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An empirical study on the impact of
microfinance institutions on development
Bachelor Thesis
supervised by the

Institute for Empirical Research in Economics (IEW)
at the University of Zurich

Prof
...
Fabrizio Zilibotti
to obtain the degree of
“Bachelor of Arts in Wirtschaftswissenschaften”

Author: Amelie Brune
Course of Studies: Economics
Closing date: August 21, 2009

Abstract
This paper examines the impact of microfinance institutions on development
in an empirical setting, and therewith aims at filling a gap in econometric assessments of microfinance institutions
...
Microcredit is the most
robust mechanism to enhance development in recent years
...
Savings is found to be the best estimator for
development in recent years, yet a structural break between 2003 and 2006 is possible
...


2

Contents

Contents
1 Introduction

4

2 The idea of microfinance institutions

6

3 Theoretical implications of the benefits of microfinance
3
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3
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3
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institutions

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1 MixMarket Data Base
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1
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4
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3 Descriptive Analysis
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3
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4
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2 Microfinance Institutions in selected African Countries
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3
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4
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4 Microfinance Institutions in selected Asian Countries
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4 Econometric Analysis
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4
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4
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2 Discussion of Relevant Explanatory Variables
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4
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4
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4
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5 Caveats
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5 Alternative Approaches to Empirical Analyses
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5
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4
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2 Ideas for a Binary Choice Approach
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Although the first MFIs have already been established in the 1980s such as
the Grameen Bank founded by 2006 Nobel Peace Prize Laureate Muhammad Yunus
(Yunus 2003), the extend to which they have been profoundly analysed in economic
research is still small
...
While the former covers qualitative case
studies of an individual MFI, the latter aims at detecting general patterns to draw
conclusions about common characteristics
...
Pilot studies are the most frequent embodiment thereof
...
As control groups are
completely missing, it may prove to be difficult to disentangle effects of microfinance
itself
...
Purely qualitative assessments are
not able to account for reverse causation or spurious correlations, which further stresses
the arguments above
...
As, for example, emphasised by Murdoch (1999), the scarcity of data was the main
reason for significant underrepresentation of econometric-based empirical studies on any
topic on MFIs
...
But the results obtained from in-depth empirical analyses
may reveal important insights into MFIs and their impact on economic development
...
In chapter 2, I explain
the origin and idea of microfinance institutions
...

Chapter 4 concentrates on both descriptive (see section 4
...
4) empirical analyses of a selected set of MFIs in Africa and Asia and draws conclusions
from the obtained results
...


5

2 The idea of microfinance institutions

2 The idea of microfinance institutions
Microfinance institutions provide small-scale financial services to poor people who are
otherwise ”excluded from the formal banking sector” (Morduch, 1999, p
...
Operating merely in developing and emerging countries, they
have specialised in offering loans of minor scale to enable individuals to start small productive businesses and enhance entrepreneurship
...
In this case, microfinance institutions often represent a first opportunity for the local population to participate in financial systems and to benefit from
access to business and capital
...
In 1983, he
founded Grameen Bank, the first institution which realised this concept and started to
operate in the microfinance business in the proper sense
...

Although there have been organisations concentrating on offering loans and saving
opportunities to needy people before (Counts, 2008, p
...
In particular, it has proposed a
number of indicators to measure the impact of poverty elimination methods (Yunus, in:
Counts, 2008, p
...
These consider primarily basic needs similar to the definition of
the International Labour Organisation in 1976 (in: Schubert, 2007), and the financial
situation of the poor
...
Similar indicators for development are discussed in
chapter 4
...
1
...
18–19)
...
xii), and the concept of free markets has also the capacity to contribute to poverty reduction (p
...
But the idea still
missing is to incorporate a social component into economic systems to meet observed
behaviour (pp
...


6

2 The idea of microfinance institutions
The idea of microfinance institutions meets both requirements
...
They enable poor people to engage in productive economic activities and thus contribute to development in low income population
strati
...
97) and the problems
related to standard banking institutions
...


7

3 Theoretical implications of the benefits of microfinance institutions

3 Theoretical implications of the benefits of
microfinance institutions
In the following, I first present the concept of group-lending as a means to avoid classical
economic problems associated with lending to poor people (see chapter 3
...
Thereupon,
I elaborate on a rather new approach first presented by Sachs et al
...


3
...
However, low income levels and the lack of assets
would exclude most people in developing countries from obtaining credit from standard
banks
...
Instead of
requiring collateral from each individual, they use peer pressure and social selectivity to
increase repayment rates and hedge against default risk
...
As groups form voluntarily, no group is willing to accept a member
whose reputation is questionable and who is likely to take too high risks in investing
the loan and risks to be unable to repay by hindsight
...

1575)
...
1570)
...
2
In addition, group-lending decreases transaction costs, another cause for standard banks
to refain from lending to the poor (Sachs, 2005, p
...
At the same time, poor individ2

Guttman (2006) distinguishes a total of three major problems which are responsible for low credit
provision for the poor in standard banking systems
...

Second, ex ante moral hazard which occurs when a borrower has incentives to take too high risks
in investing the loan, given the knowlegde that the MFI will not raise any repayment claims in case
of failure as collateral is not given
...
1–2)
...
This approach is also interesting to encounter the often assumed insufficient
creditworthiness of the poor, which is one of the main arguments to explain why contracts between standard banking institutions and poor people are often said to be not
feasible
...

The design of group-lending by Grameen Bank described above can be formalized by
means of a game-theoretical approach
...

All players (hence, the MFI and a group of five borrowers) cooperate, until one group
member defaults
...

I assume that lending is made simultaneously to all group members
...
3 The basic play resembles a prisonner’s
dilemma: the social optimum is achieved if both players cooperate, that is, if the microfinance institution grants credit and all group members eventually repay
...
In the latter case, I assume that the
exclusion from further loans is the only sanction, but no repayment claims on the part
of the MFI are made
...


Player 1 (MFI)

cooperate
defect

Player 2 (group)
cooperate defect
a1 , a2
b1 , b2
c1 , c2
d1 , d2

Figure 1: Payoff matrix for group-lending (microfinance game)
To ensure long-term cooperation on the part of the group and continuous repayment
of loans, the sum of discounted profits in every period for cooperating for player 2 (and in
fact, for every group member) has to exceed the sum of discounted profits from defecting
3

To keep structures simple, the group of m players is perceived as one single player, as no member ever
receives credit again if one of them ever defaults and all group members share common characteristics
in behaviour
...
The former are profits generated trough
small businesses realised by means of microcredit, net from interest
...
Assuming that player 2 can not receive credit from other microfinance
institutions after being denied further credit from the MFI,

c
d
π2 > π2

(1)

must hold, where

c
π2 = a2 + a2 δ +
...
+ a2 δ T −1 + b2 δ T + d2 δ T +1 +
...


(3)

t=0

a2 is the payoff from cooperating if the MFI cooperates, as well
...
d2 is the
payoff for each period after time T when subsequent credit from the MFI is denied due
to defection in period T
...
Substituting for (2) and (3)

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3 Theoretical implications of the benefits of microfinance institutions
in equation (1), the following inequality is obtained:4

c
d
π2 > π2
T −1

T −1

k−1

δ t + a2 δ T + a2 δ T +1

a2

δ t > a2

t=0
k−1+1

t=0

k−1

δ t + b2 δ T + d2 δ T +1
t=0

δt

t=0
k−1+1

1−δ
1−δ
> b2 δ T + d2 δ T +1
1−δ
1−δ
T
T +1
k
T
T +1
a2 δ (1 − δ) + a2 δ (1 − δ ) > b2 δ (1 − δ) + d2 δ (1 − δ k )
a2 δ T + a2 δ T +1

a2 δ T − a2 δ T +1 + a2 δ T +1 − a2 δ T +k+1 > b2 δ T − b2 δ T +1 + d2 δ T +1 − d2 δ T +k+1
a2 − a2 δ k+1 > b2 − b2 δ + d2 δ − d2 δ k+1
a2 − a2 δ k+1 > b2 − (b2 + d2 )δ − d2 δ k+1
...

Suppose k = 0
...
Though,
if the borrower is aware of his dependency, he would act irrational if engaging in too
risky investment projects where he runs the risk to default
...
5 Thus, the borrower will not default
...
This implies that an individual can always generate alternative
income through outside-options if he is denied further access to microcredit
...
For δ ≤ 1, we get a2 > −d2 : as long as the profit from
b2 +d
receiving microcredit exeeds the opportunity costs from alternative income, the borrower
decides not to default
...
As both scenarios are sensible, lending by microfinance institutions
is in fact efficient and may improve economic welfare of the poor
...

1−q
1
5
Note that δ = 1+r , where r is the real interest rate
...
In a repeated game with t → ∞, this results
in a Nash equilibrium
...
In her position as credit institution, the MFI’s potential to threaten is distinct,
but the group of borrowers’ is not clear at first sight
...
In this regard, the microfinance game
eventually also proves not to be a prisonner’s dilemma as the equilibrium is identical
to bilateral cooperation instead of defection, although initial reasoning suggested the
opposite
...
He argues that ’assortative matching’, that is to
say the process of group formation separating risky from safe borrowers, would only
occur in absence of ’dynamic incentives’ (p
...

This would imply that if a trigger is applied, groups would be composed of both types
of borrowers, which actually contradicts the hypothesis that this strategy would ensure
secure investments in the long run by separating risky from safe clients
...
However, he assumes throughout the feasibility of side payments
between both borrowers, where one pays a certain amount to share costs if his own
project succeeds and that of his partner fails
...
9)
...


3
...
Models incorporating poverty traps contrast clas-

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3 Theoretical implications of the benefits of microfinance institutions
sical growth models where, in case of a stable overall environment, negative economic
shocks are followed by periods of prosperous growth and not by stagnation (Sachs et al
...
By means of a poverty trap adjusted Solow model (Sachs et al
...

˜
It can be shown that both kSS and kSS are stable steady state equilibria (depending on
k < k0 or k > k0 ), but not k0
...
On the other
2
hand, f (k) can incorporate decreasing returns to scale, such that ∂f > 0 and ∂ f < 0,
∂k
∂k2
while the saving rate depends on the level of accumulated capital
...


Figure 2: Poverty trap adjusted Solow model with two stable steady states

For all levels of capital accumulation below k0 , the sum of depreciation and population
growth rates, (δ + n), exceeds marginal savings and initiates convergence towards the
˜
lower steady state equilibrium kSS with g(k) = f (k) = 0
...
Sachs et al
...
, 2004)
...
, 2004)
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2 % of rural Ugandan households did not save at all, compared to 64
...
On average, 85
...
9)
...

But this is exactly the point where the idea of microfinancial institutions applies
...
If
the poverty trap model applies in a given country, then the presence of well functioning
microfinance institutions may not only enhance aggregate growth by supporting the poor
with credit, but it can also increase confidence of foreign investors, for instance
...
This, in
turn, can reinforce complementary industrial growth
...
43)
...


3
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Poverty is, however, a phenemenon
that requires the involvement of both perspectives to be studied in all detail and to be
understood comprehensively
...
9–11)
...
However, multilateral institutions ”focus
exclusively on pursuing this goal [of poverty eradication] through large-scale economic
growth” (p
...
The problem is that development on an aggregate level does not necessarily imply welfare improvement for individuals in the poorest part of a population
...
I
argue that microfinance institutions are an example of such a mechanism
...
Increases in savings and/or saving rates can, in turn, enable an economy to pass a prohibitive level of capital accumulation and associated level
of income and, hence, to evade stagnation caused by saving traps
...
1 MixMarket Data Base
Together with the Microbanking Bulletin, the MixMarket data base is provided by the
Microfinance Information eXchange (MIX)
...
For performance data on microfinance institutions,
this is the most accurate and complete base available at this time
...

1406 microfinance institutions are currently included6 and new MFIs are added continuously
...
Microfinance institutions are also classified according to their
legal institutional form and network affiliation
...

In the following, if nothing else is specified, all data related to microfinance institutions
are gathered from the MixMarket data base
...
1
...

Descriptive statistics cover the year of the MFI’s establishment, if it is regulated,
a verbal statement of the institution’s goal, key notes on its historic background and
development process, products provided, its main funding sources, the percentage of
operations comprised by microfinance, a list of MixMarket funds investing in the MFI,
possible investment opportunities, as well as individual presentations of internal reports
...

6

www
...
org, retrieved on June 16, 2009
...
This covers
data on average loan and savings balances per borrower/saver, the number of active
borrowers, savers, and personnel, the distribution of male and female borrowers, and the
ratio of average loans/savings per borrower/saver to per capita gross national income
...

Data is published for a maximum of twelve subsequent years
...
Apparently, data for earlier periods have either not
been collected or not published yet
...
Though, the presented MixMarket data form the best
available set for large sample sizes so far
...
2 Choice of microfinance institutions in different geographic
regions
Although today MFIs are present in nearly all developing and emerging countries, I
focus on a number of selected institutions operating in Africa and Asia
...
Compared to other developing countries, those in Africa often show greatest
difficulties to catch up with the world’s more industrialised part
...
In order to make
reliable statements on the MFIs’ past impact on development and to make predictions
on future impact, long time series are crucial
...

To fulfil these criteria, I have chosen two countries each in Africa and Asia where a
number of MFIs with high quality data of substantive time series operate
...
For Asia, I have chosen six in
Cambodia and three on the Philippines
...
It is, however, not the purpose of this paper to
identify distinct causes for probable differences in either marginal impact and/or basic
levels, but to give an idea about the general importance of microfinance institutions and
to show if there is evidence to suspect differences subject to geography
...
3)
...
4
proposes an in-depth econometric analysis
...
3 Descriptive Analysis
As being said, selected MFIs provide the longest time series available for a given country,
such that descriptive trend analyses can generate reliable performance results
...

4
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1 Basic Economic Conditions in selected African Countries
Ethiopia, a landlocked developing country in East Africa, is classified as a low-income
economy by the World Bank
...
The country has experienced high volatility in real gross domestic product per
capita (GDP p
...
) growth rates since 1951
...
62%, their
range reaches from -21
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22% in the year thereafter
...

Between 1951 and 2003, the country has experienced negative growth in 18 years
...
5% in 2008 (World Factbook), which
indicates that volatility is still substantial
...
6 million people lived in Ethiopia
...
28% between 1950
and 20048 , implying that it needs 30
...
9 In the period between 1967
7

Numbers computed from Penn World Table data
...

9
The exact formula to derive the number of years n it takes for a variable to double is derived from
x1 = x0 (1 + g)n , where x1 = 2 and x0 = 1
...
The rule of 69 has proved to be more accurate than the more frequently used
8

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4 Empirical Analyses
to 1995, growth was extremely volatile with values strongly oscillating between 1
...
15% in 1991
...
Current life expectancy at birth is 53 years, the total fertility rate is
5
...
In 2000, 44
...


(a) Ethiopia

(b) Uganda

Figure 3: Levels and growth rates of per capita GDP in Ethiopia and Uganda (1950/51–
2003) (Data: Penn World Table)

Uganda is classified as a low-income economy by the World Bank, as well
...
Between 1951 and 2003, growth rates have
reached a minimum of -19
...
6% in 1994
...
In
2000, 33
...

With an average growth rate of 2
...
5
...
5 million in 2003
...
4
years
...
7 children per women and thus higher than
in Ethiopia, while life expectancy at birth is comparable with 51 years (World Bank)
...
Although resulting values are slightly underestimated, it provides better results for
any growth rate
...
3
...

10
Numbers computed from Penn World Table data
...

12
Numbers computed from Penn World Table data
...
3
...
These are all non-bank financial institutions
...
ACSI is though an exception, as it was 40 times as big
as the average institution in 2001
...
Until 2007, all MFIs have at least doubled in
size
...
21%
...
Consistenly, one should expect a similar pattern in the number of clients
over time and, in fact, one can observe a positive trend in the number of borrowers and
savers
...
1
...
For ACSI, it steadily
decreases over time, starting with 5
...
66 in 2008
...
86 (SFPI, 2001) respectively 16
...

A considerable part of borrowers in Ethiopian MFIs is female
...
ACSI has
experienced the largest decrease between 1999 and 2003, where the percentage of female
borrowers has fallen from 72
...
4% within four years
...
2% in 2007
...

Figure 4 shows average savings and credit balances per borrower/saver and an according ratio for each MFI over time
...
Missing data does not indicate their closing, but that no informa-

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4 Empirical Analyses
values
...
Only until
2003, ACSI had a loan to savings ratio smaller than one, implying a stronger focus on
savings than on credit
...
While
Wisdom showed ratios roughly around one over time, those of SFPI have been highly
volatile since 2004, with loan to savings ratios between 5
...
For the remaining three MFIs, BG, PEACE, and Wasasa, average credit
has declined relatively to savings over time, where the drop between 2001 and 2004 was
especially sharp
...
In 2003,
46% of Wisdom’s clients lived in households where each member earned less than 1 USD
per day on average
...
25 USD per day and person (in
2005 PPP) as a measure for the poverty line proposed by the World Bank, this fraction
lived well below
...

Selected microfinance institutions in Uganda are the Micro Enterprise Development
Network (MED-Net), Commercial Microfinance Limited (CML), Faulu Uganda, FINCA
Uganda, and Uganda Finance Trust Limited (U-Trust, UWFT)
...

As Figure 5 shows, the number of personnel working with microfinance institutions in
Uganda has increased steadily over time, and thus matches the development in Ethiopia
...
The same applies to all subsequent figures
...
Graphically seen, there is no clear evidence of declining numbers within
the selected institutions
...
Interestingly, from 2004 to 2005 both U-Trust and FINCA have
experienced a sudden decrease in the number of savers of -42
...
94%
...

Both U-Trust and CML have had more savers than borrowers at all times
...
33 in 2006, while the respective
ratio for U-Trust increased from initially 1
...
96 in 2006
...
These are also the only two years where positive numbers
of savers for this MFI are reported at all
...
While the number of savers exceeded that of borrowers, it was the opposite
onwards
...
With an increase of 103%, the strongest expansion took place from 1997 to 1998
...
39% to 26
...

FINCA increased its number of borrowers by factor 5
...
In 2003,
they started to serve savers as well; though these were mostly below the number of

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4 Empirical Analyses
borrowing clients
...
While the trend is on average increasing for MED-Net and CML, it
is declining for U-Trust, FINCA, and Faulu
...


Figure 7: Percentage of female borrowers in Ugandan MFIs

Analysing the relation between average loan balances per borrower and average savings
balances per saver in each institution over time, one sees that microcredit business is

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4 Empirical Analyses
predominant for most selected MFIs
...
19,
for U-Trust by factor 2
...
Only MED-Net obviously focuses strongly on savings on a
remarkable high level
...
3
...
Cambodia’s growth rate of real GDP per capita has
experienced high volatility at least since 1970, though with a positive trend
...
Since 1987, the trend reversed: an increase by factor 2
...
While actual growth rates remained highly volatile, they were
merely positive since 1988
...


(a) Cambodia

(b) Philippines

Figure 8: Levels and growth rates of per capita GDP in Cambodia (1970–2003) and the
Philippines (1950–2004) (Data: Penn World Table)

In contrast to many other developing countries, Cambodia showed a declining trend in
population growth
...
59% with only
0
...
On average, Cambodia’s population would thus double approximately
every 43
...
However, the number rised sharply to 1
...


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4 Empirical Analyses
which constitutes an outlier in a way
...
2 children per woman (World Bank), which underlines a
sounder population development than in Ethiopia or Uganda
...

Despite, again, extremely high volatile growth rates with a standard deviation of 3
...
Though,
growth has been less rapid since the beginning of the 1980s
...
17% of all years
between 1982 and 2004, compared to only 16
...
This high
frequency seemed, however, to be compensated partially by a high average growth rate
of 2
...
16 In 2007, the Philippines achieved a GNI per capita of
1620 USD in current dollars respectively 3710 international USD in PPP-adjusted terms
(World Bank)
...
Beginning with a growth rate of 3
...
81% in 2004
...
6 to 38
...
17 In 2007, the
total fertility rate was 3
...

4
...
4 Microfinance Institutions in selected Asian Countries
For Cambodia, I have chosen AMRET Co
...
, CHC-Limited Micro Finance Institution (CHC-Ltd
...
(HKL), PRASAC MFI Ltd
...
(VFC)
...

Also for Cambodian MFIs, one observes a clear positive development in the number
of employees (see Figure 9), which applies to clients, as well
...
It seems characteristical that the percentage of female borrowers lies mostly well above 50%, yet the internal development is
15

Numbers computed from Penn World Table data
...

17
Numbers computed from Penn World Table data
...
While high volatility can be observed for HKL
and PRASAC, VFC’s percentage of female borrowers is, for example, mostly stable
...
7 women per male borrower in 2008
...
shows a negative trend
...
Here, savings are clearly higher than loans by factors up to 29
...

The lowest ratio of credit to savings was reached in the year 2000, when an average
of 6
...
While VFC
used to reveal the typical pattern of loans exceeding savings, this trend has inverted in
recent years
...
For CHC-Ltd
...

For the microfinance institution SATHAPANA, data on the percentage of clients starting a microenterprise for the first time and on percentages of clients living in moderate
poverty were published for the period from 2001 and 2004
...
Nevertheless, a fairly high percentage of around 40% of the poor
started small businesses for the first time
...

Indeed, Yunus (2007) argues that enhancing private entrepreneurship contributes more
to poverty reduction than standard employment does (p
...
This is based on the belief that every human being may act as potential

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4 Empirical Analyses

Figure 10: Percentage of female borrowers in Cambodian MFIs

entrepreneur taking advantage of his economic capacity as a vehicle to surmount poverty
(Yunus, p
...

As Philippine microfinance institutions, I have selected the Life Bank Foundation, Inc
...
(NWTF), and the TSPI Development
Corporation
...

Also here, a clear positive trend in the size of microfinance institutions is apparent
...
1 from initially
39 employees in 2003 to 782 in 2007, those being already quite large in the beginning of
the period of observation grew less, but by partially important factors
...
NWTF still increased
in size by 58%
...
7 between 1997 and 2008 in this
regard
...
1 within four years only
...
As the focus on female clients is
especially obvious here, one should also note the discussion on gender inequality to which
attention was drawn by Barsoum (2006), for instance
...

Excluding microfinance services are hence regarded as not sustainable in the long run
...
The focus on microcredit is especially clear here,
which might either be due to the fact that the economic situation of microfinance clients
does not yet allow for higher saving deposits, or that the institutions’s focus really is
on lending
...


4
...
First, a
response variable that represents a suitable proxy for development within a country
must be specified and its justification, advantages and disadvantages should be discussed

28

4 Empirical Analyses

Figure 12: Number of active borrowers and savers in Philippine MFIs

carefully (see chapter 4
...
1)
...
4
...
Finally, an econometric model which is able to capture effects on
development in an appropriate way has to be specified (see chapter 4
...
3)
...
4
...
4
...

4
...
1 Discussion of Appropriate Response Variables
Development has a broad dimension and so are its definitions
...
1
...
In other
words: relevant explanatory variables from MFIs have to show a causal relationship with
the response variable which, in turn, has to be a valid estimator for development
...
In chapter 3
...
Sustainable long-term development implies convergence to a positive steady state
kSS > 0, where kSS > k0 (see Figure 2)
...
As long as ki < k0 , the equilibrium to which
˜
a country converges is kSS = 0
...
The
inherent problem is that passing k0 from below towards a positive steady state capital

29

4 Empirical Analyses
accumulation level kSS can not be explained endogenously by the given model
...
This can be achieved, for example, by changing the functional form of g(k) from
S-shape to concavity
...
If
appropriate mechanisms work at any level of income, a constant saving rate may be
realised
...
They
can offer incentives to save through different channels
...
Also, a way to achieve positive and increasing savings and/or saving rates is to guarantee the opportunity to save within a secure
environment provided by an MFI’s authority
...
If these factors (and first and foremost microcredit) have a significant effect on savings, then microfinance institutions do
contribute to development within a country
...
But as the number of microfinance institutions studied
in the econometric part of this paper is sufficiently large, major trends and patterns
should be observable equally well
...
19 It takes
one step further than Armend´riz and Morduch (2005) who used borrowers’ income for
a
impact measurements
...
However, this approach
18

Note that high population growth rates lead to an increased slope in the depreciation function d(k)
...
As developing countries often have high population growth rates, this
pattern proves to be a crucial aspect of the velocity of development depending on which side of
k0 a country stands
...

19
Also Masanjala (2002) points out that it is primarily the ability to save from profits obtained in small
microfinance businesses which contribute to poverty alleviation, not the grant of credit itself (p
...


30

4 Empirical Analyses
is more controversial than savings, as an increase in average loans granted to individuals
can reflect both positive contributions to development and contrary causes
...
Subsequent to a successful business
project enabled through microcredit, a second loan may be provided which is likely to
exceed the precedent amount
...

However, high loans may also stem from a relatively wealthier target group of a microfinance institution, obtaining higher loans due to better solvency from the beginning,
which does not necessarily reflect an improvement of the economic situation of the a population’s poorest part through microcredit itself
...
Besides, available data is restricted
such that repeated loans to the same (group of) individuals can not be separated, and
thus the effects of repeated loans on saving behaviour can not be studied explicitely
...

4
...
2 Discussion of Relevant Explanatory Variables
After the discussion of possible response variables as estimates for development in the
previous chapter, the next step is to identify factors within a microfinance institution
which may affect development
...
Then, the theoretical appropriateness of previously
selected variables with respect to credit as second response variable is reviewed
...
20
The absolute size of a microfinance institution may affect the decision of individuals
whether to sign a financial contract with an MFI
...
The larger an MFI, the more experience it may have acquired and the higher the
probability for an individual to join as client
...

20

For the time being, actual data availability across MFIs is ignored for the purpose of consistent
theoretical reasoning
...
A number of clients also start microenterprises
...
An interaction term (b × F M E)
captures a possible dependence between the decision to establish a small business and
the average loan that is granted by the microfinance institution
...
The
range of granted loans’ size should reflect the actually targeted group
...
In this regard, the image of the
concerned microfinance institution can contribute to poor people’s affirmative attitude
towards savings
...

Country-specific factors can result in possible differences between an MFI’s impact
on development, as well
...
Instead, a set Ci of country dummies could be employed in case it is reasonable
to assume significant differences in country-specific impacts
...
By defining a separate dummy for each
country, that is
Ci =

1 if MFI is operating in country i
0 otherwise

(∀i ∈ [0, 1, 2, 3]) and including C1 , C2 , and C3 into the regression equation, the problem
of perfect multicollinearity would not occur (Carter Hill, Griffiths, & Judge, 2001, pp
...
Ethiopia (for i = 0) would appear as reference group here
...


32

4 Empirical Analyses
The continent dummy A can capture part of the variation in response variables that is
not gauged by MFI-related explanatory variables
...
Although it is
averaged and can be biased if income is distributed highly unequally, it is still commonly
perceived as a good choice
...

Based on the Lorenz Curve describing cumulative national income as a function of
cumulative population, one can calculate the Gini coefficient with a range between 0
and 1 and use it as an estimate for inequality
...
Saving
depends on necessity and income level, but a correlation to national income distribution
is not convincing
...
It is sensible to verify if changes in a variable
for which a theoretical causal relation to savings is reasonable is also able to explain
changes in credit
...
For example, larger MFIs could revert to larger
funds from investors resulting in larger and/or more loans which can be granted to the
poor
...
Credit may vary depending
on the business idea proposed by microfinance clients and also on the percentage of
clients engaging in small businesses for the first time
...
It is not sensible to
consider the interaction term (b × F M I) and the percentage of loans smaller than 300
USD, however the economic control variable GDP pc as well as the continent dummy A
shall remain
...
As shown in
chapter 4
...
In fact, many have specialised in lending to women only (Counts, 2008, p
...
He implicitly argues that it is more probable for women to repay loans compared to
men
...
3)
...
An MFI may adapt its lending policies to the needs of women,
for example concerning the amount of credit needed
...

4
...
3 Statistical Regression Analysis by Ordinary Least Squares
The response variables discussed in chapter 4
...
1 have both advantages and disadvantages
...
The first set of models is truly linear, the second has a double
logarithmical form
...
However, Timax ≤ 12 does not
fulfil the assumption of a sufficient number of observations to obtain reliable regression
results
...
The intention is to provide cross-sectional results in the first
place, and to give an idea about possible differences in the variables’ marginal impact
on development over time by comparing the findings from t0 to t1
...
All models are estimated by ordinary least squares
...
4
...
4
...
Model (6) is the corresponding equation with average loan balance
per active borrower in USD, b, as dependent variable
...
Hence, F M E,
(b × F M E), and loans<300 can not be included into regression analyses
...
4
...
4
...


34

(5)

4 Empirical Analyses
bi = α + β1 ni + β2 pi + β4 si + β5 fi + δAi + γGDP pci + i
...
As such, the initial models
(5) and (6) can be rewritten as

si = α + nβ1 + pβ2 + bβ3 + δAi + GDP pcγ +
i
i
i
i

(7)

i

bi = α + nβ1 + pβ2 + sβ4 + fiβ5 + δAi + GDP pcγ +
i
i
i
i

i

(8)

and, taking natural logarithms where possible23 ,

ln(si ) = ln(α) + β1 ln(ni ) + β2 ln(pi ) + β3 ln(bi ) + δAi + γln(GDP pci ) + i
...
(10)
In models (5) and (7) respectively (9), positive incremental changes in credit are
assumed to have a positive impact on savings, thus β3 > 0
...

Though, it is not clear a priori to which extent an additional dollar of credit is able to
increase savings
...
This implies the hypothesis of
δ < 0
...

Concerning the number of personnel per MFI as a proxy for its size and the number of
years since its foundation I argued that these parameters may have a positive impact on
savings
...
A large MFI can regionally be better
known and induce further people to start saving
...
Suppose they would like to save
and open a savings account, but their income is still too low to allow for savings at all
...


35

4 Empirical Analyses
In this scenario, it is likely that β1 = β2 = 0
...

Which direction should the signs of estimated coefficients have if credit is used as a
response variable?
As emphasised earlier, credit is ambiguous as development indicator
...
However, in order to obtain credit, a client must
prove to be creditworthy, which basically will be determined by the individual’s choice of
joining a lending group with specific characteristics
...

Its funds are composed by donors’ contributions and savings deposits
...
From the merely
technical point of view, an MFI should be able to issue higher loans when being larger
compared to other institutions
...
A similar proxy
is the number of years that an MFI has already operated locally
...
This implies
the ability to issue higher credit as a consequence and hence, justifies the assumption
of β1 > 0
...
Of course, large amounts of credit can both
be traced back to either high initial loan levels or to increased loans due to successful
microcredit supported businesses before
...
The
hypothesis is thus β4 > 0
...
4
...
Nevertheless, it is not clear a priori if a higher
percentage of female borrowers induces the MFI to offer smaller or larger loans
...
Or it may
offer smaller loans if the businesses of female clients would require less financial support
than those of their male counterparts
...
The assumed signs of δ and
γ should not change in this setting, as better economic conditions should enhance the
general financial situation and, therefore, both savings and credit
...
4
...
Then, corresponding results for credit as dependent variable are discussed
...

The regression of the linear ordinary least squares model (5) is run with a total of
71 observations across countries
...
The results of this
modified data set are reported in Table 1
...
n and GDP pc are significant at the
10%-level
...
The model explains
19
...

Plotting the regression’s residuals against fitted values of s, one may argue in favour
of slight heteroscedasticity
...

Hence, depending on the chosen level of significance, standard errors obtained from this
regression are considered either valid or not valid
...
According
to Long and Ervin (2000), it is difficult to detect heteroscedasticty for sample sizes
smaller that 250 (pp
...
In 1979, Breusch
and Pagan argued that the test’s power was appropriate for samples larger than 40,
however only for α = 0
...
10 (p
...
At the 1%-level, power is not as
high and the test more often falsely accepts the null of homoscedastcity
...
224)
...
For the sake of comparison, regression results are reported for both standard
and heteroscedasticity adjusted standard errors
...
The client base of larger MFIs may be more diversified
24

Cook’s distance is a joint measure for outliers in terms of extreme observations of explanatory variables and fitted values of the dependent variable with large residuals
...


37

4 Empirical Analyses
in terms of saving capacity than within smaller institutions, and so may it be due to
experience of longer existing MFIs to which a broader range of clients may come
...
However, there are neither convincing
explanations why larger average credit should contribute to heteroscedasticity, nor why
volatility should be higher in Africa than in Asia
...
If homoscedasticity
is however rejected, I use HC3 heteroscedasticity consistent standard errors
...
223)
...
Here, b remains significant
(though only at the 5%-level), but all other estimates become insignificant
...

Hence, if changes in this variable do not seem to have a significant impact on savings,
it is sensible to estimate a reduced model without p, thus

si = α + β1 ni + β3 bi + δAi + γGDP pci + i
...
Also here, interpretation of the residual’s
variance is ambiguous
...
A Breusch-Pagan test again accepts the null of
constant variance of residuals at the 5%-level, but rejects at the 1%-level
...

The overall best estimation is provided by model (11) without HC3, considering that
homoscedasticity was accepted at the 5%-level
...
38% of the variation in savings is explained
...
On average, an increase in credit of 1 USD
25

e2
ˆ

i
Note that σi = (1−rii )2 under HC3, where rii is the diagonal element of the projection matrix
ˆ2
−1
R = X(X X) X
...


Model (5)

Model (5)
(HC3)
1009
...
21
(379
...
04)
0
...
48**
(0
...
21)
-8
...
42
(4
...
24)
-0
...
03
(0
...
12)
-756
...
92
(276
...
86)
-0
...
23
(0
...
30)
63
63
0
...
1922
4
...
24
0
...
0022
***: α = 0
...
05,

Model (11)
970
...
54)
0
...
16)
-8
...
92)

-739
...
93)
-0
...
13)
64
0
...
35
0
...
10

Model (11)
(HC3)
970
...
18)
0
...
20)
-8
...
23)

-739
...
96)
-0
...
25)
64
0
...
35
0
...
47 USD
...
Also, δ shows the expected
negative sign — savings in Africa are smaller than in Asia
...
An increase of per capita gross domestic product by 1 USD decreases average savings by 0
...
If per capita GDP increases on the base of price mechanisms instead of a rise in
the value of goods, then inflation is likely to be addressed by reducing saving deposits
temporarily
...

Do these results change if a Cobb-Douglas functional form is assumed?
The according regression results are reported in Table 2
...
The

39

4 Empirical Analyses
other estimated coefficients are however highly significant
...
17% and hence almost doubles compared to the truly linear model
...
Significance slightly decreases for A and GDP pc under HC3 estimation, but
no further variable becomes insignifiant
...
The explained variance of ln(s) of the reduced model

ln(si ) = ln(α) + β3 ln(bi ) + δAi + γln(GDP pci ) +

i

(12)

slightly increases from 36
...
08%
...
Under HC3 estimation, coefficients are still significantly different
from zero at least at the 5%-level
...
04% and as such, affirms the hypothesis of β3 > 0
...

The estimated coefficient of GDP pc is again negative
...
06% on average
...
Including not only a single continent dummy as in the above estimations, but also interaction terms between the continent dummy and each variable, none
of these ever becomes significant
...
However, the marginal impact of
several microfinance variables does not differ subject to different environments
...

How well can development be explained by credit as a proxy? To answer this question,
I apply the previous regression procedure to models (6) and (8) respectively (10)
...
As fewer microfinance
institutions have published data on this variable, the number of observations declines
to 49, though remains appropriate for econometric estimations
...


40

4 Empirical Analyses
Variable
ln(intercept)
ln(b)
ln(n)
ln(p)
A
ln(GDP pc)
degrees of freedom
adjusted R2
F-statistic
p-value (F)
Significance codes:
Standard errors in brackets
...
72**
15
...
25)
(8
...
04***
1
...
21)
(0
...
004
-0
...
30)
(0
...
02
-0
...
14)
(0
...
99***
-2
...
96)
(1
...
09***
-2
...
78)
(1
...
3617
0
...
82
8
...
0000
0
...
01, **: α = 0
...
37***
(5
...
04***
(0
...
96***
(0
...
06***
(0
...
3808
15
...
0000
*: α = 0
...
37**
(7
...
04***
(0
...
96**
(1
...
06**
(0
...
3808
15
...
0000

Table 2: Results for double logarithmic regressions with savings as response variable (t1 =
2006)

In contrast to previous results from the truly linear model, the years of experience is
the only variable with significant (positive) effect on credit
...
19%
of the total variance in credit, though the whole model per se would not be statistically
significant at the 1%-level
...

To examine if a reduced model is more appropriate, I propose to eliminate p only,
as this variable has proven not to be significant in any regression so far
...

A plot of residuals against fitted values of the response variable also shows non-constant variance of
residuals
...


Model (6)

Model (6)
(HC3)
433
...
38
(357
...
73)
0
...
07
(0
...
08)
-446
...
67
(267
...
77)
10
...
61
(4
...
37)
-0
...
17
(0
...
13)
-61
...
18
(217
...
28)
0
...
04
(0
...
14)
41
41
0
...
1919
2
...
86
0
...
0202
***: α = 0
...
05,

Model (13)
402
...
00)
0
...
07)
-337
...
70)
12
...
80)

-147
...
90)
-0
...
10)
42
0
...
99
0
...
10

Model (13)
(HC3)
402
...
75)
0
...
10)
-337
...
95)
12
...
17)

-147
...
73)
-0
...
13)
42
0
...
99
0
...
The
adjusted R2 increases to 24
...
However, only n is robust under HC3 estimation
...
An additional year of experience of the
MFI increases credit by 12
...
An increase in average savings by 1 USD
results in an increase in credit by 0
...

However, this result becomes insignificant in case of HC3 estimation
...

Taking into consideration the earlier discussion about the presence of heteroscedasticity,
one should prefer the HC3 estimation of model (13) as reliable and more conservative
result from the linear model here
...
The overall fit of the model
improves and a fairly higher adjusted R2 of 38
...
The coefficient of savings becomes significant at the 1%-level, n remains significant as well
...
As the logarithmic
specification has not achieved their significance as it did for savings, the model will once
again be estimated without A, GDP pc, p, and f , hence

ln(bi ) = ln(α) + β1 ln(ni ) + β4 ln(si ) + i
...
28%
...
27%
...
47%
...

As being said, these findings are based on data from 2006
...
27
With savings as response variable, an ordinary least squares regression of the truly
linear model (5) becomes completely insignificant
...
73∗∗ )
...
67 and β1 = 12
...
With this model
specification, 68
...
In addition, the double
logarithmic specification of model (10) yields an estimate of the coefficient of size at the
ˆ
same level of significance (β2 = −0
...
The adjusted R2 decreases to 61
...
64%
...
In 2003, the marginal effect of institutional
size on granted credit seemed to be negative
...


43

4 Empirical Analyses
Variable
ln(intercept)
ln(s)
ln(f )
ln(n)
ln(p)
A
ln(GDP pc)
degrees of freedom
adjusted R2
F-statistic
p-value (F)
Significance codes:
Standard errors in brackets
...
65
-0
...
92)
(4
...
27***
0
...
07)
(0
...
53
-0
...
37)
(0
...
47**
0
...
19)
(0
...
08
-0
...
09)
(0
...
31
0
...
61)
(0
...
49
0
...
48)
(0
...
3864
0
...
93
5
...
0002
0
...
01, **: α = 0
...
72***
(0
...
27***
(0
...
72***
(0
...
27***
(0
...
55***
(0
...
55***
(0
...
3928
0
...
20
16
...
0000
0
...
10

Table 4: Results for double logarithmic regressions with credit as response variable (t1 =
2006)

male borrowers on credit proves to be significantly negative on average
...

Contrasting the findings from 2003 and 2006, the following can be summarised:
First, savings as development indicator can only be explained in 2006 with the presented models
...
On average, a marginal increase in credit
has a positive impact on development
...
Small changes in gross domestic product per capita also show
a negative impact on development in terms of savings accounts, which may be traced
back to price mechanisms
...
The most important effect is the MFI’s experience,
measured by n, which has a positive effect at all times
...
Though, the percentage of female borrowers
is significantly negative in 2003, but not in 2006
...

Third, economic control variables (here, a continent dummy and per capita gross
domestic product), are only significant in 2006 in regressions involving savings as response variable
...
Yet, these only seem to matter in recent years
...
4
...
If both s and b are considered as appropriate proxies for development
and one assumes a mutually interdependent relation between both of them, then the
equations should be considered as simultaneous equation system to obtain unbiased
estimates for βj , δ, and γ
...
Microfinance institutions operating in selected African countries are
highlighted in orange, those working in Asia in black
...
As this paper studies different ways
to estimate development and aims at proposing the best and most consistent method,
simultaneity is implicitly precluded
...
Part of the data is quite large in its magnitude, especially for Asia
...
4
...
If the latter can be traced back to extraordinary performance of
microfinance institutions, the result would be perfectly in lign with successful realisation
of microfinance objectives
...
The data base does not allow for an answer of the nature of

45

4 Empirical Analyses

Figure 13: Correlation between savings and loans across MFIs in Ethiopia, Uganda,
Cambodia, and the Philippines in 2006

this question
...

Another point of interest are interest rates on loans and savings
...
On the part of
microfinance institutions, one might expect higher interests due to higher risk of default
...

The MixMarket data base is not encompassing, and interest rates of any kind are not
available
...

Suppose the true model includes interest rates and other possibly relevant variables,
which are though not included in regression models
...


(15)

X is a matrix including all variables taken into consideration for regression analyses
and Z is a matrix including all further relevant, though omitted, variables
...
i
...

with ∼ N (0, 1)
...

As long as X Z = 0, that is, unless X and Z are orthogonal to each other, all estimates
for β are biased and inconsistent
...
g
...
If cov(r, y) > 0, then β is overestimated
...

This problem remains immanent, however there is some evidence mitigating its severity
...
Collateral requirements were reported
as the far more important reason to refrain from standard banking institutions’ services
(p
...


47

4 Empirical Analyses

4
...
5
...
In the MixMarket data base, the longest time series traces back to
1997 (as for example in case of FINCA in Uganda)
...
Though, given that data is
in fact regularly collected by an MFI, ideally monthly since its foundation, and given that
the institution would provide access to these data for the purpose of empirical research,
one could obtain results either from a time series analysis per individual microfinance
institution, or from an (im)balanced panel analysis across several MFIs and time
...
For example, country-specific effects at any point
in time can be compared
...
5
...
4 and the idea discussed in the previous subchapter are based on response
variables with variance larger than one, and a model specification that allows for direct
interpretation of estimated marginal effects βj for any explanatory variable xj
...

But the question on how and to which extent a microfinance institution can influence development may not only be formulated in terms of real marginal effects, but
also in terms of marginal probabilities
...
By using a non-linear econometric binary
choice model with either Probit or Logit specification, the response variable would become binary with values 0 or 1
...
By numerical optimisation,
a maximum likelihood estimator of β1 and β2 can be obtained
...
The fact that ”the maximum likelihood
estimator is normally distributed, consistent, and best, in the sense that no competing
estimator has smaller variances” (Carter, Griffiths & Judge, 2001, p
...
A variance samller than one28 of the response variable does
not necessarily have to affect results in a negative way
...

The challenge of this alternative approach is to find — or define — a response variable
with properties described above, which is able to describe development in an appropriate
way
...
From V AR(x) = E(x2 ) − [E(x)]2
k
and x = 1 − n follows that V AR(x) = k(n−k)
...


49

5 Conclusions

5 Conclusions
Yunus argues that ”[w]hen the time is right, a new idea is capable of transforming
the world” (Grameen Foundation), implying that an idea implemented at convenient
time may be a key element of poverty reduction
...

Based on descriptive analyses of selected microfinance institutions, it is striking that
the numbers of employees as well as clients have been strongly increasing during the past
decade, implying increasing demand for microfinance services
...
Augmented loan portfolios may also
be evoked by the success of group-lending schemes where a trigger strategy in repeated
microfinance games is responsible for well functioning repayment systems despite the
lack of standard collateral requirements
...
This approach is also the
most self-consistent and moreover theoretically well founded concept
...
47 USD on average
...

The perspectives for microfinance institutions in the future can thus be gauged as fairly
positive
...
The concept therefore is most likely
independent from differences in economic, political, and cultural factors
...

Further studies on this topic should focus on gathering more encompassing data on
microfinance institutions, inlcuding longer time series, and use them to conduct panel
studies, for instance
...


50

6 References

6 References
´
[1] Armendariz de Aghion, B
...
(2005)
...
Cambridge (MA): MIT Press
...
(2006)
...
Canadian Journal of Development Studies 27 (1), pp
...

[3] Breusch, T
...
and Pagan, A
...
(1979)
...
Econometrica 47 (5), pp
...

[4] Carter Hill, R
...
E
...
G
...
Undergraduate
Econometrics
...
) Hoboken (NJ): Wiley
...
(2008)
...
How Nobel Prize Winner Muhammad Yunus and Microfinance Are Changing the World
...
”) Hoboken
(NJ): Wiley
...
and Fischbacher, U
...
Why social preferences matter — the
impact of non-selfish motives on competition, cooperation and incentives
...
C1–C33
...
(2009)
...
www
...
org/index
...

[8] Grameen Foundation
...
Creating a World Without Poverty
...

grameenfoundation
...
php, retrieved on May 29, 2009
...
H
...
Econometric Analysis
...
Upper Saddle River
(NJ): Prentice Hall
...
M
...
Assortative Matching, Adverse Selection, and Group
Lending
...
2006-WP-07
...
(2004)
...
Selected Findings
and Issues
...
43
...
(1955)
...
American Economic Review 45 (1), pp
...


51

6 References
[13] Long, J
...
and Ervin, L
...
(2000)
...
The American Statistician 54 (3), pp
...

[14] Masanjala, W
...
(2002)
...
Canadian Journal of Development Studies 23 (1), pp
...

[15] MixMarket
...
www
...
org, retrieved on June 16, 2009
...
(1999)
...
Journal of Economic Literature
37 (4), pp
...

[17] Musinguzi, P
...
(2000)
...

Unpublished discussion paper, University of Southhampton Discussion Papers in
Economics and Econometrics 0016, University of Southhampton, Great Britain
...
(2006)
...
nobelpeaceprize
...

[19] Sachs, J
...
(2005)
...
London: Penguin Books
...
, McArthur, J
...
, Schmidt-Traub, G
...
, Bahadur,
C
...
, and McCord, G
...
Ending Africa’s Poverty Trap
...
117–240
...
(2007)
...
Scriptum for the lecture ”Entwicklungsl¨nder in der Weltwirtschaft”, autumn term 2007
...

[22] World Bank
...
World Bank
...
html, retrieved on June 21, 2009
...
http://web
...
org/WBSITE/EXTERNAL/DATASTATI
STICS/0,,contentMDK:20535285∼menuPK:1192694∼pagePK:64133150∼piPK:64
133175∼theSitePK:239419,00
...


52

6 References
[24] The World Factbook
...
cia
...

[25] Yunus, M
...
Banker to the Poor: Micro-Lending and the Battle Against
World Poverty
...

[26] Yunus, M
...
Creating a World Without Poverty
...
New York (NY): PublicAffairs
...
(2008, 3rd December)
...


53



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