Microfinance institutions and poverty reduction: a cross regional analysis.
Javid, Attiya Yasmin ; Abrar, Afsheen
The present study investigates the role of microfinance
institutions (MFIs) to reduce poverty by reaching the poor, financial
sustainability and reaching women for 382 MFIS operating in seventy
countries located in six regions of the world from 2006 to 2012. The
results show the fact that the smaller is the size of loan, the higher
is the interest charged on these loans. The small size of loans
symbolise that MFI is targeting poor customers and help in declining
poverty. When the average loan size is small, the MFIs can serve a large
number of poor that is breadth of outreach is wide. Therefore the number
of active borrowers and women borrowers has also shown significant
positive impact on poverty reduction. As regard result of lending type
shows that group lending compared to individual generally charge
significantly low rates of interest and no collateral showing that group
lending increase outreach and reduces poverty. In legal status NGOs give
small loans, charge high interest rate and have larger number of client
especially women thus have role in cutting poverty. The results of other
factors like MFI size, capital structure, risk, profits are positive,
risk and regulation, are negative and significant contributor of
outreach generally in all regions. The overall results of the study
indicate that as depth of outreach is inversely related with the cost of
outreach and positively with sustainability. However, breadth of
outreach has significant positive relation with cost of outreach and
sustainability. These results indicate that in most of the regions and
around the world financial sustainability and outreach has trade off.
The implication of these results is that there is need of both outreach
and sustainability in order to cut poverty and survive in future. The
microfinance industry is required to be sustainable by reducing its
transaction, operational and administrative cost against its lending
interest rate and average profit.
Keywords: Outreach, Interest Rate, Financial Sustainability, Women
Outreach, Average Loan Size
1. INTRODUCTION
The alleviation of poverty is one of the most debated issues among
the academicians and policy makers. From 1950s to 1980s the poverty
reduction program has been based on increase the participation of poor
into the economy by better macroeconomic performance. Though the poor
part of population mostly engaged in informal sector (1) is identified
by researchers but has not become the part of economic models and
government policy [Robinson (2001)]. Poverty reduction has been
institutionalised in 1944 when World Bank was set up. The World Bank
worked through governments and institutions by giving loans to
developing countries called structural-adjustment programmes. These
programmes were highly unsuccessful, created dependence on aid with
little help to poor part of societies [Murduch (1999) and Diop, et al.
(2007)].
This failure due to distrust in formal institutions give the
beginning of a shift in development thinking that leads to the emergence
of microfinance. The focus is support of the informal sector by
providing credit to help people to pull them above the poverty line.
Microfinance helps these informal micro-enterprises through
micro-credit. The micro-credit approach to poverty reduction is
"the provision of small loans to individuals, usually within
groups, as capital investment to enable income generation through
self-employment" [Weber (2006)]. The informal businesses of poor
are referred as a type of un-met demand for credit. Poverty is
considered as the outcome of market failure, (2) microfinance would
correct the market failure, providing access to credit to the poor.
Credit would create economic power that would generate into social
power, lifting the poor out of poverty [Yunus (1999)].
Thereafter, microfinance is considered as an important tool for
reducing poverty. (3) These developments have generated high
expectations from the microfinance programs to alleviate poverty effects
among donors and policy makers and aid organisations. However, latter it
is recognised that microfinance programmes can play long term and
significant role to reduce poverty, MFIs need to be successful in
extending loans to poor borrowers, while at the same time being able to
at least cover the costs of their lending activities, i.e., they may
need to focus on being financial sustainable in the long run"
[Armendariz and Labie (2011)].
MFIs are facing a double challenge in reducing poverty: they have
to provide both financial services to the poor (outreach) and also cover
their costs in order to avoid bankruptcy (sustainability). This is the
main motivation to assess MFIs' both dimensions to deal poverty
that are taken into account in the present paper.
The present study tries to answer this question by analysing
whether microfmance institutions have played some role in reducing
poverty in six regions and around the world. The main focus of this
study is to find out the determinants of outreach in microfinance
industry. The study explores the dimension of outreach depth or breath
of outreach, cost of outreach and expected future outreach that are more
meaningful in alleviating poverty. The impact of institutions specific
factors like cost, profitability, and MFI age, MFI size, lending
methodology, regulation and risk on the outreach of MFIs are
investigated. The country specific factors such as economic conditions
of the country and regional dummies are also included to examine their
impact on outreach in six regions of the world.
The study contributes to the existing literature by investigating
depth, breath and cost of outreach of MFIs in reducing poverty,
increasing empowerment opportunities and maintains sustainability in
microfinance institutions. It also highlights that the tradeoff is
required by MFIs in outreach and sustainability in order to perform
microfmance activities for a longer period of time. Since the cost of
outreach is higher that demands an optimal level of profitability that
can be generated through efficient management of MFIs through cost
reducing on regular basis. This study also signifies that age, size,
regulation, lending methodology, legal status and geographic location of
MFIs, human development index and population density to capture country
specific factors also affect their outreach.
After brief introduction the remainder of the study is organised as
follows. Section two reviews the relevant literature on the role of
microfmance on poverty alleviation. Methodology and data used in the
analysis is discussed in section three. The empirical results and their
interpretation are provided in section four and last section offers
conclusion.
2. LITERATURE REVIEW
A large number of studies on the impact of microfmance in poverty
reduction has been conducted especially in developing countries in past
few years with the growth of microfmance institutions in these
countries. There is wide range of evidence that suggests that
microfmance increase income, increase business profits and lift the
people out of poverty. In contrast there are studies which supports the
contrast view that microfinance programs are successful in reducing
poverty in few regions like Asia and Latin America but not in every
region. This section provides the brief review of the most relevant
studies done in this area.
Olivares and Polance (2005) have analysed average outstanding loans
used as proxy for depth of outreach, as dependent variable with other
explanatory variables like age of institution, lending methodology,
sustainability, competition, and gender. Their results reported negative
relationship between age and loan size which means that older MFls give
loan of small sizes. Another study conducted by Mersland and Strom
(2009) document that average loan size is a main proxy of serving the
poorest of the society. They find a positive relationship between
average profit and average loan size indicating that the increase size
of loan represent increase urge for profit by MFIs. Christen and Drake
(2002) show a positive relationship between depth outreach measured by
average loan size with profitability. Their study empirically support
that MFIs in Latin America are most profitable, as their profitability
is the mixture of three properties; large loan size, competition and
regulations.
Wagenaar (2012) has worked on institutional transformation and
mission drift in microfinance institutions. According to him, there is
huge pressure from donors on microfinance institutions to be profitable.
Due to this reason some MFIs have transformed from non-profit to profit
oriented institutions. He argues that financial sustainability may lead
toward less reaching to the poorest of the poor. Results show that
transformed MFIs have significantly higher loan size and have lower
percentage of female borrowers. This shows that transformation effects
outreach that cause deviation from social mission towards profitability.
Cull, et al. (2011) investigate regulated and non-regulated microfinance
institutions. The results show that regulated MFI has high loan size
than non-regulated NGO type microfinance institutions. The operating
cost increases as loan size decreases by lending to poorer segment. To
minimise or absorb this operating cost MFI are more tempted towards
better off clients and restrict outreach to poorer segment and increases
loan size is reported. Therefore, regulated microfinance institutions
are more likely to experience deviation from social mission than
nonregulated NGO type institutions.
Rashid, et al. (2011) find positive impact of microfinance on
poverty alleviation. They show that increased fund, lower interest rate
and accessible financial services made microfinance important and
effective for poverty reduction. Another study of Zacharias (2008) shows
that average cost and efficiency goes in opposite direction. He has
addressed the issue of economics of scale in microfinance institutions
and finds evidence of scale efficiencies. His study focuses on the
operational cost and size relationship finds that bigger firm is
associated with smaller cost. The study finds that average loan size and
average cost are negatively co-related thus suggesting that increase in
average loan and firm size reduces the operational cost.
Robert, et al. (2011) examine the tradeoff between outreach and
efficiency of MFIs. They find that MFIs operating in countries with good
financial development are more efficient. They find that outreach is
negatively related with efficiency suggesting that MFIs with small loan
size are less efficient. Their findings showed that efficiency can only
be obtained when MFI will focus less on poor segment.
Cull, et al. (2007) find not a significant relationship between
loan size and profitability. For individual lender results reveal that
higher profit leads towards lower outreach resulting in crowding out the
poorer clients. Village micro banks put more focus on advancing small
loans to the very poor and bear high average cost and receive more
subsidies. Few individual lending institutions strive best for both
profitability and higher outreach to the poor; fulfilling their ultimate
promises, but these are exceptional cases. Finally their results showed
that MFIs with higher profits lead toward weak level of outreach and
kicks out the very poor from financial schemes.
Armendariz and Szafarz (2009) empirical work on Latin America and
south Asia show that poverty oriented MFIs may not serving poor neither
because of progressive lending nor because of cross subsidisation. It is
not only the result of transaction cost but also due to their own
mission fulfilling strategy and other region specific characteristics.
According to their findings if all loans are identical then transaction
cost only affects the number of loans not the size of loan. Secondly if
there are two types of clients, poor and unbanked wealthier clients,
having different transaction cost then mission drift on the loyalty of
MFIs with outreach maximisation objective. Finally MFIs may use unbanked
wealthier clients for purpose of cross subsidisation for poor showing
strong commitment with outreach.
Ghosh and Tassel (2008) observe that MFIs may drift from their
mission and start focusing on profitable less costly borrowers in order
to attract more profit oriented investors. Their results show that
funded by profit oriented donors charge higher interest rates. According
to their findings poverty gap ratio is the reason for not reaching the
poor. Higher interest rates are mainly due to very heavy transaction
cost that arises when lending small amounts to poor people is observed
by Gonzalez (2010). He further states that Microfinance interest rates
normally range between 20 to 70 percent per year, depending on the
nature of the activity, however they can touch very high level, as high
as 90 percent per year. Strom and Mersland (2007) find no significance
difference between nonprofit organisation and shareholder owned MFIs in
terms of financial performance and outreach. They do not find any
evidence that shareholder owned firm produces more better results in
terms of outreach or profitability than nonprofit organisations. So
their study clearly indicates that it is MFIs own vision and mission
that make MF1 good or bad at becoming profit orienting or setting
maximum outreach as basic objective. They find that group lending is
expensive but results in maximum outreach; on the other hand individual
lending is better for financial sustainability. In defining the
sustainability of MFIs the role of interest rates cannot be
under-valued.
Fernando (2006) shows that the Human Development Index (HDI) is a
measure that ranks countries on the basis of human development. It has
four levels ranging from "very high, "high,
"medium", and "low, human development countries. This
Index relatively measures of education, literacy, standards of living
and life expectancy for countries worldwide. According to Kai (2009) for
measuring the impact of economies of scale, another explanatory variable
population density has been introduced, the higher value of the index
shows, more population concentration. The value can range from 0 (the
population would be equally scattered all over county or region) to 100
(all population would be concentrated in one area of the country or
region) considering the effect of economies of scale, a higher value of
index may lead to reduce the operational costs, thus increasing
productivity. Add a line about the findings of HDI and PDP in two
studies.
3. METHODOLOGY AND DATA
The poverty is reduced by reaching the poor and long term serving
the poor that is possible when MFls' are financially sustainable,
therefore both outreach and financial suitability is investigated in
this study.
3.1. Methodological Framework
The main focus of this study is to examine that microfinance
institutions are playing their role to reduce poverty. The microfinance
institutions objectives include; outreach to the poor and institutional
financial
sustainability that is long run expected outreach to cut poverty
[Zeller, et al. (2002) Schreiner (2002)]. The different dimensions of
outreach are discussed in the literature Schreiner (2002) and followed
by several studies investigating outreach and financial sustainability
Mersland and Strom (2008); Woller (2006); Woller and Schreiner (2002)
and many recent studies and used by performance evaluation and impact
assessment studies by donors like USAID [Mersland and Strom (2008)].
The breadth of outreach indicates the number of poor participate in
microfinance program. (4) It is expected that the larger the number of
borrowers the better the outreach and more the poorest population is
served. The number of active borrowers is used to capture breadth of
outreach in the present study. The depth of outreach captures the value
of net gain of a borrower as a client of MFI programme and it is based
on the argument that outreach must be measured not just by total number
of borrowers but on the number of poor borrowers, (5) as their relative
level of poverty is also considered. The average loan size has been used
as a proxy measure of breadth of outreach and smaller loans indicate
poorer borrowers are served, all other things being equal. (6) The
average loan size captures the depth of outreach in the present study
following Schreiner (2001) and others.
The cost of outreach to an MFI client refers to interest rate paid
and other related costs as a result of receiving financial services from
MFIs. The cost of outreach is the highest amount the borrower would
agree to bear to get the loan [Navajas, et al. (2000)]. Therefore, all
things being equal, the less the cost of outreach the more clients are
willing to borrow. Interest charges are used as a measure of cost to
clients [Mersland and Strom (2008) and others].
The Financial sustainability is the ability of MFI to cover all its
operating and financing costs from revenue mostly from the return of
loans portfolio [Tellis and Seymour (2002) and Thapa, et al. (1992)].
The amount of return will depend on the interest rates charged and the
volume of loan outstanding which in turn depend on average loan and the
number of loans remaining outstanding. This would mean that, all things
being equal, the more clients MFIs have that take loans, at the same or
higher interest rates the higher the revenue. On the other side the
higher the cost incurred to serving its clients would mean a reduced
profitability to an MFI. This implies that in order to achieve
sustainability, the MFIs that target poorer borrowers must charge higher
interest rates [Conning (1999)]. Charging higher interest rates, which
could lead to profitability, may however, price the poorest out of the
microfinance services and thereby adversely affecting the attainment of
the social objective of the MFIs [Morduch (2000)].
Most participants in the informal sector are believed to be women
[Liedholm and Mead, (1995)]. Although female are about 50 percent of the
world's work force, and contribute about 67 percent of the
world's work, but only 10 percent of the world's wages are
earned by them and belong 1 percent of its wealth. Most female are doing
same work as male do, but females face more poverty within the household
than male, but their work is mostly not visible nor paid [Fernando
(2006b)]. It is believed that providing credit to the women by MFIs will
reduce the poverty of the household.
The following models are estimated to examine the effect of MFI
specific factors and country specific factors on the number of active
borrows and average loan size. The number of active borrowers indicator
of breadth of outreach is adopted by Armendariz, et al. (2011) and other
studies. Average loan size is also widely.
In Equation (1) AB is the number of active borrowers which measures
the breadth if outreach (7) and it is related with the capital
structure, average profit, average cost, size of MFI, age of MFI,
portfolio at risk. A set of dummy variables include: group lending will
take 1 and zero for individual lending, NGO is 1 and zero if MFI has
other legal status, operates in rural market take 1 and zero for urban
market, regulated take 1 and unregulated zero. To measure country
specific difference Human Development Index (HDI) and Population Density
per square meter (PDP) are used. HDI is a measure that ranks countries
on the basis of human development. It has four levels ranging from
"very high, "high, "medium", and "low, human
development countries. This Index relatively measures of education,
literacy, standards of living and life expectancy for countries
worldwide. For measuring the impact of economies of scale, another
explanatory variable population density has been introduced, the higher
value of the index shows, more population concentration. The value can
range from 0 (the population would be equally scattered all over county
or region) to 100 (all population would be concentrated in one area of
the country or region) considering the effect of economies of scale, a
higher value of index may lead to reduce the operational cost.
Due to interdependence of number of active borrowers, average loan
size, interest rate and financial sustainability, these four models are
estimated simultaneously given below:
[MATHEMATICAL EXPRESSION NOT REPRODUCIBLE IN ASCII] (4.1)
[MATHEMATICAL EXPRESSION NOT REPRODUCIBLE IN ASCII] (4.2)
[MATHEMATICAL EXPRESSION NOT REPRODUCIBLE IN ASCII] (4.3)
[MATHEMATICAL EXPRESSION NOT REPRODUCIBLE IN ASCII] (4.4)
The six regions are expected to be different in depth of outreach,
its breadth, women outreach, cost of outreach and financial
sustainability as indicator of future outreach. Therefore all four
models reported above are estimated by including regional dummies. Among
the six regions: Eastern Europe and central Asia. South Africa, South
Asia, East Asia and Pacific, Latin America and the Caribbean, and Middle
East and north Africa, the Eastern Europe and central Asia is taken as
base category.
As this study uses the information for 382 microfinance
institutions belonging to six regions over the period for the period
2006 to 2012, the panel data estimation technique is suitable for this
purpose. Empirical researches on possibly encounter two sources of
discrepancies, missing variables and endogeneity biases and these models
have simultaneity as well. The generalised method of moment GMM
estimator is more suitable as it deals with the problems. The
generalised method of the moment model suggested by Arellano and Bond
(1991) and modified by Blunder and Bond (1998) is used as the estimation
technique. The lag explanatory variables are used as instruments and the
Sargen test is used to test the validity of the instrumental variables.
3.2. Data
The data has been collected for 382 Micro finance institutions,
located in 70 countries throughout the six regions of the world
including: The six regions Eastern Europe and Central Asia, South
Africa, South Asia, East Asia and Pacific, Latin America and the
Caribbean, and Middle East and North Africa. The data is on annual basis
covering the period 2006 to 2013. The data is from Microfinance
Information Exchange (Mix) which is an authentic source providing
uniform data all over the world.
4. EMPIRICAL RESULTS
The effect of microfinance institution specific and country
specific factors that influence outreach to the poor and being financial
sustainability that is expected outreach of these instructions in the
long run to cut poverty. The panel data is used and generalised method
of Moments of Blunder and Bond (1998) is applied as estimation
technique. The analysis begins with the distribution of MFIs among
different regions, type, regulated or unregulated and on the country
level are presented in Table Al, A2, A3 and A4 in Appendix respectively.
The results of factors determining the breadth of outreach are
reported in Table 4. 1. The cost per borrower has negative and
significant effect on total number of active borrowers in almost all
regions and worldwide. Therefore, as cost increases MFIs serve less
borrowers by giving larger loans to fewer clients. This is also consist
with the Yunus (1999) observation that increasing cost may reduce micro
loans to the core poor clients. The results also confirm by other
studies including Mersland and Strom (2009). The age of an MFI has
positive impact on number of active borrowers which is significant for
almost all regions and also collectively indicating mature firm have
more active clients. The large sized of MFI serve more active borrowers
in all regions and collectively. The risk of repayment is inversely
related to breadth of outreach but significant in Eastern Europe, Latin
America and in world. Regulated firm have less clients but negative
relationship is significant in South Asia, Latin America and in all
regions together. Group lending relative to individual has positive
effect in Africa, Latin America and worldwide showing that group lending
increase the breadth of outreach When MFIs operate in rural markets the
number of client increases and this increase is significant in Eastern
Europe, Africa, Latin America and overall in six regions. Capital
structure has no impact on the breadth of outreach. Increase in human
development, population density also increases client served but this
relationship is significant in South Asia and worldwide. The results
show that financial sustainability is positively and significantly
related with the total number of active borrowers in South Asia, Latin
America and Eastern Europe and overall regions. This means as increase
in the number of borrows increase sustainability. The result is also in
line with the results of Logotri (2006) but in contrast with Marsland
and Storm (2008).
The results reported in Table 4.2 are the factors that affect depth
of outreach measured by average loan size. The result shows that an MFI
is able to earn higher profit when loan size is larger. This is in
conformity with Yunus (1999) argument that big loan size creates more
profit and this thing crowd out the poorer clients from credit scheme
[Christen and Drake (2002)]. The loan size increases with increase in
cost significantly in Latin America and worldwide, MFIs are needed to
increase efficiency to minimize cost and to avoid mission drift. When an
MFI is efficient, its cost is low and loan size is also small. This
result is also in line with the cost findings of Mersland and Strom
(2011), Freixas and Rochet (2008). The results indicate that average
loan size increases as size of the MFI increases in all regions. This
result is supported by Mersland and Strom (2011). MFI maturity has
positive impact on loan size and significant for South Asia, Middle
East, Latin America and worldwide. The results show that financial
sustainability has positive and significant effect on average loan size.
As average profit increases loan size also increases and as average
profit decreases average loan size also decreases. The result is
consistent with the findings of Mersland and Strom (2011) and Freixas
and Rochet (2008) model.
The cost of outreach to an MFI borrowers is captured by real
interest rate paid and other related costs as a result of receiving
financial services from an MFI. The real interest has two sided affects;
interest rate provides financial support and income to the MFI and on
the other hand it increases cost of a loan facility to the poor. It
inhibits the poor from accessing financial services. There is a relation
between cost and interest rate. It is expected that increasing cost will
increase the interest rate in order to cover the cost and be financially
sustainable on the one hand [Dlamini (2012)]. On the other hand, the
less the cost of outreach the more borrowers are willing to get loan
from the microfinance and smaller are loan size other things being
equal. [Mersland and Strom (2008)]. The results of determinants of
interest rate that is measure of cost of outreach are displayed in Table
4.3. The results show that in all six regions and worldwide average loan
size is inversely related with interest rate. Higher cost leads to less
reaching the poor. Sustainability is positively related to interest
rate. Size of MFI does not affect the interest rate in all regions but
in all regions together it has small but positive and significant effect
on interest rate. Risk of repayments negatively impact interest rate
except Eastern Europe. Capital structure, group lending compared to
individual, rural market compared to urban and regulation are not
significant contributors of cost of outreach. PDP and HDI have no role
on the interest rate charged from borrowers.
In Table 4.4 presents the results of factors contributing to
financial sustainability. The results indicate that the cost per
borrower reduces the financial sustainability of the MFIs as suggested
by the accounting theory that costs reduce profitability. This result is
also supported by Conning (1999) that MFIs with higher costs per dollar
loaned are less profitable and therefore, less financially sustainable.
As the case of type of lending group lending has positive effect on
sustainability and this is supported by the theory that MFI prefers
group lending that ensures repayment and increase financial
sustainability. This finding is in line with Hartarska (2005); Mersland
and Strom (2009); Armendariz and Morduch (2007); Cull, et al. (2007). It
is expected that mature MFIs to be more sustainable than younger ones,
but results indicate that the age of an MFI is not related to its
financial sustainability. The results show positive relationship between
MFI size and their financial sustainability that is contradiction with
findings by Hartarska (2005), but in confirmation with Mersland and
Strom (2009); Kyereboah-Coleman and Osei (2008); Cull, et al. (2007).
The number of active borrowers which measures the breadth of outreach
improves the financial sustainability of microfinance institutions that
is consistent with the results of Logotri (2006). The repayment risk
decreases the financially sustainable as expected. The rural market
participation has no role of financial sustainability. The financial
sustainability is positively related to interest rate and negatively to
average loan size. The MFI size and experience makes MFI more
financially sustainable. The capital structure, rural market, group
lending are positive contributors indicating that in most of the regions
and around the world financial sustainability and outreach has trade
off.
This goal of microfinance to reach and empower women as majority of
the world's poor is women and work in informal sector. It is
believed that providing credit to women would reduce the poverty level
of the household. The results show that group lending, rural market,
capital structure, risk and financial sustainability, MFI size,
population density have positive impact on women outreach. Age has no
effect on reaching the women and has effect on all regions together.
Regulated MFI target not to the poorest section as collateral is
required, therefore these MFIs have less women client and HDI has
positive effect. The results lead to conclusion that in case of women
financial sustainability and outreach are met simultaneously to some
extent.
The results of different measures of outreach are estimated by
using regional dummies along with other determinants. The results show
the fact that the smaller is the size of loan, the higher is the
interest charged on these loans. According to Cull, et al. (2007) a
simple indicator is average loan size showing that the small size of
loans symbolise that MFI is targeting poor customers and help in
declining poverty [Cutler (2010) and Rosenberg, et al. (2009)].The
variable for breadth outreach by number of active borrowers and women
borrowers has also shown significant positive impact on poverty
reduction [Hermes, et al. (2009)]. As regard result of lending type
shows that those MFIs who mostly lend to group compared to individual
generally charge significantly low rates of interest so the cost of
outreach is higher [Cull, et al. (2008)] showing that group lending
increase outreach and reduce poverty. The results of control variables
are almost same as obtained in above tables. The MFIs who are operating
in South Africa, South Asia, East Asia and Pacific, Latin America and
the Caribbean, and Middle East and North Africa have less financial
suitability but more active borrowers, women borrowers, average loan
size, charging relatively high interest rates as compared to Eastern
Europe and Central Asia MFIs with exception of South Asia that is
charging lower rate.
5. CONCLUSIONS
The main objective of this study is to examine that microfmance
institutions are playing their role to reduce poverty. The poverty is
reduced by reaching the poor and long term serving the poor that is
possible when MFIs' are financially sustainable, therefore both
outreach and financial suitability is investigated in this study by
conducting a cross region analysis of 382 MFIs covering six regions of
the world. In this study two approaches are used for estimations,
conducting estimations for four measures of outreach (breadth, depth,
cost, and expected future outreach) for each of the region separately
and for the world as a whole, first. Second for robustness check the
results of different measures of outreach are estimated by using
regional dummies along with other determinants.
The results show the fact that the smaller is the size of loan, the
higher is the interest charged on these loans. According to Cull, et al.
(2007) a simple indicator is average loan size showing that the small
size of loans symbolize that MFI is targeting poor customers and help in
declining poverty. The reason is that well off customers are not
attracted in small loans and in line with the results of Cutler (2010)
and Rosenberg, et al. (2009). The variable for breadth outreach by
number of active borrowers and women borrowers has also shown
significant positive impact on poverty reduction [Hermes, et al.
(2009)]. As regard result of lending type shows that those MFIs who
mostly lend to group compared to individual generally charge
significantly low rates of interest so the cost of outreach is higher
Cull, et al. (2008) showing that group lending increase outreach and
reduce poverty. MFIs lending type group lending have low rate and no
collateral compare to individual, who on average charge lower cost of
outreach (interest rates). Nonprofit institutes are more actively
meeting the objective of reaching poor and taking participants out of
poverty The results of other factors like MF1 size, capital structure,
MFI size, profit are positive and risk, regulation, are negative and
significant contributor of outreach generally in all regions. The
results support that providing credit to large number of active
borrowers and women would reduce the poverty level of the household. The
overall results of the study indicate that as depth of outreach is
inversely related with the cost of outreach and positively with
sustainability. However, breadth of outreach has significant positive
relation with cost of outreach and sustainability. These results
indicate that in most of the regions and around the world financial
sustainability and outreach has trade off. The implications of these
results is that it is required both outreach and sustainability, as in
order to survive in future, microfinance industry should be sustainable
by reducing its transaction, operational and administrative cost against
its lending interest rate and average profit.
APPENDIX
Table A1
MFIs on Regional Basis
S.No. Region Frequency %
1 East Asia and the pacific 20 5.235
2 Eastern Europe and central Asia 74 19.372
3 Middle east and north Africa 22 5.759
4 South Africa 56 14.660
5 South Asia 49 12.827
6 Latin America and the Caribbean 161 42.147
Total 382 100
Table A2
MFIs on the Basis of Legal Status
S.No. Legal Status Frequency %
1 Bank 36 9.424084
2 Credit union/cooperatives 41 10.73298
3 NBFI 140 36.64921
4 NGO 165 43.19372
Total 382 100
Table A3
MFIs on the Basis of Lending Type
S.No. Lending Types
1 Group lending
2 Individual lending
3 Village banking
Table A4
MFI on the Basis of Countries
No. of
S.No. Country MFIs
1 Albania 3
2 Angola 1
3 Argentina 2
4 Armenia 4
5 Azerbaijan 10
6 Bangladesh 4
7 Benin 4
8 Bolivia 24
9 Bosnia and Herzegovina 9
10 Brazil 6
11 Bulgaria 2
12 Burkina Faso 1
13 Cameroon 2
14 Chile 2
15 Colombia 11
16 Cambodia 11
17 Costa Rica 1
18 East Timor 2
19 Ecuador 28
20 Egypt 6
21 El Salvador 3
22 Ethiopia 6
23 Gambia 1
24 Georgia 6
25 Ghana 3
26 Guatemala 6
27 Guinea 1
28 Haiti 2
29 Honduras 2
30 India 35
31 Indonesia 1
32 Jordan 3
33 Kazakhstan 6
34 Kenya 9
35 Kosovo 6
36 Kyrgyzstan 5
37 Lebanon 1
38 Mali 3
39 Magnolia 1
40 Morocco 7
41 Mexico 13
42 Moldova 1
43 Mongolia 2
44 Montenegro 1
45 Mozambique 1
46 Nepal 6
47 Nicaragua 14
48 Nigeria 3
49 West Bank and Gaza 1
50 Pakistan 4
51 Palestine 2
52 Paraguay 4
53 Peru 38
54 Philippines 4
55 Rwanda 2
56 Republican Dominica 2
57 Russia 7
58 S Africa 3
59 Senegal 5
60 Serbia 2
61 Sudan 1
62 Tajikistan 6
63 Tanzania 5
64 Togo 2
65 Trinidad & Tobago 1
66 Tunisia 1
67 Uganda 4
68 Uzbekistan 3
69 Vietnam 2
70 Venezuela 1
REFERENCES
Aghion, Armendariz and Jonathan Morduch (2005) The Economics of
Microfinance. Cambridge, MA:MIT Press.
Brewer, E., H. Genay, W. E. Jackson, and P. R. Worthington (1996)
Performance and Access to Government Guarantees: The Case of Small
Business Investment Companies, Economic Perspectives 20:5.
Campion, A., R. Ekka, and M. Wenner (2010) Interest Rates and
Implications for Microfinance in Latin America and the Caribbean.
Inter-American Development Bank. (Working Paper Series # IDB-WP-177).
Christen, R. and D. Drake (2002) Commercialisation. The New Reality
of Microfinance.The Commercialisation of Microfnance. Balancing Business
and Development 02-22.
Copestake, J. (2007) Mainstreaming Microfinance: Social Performance
Management or Mission Drift? World Development 35:10, 1721-1738.
Cotier, P. (2010) What Drives Lending Interest Rates in the
Microfinance Sector? Microfinance Workshop Groningen University.
Cull, R., A. Demirguc-Kunt and J. Morduch (2006) Financial
Performance and Outreach: A Global Analysis of Leading Microbanks.
(World Bank Policy Research Working Paper 3827).
Cull, Robert, Asli Demirguc-Kunt and Jonathan Morduch (2008)
Microfinance Meets the Market. Journal of Economic Perspectives 23:1,
167-92.
Cull, Robert., Asli Demirguc-Kunt and Jonathan Morduch (2009) Does
Regulatory Supervision Curtail Microfinance Profitability and Outreach?
The World Bank, (Policy Research Working Paper Series:4948).
Cull. R., Asli Demirguf-Kunt and J. Morduch (2007) Financial
Performance and Outreach: A Global Analysis of Leading Microbanks. The
Economic Journal 117, F107-F133.
Dichter, T. W. and M. Harper (2007) In T. W. Dichter and M. Harper
(eds.) What's Wrong with Microfnance.
Fernando, N. A. (2006) Understanding and Dealing with High Interest
Rates on Microcredit. East Asia Department, Asian Development Bank.
Ghatak, M. and T. W. Guinnane (1999) The Economics of Lending with
Joint Liability.
Gonzalez, A. (2007) Resilience of Microfinance Institutions to
National Macroeconomic Events: An Econometric Analysis of MFI Asset
Quality. (MIX Discussion Paper No. 1).
Gonzalez, A. (2008) Efficiency Drivers of Microfinance Institutions
(MFIs): The Case of Operating Expenses. (MIX Discussion Paper No. 2).
Washington, D.C: MIX, March.
Gonzalez, A. (2010) Analyzing Microcredit Interest Rates. Mix Data
Brief No. 4. www.themix.org.
Gutierrez-Nieto, B., C. Serrano-Cinca and C. Mar Molinero (2007)
Microfinance Institutions and Efficiency. OMEGA: International Journal
of Management Science 35: 2, 131-142.
Gutierrez-Nieto, B., C. Serrano-Cinca, and C. Mar Molinero (2009)
Social Efficiency in Microfinance Institutions. The Journal of the
Operational Research 60:1, 104-119.
Hartarska, V., D. Gropper and S. Caudill (2009) Which Microfinance
Institutions Are Becoming More Cost-Effective With Time? Evidence from a
Mixture Model. Journal of Money, Credit, and Banking 41:4, 651-672.
Hartarska, Valentina (2005) Governance and Performance of
Microfinance Institutions in Central and Eastern Europe and the Newly
Independent States. World Development 33:10, 1627-3.
Hartarska, Valentina, and Denis Nadolnyak (2007) Do Regulated
Microfinance Institutions Achieve Better Sustainability and Outreach?
Crosscountry Evidence 39:10-12, 120722.
Hartarska, Valentina, and Denis Nadolnyak. (2008) An Impact
Analysis of Microfinance in Bosnia and Herzegovina 36:12, 2605-19.
Helmes, B. (2004) Interest Rate Ceilings and Microfinance: The
Story So Far.
Hermes, Niels, Robert Lensink, and Aljar Meesters (2009) Outreach
and Efficiency of Microfinance Institutions. Faculty of Economics and
Business, University of Groningen, the Netherlands.
Hudon, M. and D. Traca (2008) On the Efficiency Effects of
Subsidies in Microfinance: An empirical Inquairy. Solvay Business
School, Brussels, Belgium. (Working Paper CEB 06020).
Jonathan Morduch, Asli Demirguc-Kunt and Robert Cull (n.d.)
Financial Performance and Outreach: A Global Analysis of Leading
Microbanks. 517:2, F107-33.
Kai, H. (2009) Competition and Wide Outreach of Microfinance
Institutions. Munich Personal RePEc Archive 17143 .
Lewis, J. (2008) Microloan Sharks. Stanford Social Innovation
Review. Summer 2008.
Marquez, R. (2002) Competition Adverse Selection, and Information
Dispersion in the Banking Industry. The Review of Financial Studies 15,
901-926.
Martinez, S. and Mody A. (2003) How Foreign Participation and
Market Concentration Impact Bank Spreads: Evidence from Latin America.
Journal of Money, Credit and Banking 36: 3, 511-537.
McIntosh, C. and B. Wydick (2005) Competition and Microfinance.
Journal of Development Economics 78, 271-298.
Mersland R, 1. Guerin and B. D'Espallier (2009) Gender Bias in
Microfinane. (RUME Working Papers Series, 2009-04), Marseille, IRD.
Mersland, R. and R. Strom (2009) Microfinance Mission Drift?
Mixmarket (2007) The Microfinance Information eXchange (MIX).
Available at http://www.mixmarket.org/en/what.is.mix.asp.
Morduch, J. (2000) The Microfinance Schism. World Development 28:4,
617-629.
Navajas, Sergio (2006) Microfinance in Latin America and the
Caribbean: How Large Is the Market? Washington, D.C.: Inter-American
Development Bank.
Olivares-Polanco, F. (2005) Commercializing Microfinance and
Deepening Outreach? Empirical Evidence from Latin America. Journal of
Microfinance 7, 47-69.
Pollinger J. J., J. Outhwaite, and H. C. Guzman (2007) The Question
of Sustainability for Microfinance Institutions. Journal of Small
Business Management 45:1, 23-41.
Rhyne, Elisabeth (1998) The Yin and Yang of Microfinance: Reaching
the Poor and Sustainability. 2, 6-8.
Rhyne, Elisabeth and Maria Otero (2006) Microfinance through the
Next Decade:Visioning the Who, What, Where, When, and How. Paper
Commissioned by Global Microcredit Summit 2006. Boston MA: ACCION
International, 2006.
Robert Cull, Asli Demirguc-Kunt and Jonathan Morduch (n.d.)
Financial Performance and Outreach: A Global Analysis of Leading
Microbanks.
Robinson, M. (2001) The Microfinance Revolution: Sustainable
Finance for the Poor.
Rosemberg, R., A. Gonzalez and S. Narain (2009) The New
Moneylenders: Are the Poor being.
Rosenberg, R. (2002) Microcredit Interest Rates (O. P. No.l, Ed.)
Schreiner, M. (1997) A Framework For the Analysis of the
Performance and Sustainability of Subsidized Microfinance Organizations
With Application to BancoSol of Bolivia and to theGrameen Bank of
Bangladesh. PhD dissertation. The Ohio State University.
Tang, S. Y., Painter, G. and N. Bhatt (2002) Microcredit Programmes
in the United States: The Challenges of Outreach and Sustainability.
191-221.
Vinelli, A. (2002) Financial Sustainability in U.S. Organizations.
In J. H. Carr, and Z. Y. Ton Replicating Microfinance in the United
States. Washington, D.C: Woodrow Wilson Center Press. 137-165.
Woller, G. M., C. Dunford, and W. Woodworth (1999) Where to
Microfinance?
Yunus, M. (2007) Creating a World Without Poverty: Social Business
and the Future of Capitalism.
Yunus, M. T. (2011) Sacrificing Microcredit for Megaprofits. The
New York Times. Editorial Desk.
Attiya Yasmin Javid <attiyajavid@pide.org.pk> is Professor,
Pakistan Institute of Development Economics, Islamabad. Afsheen Abrar is
Assistant Professor, NUML University, Islamabad.
Authors Note: The errors and omissions are authors' sole
responsibility.
(1) Until 1980s the presence of in-formal microenterprises- street
vendors, home workshops, market stalls, providers of informal
transportation services-are generally considered by policy-makers and
economists to be a result of economic dysfunction [Robinson (2001)].
(2) Market imperfections, asymmetric information and the high fixed
costs of small-scale lending, decrease to reach of the poor to formal
finance, thus the poor will chose the informal financial sector or to
the worst case of financially excluded [Green, Kirkpatrick, and Murinde
(2006)].
(3) UN has declared 2005 to be the international Year of
Microcredit and Mohammad Yunus has received the Nobel Peace prize in
2006.
(4) Studies have used the number of borrowers as measures of
microfinance breadth of outreach [Mersland and Strom (2008, 2009);
Hermes, et al. (2008) and others],
(5) Navajas, et al, (2000); Hulme and Mosley (1996) and many recent
work.
(6) Mersland and Strom (2009); Cull, et al. (2007), Adongo and
Stork (2006); Hartarska (2005); Woller and Schreiner (2002) and
Schreiner (2001).
(7) As indicator of breadth of outreach is adopted by Armendariz,
et al. (2011) and other studies.
Table 4.1
Results of Determinants of Breadth of Outreach Measured by
Number of Active Borrowers
East Asia & Eastern Europe
Pacific & central Asia
Coeff t-stat Coeff t-stat
C 3.40 1.37 -3.62 * -9.14
AGE 0.06 * 2.45 0.01 0.40
CAP 0.14 0.24 0.19 1.33
GROUP -1.42 * -3.16 0.12 * 2.26
REG -0.01 * -1.87 -0.18 * -2.94
NGO 0.03 1.35 0.14 *** 1.76
RISK -0.51 -1.37 -0.67 * -5.28
FSS -0.21 -0.90 0.81 * 4.58
SIZE 0.22 * 5.45 0.77 * 4.86
Cost 0.96 * 3.14 0.51 * 3.85
Rural 0.29 0.93 0.37 * 6.65
Profit -0.69 * -2.21 0.35 * 8.14
HDI 6.65 *** 1.71 0.04 0.12
PDP 0.01 1.29 0.02 -0.19
[R.sup.2] 0.48 0.46
Middle East &
North Africa South Africa
Coeff t-stat Coeff t-stat
C 7.49 8.73 7.30 * 8.46
AGE 0.05 * 2.02 0.06 * 2.35
CAP 0.51 1.03 0.73 1.50
GROUP -0.19 * -2.96 -0.23 * -3.02
REG -0.09 -0.27 0.17 0.56
NGO 0.03 ** 1.77 0.17 ** 1.71
RISK -0.69 -1.21 -0.40 -1.03
FSS -0.97 -0.82 -0.50 -0.62
SIZE 0.22 * 5.41 0.21 * 5.16
Cost 0.32 * 3.41 0.19 * 2.77
Rural 0.06 0.17 0.05 0.13
Profit -0.42 * -1.97 -0.79 * -1.98
HDI 0.67 0.69 0.47 0.48
PDP 0.01 1.28 0.01 1.40
[R.sup.2] 0-50 0.49
Latin America
South Asia & Caribbean All world
Coeff t-stat Coeff t-stat Coeff t-stat
C -2.14 * -1.81 -3.75 * -9.59 1.38 * 6.27
AGE 0.02 ** 1.74 0.01 0.47 0.02 * 4.95
CAP 0.34 * 3.31 0.19 1.35 0.55 * 7.49
GROUP -0.30 -1.48 0.12 * 2.29 0.40 * 7.41
REG 0.30 *** 1.77 -0.19 * -3.03 -0.03 *** -1.76
NGO 0.21 * 2.11 0.09 * 3.11 0.18 * 3.14
RISK -0.16 -0.61 -0.64 * -5.24 -0.18 * -4.21
FSS 0.50 * 1.84 0.18 * 4.59 0.61 * 2.55
SIZE 0.60 * 17.34 0.77 * 5.02 0.55 * 8.26
Cost 0.08 * 2.94 0.51 * 3.92 0.73 * 5.00
Rural 0.39 0.70 0.37 * 6.67 0.42 * 6.81
Profit -0.23 -1.25 0.32 * 7.88 -0.05 -0.44
HDI 0.64 * 2.87 0.22 0.62 2.02 * 11.41
PDP 0.01 * 3.27 0.01 0.26 0.02 * 7.21
[R.sup.2] 0.45 0.40 0.49
Note: The * indicates significance at 1 percent, ** significance at 5
percent and *** significance at 10 percent.
Table 4.2
Results of Determinants of Depth of Outreach Measured by Average loan
size
East Asia & Eastern Europe Middle East &
Pacific & central Asia North Africa
Coeff t-stat Coeff t-stat Coeff t-stat
C -1.77 -1.60 1.18 2.29 0.52 3.87 *
AGE 0.02 1.15 0.01 -0.03 -0.01 -2.91 *
CAP -0.76 * -2.54 0.23 0.98 -0.15 -1.56
GROUP 0.06 0.21 0.15 * 1.90 0.23 2.96 *
REG -0.38 ** -1.73 0.03 0.37 0.08 1.39
NGO -0.03 *** -1.75 -0.02 ** -1.84 -0.33 -0.831
RISK -0.28 -0.13 -0.39 -0.50 0.05 0.07
FSS -0.02 -0.01 1.34 ** 1.83 0.17 0.36
SIZE 0.09 * 5.02 0.01 1.07 0.02 2.82 *
INT -0.82 * -5.25 0.07 0.39 -0.03 -0.18
Rural -0.34 * -1.93 -0.06 -0.66 -0.26 -3.61 *
Profit 0.88 1.30 -0.44 -1.52 -0.17 -0.73
HDI 1.92 1.01 -0.81 -1.12 -0.17 -0.96
PDP 0.01 * 3.71 0.02 * -2.59 0.00 -5.15 *
[R.sup.2] 0.43 0.44 0.38
South Africa South Asia
Coeff t-stat Coeff t-stat
C 0.11 0.30 -0.18 -0.32
AGE 0.04 3.17 * 0.01 0.86
CAP 0.11 0.46 -0.07 -0.33
GROUP -0.14 -0.67 -0.25 * -2.56
REG 0.24 1.59 0.09 1.15
NGO -0.19 * 2.46 -0.02 ** -1.79
RISK -1.40 -0.68 0.53 0.50
FSS -1.45 -1.14 -0.07 -0.16
SIZE 0.01 0.94 0.01 1.58
INT -0.06 -0.13 -0.41 -1.20
Rural -0.20 -1.06 -0.16 -0.90
Profit -0.39 -0.63 -0.01 -0.09
HDI 0.38 0.80 0.88 0.79
PDP 0.00 -1.22 0.01 -1.11
[R.sup.2] 0.35 0.35
Latin America
& Caribbean All world
Coeff t-stat Coeff t-stat
C 2.56 * 10.95 0.41 * 4.65
AGE 0.01 * 2.26 0.01 * 3.26
CAP -0.39 * -3.25 0.09 * 1.90
GROUP -0.11 * -2.46 -0.11 * -3.33
REG 0.15 * 3.04 0.22 * 6.60
NGO -0.05 * 2.75 0.16 * 2.44
RISK 0.77 * 3.74 0.42 * 2.37
FSS -0.99 * -2.68 -0.07 -0.45
SIZE 0.05 * 12.15 0.05 * 16.70
INT -0.12 -1.10 -0.17 * -1.98
Rural -0.10 * -2.05 -0.14 * -3.65
Profit -0.59 * -3.86 -0.29 * -3.71
HDI -3.82 * -11.84 -0.72 * -6.80
PDP 0.02 * -6.40 0.01 * -5.12
[R.sup.2] 0.32 0.39
Note: The * indicates significance at 1 percent, ** significance at 5
percent and *** significance at 10 percent.
Table 4.3
Results of Determination of Interest Rate as Measure of Cost of
Outreach
East Asia & Eastern Europe Middle East &
Pacific & central Asia North Africa
Coeff t-stat Coeff t-stat Coeff t-stat
C -0.39 * -2.38 0.33 * 2.73 -0.02 -0.31
AGE 0.01 * 3.67 0.01 -1.23 0.01 * 2.63
CAP -0.07 -1.59 0.07 1.29 -0.08 ** -1.87
GROUP -0.05 -1.26 -0.02 -1.25 0.01 0.24
REG -0.01 -0.24 0.01 0.31 0.08 * 2.88
NGO 0.02 ** 1.77 0.13 * 2.73 0.04 ** 1.85
RISK 0.74 * 2.30 -0.28 -1.49 0.99 * 2.70
FSS 0.18 0.88 0.33 ** 1.89 0.34 1.46
SIZE 0.01 * 1.35 0.02 -0.81 0.01 0.02
ALS -0.06 * -5.25 -0.01 * -2.39 -0.01 -1.78 ***
Rural -0.01 -0.48 0.02 0.73 0.01 0.28
Cost 0.71 * 8.87 0.26 * 3.85 0.83 * 9.71
HDI 0.49 ** 1.82 -0.20 -1.18 -0.10 -1.14
PDPSM 0.02 * 4.37 0.01 -1.60 0.01 -0.98
[R.sup.2] 0.68 0.54 0.59
South Africa South Asia
Coeff t-stat Coeff t-stat
C 0.01 0.03 0.03 0.32
AGE 0.01 * 2.56 0.01 -0.79
CAP -0.08 ** -1.86 -0.12 * -3.37
GROUP -0.01 -0.37 -0.02 -1.15
REG 0.08 * 2.72 0.02 1.34
NGO 0.01 *** 1.75 0.04 * 1.92
RISK 0.93 * 2.55 -0.10 -0.56
FSS 0.03 * 2.00 0.10 1.40
SIZE 0.01 0.51 0.02 1.43
ALS -0.01 -0.28 -0.01 -2.20
Rural 0.01 0.29 -0.01 -0.38
Cost 0.84 9.77 0.02 1.17
HDI -0.10 -1.11 0.11 0.63
PDPSM 0.01 -1.08 0.02 ** 1.88
[R.sup.2] 0.59 0.55
Latin America
& Caribbean All world
Coeff t-stat Coeff t-stat
C 0.32 * 4.77 0.13 * 6.46
AGE 0.01 * -2.28 0.01 -1.12
CAP 0.03 0.76 -0.01 -0.45
GROUP -0.01 -0.68 -0.01 -1.13
REG -0.01 -0.69 -0.01 ** -1.77
NGO 0.20 * 1.97 0.13 * 2.56
RISK -0.24 ** -1.82 -0.05 -1.28
FSS 0.21 * 2.03 0.14 * 3.98
SIZE 0.01 0.95 0.01 * 3.93
ALS -0.01 -1.80 ** -0.01 * -1.98
Rural 0.01 0.68 0.03 * 3.38
Cost 0.07 1.66 0.01 * 5.24
HDI -0.19 -1.97 0.03 1.13
PDPSM 0.02 -1.31 0.02 * -3.47
[R.sup.2] 0.54 0.55
Note: The * indicates significance at 1 percent, ** significance at
5 percent and *** significance at 10 percent.
Table 4.4
Results of Determination of Financial Sustainability as Measure of
Future Expectation of Outreach
East Asia & Eastern Europe Middle East &
Pacific & central Asia North Africa
Coeff t-stat Coeff t-stat Coeff T-STAT
C -4.25 -1.50 -0.12 -0.62 -0.31 -0.49
AGE 0.02 0.72 0.01 0.79 0.02 -0.18
CAP 0.20 * 3.58 0.10 1.13 1.23 2.89
GROUP -0.20 * 2.47 0.04 * 2.15 0.06 *** 1.77
ALS 0.30 * 1.90 0.05 * 2.28 0.10 *** 1.73
REG 0.29 0.64 -0.10 * -0.32 0.08 2.11
NGO 0.06 0.28 0.09 0.55 0.03 0.32
RISK -3.29 -0.94 -0.18 -0.66 -1.55 -0.44
SIZE 0.09 * 1.99 0.06 * 2.11 0.04 1.44
AB -0.29 * -3.16 0.27 * 4.09 0.80 * 2.15
INT -0.19 -1.21 -0.07 -0.95 -1.16 ** -1.84
Rural -0.54 * -1.91 0.03 0.86 -0.24 -0.75
Cost -0.17 -1.50 0.28 * 2.39 -0.15 * -2.1
HDI 11.81 * 2.58 0.18 0.69 0.22 0.27
PD 0.01 * 2.51 0.01 -0.11 0.03 0.71
[R.sup.2] 0.42 0.45 0.49
South Africa South Asia
Coeff t-stat Coeff t-stat
C -0.41 -0.66 0.87 * 3.00
AGE 0.01 0.30 0.02 -0.96
CAP 0.32 * 3.09 0.31 * 2.71
GROUP 0.01 1.83 ** 0.04 * 2.78
ALS -0.09 -0.59 -0.02 -0.53
REG 0.21 0.81 -0.06 -1.54
NGO 0.19 * 2.49 0.01 ** 1.85
RISK -1.49 -0.42 -1.05 -1.54
SIZE 0.03 1.27 0.06 * 11.92
AB 0.77 * 2.16 0.20 * 2.93
INT -0.90 -1.05 -0.14 -0.85
Rural -0.34 -1.03 0.06 0.68
Cost -0.57 -0.54 -0.22 * -5.23
HDI 0.36 0.44 -1.58 * -2.84
PD 0.01 0.51 0.02 -0.39
[R.sup.2] 0.40 0.42
Latin America &
Caribbean All world
Coeff t-stat Coeff t-stat
C 0.28 * 2.49 0.30 3.48
AGE 0.01 -0.96 0.01 * -2.83
CAP 0.12 * 2.20 0.25 * 8.76
GROUP 0.05 * 2.48 0.02 * 2.16
ALS -0.04 * -3.16 -0.08 * -2.32
REG -0.07 * -3.02 -0.04 * -2.04
NGO 0.04 0.38 0.10 ** 1.87
RISK 0.13 0.59 -0.36 * -3.36
SIZE 0.01 * 7.09 0.05 * 7.91
AB 0.31 * 7.05 0.01 0.83
INT -0.08 -1.53 0.01 0.22
Rural -0.03 -1.22 -0.04 -1.53
Cost 0.10 1.34 0.16 1.98
HDI -0.29 ** -1.88 0.05 0.04
PD 0.01 * -1.99 0.02 *** 1.72
[R.sup.2] 0.47 0.47
Note: The * indicates significance at 1 percent, ** significance at
5 percent and *** significance at 10 percent.
Table 4.5
Results of Determination of Women Outreach
East Asia & Eastern Europe Middle East &
Pacific & central Asia North Africa
Coeff t-stat Coeff t-stat Coeff t-stat
C 0.32 1.14 0.17 * 2.40 0.53 * 3.42
AGE 0.01 0.67 0.01 * 3.66 0.02 0.12
CAP 0.04 0.34 0.18 * 4.77 0.02 0.22
GROUP 0.03 * 2.32 0.04 * 3.29 0.13 ** 1.81
REG 0.06 0.76 0.10 0.65 0.04 0.76
NGO 0.07 * 2.35 0.01 * 1.99 0.04 ** 1.86
RISK -0.35 ** -0.81 -0.20 ** -1.85 -0.56 -1.62
FSS 0.88 *** 1.61 0.69 * 6.05 0.82 *** 1.69
SIZE 0.02 * 2.50 0.02 * 13.43 0.02 * 3.01
Profit 0.56 * 2.66 0.02 0.69 0.45 * 2.13
Rural -0.21 3.01 0.11 * 7.68 0.16 ** 1.88
Cost -0.04 -0.15 0.72 * 5.24 0.13 0.49
HDI 0.80 3.91 0.27 * 2.78 0.13 0.64
PDP 0.01 -1.11 0.02 -0.40 0.01 -0.62
[R.sup.2] 0.34 0.35 0.36
South Africa South Asia
Coeff t-stat Coeff t-stat
C 0.53 * 3.45 0.39 1.62
AGE 0.02 0.18 -0.01 * -5.52
CAP 0.01 0.11 0.52 * 5.91
GROUP 0.13 2.41 0.01 * 2.22
REG 0.05 0.86 0.07 0.25
NGO 0.48 * 2.35 0.02 ** 1.78
RISK -0.79 *** -1.66 -0.39 *** -1.69
FSS 0.81 *** 1.67 0.14 ** 1.77
SIZE 0.02 * 3.26 0.06 4.74
Profit 0.52 * 3.27 0.07 1.28
Rural 0.16 * 1.90 0.01 0.13
Cost 0.32 * 1.98 0.07 ** 1.83
HDI 0.13 ** 1.72 0.54 ** 1.79
PDP 0.01 -0.57 0.01 * 3.28
[R.sup.2] 0.35 0.32
Latin America
& Caribbean All world
Coeff t-stat Coeff t-stat
C 0.14 * 1.92 0.10 * 3.13
AGE 0.03 * 3.68 0.01 0.06
CAP 0.17 * 4.73 0.04 * 2.02
GROUP 0.05 * 3.33 0.13 * 10.63
REG 0.10 0.66 0.16 *8 1.80
NGO 0.12 *** 1.73 0.21 * 2.37
RISK -0.20 ** -1.84 -0.35 * -5.17
FSS 0.69 * 6.02 0.74 * 12.51
SIZE 0.02 * 13.55 0.02 * 20.70
Profit 0.02 0.71 0.02 0.04
Rural 0.11 * 7.67 0.09 * 6.55
Cost 0.72 * 15.08 0.36 * 12.14
HDI 0.23 * 2.30 0.22 * 5.33
PDP 0.01 0.08 0.01 * 6.05
[R.sup.2] 0.37 0.38
Note: The * indicates significance at 1 percent, ** significance at
5 percent and *** significance at 10 percent.
Table 4.6
Results of Regional Differences in outreach
Interest Rate Average Loan Size
Coefficient t-stat Coefficient t-stat
C 0.15 10.20 0.09 1.34
AGE 0.01 *** -1.73 0.01 * 2.96
CAP -0.02 -1.40 0.02 0.40
GROUP 0.01 *** 1.63 -0.12 * -3.76
REG -0.01 -1.04 0.21 * 6.08
NGO 0.07 * 2.32 -0.02 ** -1.75
RISK -0.07 ** -1.88 -0.28 *** -1.63
SIZE 0.01 * 4.28 0.04 * 14.36
Avgls -0.01 * -2.78
INT -0.24 * -2.78
Rural 0.03 * 2.86 -0.18 * -4.70
Profit 0.07 * 4.00 0.40 * 5.58
HDI 0.03 *** 1.73 0.72 * 6.80
PD 0.02 * 3.47 0.01 * 5.12
DAF 0.02 0.23 0 17 * 3.13
DEAP 0.04 * 2.46 -0.05 -0.72
DLAC 0.02 *** 1.78 -0.11 * -2.37
DMENA 0.04 * 2.67 -0.33 * -4.48
DSA -0.08 * -6.14 -0.46 * -8.20
0.52 0.50
Active Borrowers Women Borrower
Coefficient t-stat Coefficient t-stat
C -0.39 ** -1.82 -0.06 -1.66
AGE 0.01 * 3.46 0.01 * -1.94
CAP 0.30 * 4.44 0.12 * 6.41
GROUP 0.15 * 3.00 0.11 * 8.90
REG -0.18 * -2.70 -0.03 * -2.50
NGO 0.03 ** 1.79 0.02 * 11.72
RISK -1.16 * -4.70 -0.37 * -5.50
SIZE 0.54 * 5.46 0.03 * 5.50
Avgls
INT 0.36 * 6.38 0.12 * 8.26
Rural 0.03 * 2.86 0.12 * 8.26
Profit 0.83 * 4.09 0.58 * 10.23
HDI 0.01 2.05 0.06 ** 1.81
PD 0.01 * 2.93 0.01 * 2.50
DAF 1.33 * 13.90 0.09 * 3.59
DEAP 1.71 * 15.67 0.24 * 8.18
DLAC 0.55 * 7.84 0.05 * 2.67
DMENA 1.29 * 12.51 0.13 * 4.72
DSA 2.15 * 23.26 0.34 * 14.31
0.51 0.53
Financial
Sustainability
Coefficient t-stat
C 0.41 * 4.41
AGE 0.02 ** 1 80
CAP 0.22 * 7.47
GROUP 0.01 0.69
REG 0.01 ** 1.78
NGO 0.05 ** 1.76
RISK -0.09 -3.79
SIZE 0.29 * 2.69
Avgls 0.05 * 7.47
INT 0.01 * 1.34
Rural -0.04 -0.69
Profit 0.01 * 2.26
HDI 0.08 ** 1.85
PD 0.01 0.33
DAF -0.17 -3.99
DEAP 0.10 1.98
DLAC -0.18 -5.50
DMENA -0.13 -2.71
DSA -0.17 -3.82
0.54
Note: The * indicates significance at 1 percent, ** significance at
5 percent and *** significance at 10 percent.
