CHAPTER ONE
INTRODUCTION
1.1 Background to the Study
Economic growth and development processes affect and are
affected by migration of people. In traditional viewpoint, people
migrate when they are both pushed by lack of opportunities at home
and pulled by the hope of economic gains elsewhere. Thus, the hope
that migration will help associate migrants more closely with
available economic opportunities, employment and services elsewhere
is a major incentive for migration. Arguably, migration is
necessarily a part of a family strategy to raise income, obtain new
funds for investment, and insure against risks. It is not
surprising therefore that thousands of African workers with
relevant skill endowments leave their home country yearly to pursue
better economic prospects within or outside Africa. However,
migration of skilled workers could potentially hurt the sending
countries if not well managed by appropriate policies.
As populations in advanced countries continue to age, shortage
of labour in sectors such as health care continue to attract
relatively cheap but qualified labour from these developing
countries of Africa. Migration of skilled workers in this sense
contributes to the economic growth of receiving countries by
responding to real labour needs in receiving countries. In
addition, migrant workers help fulfill unmet labour requirements in
many lower-pay and low-skill jobs such as those associated with
domestic and agricultural work in developed countries. Migrants
also contribute to the scientific and technological development of
host countries. These factors partly provide the necessary impetus
for international migration flows to continue to increase, and for
the process of globalization and the interdependence of nations to
continue to deepen.
While the positive aspects of migration can lead to economic
gains for the receiving countries, it can also lead to “unintended
consequences” in both the sending and receiving countries. Some of
these consequences include an outright deprivation of vital human
resources in sending countries, and by implication the adverse
impact of migration of skilled workers on the brain drain
phenomenon in sending countries. Such deprivation of vital human
resources is rather very alarming given that the United Nations
predicts that the net number of migrants from developing to
developed countries will increase by 2.2 million people annually,
from 191 million or 3 per cent of the world population in 2005
(United Nations, 2004). This problem is even further compounded
when the long gestation period for training skilled workers is
taken into account by the migrant sending countries of Africa.
There are also the issues of cultural conflicts in receiving
countries, human trafficking, economic exploitation of migrants,
sending country dependency patterns, delayed economic growth in
sending countries, etc. In this case, a vicious cycle is easily
perpetuated.
The emigration of people with scarce skills, such as
entrepreneurs, scientists, technicians and health professionals
reduces both the stock of human capital and the overall labour
productivity of developing countries. However, if these highly
skilled migrants return, they bring with them experience, knowledge
contacts and capital, which have a positive impact on development.
Thus, gains and losses from migration depend on whether it is
temporary or permanent (Rena, 2008). In essence, African countries
stand to benefit from migration through the African
Diaspora[footnoteRef:2] expertise, knowledge, technology,
professional capacity building and a great potential for trade and
investment links. The migrant sending countries of Africa can also
benefit economically from migration through the inflow of workers’
remittances. Given these possibilities, migration is increasingly
being regarded as an important instrument for growth and
development in Sub-Saharan Africa (SSA). [2: The African Diaspora
consists of peoples of African origin that are living outside the
continent, irrespective of their citizenship and nationality.]
Migrant remittances seem to have contributed to poverty
reduction throughout Sub-Saharan Africa, leading to increased
household investments in education, entrepreneurship and health. At
the household level, remittances are spent primarily on general
consumption items in local communities which can contribute to
local economies by supporting small businesses. This in general,
has its employment generation implications in these critical
services sectors. In addition to supporting domestic consumption,
remittances can also promote investments in real assets including
building schools and clinics. Remittances flow is directly to
households and they are widely distributed in small amounts
throughout the economy. This makes remittances capable of having a
much broader effect on home country economies than either FDI or
official development assistance.
Official data on remittances inflow to Sub-Saharan Africa reveal
that, the flow of remittances to the region has been far more
stable than official aid flows and foreign direct investment (FDI).
Besides, remittances do not decline even in conditions of
instability and poor governance. Hence, remittance flows represent
one of the least volatile sources of foreign exchange earnings.
They are also more evenly spread among developing countries than
capital flows. Workers’ remittances represent one of the largest
private sources of external finance for developing countries; thus,
remittances are the main transmitter of migration’s development
benefits to sending country economies. Workers’ remittances are
inter-household transfer of money within or across national
boundaries. According to Reinke and Patterson (2005), workers’
remittances cover current transfers by migrants who are employed in
new economies and are considered residents there.
Workers’ remittances flow has steadily increased since the mid
1980s. Officially recorded remittances were an estimated US$206
billion in 2006, compared to US$19.6 billion in 1985 (World
Development Indicators 2006). Remittances have been the second most
important source of external finance for developing countries,
being twice the size of Official Development Aid (ODA) and almost
as large as Foreign Direct Investment (FDI). World Bank (2009)
reports that recorded remittances to developing countries in 2008
were estimated to have reached US$305 billion. This is equivalent
to nearly two percent of aggregate developing country GDP and well
over half of estimated FDI inflows (US$490 billion). The 2008
estimated remittances to developing countries are over twice as
large as official development aid of US$119 billion received by
developing countries.
In absolute terms, big developing countries like India, China,
Mexico and the Philippines receive the largest shares of
remittances in the world. However, in relative terms, small and
poor countries tend to be much more dependent on remittances. For
many countries with large Diasporas, workers’ remittances often
amount to at least, 15% of Gross Domestic Product (GDP). Tonga for
example had a share of remittances to GDP of 39% and Haiti and
Lesotho of 27% in 2003. Actual figures are even higher than this,
because unrecorded remittances in cash or kind are often brought by
migrants themselves or sent through third parties, and are not
declared when entering the country.
Remittance receipt in relative terms is expressed as a
percentage of GDP for the top 25 recipients in SSA in 2008 and is
reported in figure 1.1.
Figure 1.1: Sub-Saharan Africa: top 25 recipients of remittances
in 2008
Source: International Monetary Fund (IMF) (2009). Regional
Economic Outlook: Sub-Saharan Africa.
Figure 1.1 shows that Lesotho tops remittance recipients in SSA
with remittance inflow amounting to about 27.5 percent of GDP. This
is followed closely by Comoros with about 25 percent of GDP.
Mozambique and Cote d’Ivoire are the least in terms of relative
importance of remittances with about 1 percent of GDP in each of
the countries.
When considered as a share of GDP, workers’ remittances can in
fact be conveniently regarded as a vital source of finance for many
developing countries. These flows contribute to the poverty
reduction process by enhancing the living standards of the
beneficiaries. Workers’ remittances can also contribute to the
poverty reduction process through the multiplier effects of flows
which create additional demand, employment and income. Page and
Adams (2003) estimate that a 10% increase of remittances per capita
would lead to a decline of the poverty head count by 3.5%, due to
multiplier effects on GDP growth. Despite their positive impact on
poverty rates, the way in which remittances contribute to economic
growth and development is still an open question. Even if we take
account of multiplier effects, poverty reduction through
remittances is, in principle, a one-time effect. From a development
perspective the question must be whether remittances have, beyond
their immediate impact on poverty, an effect on the long-term
growth of a country.
Most remittances are made in the form of cash rather than as
goods. Therefore, remittances are financial flows made up of
private and unilateral transfers of money by a migrant worker
resident in a foreign country (host country) to a person (most
often a family member of the migrant) living in the migrant’s
country of origin (home country). In principle, there are three
ways of measuring remittance inflows in countries. According to
Addison (2004), the first approach is the balance of payments (BOP)
estimates. Other methodologies include micro or household surveys
of recipients of such flows e.g. inference from the Ghana Living
Standard Survey (GLSS). The third method is through banks or
financial institutions in origin countries i.e. focusing on
resource transfer institutions.
In terms of relative accuracy and level of coverage, the micro
or household surveys of recipients approach is likely to be the
least. The obvious explanation will be the problems of
non-disclosure by respondents and general costs associated with
micro or household surveys respectively. The BOP approach tends to
be most reliable for macro studies since aggregated data are
usually compiled and reported by the various monetary authorities
under this approach. Thus, the size of the remittances flows
employed in this study are based on BOP estimates reported by the
various central banks of the IMF member countries. For obvious
reasons, the cross–country nature of this study demands that
relevant data are drawn from a common source to allow for
uniformity of measurement standard as well as easy comparism. The
World Bank Africa Development Indicators satisfactorily meets these
requirements.
The importance of remittances for some countries in the SSA
region can be best illustrated by expressing them as a ratio to
GDP, while in others the absolute total of per-capita value of
remittances flows are more revealing. Remittance flows is widely
believed to be much more sustainable as a source of development
finance to many countries around the world. Two major forces are
expected to ensure the growth and sustenance of these flows:
Globalization and the aging populations (Olayiwola et al, 2008 and
Olayiwola, 2010). Globalization and the aging of developed economy
populations will ensure that demand for migrant workers remains
robust for years to come. Consequently, the volume of remittances
will most likely continue to grow, since migrants will continue to
support the elderly and other dependants in their countries of
origin. However, challenges remain in determining how best to
channel the flow of remittances through formal financial
institutions to promote economic growth and development in sending
countries (Chami, Barajas, Cosimano, Fullenkamp, Gapen, and
Montiel, 2008). This study empirically examines this challenge, and
sheds more light on several possible options open to some selected
SSA countries in the effort to harness maximum societal benefits
from workers’ remittances inflow.
1.2 Statement of the Problem
The major research issue in this study bothers on the
determination of the nature of relationship between remittances and
economic growth in SSA. There is so far no conclusive answer in the
literature to the question of whether workers’ remittances
constitute at the aggregate level, a vital source of development
finance to the developing countries of the Sub-Saharan African
region.
The literature on the potential developmental impact of
remittances in an economy is quite vast but mixed and can be
divided into two separate strands. One strand takes a microeconomic
approach and examines the causes and uses of remittances using
household surveys and aggregate data (Taylor, 1999). The other
strand focuses on the effects of remittances and uses macroeconomic
models (that are not based on individual maximizing behavior) to
estimate the impact of remittances. While the micro dimension of
remittances is often closely associated with the “dependency
framework”, the macro dimension is often associated with the
“developmental framework”.
In other words, workers’ remittances seen from the perspective
of individual to individual transfers often connote a relationship
between two parties that allows for regular financial support from
one party. Such support is often to meet the consumption, medical
and/or education needs of the dependant party. However, when
workers’ remittances is taken from the perspective of group to
group transfers, it connotes an arrangement that allows for group
or societal support often to meet the developmental needs of the
benefiting party. The likely negative impact of remittances
associated with the dependency framework is that it may engender a
culture of dependency among the economically active population that
benefit from remittances flows.
Workers’ remittances may on the other hand generate a number of
important positive contributions to economic growth and
development. In particular, remittances tend to reduce poverty and
inequality in recipient countries, as well as increase aggregate
investment and growth. Moreover, when perceived to behave counter –
cyclically, remittances may significantly reduce growth volatility
and help countries adjust to external and macroeconomic policy
shocks. At the microeconomic level, remittances allow poor
recipient households to increase their savings, spend more on
consumer durables and human capital, and improve children’s health
and educational outcomes. Consequently, the net impact of workers’
remittances is that it is beneficial to the recipient party if
properly managed.
Workers’ remittances are important source of finance and foreign
exchange for many African countries. They help the countries to
stabilize irregular incomes and also assist communities to build
human and social capital. Remittances receivers in many cases are
typically or financially better off than their peers who lack this
source of income (Sander and Maimbo, 2003). In this sense,
remittances are private and family funds, which may be construed as
constituting some form of familial support that does not create any
future liabilities such as debt servicing or profit transfer for
the recipient.
These transfers have been a critical means of financial support
to many poor families in developing economies for generations and
have helped them significantly in confronting the plague of
poverty. Thus, remittances reduce the problem of income inequality
in many societies. Within this perspective, there are at least four
identifiable motives for remittances in the literature; these
include (i) altruism (ii) self interest (iii) implicit family
contract: - loan repayment, and (iv) implicit family contract: -
co-insurance (Solimano, 2003). At the macroeconomic level,
remittances have a substantial positive effect on the balance of
payments and on foreign exchange revenues. This however may not be
true for net remittances. More importantly, remittance inflows,
unlike oil windfalls do not weaken institutional capacity. This is
because remittances are widely dispersed with the great bulk
allocated in small amounts to the recipients while the governments
are precluded from playing the role of “middlemen”.
The role of workers’ remittances in economic growth and
development continues to be an important issue for researchers and
policymakers. One strand of studies relates to the understanding of
the determinants and factors that shape the transfer of funds by
migrants. It also explains the amount, frequency, volume, and
duration of such transfers (Lee, Bokkerink, Smallwood, and
Hermandez-Coss, 2005). The other strand concentrates on the causes
and or uses of remittances while only a few made efforts to
directly address the macroeconomic effects of remittance transfers
(Chami, Fullenkamp, and Jahjah , 2003). This limited research
effort did not give Africa, and particularly SSA, much attention on
the issue of remittances (Sander 2003). This development is
traceable to the relatively low share of remittances going to the
African continent (15 percent of total flows to developing
countries) and the even lower share going to Sub-Saharan Africa (5
percent), and by the relatively small number of international
migrants from Africa, as well as their greater dispersion, compared
to migrants from other developing regions (sander and Maimbo,
2003).
Workers’ remittances to Africa are nevertheless an important
financial flow—with perhaps, significant developmental effects. As
shown in figure 1.1, workers’ remittance as a percentage of GDP in
many SSA countries is quite significant averaging about 8 percent
for these countries. Thus, these realities make a study on the
subject worth embarking on. Moreover, their level is probably much
higher than official data indicates (Sander and Maimbo, 2003).
Anecdotal reports support the fact that many transactions go
unrecorded or unreported, this in large part is because financial
systems and services are weak in much of Africa. The weakness of
financial systems brings about the problem of remittance leakages
as it creates obstacles for the efficient transfer of remittances
through formal money transfer services and limits the potential of
remittances to contribute to development (Gupta, Pattilo and Wagh,
2007). The weak financial systems and services in Africa has been a
major stimulus for the sustenance of the informal transfer systems
which includes personal carriage of cash or goods by migrants,
their relatives, their friends, or trusted agents. Other informal
services operate as a side business to an import-export operation,
retail shop, or currency dealership. Most of them keep little paper
or electronic documentation. Transactions are communicated by
phone, fax, or e-mail to a counterpart who will make the payment
(El-Qorchi, Maimbo, and Wilson, 2002). The best known of the
informal services are hawala and hundi, which operate in a similar
fashion. The terms can be used interchangeably, but hawala is
typically used in the context of the Middle East and Arab countries
and their migrant populations, whereas hundi is usually connected
with South Asia especially Bangladesh (Sander and Maimbo,
2003).
Workers’ remittances as a potential source of external
development finance for many developing countries provide a much
more stable source of foreign exchange than other foreign currency
flows to developing countries. This is especially relevant to SSA,
where official aid flows have fluctuated over the years. The
increasing attention is also due to the growing volume of official
financial remittances to low income countries and their potential
contribution to the development of the receiving regions. But
despite the large interest in remittances, their role in economic
growth and development remains unclear. First, it is extremely
difficult to gather accurate data on remittances. This is because
many remittances are not channeled through the payment system and
are left outside the official statistics. In addition, most studies
on workers’ remittances flows to Africa tend to be on a single
country or one migrant group at a time and this does not allow for
any form of general inference.
At the macro level, the economic growth and developmental impact
of remittances on the economy attracts two opposing views in the
literature. Within the first perspective, remittances often provide
a significant source of foreign currency, increase national income,
finance imports and contribute to the balance of payments.
Remittances also contributed to the expansion of wire transfer and
courier companies as well as money exchanges (Russell 1986; Keely
and Tran 1989; Massey 1992; Taylor et al. 1996a and 1996b). Other
studies with contrary views believe that remittances decrease the
likelihood of an improved economy. Their argument is that, the
inflow of funds can be deceptive if it creates dependence among the
recipients, encourages the continued migration of the working age
population and decreases the likelihood of investment by the
government or foreign investors because of an unreliable workforce
(Pastor and Rogers 1985; Pastor 1989). Another possible negative
effect of remittances is the possibility that they produce a “Dutch
disease” effect. For countries that receive important sums of
remittances, there is a tendency for the real exchange rate to
appreciate, penalizing non-traditional exports and hampering the
development of the tradable goods sector (Solimano, 2003).
Remittances can also be countercyclical or procyclical with the
GDP in recipient countries. On the one hand, remittances motivated
largely by altruism, are argued to have a tendency to move
counter-cyclically with the GDP in recipient countries. The
reasoning here is that migrant workers are expected to increase
their support to family members during down cycles of economic
activity back home. This expectedly will compensate the remittances
beneficiaries for lost family income due to unemployment or other
crisis-induced reasons. However, remittances conceived as
procyclical with output in recipient countries may act as a
destabilizing force. In this case, procyclical remittances increase
the capacity of swings in remittance flows to produce additional
fluctuations in output or current account balances, with serious
macroeconomic effects (Sayan, 2004). It is quite obvious from the
foregoing that, despite the increasing importance of remittances in
total international capital flows, the direct or indirect
relationship between remittances and economic growth and
development has not been adequately studied.
This study sheds additional insight into the inconclusive debate
on the remittance – growth nexus by exploring the macroeconomic
impact of remittances on economic growth and development in some
selected SSA countries. It does this within the extended
neoclassical growth framework using a balanced panel data set
spanning from 2000 to 2007 for twenty one SSA countries.
1.3 Research Questions
Given the various issues relating to the growth and
developmental role of workers’ remittances flows to SSA, a number
of research questions arise as follows:
(i) What are the roles or contributions of remittances to output
growth within the SSA?
(ii) What is the contribution of remittances to private
investment?
(iii) To what extent do remittances contribute to foreign trade
balance?
(iv) What are the various policy options that can be adopted to
better manage the macroeconomic effects of remittances in SSA?
Any research effort that provides satisfactory answers or at the
least, shed some meaningful insights into the above questions
represents a valuable guide to the understanding of the economic
growth and development role of workers’ remittances inflows to SSA.
Therefore, in this empirical study, no effort is spared in
providing meaningful answers to the above questions.
1.4 Objectives of the Study
The overall objective of this study is to investigate the
economic growth and developmental role of workers’ remittances in
selected Sub-Saharan African (SSA) countries. The specific
objectives are to:
(i) Determine the contributions of remittances to output growth
in SSA
(ii) Analyze the importance of remittances to the level of
domestic investment in SSA
(iii) Investigate the effects of remittances on trade balance in
SSA.
1.5 Statement of Research Hypotheses
The following testable hypotheses which are implied in the
research questions are considered appropriate for this study and
are therefore subjected to empirical investigation. These
hypotheses are stated in their null context as follows:
1. Workers’ remittances do not significantly promote economic
growth in selected SSA countries.
2. Workers’ remittances do not significantly impact positively
on domestic investment in selected SSA countries.
3. Workers’ remittances inflow has no significant impact on
foreign trade balance in the selected SSA countries.
1.6 Scope of the Study
The study employs data covering a period of eight years
(2000-2007). The choice of this period is explained by the
availability of data across the selected countries as well as the
fact of a dramatic rise in recorded remittance flows to the region
over this period. The study is limited to the twenty one SSA
countries that reported inward remittances receipts for the period-
2000 and 2007. These countries are:
Benin, Botswana, Cameroon, Cape Verde, Djibouti, Ethiopia,
Gabon, Ghana, Guinea, Kenya, Lesotho, Malawi, Mali, Namibia, Niger,
Nigeria, Senegal, Seychelles, Sierra Leone, Togo, Uganda.
Remittance flows will be restricted to inter-household
unilateral and unrequited transfer of cash earnings, meaning that
such transfer is void of any form of quid pro quo terms, across
national boundaries only. The implication is that remittances in
forms of material transfers by migrant workers to their home
countries, compensation of employees, or unrequited inter-household
cash transfers within each economy under investigation, are not
covered in this study. It is important to clarify here that the
study is restricted to the macroeconomic impact of remittances on
the receiving economies and not on their microeconomic impact.
1.7 Justification of the Study
A common theme motivating much of the research on remittances is
the better understanding of their role as promoter of economic
growth and development. This also includes the question of how
remittances flows can be channeled into productive investments by
appropriate policies. Black (2003) noted that despite the glaring
evidence on the extent of the flow of remittances, gaps still
remain in the understanding of how remittances are or can be used
to promote growth and development, especially given that existing
policy incentives are not generally considered as having been very
effective in channeling remittances towards economic growth. The
study is considered important to SSA countries in several ways as
follows: the SSA region is widely regarded least among remittances
recipients in the world. A good knowledge of the growth and
developmental role of remittances will help encourage regional and
national policies that will further boost the inflow of this very
important source of foreign exchange to the region. In other words,
this study helps policymakers in the various SSA countries to
better understand the phenomenon of remittances flows to the region
and how best to manipulate related policies to optimize these
flows. This hopefully will help loosen the foreign exchange
constraint that has so far weakened the capacity of most of these
African economies to operate effectively in the international
market.
The literature on remittances is replete with inadequacies
regarding an appropriate measure of remittances. Many researchers
make use of an aggregate measure of remittances and this at best
exhibit characteristics that are different from those which they
intend to study. According to Chami et al (2008), the category
‘workers’ remittances’ in the balance of payments best represents
what economists have in mind when modeling remittances. The
properties of this series differ significantly from those of
‘employee compensation’ and ‘migrants’ transfers’, so combining
these three items into a single measure of remittances, as is
common practice in the literature, can lead to invalid conclusions
about the properties of remittances and, in turn, suboptimal policy
decisions. Again, effort is made in this study to correct this
inadequacy by isolating data on workers’ remittances from the
aggregate measure commonly used in the remittances literature.
The resource-gap syndrome is more pronounced in SSA countries
than anywhere else in the world. As a consequence, the region is
often not able to meet up with its foreign exchange requirements
for imports. A stable remittances inflow can reasonably fill the
foreign exchange gap in SSA. There is however the need to properly
channel remittances into growth and development. The overall
understanding of remittances and economic development is inadequate
given the importance of this economic phenomenon. The debate on the
growth and development impact of migrants’ remittances, which is
based largely on evidence from proximate economies, is rather
inconclusive. Sub-Saharan Africa has unfortunately been grossly
under-researched in this respect. Situating the SSA countries
properly on the growth and development impact of remittance inflows
remains a major gap in the literature. This study is an attempt to
further close this identified gap. The study therefore is a
contribution to the inconclusive debate on the growth and
developmental role of workers’ remittances and it provides
empirical evidence based on data from Sub-Saharan Africa which
hopefully will further clarify the issues.
1.8 Structure of the Study
The study is divided into six chapters. The first chapter deals
with general introduction, and the second chapter focuses on
patterns of economic growth, investment, foreign trade and
remittances in SSA. The third chapter is the review of the
theoretical literature, the empirical literature, and
methodological issues in the literature. The fourth chapter
comprises of the theoretical framework and methodology. The fifth
chapter is model estimation and analysis of results. Chapter six
comprises of the summary of findings, recommendations, conclusion,
as well as limitations of the study and suggestions for further
research.
CHAPTER TWO
PATTERNS AND TRENDS OF REMITTANCES AND ECONOMIC GROWTH IN
SSA
2.0 Introduction
This chapter provides background information on patterns and
trend of economic growth, investment, trade and remittance flows to
SSA. The focus here is to determine the existence of any pattern,
distribution and trend in the identified variables that
characterize the SSA region. Such characterization helps in the
identification of necessary links among the variables of interest
within the SSA economies. The chapter is also aimed at helping the
reader form expectations on the various relationships among the
variables of choice and across the study group.
2.1 Patterns and Trends of Economic Growth in SSA
Recent trends in growth rates in SSA suggest that a large
majority of the countries in the region experienced significant
improvements in their overall growth performance since year 2000.
However, growth performance across the SSA countries selected for
this study exhibits substantial disparities over this period.
Economic growth rates for each of the sampled countries and for
each of the years within the scope of this study are presented in
table 2.1. These values are compared using the average values for
SSA as a benchmark value for each year.
Table 2.1: GDP Growth Rate in Selected SSA Countries
Country/Year
2000
2001
2002
2003
2004
2005
2006
2007
SSA
4
4
3
4
6
6
6
6
Benin
6
5
5
4
3
3
4
5
Percent of SSA (%)
150
125
167
100
50
50
67
83
Botswana
8
5
3
6
7
5
3
4
Percent of SSA (%)
200
125
100
150
117
83
50
67
Cameroon
4
5
4
4
4
2
3
3
Percent of SSA (%)
100
125
133
100
67
33
50
50
Cape Verde
7
4
5
6
-1
7
11
7
Percent of SSA (%)
175
100
167
150
-16.7
117
183
117
Djibouti
0
2
3
3
4
3
4
4
Percent of SSA (%)
0
50
100
75
67
50
67
67
Ethiopia
6
8
2
-2
14
12
11
11
Percent of SSA (%)
150
200
67
-50
233
200
183
183
Gabon
-2
2
0
2
1
3
1
6
Percent of SSA (%)
-50
50
0
50
16.7
50
16.7
100
Ghana
4
4
4
5
6
6
6
6
Percent of SSA (%)
100
100
133
125
100
100
100
100
Guinea
2
4
4
2
3
3
2
2
Percent of SSA (%)
50
100
133
50
50
50
33
33
Kenya
1
4
1
3
5
6
6
7
Percent of SSA (%)
25
100
33
75
83
100
100
117
Lesotho
5
3
2
4
5
1
8
5
Percent of SSA (%)
125
75
67
100
83
16.7
133
83
Malawi
2
-5
-4
6
6
3
8
9
Percent of SSA (%)
50
-125
-133
150
100
50
133
150
Mali
3
12
4
7
2
6
5
3
Percent of SSA (%)
75
300
133
175
33
100
83
50
Namibia
3
1
5
4
12
3
7
4
Percent of SSA (%)
75
25
167
100
200
50
117
67
Niger
-1
7
3
4
-1
7
6
3
Percent of SSA (%)
-25
175
100
100
-16.7
117
100
50
Nigeria
5
3
2
10
11
5
6
6
Percent of SSA (%)
125
75
67
250
183
83
100
100
Senegal
3
5
1
7
6
6
2
5
Percent of SSA (%)
75
125
33
175
100
100
33
83
Seychelles
4
-2
1
-6
-3
7
8
7
Percent of SSA (%)
100
-50
25
-150
-50
117
133
117
Sierra Leone
4
18
27
9
8
7
7
7
Percent of SSA (%)
100
450
900
225
133
117
117
117
Togo
-1
0
4
3
3
1
4
2
Percent of SSA (%)
-25
0
133
75
50
16.7
67
33
Uganda
6
5
6
6
7
6
11
9
Percent of SSA (%)
150
125
200
150
117
100
183
150
Source: Author’s calculation based on data from World Bank,
Africa Development Indicators online
Overall, SSA recorded a 4 percent growth rate in 2000, 2001 and
2003. The lowest growth rate of 3 percent was recorded for the
region in 2002. Growth rate rose in 2004 to 6 percent for the
region and this was sustained till 2007.
For the year 2000, Botswana recorded the highest growth rate of
8 percent representing 200 percent of SSA average for that year. In
sharp contrast, Gabon, Niger, and Togo all reported negative growth
rates for the same year. Gabon however had the worst growth rate of
-2 percent which represented -50 percent of the SSA average for
that year. The year 2001 was by no means less dramatic in terms of
recorded GDP growth rates for the selected SSA countries. For
example, Sierra Leone just recovering from long years of civil war
topped the study group at 18 percent growth rate. This figure
represented 450 percent of the average growth rate for SSA in that
year. Malawi and Seychelles reported negative GDP growth rates for
2001. But Malawi was at the bottom as she had a negative growth
rate of -5 percent which was -125 percent of SSA average for the
year.
Sierra Leone continued to be the best performer in 2002 among
the study group as the country again recorded a spectacular growth
rate figure of 27 percent representing 900 percent of SSA average
for that year. Malawi again was in the negative region with a -4
percent GDP growth rate for the year 2002 which represented -133
percent of the SSA average for the year. Surprisingly, Malawi was
the only country within the study group that actually reported a
deceleration in GDP growth rate for year 2002. Nigeria was at the
top in the year 2003 with a GDP growth rate of 10 percent
representing 250 percent of the SSA average for that year.
Seychelles came out worst performer in 2003 with a recorded
deceleration of GDP growth rate of -6 percent representing -150
percent of the SSA average for the year.
The impressive performances of majority of the SSA economies
continued in 2004 with Ethiopia taking the lead position for the
year. The Ethiopian economy grew at 14 percent representing 233
percent of the SSA average for the year. Seychelles unfortunately
could not catch up with the momentum of growth across the region as
the country again was confined to the bottom position with a
recorded negative GDP growth rate of -3 percent which represented
-50 percent of the SSA average for that year. Economic growth
figures for year 2005 revealed impressive economic performances
across the sampled SSA countries. The Ethiopian economy was again
in the lead with a growth rate of 12 percent representing 200
percent of the SSA average for the year. Lesotho and Togo on the
other hand, trailed every other country within the sampled group as
each of these countries recorded a growth rate of 1 percent in
2005. This represented 16.7 percent of the SSA average for the
year.
In 2006, three countries, Cape Verde, Ethiopia and Uganda tied
in the lead with each recording a growth rate of 11 percent for the
year. This value stood at 183 percent of the average growth rate
for the SSA region in 2006. At the bottom was Gabon with a 1
percent growth rate for 2006 which represented a meager 16.7
percent of the SSA average for the same year. In 2007, the
Ethiopian economy maintained its leading role at 11 percent growth
rate and this amounted to 183 percent of the SSA average economic
performance for the year. During the same year, Guinea and Togo
tied in the bottom position as each of the two countries recorded a
2 percent growth rate representing 33 percent of the SSA average
for the year.
A quick remark here is to observe that on the average, economic
performance remained robust in SSA over the study period. In view
of this fact, Rena (2008) pointed out that growth in most of SSA
was driven essentially by production and exports of primary
commodities. This unfortunately exposes the continent to external
shocks which consequently compels growth policies that encourages
economic diversification in the continent. Moreover, it is also
noted here that those economies that initially recorded negative
growth rates began to pick up by year 2005 and no SSA economy
within the study group reported a negative growth rate between 2005
and 2007.
2.2 Patterns and Trends of Domestic Investment in SSA
The difficulties in raising domestic savings to support rapid
capital accumulation and growth account for the inability of SSA to
provide the basic needs for their population. Within sustainable
growth framework, appropriate policies are needed especially in
raising saving rate. In some countries, sizeable increases in
domestic savings cannot be expected to take place as a
pre-condition for acceleration of investment and growth, (United
Nations Conference on Trade and Development (UNCTAD), 2001).
Capital accumulation is very vital for a sustainable process of
economic growth. It is note-worthy that though considerable
productivity gains could be attained by more intensive and
efficient use of existing resources, such gains would be one-off
and may not lead to rapid and sustained growth unless translated
into investment in productive capacity, including physical and
human infrastructure. Every economy (including those of SSA)
therefore makes investment in productive capacity a major policy
goal for all time. Table 2.2 captures the trend of domestic
investment in SSA between the periods 2002 and 2007.
Table 2.2: Domestic Investment in Selected SSA Countries (US$’
billion)
Country/Year
2000
2001
2002
2003
2004
2005
2006
2007
SSA
58.07
57.08
58.67
78.64
98.63
115.22
138.46
168.64
Benin
0.43
0.46
0.50
0.67
0.74
0.84
0.00
0.00
Percent of SSA (%)
0.74
0.81
0.85
0.85
0.75
0.73
0.00
0.00
Botswana
2.16
2.40
2.42
3.46
4.01
3.70
3.30
5.01
Percent of SSA (%)
3.72
4.20
4.12
4.40
4.07
3.21
2.38
2.97
Cameroon
1.68
1.95
2.15
2.38
2.98
3.16
3.02
3.58
Percent of SSA (%)
2.89
3.42
3.66
3.03
3.02
2.74
2.18
2.12
Cape Verde
0.10
0.10
0.13
0.15
0.35
0.37
0.45
0.58
Percent of SSA (%)
0.17
0.18
0.22
0.19
0.35
0.32
0.33
0.34
Djibouti
0.05
0.05
0.06
0.09
0.14
0.13
0.23
0.32
Percent of SSA (%)
0.09
0.09
0.10
0.11
0.14
0.11
0.17
0.19
Ethiopia
1.66
1.75
1.86
1.87
2.56
2.83
3.67
4.84
Percent of SSA (%)
2.86
3.07
3.17
2.38
2.60
2.46
2.65
2.87
Gabon
1.11
1.21
1.21
1.45
1.75
1.85
2.34
3.03
Percent of SSA (%)
1.91
2.12
2.06
1.84
1.77
1.61
1.69
1.80
Ghana
1.19
1.41
1.21
1.75
2.52
3.21
3.87
5.10
Percent of SSA (%)
2.05
2.47
2.06
2.23
2.56
2.79
2.80
3.02
Guinea
0.61
0.47
0.43
0.37
0.45
0.46
0.43
0.58
Percent of SSA (%)
1.05
0.82
0.73
0.47
0.46
0.40
0.31
0.34
Kenya
2.21
2.44
1.99
2.46
2.75
3.17
4.04
5.44
Percent of SSA (%)
3.81
4.27
3.39
3.13
2.79
2.75
2.92
3.23
Lesotho
0.40
0.33
0.30
0.32
0.40
0.40
0.38
0.44
Percent of SSA (%)
0.69
0.58
0.51
0.41
0.41
0.35
0.27
0.26
Malawi
0.24
0.26
0.00
0.44
0.53
0.67
0.72
0.93
Percent of SSA (%)
0.41
0.46
0.00
0.56
0.54
0.58
0.52
0.55
Mali
0.60
0.82
0.62
1.06
1.02
1.20
1.34
1.60
Percent of SSA (%)
1.03
1.44
1.06
1.35
1.03
1.04
0.97
0.95
Namibia
0.67
0.79
0.62
0.96
1.26
1.43
1.82
1.83
Percent of SSA (%)
1.15
1.38
1.06
1.22
1.28
1.24
1.31
1.09
Niger
0.21
0.24
0.31
0.39
0.42
0.77
0.00
0.00
Percent of SSA (%)
0.36
0.42
0.53
0.50
0.43
0.67
0.00
0.00
Nigeria
6.78
7.26
7.65
9.29
11.02
13.05
15.71
19.95
Percent of SSA (%)
11.68
12.72
13.04
11.81
11.17
11.33
11.35
11.83
Senegal
0.96
0.90
0.92
1.43
1.67
2.58
2.64
3.49
Percent of SSA (%)
1.65
1.58
1.57
1.82
1.69
2.24
1.91
2.07
Seychelles
0.15
0.25
0.18
0.07
0.09
0.22
0.25
0.30
Percent of SSA (%)
0.26
0.44
0.31
0.09
0.09
0.19
0.18
0.18
Sierra Leone
0.04
0.05
0.09
0.14
0.11
0.21
0.22
0.22
Percent of SSA (%)
0.07
0.09
0.15
0.18
0.11
0.18
0.16
0.13
Togo
0.24
0.27
0.27
0.33
0.37
0.39
0.00
0.00
Percent of SSA (%)
0.41
0.47
0.46
0.42
0.38
0.34
0.00
0.00
Uganda
1.21
1.13
1.25
1.39
1.60
2.07
2.11
2.63
Percent of SSA (%)
2.08
1.98
2.13
1.77
1.62
1.80
1.52
1.56
Source: Author’s calculation based on data from World Bank,
Africa Development Indicators online
Sub-Saharan Africa recorded some sizeable domestic investment
between 2000 and 2007 as shown in table 2.2. The figures ranged
from approximately US$58.07 billion in 2000 to US$168.64 billion in
2007 representing a change in domestic investment level of about
190.4 percent. However, another look at individual country
investment levels for each year reveals that improvement in private
investment was driven mainly by some few countries within the
sampled group. Notable among these countries (in alphabetic order)
were Botswana, Cameroon, Ethiopia, Gabon, Ghana, Kenya and
Nigeria.
Nigeria for instance remained on top of all other economies
within the study group throughout the study period. This is in
terms of capacity of the economy to mobilize private investment
internally. The country recorded a total of US$6.78 billion
domestic investment in year 2000 and this represented about 11.6
percent of total domestic investment in SSA for that year. This
figure steadily grew to US$7.26 billion representing 12.7 percent
of SSA average in 2001, US$7.65 billion representing 13.0 percent
of SSA average in 2002, US$9.29 billion representing 11.0 percent
of SSA average in 2003, US$11.0 billion representing 11.1 percent
of SSA average in 2004, US$13.0 billion representing 11.3 percent
of SSA average in 2005, US$19.9 billion representing 11.3 percent
of SSA average in 2006, and US$7.26 billion representing 11.8
percent of SSA average in 2007.
Sierra Leone appeared to be in the rear for the greater part of
the period under review. This of course is not surprising
considering the fact that this country is just recovering from a
civil war that lasted for many years. What is surprising is the
high economic growth rate recorded by the country during the same
period covered by this study. The question here is what could have
driven this growth outside of domestic investment in the economy?
Precisely, domestic investment figures for Sierra Leone range from
US$0.04 billion in 2000, to US$0.05 billion in 2001, US$0.09
billion in 2002, US$0.14 billion in 2003, US$0.11 billion in 2004,
US$0.21 billion in 2005, US$0.22 billion in 2006, and US$0.22
billion in 2007. These figures represented 0.07 percent, 0.09
percent, 0.15 percent, 0.18 percent, 0.11 percent, 0.18 percent,
0.16 percent, and 0.13 percent of the SSA average for the years
2000, 2001, 2002, 2003, 2004, 2005, 2006 and 2007 respectively.
A good number of the selected SSA countries never recorded up to
US$1.00 billion for any year during the study period. Though most
of these economies are small by most standards, it is equally
disturbing that private investment drive does not occupy any
priority place in these countries. These details are also
indicative of the predicament of resource gap among SSA economies
and probably policy misdirection for the region in its drive for
sustainable growth through investment in productive capacity.
2.3 Patterns and Trends of Foreign Trade in SSA
Export growth supports investment because it helps to earn
foreign exchange needed for capital goods imports and advanced
technology. Investment supports exports by providing the basis for
productivity growth and increased competitiveness. Investment also
allows for production to be shifted towards products with high
income elasticity, thereby helping to avert terms of trade losses.
Successful examples of industrialization and growth are thus
underpinned by rising rates of savings, investment and exports.
While African countries have in the past experienced surges of
investment and growth, they have not in general been able to
establish a virtuous circle of investment, savings and exports
(UNCTAD, 2001). Pattern of trade are captured for all countries
within the study by each country’s real external balance and this
can be seen in table 2.3.
Table 2.3: Real External Balance in Selected SSA Countries (US$’
billions)
Country/Year
2000
2001
2002
2003
2004
2005
2006
2007
SSA
10.28
1.30
-3.65
-4.17
3.95
13.76
21.26
13.65
Benin
-0.29
-0.30
-0.39
-0.46
-0.52
-0.54
0.00
0.00
Percent of SSA (%)
-2.84
-23.12
10.71
10.96
-13.06
-3.94
0.00
0.00
Botswana
1.17
0.98
0.68
0.72
0.98
1.81
2.47
1.28
Percent of SSA (%)
11.38
74.79
-18.65
-17.20
24.74
13.17
11.63
9.42
Cameroon
0.36
-0.12
-0.09
0.04
-0.07
-0.17
0.37
0.17
Percent of SSA (%)
3.52
-9.53
2.33
-1.07
-1.72
-1.23
1.73
1.23
Cape Verde
-0.18
-0.18
-0.23
-0.28
-0.36
-0.33
-0.39
-0.51
Percent of SSA (%)
-1.75
-14.09
6.17
6.60
-9.11
-2.39
-1.86
-3.71
Djibouti
-0.08
-0.05
-0.03
-0.06
-0.11
-0.07
-0.13
-0.17
Percent of SSA (%)
-0.82
-3.72
0.84
1.37
-2.90
-0.53
-0.63
-1.25
Ethiopia
-0.98
-0.96
-1.09
-1.21
-1.68
-2.51
-3.44
-3.77
Percent of SSA (%)
-9.50
-73.47
29.85
28.92
-42.45
-18.23
-16.19
-27.60
Gabon
1.84
1.22
0.95
1.47
2.17
3.21
3.14
3.33
Percent of SSA (%)
17.93
93.94
-25.94
-35.21
54.86
23.33
14.75
24.43
Ghana
-0.92
-1.04
-0.75
-1.21
-1.87
-2.68
-3.14
-3.96
Percent of SSA (%)
-8.93
-79.73
20.66
29.12
-47.32
-19.52
-14.78
-29.04
Guinea
-0.13
-0.04
-0.13
-0.09
-0.16
-0.09
-0.09
-0.10
Percent of SSA (%)
-1.29
-3.11
3.48
2.05
-3.97
-0.64
-0.42
-0.75
Kenya
-1.29
-1.31
-0.71
-0.89
-1.01
-1.40
-2.22
-3.02
Percent of SSA (%)
-12.51
-100.44
19.35
21.29
-25.50
-10.16
-10.46
-22.14
Lesotho
-0.52
-0.41
-0.42
-0.55
-0.63
-0.71
-0.70
-0.83
Percent of SSA (%)
-5.02
-31.13
11.45
13.25
-15.94
-5.15
-3.31
-6.10
Malawi
-0.17
-0.19
-0.66
-0.53
-0.48
-0.70
-0.76
-0.75
Percent of SSA (%)
-1.65
-14.66
18.14
12.65
-12.12
-5.09
-3.56
-5.51
Mali
-0.31
-0.45
-0.25
-0.48
-0.60
-0.62
-0.48
-0.67
Percent of SSA (%)
-2.97
-34.23
6.72
11.44
-15.29
-4.51
-2.24
-4.92
Namibia
-0.14
-0.23
-0.07
-0.45
-0.15
0.01
0.31
-0.16
Percent of SSA (%)
-1.40
-17.68
1.91
10.75
-3.79
0.07
1.46
-1.20
Niger
-0.14
-0.15
-0.19
-0.25
-0.30
-0.31
0.00
0.00
Percent of SSA (%)
-1.38
-11.48
5.29
6.00
-7.69
-2.27
0.00
0.00
Nigeria
10.09
5.14
-0.41
1.53
11.33
17.39
22.12
17.42
Percent of SSA (%)
98.21
394.12
11.10
-36.71
286.83
126.41
104.05
127.68
Senegal
-0.44
-0.44
-0.56
-0.83
-1.04
-1.35
-1.64
-2.53
Percent of SSA (%)
-4.24
-33.81
15.21
19.92
-26.29
-9.84
-7.70
-18.55
Seychelles
-0.02
-0.13
-0.01
0.08
0.01
-0.19
-0.17
-0.32
Percent of SSA (%)
-0.20
-10.25
0.23
-1.89
0.35
-1.39
-0.82
-2.35
Sierra Leone
-0.13
-0.15
-0.17
-0.17
-0.12
-0.16
-0.11
-0.12
Percent of SSA (%)
-1.31
-11.27
4.69
4.18
-3.03
-1.16
-0.51
-0.90
Togo
-0.27
-0.26
-0.26
-0.24
-0.28
-0.36
-0.43
-0.51
Percent of SSA (%)
-2.58
-19.78
7.25
5.72
-7.03
-2.59
-2.04
-3.76
Uganda
-0.73
-0.74
-0.88
-0.94
-0.83
-1.02
-1.35
-1.65
Percent of SSA (%)
-7.13
-56.91
24.15
22.57
-21.03
-7.43
-6.37
-12.08
Source: Author’s calculation based on data from World Bank,
Africa Development Indicators online
Table 2.3 shows the real external balance on goods and services
for all selected SSA countries for this study. With the exception
of Botswana, Gabon and Nigeria, none of these countries performed
impressively well as they all remained in the negative region for
most years within the study period. On the average, SSA also
performed well having negative entries for just two (2002 and 2003)
of eight years covered by this study. The positive outlook of real
external balance for the overall SSA economy is undoubtedly as a
result of the overwhelming size of the Nigerian economy within the
region.
A comparism of the figures in Table 2.3 reveals the predominance
of the Nigerian economy throughout the period under review. In a
number of cases, the real external balance (REB) for the country
was higher than the net figures for SSA as a region. In year 2000,
REB for the country stood at US$10.09 billion or 98.21 percent of
the net value for SSA. The year 2001 was US$5.14 billion or 394
percent of the net value for SSA. Year 2002 figures were in the
negative for the country at -US$0.41billion, but the economy still
stood above the SSA average at 11.1 percent. Interestingly, REB for
all the selected SSA countries (except Botswana) were the negative
for this year meaning that it was a particularly bad year for trade
in the region. Nigeria’s REB picked again in 2003 standing
US$1.53billion, US$11.33 billion in 2004, US$17.39 billion in 2005,
US$22.12 billion in 2006, and US$17.42 billion in 2007. These
figures represented -36.71 percent, 286.83 percent, 126.41 percent,
104.05 percent, and 127.68 percent of the net REB for SSA in the
years 2003, 2004, 2005, 2006 and 2007 respectively.
Benin, Cape Verde, Djibouti, Ethiopia, Ghana, Guinea, Kenya,
Lesotho, Malawi, Mali, Niger, Senegal, Sierra Leone, Togo and
Uganda all had negative real external balance figures for all the
years covered by this study. What this means is that each of these
countries simply imported much more than they exported during each
year throughout the period under review. Again this is indicative
of the poor health of most Sub-Saharan African economies.
2.4 Patterns and Trends of Workers’ Remittances flow to SSA
Remittances flows are important and stable source of external
finance for many countries and constitute a substantial part of
financial inflows for countries with a large migrant labour force.
Officially recorded remittances received by developing countries
are estimated to have exceeded US$93 billion in 2003 and have since
increased dramatically totaling an estimated US$167 billion in
2005, according to World Bank (2006) estimates. Remittance flows to
SSA region have grown steadily from US$4.62billion in 2000 to
US$4.66billion in 2001. The figures stood at US$5.03billion in 2002
and US$6.00billion in 2003. It rose to US$8.05billion and
US$9.41billion in 2005. And finally remittance flows to SSA further
rose to US$12.6billion in 2006 and US$18.6billion in 2007.
The explanations for this dramatic rise in remittance flows to
SSA are quite obvious. First, remittances through informal channels
are being subjected to greater scrutiny since the events of
September 11, 2001. The discovery of the large size of these flows
has prompted governments worldwide to improve the recording
efforts. Second, reduction in remittance costs and expansion of
remittance networks have increased migrants’ disposable incomes and
their incentives to remit. Third, the depreciation of the U.S.
dollar has raised the value of remittances from Europe and Japan.
The appreciation of the Euro relative to the U.S. dollar may
account for some 7 percent of the increase in remittances to
developing countries during 2001–2005 (Mohapatra and others, 2006).
Finally, growth in migrant stocks (due to falling travel costs and
increased globalization) and an increase in migrant incomes have
also contributed to higher remittances. Table 2.4 provides details
of remittance flows to Sub-Saharan Africa and other developing
countries.
Table 2.4: Remittance Flows to Selected SSA Countries, (US$
billions)
Country/Year
2000
2001
2002
2003
2004
2005
2006
2007
SSA
4.62
4.66
5.03
6.00
8.05
9.41
12.65
18.62
Benin
0.08
0.08
0.07
0.05
0.05
0.14
0.19
0.19
Percent of SSA (%)
1.74
1.67
1.39
0.83
0.67
1.46
1.47
1.00
Botswana
0.00
0.00
0.00
0.00
0.05
0.08
0.08
0.08
Percent of SSA (%)
0.01
0.01
0.00
0.00
0.63
0.88
0.62
0.43
Cameroon
0.01
0.01
0.01
0.06
0.10
0.07
0.12
0.15
Percent of SSA (%)
0.26
0.15
0.28
1.01
1.22
0.71
0.93
0.83
Cape Verde
0.09
0.08
0.08
0.11
0.11
0.14
0.14
0.14
Percent of SSA (%)
1.85
1.71
1.68
1.81
1.40
1.45
1.07
0.74
Djibouti
0.001
0.001
0.001
0.003
0.003
0.003
0.004
0.004
Percent of SSA (%)
0.02
0.02
0.02
0.05
0.04
0.03
0.03
0.02
Ethiopia
0.05
0.02
0.03
0.05
0.13
0.17
0.17
0.36
Percent of SSA (%)
1.15
0.39
0.66
0.78
1.66
1.84
1.34
1.91
Gabon
0.002
0.001
0.001
0.004
0.001
0.001
0.001
0.001
Percent of SSA (%)
0.05
0.03
0.02
0.06
0.02
0.02
0.01
0.01
Ghana
0.03
0.05
0.04
0.07
0.08
0.10
0.11
0.12
Percent of SSA (%)
0.70
0.98
0.87
1.09
1.02
1.05
0.83
0.63
Guinea
0.00
0.01
0.02
0.11
0.04
0.04
0.04
0.02
Percent of SSA (%)
0.03
0.19
0.30
1.85
0.52
0.44
0.33
0.08
Kenya
0.05
0.05
0.06
0.07
0.38
0.42
0.57
0.65
Percent of SSA (%)
1.10
1.09
1.14
1.10
4.67
4.52
4.51
3.47
Lesotho
0.00
0.00
0.01
0.01
0.01
0.01
0.00
0.01
Percent of SSA (%)
0.00
0.03
0.19
0.19
0.18
0.07
0.04
0.07
Malawi
0.04
0.04
0.03
0.03
0.00
0.01
0.02
0.03
Percent of SSA (%)
0.89
0.88
0.58
0.50
0.03
0.06
0.13
0.17
Mali
0.07
0.08
0.13
0.14
0.14
0.15
0.19
0.32
Percent of SSA (%)
1.50
1.76
2.51
2.32
1.72
1.63
1.52
1.74
Namibia
0.00
0.00
0.00
0.00
0.01
0.01
0.01
0.01
Percent of SSA (%)
0.10
0.08
0.06
0.08
0.07
0.08
0.05
0.03
Niger
0.00
0.01
0.01
0.01
0.04
0.05
0.05
0.05
Percent of SSA (%)
0.10
0.30
0.17
0.19
0.53
0.48
0.39
0.26
Nigeria
1.39
1.17
1.21
1.06
2.27
3.33
3.33
1.79
Percent of SSA (%)
30.11
25.02
24.03
17.73
28.25
35.39
26.32
9.64
Senegal
0.18
0.26
0.30
0.45
0.56
0.72
0.85
1.11
Percent of SSA (%)
3.88
5.57
5.90
7.48
7.00
7.62
6.73
5.95
Seychelles
0.003
0.002
0.002
0.005
0.007
0.012
0.013
0.011
Percent of SSA (%)
0.06
0.03
0.04
0.08
0.08
0.13
0.10
0.06
Sierra Leone
0.01
0.01
0.01
0.03
0.02
0.00
0.05
0.15
Percent of SSA (%)
0.15
0.13
0.15
0.43
0.31
0.02
0.37
0.79
Togo
0.02
0.05
0.09
0.13
0.15
0.16
0.20
0.20
Percent of SSA (%)
0.34
1.11
1.72
2.14
1.91
1.75
1.58
1.07
Uganda
0.24
0.34
0.42
0.31
0.31
0.32
0.41
0.45
Percent of SSA (%)
5.15
7.34
8.36
5.11
3.86
3.42
3.25
2.43
Source: Author’s calculation based on data from World Bank,
Africa Development Indicators online
A breakdown of the SSA remittance figures in Table 2.4 shows
that flows to Nigeria top the list of recipients within the study
group throughout the study period. The country recorded a total of
about US$1.39billion in 2000, US$1.17billion in 2001,
US$1.21billion in 2002, US$1.06billion in 2003, US$2.27billion in
2004, US$3.33billion in 2005, US$3.33billion in 2006 and
US$1.79billion in 2007. These figures represent 30.1 percent, 25.02
percent, 24.0 percent, 17.7 percent, 28.2 percent, 35.3 percent,
and 9.64 percent of the SSA total for the years 2000, 2001, 2002,
2003, 2004, 2005, 2006 and 2007 respectively.
Remittance flows to most of the countries covered in this study
are actually very small in when compared to the big recipients such
as Nigeria. A further examination of figures in table 2.4 reveals
that a number of these countries never received up to 1 percent of
the recorded remittance flows to SSA at any given year throughout
the study period. Included in this group are: Botswana, Djibouti,
Gabon, Lesotho, Malawi, Namibia, Niger, Seychelles and Sierra
Leone. Despite the small amount flowing to these countries over the
years, it is often not surprising to see that these flows are quite
significant when measured as a ratio to receiving country’s Gross
Domestic Product (GDP). Such realities provide the necessary
impetus to encourage remittance flows with relevant policy measures
in these SSA countries.
2.5 Trends in Workers’ Remittances and Growth Indicators in
SSA
Workers’ remittances may exhibit trends and patterns with key
development and economic growth indicators such as output growth,
investment and foreign trade or real external balance. Such trends
can help in predicting the path or direction of any of these
variables and this in turn can be a useful guide in appropriate
policy formulation. Figure 2.1 below shows trends in workers’
remittances, economic growth, investment and real external balance
in SSA between 2000 and 2007.
Figure 2.1: Trends in Workers’ Remittances and Selected Economic
Growth Indicators in SSA
Source: Plotted by author based on data from World Bank, Africa
Development Indicators online
Figure 2.1 suggests that investment and economic growth in SSA
countries have similar patterns of growth over the study period. A
similar behavioural pattern cannot be concluded for remittances on
the one hand, and domestic investment or economic growth on the
other hand. No single pattern between real external balance and the
other three variables is observed throughout the period covered by
the study. These results are however not sufficient to prescribe
any policy direction for the SSA economies as they only indicate
some patterns in behaviour of the selected variables over time. It
will require a cause-effect analysis to determine the exact nature
of relationships among these variables.
2.6 Sources and Destination of Remittance Flows
Remittances flow to Africa represents the least in terms of
relative share of flows to the different regions of the world.
Table 2.5 below provides estimates of the regional distribution of
remittances flow by sources and destination in year 2000.
Table 2.5: Estimated flows of remittances by region, 2000. US$
billions
Sending Region
Receiving Region
Africa
Asia
Europe
Latin America & Caribbean
North America
Oceania
Total
Africa
3.7
0.5
0.1
0.0
0.0
0.0
4.2
Asia
3.4
31.5
3.4
0.5
0.2
0.0
39.0
Europe
2.6
3.2
9.5
0.4
0.4
0.1
16.2
Latin America & Caribbean
0.0
0.1
0.6
1.1
0.1
0.0
1.8
North America
0.7
7.9
5.7
14.2
0.9
0.1
29.6
Oceania
0.0
0.2
0.4
0.0
0.0
0.1
0.8
Total
10.4
43.4
19.6
16.2
1.6
0.3
91.5
Bold figures indicate flows between countries in the same
region.
Source: Harrison (2004). Adapted from Carling (2005)
Evidence from the above table reveals that about one third of
global remittances are estimated to flow between Asian countries.
This places the Asian region on top of all other regions in terms
of intra-regional remittance flows. Within Europe, intra-regional
remittances flow is also quite substantial making this region the
second largest. When inter-regional flows are considered, North
America to Latin America and the Caribbean top the list while North
America to Asia follows. Table 2.5 also shows that African
countries receive more remittances from elsewhere in Africa than
they do from other continents. However, the largest
inter-continental sources are from Asia, Europe and North America
in that order. The relative dominance of Asia as number one source
region of remittance flow to Africa has since changed in favour of
North America. Fadayomi (2009: 15) stated that “almost ¾ of
remittances to Sub-Saharan Africa in 2007 were sent from the United
States and Western Europe, while the rest were sent Gulf States,
other developed countries and developing countries”.
2.7 Country Level Analysis of Distribution of Remittance Flows
to SSA
At the country level, distributions of remittance flows to SSA
countries are not easily determined owing to the non-existent or
scanty nature of available data. In terms of volume and value of
remittance flows to SSA, evidence from available data show that no
sub-region in SSA is left out from remittance flows. However, the
West and East African sub-regions dominate in terms of
concentration of remittance inflows while Central and Southern
African sub-regions are barely represented with two and three
countries respectively reporting data on remittances for most of
the periods covered in this study. Details of volume and value of
remittance flows to SSA by sub-region and by country are presented
in Table 2.6.
Table 2.6: Volume and Value of Remittance Flows to SSA by
Sub-Region and by Country
Sub-region and
Country
Remittances
Sub-region and
Country
Remittances
US$ million
% of GDP
US$ million
% of GDP
2000
2006
2000
2006
2000
2006
2000
2006
Eastern Africa
Western Africa
Burundi
Benin*
80.48
186.19
3.57
4.03
Comoros
Burkina Faso
62.47
2.39
Djibouti*
0.72
3.66
0.13
0.48
Cape Verde*
85.69
135.83
16.13
11.30
Eritrea
Cote d’Ivoire
Ethiopia*
53.16
169.18
0.65
1.12
Gambia
62.87
12.38
Kenya*
584.85
570.46
4.61
2.54
Ghana*
32.40
105.25
0.65
0.83
Madagascar
Guinea*
1.17
41.64
0.04
1.30
Malawi*
3.62
17.17
0.21
0.54
Guinea Bissau
Mauritius
Liberia
Mozambique
15.83
0.22
Mali*
69.18
192.73
2.86
3.29
Rwanda
3.62
17.17
0.21
0.61
Niger*
4.55
49.06
0.25
1.35
Seychelles*
2.98
13.08
0.49
1.35
Nigeria*
1391.79
3328.69
3.03
2.27
Somalia
Senegal*
179.22
850.58
3.82
9.08
Uganda*
238.10
411.00
3.84
4.13
Sierra Leone*
7.13
47.35
1.12
3.33
Tanzania
8.99
0.06
Togo*
15.71
199.95
1.18
9.01
Central Africa
Southern Africa
Cameroon*
11.85
117.65
0.12
0.66
Angola
CA Republic
Botswana*
0.35
78.74
0.01
0.72
Chad
Lesotho*
0.14
4.46
0.02
0.29
DR Congo
Namibia*
4.49
6.54
0.11
0.08
Eq. Guinea
South Africa
Gabon*
2.26
1.48
0.04
0.02
Swaziland
São Tomé and Príncipe
Zambia
Zimbabwe
Source: Author’s Computations based on Data from Africa
Development Indicators online, 2010
*indicate countries included in this study
An effort to determine how much of remittance flows can be
associated with productive activities or economic growth in
recipient economies of SSA necessarily begins with the
identification of top remittance recipients from the four
sub-regional blocks in SSA. Available data reveal that Nigeria tops
in the West African sub-region, Kenya tops in East Africa; Botswana
tops the list in Southern Africa sub-region and Cameroon occupies
that position in the central Africa sub-region. An annual
classification (covering the study period, 2000 -2007) of
remittances and other major growth indicators for the identified
top remittance recipients are presented in Table 2.7.
Table 2.7: Major Growth Indicators of Sub-Regional Top
Remittance Recipients in SSA (US$’Million)
Country
year
GDP
INV
REB
WR
Nigeria
(West Africa)
2000
45983.6
9317.43
10092.99
1391.79
2001
47999.78
11563.31
5138.631
1166.628
2002
59116.85
12249.57
-405.57
1208.94
2003
67656.02
13910.33
1530.907
1062.84
2004
87845.42
16261.06
11326.93
2272.701
2005
112248.6
21071.68
17388.16
3328.694
2006
146869
25370.21
22123.33
3328.694
2007
165920.9
25370.21
17424.52
17945.94
Kenya
(East Africa)
2000
12691.28
2210.071
-1286.12
584.8543
2001
12986.52
2440.211
-1309.52
50.91443
2002
13149.26
1990.564
-707
57.14348
2003
14903.63
2456.439
-888.053
65.8453
2004
16091.63
2750.309
-1007.05
375.8113
2005
18769.01
3169.203
-1398
424.991
2006
22478.65
4038.904
-2223
570.4593
2007
26950.31
5437.966
-3022
645.1811
Botswana
(Southern Africa)
2000
6177.184
2160.083
1169.572
0.352816
2001
6033.253
2397.494
975.1013
0.359518
2002
5933.281
2416.915
681.4528
0.015803
2003
8277.572
3455.007
717.251
0.022223
2004
9827.417
4007.657
976.8438
50.82159
2005
10512.51
3699.524
1811.447
82.35632
2006
11006.46
3299.392
2471.827
78.74315
2007
12323.81
5010.711
1284.973
80.0393
Cameroon
(Central Africa)
2000
10075.04
1684.636
361.8344
11.84716
2001
9598.224
1949.526
-124.231
6.78832
2002
10879.78
2153.019
-85.2043
14.14916
2003
13621.81
2383.246
44.62519
60.55743
2004
15775.36
2983.054
-67.8614
98.38632
2005
16587.86
3163.024
-168.54
67.12822
2006
17956.99
3019.452
368.2258
117.648
2007
20691.56
3582.002
168.3954
154.0269
Source: World Bank, Africa Development Indicators online,
2010
An inspection of data in Table 2.7 reveals a steady rise in
values of all variables observed between 2000 and 2007. The only
exception here has to do with data on the variable - external
balance which have mixed signs across periods and countries. The
observed relationships are further captured in separate figures
below for each of the top remittance recipients. This is to allow
for additional insights regarding the existence of any unique
characterization of remittance flows into SSA.
Figure 2.2: Remittance Receipts and other Growth Indicators in
Nigeria (2000 – 2007)
Source: Plotted by author based on data from African Development
Online, 2010
The volume of remittance flows to Nigeria continued to remain
below the investment and aggregate output (GDP) curves throughout
the period under review. However, remittances to Nigeria remained
in the positive region and exhibited an upward trend over time.
Remittances flow to Nigeria continued to grow as GDP and domestic
investment rises. This pattern is particularly so from the period
2004 and 2007. External balance, which captures the external trade
sector, failed to demonstrate a similar relationship with the other
variables over time. What is observed with this variable is a
pattern of cycles the investment and remittance curves throughout
the study period.
The same set of variables is examined below in Figure 2.3 for
Kenya which represents the east African region. This is to verify
whether a similar pattern of behaviour exists among the four
sub-regions.
Figure 2.3: Remittance Receipts and other Growth Indicators in
Kenya (2000 – 2007)
Source: Plotted by author based on data from African Development
Online, 2010
Relationships among the variables GDP, domestic investment,
external balance and remittance receipts for Kenya between 2000 and
2007 are shown in figure 2.3. One major contrasting observation in
the figure from the case of Nigeria is the behaviour of the
variable, external balance which remained predominantly in the
negative region and maintains a downward trend throughout the study
period.
Remittances remain in the positive region throughout the study
period but with some downward trend observed between 2000 and 2003.
Remittances however rose sustainably between 2003 and 2007.
Investment and GDP on the average remained positive and upward
sloping. One very interesting pattern noticed here is the period
2003 upward. GDP, investment and remittances all exhibited very
similar swings during this period. This behaviour is quite similar
to what was noticed in the case of Nigeria. But can a similar
relationship hold for Botswana in southern Africa? Figure 2.4 below
reveals the answer.
Figure 2.4: Remittance Receipts and other Growth Indicators in
Botswana (2000 – 2007)
Source: Plotted by author based on data from African Development
Online, 2010
The case of Botswana appears quite interesting with all
variables exhibiting a marked difference from the case Kenya. Here,
none of the variables appeared in the negative region. Of
particular note is the variable external balance which is
substantially positively sloped contrasting sharply the cases of
Nigeria and Kenya. This is indicative of a relatively healthy
economy. While GDP, investment and external balance on the average,
grew in the same upward direction from 2002, the variable external
balance started fading in the downward direction from the period
2006. Remittances inflow though positive, remained minimal slightly
rising above the horizontal axis from throughout the study period.
Cameroon in central Africa is next examined below in figure
2.6.
Figure 2.5: Remittance Receipts and other Growth Indicators in
Cameroon (2000 – 2007)
Source: Plotted by author based on data from African Development
Indicator, Online, 2010
The average pattern in the case of Cameroon is again different
from the other three top remittance recipients in SSA. While GDP
and investment curves are continuously upward sloping from the
period 2001, remittances curve averages out the eternal balance
curve. Although both curves remained substantially in the positive
region, both were barely above the horizontal axis indicating a
rather negligible value for these variables. The remittances curve
interestingly is very similar to the case of Botswana which was
stable throughout the period under review around the horizontal
axis meaning that inflows are minimal.
It is also compelling at this juncture to consider the least
remittance recipients from each of the SSA sub-regions in order to
obtain a more balanced and fair picture. The overall idea here is
to probe for the presence of similar characterizations of
remittance flows to SSA among these least remittance recipients.
Data on major growth indicators and remittances for the four least
remittance recipients are presented in Table 2.8.
Table 2.8: Growth Indicators of least Sub-Regional Remittance
Recipients in SSA (US$’Million)
Country
year
GDP
INV
REB
WR
Guinea
(West Africa)
2000
3112.363
613.2339
-132.777
1.166455
2001
3039.157
468.2449
-40.5415
8.71587
2002
3208.305
431.5194
-127.189
15.16
2003
3619.436
368.5984
-85.68
111.046
2004
3938.328
447.3895
-156.784
41.64
2005
3260.598
458.0511
-88.4114
41.64
2006
3203.923
427.4501
-89.4554
41.64
2007
4563.586
575.8159
-102.179
15.07
Djibouti
(East Africa)
2000
551.2309
48.45854
-84.4807
0.72023
2001
572.4174
45.0487
-48.5199
0.708976
2002
591.122
59.40604
-30.6098
0.787752
2003
622.0447
89.6557
-56.9657
2.909054
2004
666.0721
143.2864
-114.553
2.970949
2005
708.8436
134.4804
-73.2384
2.993456
2006
760.6529
227.2663
-134.115
3.657418
2007
817.6805
317.8634
-170.104
3.544882
Lesotho
(Southern Africa)
2000
783.1093
395.5415
-515.861
0.138586
2001
711.0866
325.8268
-405.828
1.300182
2002
669.718
300.0478
-418.334
9.772631
2003
994.2572
323.4153
-552.491
11.46537
2004
1289.785
404.1968
-629.386
14.37744
2005
1375.998
401.0849
-707.811
6.948424
2006
1517.512
378.1838
-703.336
4.461993
2007
1669.564
442.8817
-832.964
12.87145
Gabon
(Central Africa)
2000
5067.839
1109.961
1842.789
2.258502
2001
4712.84
1211.642
1224.853
1.23868
2002
4931.504
1208.803
947.9257
1.156404
2003
6054.886
1450.454
1468.341
3.805917
2004
7178.136
1750.973
2166.439
1.431046
2005
8665.739
1846.705
3209.592
1.478762
2006
9545.985
2340.1
3135.111
1.478762
2007
11567.59
3028.015
3333.316
1.478762
Source: World Bank, Africa Development Indicators online,
2010
For the purpose of providing additional insight, data covering
the study period (2000-2007), on all variables and for each of the
four countries listed in Table 2.8 are plotted in the figures below
as was done earlier on, in the cases of top remittance recipients.
These figures are presented and discussed in turn.
Figure 2.6: Remittance Receipts and other Growth Indicators in
Guinea (2000 – 2007)
Source: Plotted by author based on data from African Development
Online, 2010
GDP trend for Guinea in West Africa follows a cyclical pattern
in the period under review while domestic investment and external
balance curves, although in the positive region are slightly
negatively sloped. External balance curve is completely in the
negative region meaning that this country was never able to meet
its trading obligations to her trading partners during the period
under review. Remittances flow is stable, positive and minimal
around the horizontal axis. Djibouti in East Africa is considered
in figure 2.7 below. Again the goal here is to examine whether
behaviour similar to those of Guinea is exhibited.
Figure 2.7: Remittance Receipts and other Growth Indicators in
Djibouti (2000 – 2007)
Source: Plotted by author based on data from African Development
Online, 2010
Evidence from Djibouti reveals that GDP and domestic investment
exhibited upward trend from 2000 up until 2007. Remittances again
remained stable around the horizontal axis demonstrating little or
no improvement over time. External balance variable is disturbingly
in the negative region and negative sloping all through the period
of the review again indicating the inability of this country to
settle its trading obligations with her trading partners. What is
rather striking in these behaviours is the extremely weak nature of
these least remittance recipients as revealed by their negative
external balances. What remains is to see whether Lesotho and Gabon
will also exhibit similar behavioural patterns. Figure 2.8 reveals
the case of Lesotho.
Figure 2.8: Remittance Receipts and other Growth Indicators in
Lesotho (2000 – 2007)
Source: Plotted by author based on data from African Development
Online, 2010
Apart from GDP and investment which are largely in the positive
region and upward sloping, the other growth indicators for Lesotho
are most unimpressive as shown in figure 2.8. The variable -
eternal balance exhibited predominantly downward trends and
remained in the negative region throughout the study period. One
surprising observation is the fact that the period of GDP and
investment growth (2002) unfortunately coincides with the period of
further decline in external balance meaning that the observed
growth in GDP and investment did not translate into a healthy
foreign trade sector. The negative values observed for the variable
- external balance further add to the curiosity on whether any
systematic link exists between a weak foreign trade sector and low
remittance inflows. An examination of the case of Gabon in figure
2.9 below will shed more light on these relationships.
Figure 2.9: Remittance Receipts and other Growth Indicators in
Gabon (2000 – 2007)
Source: Plotted by author based on data from African Development
Online, 2010
All growth indicators for Gabon exhibit a more impressive
pattern of behaviour than the other three least remittance
recipient economies in SSA. As can be seen, these variables
including remittances are in the positive region. GDP, investment,
and external balance clearly demonstrate upward trends on the
average and this is indicative of a much more healthy economy than
the other three least remittance recipient economies of SSA.
Remittances itself though positive and stable around the horizontal
axis is quite minimal. The evidence provided by data on Gabon makes
the exact nature of relationship among remittances and growth
indicators included in this study rather unclear and inconclusive.
This therefore calls for further investigation.
CHAPTER THREE
REVIEW OF THE LITERATURE
3.1 Conceptual and Measurement Issues
Remittances are defined by the World Bank (2007) as “the sum of
workers’ remittances, compensation of employees, and migrant
transfers”. The main sources of official data on migrants'
remittances are the annual balance of payments records of
countries, which are compiled in the Balance of Payments Statistics
Yearbook published by the International Monetary Fund (IMF). It is
therefore most logical to examine the definition of remittances as
provided by the IMF. The IMF Balance of Payments Manual 5 (BMP5)
does not define workers or migrants. According to the Balance of
Payments Textbook, “workers’ remittances consist of goods or
financial instruments transferred by migrants living and working in
new economies to residents of the economies in which the migrants
formerly resided”. It further states that workers’ remittances are
“transfers made by migrants who are employed by entities of
economies in which the workers are considered residents” and that
transfers of self-employed migrants “are not classified as workers’
remittances but as current transfers”. This distinction is
necessary since “workers’ remittances, according to the balance of
payments convention, arise from labour and not from entrepreneurial
i
