 Although this is a very rough
estimate assuming big differences in demand for microcredit in different countries the
number seems to be the most meaningful In contrast to the estimate of the Microcredit
Summit Campaign it does not include every single household living on less than $1 a
day but according to the definition presented in chapter 1 it counts everyone who has
no regular access to traditional financial institutions but demands such services
Obviously not all people who draw on moneylenders have financial needs that could be
matched through MFIs On the other hand interest rates charged by moneylenders tend
125 See Yunus (1998b) 126 See Christen et al (1995) p 15127 See Daley Harris (2003) p 22 128 See Robinson (2001) p 26129 See Robinson (2001) p 215
25
to be considerably higher than those of MFIs The former normally charge effective
monthly rates between ten and several hundred percent per month the latter generally
charge between 15 and five percent which enables them to attract additional clients130
42 The Supply of Microcredit
In spite of the impressive growth of MFIs around the world the demand for microcredit
is far from being met and this it is not likely to change in the near future The
Microcredit Summit Campaign reported that by the end of 2002 67606080 clients131
were reached through MFIs and that this number has increased by almost 40 percent
annually for the last five years132 It is likely that this tremendous speed of growth is at
least partly due to including MFIs which have not been reporting to the Campaign from
its start in 1997 although they have already existed at that time These institutions
contributed 22 percent to the growth in poorest clients in 2000 578 percent in 2001 and
338 percent in 2002 The growth of the poorest clients increased at least party because
of an expanded definition of the term ldquopoorestrdquo133 Since the contribution of MFIs
which previously have not been considered can be expected to decrease dramatically
the growth rate as stated by the Microcredit Summit Campaign can not be used to
predict the future development of the microfinance sector Another factor likely to slow
down the growth is the concentration of microfinance activities in some Asian countries
where almost 90 percent of the poorest microfinance clients live today134 Even if one
takes into consideration the relative size of Asiarsquos population and the fact that many
MFI customers in Latin America are relatively better off and therefore are not included
in this numbers the coverage of this part of the world far exceeds the others In
Bangladesh for example the microfinance market is close to saturation More than
eleven million households were served by several hundred MFIs in 2001135 Among
them are Grameen Bank and BRAC two of the best known MFIs in the world both
providing their services to more than three million customers With an average
household size of five it can be assumed that in Bangladesh the number of people
130 See Gibbons and Meehan (1999) pp 144 et sqq131 41594778 of them belonged to the poorest before they took their first loan The relative numbers in the following are for these poorest clients only since no other current data was available It can be assumed though that this works as a good proxy for the total number of clients 132 See Daley Harris (2003) p 3133 See Daley Harris (2003) p 17134 See Daley Harris (2003) p 21135 See Ahmed (2003)
26
benefiting from microcredit already surpasses the number of people living below the
poverty line which is estimated to be slightly higher than 50 million136 Therefore
Bangladesh will not contribute to the growth of the microfinance sector as much as it
has done in previous years This is also true for Vietnam Thailand and to a lesser
extent Indonesia Eight of the nine MFIs serving more than one million clients are based
in these countries while the ninth is based in India where due to its one billion
inhabitants the microfinance market is still far from saturation137 In contrast the
supply in Brazil meets less than two percent of the demand which is estimated to be
about 58 million potential clients138 For these reasons greater amount of future growth
must come from smaller or new MFIs in Latin America India China and especially
Africa where almost 30 percent of the worldrsquos poorest live139
43 Meeting the Demand
To fill the gap between the demand and supply for microcredit tremendous investments
are necessary to increase the loan funds of MFIs and build up their capacity through
upgrading existing institutions or building new ones Again estimates on how much
capital is needed vary greatly with the highest being at more than $300 billion140
In 1997 the Microcredit Summit Campaign estimated that $216 billion would be
needed to achieve their goal of providing microcredit to 100 million of the poorest
households This was calculated in the following way Since some 8 million people
already received microcredit in 1997 another 92 million needed to be reached
Assuming $200 ($150 for loan fund and $50 for capacity building) would be needed per
person for 88 million people in developing countries and $1000 ($500 for loan fund and
$500 for capacity building) would be needed for 4 million people in industrialized
countries the capital required ends up to be $216 billion141 For several reasons this
136 See CIA (2004)137 These institutions are The Grameen Bank BRAC Proshika and the Association for Social Advancement (ASA) in Bangladesh the Vietnam Bank for Agriculture and Rural Development (VBARD) and the Vietnam Bank for the Poor (VBA) in Vietnam BRI in Indonesia Bank for Agriculture and Agricultural Co-operatives (BAAC) in Thailand the National Bank for Agriculture and Rural Development (NABARD) in India See Ahmed (nd) p 1 Llanto (nd) p 337138 See Mezzera (2002) p 23139 See See Chen and Ravallion (2004) p 29140 See Clear Profit (2004) Prisma (2002)141 See The Microcredit Summit (1997)
27
number is not qualified to predict the total amount of capital needed to meet the demand
for microcredit On the one hand it focuses mainly on the low end of the market and
therefore underestimates the average loan fund needed On the other hand it does not
take the increasing capital demand from established MFIs into account A survey of 119
MFIs found that the average loan size to increased from $406 in 2002 to $498 in
2003142 This is mainly due to the fact that MFI clients once they have paid back their
loans usually demand larger ones for the continual development of their businesses
and therefore further increase the demand for capital of established MFIs The Grameen
Bank for example has a ceiling on its loans which increases or decreases depending on
the borrowers performance regarding repayments and savings143 While the maximum
amount for the first loan is fixed at approximately $75144 the largest loan disbursed so
far was $17195145 Thus if one estimates that by now 100 million people are borrowing
from MFIs146 another 170 million need to be reached to meet the estimated demand
Assuming an average of $600 ($400 for loan fund and $200 for capacity building) is
needed for every new client and another $200 is needed for every existing client to meet
the demand for larger loans a total of $122 billion is required This rough estimate
helps to convey the approximate amount of capital needed to meet the demand for
microcredit
So far the demand for funds is being partly met by donors which annually provide
between $500 million and $1 billion147 and through the mobilization of local savings
Obviously the amount of money provided by donors will not be able to meet the capital
demand for microcredit in the short term The mobilization of savings on the other hand
has been extremely successful in some cases with BRI probably being the most
prominent example After adapting commercial principals in October 1984 BRI was
able to raise its deposits from $161060 to more than $32 billion in 2003 which equals
almost two times its current loan portfolio148 Many other MFIs like BDB in Indonesia
142 Own calculations Without BRI the numbers would be $343 and $409 See Appendix 1143 See Grameen Bank (2003) p 13144 The accurate amount is 5000 Taka See Interview with Shaw Newaz145 Grameen Bank (2004)146 According to the data provided by the Daley Harris (2003) an annual increase in MFI clients ofapproximately 25 percent from 31122002 till the 3092004 would be needed to reach 100 million clients by now This rated is considerably below the average of the previous five years (38 percent) Therefore it can be assumed as realistic despite the growth hindering factors presented above147 See CGAP (2003) p 8148 See Robinson (2002) p 273 Mix Market (2004)
28
XacBank in Mongolia the Equity Building Society in Kenya or the Centenary Rural
Development Bank in Uganda also have managed to cover their loan portfolio fully
through internally mobilized resources149 The Grameen Bank is also expected to do so
in the first half of 2005150 In addition to raising much needed capital for on-lending the
provision of saving services can deliver notable social benefits itself151
Despite these impressive achievements even the combination of donor money and local
savings at their current levels will not be able to provide the capital needed to continue
the rapid growth of the microfinance sector Especially in their early years MFIs rely on
outside funding BRI for example needed six years before the amount of locally
mobilized savings surpassed the total amount of outstanding loans During this time
expenses and the loan portfolio were covered through a government grant worth $20
million and two World Bank loans of $5 and $97 million respectively152 It also
benefited from a network of more than 3600 branches which were established
throughout the country during the 1970s and early 80s in order to provide government
subsidized credit in rural areas153
The Grameen Bank also widely known as a best practice MFI has received about $175
million in direct and indirect subsidies between 1985 and 1996154 and continues to rely
on outside funding at below market interest rates This is made possible either through
special loans from the Bangladesh Bank or through offering bonds guaranteed by the
Bangladesh government155 - an option most MFIs do not have BDB might be one of the
very few examples which were able to finance their activities through savings and
commercial loans from the start but its outreach did not reach a large scale nor did it
serve the low end of the market In 2000 after 30 years of operation BDB provides
credit to only 10417 clients with an average loan balance of more than $5000156
approximately eight times the countries GDP per capita157
149 See Mix Market (2004)150 See Grameen Bank (2004)151 See Robinson (2001) pp 263 et sqq152 See Seibel and Schmidt (2000) p 4153 See Robinson (2002) p 180154 See Morduch (1999b) p 8155 See Morduch (1999ba) p 25 et sqq156 See Robinson (2002) p 387157 See CIA (2004)
29
Another problem keeping many MFIs from collecting savings is that they do not want
to become a regulated financial institution or do not meet the criteria in their respective
country and therefore they are simply not allowed to mobilize savings from the public
In summary the examples and numbers presented in this chapter support the argument
that the amount of capital that can be raised through donors and locally mobilized
savings is not enough for continuous rapid growth of the microfinance sector If this
lack of capital is not met through other sources the microfinance sector will fail to
contribute its full potential to the achievement of the MDGs
44 Microfinance and the Capital Markets
Regardless of whether the amount of capital needed for the development of the
microfinance sector is $20 or $300 billion it represents only a tiny fraction of the
worldwide capital markets which are estimated at $30 trillion158 Therefore if the
microfinance industry were able to tap the financial markets it would be able to grow
much faster and soon serve the millions of micro-entrepreneurs which currently can not
develop theirs businesses because of capital constrains Another advantage would be
that scarce donor money currently used for the development of the microfinance sector
could be used for other projects that do not have the potential to draw money from
commercial sources This view is shared by Michael Chu the former CEO of ACCION
who made the following statement in 1998 ldquoMicrofinance today stands at the threshold
of its next major stage the connection with the capital marketsrdquo159 Many attempts have
been made since that time Successful MFIs like BancoSol in Bolivia further
strengthened their ties to the capital markets which in some cases already provide the
majority of their funding160 Microfinance investment advisors like BlueOrchard
Finance have become middlemen for MFIs and the financial markets Nevertheless
these links are still far from reaching major scale Currently only approximately 20
percent of MFIs funding comes from commercial sources161 and the biggest bond issue
dedicated to fund MFIs totals only $40 million In addition these funds mainly end up
158 See Brynjolfsson (2004) 159 Chu (1998) quoted in Robinson (2001) p 23160 See Robinson (2001) p 69161 See Dominiceacute (2004)
30
in established institutions in Latin America or Eastern Europe162 while smaller
organizations only benefit indirectly if at all
162 See Clear Profit (2004) IMI (2004)
31
5 Credit Rationing
Until recently the predominant answer to why commercial banks or venture capital
companies did not invest in the microfinance sector was that the poor are not bankable
Besides lacking education and therefore not being able to deal with formal financial
institutions they were viewed as bad credit risk who were unable to invest the borrowed
money in a way that would allow them to repay the loan and interest at a commercial
rate163 Another reason that kept attention away from the idea of providing financial
services to low income people was the belief that informal moneylenders already met
this demand These skeptics felt affirmed through the poor performance of subsidized
credit programs as described in chapter 22 Although it is true that moneylenders
serve a huge number of people in the developing world they more often than not charge
usury interest rates of up to 20000 percent per month164 While the argument that poor
people are not able to participate in the formal financial market can be overcome by
adapting the services accordingly165 the claim of low returns on their investments is not
only proved wrong by empirical evidence but also contradicts economic theory as will
be shown in chapter 53
51 The imperfect Information Paradigm
A more elaborate explanation for the short supply of financial services to low income
people that can be derived from the imperfect information paradigm based
predominantly on the works of Akerlof166 and Stiglitz and Weiss167 After giving a brief
summary of their argument an adaptation of their findings to the microfinance market
will be presented and subsequently it will be shown how their conclusions can be
overcome
Behind the imperfect information paradigm lies the theory of asymmetric information
which simply states that if two parties conduct a transaction one is likely to have more
163 See Ghatak (1983) p 21 et sqq Yunus (1998) p 102 et sqq Robinson (2001) p 35 et sqq164 See Robinson (2001) p 17165 See Seibel (2003b) p 2 BRAC (2003) pp 15et sqq Yunus (1998) pp 151 et sqq 166 See Akerlof (1970) pp 488 et sqq167 See Stiglitz and Weiss (1981) pp 393 et sqq
32
information than the other and is trying to use that for its own advantage168 Applied to
the banking sector this means that a person applying for credit can better judge the
likelihood of repaying the loan than the bank This is because the borrower has better
knowledge of the market she wants to invest in her skills and her willingness to repay
Moreover the bank might not be able to observe if the borrower uses the loan for the
agreed purpose These occurrences can lead to what is known as adverse selection and
moral hazard In this case adverse selection refers to the problem that banks might
attract borrowers with a low probability of repayment if they can not distinguish
between high and low risk loan applicants Moral hazard occurs after the provision of
the loan when the borrower spends the money on a purpose different to the prescribed
purpose and therefore lowers the probability of repayment This can happen eg by
investing in a more risky project or through spending the money on consumption If the
bank is not able to find a cost effective way to avoid these problems it might raise its
interest rate in order to compensate for the increased risk
Figure 1 Expected Bank Return and the Interest Rate
Source Stiglitz and Weiss (1981) p 394
Since this might discourage low risk borrowers from applying for credit and encourage
borrowers who continue to take loans to invest in riskier projects the share of high risk
168 See Neus (1998) p 85 et sqq
INTEREST RATEI
EX
PE
CT
ED
RE
TU
RN
TO
TH
E B
AN
K
33
borrowers could increase and therefore reinforce the problems stated above Thus
increasing the interest rate beyond a certain point actually leads to a decrease in the
expected return to the lender This context is illustrated in figure 1 with I being the
interest rate which maximizes the expected returns to the bank Obviously the bank
would charge the interest rate I in order to maximize its expected return However this
price for capital was not determined through supply and demand as economic theory
would predict It is conceivable that at the interest rate I the demand for credit exceeds
the supply but even if loan applicants would offer to pay a higher interest rate the bank
would refuse because it associates such a loan with high risk As a result credit might
be rationed169
52 Adaptation to the Microfinance Sector
Through some adaptations this model can also help to explain the lack of funds
provided to low income people In the original model of Stiglitz and Weiss several
assumptions have been made that need to be suspended in order to compare the credit
markets for low and high income people and give an explanation why the latter is
widely neglected by institutional investors
Evidently the assumptions that the amount borrowed is equal for each loan applicant
and that transaction costs170 need not to be taken into account171 are not suitable for this
context While the average loan size of MFI customers is much smaller than that of
clients from traditional banks the transaction costs as a share of the loan are
considerably higher because the lenderrsquos costs for conscientious processing a credit
applications are only slightly smaller for a $50 loan than for a $100000 or a
$10000000 loan
In figure 2 the R(I)large curve represents the return to the bank for large loans with
regard to the interest rate I and the R(I)small curve describes the same correlation for
small loans It is shifts downwards to reflect the assertion that the imperfect information
169 See Stiglitz and Weiss (1981) p 394170 In this paper the term bdquotransaction costsldquo refers to the operating expense ratio as defined by MicroRate It ldquois calculated by dividing all expenses related to the operation of the institution (including all the administrative and salary expenses depreciation and board fees) by the period average gross portfoliordquo See MicroRate and Inter-American Development Bank (IADB) (2003) p 16 171 See Stiglitz and Weiss (1981) p 396
34
paradigm has a more severe effect on poor people than on the better off They are
expected to have less profitable investment opportunities at their disposal172 and
therefore are more likely to invest in riskier projects which increase the probability of
default and hence decrease the expected return to the bank Additionally one might
expect poor people to be more likely than others to spend borrowed money on
consumption instead of an income generating activity particularly if a crisis arises It
seems understandable that food or urgently needed medicine are given priority over
repaying a loan
The second shift downwards is due to transaction costs As stated above they are
relatively higher for smaller loans Obviously transaction costs are incurred in the
provision of a large loan as well but since they are much smaller with regard to the loan
amount they are not included in the diagram for reasons of clarity
Figure 2 The extended Model
Source Own diagram adapted from Stiglitz and Weiss (1981) p 394
172 See Khandker (1998) p 8
INTEREST RATE I
SmallLoans
LargeLoans
Transaction costs
Lack of investment opportunities
R(I)large
R(I)small
EX
PE
CT
ED
RE
TU
RN
TO
TH
E B
AN
K
35
53 Overcoming Credit Rationing for the Microfinance Sector
If the conclusions in chapter 51 hold it is rational for a profit maximizing investor to
neglect the microfinance sector as long as no surplus funds in the market for large loans
exist This finding can help to explain the small amount of money provided to the
microfinance sector from commercial investors On the other hand it has to be stated
that this theory is reflexive as defined by Soros173 It not only explains but also forms
reality since it has the potential to reinforce the view of potential investors that
microfinance is a less profitable business174 Therefore demonstrating under which
conditions microfinance can be profitable and in some cases be more profitable than
traditional businesses is of crucial importance
To provide a fairer view of the microfinance sector a further assumption of the Stiglitz
and Weiss model that needs to be suspended is that all investments made by the
borrowers have the same expected return175 As stated above this contradicts economic
theory which claims ceteris paribus capital productivity decreases while the amount of
fixed capital increases In combination with a low capital endowment micro-enterprises
are usually faced with an excess supply of unskilled labor especially in developing
countries176 Hence small enterprises use far less capital per employee than big business
and therefore their marginal productivity of capital is much higher177 This is intuitive if
one imagines an economic actor who wants to invest several packages of capital
Obviously she would invest the first package where she expects the highest return the
second package where she expects the second highest return and so on Each additional
investment opportunity would lead to lower or at best equal returns178 While this
simplified example has limitations it demonstrates how the marginal productivity of
capital can diminish Although it might actually increase until a certain point179 this can
be expected to be so low in this context that it has no influence on the correlation as
shown in figure 2
173 See Soros (1998) pp 14 et sqq174 See Goodwin-Groen (1999) p 8175 See Stiglitz and Weiss (1981) p 395176 See Perkins et al (2001) pp 95 et sqq177 See Tschach (2000) p 8178 See Rosenberg (2002) p 11179 See Rechard G Lipsey (1979) pp 211 et sqq
36
Figure 3 Marginal Productivity of Capital
Source Dornbusch and Fischer (1995) p 406
Even if good investment opportunities for poor people exist the question remains if it is
possible to distinguish between high and low risk borrowers The problem of adverse
selection is overcome in a cost effective way in many MFIs180 For the better off poor
for example institutions like BRI base their decision on whether or not to approve a
loan by assessing the repayment ability of potential borrowers from their current income
flows and not from the uncertain returns generated by the loan181 Additionally
collateral is used in some cases to attract low risk borrowers182 In contrast to
industrialized countries this is usually not done to cover the potential losses of the
lender but to punish the defaulter and therefore increase her willingness to repay183
Obviously this does not always work for the poorest since they often neither posses any
goods that could work as collateral nor do they have sufficient earnings prior to
obtaining a loan for starting an income generating activity Here the so called group-
lending model can help to identify creditworthy borrowers The most prominent
institution using this approach is the Grameen Bank which only provides credit to
180 See Farrington (2000) p 20181 See Robinson (2001) p 80 Robinson (2002) p 238182 See Bester (1985) p 850 et sqq183 See Schmidt and Tschach (2001) p 15 Robinson (2002) p 244
FIXED CAPITAL 0
MA
RG
INA
L P
RO
DU
CT
IVIT
Y
37
members of a group of five These groups are formed by their members without
interference of the Grameen Bank Although in this particular case no joint liability
exists for the members of the group nobody can receive a new loan if another member
of the group fails to repay on time184 Therefore the group formation work as a
screening process Since the borrowers do not want to risk their ability to obtain further
loans they carefully select with whom to form a group Usually the members know
each other for a long period of time and therefore they can make a meaningful judgment
of each othersrsquo ability to repay the loan Other MFIs even require the members of a
group to mutually guarantee each othersrsquo loans185 While this might further increase
borrowersrsquo efforts to search for trustworthy group members it might also keep potential
borrowers from applying for a loan since she does not want be held responsible for
defaulting members This mechanism enables MFIs to partly pass on the transaction
costs related to the selection of low risk borrowers to the borrowers themselves186
Many MFIs have also largely overcome the problem of moral hazard by creating
incentives to ensure a high repayment rate even among the poorest In some cases their
customers go hungry in order to pay back their loan even though no legal action would
be taken against them if they would refuse to do so187 One way to achieve this is to
build up peer pressure through the formation of groups as described above188 Another
and probably the most important is to limit access to future loans to those borrowers
who repay on time The demand for successive loans is extremely high In a 1996
survey 98 percent of BRI borrowers planed to apply for another loan189 and in 1993
less than 30 percent of Grameen Bank loans went to first time borrowers190 Especially
the poorest highly value the option to reborrow191 and many MFIs see this as their
primary incentive to ensure repayment192 According to Schmidt and Tschach ldquothe net
present value of future access to credit works out to be roughly half the value of the
economic advantage to be gained from the intended non-repaymentrdquo193 This can also
184 See Yunus (1998) p 135185 See Schmidt and Zeitinger (1997) p 6186 See Stiglitz (1990) p353187 Own observation at the Grameen Bank in Bangladesh (2003)188 See Hoff and Stiglitz (1990) p 249189 See Robinson (2002) p 251190 See Khandker Khalily and Khan (1995) p 93191 See Gibbons (2000) p 15 Hashemi and Schuler (1997) p 43192 See Gibbons and Meehan (1999) p 160193 See Schmidt and Tschach (2001) p 16
38
explain the occurrence of a drop in the repayment rate once a MFI is no longer seen as
viable and therefore is not expected to provide loans in the future194
With the help of the described mechanisms MFIs around the world are able to keep
repayment rates high A survey of 69 MFIs from 36 different countries each serving
more than 10000 clients in 2002 found the portfolio at risk (PAR)195 varied between
zero and 231 percent While the average was 36 percent the median was found to be
229 percent196 One of the MFIs included in this sample is BRIs whorsquos 12-month loss
ratio has never exceeded five percent since the start of its transformation in 1984 and
from 1997 to 1998 the ratio actually fell from 22 to 194 percent197 The latter deserves
special attention because the Asian financial crisis reached its peak at that time with
Indonesia being hardest hit as illustrated by a statement from The Economist in July
1998 Even with the fierce competition from its neighbors Indonesia would probably
walk away with the prize for Asias most desperate banking systemrdquo198
The findings that MFIs can adapt their services to low income people in order to ensure
a high repayment rate and that poor people do not lack profitable investment
opportunities are illustrated in figure 4 From this diagram it can be seen that under the
new assumptions the interest rate at which the bank maximizes its return differs for
large (I(l)) and small loans (I(s)) According to the assumption that micro-
entrepreneurs can realize a higher return on their investments the bank can charge them
a higher rate of interest without bearing an increased risk Nevertheless in this example
the bank would still serve the market for large loans first because of the higher
transaction costs for smaller loans
The view as described in figure 4 is shared among most traditional banks and investors
in industrialized as well as in developing countries In addition to neglecting the
possibility of generating profits by offering microcredit themselves199 they also hesitate
to lend to MFIs because they consider their business too risky
194 See Schreiner (1997) p 64195 ldquoPAR shows the real risk of the portfolio by comparing outstanding loan balances for loans with atleast one late payment to the outstanding loan portfoliordquo Gross and de Silva (2002) p 22196 Own calculations See Appendix 2197 See Seibel (2000) p 11198 The Economist (1998) pp 92 et sqq199 Busch and Kort (2004) p 8
39
Figure 4 The extended Model
Source Own diagram adapted from Stiglitz and Weiss (1981) p 394 Tschach (2000)
p 17
This attitude can be observed by comparing the ratio of equity to liabilities which is
considerably higher for MFIs than for conventional banks200 When it comes to MFI
start-ups and those MFIs serving the low end market in remote areas even experienced
microfinance practitioners are skeptical if interest rates that fully recover all costs can
be charged201
Theoretically there are two ways to adjust this model to arrive at a conclusion which is
more favorable with regard to the profitability of microcredit One is to cut the
transaction costs and therefore reduce the downward shift of the R(I)small curve the
other is to allow the bank to further raise the interest rate without experiencing a
decrease in its return This means to increase I(s) and the respective rate of return
While in 2000 Tschach stated that transaction costs vary between 10 and 20 percent for
loans provided through the group lending model and between 15 and 30 percent for
200 See MicroRate and IADB (2003) p 30201 See Volkery (2004) p 33 Gibbons (2000) p 15 Gibbons and Meehan (2002) p 29 Goodwin-Groen (1999) p 8
INTEREST RATE I(l)
SmallLoans
LargeLoans
Transaction costs
I(s)
R(i)large
R(i)small
EX
PE
CT
ED
RE
TU
RN
TO
TH
E B
AN
K
40
individual loans202 it was recommended in 1999 that MFIs should target a range
between 15 and 25 percent203 Some best practices on the other hand have already
achieved single digit numbers Currently BDB might be the most efficient MFI in the
world with transaction costs at just 47 percent in 2001204 Even though the low costs of
BDB have to be acknowledged its achievement has to be put in perspective As stated
above with an average loan balance of more than $5000 it does not serve the low end
market In addition it works in an environment with a high population density which
means that it can reach a relatively large group of borrowers per branch This is a
comparative advantage many Asian MFIs enjoy as can be illustrated by comparing
Bangladesh and Bolivia Both countries are at the forefront of the development of
microfinance in their respective continent but while in Bangladesh more than 1000
people are living per square kilometer the average for Bolivia is only eight205
Therefore it is consistent that the most efficient MFI in Latin America Fondo
Financiero Privado para el Fomento a Iniciativas Economicas has transaction costs of
114 percent206 With an average loan size greater than the annual GDP per Capita this
institution also does not serve the low end market207
Despite the impressive efficiency gains in the described examples most MFIs are far
from achieving these numbers and many are unlikely to reach them due to the
environment within which they work A survey of 67 MFIs from 31 countries found the
average transactions costs in 2002 to be 279 percent with a median of 206 percent208
However even if these institutions were to increase their efficiency to best practice
standards their transaction costs would still be significantly higher than those of
traditional banks providing much larger loans For these banks the respective costs vary
in a range between 05 and 3 percent209 According to this argument charging interest
rates considerably higher than conventional banks is the only way for MFIs to generate
higher returns and hence successfully compete for capital
202 See Tschach (2000) pp 100 et sqq203 See Gibbons and Meehan (1999) p 149204 See M-Cril (2001b) p 4205 See CIA (2004)206 See MicroRate (2004)207 In this paper the term ldquolow endrdquo refers to the definition of the MBB (2003) p 54 Loans worth less than 20 percent of the respective countryrsquos GDP per capita are described that way 208 Own calculations See Appendix 3209 See M-Cril (2004a) p 16
41
6 Interest Rates
61 Setting the right Interest Rate
Before addressing the questions to what extend MFIs can raise their interest rates
without putting the repayment rate or the social benefits of their customers at risk a
basic model will be presented This model will illustrate how a MFI should set their
rates in order to not only cover their costs but also to generate an appropriate profit to
finance further growth and attract additional capital
In 2002 CGAP revised its 1996 paper ldquoMicrocredit Interest Ratesrdquo210 which outlines
the standard method of setting sustainable interest rates for commercially oriented
MFIs According to this model the annual effective interest rate (I) should be calculated
as shown below
(1) I = LL
IIKCFLLTA
minusminus+++
1
With each variable being a decimal fraction of the average outstanding loan portfolio
whereby TA stands for the transaction costs as described above LL represents the
annual loan loss and II stands for investment income eg on liquid assets The cost of
funds (CF) consist of the interest and administrative costs needed to obtain deposits and
commercial loans as well as of the imputed costs on equity due to inflation K stands for
the capitalization rate which represents the net real profit Keeping this rate high is
important to finance the future growth of the loan portfolio This can be either done
through investors attracted by high profitability or through borrowing For the latter an
increase in equity is inevitable since it is required as a safety cushion by lenders
Since this model ignores the timing of cash flows and does not take taxes into account
it has to be regarded as fairly imprecise and hence should not be used for business
planning Nevertheless it can be used for an approximation of the interest rate that a
MFI would need to charge to provide its services as planned In the following I will
210 See Rosenberg (2002) pp 1 et sqq
42
apply this model on a fictitious MFI working in a rural area of Latin America with low
end customers In this setting it seems realistic to estimate transaction costs of 35
percent and loan loss rate of two percent211 If funds were borrowed at commercial
terms their costs can be assumed to equal at least 15 percent of the average outstanding
loan portfolio212 Estimating the capitalization rate is more challenging First the
targeted portfolio growth rate is set at 75 percent This is slightly below the 751 percent
average annual portfolio growth between 2000 and 2002 found by a survey of 25
different MFIs based in Central and South America213 If the extend to which the MFI
can leverage stays constant the loan portfolios growth would be limited by the growth
rate of the equity To express the capital needed for this growth as a share of the loan
portfolio it is necessary to estimate the ratio between the equity and the outstanding
loan amount According to the survey mentioned above the loan portfolios of the 25
Latin American MFIs equal on average 215 times their equity214 With this number the
capital needed to increase the equity by 75 percent would corresponds to approximately
35 percent of outstanding loan amount (075215) Finally the investment income has to
be estimated Since liquid assets that are available short term do not generate high
returns say five percent it does not seem advisable for the MFI to hold more than a
quarter of its loan portfolio in this form Hence the profit generated in this way would
equal 125 percent of the outstanding loan amount Using these numbers the equation to
calculate the annual effective interest rate reads as follows
(2) I = LL
IIKCFLLTA
minusminus+++
1 =
0201
01250350150020350
minusminus+++
= 0875
As a result the MFI would need to charge an annual effective interest rate of
approximately 875 percent on its loans in order to sustainable provide its services and
finance its growth without depending on donor money This rate might decrease once
the MFI matures the growth slows down and cheaper funds become available but it
will stay significantly higher than any rate charged by conventional banks
211 MicroRate and IADB (2004) pp 6 and 16212 See MicroRate and IADB (2004) p 616 and 28213 Own calculation See Appendix 4214 Own calculations See Appendix 5
43
62 Can Micro-Entrepreneurs bear these Rates
Although most MFIs charge rates significantly below 875 percent many critics have
strenuously argued against any rates exceeding those of traditional banks Rosanna
Barbero of Oxfam labeled an interest rate of 52 percent charged by a Cambodian MFI
ldquoludicrous evil and disgusting and stated that ldquo[n]o business in the world can make a
profit at these interest ratesldquo215 The former finance minister of Bangladesh Shah Kibria
even categorized the 20 percent effective rate charged by the Grameen Bank as to
high216 Many practitioners therefore believe in a strong negative correlation between
the interest rate and the demand for loans217 Others have argued more generally that
concentrating on profitability and therefore charging high interest rates diverts MFIs
from serving the poorest218
These views are still shared among many MFI managers donor agencies and especially
investors and politicians While the former are unwilling to charge interest rates for
funds they received ldquocheaplyrdquo (through grants or subsidized loans) and are worried
about undermining their social goals by charging higher rates of interest219 the latter are
reluctant to invest for reasons stated above or impose interest caps to catch the attention
of the public by pretending to protect the poor from usury rates220
In chapter 53 it has been described that micro-entrepreneurs due to their smaller
capital endowment have even better investment opportunities than big business The
extend to which this is true has not yet been answered An indication is the high
repayment rate observed within MFIs around the globe If their customers capital yield
did not exceed the charged interest rate how would they be able to repay According to
Gibbons and Meehan customers of MFIs can generally generate returns of more than
100 percent on their invested capital221 and ldquo[r]esearch in India Kenya and the
Philippines found that the average annual return on investments in microenterprises
215 See Kate and Roeun (2004)216 See Hodson (2001) min 1100217 See Morduch (1999a) p 1594218 See Prisma (2002) p 1219 See Schreiner (1997) p 60 Khandker (1998) p 106 220 See Gross and de Silva (2002) p 32 Jansson and Wenner (1997) p 36 et sqq Campion (2002) p 59221 See Gibbons and Meehan (1999) p 131
44
ranged from 117 to 847 percentrdquo222 Schmidt and Tschach found the marginal
productivity of capital to be as high as 1000 percent for the smallest loans provided by
the Bolivian MFI Caja Los Andes223 These findings are confirmed by the observation
of Rosenberg who found while working as a microfinance consultant for ten years he
never heard of a single MFI having problems to attract clients because interest rates
were too high224
To get a better understanding of the investment opportunities of low income people in
developing countries a typical example on how MFI clients invest their loans is as
follows
Zobair is working as a rickshaw puller in Bangladesh Like most of his colleagues he
does not own the rickshaw he is riding Therefore he has to pay a daily rent of about
$030 to the owner Since his average income of approximately $15 per day is hardly
enough to feed his family he is not able to save the $100 necessary to buy a rickshaw
on his own 225 If he could do so through obtaining a loan his income would increase by
$030 every day because he would not have to pay the rent for the rickshaw anymore
Assuming an average of six working days per week 226 and a life span of the rickshaw
of 5 years his internal rate of return would equal 15324 percent annually227
Consequently any interest rate charged by a MFI would be advantageous to him as long
as it would not exceed 15324 percent228
63 Should the Interest Rate be subsidized anyway
Despite the fact that numerous micro-entrepreneurs are able to generate tremendous
returns on their investment obviously not all are able to use capital in such a productive
way and therefore can not afford microcredit at commercial rates In order to reach
these people as well many MFIs continue to use donor money in order to keep their
interest rates low But even if the problems related to subsidized credit as described in
222 See Helms and Reille (2004) p 3223 See Schmidt and Tschach (2001) p 6224 See Rosenberg (2002) p 10225 This examples draws on observations made by the author in Dhaka (Bangladesh) during 2003226 Obviously extended holidays are not a viable option in this surrounding 227 Own calculation See Appendix 6228 This result is only valid if the loan is repaid in daily instalments For a weekly repayment schedule the interest rate charged by the MFI must not exceed 15119 percent in order to still be beneficial for Zobair
45
chapter 23 do not arise it might still not be the most effective tool to help poor people
as will be illustrated in the following example
A MFI faces two groups of potential clients one with businesses able to generate a
return of 125 percent on borrowed capital and another with a possible returns of 50
percent Assuming budget costs according to equation (2) the institution needs to
charge an interest rate of 875 percent and therefore only serves the former group
Supposed each group consists of 50 members demanding $100 loans the net gains to
society (NGS) could be calculated as follows
(3) NGS = 50 times ($125 ndash $875) = $1875
These gains would be due to the investments of the more profitable group which were
made possible through the loans provided by the MFI The less profitable group would
not borrow since their expected returns are not sufficient to pay for the interest If the
interest rate would be lowered to 30 percent both groups would be able to generate net
gains and therefore borrow from the MFI In order to provide loans at this rate the
institution would need to raise additional capital from non commercial sources The
NGS would be calculated as follows
(4) NGS = 50 times ($125 - $30) + 50 times ($50 - $30) + 100 times ($30 - $875) = 0
While the first terms represent the net gains to the respective groups the last describes
the costs incurred in providing the loans At a rate of 30 percent each loan would need
to be subsidized with $575 Hence the NGS actually fall after the introduction of the
subsidized loan This is due to the fact that the less profitable group is encouraged to
invest in relatively unproductive businesses In addition future growth of the MFI could
be jeopardized due to scarce donor money which is needed to finance the interest rate
subsidy Therefore it seems more advisable to continue to charge a rate of 875 percent
and spend the money used for subsidization on other programs such as health care or
education229
229 In Appendix 7 it will be shown that this result generally holds
46
7 Empirical verification
71 Setting up a Sample
To see if the findings of the previous chapters hold the effects which interest rates
charged by MFIs have on their performance will be analyzed in the following Up to
now such a study does not exist mainly because of a lack of adequate data Most MFIs
do not provide accurate information about the annual effective interest rate they charge
and therefore make an evaluation difficult
In 2002 Rosenberg distinguished eight different categories on how microcredit interest
rates are quoted230 These categories differ in several ways On the contrary to
traditional banks for example it is common for MFIs to state interest rates calculated on
a ldquoflatrdquo balance rather than on a declining one This means that the total loan amount is
used to determine the interest rate ignoring installments paid by the borrowers normally
on a weekly or monthly basis In addition many MFIs charge a certain upfront fee prior
to the loan disbursement require compulsory savings at a lower rate or state their
interest rate for semi annual terms only On the one hand this is done to provide
numbers that are more meaningful to MFI customers who often lack the necessary math
skills to deal with compound interest on the other hand it is done to circumvent interest
rate ceilings imposed by the government231 Another problem is that most MFIs offer
different loan products without itemizing their respective shares to their total loan
portfolio As a result it is not possible to calculate a weighted average even if the rate
stated by the respective MFI could be transformed into an effective interest rate
Usually the portfolio yield is used as a proxy in order to make statements about the
interest rate charged by a certain MFI232 It is generally ldquocalculated by dividing total
cash financial revenue (all income generated by the loan portfolio but not accrued
interest) by the period average gross portfoliordquo233 The advantage of this method is that
even the hidden costs are considered Nevertheless it also has a severe shortcoming by
not taking late or defaulted payments into account Therefore the portfolio yield does
230 See Rosenberg (2002) p 5231 MicroRate (2002) p 8232 See MicroRate (nd)233 MicroRate and IADB (2003) p 39
47
not allow to draw conclusions regarding the correlation between the interest rate
charged by a MFI and its PAR
72 Examining the Sample
Through the appearance of rating agencies specialized in the microfinance sector more
adequate information has become available in recent years While MicroRate only
publishes the portfolio yield of rated MFIs M-Cril Microfinanza Microserve and
Planet Rating actually provide information about the annual effective interest rate for at
least some of the MFIs they analyze Although it is labelled differently from all of the
four institutions234 the term describes what is ldquothe highest income or yield that an
organisation can earn from its portfolio based on the terms of its loansrdquo235
Currently236 reports of 39 different MFIs from 20 countries providing accurate
information about the effective annual interest rate are available to the public This
sample should be used to verify the findings of the previous chapters237 Since a
comparison is made between the performances of MFIs based in different countries and
the ratings have been carried out in different years several adjustments are necessary
First the inflation of the respective country and the respective year(s)238 has to be taken
into account in order to only compare the real rates239 In addition the average
outstanding loan amount per borrower is divided by the respective countryrsquos GDP per
capita Since it can be assumed that ldquoonly the poorer households will be willing to take
the smallest loansrdquo240 this number can be used as a proxy for the poverty level
Although the sample size is far to small to represent the microfinance sector as a whole
and the results are statistically not significant the findings can still be used to underline
the theoretical conclusions drawn in the previous chapters In figure 5 the connection
234 M-Cril uses the name ldquoannual percentage raterdquo See eg M-Cril (2004a) p 25 Microfinanza uses the name ldquoexpected portfolio yieldrdquo See eg Microfinanza (2002c) p 25 Planet Rating uses the name ldquoannual effective interest raterdquo See eg Planet Rating (2004d) p 1 Microserve uses the name ldquotheoretical yieldrdquo See Microserve (2003) p 62235 See M-Cril (2004a) p 25236 As of September 28th 2004237 See Appendix 8 For exchange rates see FXTOP (2004)238 Where necessary a weighted average of the annual inflation rate was used See Appendix 9239 This is done through the following formula ir = (I ndash F) (1 + F100) While ir represents the real annual effective interest rate F represents the inflation rate 240 Morduch (1998) p 1572
48
between the average loan size and the transaction costs as a share of the average loan
portfolio is illustrated
Figure 5 Loan Size vs Interest Rate241
Source Own diagram
000
1000
2000
3000
4000
5000
6000
7000
8000
9000
10000
0 100 200 300 400 500 600
Loan Size
Inte
res
t R
ate
It can be seen that the interest rate is negative correlated to the loans size This can be
explained by the relative higher transaction cost for smaller loans as described in
chapter 52 In order to cover their costs MFIs serving the low end market need to
charge higher rates to their customers than those organizations serving the better off
poor Obviously there are several assumptions to this general finding Especially
striking are the two MFIs with an average loan size of approximately five times their
countries GDP per capita which still high interest rates This occurrence can be
explained by taking a closer look to the respective organizations One was established
less than two years prior to its rating and therefore still bears a lot of start up costs242
241 The equation for the regression line reads as follows Y = -00219X + 365 The correlation coefficient is 014242 See Microfinanza (2002b) p 1
49
the other managed to stay profitable while it almost quadrupled its loan portfolio in the
last two years243
Figure 6 Interest Rate vs PAR244
Source Own diagram
0
5
10
15
20
25
30
35
0 20 40 60 80 100 120
Interest Rate
PA
R
In Figure 6 the crucial correlation between the interest rates charged by a MFIs and its
PAR245 is examined According to the given sample the view of traditional banks and
investors that a higher interest rate leads to a higher default rate does not hold
Obviously one has to avoid to draw the opposite conclusion namely that a high interest
rates decreases the PAR The connection illustrated in figure 6 has to be interpreted as
follows Since high interest rates are related to small loans the low PAR for MFIs
charging high interest rates can actually be explained by the tremendous profitability of
small size investments Despite the high rates their customers are even more likely to
repay
243 See Planet Rating (2003b)244 The equation for the regression line reads as follows Y = -00768X + 68433 The correlation coefficient is 0235245 M-Cril only publishes the PAR for overdues greater than 60 days Therefore these ratios are used as a proxy for the industry standard of 30 days for some Asian MFIs
50
Finally it has to be examined if charging high interest rates actually enables MFI to
generate higher returns Although it can be expected that the combination of a low PAR
and a high interest rate leads to a high profitability it still has to be checked if this is not
outdone by soaring transaction costs Figure 7 illustrates the correlation between the
interest rate charged by a MFI and its financial self-sufficiency (FSS) The latter is the
ldquo[r]atio of total income to total adjusted expenses for the year Adjustments are made
for subsidised cost of funds (relative to market interest rate) equity (with respect to
inflation) and in-kind donationsrdquo246 It can be seen that the regression line actually does
indicate a positive correlation between the interest rate and the profitability of a MFI
Figure 7 Interest Rate vs FSS247
Source Own diagram248
0
20
40
60
80
100
120
140
160
180
0 20 40 60 80 100
Interest Rate
FS
S
246 M-Cril (2004a) p 53247 The equation for the regression line reads as follows Y = 02839X + 8901 The correlation coefficient is 0174248 Since the interest rate the customers of the MFI Foccas have to pay includes fees which are not passed on to the institution its interest rate in this diagram is set at 723 percent instead of the 10715 percent used for figure 6 See Planet Rating (2003b) p 1
51
This result does not necessarily disprove the findings of Stiglitz and Weiss since it can
be argued that MFIs simply do no increase their interest rates to the point where they
would maximize their expected returns But if this would be true why do MFIs not
charge higher rates of interest given the demand described in chapter 41 and 43 In
mature markets competition normally ensures prices not to exceed a certain level but
since many MFIs still operate in a ldquosellerrsquos marketrdquo249 this can not explain the findings
as described in figure 7 Therefore it has to be assumed that a combination of the
unwillingness of many microfinance practitioners to burden their customers with high
interest rates and the plain disbelief of traditional investors that micro-entrepreneurs can
bear those rates is responsible for this occurrence
249 See MicroRate and IADB (2003) p 9
52
8 Conclusions
It has been shown that MFIs are not only contributing significantly to the development
of the financial sector in their respective countries but also that they play an important
role to eradicate poverty by providing much needed capital to low income people which
are able to generate tremendous returns on their investments
The fact that the demand for microcredit is not met is mainly due to the view of most
for profit investors and traditional banks that offering financial services to poor people
can not be done profitable Because of this conviction they hardly invest in the
microfinance sector This does not have to be the case according to the findings of this
paper Although faced with relatively high transaction costs MFIs are able to charge
interest rates at levels that fully recover their costs Elizabeth Rhynersquos claim ldquothat the
most financially viable programs differed from their less viable peers in their
willingness to set interest rates at levels that would fully recover costsrdquo250 is backed by
the findings of this paper that high profitability is correlated to high interest rates
Theoretical models based on the findings of Stiglitz and Weiss can not be used as a
justification to ration credit for the microfinance sector since the interest rate that
maximizes profits to the lender can be assumed to exceed 100 percent for many MFIs
Nevertheless this rate is hardly charged although it has been shown that it can be done
The Mexican MFI Compartamos for example manages to keep its PAR as low as one
percent while charging an effective interest rate of more than 100 percent to
approximately 160000 clients251 In combination with this case the conclusions drawn
from examining the sample of MFIs in chapter 7 the claim of Hulme and Mosley as
stated in the introduction can be considered as wrong MFIs are in fact able to finance
rapid growth stay profitable by charging corresponding interest rates and still have a
significantly positive impact on the poverty level of their clients In the long run gains
in efficiency economies of scale a slowdown in growth and competition will ensure
interest rates drop as it has already been the case in countries like Bangladesh and parts
of Bolivia252
250 See Rhyne (1998) p 7251 See MicroRate (2004)252 See Microrate and IADB (2003) p 9
53
According to a MicroRate survey many MFIs are more profitable than Citibank and also
generate a higher return on investment than commercial banks in their respective
countries253 Investments companies like IMI or Blue Orchard will soon be able to
present a meaningful track record of their microfinance investments to potential
investors Ultimately the capital markets can not ignore the facts proving that it actually
can be profitable to invest in the microfinance sector but in order to raise money
quickly microfinance practitioners will have to continue to intensively promote their
cause not only to for profit investors but also to donors and multilateral agencies like
the World Bank
253 See MicroRate (2002) p 10
54
Appendix
Appendix 1 Average loan balance
Source Data is available through the Mix Market (2004)
Organization
Loan Portfolio 2002 (US$)
Loan Portfolio 2003 (US$)
Number of borrowers 2002
Number of Borrowers 2003
2CM 1263602 1400438 3622 3708ACF 955503 1611401 285 370ACLEDA 26846703 39391301 82598 98905ACME 1460881 1714844 4283 4600ADIM 369065 407798 1122 1395AFK 933306 1706577 250 467AgroInvest 4684249 9697411 5208 9629Al Amana 15593277 28677666 78114 101610AMSSFMC 612167 1040756 6183 6886AREGAK 3285273 3987011 11841 14377AVFS 214331 269819 1883 2866BancoSol 83629049 91175000 42290 56707BESA 10563980 15114430 4488 5061BPR AK 613362 876130 1730 3879BPR BMMS 133949 237946 1755 1779BRI 1344006170 1720072773 3056103 3100358BZMF 1592508 1922097 1250 1331CBDIBA 216587 242465 5764 2877CCA 2146235 4582302 4070 6585CCCP 447534 851678 6265 9450CEP 3795400 5261957 32291 42132CERUDEB 25093643 34873228 34490 44796CMEDFI 227674 250244 3467 3781CMM - Bogota 4836000 8135968 15635 22038CMMB 34880 56964 42 190COAC Maquita Cushunchic
870084 1855718 6603 7732
CODES 280843 263091 60 60CODESARROLLO 6714007 12935951 4391 6896Constanta 2943822 3536047 16134 18588COOPEC CAMEC MN
7152 29821 92 77
Crear - Tacna 3891116 4636094 3671 4948CREDIT 642094 81838 7532 8097CRYSTAL FUND 366456 421403 1379 1061DBACD 3473701 3876526 12812 19606ECLOF - ECU 1154292 728312 860 416ECLOF - MAL 441734 407227 1118 1500EKI 11833244 19245751 8999 13323EMT 4481589 5765281 84781 92173ESED 8579460 6834742 22790 20035
55
Eshet 185741 462569 3308 6540Faulu - KEN 9027332 7206344 17463 15000FDL 12503027 16545332 21306 25106FIE 35818903 41597315 26468 33100FINADEV 5512586 9770323 12775 14709Finance Salone 211312 434298 2225 7159Finca - TAN 1293430 1854834 20648 27499Finca - UGA 2451703 2798869 35610 36912FINCORP 4761288 10236896 941 858FJN 5473563 8037662 8107 11133FMFB 308158 1188896 713 3558FMM -Bucaramanga
6355518 10227000 25814 42464
FODEM 739181 939824 1909 2501FundaciESPOIR
898561 1883446 5911 9464
FUNDESER 798907 1373113 4072 5065Gasha 323748 413742 5504 6423GGLS Save the Children
64235 137957 1291 2362
GK 56986 166971 951 2718HKL 1363365 1420357 6648 5372HOPE 402799 603488 1098 1562IAMD 42132 56550 2780 2772IDECE 21312 39453 150 232IDF 2031944 2626382 31003 36580IMCEC - Dakar 254759 688449 1018 2983IMCEC - Thies 199799 571122 1164 1261
ISSIA 221615 246792 1409 1698JMCC 1962355 2609723 1471 2333KAFC 21710638 29241051 24850 32097KAMURJ 1003935 1411258 5559 5691Kashf 2355965 6271498 29655 59389KMBI 721409 1626666 11973 27266KPSCA 109299 128063 362 794K-Rep 14490447 20699963 38739 45379KSCS 18978 43740 140 297KVT 44075 70621 241 373LAPO 922478 1194633 18740 19139MEC ADEFAP 27788 69248 198 202MEC Bosangani 14357 31086 364 540MEDF 104113 136257 1278 1184Meklit 233170 252232 2084 3577Metemamen 22123 57778 943 1501MFSC 109261 171090 511 687MIKRA 2951028 5008784 4145 6095MIKROFIN 9560502 18380263 5633 7426Miselini 737387 1026639 10182 11431MRFC 11475440 9133130 163000 180000Mushuc Runa 2089076 5418325 3139 6232Nirdhan 2886777 3016171 29589 27457OCSSC 5245186 7658413 42157 6215o
56
Otiv Diana 95992 638422 229 1073Otiv Sambava 188094 437974 2002 1442Otiv Tana 66465 673175 337 1269Partner 9976448 15321304 7139 11935PCA 6878257 6885926 63113 58147PEACE 420746 627295 4192 5428PEDF 164399 254233 2357 3340Piyeli 809447 1206656 8674 4745PRESTANIC 2827502 3540367 1477 2605PRIDE - MAL 991888 854631 5376 5601PRIZMA 3881581 6838978 8112 10968ProMujer -Nicaragua
1006871 1424437 10436 13047
PTF 891566 1068881 8500 9070RBST 818594 1058115 619 723REMECU 1381705 1483471 10330 13996
RUSCA 60887 100820 454 994
SCSCS 89423 157472 873 1007SFPI 709497 903556 7728 9552Sidama 934260 1011798 10267 11346SPBD 117807 186029 647 1740Sunlink 819138 1056823 3401 3833Sunrise 5412366 8782868 4560 7256TEBA 108032426 176300111 163021 157776TIAVO 281978 838905 2049 459TPC 1140429 2267148 22869 31668TSPI 4650989 5383755 49649 75617UNICECAM 3442843 5943804 16039 19031Wasasa 230657 274908 2850 3728Wisdom 1306066 1404463 10524 12054XacBank 4910098 9829503 11063 18610Zakoura 15907288 12444768 103720 118980
Appendix 2 Portfolio at Risk
Source Data is available through the Mix Market (2004)
Organization PAR 2002ABA 202ACEP 464ACLEDA 175ACODEP 452ACSI 209Al Amana 010Apoyo Integral
483
AREGAK 692Banco Solidario
500
BancoSol 660BASIX 1296
57
BRI 437BURO Tangail
350
CEP 200CERUDEB 103CMAC -Sullana
567
CMM -Bogota
176
Compartamos 111Constanta 304Credi Fe 212CREDIAMIGO 409DBACD 010EBS 847EMT 010ESED 1311FADES 2311Faulu - KEN 246Faulu - UGA 096FDL 212FECECAM 428FED 436FIE 598FINADEV 021Finamerica 1133Finca - TAN 000Finca - UGA 297FMM -Bucaramanga
094
FMM -Popayan
088
FONDEP 013FORA 064Genesis Empresarial
1197
IDF 017KAFC 106Kashf 000KMBI 128K-Rep 229MiBanco 309MRFC 1742Nirdhan 373
PADME 079PAMECAS 284PCA 379PRIDE - TAN 018ProMujer -Nicaragua
073
RCPB 600REMECU 157SHARE 000
58
Soluci 182Spandana 014TEBA 106TSPI 355UMU 125UNICECAM 405Urwego 290UWFT 363WAGES 736WWB -Medellin
235
XacBank 061Zakoura 095
Appendix 3 Transaction Costs
Source Data is available through the Mix Market (2004)
OrganizationTransaction Costs
Acci Rural 1154ACEP 858ACLEDA 2430ACODEP 2920ACSI 924Al Amana 2576AREGAK 2856AssEF 1919Banco Solidario
1826
BancoSol 1210BASIX 1317BRI 1353BURO Tangail
2053
CEP 1759CERUDEB 5109CMAC -Sullana
1784
CMM -Bogota
2089
Compartamos 3341Constanta 4597Credi Fe 1978CREDIAMIGO 2525DBACD 1742EBS 2377EMT 3220ESED 1343FADES 1673FAMA 2436
59
Faulu - KEN 2253Faulu - UGA 4962FDL 1726FECECAM 2587FED 4083FIE 1125Finamerica 1563Finca - TAN 10753Finca - UGA 9096FMM -Bucaramanga
1925
FMM -Popayan
1112
FONDEP 5477FORA 3481Genesis Empresarial
1626
IDF 1695
K-Rep 1909LAPO 3511MiBanco 2456Nirdhan 1325NWTF 3109OCSSC 1155PADME 1131PAMECAS 1705PCA 1670PRIDE - TAN 4273ProMujer -Nicaragua
5078
RCPB 2059SHARE 2308Sidama 2662Soluci 2906Spandana 641TEBA 1213TSPI 3898UMU 4023UNICECAM 10120Urwego 7437Wisdom 1906WWB -Medellin
1703
XacBank 4144Zakoura 1881
60
Appendix 4 Portfolio Growth
Source Data is available through the Mix Market (2004)
Organization
Total Loan Portfolio in 2000
Total Loan Portfolio in 2002
ACODEP 5889394 7258487Adelante 4327 88594ADRI 1514681 2591240AgroCapital 11100088 12018280Banco Solidario 39632165 103420000
BancoSol 78031172 83629049CMAC - Sullana 14596365 28055720
COAC Maquita Cushunchic
348443 870084
CODESARROLLO 1374801 6714007Compartamos 10804279 41825248Crear - Tacna 3778816 3891116
Credi Fe 781616 9393936ECLOF - ECU 179247 1154292
FADES 11948814 15501578FAMA 6201411 8835134FIE 22524645 35818903Finamerica 16575104 16097113FINCOMUN 3278938 5696556FMM - Popayan 6241821 12212867
FONDECO 3456625 5101801Genesis Empresarial
11154234 17746288
MiBanco 36964072 95873333Mushuc Runa 90737 2089076ProMujer -Nicaragua
426541 1006871
WWB - Medellin 2891207 4580998
Appendix 5 Portfolio vs Equity
Source Data is available through the Mix Market (2004)
OrganizationLoan Portfolio Equity
ACODEP 7258487 1921447Adelante 88594 72973
ADRI 2591240 781477AgroCapital 12018280 10766101Banco Solidario 103420000 12961000BancoSol 83629049 15299415CMAC - Sullana 28055720 6210291
61
COAC Maquita Cushunchic
870084 260331
CODESARROLLO 6714007 1285103
Compartamos 41825248 18350446
Crear - Tacna 3891116 1016912Credi Fe 9393936 863848ECLOF - ECU 1154292 459226FADES 15501578 4138972FAMA 8835134 6377663FIE 35818903 5360484Finamerica 16097113 3817960FINCOMUN 5696556 1042241FMM - Popayan 12212867 8510494FONDECO 5101801 1658075Genesis Empresarial
17746288 4765816
MiBanco 95873333 24261889Mushuc Runa 2089076 434311ProMujer -Nicaragua
1006871 1196015
WWB - Medellin 4580998 2213249
Appendix 6 Internal Rate of Return
Source Excel (German Version) calculation based on own data
A B C D E F
1 Date Cash Flow
Interest Rate Internal Rate of Return Balance Interest Principal
23 01012004 -100 15324 100 025489547 0045104534 02012004 03 999548955 025489547 0045104535 03012004 03 99909676 02547805 004521956 04012004 03 998643412 025466524 0045334767 05012004 03 998188909 025454968 0045450328 06012004 03 997733247 025443383 0045566179 08012004 03 999826083 050928361 -0209283610 09012004 03 999374595 025485114 004514886
hellip hellip hellip hellip hellip helliphellip hellip hellip hellip hellip hellip helliphellip hellip hellip hellip hellip hellip hellip1562 23122008 03 177951388 000528711 0294712891563 25122008 03 148859724 000908336 0290916641564 26122008 03 119239161 000379437 0296205631565 27122008 03 089543096 000303935 0296960651566 28122008 03 059771337 000228241 0297717591567 29122008 03 029923692 000152354 0298476461568 30122008 03 -3434E-07 000076274 029923726
62
The formula in the square C3 reads as follows
ldquoXINTZINSFUSS(B3B1568A3A156815)rdquo
Appendix 7 Subsidized Interest Rates and the Net Gains to Society
SourceOwn calculations
For simplicity only two groups of potential clients are distinguished This is possible
since using a continuum of potential clients would lead to the same results In addition it
is assumed that the amount of every loan (L) is equal and that all clients invest the
whole loan amount Group H consist of NH potential clients with a rate of return (rH) on
their invested capital higher than the cost recovering interest rate charged by the MFI
(iC) Group L consists of NL potential clients with a rate of return (rL) on their invested
capital lower than iC If the MFI charges iC the NGS can be calculated as follows
NGSC = NH times (rH - iC) times L
Since rH is bigger than iH (rH gt iC) according to the definition presented above the term
NGSH must be positive as long as NH does not equal zero If the MFI introduces a
subsidised interest rate (iS) lower than rL the NGS can be calculated as follows
(1) NGSS = NH times (rH - iS) times L + NLtimes (rL - iS) times L + (NH + NL) times (iS - iC) times L
(2) NGSS = NH times (rH- iC) times L + NLtimes (rL - iC) times L
The term (NH + NL) times (iS - iC) times L describes the amount of money that is needed in order
to subsidize the interest rate to the level iS By setting up an inequation it can be
examined under which conditions the NGSS are bigger than the NGSC
(3) NGSS gt NGSC
(4) NH times (rH- iC) times L + NLtimes (rL - iC) times L gt NH times (rH - iC) times L
(5) NLtimes (rL - iC) times L gt 0
(6) rL gt iC
63
So the NGSS could only be bigger than the NGSC if equation 6 holds This is
impossible since it violated the definitions presented above Therefore the introduction
of subsidized interest rates is always accompanied with a drop in the NGS
Appendix 8 Interest Rate vs Loan Size vs FSS vs PAR
Source Data is available through the Mix Market (2004)
Organization Country
Real Interest Rate
Loan Size (divided by the GDP per Capita) FSS PAR
BTFFKyrgyz Republic 3803 48260 1487 698
BesaFoundation Albania 2184 16076 684 260RFF Albania 1198 5783 4764 277PSHM Albania 2194 000 5758 198Mi-Bospo Bosnia 2974 5499 1261 020Prizma Bosnia 3474 3569 103 064Agroinvest Serbia 2201 4401 875 020KCLF Kazakhstan 5713 1713 865 090
Foccas Uganda10716 (723) 1550 584 29
ACEP Senegal 3280 20941 1643 1Padme Benin 2715 13575 1667 08Papme Benin 3086 53659 1405 24Vital Finance Benin 2676 9394 1015 17Finadev Benin 1738 14850 1024 21ABA Egypt 2579 1613 1168 88ASBA Egypt 2597 1702 1252 68DBACD Egypt 2490 1643 1073 0SBACD Egypt 2500 1734 982 67AMSSF Morocco 6926 787 1306 04Fondep Morocco 5199 650 889 071Zakoura Morocco 4414 900 98 006ENDA Tunisia 4008 1351 110 102BSFL India 1954 3269 856 99Share India 3426 1440 951 0Spandana India 2942 1618 1367 026SWC India 1864 2626 42 3036SKS India 2248 1912 578 0Grama Vidiya India 3176 1221 76 18Sneha India 3451 1433 933 0Buro Bangladesh 3206 1882 1093 17Upap Pakistan 2073 8183 757 03Seeds Sri Lanka 1004 1088 605 287EMT Cambodia 4324 1676 1016 01TPC Cambodia 4470 2035 832 27
64
WTF Phillippines 5816 1095 941 74TSKI Phillippines 5794 777 96 79Cacja Ecuador 862 6189 9460 897ACME Haiti 6043 6934 11685 450Grupo Cama Mexico 8961 267 10717 288
65
Appendix 9 Inflation vs GDP per Capita
Source IMF (2004)
Country Subject Description Units Scale 2000 2001 2002 2003 2004
Albania Gross domestic product per capita current prices US dollars Units 1083988 1238206 1396172 1757778 2229712
Albania Inflation annual percent change Percent 00 31 52 24 34
Bangladesh Gross domestic product per capita current prices US dollars Units 329310 327980 344494 369495 393717
Bangladesh Inflation annual percent change Percent 22 15 38 54 64
Benin Gross domestic product per capita current prices US dollars Units 361340 368213 405951 494725 560129
Benin Inflation annual percent change Percent 42 40 24 15 26
Bosnia and Herzegovina Gross domestic product per capita current prices US dollars Units 1255837 1321429 1466090 1807392 2070508
Bosnia and Herzegovina Inflation annual percent change Percent 50 32 03 02 09
Cambodia Gross domestic product per capita current prices US dollars Units 276413 280352 296577 305940 321247
Cambodia Inflation annual percent change Percent -08 02 33 12 20
Ecuador Gross domestic product per capita current prices US dollars Units 1227711 1590267 1804362 1957183 2082156
Ecuador Inflation annual percent change Percent -77 377 126 79 32
Egypt Gross domestic product per capita current prices US dollars Units 1550982 1461431 1278462 1188060 1083158
Egypt Inflation annual percent change Percent 28 24 24 32 52
India Gross domestic product per capita current prices US dollars Units 454206 458849 472915 542554 602625
India Inflation annual percent change Percent 40 38 43 38 47
Kazakhstan Gross domestic product per capita current prices US dollars Units 1236159 1490946 1655148 2000598 2579554
Kazakhstan Inflation annual percent change Percent 134 83 59 64 68
Kyrgyz Republic Gross domestic product per capita current prices US dollars Units 278256 306130 321079 349632 380637
Kyrgyz Republic Inflation annual percent change Percent 187 69 21 31 45
66
Mexico Gross domestic product per capita current prices US dollars Units 5957486 6274468 6425203 6111754 6377064
Mexico Inflation annual percent change Percent 95 64 50 45 44
Morocco Gross domestic product per capita current prices US dollars Units 1161302 1162154 1199584 1432725 1541041
Morocco Inflation annual percent change Percent 19 06 28 12 20
Pakistan Gross domestic product per capita current prices US dollars Units 437381 400356 440471 492913 538120
Pakistan Inflation annual percent change Percent 44 31 32 29 46
Philippines Gross domestic product per capita current prices US dollars Units 979423 900225 950707 963765 1018710
Philippines Inflation annual percent change Percent 43 61 31 30 54
Russia Inflation annual percent change Percent 208 215 158 137 103
Senegal Gross domestic product per capita current prices US dollars Units 478704 474460 507408 634171 714622
Senegal Inflation annual percent change Percent 09 30 23 -00 08
Serbia and Montenegro Gross domestic product per capita current prices US dollars Units 1031263 1389384 1882036 2491799 2795805
Serbia and Montenegro Inflation annual percent change Percent 699 911 212 113 79
Sri Lanka Gross domestic product per capita current prices US dollars Units 846811 796025 828256 904330 982466
Sri Lanka Inflation annual percent change Percent 62 142 96 63 64
Tunisia Gross domestic product per capita current prices US dollars Units 2034360 2065140 2149421 2534823 2881273
Tunisia Inflation annual percent change Percent 30 19 28 28 34
Uganda Gross domestic product per capita current prices US dollars Units 293404 249682 279587 280802 287204
Uganda Inflation annual percent change Percent 45 -20 57 51 35
67
References
Akerlof George A The Market for ldquoLemonsrdquo Qualitative Uncertainty and the Market Mechanism in Quarterly Journal of Economics Vol 84 (1970) pp 488-500
Amin Ruhul et al Integration of an Essential Service Package (ESP) in Child and Reproductive Health and Family Planning with a Micro-Credit Program for poor Women Experience from a Pilot Project in Rural Bangladesh in World Development Vol 29 (2001) No 9 pp 1611-1621
Bester Helmut Screening vs Rationing in Credit Markets with Imperfect Information in The American Economic Review Vol 75 (1985) No 4 pp 850855
Borst Dietmar Microfinance ndash Theoretische Grundlagen fuumlr den Einsatz sowie die Abschaumltzung des Potentials anhand einer Datenbankuntersuchung zur Verwundbarkeit der laumlndlichen Bevoumllkerung in Vietnam unpublished diploma thesis Karlsruhe 2004
BRAC Annual Report 2002 Dhaka 2003
Busch Alexander Kort Katharina Die Peanuts-Banker und ihre Kunden in Handelsblatt Nr 150 published August 5th 2004 p 8
Campion Anita Challenges to Microfinance Commercialization in Journal of Microfinance Vol 4 (1999) No 2 pp 57-65
Chu Michael Key Issues of Development Finance Somerville (MA) 1998
Dornbusch Ruumldiger Fischer Stanley Makrooumlkonomie Oldenburg 1995
Dunn Seth Flavin Christopher Moving the Climate Change Agenda Forward in State of the World New York London 2002 pp 24-50
Farrington Todd Efficiency in Microfinance Institutions in The MicroBanking Bulletin Issue No 4 pp 18-24
Gardner Gary The Challenge for Johannesburg Creating a More Secure World in State of the World New York London 2002 pp 3-23
Ghatak Subrata On Interregional Variations in Rural Interest Rates in Journal of Developing Areas Issue 18 pp 21-34
Gibbons David Serving the Poorest Sustainably in The MicroBanking Bulletin Issue No 5 (2000) pp 13-16
Gibbons David Meehan Jennifer W The Microcredit Summitrsquos Challenge WorkingToward Institutional Financial Self-Sufficiency While Maintaining a Commitment to Serving the Poorest Families in Journal of Microfinance Vol 1 (1999) No 1 pp 131-192
68
Goodwin-Groen Ruth Do Asian MFIs Access Funds from Commercial Banks inThe MicroBanking Bulletin Issue No 3 pp 8-10
Grameen Bank (ed) Grameen Generalized System Dhaka 2003
Gross Alexandra de Silva Samantha Social Fund Support of Microfinance A Reviewof Implementation Experience The World Bank Social Protection Discussion Paper No 0215 Washington DC 2002
Hashemi Syed M Schuler Sidney R Sustainable Banking with the Poor A Case Study of Grameen Bank Dhaka 1997
Helms Brigit Reille Xavier Interest Rate Ceilings and Microfinance The story so farConsultative Group to assist the Poor Occasional Paper No 9 September 2004 Washington DC 2004
Hoff Karla Stiglitz Joseph E Introduction Imperfect Information and Rural Credit Markets-Puzzles and Policy Perspectives in The World Bank Economic Review Vol 4 (1990) No 3 pp 235-250
Holcombe Susan Managing to Empower The Grameen Bankrsquos Experience of Poverty Allevation Dhaka 1995
Hulme David Mosley Paul Finance against Poverty London 1996
Jalvaani (ed) Flush with loans Micro credit for rural sanitation Vol 2 (1999) No 2 pp 1-2
Khandker Shahidur R Fighting Poverty with Microcredit Experience in Bangladesh Oxford et al 1998
Khandker Shahidur R Khalily Baqui Khan Zahed Grameen Bank Performance andSustainability The World Bank Discussion Paper No 306 Washington DC 1995
Lipsey Rechard G An Introduction to Positive Economics 5th edition London 1979
Littlefield Elizabeth Morduch Jonathan Hashemi Syed M Is Microfinance an Effective Strategy to Reach the Millennium Development Goals Consultative Group to Assist the Poorest Focus Note No 24 Washington DC 2003
Martinot Eric Cabraal Anil World Bank Solar Home Systems Projects Experience and Lessons Learned 1993-2000 in Renewable Energy Oxford 2000 pp 1-8
M-Cril Microfinance Review 2003 revised February 2004 Gurgaon 2004a
Mezzera Jaime Microcredit in Brazil The Gap Between Supply and Demand in The MicroBanking Bulletin Issue No 8 (2000) pp 22-24
The MicroBanking Bulletin (ed) Note to the Reader Vol 1 (1997) Issue No 1 pp 5-8
69
The MicroBanking Bulletin (ed) An Introduction to the Peer Groups and Tables Issue No 9 (2003) pp 53-60
MicroRate IADB Performance Indicators for Microfinance Institutions Technical Guide 3rd edition Washington DC 2003
MkNelly Barbara Dunford Christopher Impact of Credit with Education on Mothers and Their Young Childrenrsquos Nutrition Lower Pra Rural Bank Credit with Education Program in Ghana Freedom from Hunger Research Paper No 4 Davis (CA) 1998
MkNelly Barbara Dunford Christopher Impact of Credit with Education on Mothers and Their Young Childrenrsquos Nutrition CRECER Credit with Education Program in Bolivia Freedom from Hunger Research Paper No 5 Davis (CA) 1999
Morduch Jonathan The Microfinance Promise in Journal of Economic Literature Vol 37 (1999b) No 4 pp 1569-1614
Neus Werner Einfuumlhrung in die Betriebswirtschaftslehre Tuumlbingen 1998
Otero Maria Bringing Development Back into Microfinance Journal of Microfinance Vol 1 (1999) No 1 pp 8-19
Panjaitan-Drioadisuryo Rosintan D M Cloud Kathleen Gender self-employment and microcredit programs An Indonesian case study in The Quarterly Review of Economics and Finance Vol 39 (1999) pp 769ndash779
Perkins Dwight H et al Economics of Development 5th edition New York London 2001
Pitt Mark M Khandker Shahidur R Credit Programs for the Poor and the Health Status of Children in Rural Bangladesh in International Economic Review Vol 44 (2003) No 1 pp 87-118
Raiffeisen Friedrich W The Credit Unions 8th edition Neuwied 1966
Rhyne Elizabeth The Yin and Yang of Microfinance Reaching the Poor and Sustainability in The MicroBanking Bulletin Issue No 2 (1998) pp 6-9
Richardson David C Unorthodox Microfinance The Seven Doctrines of Success in The MicroBanking Bulletin Issue No 4 (2000) pp 3-7
Robinson Marguerite S The Microfinance Revolution Sustainable Finance for the Poor Washington DC 2001
Robinson Marguerite S The Microfinance Revolution Volume 2 Lessons from Indonesia Washington DC 2002
Rosenberg Richard Microcredit Interest Rates Consultative Group to assist the Poorest Occasional Paper No 1 revised November 2002 Washington DC 2002
70
Roth Michael Steinwand Dirk Mikrofinanz Weltweites Erfolgsmodell nur nicht inDeutschland Zur Uumlbertragbarkeit der Erfahrungen aus Entwicklungslaumlndern auf Deutschland Deutsche Gesellschaft fuumlr Technische Zusammenarbeit (ed) Eschborn2004
Schmidt Reinhard H Tschach Ingo Microfinance as a Nexus of Incentives Finance and Accounting Working Paper No 87A Frankfurt 2001
Schreiner Mark A Framework for the Analysis of the Performance and Sustainability of Subsidized Microfinance Organizations with Application to Banco Sol of Bolivia and Grameen Bank of Bangladesh unpublished PhD dissertation Columbus (O) 1997
Seibel Hans D Recent Developments in Microfinance Development Research Center Working Paper No 1998-5 Cologne 1998
Seibel Hans D History matters in microfinance in Small Enterprise Development ndashAn International Journal of Microfinance and Business Development Vol 14 (2003a) No 2 pp 10-12
Seibel Hans D Schmidt Petra How an Agricultural Development Bank Revolutionized Rural Finance The Case of Bank Rakyat Indonesia International Fund for Agricultural Development Rural Finance Working Paper B 5 Rome 2000
Sen Amartya Oumlkonomie fuumlr den Menschen ndash Wege zu Gerechtigkeit und Solidaritaumlt in der Marktwirtschaft Muumlnchen Wien 2000
Serageldin Ismail The View of the Chair in Consultative Group to Assist the Poorest Newsletter Issue No1 (1996) pp 1 11-12
Soros George Die Krise des globalen Kapitalismus Offene Gesellschaft in Gefahr Berlin 1998
Staschen Stefan Regulation and Supervision of Microfinance Institutions State of Knowledge Deutsche Gesellschaft fuumlr Technische Zusammenarbeit (ed) Eschborn 1999
Steinwand Dirk The Alchemy of Microfinance The Evolution of the IndonesianPeoples Credit Banks (BPR) to 1999 and a Contemporary Analysis Berlin 2001
Stiglitz Joseph E Peer Monitoring and Credit Markets in The World Bank Economic Review Vol 4 (1990) No 3 pp 351-366
Stiglitz Joseph E Weiss Andrew Credit Rationing in Markets with Imperfect Information in The American Economic Review Vol 71 (1981) No 3 pp 393-410
Tschach Ingo Theorie der Entwicklungsfinanzierung Mit Kleinkreditprogrammen Kredit- und Arbeitsmarktsegmentierung uumlberwinden Frankfurt 2000
UNDP Human Development Report 2004 New York 2004
71
UNFPA state of the world population 2004 New York 2004
UNICEF The State of the Worldrsquos Children 2002 NewYork Geneva 2002
Varley Robert C G Financial Services and Environmental Health Household Credit for Water and Sanitation Environmental Health Project Applied Study No 2 Washington DC 1995
Volkery Carsten Kampf um Straszligenhaumlndler in Die Zeit Nr 23 published May 27th
2004 p 33
Wardhana Ali Introduction in The Microfinance Revolution ndash Sustainable Finance for the Poor Washington DC 2001 pp XVII-XXVII
Woodworth Warner Woller Gary Greetings from the Editors Journal of Microfinance Vol 1 (1999) No 1 p 6
The World Bank Group World Development Indicators 2004 Washington DC 2004
Worldwatch Institute (2002) Vital Signs 2002 New York London 2002
Wimmer Nancy Barua Dipal Less is more Microfinance for solar energy in rural areas in Renewable Energy World Review Issue 2004-2005 Vol 7 (2004) No4 pp 170-179
Yunus Muhammad Grameen Bank II ndash Designed to Open new Possibilities Dhaka 2002
Yunus Muhammad Grameen ndash Eine Bank fuumlr die Armen dieser Welt Muumlnchen 1998a
Internet References
Abishek Lal (nd) An Overview of Microfinance and Environmental Management [http wwwgdrcorgicmenvironabhishekhtml] (availability date October 5 2004)
ACCION (nd) our history [httpwwwaccionorgabout_our_historyasp] (availability date October 5 2004)
ACCION (nd) key statistics [httpwwwaccionorgabout_key_statsasp] (availability date October 5 2004)
Ahmad Zulfiqar (nd) Forms of Regional Cooperation in Microfinance in South Asia [httpwwwbwtporgarcmpakistanIV_News_and_EventsBWTPworkshopZulfiqar20Ahmad20paper20(BWTP-PMN2029Jan04)pdf (availability date October 6 2004)
72
Ahmed Salehuddin (2003) Foreword [httpwwwpksf-bdorgaprm_summit_brochure htm] (availability date September 30 2004)
Annan Kofi (2002) Statement at The Microcredit Summit +5 [httpwww microcreditsummitorgenews2003-03_sp_chowdhuryhtml) (availability date October 5 2004)
Barnes Carolyn (2001) Microfinance Program Clients and Impact An Assessment of Zambuko Trust Zimbabwe [httpwwwmicrofinancegatewayorgfiles18553_Barnes_Zambuko_Trust_2001pdf] (availability date October 5 2004)
Barnes Carolyn Gaile Gary Kibombo Richard (2001) The Impact of Three Microfinance Programs in Uganda [httpwwwmicrofinancegatewayorgfiles2935_Barnes_2001pdf] (availability date October 5 2004)
Barua Dipal (2004) Success of Grameen Shakti in the Field of Renewable Energy Sector in Bangladesh [httpwwwrenewables2004depptPresentation1-SessionVA(14-1530h)-Baruapdf] (availability date September 30 2004)
Bhatt Ela (1997) In 1975 [httpwwwmicrocreditsummitorgdeclarationhtm] (availability date September 30 2004)
BlueOrchard (2004a) Microfinance [httpwwwblueorchardchenmicrofinance_institutions asp] (availability date October 5 2004)
BlueOrchard (2004b) January 2004 Newsletter [httpwwwblueorchardchmedialibrarywebsitenewsletter_jan_2004pdf] (availability date October 5 2004)
Brynjolfsson John (2004) John Brynjolfsson Discusses Recent Trends in TIPS Issuance [httpwwwpimcocomLeftNavPIMCO+Spotlight2004Spotlight_2_04htm] (availability date October 5 2004)
CGAP (2003) Report to the Board of Executive Directors [httpwww-wdsworldbankorgservletWDSContentServerWDSPIB20031208000012009_20031208101736RenderedPDF27441pdf] (availability date October 5 2004)
Chen Shaohua Ravallion Martin (2004) How have the worldrsquos poorest fared since the early 1980s [httpwwwworldbankorgresearchpovmonitorMartinPapersHow_have_the_poorest_fared_since_the_early_1980spdf] (availability date October 5 2004)
Cheston Susy Kuhn Lisa (2002) Empowering Women through Microfinance[httpwwwmicrofinancegatewayorgfiles3240_Cheston_2002doc] (availability date October 5 2004)
Christen Robert P et al (1995) Maximizing the Outreach of Microenterprise FinanceAn Analysis of Successful Microfinance Programs [httpwwwdecorgpdf_docsPNABS519 pdf] (availability date October 5 2004)
73
CIA (2004) The World Factbook [httpwwwciagovciapublicationsfactbook] (availability date October 5 2004)
Clear Profit (2004) Microfinance Bond Record May Double [httpwwwclear-profitcomissuescpsep04txt] (availability date September 30 2004)
Daley-Harris Sam (2003) State of the Microcredit Summit Campaign Report 2003 [httpwwwmicrocreditsummitorgpubsreportssocr2003SOCR03-E[txt]pdf] (availability date September 30 2004)
Dominiceacute Robert (2004) Interview in Microfinance Bond Record May Double [httpwwwclear-profitcomissuescpsep04txt] (availability date September 30 2004)
Donahue Jill Kabbucho Kamau Osinde Sylvia (2001) HIVAIDSmdashResponding To A Silent Economic Crisis Among Microfinance Clients In Kenya and Uganda [httpwwwmicrosave-africacomget_fileaspdownload_id=541] (availability date September 30 2004)
Donahue Jill Sussman Linda (1999) Building a Multi-Sectoral Response Follow-Up Assessment of Programming for Children and Families Affected by HIVAids in Kenya [httpwwwdecorgpdf_docspnacg778pdf] (availability date September 30 2004)
The Economist (1998) [httpwwweconomistcomdisplaystorycfmstory_id=S2629H3C28Q13F240A] (availability date September 30 2004)
Finca (nd) Introduction [httpvillagebankingorgwhereindexphp3] (availability date September 30 2004)
Fischer Stanley (2003) Statement at The Asia Society and Womens World BankingAnnual Microfinance Conference [httpwwwiiecomfischerpdffischer051303pdf] (availability date September 30 2004)
Friedman Milton (nd) Samuha [httpwwwsamuhaorgm-1htm] availability date September 30 2004)
FXTOP (2004) Historical Exchange Rates [httpfxtopcomdehistoratesphp3] (availability date September 30 2004)
Gibbons David Meehan Jennifer W (2002) Financing Microfinance for Poverty Reduction [httpwwwmicrocreditsummitorgpapersfinancing_finalpdf] (availability date September 30 2004)
Grameen Bank (2004) Grameen Bank At a Glance [httpwwwgrameen-infoorgbankcdshtml] (availability date September 30 2004)
Grameen Trust (nd) Grameen Bank Replication Program [httpwwwgrameen-infoorggrameengtrustreplicationhtml8721] (availability date September 30 2004)
74
Hossain Farhad (2004) Microfinance in Development [httpwwwvalthelsinkifi staff jkoponenb1104FarhadFeb2304pdf] (availability date October 5 2004)
IMF (2004) Data [httpwwwimforgexternalpubsftweo200402datadbginimcfm] (availability date October 5 2004)
IMI (2004) Investments [httpwwwimi-agcomoverviewindexhtml] (availability date September 30 2004)
IPCC (2001) Summary for Policymakers [httpwwwipccchpubspm22-01pdf] (availability date September 30 2004)
Jansson Tor Wenner Mark (1997) Financial Regulation and its Significance for Microfinance in Latin America and the Caribbean [httpwwwgdrcorgicmgoverniadb-janssonpdf] (availability date October 5 2004)
Ken Daniel Ten Roeun Van (2004) The Cycle of Debt - As Microcredit Institutions Grow Some Question Their Effect on Poverty [httpwwwcamnetcomkhcambodiadaily selected_featurescd-21-02-04htm] (availability date September 30 2004)
Kim Julia (2002) Social Interventions for HIVAIDS - Intervention with Microfinance for AIDS and Gender Equity [httpwwwwitsaczaradarPDF20filesIntervention_monograph_no_picspdfpdf] (availability date September 30 2004)
Llanto Gilberto (nd) Vietnam [httpwwwadborgDocumentsBooksCentral_Banks_MicrofinanceCountry_Studiesvietnampdf] (availability date September 30 2004)
The Microfinance Gateway (nd) Frequently Asked Questions [httpwwwmicrofinance gatewayorgsectionfaq1] (availability date October 5 2004)
Microfinance Rating and Assessment Fund (2004) Qualified Raters [httpwwwmfrating orgmfi_institutionsqualified_ratershtml] (availability date October 5 2004)
Microcredit Summit (1997) Declaration and Plan of Action [httpwwwmicrocreditsummit orgdeclarationhtm] (availability date September 30 2004)
MicroRate (nd) Performance Indicators and Ratios [httpwwwmicroratecomENGLISHsiteRATINGSindicatorshtml] (availability date September 30 2004)
MicroRate (2002) The Finance of Microfinance [httpwwwmicroratecomPDFFinance20of20Microfinancepdf] (availability date September 30 2004)
MicroRate (2004) Adjusted comparison table [httpwwwmicroratecomENGLISHsitePDFAdjusted20Comparison20Table060320engpdf] (availability date October 5 2004)
75
Mix Market (2004) The Mix Market [httpwwwmixmarketorg] (availability date October 5 2004)
Morduch Jonathan (1999b) The Grameen Bank A Financial Reckoning [httpwwwwwsprincetonedu~rpdsmacarthurdownloadsmorduch_grameen_bankpdf] (availability date September 30 2004)
Pallen Dean (1997) Environmental Sourcebook for Micro-Finance Institutions [httpwwwacdi-idagccaINETIMAGESNSFvLUImagesea20summaries$fileSOURC Epdf] (availability date September 30 2004)
Prisma (2002) The Case for Private Capital Market Creation in the Development Field of Microfinance [httpwwwsocialenterprisenetpdfsprivate_capital_marketpdf] (availability date September 30 2004)
Schmidt Reinhard H Zeitinger C-P (1997) Critical Issues in Microbusiness Finance and the Role of Donors No 6 [httpwwwgdrcorgicmmfi-donorpdf] (availability date September 30 2004)
Seibel Hans D (2003b) Commodity finance a commercial proposition Micro- and Mesofinance for Agricultural Commodity Production Processing and Trade [httpwwwuni-koelndeew-fakaef05-20042003-420Commodity20Financepdf] (availability date September 30 2004)
Simanowitz Anton Walter Alice (2002) Ensuring Impact Reaching the Poorest while Building Financially Self-sufficient Institutions and Showing Improvement in the Lives of the Poorest Families [httpwwwidsacukimpactPublicationsWorkingPapersOP3MCSSumdoc] (availability date September 30 2004)
Smith Stephen C Jain Sanjay (1999) Village Banking and Maternal and Child Health Theory and Evidence from Ecuador and Honduras[httphomegwuedu~scsmith healthrevwd801pdf] (availability date September 30 2004)
United Nations (1999) International Year of Microcredit 2005 [httpods-dds-nyunorgdoc UNDOCGENN9976933PDFN9976933 pdfOpenElement] (availability date October 5 2004)
United Nations (2000) United Nations Millennium Declaration [httpods-dds-nyunorgdocUNDOCGENN0055951PDFN0055951pdfOpenElement] (availability date October 5 2004)
US Census Bureau (2004) Total Midyear Population for the World 1950-2050 [httpwwwcensusgovipcwwwworldpophtml] (availability date October 5 2004)
WHO (2004) Making pregnancy safer [httpwwwwhointmediacentrefactsheets fs276en] (availability date September 30 2004)
WHO (2001) Child Health [httpwwwwhointmipfiles2082AAGChildHealthpdf] (availability date September 30 2004)
76
The World Bank Group (nd) Health Nutrition and Population and the Millennium Development Goals [www1worldbankorghnpMDGMDG20-20HNPbookletpdf] (availability date September 30 2004)
Yunus Muhammad (1998) Championing the Right to Credit for Poor Women Around the World [httpaspgrameencom dialoguedialogue34interviewhtml] (availability date September 30 2004)
UNAIDS (2004) [httpwwwunaidsorgbangkok2004GAR2004_pdfUNAIDSGlobalReport2004_enpdf] (availability date September 30 2004)
Ratings
M-Cril (2000) SPANDANA [httpwwwratingfundorgspanishdocsSPANDANA_RatingReportpdf] (availability date October 7 2004)
M-Cril (2001a) BASIX [httpwwwbasixindiacomMcrilasp] (availability date October 7 2004)
M-Cril (2001b) BDB [httpwwwratingfundorgspanishdocsRF_BDBpdf] (availability date October 7 2004)
M-Cril (2001c) SNEHA [httpwwwratingfundorgspanishdocsRF_Sneha-u1pdf] (availability date October 7 2004)
M-Cril (2002a) KCLF [httpwwwratingfundorgdocsRF-KCLF-risk20reportdoc] (availability date October 7 2004)
M-Cril (2002b) NWTF [httpwwwratingfundorgspanishdocsRF_NWTFpdf] (availability date October 7 2004)
M-Cril (2002c) SEEDS [httpwwwratingfundorgspanishdocsRF_SEEDS_2002_Ratingpdf] (availability date October 7 2004)
M-Cril (2002c) Share [httpwwwratingfundorgspanishdocsRF_SHAREpdf] (availability date October 7 2004)
M-Cril (2002d) TSKI [httpwwwratingfundorgspanishdocsRF_Tski_mcrilfinal(-) reportpdf] (availability date October 7 2004)
M-Cril (2003a) ASA [httpwwwratingfundorgdocsASA20updatepdf] (availability date October 7 2004)
M-Cril (2003b) BURO [httpwwwm-crilcomburopdf] (availability date October 7 2004)
M-Cril (2003c) EMT [httpwwwratingfundorgdocsEMTpdf] (availability date October 7 2004)
77
M-Cril (2003d) SKS [httpwwwmixmarketorgendemanddemandshowprofileaspett=25ampshowinfo=adjusted] (availability date October 7 2004)
M-Cril (2003d) TPC [httpwwwratingfundorgdocsTPC_Finalpdf] (availability date October 7 2004)
M-Cril (2004b) UPAP [httpwwwratingfundorgdocsUPAP_2004pdf] (availability date October 7 2004)
Microfinanza (2002a) ACME [httpwwwratingfundorgspanishdocsACME_finalpdf] (availability date October 7 2004)
Microfinanza (2002b) BTFF [httpwwwratingfundorgspanishdocsBTFF_RatingReportpdf] (availability date October 7 2004)
Microfinanza (2002c) BESA [httpwwwratingfundorgspanishdocsBESA_RatingReportpdf] (availability date October 7 2004)
Microfinanza (2002d) CAME [httpwwwratingfundorgdocsEvaluacionCAME(-) Finaldoc] (availability date October 7 2004)
Microfinanza (2002e) RFF [httpwwwratingfundorgdocsRFF20finalpdf] (availability date October 7 2004)
Microfinanza (2002f) PSHM [httpwwwratingfundorgspanishdocsPSHM_Reportpdf] (availability date October 7 2004)
Microfinanza (2003) CAJCA [httpwwwratingfundorgdocsCalificacion_Jardin_Azuayo_ratingpdf] (availability date October 7 2004)
Microserve (2003) ENDA [httpwwwmixmarketorgendemanddemandshowprofileaspett=865ampshowinfo=adjusted] (availability date October 7 2004)
Planet Rating (2002a) FONDEP [httpwwwmfratingorgRatingscompleted_ratingshtml] (availability date October 7 2004)
Planet Rating (2002b) PRIZMA [httpwwwmixmarketorgendemanddemandshowprofileaspett=111ampshowinfo=adjusted] (availability date October 7 2004)
Planet Rating (2002c) SWS [httpwwwratingfundorgspanishdocsSWC_reportpdf] (availability date October 7 2004)
Planet Rating (2002d) ZAKOURA [httpwwwratingfundorgspanishdocsRF_Zakourapdf] (availability date October 7 2004)
Planet Rating (2003a) AMSSF [httpwwwratingfundorgdocsPlanetRating_AMSSF_010803pdf] (availability date October 7 2004)
Planet Rating (2003b) FOCCAS [httpwwwratingfundorgdocsPlanetRatingFOCCAS120803pdf] (availability date October 7 2004)
78
Planet Rating (2003c) PADME [httpwwwmfratingorgdocsPlaNetRatingPADME070302_Englishpdf] (availability date October 7 2004)
Planet Rating (2003d) PAPME [httpwwwmfratingorgdocsPAPME_PlanetRating080903pdf] (availability date October 7 2004)
Planet Rating (2003e) VITAL FINANCE [httpwwwmfratingorgdocsVital20Finance_Sept202003pdf] (availability date October 7 2004)
Planet Rating (2004a) ABA [httpwwwratingfundorgdocsABA_April202004pdf] (availability date October 7 2004)
Planet Rating (2004b) ACEP [httpwwwmfratingorgdocsACEPSeacuteneacutegal_2004pdf] (availability date October 7 2004)
Planet Rating (2004c) AGROINVEST [httpwwwratingfundorgdocsAgroInvest_June202004pdf] (availability date October 7 2004)
Planet Rating (2004d) ASBA [httpwwwratingfundorgdocsASBA_April202004pdf] (availability date October 7 2004)
Planet Rating (2004e) DBACD [httpwwwratingfundorgdocsDBACD_April202004pdf] (availability date October 7 2004)
Planet Rating (2004f) FINADEV [httpwwwmfratingorgdocsFinadev_2004pdf] (availability date October 7 2004)
Planet Rating (2004g) MI-BOSPO [httpwwwratingfundorgdocsMIBOSPO_160404pdf] (availability date October 7 2004)
Planet Rating (2004h) SBACD [httpwwwratingfundorgdocsSBACD_PlanetRating300604pdf] (availability date October 7 2004)
Other Sources
Interview Shaw Newaz Deputy General Manager of the Grameen Bank October 30th
2003
Hodson Charles (2001) Your Business Your World Jim Boulden CNN (ed) Dhaka 2001
13
3 The Impact of Microcredit
31 Microcredit and the Millennium Development Goals
In 1996 Ismail Serageldin the then chair of the Consultative Group to Assist the Poorest
(CGAP)48 claimed that ldquo[m]icrofinance is a proven instrument to assist the very poorrdquo49
This view is also shared by the World Watch Institute50 and underlines what has been
stated above namely that microfinance can be used as a strong anti-poverty tool But
does microfinance actually meet these expectations and keep this promise51
The impact that microcredit has on the lives of poor people will be demonstrated by
showing how it contributes to each of the eight Millennium Development Goals
(MDGs)52 which are related to the reduction of poverty in all its forms These goals
were resolved in September 2000 by the General Assembly of the UN in their
Millennium Declaration53
32 The Eradication of extreme Poverty and Hunger
The aim of the first MDG is to halve the proportion of people who live on less than $1 a
day between 1990 and 2015 According to current population projections of the World
Bank54 this would equal 849 million people in 201555
48 The Consultative Group to Assist the Poorest is a consortium of 28 public and private development agencies working together to expand access to financial services for the poor in developing countries and was established by the World Bank in 1995 Recently it changed its name to Consultative Group to Assist the Poor49 See Serageldin (1996) p 1150 See Gardner (2002) p 1851 See Morduch (1999a) pp 1569 et sqq52 The Millennium Development Goals are (1) eradicate extreme poverty and hunger (2) achieve universal primary education (3) promote gender equality and empower women (4) reduce child mortality (5) improve maternal health (6) combat HIVAIDS malaria and other diseases (7) ensure environmental sustainability and (8) develop a global partnership for development53 See United Nations (2000)54 See World Bank (2004) p 38 et sqq55 Although it is not explicitly mentioned in the Millennium Declaration it is commonly assumed that the share of people living on less than $1 in low and middle income countries should be halved If the share would be calculated with regard to the worldrsquos total population the goal for 2015 would 818 million people For the worldrsquos total population in 1990 see US Census Bureau (2004)
14
Today almost 11 billion people live on less than $1 and more than 27 Billion live on
less than $2 per day56 The mean income for those living under $1 a day is $077 and it
is $125 for those living under $2 a day57 While the number of people living on less
than $1 per day is slowly decreasing and is expected to be 913 million in 2015 the
number of people living on less than $2 a day is actually increasing58 One of the
outcomes from this degree of poverty is that more than 27000 children die every day
from mostly preventable diseases many of them related to hunger59
Microcredit enables poor people to start new businesses or to diversify existing ones
which helps them to increase their income In addition to large amounts of anecdotal
evidence several studies have documented the positive economic impact microcredit
has on its clients Cloud and Panjaitan-Drioadisuryo have found that the average income
of a sample of BRI borrowers has increased by 112 percent and that 90 percent of their
families have crossed the poverty line60 Only 12 out of the 121 respondents of that
study reported that their income had not increased61 According to the Grameen Bank
website 5109 percent of their clients have crossed the poverty line since they took their
first loan62
A study conducted by Barnes showed that the program of the Zambuko Trust a local
MFI in Zambia had a considerable impact on the poorest clients consumption of meat
fish and chicken63 While 76 percent of the continuing clients of the MFI called Share in
India significantly increased their income and 50 percent have crossed the poverty line 64 Khandker discovered in his well known study ldquoFighting poverty with microcreditrdquo
that there is a connection between the microcredit programs of three Bangladeshi MFIs
and household per capita expenditure For every dollar borrowed by a Grameen Bank
member household consumption increases by $018 In addition he found that 5 percent
56 See Chen and Ravallion (2004) p 2957 In fact those people live on less than $108 and $215 respectively a day in 1993 PPP This means that the nominal dollar value of their income is considerably lower See Chen and Ravallion (2004) p 9 58Both numbers are decreasing in Asia but increasing in the rest of the world See Chen and Ravallion (2004) p 22 et sqq59 See UNICEF (2002) p 660 A consistent definition of the term ldquopoverty linerdquo does not exists among different nations Therefore the term will be used according to the definition of the respective country in this paper61 See Panjaitan-Drioadisuryo and Cloud (1999) p 77562 See Grameen Bank (2004) 63 See Barnes (2001) p 8664 See Simanowitz and Walter (2002) p 16
15
of Grameen Bank borrowers move out of poverty every year65 Supposing Khandkerrsquos
findings were correct for all MFIs worldwide and the Microcredit Summit Campaign
achieved its goal of reaching 100 million of the poorest households with microcredit by
2005 then 25 million people (assuming an average family size of five) would leave
poverty every year66 Although this number would have to be adjusted in order take into
consideration the MFI clients who have crossed the poverty line already and of course
the experiences made in Bangladesh can not be transferred precisely to other countries
it still demonstrates the enormous effect that microcredit can have on assisting the
poorest to move out of poverty
Although a 1996 study of Hulme and Mosley states that providing microcredit can also
have a negative impact on the income of the poorest households67 these findings can
be considered as disproved by the recent bulk of evidence drawing favorable
conclusions68
33 Achievement of universal primary Education
The aim of the second MDG is to ensure that all children will be able to complete
primary school by 2015
Currently more than 100 million children most of them girls are not in school69
Besides school fees poor households often can not afford to send their children to
school because they need them to help in the family business
Microcredit programs mainly contribute to the second MDG by increasing families
income and therefore enabling parents to send their children to school Barnes Gaile
and Kibombo found that clients of an MFI in Uganda spent significantly more on
childrenrsquos education than non-clients70 and in Zambia Barnes showed that ongoing
participation in the Zambuko Trustrsquos program had a positive impact on the members
65 See Khandker (1998) p 5666 See Daley-Harris (2003) p 2467 See Hulme and Mosley (1996) p 180 et sqq 68 See Gibbons and Meehan (1998) p 13669 See UNICEF (2002) p 2270 See Barnes Gaile and Kibombo (2001) p 64
16
children staying in school71 In Bangladesh the probability of girls enrolling in school
increased by 19 percent for every 1 percent increase in Grameen Bank loans to female
clients For boys this number was even higher with the mean being 24 percent72
34 Promote gender Equality and empower Women
The aim of the third MDG is to eliminate the disparity in the ratios of girls to boys in
primary secondary and tertiary education in the ratio of literate females to males and to
increase the share of women in the labor market and in parliament73
At present the literacy rate for women is lower than for man all over the world
According to the Human Development Report 2004 the average female literacy rate as
a percentage of male literacy rate is 759 in developing countries and is as low as 37 in
Niger74 But women are not only discriminated against in education but also in access to
medical services and therefore have a higher mortality rate than man75 The worldwide
tendency for women to be underrepresented in the labor market and in the parliaments is
even more severe in developing countries76 Although several women have become
heads of state in various Asian countries (eg Bangladesh India and Indonesia) this is
probably due to them being wives or daughters of former respected male politicians
Since women have a higher repayment rate than man77 and also tend to invest increases
in income on the household and on their children rather than on themselves78 most
MFIs prefer female clients79 Therefore they empower women in many ways Often
MFIs not only encourage women to become involved in financial transactions for the
first time but also to become independent active members of the economy and to
acquire assets in their own names Cheston and Kuhn found that 68 percent of the
women participating in an MFI program in Nepal ldquohellip experienced an increase their
71 See Barnes (2001) p 8472 See Khandker (1998) p 4973 See World Bank (2001) p 2074 See UNDP (2004) pp 225 et sqq75 See Sen (2000) p 23276 See Sen (2000) pp 242 et sqq77 See Littlefield Morduch and Hashemi (2003) p 778 See Yunus (1998a) pp 116 et sqq79 According to the Microcredit Summit Campaign Report 79 or 37677080 of the poorest clients were women See Daley-Harris (2003) p 3
17
decision-making roles in the areas of family planning childrenrsquos marriage buying and
selling property and sending their daughters to school - all areas of decision making
traditionally dominated by menrdquo80 The program of the Lower Pra Rural Bank in Ghana
had an positive impact on womenrsquos participation in the community81 which is true as
well for the CRECER program in Bolivia82 In Bangladesh the Grameen Bank and the
Bangladesh Rural Advancement Committee (BRAC) the two biggest MFIs of the
country had a significant positive effect on womenrsquos empowerment measured through
eight different indicators83 After joining Grameen Bank only 21 percent of the female
members considered themselves as unemployed while this number was 50 percent
before joining84 According to the Grameen Bank website 93 percent of the Bankrsquos
shares are owned by their borrowers which elect the members of the board every three
years They also get familiar with the election process by more frequently voting for
representatives at the lower level of the organizational structure Partly because of this
experience they are more likely to run for public office In the 2003 local government
elections Grameen Bank members constituted 24 of the seats reserved for women
while they represent less than 10 of Bangladeshi adult female population85 Female
clients of MFIs from countries like the Philippines Bolivia and Nepal have reported
similar occurrences86
35 Reduce Child Mortality and improve Maternal Health
The aim of the fourth MDG is to reduce the under-five mortality rate by two-thirds
between 1990 and 2015 and the fifth MDG strives for a three quarter reduction in the
maternal mortality ratio by the same date
As has been stated above more than 10 million children are dying annually in the
developing world of mostly preventable causes with malnutrition playing a role in over
80 See Cheston and Kuhn (2002) p 1881 See MkNelly and Dunford (1998) p 5482 See MkNelly and Dunford (1999) p 7183 The eight different indicators are ldquofreedom of movement economic security ability to make small and larger independent purchases participation in important family decisions relative freedom from domination by the family political and legal awareness and participation in political campaigning and public protestsrdquo Hashemi and Schuler (1998) p 3684 See Holcombe (1995) p 5185 See Grameen Bank (2004)and CIA (2004)86 See Littlefield Morduch and Hashemi (2003) p 8
18
half of the childrsquos deaths and in over 50 countries child mortality rates are greater than
100 deaths per 1000 live births87 Maternal mortality is also a significant problem in the
developing world with more than 500000 women dying every year from pregnancy
related causes88
MFIs are mainly contributing to the these MDGs by increasing families income and
therefore enabling the households to afford better nutrition and medical services
Furthermore they are often linked with microinsurance or health education programs
In addition to what has been showed in chapter 31 Pitt Khandker and Millimet
estimate that a 10 percent increase in the loan size of a female borrower in Bangladesh
increases the arm circumference of their daughters by 6389 Smith and Jain found that
village banking in Ecuador had a positive effect on child diarrhea90 which is responsible
for 15 of child deaths91 Since Sen argues that an improved status of women within
the family reduces child mortality92 the empowerment of women through MFIs is also
contributing to this cause
Although no study has been conducted so far on the direct impact of microcredit on
maternal health it can be assumed that an overall improvement of access to medical
services reduces maternal mortality as well A study of the Morgan State University for
example suggests that microcredit has a positive effect on the prevalence of
contraceptives93 which leads to a decrease of unwanted pregnancies and therefore
reduces maternal death
36 Combat HIVAIDS Malaria and other diseases
The aim of the sixth MDG is to halt and begin to reverse by 2015 the spread of
HIVAIDS malaria and other major diseases and to assist children orphaned by HIV
87 See World Bank (2001) p 888 See WHO (2004) 89 See Pitt Khandker and Millimet (2003) p 11390 See Smith and Jain (1999) p 3791 See WHO (2001) 92 See Sen (2000) p 23593 See Amin et al (2001) p 1614
19
In 2003 29 million people died because of HIV and about 48 million became infected
the greatest number since AIDS was discovered 23 years ago94 This pandemic has lead
to a tremendous decrease in the life expectancy in the hardest hit countries Botswana
for example one of the richest and most democratic countries in Africa has a
HIVAIDS adult prevalence rate of 388 and a life expectancy at birth of less than 31
years95
Malaria not only causes more than one million deaths annually it leads also to 300 ndash
500 million clinical cases a year Both numbers have been steadily increasing over the
past two decades96 More than two million people a year are killed by tuberculosis
another global health problem This curable disease is estimated to cost poor
communities about $12 billion every year since even those who survive normally lose
more than 3 month of work time while recovering97
MFIs contribute to the sixth MDG in several ways By increasing clientrsquos income they
help households affected by HIV or other diseases to better cope with the situation
Besides spending more money on health services and nutrition MFI clients also tend to
be more able and willing to support AIDS orphans than non clients98 In addition to the
already stated increase in the use of contraceptives99 several innovative approaches to
deal with disease related crisis have also arisen This is of course necessary not only to
counteract the devastating effect the above discussed epidemics can have on MFI
clients but also to not put the viability of the respective institution at risk One option is
to integrate education services in the MFI programs and encourage clients to form
solidarity groups100 It has been shown that these services do not necessarily decrease
the effectiveness of the institutionsrsquo employees101 Another way is to strengthen the ties
to NGOs specialize in dealing with the respective disease Synergies gained through this
cooperation can help clients to better deal with the situation and in the end increase their
94 See UNAIDS (2004) p 2395 See CIA (2004)96 See World Bank (2001) p 1697 See World Bank (2001) p 1298 See Barnes (2001) p 6499 See also Kim et al (2002) p 18100 See Donahue and Sussman (1999) p A 14101 See Donahue Kabbucho and Osinde (2001) p 25
20
repayment rates Various MFIs also have introduced loan and health insurance products
or cultivated linkages with organizations doing so102
It has to be stated that despite the benefits MFIs can provide to people effected by
HIVAIDS or other diseases microcredit can also be a burden for those who are already
chronically ill These people can still benefit through loans provided to members of the
family or the community or through one of the other services mentioned above
37 Ensure environmental Sustainability
The aims of the seventh MDG are to support and promote the principles of sustainable
development and put them into action and to improve the lives of slum dwellers and
people without sustainable access to safe drinking water and sanitation
Today climate change is considered as the major environmental problem103 The
Intergovernmental Panel on Climate Change (IPCC) states that human activities
contribute to most of the 06 degC increase in global average temperature over the 20th
century and the predicted increase of another 14 to 58 degC between 1990 and 2100104
Emission of carbon from fossil fuel is reported to have the dominant influence on this
development While the total emission was 16 billion tons in 1950 it was already 65
billion tons in 2000 and is expected to continue to grow105 This development would
lead to a rise in the average sea level of between 9 and 88 centimeters during the next
century106 Furthermore it is predicted that global warming increases the risk of extreme
events like cyclones or floods leads to an increase in the number of people infected by
diseases like malaria and decreases the potential crop harvest and water availability
especially in developing countries107 In 2000 already 11 billion people lacked access to
clean drinking water and 24 billion to basic sanitation108
102 See Barnes (2001) p 40 Barnes Gaile and Kibombo (2001) p 13 and Grameen Bank (2004)103 See Gardner (2002) p 5104 See IPCC (2001) pp 2 et sqq105 Worldwatch Institute (2002) p 52 et sqq106 See IPCC (2001) p 16107 See Dunn and Flavin p 29108 See UNFPA (2004) p 18
21
MFIs contribute to achieving the seventh MDG in several ways By providing loans for
the purchase of renewable energy technologies they help people in developing
countries to increase their per capita energy consumption without increasing the carbon
dioxide emission In a 2003 survey of 140 MFIs from 80 different countries 21 said
they provide credits for solar home systems and another 19 stated they are interested in
becoming engaged in this business109 While Grameen Shakti a rural energy service
company cooperating with the Grameen Bank in Bangladesh has already installed more
than 23000 solar home systems110 a 2000 World Bank study reports twelve projects
providing solar home systems to rural households with a target of 500000
installations111 It has also been suggested that MFIs should raise environmental
awareness among their clients112 but so far no data is available on how staff can cope
with this additional task Many MFIs also provide loans for improvements in sanitation
and the water supply of their clients Varley gives several examples from Africa Asia
and Latin America on how microcredit not only has helped to invest in rainwater
collection systems but also how it has enabled households to increase their water
supply through community water associations113 In addition many MFIs provide credit
for the construction of sanitary latrines114 The situation of slum dwellers is also
positively effected by MFIs Directly through their services in poor urban communities
and indirectly by creating jobs in rural areas and therefore easing the pressure on urban
labor markets
38 Develop a global Partnership for Development
The eight MDG is about the means to achieve the other seven MDGs It calls for all
players involved in the endeavor of development and poverty eradication to work as
partners in a global context
Again MFIs are contributing to the eight MDG in many ways This is occurring through
international networks that provide funding and technical assistance through internet
information portals and specialized journals through social and for profit investors and
109 See Wimmer and Barua (2004) p 174110 Barua (2004) 111 See Martinot and Cabraal (2000) p 6112 See Pallen (1997) p 11 Lal (nd)113 See Varley (1995) pp 39 et sqq114 See Jalvaani (1999) pp 1 et sqq Varley (1995) pp 39 et sqq
22
specialized rating agencies The Bangladesh-based Grameen Trust is one of around 30
networks in operation Besides collaborating with over 200 MFIs around the world it
has directly operated three projects in Afghanistan Kosovo and Myanmar115 While the
ACCION network serves almost 12 million active clients in 19 countries throughout
America and sub-Saharan Africa116 FINCArsquos network operates in three different
continents where it serves more than 200000 customers117 In November 1997 the
MicroBanking Bulletin (MBB) was first published by the microfinance program at the
Economic Institute at the University of Colorado118 Its aim is to develop a database on
the financial performance of MFIs from all over the world which is now available
through the Mix Market an internet portal that also provides information about more
than 300 MFIs investors donor institutions and other related development
organizations119 Two years later the Marriott School at Brigham Young University
started to publish the Journal of Microfinance which has an editorial board of
microfinance experts from all over the world and offers the latest research on this
topic120 In the late 1990s a number of companies became attracted by the microfinance
market and started to invest in MFIs The German based Internationale Mikro
Investitionen Aktiengesellschaft (IMI) for example has already invested more than euro46
million in 19 MFIs in four different continents and plans to invest another euro27 million
before October 2004121 BlueOrchard Finance a microfinance investment consultancy
has channeled more than $60 million worth of private capital to some 40 MFIs
worldwide through investment funds and bond issues122 Big commercial banks like
Citigroup Deutsche Bank and ABN Amro also started to get involved in the
microfinance sector although this is mainly still perceived as a public relation activity
and not as a for-profit investment123 There are also several rating agencies specializing
in MFIs Dependent on their rating these institutions can help MFIs to receive money
from donors or investors Four of the most prominent rating agencies are PlanetFinance
115 See Grameen Trust (nd)116 See ACCION (nd)117 See FINCA (nd)118 See MicroBanking Bulletin (1997) p 5119 See The Mix (2004)120 See Woodworth and Woller (1999) p 6121 See IMI (2004)122 See BlueOrchard (2004b) p 3123 See Busch and Kort (2004) p 8 Fischer (2003) p 6
23
with headquarters in France M-Cril based in India Microfinanza in Italy and
MicroRate with offices in the USA and South Africa124
124 See Microfinance Rating and Assessment Fund (2004)
24
4 Microcredit Outreach
41 The Demand for Microcredit
Although it has been shown that microcredit is one of the most effective poverty
eradication tools that it is considered a human right by some of its advocates125 and it
can contribute considerably to the development of the financial sector in developing
countries an enormous gap still exists between supply and demand for microcredit
Estimates on the demand for microcredit vary greatly While USAID estimates the
number of potential microfinance clients is between 100 and 200 million126 the
Microcredit Summit Campaign states the total demand is more than 234 million
people127 CGAP recognizes some 500 million micro-entrepreneurs who have the
potential to become customers of MFIs128
Marguerite Robinson calculates the demand as follows ldquoAssuming five people to a
household among the 45 billion people living in low- and lower-middle-income
economies in 1999 (World Bank World Development Report 20002001) there are 900
million households in those economies If estimating conservatively we assume that
informal commercial moneylenders supply credit to 30 percent of these households at
least once a year this would mean that there are 270 million households borrowing
from informal moneylenders in a year Undoubtedly however many of these
households borrow multiple times within a yearrdquo129 Although this is a very rough
estimate assuming big differences in demand for microcredit in different countries the
number seems to be the most meaningful In contrast to the estimate of the Microcredit
Summit Campaign it does not include every single household living on less than $1 a
day but according to the definition presented in chapter 1 it counts everyone who has
no regular access to traditional financial institutions but demands such services
Obviously not all people who draw on moneylenders have financial needs that could be
matched through MFIs On the other hand interest rates charged by moneylenders tend
125 See Yunus (1998b) 126 See Christen et al (1995) p 15127 See Daley Harris (2003) p 22 128 See Robinson (2001) p 26129 See Robinson (2001) p 215
25
to be considerably higher than those of MFIs The former normally charge effective
monthly rates between ten and several hundred percent per month the latter generally
charge between 15 and five percent which enables them to attract additional clients130
42 The Supply of Microcredit
In spite of the impressive growth of MFIs around the world the demand for microcredit
is far from being met and this it is not likely to change in the near future The
Microcredit Summit Campaign reported that by the end of 2002 67606080 clients131
were reached through MFIs and that this number has increased by almost 40 percent
annually for the last five years132 It is likely that this tremendous speed of growth is at
least partly due to including MFIs which have not been reporting to the Campaign from
its start in 1997 although they have already existed at that time These institutions
contributed 22 percent to the growth in poorest clients in 2000 578 percent in 2001 and
338 percent in 2002 The growth of the poorest clients increased at least party because
of an expanded definition of the term ldquopoorestrdquo133 Since the contribution of MFIs
which previously have not been considered can be expected to decrease dramatically
the growth rate as stated by the Microcredit Summit Campaign can not be used to
predict the future development of the microfinance sector Another factor likely to slow
down the growth is the concentration of microfinance activities in some Asian countries
where almost 90 percent of the poorest microfinance clients live today134 Even if one
takes into consideration the relative size of Asiarsquos population and the fact that many
MFI customers in Latin America are relatively better off and therefore are not included
in this numbers the coverage of this part of the world far exceeds the others In
Bangladesh for example the microfinance market is close to saturation More than
eleven million households were served by several hundred MFIs in 2001135 Among
them are Grameen Bank and BRAC two of the best known MFIs in the world both
providing their services to more than three million customers With an average
household size of five it can be assumed that in Bangladesh the number of people
130 See Gibbons and Meehan (1999) pp 144 et sqq131 41594778 of them belonged to the poorest before they took their first loan The relative numbers in the following are for these poorest clients only since no other current data was available It can be assumed though that this works as a good proxy for the total number of clients 132 See Daley Harris (2003) p 3133 See Daley Harris (2003) p 17134 See Daley Harris (2003) p 21135 See Ahmed (2003)
26
benefiting from microcredit already surpasses the number of people living below the
poverty line which is estimated to be slightly higher than 50 million136 Therefore
Bangladesh will not contribute to the growth of the microfinance sector as much as it
has done in previous years This is also true for Vietnam Thailand and to a lesser
extent Indonesia Eight of the nine MFIs serving more than one million clients are based
in these countries while the ninth is based in India where due to its one billion
inhabitants the microfinance market is still far from saturation137 In contrast the
supply in Brazil meets less than two percent of the demand which is estimated to be
about 58 million potential clients138 For these reasons greater amount of future growth
must come from smaller or new MFIs in Latin America India China and especially
Africa where almost 30 percent of the worldrsquos poorest live139
43 Meeting the Demand
To fill the gap between the demand and supply for microcredit tremendous investments
are necessary to increase the loan funds of MFIs and build up their capacity through
upgrading existing institutions or building new ones Again estimates on how much
capital is needed vary greatly with the highest being at more than $300 billion140
In 1997 the Microcredit Summit Campaign estimated that $216 billion would be
needed to achieve their goal of providing microcredit to 100 million of the poorest
households This was calculated in the following way Since some 8 million people
already received microcredit in 1997 another 92 million needed to be reached
Assuming $200 ($150 for loan fund and $50 for capacity building) would be needed per
person for 88 million people in developing countries and $1000 ($500 for loan fund and
$500 for capacity building) would be needed for 4 million people in industrialized
countries the capital required ends up to be $216 billion141 For several reasons this
136 See CIA (2004)137 These institutions are The Grameen Bank BRAC Proshika and the Association for Social Advancement (ASA) in Bangladesh the Vietnam Bank for Agriculture and Rural Development (VBARD) and the Vietnam Bank for the Poor (VBA) in Vietnam BRI in Indonesia Bank for Agriculture and Agricultural Co-operatives (BAAC) in Thailand the National Bank for Agriculture and Rural Development (NABARD) in India See Ahmed (nd) p 1 Llanto (nd) p 337138 See Mezzera (2002) p 23139 See See Chen and Ravallion (2004) p 29140 See Clear Profit (2004) Prisma (2002)141 See The Microcredit Summit (1997)
27
number is not qualified to predict the total amount of capital needed to meet the demand
for microcredit On the one hand it focuses mainly on the low end of the market and
therefore underestimates the average loan fund needed On the other hand it does not
take the increasing capital demand from established MFIs into account A survey of 119
MFIs found that the average loan size to increased from $406 in 2002 to $498 in
2003142 This is mainly due to the fact that MFI clients once they have paid back their
loans usually demand larger ones for the continual development of their businesses
and therefore further increase the demand for capital of established MFIs The Grameen
Bank for example has a ceiling on its loans which increases or decreases depending on
the borrowers performance regarding repayments and savings143 While the maximum
amount for the first loan is fixed at approximately $75144 the largest loan disbursed so
far was $17195145 Thus if one estimates that by now 100 million people are borrowing
from MFIs146 another 170 million need to be reached to meet the estimated demand
Assuming an average of $600 ($400 for loan fund and $200 for capacity building) is
needed for every new client and another $200 is needed for every existing client to meet
the demand for larger loans a total of $122 billion is required This rough estimate
helps to convey the approximate amount of capital needed to meet the demand for
microcredit
So far the demand for funds is being partly met by donors which annually provide
between $500 million and $1 billion147 and through the mobilization of local savings
Obviously the amount of money provided by donors will not be able to meet the capital
demand for microcredit in the short term The mobilization of savings on the other hand
has been extremely successful in some cases with BRI probably being the most
prominent example After adapting commercial principals in October 1984 BRI was
able to raise its deposits from $161060 to more than $32 billion in 2003 which equals
almost two times its current loan portfolio148 Many other MFIs like BDB in Indonesia
142 Own calculations Without BRI the numbers would be $343 and $409 See Appendix 1143 See Grameen Bank (2003) p 13144 The accurate amount is 5000 Taka See Interview with Shaw Newaz145 Grameen Bank (2004)146 According to the data provided by the Daley Harris (2003) an annual increase in MFI clients ofapproximately 25 percent from 31122002 till the 3092004 would be needed to reach 100 million clients by now This rated is considerably below the average of the previous five years (38 percent) Therefore it can be assumed as realistic despite the growth hindering factors presented above147 See CGAP (2003) p 8148 See Robinson (2002) p 273 Mix Market (2004)
28
XacBank in Mongolia the Equity Building Society in Kenya or the Centenary Rural
Development Bank in Uganda also have managed to cover their loan portfolio fully
through internally mobilized resources149 The Grameen Bank is also expected to do so
in the first half of 2005150 In addition to raising much needed capital for on-lending the
provision of saving services can deliver notable social benefits itself151
Despite these impressive achievements even the combination of donor money and local
savings at their current levels will not be able to provide the capital needed to continue
the rapid growth of the microfinance sector Especially in their early years MFIs rely on
outside funding BRI for example needed six years before the amount of locally
mobilized savings surpassed the total amount of outstanding loans During this time
expenses and the loan portfolio were covered through a government grant worth $20
million and two World Bank loans of $5 and $97 million respectively152 It also
benefited from a network of more than 3600 branches which were established
throughout the country during the 1970s and early 80s in order to provide government
subsidized credit in rural areas153
The Grameen Bank also widely known as a best practice MFI has received about $175
million in direct and indirect subsidies between 1985 and 1996154 and continues to rely
on outside funding at below market interest rates This is made possible either through
special loans from the Bangladesh Bank or through offering bonds guaranteed by the
Bangladesh government155 - an option most MFIs do not have BDB might be one of the
very few examples which were able to finance their activities through savings and
commercial loans from the start but its outreach did not reach a large scale nor did it
serve the low end of the market In 2000 after 30 years of operation BDB provides
credit to only 10417 clients with an average loan balance of more than $5000156
approximately eight times the countries GDP per capita157
149 See Mix Market (2004)150 See Grameen Bank (2004)151 See Robinson (2001) pp 263 et sqq152 See Seibel and Schmidt (2000) p 4153 See Robinson (2002) p 180154 See Morduch (1999b) p 8155 See Morduch (1999ba) p 25 et sqq156 See Robinson (2002) p 387157 See CIA (2004)
29
Another problem keeping many MFIs from collecting savings is that they do not want
to become a regulated financial institution or do not meet the criteria in their respective
country and therefore they are simply not allowed to mobilize savings from the public
In summary the examples and numbers presented in this chapter support the argument
that the amount of capital that can be raised through donors and locally mobilized
savings is not enough for continuous rapid growth of the microfinance sector If this
lack of capital is not met through other sources the microfinance sector will fail to
contribute its full potential to the achievement of the MDGs
44 Microfinance and the Capital Markets
Regardless of whether the amount of capital needed for the development of the
microfinance sector is $20 or $300 billion it represents only a tiny fraction of the
worldwide capital markets which are estimated at $30 trillion158 Therefore if the
microfinance industry were able to tap the financial markets it would be able to grow
much faster and soon serve the millions of micro-entrepreneurs which currently can not
develop theirs businesses because of capital constrains Another advantage would be
that scarce donor money currently used for the development of the microfinance sector
could be used for other projects that do not have the potential to draw money from
commercial sources This view is shared by Michael Chu the former CEO of ACCION
who made the following statement in 1998 ldquoMicrofinance today stands at the threshold
of its next major stage the connection with the capital marketsrdquo159 Many attempts have
been made since that time Successful MFIs like BancoSol in Bolivia further
strengthened their ties to the capital markets which in some cases already provide the
majority of their funding160 Microfinance investment advisors like BlueOrchard
Finance have become middlemen for MFIs and the financial markets Nevertheless
these links are still far from reaching major scale Currently only approximately 20
percent of MFIs funding comes from commercial sources161 and the biggest bond issue
dedicated to fund MFIs totals only $40 million In addition these funds mainly end up
158 See Brynjolfsson (2004) 159 Chu (1998) quoted in Robinson (2001) p 23160 See Robinson (2001) p 69161 See Dominiceacute (2004)
30
in established institutions in Latin America or Eastern Europe162 while smaller
organizations only benefit indirectly if at all
162 See Clear Profit (2004) IMI (2004)
31
5 Credit Rationing
Until recently the predominant answer to why commercial banks or venture capital
companies did not invest in the microfinance sector was that the poor are not bankable
Besides lacking education and therefore not being able to deal with formal financial
institutions they were viewed as bad credit risk who were unable to invest the borrowed
money in a way that would allow them to repay the loan and interest at a commercial
rate163 Another reason that kept attention away from the idea of providing financial
services to low income people was the belief that informal moneylenders already met
this demand These skeptics felt affirmed through the poor performance of subsidized
credit programs as described in chapter 22 Although it is true that moneylenders
serve a huge number of people in the developing world they more often than not charge
usury interest rates of up to 20000 percent per month164 While the argument that poor
people are not able to participate in the formal financial market can be overcome by
adapting the services accordingly165 the claim of low returns on their investments is not
only proved wrong by empirical evidence but also contradicts economic theory as will
be shown in chapter 53
51 The imperfect Information Paradigm
A more elaborate explanation for the short supply of financial services to low income
people that can be derived from the imperfect information paradigm based
predominantly on the works of Akerlof166 and Stiglitz and Weiss167 After giving a brief
summary of their argument an adaptation of their findings to the microfinance market
will be presented and subsequently it will be shown how their conclusions can be
overcome
Behind the imperfect information paradigm lies the theory of asymmetric information
which simply states that if two parties conduct a transaction one is likely to have more
163 See Ghatak (1983) p 21 et sqq Yunus (1998) p 102 et sqq Robinson (2001) p 35 et sqq164 See Robinson (2001) p 17165 See Seibel (2003b) p 2 BRAC (2003) pp 15et sqq Yunus (1998) pp 151 et sqq 166 See Akerlof (1970) pp 488 et sqq167 See Stiglitz and Weiss (1981) pp 393 et sqq
32
information than the other and is trying to use that for its own advantage168 Applied to
the banking sector this means that a person applying for credit can better judge the
likelihood of repaying the loan than the bank This is because the borrower has better
knowledge of the market she wants to invest in her skills and her willingness to repay
Moreover the bank might not be able to observe if the borrower uses the loan for the
agreed purpose These occurrences can lead to what is known as adverse selection and
moral hazard In this case adverse selection refers to the problem that banks might
attract borrowers with a low probability of repayment if they can not distinguish
between high and low risk loan applicants Moral hazard occurs after the provision of
the loan when the borrower spends the money on a purpose different to the prescribed
purpose and therefore lowers the probability of repayment This can happen eg by
investing in a more risky project or through spending the money on consumption If the
bank is not able to find a cost effective way to avoid these problems it might raise its
interest rate in order to compensate for the increased risk
Figure 1 Expected Bank Return and the Interest Rate
Source Stiglitz and Weiss (1981) p 394
Since this might discourage low risk borrowers from applying for credit and encourage
borrowers who continue to take loans to invest in riskier projects the share of high risk
168 See Neus (1998) p 85 et sqq
INTEREST RATEI
EX
PE
CT
ED
RE
TU
RN
TO
TH
E B
AN
K
33
borrowers could increase and therefore reinforce the problems stated above Thus
increasing the interest rate beyond a certain point actually leads to a decrease in the
expected return to the lender This context is illustrated in figure 1 with I being the
interest rate which maximizes the expected returns to the bank Obviously the bank
would charge the interest rate I in order to maximize its expected return However this
price for capital was not determined through supply and demand as economic theory
would predict It is conceivable that at the interest rate I the demand for credit exceeds
the supply but even if loan applicants would offer to pay a higher interest rate the bank
would refuse because it associates such a loan with high risk As a result credit might
be rationed169
52 Adaptation to the Microfinance Sector
Through some adaptations this model can also help to explain the lack of funds
provided to low income people In the original model of Stiglitz and Weiss several
assumptions have been made that need to be suspended in order to compare the credit
markets for low and high income people and give an explanation why the latter is
widely neglected by institutional investors
Evidently the assumptions that the amount borrowed is equal for each loan applicant
and that transaction costs170 need not to be taken into account171 are not suitable for this
context While the average loan size of MFI customers is much smaller than that of
clients from traditional banks the transaction costs as a share of the loan are
considerably higher because the lenderrsquos costs for conscientious processing a credit
applications are only slightly smaller for a $50 loan than for a $100000 or a
$10000000 loan
In figure 2 the R(I)large curve represents the return to the bank for large loans with
regard to the interest rate I and the R(I)small curve describes the same correlation for
small loans It is shifts downwards to reflect the assertion that the imperfect information
169 See Stiglitz and Weiss (1981) p 394170 In this paper the term bdquotransaction costsldquo refers to the operating expense ratio as defined by MicroRate It ldquois calculated by dividing all expenses related to the operation of the institution (including all the administrative and salary expenses depreciation and board fees) by the period average gross portfoliordquo See MicroRate and Inter-American Development Bank (IADB) (2003) p 16 171 See Stiglitz and Weiss (1981) p 396
34
paradigm has a more severe effect on poor people than on the better off They are
expected to have less profitable investment opportunities at their disposal172 and
therefore are more likely to invest in riskier projects which increase the probability of
default and hence decrease the expected return to the bank Additionally one might
expect poor people to be more likely than others to spend borrowed money on
consumption instead of an income generating activity particularly if a crisis arises It
seems understandable that food or urgently needed medicine are given priority over
repaying a loan
The second shift downwards is due to transaction costs As stated above they are
relatively higher for smaller loans Obviously transaction costs are incurred in the
provision of a large loan as well but since they are much smaller with regard to the loan
amount they are not included in the diagram for reasons of clarity
Figure 2 The extended Model
Source Own diagram adapted from Stiglitz and Weiss (1981) p 394
172 See Khandker (1998) p 8
INTEREST RATE I
SmallLoans
LargeLoans
Transaction costs
Lack of investment opportunities
R(I)large
R(I)small
EX
PE
CT
ED
RE
TU
RN
TO
TH
E B
AN
K
35
53 Overcoming Credit Rationing for the Microfinance Sector
If the conclusions in chapter 51 hold it is rational for a profit maximizing investor to
neglect the microfinance sector as long as no surplus funds in the market for large loans
exist This finding can help to explain the small amount of money provided to the
microfinance sector from commercial investors On the other hand it has to be stated
that this theory is reflexive as defined by Soros173 It not only explains but also forms
reality since it has the potential to reinforce the view of potential investors that
microfinance is a less profitable business174 Therefore demonstrating under which
conditions microfinance can be profitable and in some cases be more profitable than
traditional businesses is of crucial importance
To provide a fairer view of the microfinance sector a further assumption of the Stiglitz
and Weiss model that needs to be suspended is that all investments made by the
borrowers have the same expected return175 As stated above this contradicts economic
theory which claims ceteris paribus capital productivity decreases while the amount of
fixed capital increases In combination with a low capital endowment micro-enterprises
are usually faced with an excess supply of unskilled labor especially in developing
countries176 Hence small enterprises use far less capital per employee than big business
and therefore their marginal productivity of capital is much higher177 This is intuitive if
one imagines an economic actor who wants to invest several packages of capital
Obviously she would invest the first package where she expects the highest return the
second package where she expects the second highest return and so on Each additional
investment opportunity would lead to lower or at best equal returns178 While this
simplified example has limitations it demonstrates how the marginal productivity of
capital can diminish Although it might actually increase until a certain point179 this can
be expected to be so low in this context that it has no influence on the correlation as
shown in figure 2
173 See Soros (1998) pp 14 et sqq174 See Goodwin-Groen (1999) p 8175 See Stiglitz and Weiss (1981) p 395176 See Perkins et al (2001) pp 95 et sqq177 See Tschach (2000) p 8178 See Rosenberg (2002) p 11179 See Rechard G Lipsey (1979) pp 211 et sqq
36
Figure 3 Marginal Productivity of Capital
Source Dornbusch and Fischer (1995) p 406
Even if good investment opportunities for poor people exist the question remains if it is
possible to distinguish between high and low risk borrowers The problem of adverse
selection is overcome in a cost effective way in many MFIs180 For the better off poor
for example institutions like BRI base their decision on whether or not to approve a
loan by assessing the repayment ability of potential borrowers from their current income
flows and not from the uncertain returns generated by the loan181 Additionally
collateral is used in some cases to attract low risk borrowers182 In contrast to
industrialized countries this is usually not done to cover the potential losses of the
lender but to punish the defaulter and therefore increase her willingness to repay183
Obviously this does not always work for the poorest since they often neither posses any
goods that could work as collateral nor do they have sufficient earnings prior to
obtaining a loan for starting an income generating activity Here the so called group-
lending model can help to identify creditworthy borrowers The most prominent
institution using this approach is the Grameen Bank which only provides credit to
180 See Farrington (2000) p 20181 See Robinson (2001) p 80 Robinson (2002) p 238182 See Bester (1985) p 850 et sqq183 See Schmidt and Tschach (2001) p 15 Robinson (2002) p 244
FIXED CAPITAL 0
MA
RG
INA
L P
RO
DU
CT
IVIT
Y
37
members of a group of five These groups are formed by their members without
interference of the Grameen Bank Although in this particular case no joint liability
exists for the members of the group nobody can receive a new loan if another member
of the group fails to repay on time184 Therefore the group formation work as a
screening process Since the borrowers do not want to risk their ability to obtain further
loans they carefully select with whom to form a group Usually the members know
each other for a long period of time and therefore they can make a meaningful judgment
of each othersrsquo ability to repay the loan Other MFIs even require the members of a
group to mutually guarantee each othersrsquo loans185 While this might further increase
borrowersrsquo efforts to search for trustworthy group members it might also keep potential
borrowers from applying for a loan since she does not want be held responsible for
defaulting members This mechanism enables MFIs to partly pass on the transaction
costs related to the selection of low risk borrowers to the borrowers themselves186
Many MFIs have also largely overcome the problem of moral hazard by creating
incentives to ensure a high repayment rate even among the poorest In some cases their
customers go hungry in order to pay back their loan even though no legal action would
be taken against them if they would refuse to do so187 One way to achieve this is to
build up peer pressure through the formation of groups as described above188 Another
and probably the most important is to limit access to future loans to those borrowers
who repay on time The demand for successive loans is extremely high In a 1996
survey 98 percent of BRI borrowers planed to apply for another loan189 and in 1993
less than 30 percent of Grameen Bank loans went to first time borrowers190 Especially
the poorest highly value the option to reborrow191 and many MFIs see this as their
primary incentive to ensure repayment192 According to Schmidt and Tschach ldquothe net
present value of future access to credit works out to be roughly half the value of the
economic advantage to be gained from the intended non-repaymentrdquo193 This can also
184 See Yunus (1998) p 135185 See Schmidt and Zeitinger (1997) p 6186 See Stiglitz (1990) p353187 Own observation at the Grameen Bank in Bangladesh (2003)188 See Hoff and Stiglitz (1990) p 249189 See Robinson (2002) p 251190 See Khandker Khalily and Khan (1995) p 93191 See Gibbons (2000) p 15 Hashemi and Schuler (1997) p 43192 See Gibbons and Meehan (1999) p 160193 See Schmidt and Tschach (2001) p 16
38
explain the occurrence of a drop in the repayment rate once a MFI is no longer seen as
viable and therefore is not expected to provide loans in the future194
With the help of the described mechanisms MFIs around the world are able to keep
repayment rates high A survey of 69 MFIs from 36 different countries each serving
more than 10000 clients in 2002 found the portfolio at risk (PAR)195 varied between
zero and 231 percent While the average was 36 percent the median was found to be
229 percent196 One of the MFIs included in this sample is BRIs whorsquos 12-month loss
ratio has never exceeded five percent since the start of its transformation in 1984 and
from 1997 to 1998 the ratio actually fell from 22 to 194 percent197 The latter deserves
special attention because the Asian financial crisis reached its peak at that time with
Indonesia being hardest hit as illustrated by a statement from The Economist in July
1998 Even with the fierce competition from its neighbors Indonesia would probably
walk away with the prize for Asias most desperate banking systemrdquo198
The findings that MFIs can adapt their services to low income people in order to ensure
a high repayment rate and that poor people do not lack profitable investment
opportunities are illustrated in figure 4 From this diagram it can be seen that under the
new assumptions the interest rate at which the bank maximizes its return differs for
large (I(l)) and small loans (I(s)) According to the assumption that micro-
entrepreneurs can realize a higher return on their investments the bank can charge them
a higher rate of interest without bearing an increased risk Nevertheless in this example
the bank would still serve the market for large loans first because of the higher
transaction costs for smaller loans
The view as described in figure 4 is shared among most traditional banks and investors
in industrialized as well as in developing countries In addition to neglecting the
possibility of generating profits by offering microcredit themselves199 they also hesitate
to lend to MFIs because they consider their business too risky
194 See Schreiner (1997) p 64195 ldquoPAR shows the real risk of the portfolio by comparing outstanding loan balances for loans with atleast one late payment to the outstanding loan portfoliordquo Gross and de Silva (2002) p 22196 Own calculations See Appendix 2197 See Seibel (2000) p 11198 The Economist (1998) pp 92 et sqq199 Busch and Kort (2004) p 8
39
Figure 4 The extended Model
Source Own diagram adapted from Stiglitz and Weiss (1981) p 394 Tschach (2000)
p 17
This attitude can be observed by comparing the ratio of equity to liabilities which is
considerably higher for MFIs than for conventional banks200 When it comes to MFI
start-ups and those MFIs serving the low end market in remote areas even experienced
microfinance practitioners are skeptical if interest rates that fully recover all costs can
be charged201
Theoretically there are two ways to adjust this model to arrive at a conclusion which is
more favorable with regard to the profitability of microcredit One is to cut the
transaction costs and therefore reduce the downward shift of the R(I)small curve the
other is to allow the bank to further raise the interest rate without experiencing a
decrease in its return This means to increase I(s) and the respective rate of return
While in 2000 Tschach stated that transaction costs vary between 10 and 20 percent for
loans provided through the group lending model and between 15 and 30 percent for
200 See MicroRate and IADB (2003) p 30201 See Volkery (2004) p 33 Gibbons (2000) p 15 Gibbons and Meehan (2002) p 29 Goodwin-Groen (1999) p 8
INTEREST RATE I(l)
SmallLoans
LargeLoans
Transaction costs
I(s)
R(i)large
R(i)small
EX
PE
CT
ED
RE
TU
RN
TO
TH
E B
AN
K
40
individual loans202 it was recommended in 1999 that MFIs should target a range
between 15 and 25 percent203 Some best practices on the other hand have already
achieved single digit numbers Currently BDB might be the most efficient MFI in the
world with transaction costs at just 47 percent in 2001204 Even though the low costs of
BDB have to be acknowledged its achievement has to be put in perspective As stated
above with an average loan balance of more than $5000 it does not serve the low end
market In addition it works in an environment with a high population density which
means that it can reach a relatively large group of borrowers per branch This is a
comparative advantage many Asian MFIs enjoy as can be illustrated by comparing
Bangladesh and Bolivia Both countries are at the forefront of the development of
microfinance in their respective continent but while in Bangladesh more than 1000
people are living per square kilometer the average for Bolivia is only eight205
Therefore it is consistent that the most efficient MFI in Latin America Fondo
Financiero Privado para el Fomento a Iniciativas Economicas has transaction costs of
114 percent206 With an average loan size greater than the annual GDP per Capita this
institution also does not serve the low end market207
Despite the impressive efficiency gains in the described examples most MFIs are far
from achieving these numbers and many are unlikely to reach them due to the
environment within which they work A survey of 67 MFIs from 31 countries found the
average transactions costs in 2002 to be 279 percent with a median of 206 percent208
However even if these institutions were to increase their efficiency to best practice
standards their transaction costs would still be significantly higher than those of
traditional banks providing much larger loans For these banks the respective costs vary
in a range between 05 and 3 percent209 According to this argument charging interest
rates considerably higher than conventional banks is the only way for MFIs to generate
higher returns and hence successfully compete for capital
202 See Tschach (2000) pp 100 et sqq203 See Gibbons and Meehan (1999) p 149204 See M-Cril (2001b) p 4205 See CIA (2004)206 See MicroRate (2004)207 In this paper the term ldquolow endrdquo refers to the definition of the MBB (2003) p 54 Loans worth less than 20 percent of the respective countryrsquos GDP per capita are described that way 208 Own calculations See Appendix 3209 See M-Cril (2004a) p 16
41
6 Interest Rates
61 Setting the right Interest Rate
Before addressing the questions to what extend MFIs can raise their interest rates
without putting the repayment rate or the social benefits of their customers at risk a
basic model will be presented This model will illustrate how a MFI should set their
rates in order to not only cover their costs but also to generate an appropriate profit to
finance further growth and attract additional capital
In 2002 CGAP revised its 1996 paper ldquoMicrocredit Interest Ratesrdquo210 which outlines
the standard method of setting sustainable interest rates for commercially oriented
MFIs According to this model the annual effective interest rate (I) should be calculated
as shown below
(1) I = LL
IIKCFLLTA
minusminus+++
1
With each variable being a decimal fraction of the average outstanding loan portfolio
whereby TA stands for the transaction costs as described above LL represents the
annual loan loss and II stands for investment income eg on liquid assets The cost of
funds (CF) consist of the interest and administrative costs needed to obtain deposits and
commercial loans as well as of the imputed costs on equity due to inflation K stands for
the capitalization rate which represents the net real profit Keeping this rate high is
important to finance the future growth of the loan portfolio This can be either done
through investors attracted by high profitability or through borrowing For the latter an
increase in equity is inevitable since it is required as a safety cushion by lenders
Since this model ignores the timing of cash flows and does not take taxes into account
it has to be regarded as fairly imprecise and hence should not be used for business
planning Nevertheless it can be used for an approximation of the interest rate that a
MFI would need to charge to provide its services as planned In the following I will
210 See Rosenberg (2002) pp 1 et sqq
42
apply this model on a fictitious MFI working in a rural area of Latin America with low
end customers In this setting it seems realistic to estimate transaction costs of 35
percent and loan loss rate of two percent211 If funds were borrowed at commercial
terms their costs can be assumed to equal at least 15 percent of the average outstanding
loan portfolio212 Estimating the capitalization rate is more challenging First the
targeted portfolio growth rate is set at 75 percent This is slightly below the 751 percent
average annual portfolio growth between 2000 and 2002 found by a survey of 25
different MFIs based in Central and South America213 If the extend to which the MFI
can leverage stays constant the loan portfolios growth would be limited by the growth
rate of the equity To express the capital needed for this growth as a share of the loan
portfolio it is necessary to estimate the ratio between the equity and the outstanding
loan amount According to the survey mentioned above the loan portfolios of the 25
Latin American MFIs equal on average 215 times their equity214 With this number the
capital needed to increase the equity by 75 percent would corresponds to approximately
35 percent of outstanding loan amount (075215) Finally the investment income has to
be estimated Since liquid assets that are available short term do not generate high
returns say five percent it does not seem advisable for the MFI to hold more than a
quarter of its loan portfolio in this form Hence the profit generated in this way would
equal 125 percent of the outstanding loan amount Using these numbers the equation to
calculate the annual effective interest rate reads as follows
(2) I = LL
IIKCFLLTA
minusminus+++
1 =
0201
01250350150020350
minusminus+++
= 0875
As a result the MFI would need to charge an annual effective interest rate of
approximately 875 percent on its loans in order to sustainable provide its services and
finance its growth without depending on donor money This rate might decrease once
the MFI matures the growth slows down and cheaper funds become available but it
will stay significantly higher than any rate charged by conventional banks
211 MicroRate and IADB (2004) pp 6 and 16212 See MicroRate and IADB (2004) p 616 and 28213 Own calculation See Appendix 4214 Own calculations See Appendix 5
43
62 Can Micro-Entrepreneurs bear these Rates
Although most MFIs charge rates significantly below 875 percent many critics have
strenuously argued against any rates exceeding those of traditional banks Rosanna
Barbero of Oxfam labeled an interest rate of 52 percent charged by a Cambodian MFI
ldquoludicrous evil and disgusting and stated that ldquo[n]o business in the world can make a
profit at these interest ratesldquo215 The former finance minister of Bangladesh Shah Kibria
even categorized the 20 percent effective rate charged by the Grameen Bank as to
high216 Many practitioners therefore believe in a strong negative correlation between
the interest rate and the demand for loans217 Others have argued more generally that
concentrating on profitability and therefore charging high interest rates diverts MFIs
from serving the poorest218
These views are still shared among many MFI managers donor agencies and especially
investors and politicians While the former are unwilling to charge interest rates for
funds they received ldquocheaplyrdquo (through grants or subsidized loans) and are worried
about undermining their social goals by charging higher rates of interest219 the latter are
reluctant to invest for reasons stated above or impose interest caps to catch the attention
of the public by pretending to protect the poor from usury rates220
In chapter 53 it has been described that micro-entrepreneurs due to their smaller
capital endowment have even better investment opportunities than big business The
extend to which this is true has not yet been answered An indication is the high
repayment rate observed within MFIs around the globe If their customers capital yield
did not exceed the charged interest rate how would they be able to repay According to
Gibbons and Meehan customers of MFIs can generally generate returns of more than
100 percent on their invested capital221 and ldquo[r]esearch in India Kenya and the
Philippines found that the average annual return on investments in microenterprises
215 See Kate and Roeun (2004)216 See Hodson (2001) min 1100217 See Morduch (1999a) p 1594218 See Prisma (2002) p 1219 See Schreiner (1997) p 60 Khandker (1998) p 106 220 See Gross and de Silva (2002) p 32 Jansson and Wenner (1997) p 36 et sqq Campion (2002) p 59221 See Gibbons and Meehan (1999) p 131
44
ranged from 117 to 847 percentrdquo222 Schmidt and Tschach found the marginal
productivity of capital to be as high as 1000 percent for the smallest loans provided by
the Bolivian MFI Caja Los Andes223 These findings are confirmed by the observation
of Rosenberg who found while working as a microfinance consultant for ten years he
never heard of a single MFI having problems to attract clients because interest rates
were too high224
To get a better understanding of the investment opportunities of low income people in
developing countries a typical example on how MFI clients invest their loans is as
follows
Zobair is working as a rickshaw puller in Bangladesh Like most of his colleagues he
does not own the rickshaw he is riding Therefore he has to pay a daily rent of about
$030 to the owner Since his average income of approximately $15 per day is hardly
enough to feed his family he is not able to save the $100 necessary to buy a rickshaw
on his own 225 If he could do so through obtaining a loan his income would increase by
$030 every day because he would not have to pay the rent for the rickshaw anymore
Assuming an average of six working days per week 226 and a life span of the rickshaw
of 5 years his internal rate of return would equal 15324 percent annually227
Consequently any interest rate charged by a MFI would be advantageous to him as long
as it would not exceed 15324 percent228
63 Should the Interest Rate be subsidized anyway
Despite the fact that numerous micro-entrepreneurs are able to generate tremendous
returns on their investment obviously not all are able to use capital in such a productive
way and therefore can not afford microcredit at commercial rates In order to reach
these people as well many MFIs continue to use donor money in order to keep their
interest rates low But even if the problems related to subsidized credit as described in
222 See Helms and Reille (2004) p 3223 See Schmidt and Tschach (2001) p 6224 See Rosenberg (2002) p 10225 This examples draws on observations made by the author in Dhaka (Bangladesh) during 2003226 Obviously extended holidays are not a viable option in this surrounding 227 Own calculation See Appendix 6228 This result is only valid if the loan is repaid in daily instalments For a weekly repayment schedule the interest rate charged by the MFI must not exceed 15119 percent in order to still be beneficial for Zobair
45
chapter 23 do not arise it might still not be the most effective tool to help poor people
as will be illustrated in the following example
A MFI faces two groups of potential clients one with businesses able to generate a
return of 125 percent on borrowed capital and another with a possible returns of 50
percent Assuming budget costs according to equation (2) the institution needs to
charge an interest rate of 875 percent and therefore only serves the former group
Supposed each group consists of 50 members demanding $100 loans the net gains to
society (NGS) could be calculated as follows
(3) NGS = 50 times ($125 ndash $875) = $1875
These gains would be due to the investments of the more profitable group which were
made possible through the loans provided by the MFI The less profitable group would
not borrow since their expected returns are not sufficient to pay for the interest If the
interest rate would be lowered to 30 percent both groups would be able to generate net
gains and therefore borrow from the MFI In order to provide loans at this rate the
institution would need to raise additional capital from non commercial sources The
NGS would be calculated as follows
(4) NGS = 50 times ($125 - $30) + 50 times ($50 - $30) + 100 times ($30 - $875) = 0
While the first terms represent the net gains to the respective groups the last describes
the costs incurred in providing the loans At a rate of 30 percent each loan would need
to be subsidized with $575 Hence the NGS actually fall after the introduction of the
subsidized loan This is due to the fact that the less profitable group is encouraged to
invest in relatively unproductive businesses In addition future growth of the MFI could
be jeopardized due to scarce donor money which is needed to finance the interest rate
subsidy Therefore it seems more advisable to continue to charge a rate of 875 percent
and spend the money used for subsidization on other programs such as health care or
education229
229 In Appendix 7 it will be shown that this result generally holds
46
7 Empirical verification
71 Setting up a Sample
To see if the findings of the previous chapters hold the effects which interest rates
charged by MFIs have on their performance will be analyzed in the following Up to
now such a study does not exist mainly because of a lack of adequate data Most MFIs
do not provide accurate information about the annual effective interest rate they charge
and therefore make an evaluation difficult
In 2002 Rosenberg distinguished eight different categories on how microcredit interest
rates are quoted230 These categories differ in several ways On the contrary to
traditional banks for example it is common for MFIs to state interest rates calculated on
a ldquoflatrdquo balance rather than on a declining one This means that the total loan amount is
used to determine the interest rate ignoring installments paid by the borrowers normally
on a weekly or monthly basis In addition many MFIs charge a certain upfront fee prior
to the loan disbursement require compulsory savings at a lower rate or state their
interest rate for semi annual terms only On the one hand this is done to provide
numbers that are more meaningful to MFI customers who often lack the necessary math
skills to deal with compound interest on the other hand it is done to circumvent interest
rate ceilings imposed by the government231 Another problem is that most MFIs offer
different loan products without itemizing their respective shares to their total loan
portfolio As a result it is not possible to calculate a weighted average even if the rate
stated by the respective MFI could be transformed into an effective interest rate
Usually the portfolio yield is used as a proxy in order to make statements about the
interest rate charged by a certain MFI232 It is generally ldquocalculated by dividing total
cash financial revenue (all income generated by the loan portfolio but not accrued
interest) by the period average gross portfoliordquo233 The advantage of this method is that
even the hidden costs are considered Nevertheless it also has a severe shortcoming by
not taking late or defaulted payments into account Therefore the portfolio yield does
230 See Rosenberg (2002) p 5231 MicroRate (2002) p 8232 See MicroRate (nd)233 MicroRate and IADB (2003) p 39
47
not allow to draw conclusions regarding the correlation between the interest rate
charged by a MFI and its PAR
72 Examining the Sample
Through the appearance of rating agencies specialized in the microfinance sector more
adequate information has become available in recent years While MicroRate only
publishes the portfolio yield of rated MFIs M-Cril Microfinanza Microserve and
Planet Rating actually provide information about the annual effective interest rate for at
least some of the MFIs they analyze Although it is labelled differently from all of the
four institutions234 the term describes what is ldquothe highest income or yield that an
organisation can earn from its portfolio based on the terms of its loansrdquo235
Currently236 reports of 39 different MFIs from 20 countries providing accurate
information about the effective annual interest rate are available to the public This
sample should be used to verify the findings of the previous chapters237 Since a
comparison is made between the performances of MFIs based in different countries and
the ratings have been carried out in different years several adjustments are necessary
First the inflation of the respective country and the respective year(s)238 has to be taken
into account in order to only compare the real rates239 In addition the average
outstanding loan amount per borrower is divided by the respective countryrsquos GDP per
capita Since it can be assumed that ldquoonly the poorer households will be willing to take
the smallest loansrdquo240 this number can be used as a proxy for the poverty level
Although the sample size is far to small to represent the microfinance sector as a whole
and the results are statistically not significant the findings can still be used to underline
the theoretical conclusions drawn in the previous chapters In figure 5 the connection
234 M-Cril uses the name ldquoannual percentage raterdquo See eg M-Cril (2004a) p 25 Microfinanza uses the name ldquoexpected portfolio yieldrdquo See eg Microfinanza (2002c) p 25 Planet Rating uses the name ldquoannual effective interest raterdquo See eg Planet Rating (2004d) p 1 Microserve uses the name ldquotheoretical yieldrdquo See Microserve (2003) p 62235 See M-Cril (2004a) p 25236 As of September 28th 2004237 See Appendix 8 For exchange rates see FXTOP (2004)238 Where necessary a weighted average of the annual inflation rate was used See Appendix 9239 This is done through the following formula ir = (I ndash F) (1 + F100) While ir represents the real annual effective interest rate F represents the inflation rate 240 Morduch (1998) p 1572
48
between the average loan size and the transaction costs as a share of the average loan
portfolio is illustrated
Figure 5 Loan Size vs Interest Rate241
Source Own diagram
000
1000
2000
3000
4000
5000
6000
7000
8000
9000
10000
0 100 200 300 400 500 600
Loan Size
Inte
res
t R
ate
It can be seen that the interest rate is negative correlated to the loans size This can be
explained by the relative higher transaction cost for smaller loans as described in
chapter 52 In order to cover their costs MFIs serving the low end market need to
charge higher rates to their customers than those organizations serving the better off
poor Obviously there are several assumptions to this general finding Especially
striking are the two MFIs with an average loan size of approximately five times their
countries GDP per capita which still high interest rates This occurrence can be
explained by taking a closer look to the respective organizations One was established
less than two years prior to its rating and therefore still bears a lot of start up costs242
241 The equation for the regression line reads as follows Y = -00219X + 365 The correlation coefficient is 014242 See Microfinanza (2002b) p 1
49
the other managed to stay profitable while it almost quadrupled its loan portfolio in the
last two years243
Figure 6 Interest Rate vs PAR244
Source Own diagram
0
5
10
15
20
25
30
35
0 20 40 60 80 100 120
Interest Rate
PA
R
In Figure 6 the crucial correlation between the interest rates charged by a MFIs and its
PAR245 is examined According to the given sample the view of traditional banks and
investors that a higher interest rate leads to a higher default rate does not hold
Obviously one has to avoid to draw the opposite conclusion namely that a high interest
rates decreases the PAR The connection illustrated in figure 6 has to be interpreted as
follows Since high interest rates are related to small loans the low PAR for MFIs
charging high interest rates can actually be explained by the tremendous profitability of
small size investments Despite the high rates their customers are even more likely to
repay
243 See Planet Rating (2003b)244 The equation for the regression line reads as follows Y = -00768X + 68433 The correlation coefficient is 0235245 M-Cril only publishes the PAR for overdues greater than 60 days Therefore these ratios are used as a proxy for the industry standard of 30 days for some Asian MFIs
50
Finally it has to be examined if charging high interest rates actually enables MFI to
generate higher returns Although it can be expected that the combination of a low PAR
and a high interest rate leads to a high profitability it still has to be checked if this is not
outdone by soaring transaction costs Figure 7 illustrates the correlation between the
interest rate charged by a MFI and its financial self-sufficiency (FSS) The latter is the
ldquo[r]atio of total income to total adjusted expenses for the year Adjustments are made
for subsidised cost of funds (relative to market interest rate) equity (with respect to
inflation) and in-kind donationsrdquo246 It can be seen that the regression line actually does
indicate a positive correlation between the interest rate and the profitability of a MFI
Figure 7 Interest Rate vs FSS247
Source Own diagram248
0
20
40
60
80
100
120
140
160
180
0 20 40 60 80 100
Interest Rate
FS
S
246 M-Cril (2004a) p 53247 The equation for the regression line reads as follows Y = 02839X + 8901 The correlation coefficient is 0174248 Since the interest rate the customers of the MFI Foccas have to pay includes fees which are not passed on to the institution its interest rate in this diagram is set at 723 percent instead of the 10715 percent used for figure 6 See Planet Rating (2003b) p 1
51
This result does not necessarily disprove the findings of Stiglitz and Weiss since it can
be argued that MFIs simply do no increase their interest rates to the point where they
would maximize their expected returns But if this would be true why do MFIs not
charge higher rates of interest given the demand described in chapter 41 and 43 In
mature markets competition normally ensures prices not to exceed a certain level but
since many MFIs still operate in a ldquosellerrsquos marketrdquo249 this can not explain the findings
as described in figure 7 Therefore it has to be assumed that a combination of the
unwillingness of many microfinance practitioners to burden their customers with high
interest rates and the plain disbelief of traditional investors that micro-entrepreneurs can
bear those rates is responsible for this occurrence
249 See MicroRate and IADB (2003) p 9
52
8 Conclusions
It has been shown that MFIs are not only contributing significantly to the development
of the financial sector in their respective countries but also that they play an important
role to eradicate poverty by providing much needed capital to low income people which
are able to generate tremendous returns on their investments
The fact that the demand for microcredit is not met is mainly due to the view of most
for profit investors and traditional banks that offering financial services to poor people
can not be done profitable Because of this conviction they hardly invest in the
microfinance sector This does not have to be the case according to the findings of this
paper Although faced with relatively high transaction costs MFIs are able to charge
interest rates at levels that fully recover their costs Elizabeth Rhynersquos claim ldquothat the
most financially viable programs differed from their less viable peers in their
willingness to set interest rates at levels that would fully recover costsrdquo250 is backed by
the findings of this paper that high profitability is correlated to high interest rates
Theoretical models based on the findings of Stiglitz and Weiss can not be used as a
justification to ration credit for the microfinance sector since the interest rate that
maximizes profits to the lender can be assumed to exceed 100 percent for many MFIs
Nevertheless this rate is hardly charged although it has been shown that it can be done
The Mexican MFI Compartamos for example manages to keep its PAR as low as one
percent while charging an effective interest rate of more than 100 percent to
approximately 160000 clients251 In combination with this case the conclusions drawn
from examining the sample of MFIs in chapter 7 the claim of Hulme and Mosley as
stated in the introduction can be considered as wrong MFIs are in fact able to finance
rapid growth stay profitable by charging corresponding interest rates and still have a
significantly positive impact on the poverty level of their clients In the long run gains
in efficiency economies of scale a slowdown in growth and competition will ensure
interest rates drop as it has already been the case in countries like Bangladesh and parts
of Bolivia252
250 See Rhyne (1998) p 7251 See MicroRate (2004)252 See Microrate and IADB (2003) p 9
53
According to a MicroRate survey many MFIs are more profitable than Citibank and also
generate a higher return on investment than commercial banks in their respective
countries253 Investments companies like IMI or Blue Orchard will soon be able to
present a meaningful track record of their microfinance investments to potential
investors Ultimately the capital markets can not ignore the facts proving that it actually
can be profitable to invest in the microfinance sector but in order to raise money
quickly microfinance practitioners will have to continue to intensively promote their
cause not only to for profit investors but also to donors and multilateral agencies like
the World Bank
253 See MicroRate (2002) p 10
54
Appendix
Appendix 1 Average loan balance
Source Data is available through the Mix Market (2004)
Organization
Loan Portfolio 2002 (US$)
Loan Portfolio 2003 (US$)
Number of borrowers 2002
Number of Borrowers 2003
2CM 1263602 1400438 3622 3708ACF 955503 1611401 285 370ACLEDA 26846703 39391301 82598 98905ACME 1460881 1714844 4283 4600ADIM 369065 407798 1122 1395AFK 933306 1706577 250 467AgroInvest 4684249 9697411 5208 9629Al Amana 15593277 28677666 78114 101610AMSSFMC 612167 1040756 6183 6886AREGAK 3285273 3987011 11841 14377AVFS 214331 269819 1883 2866BancoSol 83629049 91175000 42290 56707BESA 10563980 15114430 4488 5061BPR AK 613362 876130 1730 3879BPR BMMS 133949 237946 1755 1779BRI 1344006170 1720072773 3056103 3100358BZMF 1592508 1922097 1250 1331CBDIBA 216587 242465 5764 2877CCA 2146235 4582302 4070 6585CCCP 447534 851678 6265 9450CEP 3795400 5261957 32291 42132CERUDEB 25093643 34873228 34490 44796CMEDFI 227674 250244 3467 3781CMM - Bogota 4836000 8135968 15635 22038CMMB 34880 56964 42 190COAC Maquita Cushunchic
870084 1855718 6603 7732
CODES 280843 263091 60 60CODESARROLLO 6714007 12935951 4391 6896Constanta 2943822 3536047 16134 18588COOPEC CAMEC MN
7152 29821 92 77
Crear - Tacna 3891116 4636094 3671 4948CREDIT 642094 81838 7532 8097CRYSTAL FUND 366456 421403 1379 1061DBACD 3473701 3876526 12812 19606ECLOF - ECU 1154292 728312 860 416ECLOF - MAL 441734 407227 1118 1500EKI 11833244 19245751 8999 13323EMT 4481589 5765281 84781 92173ESED 8579460 6834742 22790 20035
55
Eshet 185741 462569 3308 6540Faulu - KEN 9027332 7206344 17463 15000FDL 12503027 16545332 21306 25106FIE 35818903 41597315 26468 33100FINADEV 5512586 9770323 12775 14709Finance Salone 211312 434298 2225 7159Finca - TAN 1293430 1854834 20648 27499Finca - UGA 2451703 2798869 35610 36912FINCORP 4761288 10236896 941 858FJN 5473563 8037662 8107 11133FMFB 308158 1188896 713 3558FMM -Bucaramanga
6355518 10227000 25814 42464
FODEM 739181 939824 1909 2501FundaciESPOIR
898561 1883446 5911 9464
FUNDESER 798907 1373113 4072 5065Gasha 323748 413742 5504 6423GGLS Save the Children
64235 137957 1291 2362
GK 56986 166971 951 2718HKL 1363365 1420357 6648 5372HOPE 402799 603488 1098 1562IAMD 42132 56550 2780 2772IDECE 21312 39453 150 232IDF 2031944 2626382 31003 36580IMCEC - Dakar 254759 688449 1018 2983IMCEC - Thies 199799 571122 1164 1261
ISSIA 221615 246792 1409 1698JMCC 1962355 2609723 1471 2333KAFC 21710638 29241051 24850 32097KAMURJ 1003935 1411258 5559 5691Kashf 2355965 6271498 29655 59389KMBI 721409 1626666 11973 27266KPSCA 109299 128063 362 794K-Rep 14490447 20699963 38739 45379KSCS 18978 43740 140 297KVT 44075 70621 241 373LAPO 922478 1194633 18740 19139MEC ADEFAP 27788 69248 198 202MEC Bosangani 14357 31086 364 540MEDF 104113 136257 1278 1184Meklit 233170 252232 2084 3577Metemamen 22123 57778 943 1501MFSC 109261 171090 511 687MIKRA 2951028 5008784 4145 6095MIKROFIN 9560502 18380263 5633 7426Miselini 737387 1026639 10182 11431MRFC 11475440 9133130 163000 180000Mushuc Runa 2089076 5418325 3139 6232Nirdhan 2886777 3016171 29589 27457OCSSC 5245186 7658413 42157 6215o
56
Otiv Diana 95992 638422 229 1073Otiv Sambava 188094 437974 2002 1442Otiv Tana 66465 673175 337 1269Partner 9976448 15321304 7139 11935PCA 6878257 6885926 63113 58147PEACE 420746 627295 4192 5428PEDF 164399 254233 2357 3340Piyeli 809447 1206656 8674 4745PRESTANIC 2827502 3540367 1477 2605PRIDE - MAL 991888 854631 5376 5601PRIZMA 3881581 6838978 8112 10968ProMujer -Nicaragua
1006871 1424437 10436 13047
PTF 891566 1068881 8500 9070RBST 818594 1058115 619 723REMECU 1381705 1483471 10330 13996
RUSCA 60887 100820 454 994
SCSCS 89423 157472 873 1007SFPI 709497 903556 7728 9552Sidama 934260 1011798 10267 11346SPBD 117807 186029 647 1740Sunlink 819138 1056823 3401 3833Sunrise 5412366 8782868 4560 7256TEBA 108032426 176300111 163021 157776TIAVO 281978 838905 2049 459TPC 1140429 2267148 22869 31668TSPI 4650989 5383755 49649 75617UNICECAM 3442843 5943804 16039 19031Wasasa 230657 274908 2850 3728Wisdom 1306066 1404463 10524 12054XacBank 4910098 9829503 11063 18610Zakoura 15907288 12444768 103720 118980
Appendix 2 Portfolio at Risk
Source Data is available through the Mix Market (2004)
Organization PAR 2002ABA 202ACEP 464ACLEDA 175ACODEP 452ACSI 209Al Amana 010Apoyo Integral
483
AREGAK 692Banco Solidario
500
BancoSol 660BASIX 1296
57
BRI 437BURO Tangail
350
CEP 200CERUDEB 103CMAC -Sullana
567
CMM -Bogota
176
Compartamos 111Constanta 304Credi Fe 212CREDIAMIGO 409DBACD 010EBS 847EMT 010ESED 1311FADES 2311Faulu - KEN 246Faulu - UGA 096FDL 212FECECAM 428FED 436FIE 598FINADEV 021Finamerica 1133Finca - TAN 000Finca - UGA 297FMM -Bucaramanga
094
FMM -Popayan
088
FONDEP 013FORA 064Genesis Empresarial
1197
IDF 017KAFC 106Kashf 000KMBI 128K-Rep 229MiBanco 309MRFC 1742Nirdhan 373
PADME 079PAMECAS 284PCA 379PRIDE - TAN 018ProMujer -Nicaragua
073
RCPB 600REMECU 157SHARE 000
58
Soluci 182Spandana 014TEBA 106TSPI 355UMU 125UNICECAM 405Urwego 290UWFT 363WAGES 736WWB -Medellin
235
XacBank 061Zakoura 095
Appendix 3 Transaction Costs
Source Data is available through the Mix Market (2004)
OrganizationTransaction Costs
Acci Rural 1154ACEP 858ACLEDA 2430ACODEP 2920ACSI 924Al Amana 2576AREGAK 2856AssEF 1919Banco Solidario
1826
BancoSol 1210BASIX 1317BRI 1353BURO Tangail
2053
CEP 1759CERUDEB 5109CMAC -Sullana
1784
CMM -Bogota
2089
Compartamos 3341Constanta 4597Credi Fe 1978CREDIAMIGO 2525DBACD 1742EBS 2377EMT 3220ESED 1343FADES 1673FAMA 2436
59
Faulu - KEN 2253Faulu - UGA 4962FDL 1726FECECAM 2587FED 4083FIE 1125Finamerica 1563Finca - TAN 10753Finca - UGA 9096FMM -Bucaramanga
1925
FMM -Popayan
1112
FONDEP 5477FORA 3481Genesis Empresarial
1626
IDF 1695
K-Rep 1909LAPO 3511MiBanco 2456Nirdhan 1325NWTF 3109OCSSC 1155PADME 1131PAMECAS 1705PCA 1670PRIDE - TAN 4273ProMujer -Nicaragua
5078
RCPB 2059SHARE 2308Sidama 2662Soluci 2906Spandana 641TEBA 1213TSPI 3898UMU 4023UNICECAM 10120Urwego 7437Wisdom 1906WWB -Medellin
1703
XacBank 4144Zakoura 1881
60
Appendix 4 Portfolio Growth
Source Data is available through the Mix Market (2004)
Organization
Total Loan Portfolio in 2000
Total Loan Portfolio in 2002
ACODEP 5889394 7258487Adelante 4327 88594ADRI 1514681 2591240AgroCapital 11100088 12018280Banco Solidario 39632165 103420000
BancoSol 78031172 83629049CMAC - Sullana 14596365 28055720
COAC Maquita Cushunchic
348443 870084
CODESARROLLO 1374801 6714007Compartamos 10804279 41825248Crear - Tacna 3778816 3891116
Credi Fe 781616 9393936ECLOF - ECU 179247 1154292
FADES 11948814 15501578FAMA 6201411 8835134FIE 22524645 35818903Finamerica 16575104 16097113FINCOMUN 3278938 5696556FMM - Popayan 6241821 12212867
FONDECO 3456625 5101801Genesis Empresarial
11154234 17746288
MiBanco 36964072 95873333Mushuc Runa 90737 2089076ProMujer -Nicaragua
426541 1006871
WWB - Medellin 2891207 4580998
Appendix 5 Portfolio vs Equity
Source Data is available through the Mix Market (2004)
OrganizationLoan Portfolio Equity
ACODEP 7258487 1921447Adelante 88594 72973
ADRI 2591240 781477AgroCapital 12018280 10766101Banco Solidario 103420000 12961000BancoSol 83629049 15299415CMAC - Sullana 28055720 6210291
61
COAC Maquita Cushunchic
870084 260331
CODESARROLLO 6714007 1285103
Compartamos 41825248 18350446
Crear - Tacna 3891116 1016912Credi Fe 9393936 863848ECLOF - ECU 1154292 459226FADES 15501578 4138972FAMA 8835134 6377663FIE 35818903 5360484Finamerica 16097113 3817960FINCOMUN 5696556 1042241FMM - Popayan 12212867 8510494FONDECO 5101801 1658075Genesis Empresarial
17746288 4765816
MiBanco 95873333 24261889Mushuc Runa 2089076 434311ProMujer -Nicaragua
1006871 1196015
WWB - Medellin 4580998 2213249
Appendix 6 Internal Rate of Return
Source Excel (German Version) calculation based on own data
A B C D E F
1 Date Cash Flow
Interest Rate Internal Rate of Return Balance Interest Principal
23 01012004 -100 15324 100 025489547 0045104534 02012004 03 999548955 025489547 0045104535 03012004 03 99909676 02547805 004521956 04012004 03 998643412 025466524 0045334767 05012004 03 998188909 025454968 0045450328 06012004 03 997733247 025443383 0045566179 08012004 03 999826083 050928361 -0209283610 09012004 03 999374595 025485114 004514886
hellip hellip hellip hellip hellip helliphellip hellip hellip hellip hellip hellip helliphellip hellip hellip hellip hellip hellip hellip1562 23122008 03 177951388 000528711 0294712891563 25122008 03 148859724 000908336 0290916641564 26122008 03 119239161 000379437 0296205631565 27122008 03 089543096 000303935 0296960651566 28122008 03 059771337 000228241 0297717591567 29122008 03 029923692 000152354 0298476461568 30122008 03 -3434E-07 000076274 029923726
62
The formula in the square C3 reads as follows
ldquoXINTZINSFUSS(B3B1568A3A156815)rdquo
Appendix 7 Subsidized Interest Rates and the Net Gains to Society
SourceOwn calculations
For simplicity only two groups of potential clients are distinguished This is possible
since using a continuum of potential clients would lead to the same results In addition it
is assumed that the amount of every loan (L) is equal and that all clients invest the
whole loan amount Group H consist of NH potential clients with a rate of return (rH) on
their invested capital higher than the cost recovering interest rate charged by the MFI
(iC) Group L consists of NL potential clients with a rate of return (rL) on their invested
capital lower than iC If the MFI charges iC the NGS can be calculated as follows
NGSC = NH times (rH - iC) times L
Since rH is bigger than iH (rH gt iC) according to the definition presented above the term
NGSH must be positive as long as NH does not equal zero If the MFI introduces a
subsidised interest rate (iS) lower than rL the NGS can be calculated as follows
(1) NGSS = NH times (rH - iS) times L + NLtimes (rL - iS) times L + (NH + NL) times (iS - iC) times L
(2) NGSS = NH times (rH- iC) times L + NLtimes (rL - iC) times L
The term (NH + NL) times (iS - iC) times L describes the amount of money that is needed in order
to subsidize the interest rate to the level iS By setting up an inequation it can be
examined under which conditions the NGSS are bigger than the NGSC
(3) NGSS gt NGSC
(4) NH times (rH- iC) times L + NLtimes (rL - iC) times L gt NH times (rH - iC) times L
(5) NLtimes (rL - iC) times L gt 0
(6) rL gt iC
63
So the NGSS could only be bigger than the NGSC if equation 6 holds This is
impossible since it violated the definitions presented above Therefore the introduction
of subsidized interest rates is always accompanied with a drop in the NGS
Appendix 8 Interest Rate vs Loan Size vs FSS vs PAR
Source Data is available through the Mix Market (2004)
Organization Country
Real Interest Rate
Loan Size (divided by the GDP per Capita) FSS PAR
BTFFKyrgyz Republic 3803 48260 1487 698
BesaFoundation Albania 2184 16076 684 260RFF Albania 1198 5783 4764 277PSHM Albania 2194 000 5758 198Mi-Bospo Bosnia 2974 5499 1261 020Prizma Bosnia 3474 3569 103 064Agroinvest Serbia 2201 4401 875 020KCLF Kazakhstan 5713 1713 865 090
Foccas Uganda10716 (723) 1550 584 29
ACEP Senegal 3280 20941 1643 1Padme Benin 2715 13575 1667 08Papme Benin 3086 53659 1405 24Vital Finance Benin 2676 9394 1015 17Finadev Benin 1738 14850 1024 21ABA Egypt 2579 1613 1168 88ASBA Egypt 2597 1702 1252 68DBACD Egypt 2490 1643 1073 0SBACD Egypt 2500 1734 982 67AMSSF Morocco 6926 787 1306 04Fondep Morocco 5199 650 889 071Zakoura Morocco 4414 900 98 006ENDA Tunisia 4008 1351 110 102BSFL India 1954 3269 856 99Share India 3426 1440 951 0Spandana India 2942 1618 1367 026SWC India 1864 2626 42 3036SKS India 2248 1912 578 0Grama Vidiya India 3176 1221 76 18Sneha India 3451 1433 933 0Buro Bangladesh 3206 1882 1093 17Upap Pakistan 2073 8183 757 03Seeds Sri Lanka 1004 1088 605 287EMT Cambodia 4324 1676 1016 01TPC Cambodia 4470 2035 832 27
64
WTF Phillippines 5816 1095 941 74TSKI Phillippines 5794 777 96 79Cacja Ecuador 862 6189 9460 897ACME Haiti 6043 6934 11685 450Grupo Cama Mexico 8961 267 10717 288
65
Appendix 9 Inflation vs GDP per Capita
Source IMF (2004)
Country Subject Description Units Scale 2000 2001 2002 2003 2004
Albania Gross domestic product per capita current prices US dollars Units 1083988 1238206 1396172 1757778 2229712
Albania Inflation annual percent change Percent 00 31 52 24 34
Bangladesh Gross domestic product per capita current prices US dollars Units 329310 327980 344494 369495 393717
Bangladesh Inflation annual percent change Percent 22 15 38 54 64
Benin Gross domestic product per capita current prices US dollars Units 361340 368213 405951 494725 560129
Benin Inflation annual percent change Percent 42 40 24 15 26
Bosnia and Herzegovina Gross domestic product per capita current prices US dollars Units 1255837 1321429 1466090 1807392 2070508
Bosnia and Herzegovina Inflation annual percent change Percent 50 32 03 02 09
Cambodia Gross domestic product per capita current prices US dollars Units 276413 280352 296577 305940 321247
Cambodia Inflation annual percent change Percent -08 02 33 12 20
Ecuador Gross domestic product per capita current prices US dollars Units 1227711 1590267 1804362 1957183 2082156
Ecuador Inflation annual percent change Percent -77 377 126 79 32
Egypt Gross domestic product per capita current prices US dollars Units 1550982 1461431 1278462 1188060 1083158
Egypt Inflation annual percent change Percent 28 24 24 32 52
India Gross domestic product per capita current prices US dollars Units 454206 458849 472915 542554 602625
India Inflation annual percent change Percent 40 38 43 38 47
Kazakhstan Gross domestic product per capita current prices US dollars Units 1236159 1490946 1655148 2000598 2579554
Kazakhstan Inflation annual percent change Percent 134 83 59 64 68
Kyrgyz Republic Gross domestic product per capita current prices US dollars Units 278256 306130 321079 349632 380637
Kyrgyz Republic Inflation annual percent change Percent 187 69 21 31 45
66
Mexico Gross domestic product per capita current prices US dollars Units 5957486 6274468 6425203 6111754 6377064
Mexico Inflation annual percent change Percent 95 64 50 45 44
Morocco Gross domestic product per capita current prices US dollars Units 1161302 1162154 1199584 1432725 1541041
Morocco Inflation annual percent change Percent 19 06 28 12 20
Pakistan Gross domestic product per capita current prices US dollars Units 437381 400356 440471 492913 538120
Pakistan Inflation annual percent change Percent 44 31 32 29 46
Philippines Gross domestic product per capita current prices US dollars Units 979423 900225 950707 963765 1018710
Philippines Inflation annual percent change Percent 43 61 31 30 54
Russia Inflation annual percent change Percent 208 215 158 137 103
Senegal Gross domestic product per capita current prices US dollars Units 478704 474460 507408 634171 714622
Senegal Inflation annual percent change Percent 09 30 23 -00 08
Serbia and Montenegro Gross domestic product per capita current prices US dollars Units 1031263 1389384 1882036 2491799 2795805
Serbia and Montenegro Inflation annual percent change Percent 699 911 212 113 79
Sri Lanka Gross domestic product per capita current prices US dollars Units 846811 796025 828256 904330 982466
Sri Lanka Inflation annual percent change Percent 62 142 96 63 64
Tunisia Gross domestic product per capita current prices US dollars Units 2034360 2065140 2149421 2534823 2881273
Tunisia Inflation annual percent change Percent 30 19 28 28 34
Uganda Gross domestic product per capita current prices US dollars Units 293404 249682 279587 280802 287204
Uganda Inflation annual percent change Percent 45 -20 57 51 35
67
References
Akerlof George A The Market for ldquoLemonsrdquo Qualitative Uncertainty and the Market Mechanism in Quarterly Journal of Economics Vol 84 (1970) pp 488-500
Amin Ruhul et al Integration of an Essential Service Package (ESP) in Child and Reproductive Health and Family Planning with a Micro-Credit Program for poor Women Experience from a Pilot Project in Rural Bangladesh in World Development Vol 29 (2001) No 9 pp 1611-1621
Bester Helmut Screening vs Rationing in Credit Markets with Imperfect Information in The American Economic Review Vol 75 (1985) No 4 pp 850855
Borst Dietmar Microfinance ndash Theoretische Grundlagen fuumlr den Einsatz sowie die Abschaumltzung des Potentials anhand einer Datenbankuntersuchung zur Verwundbarkeit der laumlndlichen Bevoumllkerung in Vietnam unpublished diploma thesis Karlsruhe 2004
BRAC Annual Report 2002 Dhaka 2003
Busch Alexander Kort Katharina Die Peanuts-Banker und ihre Kunden in Handelsblatt Nr 150 published August 5th 2004 p 8
Campion Anita Challenges to Microfinance Commercialization in Journal of Microfinance Vol 4 (1999) No 2 pp 57-65
Chu Michael Key Issues of Development Finance Somerville (MA) 1998
Dornbusch Ruumldiger Fischer Stanley Makrooumlkonomie Oldenburg 1995
Dunn Seth Flavin Christopher Moving the Climate Change Agenda Forward in State of the World New York London 2002 pp 24-50
Farrington Todd Efficiency in Microfinance Institutions in The MicroBanking Bulletin Issue No 4 pp 18-24
Gardner Gary The Challenge for Johannesburg Creating a More Secure World in State of the World New York London 2002 pp 3-23
Ghatak Subrata On Interregional Variations in Rural Interest Rates in Journal of Developing Areas Issue 18 pp 21-34
Gibbons David Serving the Poorest Sustainably in The MicroBanking Bulletin Issue No 5 (2000) pp 13-16
Gibbons David Meehan Jennifer W The Microcredit Summitrsquos Challenge WorkingToward Institutional Financial Self-Sufficiency While Maintaining a Commitment to Serving the Poorest Families in Journal of Microfinance Vol 1 (1999) No 1 pp 131-192
68
Goodwin-Groen Ruth Do Asian MFIs Access Funds from Commercial Banks inThe MicroBanking Bulletin Issue No 3 pp 8-10
Grameen Bank (ed) Grameen Generalized System Dhaka 2003
Gross Alexandra de Silva Samantha Social Fund Support of Microfinance A Reviewof Implementation Experience The World Bank Social Protection Discussion Paper No 0215 Washington DC 2002
Hashemi Syed M Schuler Sidney R Sustainable Banking with the Poor A Case Study of Grameen Bank Dhaka 1997
Helms Brigit Reille Xavier Interest Rate Ceilings and Microfinance The story so farConsultative Group to assist the Poor Occasional Paper No 9 September 2004 Washington DC 2004
Hoff Karla Stiglitz Joseph E Introduction Imperfect Information and Rural Credit Markets-Puzzles and Policy Perspectives in The World Bank Economic Review Vol 4 (1990) No 3 pp 235-250
Holcombe Susan Managing to Empower The Grameen Bankrsquos Experience of Poverty Allevation Dhaka 1995
Hulme David Mosley Paul Finance against Poverty London 1996
Jalvaani (ed) Flush with loans Micro credit for rural sanitation Vol 2 (1999) No 2 pp 1-2
Khandker Shahidur R Fighting Poverty with Microcredit Experience in Bangladesh Oxford et al 1998
Khandker Shahidur R Khalily Baqui Khan Zahed Grameen Bank Performance andSustainability The World Bank Discussion Paper No 306 Washington DC 1995
Lipsey Rechard G An Introduction to Positive Economics 5th edition London 1979
Littlefield Elizabeth Morduch Jonathan Hashemi Syed M Is Microfinance an Effective Strategy to Reach the Millennium Development Goals Consultative Group to Assist the Poorest Focus Note No 24 Washington DC 2003
Martinot Eric Cabraal Anil World Bank Solar Home Systems Projects Experience and Lessons Learned 1993-2000 in Renewable Energy Oxford 2000 pp 1-8
M-Cril Microfinance Review 2003 revised February 2004 Gurgaon 2004a
Mezzera Jaime Microcredit in Brazil The Gap Between Supply and Demand in The MicroBanking Bulletin Issue No 8 (2000) pp 22-24
The MicroBanking Bulletin (ed) Note to the Reader Vol 1 (1997) Issue No 1 pp 5-8
69
The MicroBanking Bulletin (ed) An Introduction to the Peer Groups and Tables Issue No 9 (2003) pp 53-60
MicroRate IADB Performance Indicators for Microfinance Institutions Technical Guide 3rd edition Washington DC 2003
MkNelly Barbara Dunford Christopher Impact of Credit with Education on Mothers and Their Young Childrenrsquos Nutrition Lower Pra Rural Bank Credit with Education Program in Ghana Freedom from Hunger Research Paper No 4 Davis (CA) 1998
MkNelly Barbara Dunford Christopher Impact of Credit with Education on Mothers and Their Young Childrenrsquos Nutrition CRECER Credit with Education Program in Bolivia Freedom from Hunger Research Paper No 5 Davis (CA) 1999
Morduch Jonathan The Microfinance Promise in Journal of Economic Literature Vol 37 (1999b) No 4 pp 1569-1614
Neus Werner Einfuumlhrung in die Betriebswirtschaftslehre Tuumlbingen 1998
Otero Maria Bringing Development Back into Microfinance Journal of Microfinance Vol 1 (1999) No 1 pp 8-19
Panjaitan-Drioadisuryo Rosintan D M Cloud Kathleen Gender self-employment and microcredit programs An Indonesian case study in The Quarterly Review of Economics and Finance Vol 39 (1999) pp 769ndash779
Perkins Dwight H et al Economics of Development 5th edition New York London 2001
Pitt Mark M Khandker Shahidur R Credit Programs for the Poor and the Health Status of Children in Rural Bangladesh in International Economic Review Vol 44 (2003) No 1 pp 87-118
Raiffeisen Friedrich W The Credit Unions 8th edition Neuwied 1966
Rhyne Elizabeth The Yin and Yang of Microfinance Reaching the Poor and Sustainability in The MicroBanking Bulletin Issue No 2 (1998) pp 6-9
Richardson David C Unorthodox Microfinance The Seven Doctrines of Success in The MicroBanking Bulletin Issue No 4 (2000) pp 3-7
Robinson Marguerite S The Microfinance Revolution Sustainable Finance for the Poor Washington DC 2001
Robinson Marguerite S The Microfinance Revolution Volume 2 Lessons from Indonesia Washington DC 2002
Rosenberg Richard Microcredit Interest Rates Consultative Group to assist the Poorest Occasional Paper No 1 revised November 2002 Washington DC 2002
70
Roth Michael Steinwand Dirk Mikrofinanz Weltweites Erfolgsmodell nur nicht inDeutschland Zur Uumlbertragbarkeit der Erfahrungen aus Entwicklungslaumlndern auf Deutschland Deutsche Gesellschaft fuumlr Technische Zusammenarbeit (ed) Eschborn2004
Schmidt Reinhard H Tschach Ingo Microfinance as a Nexus of Incentives Finance and Accounting Working Paper No 87A Frankfurt 2001
Schreiner Mark A Framework for the Analysis of the Performance and Sustainability of Subsidized Microfinance Organizations with Application to Banco Sol of Bolivia and Grameen Bank of Bangladesh unpublished PhD dissertation Columbus (O) 1997
Seibel Hans D Recent Developments in Microfinance Development Research Center Working Paper No 1998-5 Cologne 1998
Seibel Hans D History matters in microfinance in Small Enterprise Development ndashAn International Journal of Microfinance and Business Development Vol 14 (2003a) No 2 pp 10-12
Seibel Hans D Schmidt Petra How an Agricultural Development Bank Revolutionized Rural Finance The Case of Bank Rakyat Indonesia International Fund for Agricultural Development Rural Finance Working Paper B 5 Rome 2000
Sen Amartya Oumlkonomie fuumlr den Menschen ndash Wege zu Gerechtigkeit und Solidaritaumlt in der Marktwirtschaft Muumlnchen Wien 2000
Serageldin Ismail The View of the Chair in Consultative Group to Assist the Poorest Newsletter Issue No1 (1996) pp 1 11-12
Soros George Die Krise des globalen Kapitalismus Offene Gesellschaft in Gefahr Berlin 1998
Staschen Stefan Regulation and Supervision of Microfinance Institutions State of Knowledge Deutsche Gesellschaft fuumlr Technische Zusammenarbeit (ed) Eschborn 1999
Steinwand Dirk The Alchemy of Microfinance The Evolution of the IndonesianPeoples Credit Banks (BPR) to 1999 and a Contemporary Analysis Berlin 2001
Stiglitz Joseph E Peer Monitoring and Credit Markets in The World Bank Economic Review Vol 4 (1990) No 3 pp 351-366
Stiglitz Joseph E Weiss Andrew Credit Rationing in Markets with Imperfect Information in The American Economic Review Vol 71 (1981) No 3 pp 393-410
Tschach Ingo Theorie der Entwicklungsfinanzierung Mit Kleinkreditprogrammen Kredit- und Arbeitsmarktsegmentierung uumlberwinden Frankfurt 2000
UNDP Human Development Report 2004 New York 2004
71
UNFPA state of the world population 2004 New York 2004
UNICEF The State of the Worldrsquos Children 2002 NewYork Geneva 2002
Varley Robert C G Financial Services and Environmental Health Household Credit for Water and Sanitation Environmental Health Project Applied Study No 2 Washington DC 1995
Volkery Carsten Kampf um Straszligenhaumlndler in Die Zeit Nr 23 published May 27th
2004 p 33
Wardhana Ali Introduction in The Microfinance Revolution ndash Sustainable Finance for the Poor Washington DC 2001 pp XVII-XXVII
Woodworth Warner Woller Gary Greetings from the Editors Journal of Microfinance Vol 1 (1999) No 1 p 6
The World Bank Group World Development Indicators 2004 Washington DC 2004
Worldwatch Institute (2002) Vital Signs 2002 New York London 2002
Wimmer Nancy Barua Dipal Less is more Microfinance for solar energy in rural areas in Renewable Energy World Review Issue 2004-2005 Vol 7 (2004) No4 pp 170-179
Yunus Muhammad Grameen Bank II ndash Designed to Open new Possibilities Dhaka 2002
Yunus Muhammad Grameen ndash Eine Bank fuumlr die Armen dieser Welt Muumlnchen 1998a
Internet References
Abishek Lal (nd) An Overview of Microfinance and Environmental Management [http wwwgdrcorgicmenvironabhishekhtml] (availability date October 5 2004)
ACCION (nd) our history [httpwwwaccionorgabout_our_historyasp] (availability date October 5 2004)
ACCION (nd) key statistics [httpwwwaccionorgabout_key_statsasp] (availability date October 5 2004)
Ahmad Zulfiqar (nd) Forms of Regional Cooperation in Microfinance in South Asia [httpwwwbwtporgarcmpakistanIV_News_and_EventsBWTPworkshopZulfiqar20Ahmad20paper20(BWTP-PMN2029Jan04)pdf (availability date October 6 2004)
72
Ahmed Salehuddin (2003) Foreword [httpwwwpksf-bdorgaprm_summit_brochure htm] (availability date September 30 2004)
Annan Kofi (2002) Statement at The Microcredit Summit +5 [httpwww microcreditsummitorgenews2003-03_sp_chowdhuryhtml) (availability date October 5 2004)
Barnes Carolyn (2001) Microfinance Program Clients and Impact An Assessment of Zambuko Trust Zimbabwe [httpwwwmicrofinancegatewayorgfiles18553_Barnes_Zambuko_Trust_2001pdf] (availability date October 5 2004)
Barnes Carolyn Gaile Gary Kibombo Richard (2001) The Impact of Three Microfinance Programs in Uganda [httpwwwmicrofinancegatewayorgfiles2935_Barnes_2001pdf] (availability date October 5 2004)
Barua Dipal (2004) Success of Grameen Shakti in the Field of Renewable Energy Sector in Bangladesh [httpwwwrenewables2004depptPresentation1-SessionVA(14-1530h)-Baruapdf] (availability date September 30 2004)
Bhatt Ela (1997) In 1975 [httpwwwmicrocreditsummitorgdeclarationhtm] (availability date September 30 2004)
BlueOrchard (2004a) Microfinance [httpwwwblueorchardchenmicrofinance_institutions asp] (availability date October 5 2004)
BlueOrchard (2004b) January 2004 Newsletter [httpwwwblueorchardchmedialibrarywebsitenewsletter_jan_2004pdf] (availability date October 5 2004)
Brynjolfsson John (2004) John Brynjolfsson Discusses Recent Trends in TIPS Issuance [httpwwwpimcocomLeftNavPIMCO+Spotlight2004Spotlight_2_04htm] (availability date October 5 2004)
CGAP (2003) Report to the Board of Executive Directors [httpwww-wdsworldbankorgservletWDSContentServerWDSPIB20031208000012009_20031208101736RenderedPDF27441pdf] (availability date October 5 2004)
Chen Shaohua Ravallion Martin (2004) How have the worldrsquos poorest fared since the early 1980s [httpwwwworldbankorgresearchpovmonitorMartinPapersHow_have_the_poorest_fared_since_the_early_1980spdf] (availability date October 5 2004)
Cheston Susy Kuhn Lisa (2002) Empowering Women through Microfinance[httpwwwmicrofinancegatewayorgfiles3240_Cheston_2002doc] (availability date October 5 2004)
Christen Robert P et al (1995) Maximizing the Outreach of Microenterprise FinanceAn Analysis of Successful Microfinance Programs [httpwwwdecorgpdf_docsPNABS519 pdf] (availability date October 5 2004)
73
CIA (2004) The World Factbook [httpwwwciagovciapublicationsfactbook] (availability date October 5 2004)
Clear Profit (2004) Microfinance Bond Record May Double [httpwwwclear-profitcomissuescpsep04txt] (availability date September 30 2004)
Daley-Harris Sam (2003) State of the Microcredit Summit Campaign Report 2003 [httpwwwmicrocreditsummitorgpubsreportssocr2003SOCR03-E[txt]pdf] (availability date September 30 2004)
Dominiceacute Robert (2004) Interview in Microfinance Bond Record May Double [httpwwwclear-profitcomissuescpsep04txt] (availability date September 30 2004)
Donahue Jill Kabbucho Kamau Osinde Sylvia (2001) HIVAIDSmdashResponding To A Silent Economic Crisis Among Microfinance Clients In Kenya and Uganda [httpwwwmicrosave-africacomget_fileaspdownload_id=541] (availability date September 30 2004)
Donahue Jill Sussman Linda (1999) Building a Multi-Sectoral Response Follow-Up Assessment of Programming for Children and Families Affected by HIVAids in Kenya [httpwwwdecorgpdf_docspnacg778pdf] (availability date September 30 2004)
The Economist (1998) [httpwwweconomistcomdisplaystorycfmstory_id=S2629H3C28Q13F240A] (availability date September 30 2004)
Finca (nd) Introduction [httpvillagebankingorgwhereindexphp3] (availability date September 30 2004)
Fischer Stanley (2003) Statement at The Asia Society and Womens World BankingAnnual Microfinance Conference [httpwwwiiecomfischerpdffischer051303pdf] (availability date September 30 2004)
Friedman Milton (nd) Samuha [httpwwwsamuhaorgm-1htm] availability date September 30 2004)
FXTOP (2004) Historical Exchange Rates [httpfxtopcomdehistoratesphp3] (availability date September 30 2004)
Gibbons David Meehan Jennifer W (2002) Financing Microfinance for Poverty Reduction [httpwwwmicrocreditsummitorgpapersfinancing_finalpdf] (availability date September 30 2004)
Grameen Bank (2004) Grameen Bank At a Glance [httpwwwgrameen-infoorgbankcdshtml] (availability date September 30 2004)
Grameen Trust (nd) Grameen Bank Replication Program [httpwwwgrameen-infoorggrameengtrustreplicationhtml8721] (availability date September 30 2004)
74
Hossain Farhad (2004) Microfinance in Development [httpwwwvalthelsinkifi staff jkoponenb1104FarhadFeb2304pdf] (availability date October 5 2004)
IMF (2004) Data [httpwwwimforgexternalpubsftweo200402datadbginimcfm] (availability date October 5 2004)
IMI (2004) Investments [httpwwwimi-agcomoverviewindexhtml] (availability date September 30 2004)
IPCC (2001) Summary for Policymakers [httpwwwipccchpubspm22-01pdf] (availability date September 30 2004)
Jansson Tor Wenner Mark (1997) Financial Regulation and its Significance for Microfinance in Latin America and the Caribbean [httpwwwgdrcorgicmgoverniadb-janssonpdf] (availability date October 5 2004)
Ken Daniel Ten Roeun Van (2004) The Cycle of Debt - As Microcredit Institutions Grow Some Question Their Effect on Poverty [httpwwwcamnetcomkhcambodiadaily selected_featurescd-21-02-04htm] (availability date September 30 2004)
Kim Julia (2002) Social Interventions for HIVAIDS - Intervention with Microfinance for AIDS and Gender Equity [httpwwwwitsaczaradarPDF20filesIntervention_monograph_no_picspdfpdf] (availability date September 30 2004)
Llanto Gilberto (nd) Vietnam [httpwwwadborgDocumentsBooksCentral_Banks_MicrofinanceCountry_Studiesvietnampdf] (availability date September 30 2004)
The Microfinance Gateway (nd) Frequently Asked Questions [httpwwwmicrofinance gatewayorgsectionfaq1] (availability date October 5 2004)
Microfinance Rating and Assessment Fund (2004) Qualified Raters [httpwwwmfrating orgmfi_institutionsqualified_ratershtml] (availability date October 5 2004)
Microcredit Summit (1997) Declaration and Plan of Action [httpwwwmicrocreditsummit orgdeclarationhtm] (availability date September 30 2004)
MicroRate (nd) Performance Indicators and Ratios [httpwwwmicroratecomENGLISHsiteRATINGSindicatorshtml] (availability date September 30 2004)
MicroRate (2002) The Finance of Microfinance [httpwwwmicroratecomPDFFinance20of20Microfinancepdf] (availability date September 30 2004)
MicroRate (2004) Adjusted comparison table [httpwwwmicroratecomENGLISHsitePDFAdjusted20Comparison20Table060320engpdf] (availability date October 5 2004)
75
Mix Market (2004) The Mix Market [httpwwwmixmarketorg] (availability date October 5 2004)
Morduch Jonathan (1999b) The Grameen Bank A Financial Reckoning [httpwwwwwsprincetonedu~rpdsmacarthurdownloadsmorduch_grameen_bankpdf] (availability date September 30 2004)
Pallen Dean (1997) Environmental Sourcebook for Micro-Finance Institutions [httpwwwacdi-idagccaINETIMAGESNSFvLUImagesea20summaries$fileSOURC Epdf] (availability date September 30 2004)
Prisma (2002) The Case for Private Capital Market Creation in the Development Field of Microfinance [httpwwwsocialenterprisenetpdfsprivate_capital_marketpdf] (availability date September 30 2004)
Schmidt Reinhard H Zeitinger C-P (1997) Critical Issues in Microbusiness Finance and the Role of Donors No 6 [httpwwwgdrcorgicmmfi-donorpdf] (availability date September 30 2004)
Seibel Hans D (2003b) Commodity finance a commercial proposition Micro- and Mesofinance for Agricultural Commodity Production Processing and Trade [httpwwwuni-koelndeew-fakaef05-20042003-420Commodity20Financepdf] (availability date September 30 2004)
Simanowitz Anton Walter Alice (2002) Ensuring Impact Reaching the Poorest while Building Financially Self-sufficient Institutions and Showing Improvement in the Lives of the Poorest Families [httpwwwidsacukimpactPublicationsWorkingPapersOP3MCSSumdoc] (availability date September 30 2004)
Smith Stephen C Jain Sanjay (1999) Village Banking and Maternal and Child Health Theory and Evidence from Ecuador and Honduras[httphomegwuedu~scsmith healthrevwd801pdf] (availability date September 30 2004)
United Nations (1999) International Year of Microcredit 2005 [httpods-dds-nyunorgdoc UNDOCGENN9976933PDFN9976933 pdfOpenElement] (availability date October 5 2004)
United Nations (2000) United Nations Millennium Declaration [httpods-dds-nyunorgdocUNDOCGENN0055951PDFN0055951pdfOpenElement] (availability date October 5 2004)
US Census Bureau (2004) Total Midyear Population for the World 1950-2050 [httpwwwcensusgovipcwwwworldpophtml] (availability date October 5 2004)
WHO (2004) Making pregnancy safer [httpwwwwhointmediacentrefactsheets fs276en] (availability date September 30 2004)
WHO (2001) Child Health [httpwwwwhointmipfiles2082AAGChildHealthpdf] (availability date September 30 2004)
76
The World Bank Group (nd) Health Nutrition and Population and the Millennium Development Goals [www1worldbankorghnpMDGMDG20-20HNPbookletpdf] (availability date September 30 2004)
Yunus Muhammad (1998) Championing the Right to Credit for Poor Women Around the World [httpaspgrameencom dialoguedialogue34interviewhtml] (availability date September 30 2004)
UNAIDS (2004) [httpwwwunaidsorgbangkok2004GAR2004_pdfUNAIDSGlobalReport2004_enpdf] (availability date September 30 2004)
Ratings
M-Cril (2000) SPANDANA [httpwwwratingfundorgspanishdocsSPANDANA_RatingReportpdf] (availability date October 7 2004)
M-Cril (2001a) BASIX [httpwwwbasixindiacomMcrilasp] (availability date October 7 2004)
M-Cril (2001b) BDB [httpwwwratingfundorgspanishdocsRF_BDBpdf] (availability date October 7 2004)
M-Cril (2001c) SNEHA [httpwwwratingfundorgspanishdocsRF_Sneha-u1pdf] (availability date October 7 2004)
M-Cril (2002a) KCLF [httpwwwratingfundorgdocsRF-KCLF-risk20reportdoc] (availability date October 7 2004)
M-Cril (2002b) NWTF [httpwwwratingfundorgspanishdocsRF_NWTFpdf] (availability date October 7 2004)
M-Cril (2002c) SEEDS [httpwwwratingfundorgspanishdocsRF_SEEDS_2002_Ratingpdf] (availability date October 7 2004)
M-Cril (2002c) Share [httpwwwratingfundorgspanishdocsRF_SHAREpdf] (availability date October 7 2004)
M-Cril (2002d) TSKI [httpwwwratingfundorgspanishdocsRF_Tski_mcrilfinal(-) reportpdf] (availability date October 7 2004)
M-Cril (2003a) ASA [httpwwwratingfundorgdocsASA20updatepdf] (availability date October 7 2004)
M-Cril (2003b) BURO [httpwwwm-crilcomburopdf] (availability date October 7 2004)
M-Cril (2003c) EMT [httpwwwratingfundorgdocsEMTpdf] (availability date October 7 2004)
77
M-Cril (2003d) SKS [httpwwwmixmarketorgendemanddemandshowprofileaspett=25ampshowinfo=adjusted] (availability date October 7 2004)
M-Cril (2003d) TPC [httpwwwratingfundorgdocsTPC_Finalpdf] (availability date October 7 2004)
M-Cril (2004b) UPAP [httpwwwratingfundorgdocsUPAP_2004pdf] (availability date October 7 2004)
Microfinanza (2002a) ACME [httpwwwratingfundorgspanishdocsACME_finalpdf] (availability date October 7 2004)
Microfinanza (2002b) BTFF [httpwwwratingfundorgspanishdocsBTFF_RatingReportpdf] (availability date October 7 2004)
Microfinanza (2002c) BESA [httpwwwratingfundorgspanishdocsBESA_RatingReportpdf] (availability date October 7 2004)
Microfinanza (2002d) CAME [httpwwwratingfundorgdocsEvaluacionCAME(-) Finaldoc] (availability date October 7 2004)
Microfinanza (2002e) RFF [httpwwwratingfundorgdocsRFF20finalpdf] (availability date October 7 2004)
Microfinanza (2002f) PSHM [httpwwwratingfundorgspanishdocsPSHM_Reportpdf] (availability date October 7 2004)
Microfinanza (2003) CAJCA [httpwwwratingfundorgdocsCalificacion_Jardin_Azuayo_ratingpdf] (availability date October 7 2004)
Microserve (2003) ENDA [httpwwwmixmarketorgendemanddemandshowprofileaspett=865ampshowinfo=adjusted] (availability date October 7 2004)
Planet Rating (2002a) FONDEP [httpwwwmfratingorgRatingscompleted_ratingshtml] (availability date October 7 2004)
Planet Rating (2002b) PRIZMA [httpwwwmixmarketorgendemanddemandshowprofileaspett=111ampshowinfo=adjusted] (availability date October 7 2004)
Planet Rating (2002c) SWS [httpwwwratingfundorgspanishdocsSWC_reportpdf] (availability date October 7 2004)
Planet Rating (2002d) ZAKOURA [httpwwwratingfundorgspanishdocsRF_Zakourapdf] (availability date October 7 2004)
Planet Rating (2003a) AMSSF [httpwwwratingfundorgdocsPlanetRating_AMSSF_010803pdf] (availability date October 7 2004)
Planet Rating (2003b) FOCCAS [httpwwwratingfundorgdocsPlanetRatingFOCCAS120803pdf] (availability date October 7 2004)
78
Planet Rating (2003c) PADME [httpwwwmfratingorgdocsPlaNetRatingPADME070302_Englishpdf] (availability date October 7 2004)
Planet Rating (2003d) PAPME [httpwwwmfratingorgdocsPAPME_PlanetRating080903pdf] (availability date October 7 2004)
Planet Rating (2003e) VITAL FINANCE [httpwwwmfratingorgdocsVital20Finance_Sept202003pdf] (availability date October 7 2004)
Planet Rating (2004a) ABA [httpwwwratingfundorgdocsABA_April202004pdf] (availability date October 7 2004)
Planet Rating (2004b) ACEP [httpwwwmfratingorgdocsACEPSeacuteneacutegal_2004pdf] (availability date October 7 2004)
Planet Rating (2004c) AGROINVEST [httpwwwratingfundorgdocsAgroInvest_June202004pdf] (availability date October 7 2004)
Planet Rating (2004d) ASBA [httpwwwratingfundorgdocsASBA_April202004pdf] (availability date October 7 2004)
Planet Rating (2004e) DBACD [httpwwwratingfundorgdocsDBACD_April202004pdf] (availability date October 7 2004)
Planet Rating (2004f) FINADEV [httpwwwmfratingorgdocsFinadev_2004pdf] (availability date October 7 2004)
Planet Rating (2004g) MI-BOSPO [httpwwwratingfundorgdocsMIBOSPO_160404pdf] (availability date October 7 2004)
Planet Rating (2004h) SBACD [httpwwwratingfundorgdocsSBACD_PlanetRating300604pdf] (availability date October 7 2004)
Other Sources
Interview Shaw Newaz Deputy General Manager of the Grameen Bank October 30th
2003
Hodson Charles (2001) Your Business Your World Jim Boulden CNN (ed) Dhaka 2001
