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Effects of Institutional Context on the Performance of Microfinance Institutions
Sougand Golesorkhi, Manchester Metropolitan University, UK*
Roy Mersland, University of Agder, Norway
Trond Randøy, University of Agder, Norway
ABSTRACT
This paper explores the performance effect of institutional distance between microfinance institutions (MFI) in developing countries and their international cooperative partners in developed countries. We address institutional distance in relation to both formal and informal dimensions. Furthermore, we investigate whether highly experienced MFIs are able to overcoming the impediments of institutional distance. The paper contents that informal institutional distance has a sigmoid impact on MFIs performance, with performance first increasing, then declining and finally improving again as informal institutional distance increase. We also argue that there is a negative effect of formal institutional distance on MFIs’s performance. Finally, we find that MFIs experience has a positive moderating impact on the both dimensions of institutional distance/performance relationship. Our results is supported by our empirical evidence – based on a sample of 405 MFIs from 74 countries – using a panel data between 1996 and 2009. The paper contributes by bridging the literature in both international business and microfinance research by theoretically and empirically examining the relationship between the institutional distance and MFIs performance.
*corresponding author: [email protected]
1. Introduction
Microfinance institutions (MFIs) provide poor people and micro-entrepreneurs with banking
services. In this paper we investigate two research questions; “How does the institutional distance
between MFIs and their international stakeholders affect their performance?” and “How does the
experience of the MFIs moderates the relationship between performance and institutional distance.
This research is motivated by the fact that the microfinance industry is a highly international
industry with thousands of partnerships, investments and contracts being organized between actors
in developed countries with MFIs operating in developing countries (www.mixmarket.org).
Institutional distance between MFIs and their international cooperative partners is thus deemed to
be important. Furthermore, rating agencies (of MFIs) highlight the importance of institutional
analysis in rating reports. However, the rating reports lack consistency in selection of institutional
indicators, and this suggests that there is little common understanding of which dimensions of the
institutional context are most likely to influence the performance of MFIs. Furthermore, there is a
lack of attention to role of institutional distance between MFIs and their international stakeholders.
The few studies that have attempted to empirically trace the relationship between different
environmental dimensions and the performance of MFIs, have predominately been concerned with
identifying which macroeconomic and business friendliness factors that influences MFIs’
performance (e.g. (Ahlin et al., 2010, Vanroose, 2008). However, according to our knowledge no
former study has looked into the effect of institutional distance between the MFI and its foreign
stakeholders.
The microfinance industry is a highly global industry – in terms of level of foreign
involvement – both in terms of capital flows and knowledge transfers. However, little research has
been conducted on the international nature of the microfinance industry- with only one recent
exception (Mersland et al., 2011). Our study contributes theoretical and empirically by applying an
international business framework. We build on recent calls to investigate broader concept of
institutional distance (Ghemawat, 2007, Xu and Shenkar, 2002) by distinguishing between formal
and informal aspects ((Dunning and Lundan, 2008a, , 2008b, North, 1990). Specifically, we see the
microfinance industry be well suited for such research – as the industry is highly global with many
international linkage (in terms of ownership, knowledge transfers, loans, personal transfers, network
membership etc.) – but at the same time, its banking services are rather uniform across countries.
The implications of national differences have been primarily studied in the context of
foreign direct investment, with the emphasis that multinational firms suffer from “liabilities of
foreignness” when entering foreign countries (Hymer, 1976, Johanson and Vahlne, 2009). This is
driven by foreign firm’s unfamiliarity with the local business environment and their need to
coordinate activities across spatial distance, as well as coping with cultural, institutional, and
economic differences between their home countries and the foreign countries they enter (Luo and
Mezias, 2002, Sethi and Judge, 2009, Slangen and Beugelsdijk, 2010). In particular the effects of
institutional differences are analysed in relation to exploitation of comparative institutional
advantages by subsidiaries and the effect of institutional distance between the headquarter and the
subsidiaries (Dunning, 2000, 1998, Rugman and Verbeke, 2001, Xu and Shenkar, 2002). Both these
research paths have their analogies in relation to microfinance research firstly, to analyse how
institutional distance between the MFI and its international stakeholders affect its performance,
secondly, how the experience of the MFI moderates the relationship between performance and
institutional distance. The role of experience in facilitating firms advancing on the learning curve
has been documented in the literature (Argyres, 1966, Ethiraj et al., Johanson and Vahlne, 1977,
Wernerfelt, 2005). Whereas the international business literature mostly looks at the impact of
institutional distance in the context of parent-subsidiary relations, in the microfinance industry the
typical relationship is reversed – as we look at the impact of institutional distance between the MFI
from the developing countries being engaged in a transaction with partners in developed countries.
In our discussion of institutional distance, we consider that both distinct (but related)
concepts of formal and informal institutional distance are equally relevant factors which impact the
performance of MFIs. The formal dimension of institutional distance consist of economic, political,
judicial rules and contracts, which create institutional differences between countries (Henisz and
Williams, 1999, Rutherford, 1994, Williamson, 1985). While the informal institutions are often
interpreted as a subsystem within the whole of the institutional context (North, 1990, Peng et al.,
2008, Williamson, 2000). It offers a deeper insight into the development of institutions and in
Williamsons’ terminology consist of customs, traditions, language, beliefs, and habits. These have
been described as the foundation of formal institutions (North, 1990, 2005, Williamson, 2000).
In this study, we focus on the individual micro-finance entity – as it typically reaches
“North” for resources and support. This implies that our perspective is one of the “global South”:
How can an MFI in the developing world benefit from internationalization despite the institutional
distance that exist between the MFI and its stakeholders? This perspective differs from the general
assumption of the international business research that typically has concentrates on multinational
firms reaching “out”. The focus of the study is on the financial performance of the MFI – being
measured in terms of real return of assets, as well as performance indicators such operational costs.
We will utilise data from 405 MFIs in 74 developing countries – assessed between 1996 and 2009 –
in order to empirically test how the performance of MFI depends on the institutional distance
between MFIs and their international cooperative partners.
2. Background on Microfinance Industry
Past research shows that the microfinance industry is subject to substantial international influence
from capital providers, knowledge providers – and cross-country networks. Specifically, a global
survey (Mersland, Randøy & Strøm, 2011) shows that 38% of the MFIs have an international
initiator, 41% have international commercial debt, 51% have international subsidized debt, 24%
have at least one international director, and 33% are members of a recognized international
network. The international capital provided comes in multiple forms – both as donations (typically
to MFIs that are nonprofit organizations) – or as loans or equity (to shareholder MFIs). The
knowledge transfer comes typically through the form of free or subsidised transfer of “best
practices”, policy guidelines, strategic planning, or even software (see
www.microfinancegateway.org for an overview). Finally, internationalisation in the industry comes
in the form of network membership – such as Accion International, Women’s World Banking,
Finca or Opportunity International.
Today all major multilateral development organizations, like the IMF, the World Bank, The
Asian Bank, the EU, the UN and the Inter American Development Bank dedicate funding and
research to microfinance. Specialized agencies like the Consultative Group to Assist the Poor
(www.cgap.org) provide the industry with specific guidelines and issue policy recommendations.
The international recognition for microfinance as a development tool culminated with the UN
declaring 2005 as the year of Microcredit and the Nobel’s peace prize being awarded to Mohammad
Yunus and his Grameen Bank in 2006.
Increasingly microfinance is becoming an attractive investment opportunity(Walter and
Krauss, 2008). Interestingly, a number of international banks such as Citibank, HSBC, Deutsche
Bank, BNP Paribas, ABN Ambro and Barclays are engaged in microfinance activities and in 2006
held a portfolio in MFIs of more than 500 million US dollars (ING, 2006). For example,
international holding companies, such as Procredit Holding with a total portfolio of nearly 400
million invested in 22 national MFIs around the globe, are emerging (Reille and Forster, 2008).
Between 2004 and 2006 the total stock of foreign capital investment in microfinance more than
tripled to US$ 4 billion, and 40 specialized international investment funds have been established
during the last couple of years (Reille and Forster, 2008).
Modern microfinance, as pioneered by Mohammad Yunus the founder of Grameen Bank in
1976, was born in a philanthropic development culture. Historically, the focus was on the build-up
of local capacity and the gradual exiting of international founders and donors. Still, several in the
microfinance community consider internationalization in MFIs to be transitional phenomena. In
their view, the ultimate goal is to build local MFIs as an integrated part of the national financial
system – with local owners and focus on relations with domestic stakeholders.
Thus, to some the inflow of international capital and expertise - increasingly with profit motives - is
a threat – or mission drift. Such arguments are commonly based on ideology or politics- and not on
empirical facts. So far, few have asked the question to what degree international cooperation
influences MFIs performance – the results from (Mersland et al., 2011) indicate that the
internationalization of MFI to a large extend enhances social performance but does not enhance
financial performance- and how the institutional distance of such cooperating affects its
effectiveness. This paper aims at filling this void.
3. Main Effects of Institutional Distance on MFIs Performance
3.1 Formal Institutions
Nations possess unique institutional environments that include formal and informal constraints on
human and organizational behavior (Scott, 1995). Formal institutions set the rules by which
economic actors have to interact (North, 1990) for instance when establishing contracts or
employment relationships. When a multinational company contemplates investing as a foreign
investor, it will be partially guided by the barriers to learning it perceives with regard to the market
conditions in that location. In similar fashion – a MFI has to consider the direct and indirect costs of
close cooperattion with institutionally very different partners. For example, for-profit MFIs with
international stakeholders will have to report to their investors – that commonly will demand a
board seat – or other kinds of monitoring mechanisms. For non-profit MFIs (NGOs), a donor from
the global North would typically demand extensive reporting – which could have significant cost
implications for the MFI. Increasingly unfamiliar formal institutional environments lead to higher
unfamiliarity hazards, to a lower propensity of building trust to higher information asymmetries
between collaborators, and to higher transaction and coordination costs (Mahoney, 1992). For
example, increasing diversity in formal institutional settings due to differing legal systems, gives
rises to higher transactions and coordination costs as it increases the costs of contracting (Chang
and Rosenzweig, 2001). Differences in formal institutions are likely to inhibit the transfer of
business practices to the party who operates under local rules (Kostova and Roth, 2002). In the
context of MFIs, differences in institutional settings impede the ability of MFIs to transfer
successful banking products from one country to another.
The required restructuring/adaptation of the organization would increase with institutional
distance, yet the legal framework may constrain restructuring, especially if this involves for
example staff redundancies, or capital restructuring. Formal institutional distance increases the costs
that the international cooperative partners of MFIs anticipate as being necessary to incur in
monitoring MFIs’ adherence to contractual obligations. In cases, that MFIs organization are
designed to fit very different formal institutional context the transfer of resources, capabilities and
capital by international cooperative partner may offer less value and productivity because of higher
costs of restructuring and adaptation.
The argument above leads to the following hypothesis:
H1) The MFI performance is negatively affected by increasing formal institutional distance between
MFI and its international corporative partners.
3.2 Informal Institutions
Informal institutions are humanly devised patterns of interaction that are not formally
codified but embedded in the shared norms, values and beliefs of a society (North, 1990, 2005).
Even without codification, they may impose powerful restrictions on individual actors, and they are
describe as the foundation for formal institutional settings and are often very persistent even in the
event of changes in formal institutions, for example by an act of legislation (ibid). Informal
institutions influence attitudes to work, perception of organisational purpose, approaches to problem
solving and conflict resolution, ways of thinking and behaving that could introduce important
barriers in the cooperation between firms from substantially different informal institutional settings.
The notion of informal institutions encompasses culture as operationalized by Hofstede (2001),
Schwartz (1994) and others (Estrin et al., 2009, Slangen and van Tulder, 2009). Knowledge about
informal institutions is often tacit (Boyacigiller et al., 2004) so that overcoming the across-cultural
differences requires intensive cross-cultural communication. As a result, individual and
organizational learning is typically rather slow. However, informal rules strongly influence
economic behaviour because they moderate, for instance, the transfer and management of
knowledge in inter-firm collaboration and headquarter-subsidiary performance (Cantwell, 2009,
Davis and Meyer, 2004, García Pont et al., 2009, Yamin and Andersson, 2011).
Bridging cultural differences requires organizational learning, but this has been shown to
relate non-linearly to outcomes and performance because of the magnitude of the impact and
tacitness of the concept (Björkman et al., 2007, Kotabe et al., 2007, Slangen and Hennart, 2008).
When cultural differences become very large, ‘the two parties collaborating may be so different as
to make it unlikely that they possess capabilities that are relevant for each other. Moreover, with
growing cultural distance, the likelihood increases that the combining firms’ practices are
incompatible and lead to implementation problems. At low levels of cultural distance, the
differences between a MFI and its international cooperative partners are elusive with few barriers
inhibiting communication. As a result, any differences that could potentially introduce problems
are not immediately addressed, or even are inappropriately addressed through the application of
unsuitable routines (Heimeriks, 2010). At intermediate levels, the cultural and societal differences
between a Microbank and its international cooperative partners are higher and more apparent
leading to wide divergence in attitudes to work, perception and problem solving practices. The costs
of communication and collaboration increase because informal institutional differences are likely to
inhibit the functioning of cooperative modes between a MFI and its international cooperative
partners. MFIs’ international cooperative partners thus find it harder and/ or even more costly to
transfer knowledge, resources and business practices that in turn can improve the MFI performance,
especially when the nature of the knowledge and practices transferred are fundamentally different
between the two parties. However, beyond a certain threshold, MFI is prepared to address any
barriers to effective collaboration arising from these differences by, for example, adopting past
routines and making higher investments in co-specialised resources and the payoff of experiential
learning leads to improved performance.
The argument above leads to the following hypothesis;
H2) The relationship between informal institutional distance and MFI performance is sigmoid, with
performance first increasing, then declining and finally increase again as informal institutions
increases.
3.3 Interaction Effects of Institutional Distance and MFI Experience
The literature has argued that through experience firms’ advance along learning curves (Argyres,
1966, Ethiraj et al., Johanson and Vahlne, 1977, Wernerfelt, 2005). These learning curve
experiences can provide a broader mind-set and a greater ability to respond to changes in
institutional factors, thereby providing institutional capital to the firm. Such learning curve
advantages are resource-based advantages that facilitate adoption of new capabilities and adaptation
of existing resources to changes in institutional environments. International business literature has
suggested that international experience may provide a firm with dynamic learning capabilities
(Chang and Rosenzweig, 2001, Madhok, 1997). Given the context of this study we expand this
notion to MFIs experience to reach out to “North” for resources and support from developed
countries and as such how its experiential/dynamic learning in doing business with the “North” will
influence its performance.
To ease cross-cultural communication, the closer cooperation between MFIs providing the
knowledge of the local business environment and their international cooperative partners providing
(for example resources and capital) can help in managing cross-cultural interfaces. Institutional
differences may best be overcome gradually by experiential learning and thus by close interaction
between individuals working directly together. We propose that MFIs experienced based learning
capabilities are an important advantage to overcome the diversity of the institutional environment of
their international cooperative partners. MFIs with lower levels of experience based learning
capabilities tend to have difficulties in interpreting, understanding, adapting to the knowledge and
resources transferred and doing business with their international cooperative partners. They are
constraint by their own internal institutional context and mechanisms and therefore their ability and
perhaps willingness to change and improve performance is restricted (Oliver, 1997). In such cases,
MFIs have difficulty internalizing needed changes that allow them to be successful and take
advantage of their international networks. In contrast, MFIs possessing higher levels of experience
based learning capabilities are much less influenced by institutional context differences with their
international enablers. These firms have the ability to overcome the “liability of foreignness”
encountered when cooperating with their international cooperative partners with differing
institutional contexts.
The above argument leads to the following hypothesis
H3) The MFI experience will positively moderate the relationship between performance and formal
and informal institutional distance.
Based on the above discussion, we apply a model of MFIs performance that incorporates formal and
informal institutional distance with their international corporative partners , and the moderating
effects of the MFI experience, and other MFI specific control variables as below;
Microbank performance = f (formal institutional distance, informal institutional distance,
moderating effect of experience on formal and informal institutional distance + MFI specific
control variables
4. Methodology
4.1 Source of Data
The dataset is a collection of 405 MFIs that have been chosen to be assessed by one of the five
leading rating agencies specialized in microfinance: MicroRate, Microfinanza, Planet Rating, Crisil
and M-Cril. Thus, MFIs’ decision to become rated by an international rating agent already indicates
that the MFI in this study is internationally oriented. Comparisons of the rating methodologies
applied by the five rating agencies reveal no major differences on all applied variables in this study.
The five microfinance rating agencies differ in their emphasis and the extent of provided
information. Thus, there are a different number of observations related to different variables. When
needed, all entries in the dataset have been annualized and dollarized using official exchange rates
at the given time. The rating reports, that represent the basis for the constructed database, are from
1996 to 2009. The dataset comprises MFIs from 74 countries. This dataset provides an extended up-
to-date version of the dataset used in previous studies (see Mersland et al., 2011, Mersland and
Strøm, 2009, 2010).
The rated MFIs we analyze have a number of legal and organizational forms; but three
forms stand out: they are non-profit organizations, member-based cooperatives, or shareholder
controlled firms with various degrees of profit motivation. In addition, the universe of microfinance
providers consists also of other organizational and legal forms. For example, throughout the world,
there are a large number of informal rotating savings and credit associations (ROSCAs) that have
been initiated by the poor (Ambec and Treich, 2007, Bouman, 1995) or have been promoted by
donors (Allen, 2006). At the same time, it is also common to see government ownership of different
types of rural, agriculture, development, and postal banks (Christen et al., 2004). However, none of
these institutions is formal private suppliers of microfinance services with an interest in becoming
rated by a third party. Moreover, our approach also implies that we exclude numerous small savings
and credit cooperatives, and development programs that offer microcredit solely as a welfare
service (non-sustainable). We argue that the 405 MFIs in our dataset represent commercial and
professionally oriented institutions that have decided to be publicly rated with the motivation to
improve access to funding, benchmark themselves against others, and to increase transparency (see
www.ratingfund2.org). It must also be noted that our dataset only accounts for rated MFIs. We
will argue that using MFIs that are internationally rated has at least four advantages compared to
data from commonly used databases of MFIs, such as Mix-market (www.mixmarket.org). First, raw
data (the rating reports) are publicly available at www.ratingfund2.org, second, several more
variables, especially variables relevant for this study like international initiator and membership in
networks are available from the rating reports. Third, the data is not self-reported, as in Mix-market,
but collected and verified by a third party (the rating agency). Fourth, a bias towards large MFIs is
avoided. Mixmarket data includes most of the very large MFIs, whereas the rated MFIs used in this
study have a wider distribution in terms of size. Several, but not all, of the largest MFIs in the world
do not undertake microfinance rating reports because they instead undergo traditional rating from
agencies like the Standard & Poor’s. The size bias in the Mixmarket data is therefore smaller in our
dataset (Table 1). Therefore, we suggest that a dataset built on rating reports is more representative
for the industry than the Mixmarket sample.
--------------------------------------
Insert Table 1 about here
--------------------------------------
4. 2 Dependent and Independent Variables
We measure financial performance of the MFI (dependent variable) in terms of real Return
on Assets (ROA), and additionally include operational expenses ratio relative to assets (OEA). Our
main indicator of financial performance is ROA, as it “summarizes” the financial success of the
MFI. These measures have been used in previous studies (see Mersland et al 2011, Mersland and
Strøm 2009, 2010). Whereas return on assets is both driven by costs and income – the operational
costs is interesting - as it is not “distorted” by the competitive environment of the MFI. This is
particularly important - as the competitive environment can be significantly different from country
to country (as also indicated by the Economist Survey 2010).
The independent variables Formal institutional distance concerns laws and rules that
influence business strategies and operations. To measure this dimension we proxy the formal
institutions by items of the economic freedom index developed by the Heritage Foundation (also see
(Meyer et al., 2009). This index provides information about a broad notion of institutions, focusing
on the freedom of individuals and firms in a country to pursue their business activities. This index
has been used in its aggregate form in previous studies (Bengoa and Sanchez-Robles, 2003,
Berggren and Jordahl, 2005, Meyer et al., 2009, Stroup, 2007). Our theoretical considerations
suggest that our concept of institutions focuses on institutions that support market efficiency.
Freedom House provides aggregate values of the overall quality of formal institutional indicators
for most countries in the world since 1995. The aggregate annual values include evaluations of a
country’s business, trade, investment, financial freedom and property rights system. For each of the
MFIs in our dataset we computed the formal institutional distance by using the absolute value of the
average differences between the annual values for the countries of international cooperative partners
and the values for the countries of each MFI.
Informal institutional distance between countries concerns rules embedded in values, norms
and beliefs (North 1990, 2005). Empirical studies have employed the index developed by Kogut
and Singh (1988), on the basis of Hofstede’s (1980) work on national culture, to capture informal
institutional distance for example on entry mode decisions (Barkema et al., 1996, Kogut and Singh,
1988, Slangen and Hennart, 2008, Slangen and van Tulder, 2009). Recent evidence also suggests
consistency of results with those attained using other cultural distance measures (Kim and Gray,
2008). We extend this argument to our analysis of MFIs, and measure cultural distance using Kogut
and Singh’s (1988) index 6 .
(Cultural distance j ) = ∑=
4
1i
{ } 4/ V/)( 2
iiuij II −
where I ij stands for the index for the ith cultural dimension 7 and jth country, V i is the variance of
the index of the ith dimension, u indicates the nation from which the cultural distance is calculated
(which is the UK in this paper) and (cultural distance j ) is the cultural distance of the jth country
from the country of the international cooperative partner.
The MFIs experience reflects the number of years since they started their operations. Hypothesis 3
is tested through the estimation of moderating effect of MFIs on formal and informal institutional
distance.
We also apply MFI control variables that are typically included in recent microfinance performance
research (Cull et al., 2007, Mersland et al., 2011, 2009, 2010). We include the following
organization-specific (MFI) control variables, international initiator, member of international
network, type, assets (size), regulation, and average loan (in the financial performance regression).
For the discussion on all variables, see Table 2.
--------------------------------------
Insert Table 2 about here
--------------------------------------
5. Discussion of Results
Table 3 provides descriptive statistics for the variables used in this study. Table 4 highlights the
correlation matrix. None of the correlation coefficients in the table is of high magnitude (see
(Kennedy, 2008) p. 196). Table 5 reports of the random effect specifications using the generalised
least squares in panel data estimation on 405 MFIs. The choice of random effect model was
determined by the nature of variables used in this study, which are mainly time invariant as well as
our robustness check that reviled a weak support for the effect of the institutional distance on MFIs
performance using the fixed effect specification. This suggests our hypothesised relationship
between institutional distance and MFIs performance to be a stronger determinant of variation in
MFIs performance across firms rather than within firms over time. M1 in Table 5 highlights the
results for only the main effects and MFI control variables having ROA as the dependent variable
while M2 reports on the full model including moderating terms. M3 reports on the main effects and
MFI control variables taking into account OEA as the dependent variable while M4 reports on the
full model.
--------------------------------------
Insert Table 3 and 4 about here
--------------------------------------
Table 5, M1 and M2 show that formal institutional distance between MFIs and their international
cooperative partners is significant and negatively affecting ROA this is caused by the direct and
indirect costs of close co-operation with institutionally different partners. However, the results are
not statistically significant on OEA although negatively signed. These sets of results confirm H1.
The effects of informal institutions on MFIs performance are significant, first increasing, then
declining and finally increasing again as informal institutions between MFIs and their cooperative
partners increases in all models supporting H2 . Our results support the sigmoid effect of informal
institutional distance on MFIs performance, with the inflection point being at 3.2 levels of informal
institutional distance. This suggests that the MFIs in our sample start experiencing substantial
decrease in their performance after their exposure to international cooperative partners introduces
informal/cultural divergence higher than 3.2 points. It is worth noting that as informal institutional
distance increases further the effects on MFIs performance become greater as the significant and
positive coefficient of the cubic term for informal institutional suggest in M 1 to M3. However, this
effect becomes close to asymptotic, as the positive coefficient of the cubic term for informal
institutional distance in M4 is only marginally significant. The results in M2, incorporating
moderating effects of experience confirm H3. We find significant and positive sign for the effect on
experience on informal and informal institutional distance. These significant results confirm that
MFIs experience helps them to overcome the institutional differences with their international
cooperative partners and improve their performance. This is due to the MFIs high levels of
experience based learning capabilities gained from previous transactions with their international
cooperative partners that enables them to interpret, understand, and adapt to the knowledge and
resources transferred from their international cooperative partners which in turn will positively
affect their performance. However, we only find a positive significant sign for the moderating effect
of experience on iformal institutions in M4.
The MFI control variables in regards to the international initiator revealed a positive and
significant effect on both measures of MFI performance (ROA and OED) in all models. The MFIs
membership in an international network also significantly and positively affects the performance of
MFIs in all models except M1. These results indicate that international influence from the
developed economies enhances the accounting performance of MFIs captured by ROA and OEA.
These results extend the finding by Mersland et al., (2011) as they only find a positive and
significant effect of internationalisation on non financial performance of MFIs. We find the
regulation of the MFIs by the banking industry did not improve their performance this variable is
significant and negatively signed in all models. We only find significant and a positive sign for the
type of MFIs (MFIs being part of shareholder firms) in M3 and M4 to enhance their performance.
We note that M2 has the highest value for R2 (0.261), as seen in Table 5, and therefore seems the
most preferable model based on the regressions. Overall, in the light of these results, the regression
specifications appear to have both acceptable explanatory and predictive abilities.
--------------------------------------
Insert Table 5 about here
--------------------------------------
Figure 1: Sigmoid Effect of Informal Institutional Distance on MFIs Performance
6. Conclusion
This study revels that key dimensions of institutional distance both formal and informal institutions
affect the financial performance of MFIs. Our overall conclusion is that formal institutional distance
negatively affected the performance of MFIs while the effect of informal institutions on the MFIs
performance was sigmoid, with performance first increasing, then declining and finally increasing
again as informal institutional distance increases. The experience of MFIs has positive moderating
effects in overcoming the formal and informal institutional distance and improving the performance
of MFIs. One of the implications of our findings relates to the management and choice of
international cooperative partners of MFIs. A desire to form partnership with international partners
from distant institutional settings should be balanced out with international partners from proximate
institutional settings, so that institutional distance in MFIs portfolios of internationalisation
exposure remains at manageable and effective levels. However the more experiences MFIs are
better positioned to benefit from moving down the experience curve to reduce their costs of creating
value and increase their profitability.
These results are particularly interesting in relation to microfinance debate. The more profitable
seeking microfinance industry is better able to serve the poorest members of the community since
their profit motives leads them to be more efficient and more willing to seek out new markers for
their loans (Hermesa and Lensink, 2011, Morduch, 2000). This in turn will strike a balance between
the logics they combine (financial and social performance).
This study addresses the call for closer investigation of international influences on financial
performance of MFIs (Mersland et al., 2011). This is an import investigation in an increasingly
internationalised industry where most MFIs struggle to become financially viable; there is certainly
a need for understanding the elements that can enhance the MFI’s financial performance and not
only their social outreach. This study contributes to MFIs research by considering the effects of
formal and informal institutional distance between MFIs and their international cooperative partners
and the moderating effect of MFI experience on overcoming such divergences. This study also
contributes to application of institutional economies developed by North and recently applied to
multinational enterprises by Dunning and Lundan (2008a, 2008b) as a valuable insight for
theorizing about MFIs performance. Furthermore this study provides empirical evidence to illustrate
the effect of institutional distance relaying on the Northian strand of institutional theory to
distinguishes formal and informal distance on MFIs performance thus respond to calls to develop
institutional theory more rigorously without blending arguments (Estrin et al., 2009, Gelbuda et al.,
2008).
One of the limitations of this study resonates to the calculation of informal institutional distance
based on Hofstede’s cultural indicators. There has been a lot of criticism about the accuracy and
comprehensiveness of Hofstede’s cultural indicators in the international business literature, which
raise concerns about the extent to which our measures can capture all the tacit and elusive
dimensions of cross-national divergence arising from societal, national and other elements of
culture.
Table 1: Comparing data from Mixmarket and rating reports (this data)
Mixmarket (2006) Rating reports 704 MFIs 405 MFIs
Variables Mean Median Mean Median
Age (years) 12 9 14 13 Total assets US$ 45,566,650 6,169,918 6,348,701 2,672,081 Total staff # 400 94 85 49 # Active loan clients 73564 10102 12543 4878 Gross loan portfolio US$ 33,072,688 4,438,677 4,276,508 1,972,629 Average outstanding loan US$ 1026 456 731 387
Table 2: Variables used in the study
Variables Explanation/definition Hypotheses
Dependent
variables Dependent variables included in
the study
ROA Operational net income divided on average annual assets and adjusted for country inflation
OEA Operational expense ratio related to annual average total assets
Independent
variables Independent variables included
in the study
Formal institutional distance Absolute differences between MF country of origin and its international
-
Informal institutional distance (Cultural distance j ) =
∑=
4
1i
{ } 4/ V/)( 2
iiuij II −
Sigmoid
MF experience The years since the MF started microfinance operations
Moderating effect of experience on formal and informal institutional distance (+)
MF control
variables
MFI level control variables
included in the study
International initiator Whether or not the MFI was initiated by an international agent Yes = 1, No = 0
Member international network
Whether or not MFI is a member of an international microfinance network
Yes = 1, No = 0
type Whether or not MFI is a shareholder firm or a non-profit firm Yes=1, No=0
Regulation Whether or not the MF is regulated by banking authorities
Assets The natural logarithm of the MF’s assets
Average loan Average outstanding loan per loan client
Table 3: Descriptive statistics
Mean Std. Dev. Min Max Obs
Dependent variable
ROA 0.008 0.126 -0.990 0.342 1518
OEA 0.218 0.156 0.016 1.712 1268
Independent variable Informal institutional distance 0.452 1.076 0.000 6.435 1617
formal institutional distance 14.244 11.336 0.000 76.550 1616
MF experience 14.401 6.807 3.000 86.000 1605
MF Control variables
international initiator 0.389 0.488 0.000 1.000 1600
international network 0.341 0.474 0.000 1.000 1595
regulation 0.283 0.456 0.000 3.000 1568
average loan (US$) 731 1221 2016 24589 1492
assets 6.425 0.588 4.285 8.395 1585
type 0.399 0.473 0.000 1.000 1606
Table 4: Bivariate Correlation Matrix
1 2 3 4 5 6 7 8 9
ROA 1
OEA -0.330* 1
formal institutional distance 0.032 0.044 1
informal institutional distance 0.071* 0.036 0.163* 1.000
MF experience 0.049 -0.109* 0.355 -0.036 1.000
international initiator *-0.031 0.172* 0.408* -0.060 -0.113* 1.000
international network 0.058 0.166* 0.317* 0.226* 0.087* 0.300* 1.000
regulation 0.002 -0.153* -0.055 -0.056 0.021 -0.020 -0.095* 1.000
assets 0.286* *-0.240 -0.017 -0.022 0.294* 0.024 0.1420* 0.183* 1.000
type -0.057 -0.060 -0.076 -0.150* 0.109* 0.060* 0.087 0.370* 0.146*
outstanding loan 0.004 -0.000* 0.022 0.222* -0.003 -0.033 0.035 -0.025 0.019
Table 5: Results
ROA (M1)
Interaction (M2)
OEA (M3)
Interaction (M4)
Coef Std. Err Coef Std. Err Coef Std. Err
Coef Std. Err
formal institutional distance -0.001** 0.000 -0.002** 0.001 -0.003 0.001 -0.004 0.001
informal institutional distance 0.134*** 0.048 0.172*** 0.053 0.055** 0.129 0.091** 0.103
informal institution square -0.077*** 0.025 -0.077*** 0.027 -0.029** 0.068 -0.038* 0.033
Informal institution cubic 0.008*** 0.003 0.009*** 0.003 0.003* 0.008 0.004* 0.004
MF experience -0.002** 0.001 -0.001** 0.002 0.001 0.001 0.007** 0.003
experience*informal IND 0.005** 0.010 -0.001 0.001
experience*formal IND 0.000** 0.000 0.004** 0.003
international initiator 0.014*** 0.008 0.011** 0.036 0.041** 0.012 0.041** 0.015
international network 0.011 0.012 0.013** 0.036 0.059*** 0.011 0.056*** 0.015
regulation -0.015** 0.011 -0.022** 0.011 -0.032** 0.014 -0.032** 0.014
assets 0.085*** 0.008 0.087*** 0.008 -0.081*** 0.010 -0.081*** 0.010
type -0.021 0.007 -0.001 0.007 0.037*** 0.008 0.034*** 0.008
average loan 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000
cons -0.498*** 0.053 -0.514 0.047 0.717** 0.062 0.711** 0.064
n 1341 1132
overall R2
0.163 0.261 0.132 0.212
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