quantitative approach to measure impact of microfinance

Journal of International Development

J. Int. Dev. 16, 331–353 (2004)

Published online in Wiley InterScience (www.interscience.wiley.com). DOI: 10.1002/jid.1081

QUANTITATIVE APPROACH TO IMPACTANALYSIS OF MICROFINANCE

PROGRAMMES IN BANGLADESH—WHATHAVE WE LEARNED?

M. A. BAQUI KHALILY*

Department of Finance and Banking, University of Dhaka, Bangladesh

Abstract: The quantitative impact assessment of microfinance programmes, like the pro-

grammes themselves, originated in Bangladesh. This essay reflects on the significance and

usefulness for present day researchers of the analytical advances made in Bangladesh

since the beginning of the 1990s. Particularly in the area of selection bias, fungibility and

the assessment of wider impacts, it argues, those advances are crucial, and need to be borne

in mind by all practitioners; but financial sustainability remains an unresolved problem.

Copyright # 2004 John Wiley & Sons, Ltd.

Microfinance as a concept is nothing new. But it did not draw the attention of the

professionals, international agencies, and policymakers until microfinance as a concept for

poverty alleviation through institutional mechanisms was globally perceived. The Gram-

een experiments and the successful operation of Grameen Bank have led to the wider

acceptability of the strategy that the access to credit of the poor households through

institutional arrangements matters. The institutional mechanism is based on the concept of

‘group-lending’. ‘Group-based’ production technologies are diverse in Bangladesh. The

production technologies used by BRAC, ASA and PROSHIKA are different in nature.

It has been over two decades that microfinance services are being provided to the poor

households through microfinance institutions. As the goal of providing such services has

all along been poverty alleviation, quite a large number of impact studies have been

conducted in Bangladesh. However, the objectives of the studies have been diverse. Most

of the studies evaluated impact at the household level (e.g., Khandker, 1998a; Zohir et al.,

2001; Pitt and Khandker, 1998b; Mustafa et al., 1996; Husain, 1998). Few studies have

focused on the supply-side analysis of impact of microfinance (e.g., Khandker et al., 1995;

Copyright # 2004 John Wiley & Sons, Ltd.

*Correspondence to: M. A. Baqui Khalily, Department of Finance and Banking, University of Dhaka, Dhaka1000, Bangladesh. E-mail: [email protected]

Khalily et al., 2002), but none have been conducted from the macroeconomic perspective.

Consequently, we have incomplete understanding of the impact of microfinance both at

the micro and macro level.

Impact analysis, using demand-side or household level data, has dominated the

microfinance research agenda during the past decade. Quite a large number of studies

have been conducted with diversified methodologies—quantitative and qualitative mod-

els. The general conclusion of the studies has been positive impact of micro credit at the

household, enterprise and individual levels. Extent of impact is the subject of the

quantitative approach to impact analysis. The approaches to and the methods of impact

assessment are diverse. They vary from descriptive to econometric; from limited use to

extensive use of econometric techniques. What lessons do we get from such analysis?

These questions are addressed in this paper.

MICROFINANCE IN PERSPECTIVE

Microfinance has been viewed from different perspectives. A very common perspective

has been poverty alleviation. Most studies have focused on determining the extent of

impact at the household level (e.g. Khandker, 1998; Husain, 1998; Zohir et al., 2001).

Micro credit impacts on poverty reduction through its impact on income, employment,

consumption, asset accumulation and savings.

But over-excitement of impact of microfinance in poverty alleviation tends to under-

mine the long-term role of micro finance in the sustainability of MFIs. The failure of

development banks and the adverse impact of distortions in rural financial markets (e.g.,

Von Pischke et al., 1993; Adams et al., 1984; Braverman and Guasch, 1989; Meyer and

Nagarajan, 2000) have caused emphasis to be placed on sustainability of microfinance

institutions as a process of developing rural financial markets and sustaining credit

facilities for the poor households (e.g. Khalily et al., 2000; Khandker et al., 1995; Yaron,

1992). However, the development sociologists view the contribution of microfinance and

microfinance institutions as the process of reducing the role of the state in financial

markets.

In the absence of ownership and/or regulation, the utility function of MFI top execu-

tives may dominate idealized patterns of organizational behaviour. In recent years, the

role of MFIs has been viewed more as a search for political influence. Cheap donor money

may contribute to such a process of promotion of political interests. In addition, cheap

money may make operation costly in the absence of any incentive for cost-effective

operations. These are likely to undermine the basic role of micro finance in poverty

alleviation.

Poor households do not have higher income level that can absorb adverse effects of

external shocks. Zaman using BRAC experience showed that micro finance contributes to

consumption-smoothening and minimizing vulnerability. Similar findings were also

derived in other studies (e.g., Sen, 2001).

Feminists and gender specialists argue that microfinance empowers women because

access to micro-credit has increased their role in family decision-making. The female

members are not only involved in economic decisions but also in family well-being.

Several empirical studies provide empirical evidence of women’s empowerment because

of microfinance (Hashemi, Schuler and Riley, 1996; Mayoux, 1999; Mahmud, 2001a,b;

Halder, 1998).

332 M. A. Baqui Khalily

Copyright # 2004 John Wiley & Sons, Ltd. J. Int. Dev. 16, 331–353 (2004)

MICROFINANCE PROGRAMMES FOR POVERTYALLEVIATION

IN BANGLADESH

In the late seventies and early eighties, two approaches were experimented for financing

poverty alleviation programmes of non-government organizations. One was the external-

finance based experiment as adopted by Grameen Bank, and the other was the self-reliant

model experimented by BRAC and ASA. The Grameen model experimentally made use of

bank credit for its expansion. The underlying thesis was that access to external credit

would accelerate the process of poverty alleviation. BRAC started its initial experiment on

self-reliance based on local resource mobilization in the early seventies. ASA did

experiment with a similar approach in the eighties. These experiments led to the general

conclusion that the pace of poverty alleviation, based on mobilization of local resources, is

very slow and negligible in most cases because of limited surplus resources. The success

of the Grameen Bank model and the limited success of local-resource based approach led

to searching for external finance. Bangladesh Bank as well as the international agencies

contributed to the early take-off of microfinance in Bangladesh. The major MFIs, like

ASA, PROSHIKA and BRAC, have been highly dependent on cheap funds.

During the past two decades there has been a wide expansion of microfinance services

in Bangladesh. There is no precise estimate of the number of MFIs and the number of

branches operating in the country. However, it is widely believed that more than 1000

MFIs with a network of over 4000 branches have been operating. It is a sector that has

created jobs for over 100 000 employees.

MFIs have grown over time with both government and non-government ownership. The

major programmes of the government are Bangladesh Rural Development Board (BRDB)

and Palli Daridro Bimochon Foundation (Rural Poverty Alleviation Foundation).

Grameen Bank is recognized as a specialized bank. The other MFIs are non-government

entities (to be referred subsequently as non-government MFIs). Until December 2001, 632

Table 1. Structure of microfinance in Bangladesh, 2000–01 (In Million)

MFIs Total active Total Cumulative Outstandingmembers net savings disbursement loan

Grameen 2.38 11 758.00 147 048.00 13 151.00

% 12.54 48.55 40.48 28.25

BRAC 3.51 4614.56 77 593.75 8537.83

% 18.50 19.06 21.36 18.34

ASA 1.98 2010.12 43 704.18 7309.52

% 10.44 8.30 12.03 15.70

Proshika 2.64 1639.97 20 611.88 5009.40

% 13.92 6.77 5.67 10.76

Top 22 except top 3 MFIs 2.66 2005.25 27 343.64 4953.67

% 14.02 8.28 7.53 10.64

BRDB 3.6 0 21 090.00 3387.00

% 18.98 0.00 5.81 7.28

PDBF 0.29 481 7746.00 716

% 1.53 1.99 2.13 1.54

Other small MFIs 1.91 1708.13 18 085.79 3486.63

% 10.07 7.05 4.98 7.49

Total 18.97 24 217.04 363 223.24 46 551.05

(100) (100) (100) (100)

Source: Credit and Development Forum (CDF), MFI Statistics, June 2002.

Microfinance Programmes in Bangladesh 333


MFIs including Grameen Bank and two government programmes had active members of

18.97 million and disbursed a cumulative total of Tk. 363 billion, and loans outstanding of

Tk. 46.6 billion (Table 1). The share of Grameen Bank has been around 13 per cent. Three

leading non-government MFIs (ASA, BRAC and PROSHIKA) constitute around 43

per cent of total members mobilized. Although the share in membership of Grameen Bank

is around 13 per cent, its share in loans outstanding has been around 29 per cent. This is

because of increasing loan size. Two government programmes with a share of around

22 per cent in membership mobilization had loans outstanding of Tk. 4 billion by the end of

2001 (Table 1). This suggests that non-government MFIs provide credit to the almost fifty

per cent of the aggregate members mobilized. This large amount of disbursement (annual

disbursement of over Taka 40 billion annually) is likely to have wider impact at the

household, individual and village levels.

PERSPECTIVE OF IMPACT ANALYSIS

Poor households are subject to liquidity constraints. As such, any additional flow of

external financial resources, be it from MFIs or banks or individuals, will relax the

intensity of this constraint. Hence, it will enable the households to broaden the portfolio

mix, which in turn will have positive impact outcomes at the household level. Outcomes

may be classified into intermediate-outcomes and end-outcome. Intermediate outcomes

include income, consumption expenditures, assets accumulation, savings, child education,

nutritional intake and employment. Poverty reduction is the end-outcome. All the

intermediate outcomes have a compounded impact on the end-outcome. However,

feminists, development sociologists and women professionals may consider female

empowerment an end-outcome as well. But given the historical underlying reason of

the emergence of microfinance, poverty-reduction is the end-outcome. Women’s empow-

erment may be termed a spillover impact of intermediate outcomes. At the enterprise level,

impacts will increase in terms of revenue, profit, assets, and employment, among others

(Chen and Dunn, 1996; Dunn and Arbuckle, 2001; Sinha, 1998). At the individual level,

impacts are found in women’s empowerment and increase in personal savings among

others In addition, there will always have spillover impacts—increase in wages; invest-

ment (Khandker, 1998a; Hulme, 2000).

Finance will always have positive impact at the household level or at the individual level

when such credit is more structured and targeted with strict monitoring. Because of such

obvious impact, professionals often question the need for impact assessment (as quoted in

Morduch). Nevertheless, there is still the need for assessing the extent of outcome on

several grounds. First, financial resources should be allocated efficiently so that there can

be a net positive welfare gain. Second, the microfinance programme impact can be

externally validated for continuity in intervention. Third, effectiveness of microfinance

can be compared against the rate of return on alternative uses, which in turn will contribute

to efficient allocation of resources. Fourth, there will be deeper understanding of the

process through which microfinance intervention benefits poor households and the process

through which spillover impacts occur at the village and regional level. On the top of these

arguments, donors have a special preference for impact analysis in order to justify their

investment to their taxpayers. Impact studies are donor-driven. They have little utility to

the MFIs (Hulme, 2000). Nevertheless the findings add to our knowledge. How credible is

the knowledge? We now examine this question.



METHODOLOGICAL DEBATE IN DEMAND SIDE ANALYSIS:

WHAT DO WE LEARN?

Quite a large number of studies have been conducted on the impact of microfinance or

micro credit at the household level during the past fifteen years. Morduch and Haley

(2002) have done a comprehensive review of the impact literature. The researchers in the

AIMS project of USAID conducted a review of the selected major studies. In Bangladesh,

Rahman (1998) conducted a comprehensive survey of the impact studies carried out in

Bangladesh. This section is drawn upon those reviews.

Fundamentally, there has been debate over the methodologies of impact studies. Such

debate arises because of possible selection bias, endogeneity of program placement and

fungibility of fund. As Gaile and Foster argue, impact research focuses on precision and

accurate assessment of impact. Hulme describes the methodological issue as complex

because of selection bias and endogeneity. Hulme (2000) identifies several sources of

selection bias: (i) locational selection; (ii) difference in ‘invisible’ attributes between the

treatment group and control group; (iii) Hawthorne effect of intervention on treatment

group; (iv) contamination of control groups by treatment groups; and (v) fungibility of

micro credit. Methodologies followed in different studies are not necessarily consistent

and unique, and have not been able to control the sources of selection bias. Nevertheless,

there is a consensus that programme endogeneity and selection bias have to be tackled

appropriately for reliable estimates of the impact.

The decision of individuals to participate or not to participate in microfinance

programmes is determined by the extent of incentives provided by microfinance institu-

tions, given observable and unobservable characteristics of the family and the individuals

including financial wealth. The personal and family characteristics, behaviour and

attitudes differ from individual to individual. Hence, they too emerge as the determinants

of programme participation. The known and observable characteristics can be defined and

measured, but there will be always be some unobservable characteristics that have

influence on programme participation. The extent of impact of credit is, however, also

impacted by programme placement. It is well evident that microfinance institutions place

their branches in accessible and infrastructurally developed areas (e.g., Khandker, 1995).

Hence, programme placement does have impact on the outcome at the borrower level.

However, identifying the socio-eco-political factors and environment in assessing pro-

gramme impact at the household level can control this endogeneity. Hulme argues that

with the exception of fungibility, other sources of selection bias can be tackled through

careful selection of control groups. Most of the studies (e.g., Pitt and Khandker, 1996;

Mustafa et al., 1996; Hashemi et al., 1996; Chen and Dunn, 1996; Dunn and Arbuckle,

2001; Coleman, 1999) used quasi-experimental design (treatment group and control

group) to estimate the effect of micro credit. The difference between the parameter

estimates of treatment and control groups is the effect of intervention. However, precision

depends on the ability to control for observable and unobservable characteristics.

The issue of fungibility of credit is a critical problem in precisely determining the impact

of credit (Adams et al., 1984; David and Meyer, 1983; Von Pischke 1983). This arises from

inability to separate out the uses of micro credit and other funds between households and

enterprise. No studies have successfully controlled for fungibility. It is a matter of concern,

as argued by Hulme (2000), when impact studies ‘focus exclusively on the enterprise’. The

problem is equally present when there is inseparability of enterprises and household

activities and behaviour in most of the poor households, and inseparability between micro



credit and informal and/or formal credit. Khandker (1998b) has candidly recognized the

problem of fungibility in impact assessment. However, he argues that ‘the close monitor-

ing of group-based credit partly resolves the problem of fungibility’. Failure to control for

fungibility may over-estimate the impacts of micro credit intervention. This is particularly

true when households have access to multiple sources of credit (Khalily et al., 2002;

Husain et al., 1998; Khandker, 1998a; Sinha and Matin, 1998).

As the issue of fungibility is not fully tractable in the impact assessment of micro credit,

several other approaches have emerged for a better understanding of the process through

which micro credit intervention influences desired outcome. They are: case study, house-

hold economic portfolio and anthropological studies. Mosley (1997) positively argues for

extensive case study in order to understand the process and influence of interventions, and

identify the difference between intended use and actual use of micro credit in order to

control for fungibility. Similarly the anthropological approach to impact studies considers

households as system and interaction among the family members and other different

agents based on their utility functions (Gaile and Foster, 1996). This minimizes degree of

the so-called unobservable factors in ‘heavy-duty’ econometric studies. More information

is available in case-based and anthropological studies. However, a good combination of

case, anthropological and econometric approaches would provide comprehensive infor-

mation on the nature and process of intervention and its impact on desired outcomes.

Khandker and Faruquee (2001) used a different approach to study the impact of

agricultural credit on desired outcomes in Pakistan. They followed a two-stage approach.

In the first stage, demand for credit was determined using household-level and village/

regional-level characteristics. The predicted demand for credit was used as a variable in

the household welfare outcome models in the second stage. The variables included

instrumental variables and predicted demand for credit.

Although somewhat conventional in concept and approach, the AIMS Team used a

Household Economic Portfolio model. In the model, total household resources—inflow

and outflow—are accounted for. Three aspects—feminist, anthropology and economic—

were the underlying constituents of the framework. Based on both the case-study and

econometric approaches, the framework provides separate estimates of the impact of

microfinance on desired outcomes. The issue of fungibility is tackled within this approach.

REVIEWOF SELECTED IMPACT STUDIESWITH DIFFERENTAPPROACHES

Four major impact studies that used different approaches are discussed in this section.

They are: (i) the World Bank study (Khandker, 1998a) conducted in Bangladesh in 1992–

94; (ii) the BRAC studies (Mustafa et al., 1996, and Husain et al., 1998) on impact of

BRAC RDP credit in Bangladesh; (iii) the AIMS study (Dunn and Arbuckle, 2001)

conducted in Peru during mid-90s; and (iv) the PKSF study in Bangladesh (Zohir et al.,

2001). These studies are selected from the perspectives of quantitative methodology used

and coverage of the study.

The World Bank Study (Khandker, 1998a): Rigorous Econometric Analysis

The World Bank study was the first major study on the impact of microfinance in

Bangladesh conducted in 1992–94 by Khandker in collaboration with the Bangladesh



Institute of Development Studies (BIDS). The study examined and assessed the impact of

three major microfinance programmes—Grameen Bank, BRAC credit programmes (Rural

Development Programme and Rural Credit Programme) and RD-12, a government micro-

finance programme under the Bangladesh Rural Development Board—in Bangladesh.

Impact was assessed at three levels—household, village and institution. Considering the

scope, coverage, impact outcome set and comprehensive and sound methodology used, the

study is often regarded as ‘mother of all surveys in microfinance’. It is the first major study

that unearthed impact of microfinance and provided a good understanding of the extent

and the process through which microfinance influence its multiple target.

The survey was conducted over 1800 households selected randomly from 86 villages in

29 thanas. Of the 29 thanas, five thanas as non-programme control, and 24 thanas (eight

covering each of the programmes) as programme areas were selected. Three villages from

each thana were selected randomly. The targeted households were selected based on the

pre-study village census on selected characteristics. Targeted poor households were

selected based on landholding of less than or up to 50 decimals. Control households

included non-participants and non-target households (with landholding of more than 50

decimals).

The outcome parameters considered in the household level analysis were consumption,

savings, income, education, nutrition, and wealth accumulation. At the individual level,

the major indicator was female empowerment. The village level outcome parameters were

wage and employment. The institutional outcome parameters were outreach, cost effi-

ciency and sustainability. A set of comprehensive questionnaires were designed, pre-tested

and administered for data collection. In order to control for seasonality at the household

and village levels, three rounds of survey were conducted over the same set of households.

The major findings of the study were quite expected. First, micro-credit contributes to

poverty alleviation. At the household level, 5 per cent of Grameen and 3 per cent of BRAC

households rose above the poverty level every year. At the village level, there were

significant decline in moderate poverty and extreme poverty. Second, there has been an

increase in average household income by around 30 per cent for Grameen Bank and

33 per cent for BRAC clients. Several factors like increase in self-employment and

increase in wages because of shrinkage in labor supply may have contributed to it. Third,

as a consequent of decline in labour supply, wages in Grameen villages and self-

employment in off-farm economic activities in programme villages increased. Fourth,

marginal propensity of female borrowers to consumption out of loan was higher than that

of male borrowers. It was estimated at 18 per cent for women borrowers as against

11 per cent for male borrowers. Fifth, microfinance had positive impact on net worth. A

10 per cent increase in BRAC credit increased household net worth by 0.09 per cent, and

0.14 per cent for female borrowers. Sixth, the impact was positive on children’s schooling.

A one per cent increase in Grameen credit for female borrowers increases the probability

of school enrollment by 1.9 per cent for girls and 2.4 per cent for boys. Seventh, micro-

credit contributed to smoothening consumption and reducing vulnerability.

The major limitations of the demand-side analysis were failure to (i) control for

fungibility, and (ii) separate out effects of other sources of credit (informal and formal)

from that of microfinance on impact outcomes. Expected effects of these failures on

impact outcomes are probably ambiguous. However, these do not undermine the impact

findings. The findings are quite expected. Khandker (1998a) justified the micro-credit

intervention through comparative analysis of social-cost benefits of micro-credit and other

alternative interventions like the food for works programme.



One of the great strengths of the study is the application of sound econometric

techniques in solving the problems of endogeneity and determining efficiently impact

outcomes. As a result, the author could explain the impact of micro credit intervention on

welfare outcomes in terms of elasticity. The authors used maximum likelihood methods to

jointly determine the demand for credit and the impact outcomes. Based on the weighted

sampling, the authors tested for specification of the equations estimating impact outcomes.

The tests showed that credit impact by gender varies, being higher for women. The authors

finally estimated impact outcomes using fixed effect instrumental methods controlling for

both village and household heterogeneity. This enabled them to control for sample

selection bias.

The major conclusions were: microfinance makes a difference, and contributes to better

understanding of the comprehensive positive impact at the household and individual

levels. Not only that, microfinance impacts at the household and individual levels, it makes

an expected impact in labour market—higher wage because of increase in self-

employment and decline in the supply of labour.

The extent of impact as shown by Pitt and Khandker (1996) and Khandker (1998a) was

not free of any criticism. Morduch questioned the findings at the household level and

argued that due to sample bias, impact was over-estimated. He estimated that 30 per cent

of the programme participants had land of above 50 decimals. Using Khandker’s data set,

Morduch (1998) argued that the impact of Grameen Bank credit was minimal. However,

Pitt (1999) disagreed and re-estimated the impact outcomes, and showed that there were

no changes in the findings and the estimates were robust.

The AIMS Study in Peru (Dunn and Arbuckle, 2001): Household

Economic Portfolio Analysis

The major limitations of cross-sectional econometric-based studies (e.g., Khandker,

1998a) on impact of micro-credit are limited effectiveness in tackling the problem of

selection bias and attribution, and fungibility. The possible problems of selection bias and

attribution are much reduced in the studies using panel data. However, the problem of

fungibility is difficult to tackle. The assessing the Impact of Micro enterprise Services

(AIMS) project of USAID used the Household Economic Portfolio (HEP) framework for

assessing impact of micro enterprise services at three levels—household, enterprise and

individual. As argued by the AIMS Team, the HEP model tackles the problem of

fungibility as total household and economic activities along with total flow of financial

resources are considered. Under the project, three major studies were conducted in Peru,

India and Zimbabwe. The framework used was uniform. I decided to report the findings of

the Peru study for several reasons. First, during the period of study, the Peru economy was

in recession. Second, culturally Peru is different from Bangladesh. Differences between

the findings of the World Bank (Khandker) study in Bangladesh and the findings of the

Peru study may provide some understanding of the effectiveness of microfinance in a

different socio-cultural and political environments.

The Peru study evaluates the impact of a microfinance institution—Accion Comuni-

taria of Peru (ACP)—which later on became a bank, known as Mibanco. It is a

longitudinal study using data of 1997 and 1999, conducted over the same households

although some of the households in the 1997 survey were absent. The 1997 survey had a

sample of 701 households. Finally, the 1999 survey contained samples of 520 households,



of which 305 were in the treatment group and 175 were non-client control households. The

sample design was quasi-experimental. Several statistical techniques were used. The

changes in group-differences in impact variables between 1997 and 1999 were tested by

t-test. Analysis of covariance was used to test for impact hypotheses. Two steps were

followed in the ANCOVA procedures in the Peru study. First, it identified a matching

group of treatment and control households that have the same 1997 values for the impact

outcomes and moderating variables. In the second stage, a similarly matched group of

treatment and control households were identified using the 1999 values for impact

outcomes and moderating variables. Then the differences in outcomes and the effects

are statistically compared and tested.

Analyses were made at the enterprise, household and individual levels. At the enterprise

level, micro-credit has a positive impact on microenterprise net revenue (treatment group

had higher average profit of more than US$1000 than the non-client households),

accumulation of fixed assets (average accumulation in fixed assets was US$500 higher

for the treatment group), and employment generation (treatment group had provided about

9 more employment days).

The findings at the household level are little diverse. Impact of micro-credit was not

positive for all the outcomes. It had positive impact on income (treatment group had higher

per capita income of more than US$266 in real terms in 1999). Micro-credit as expected

had contributed to income diversification. No positive impact of micro credit on expen-

ditures on household appliances and education was reported. However, income-increase for

the treatment group contributed to increase in expenditure on food consumption.

At the individual level the findings of the Peru study are mixed. On the positive side,

micro-credit enables female borrowers to have control over financial decisions, and be

prepared for the future. But on the negative side, the study team did not find any positive

impact of micro-credit on personal savings, self esteem and respect from others.

Although the findings have been mixed, the study showed that finance matters for

poverty alleviation. Small loans make a difference but it may not be adequate to cope with

the adverse impact of externalities and economic recession. This is the evidence of the

Peru study. The extent of economic recession during 1997–99 was such that higher level of

enterprise profit and income diversification could not contribute to assets accumulation

and education expenditures because incremental income could not outweigh adverse

impact of economic recession and therefore, was mostly spent on food expenditures.

The BRAC Study (Mustafa et al., 1996; Husain, 1998):

A Comprehensive Descriptive Study

Bangladesh Rural Advancement Committee (BRAC) conducted two major impact studies

of the RDP credit programme in the 90s. Mustafa and his team conducted the first impact

study in 1992–93. Husain and his team conducted the second impact study in 1996–97.

The basic objective of the first impact study was to assess the impact of Rural Development

Programme (RDP) at the household and individual levels. In order to have a wider

understanding of the nature and the process of impact-creation, the study focused on

households survey, village profiles and village organization survey through case study. A

total of 2125 households including 1375 RDP member households and 750 control

households were selected for the household survey. Profiles of 225 villages including 150

RDP villages, and case study of 15 village organizations were also prepared. The analysis



was made based on the two-round survey data of the selected households. By and large, the

study is descriptive in nature. The determinants of consumption expenditure and

accumulation of wealth were identified through regression analysis. The methodology

was a combination of econometric and case approaches.

Despite being a descriptive one, the study provides some meaningful findings. Older

members of RDP are better off than the younger members and non-participating control

group. They are economically better off. The study found that the four-year or more old

member households had asset value of more than 112 per cent, average weekly

expenditures of more than 26 per cent and per capita weekly expenditure of 15 per cent

higher than those of younger member households of less than one year. In order to measure

the impact of RDP credit and ‘contextual’ variables on ‘wealth’ and ‘consumption

expenditure’, the authors used OLS. Education was found to have a significant impact

on wealth accumulation. RDP credit had relatively weaker impact although the coefficient

was significant and positive. RDP loan also had positive impact on consumption

expenditures. A higher dependency ratio reduced the level of consumption. Given the

nature of variables included in the regression equation, it is highly probable that there were

problems of multicollinearity and endogeneity. The consistent finding was the fact that

RDP credit had larger impact on female-headed households compared with the male-

headed households. Local conditions and initial wealth or endowment do matter in

improvement in economic well-being. However, like other studies, the issue of fungibility

was not resolved. It was reported in the study that nearly half of the households

(46 per cent for male and 41 per cent for female) had loans from informal sources. The

average amount of indebtedness of the informal borrowers was around Tk. 3500. It was

around Taka 1400 for all the sample households. Through case studies, the study showed

that women are better off. They are more empowered than before. But such empowerment

increases with duration of membership with BRAC and size of RDP loan.

Although the findings are nothing unexpected, the study could not tackle the problem of

fungibility. Application of econometric technique was quite limited. As such, the findings

from the descriptive analysis often remain econometrically untested. Thus, the conclu-

sions may not be robust. However, the study provides a more comprehensive under-

standing of the process and the nature of impact of RDP inputs and other contextual

variables influencing the desirable outcomes.

BRAC did a second impact study in 1998. In addition to the outcome parameters

considered in the first impact study in 1996, the second impact study focused on poverty

reduction and its correlates, and women’s empowerment in particular. Total number of

selected households was 1700, of which 1250 were the BRAC households.

The findings were no different from the first impact study. RDP credit does have positive

impact on non-land assets (380 per cent higher), networth (50 per cent higher), savings

(100 per cent higher). Because of the BRAC NFPE programme, the programme has

positive impact on children’s schooling. The derived benefits are more pronounced for

the older members of BRAC. The study raised the question of sustainability of impact

based on the finding that ‘members with 84þ months of membership length owned less

assets than 48–84 months group’.

The critical findings emerged from the panel data analysis (Mallik, 1998) are: (i) an

increase in about 8 percentage point in self-employment; (ii) an increase by over 7

percentage point in training and loan; and (iii) percentage of BRAC members borrowing

from informal sources declined significantly; an increase in current value of total asset by

over 26 per cent.



Halder (1998) did an analysis of poverty reduction and women empowerment in the

second impact study. No measure of poverty reduction was made using the panel data. She

provided an analysis of poverty reduction through comparing indices among participating

households classified by length of participation, and also with control group. She used two

indices—poverty-gap and FGT1—in estimating incidence of poverty. She estimated that

incidence of poverty was 32 per cent higher for the control households. Halder, using the

poverty-gap and FGT indices, showed that there is an inverse relationship between length

of membership and intensity of poverty. Intensity of poverty is lower for the older

members. Poverty-gap was estimated at 11.0 per cent for the households with membership

of more than 4 years as against 15.3 per cent for the younger members with less than one

year of duration. Similarly, she estimated, based on the poverty gap index, that poverty gap

for the BRAC members was 13 per cent as against 19 per cent for comparison households.

This means that intensity of poverty is six per cent lower for the BRAC members. She

found an inverse relationship between RDP credit and incidence of poverty. Such a result

is quite expected.

Farashuddin and others assessed the impact of RDP credit on women’s empowerment.

She considered three pathways to empowerment. They are material, perceptional, and

relational or power pathways. Around 45 per cent of the female members were involved in

income generating activities, an increase of about 17-percentage point from the pre-

membership period. Although not overwhelming, an increasing number of female

members do have control over their own savings and do participate in the decision

making process. Their dependency, as reported in the study, has declined over time, and

they are more respected than before.

Although the findings demonstrate positive impact of RDP credit and other inputs at the

household and individual levels, the study is more descriptive in nature. In only very

selective cases like determining wealth and consumption expenditures, the authors applied

regression technique. Endogeneity was controlled for. Moreover, the second impact study

could also not address the issue of fungibility. It would have provided excellent evidence

on sustainability of RDP impact had the authors compared the changes in the impact

outcomes on the households studied under both the first and second impact study.

The PKSF Study (Zohir et al., 2001): A More Disaggregated Analysis for

Better Understanding

Zohir and his colleagues at BIDS conducted a PKSF sponsored study on ‘Monitoring and

Evaluation of Microfinance Institutions’ in 1998–2000. As a part of the study, the research

team examined the impact of micro-credit programme of the Partner Organizations2 at the

household, institution and individual levels. The study was conducted over 2903 sample

rural households in 91 villages spread over 23 thanas in 13 regions. A three-round survey

was conducted to capture for seasonality and time-bound effect. It is perhaps the first study

in Bangladesh that conducted a three-round survey in during the period 1998–2000. As

such, this study provides information on impacts based on both cross-sectional and

dynamic analyses.

1The Foster–Green–Thombecke (FGT) index of poverty.2MFIs that have borrowed under a defined framework from PKSF are termed as partner organizations.



The basic objectives were to assess impact of micro-credit on economic well-being,

social outcomes, poverty reduction, and women’s empowerment. The study provides an

analysis of the micro-credit impact by disaggregating target households by regular

participation, complete dropout, recent dropout, new participants and non-participants.

Consequently, intra-target group dynamics in relation to length of membership and impact

outcomes, and impact outcome through comparative analysis of treatment and control

groups are derived. In addition, the study provides a clear and systematic assessment of the

impact ofcrediton poverty reduction. Suchanalyses werepossible because of three-yeardata.

The research team adopted both descriptive and econometric analyses for evaluating

the impact of micro credit on desirable outcomes. Regression technique was used in

possible cases to identify the determinants of outcomes. The descriptive analysis, because

of disaggregation of target households by nature and length of participation, provides a

deeper understanding of the extent of impact on desirable outcomes.

Impact of micro-credit on economic well-being showed that the percentage of regular

participants in farm activities has declined during the period 1997–2000. This has been

because of increase in self-employment. More than three-fourths of the participants were

engaged in self-employment. Consequently, crops as a source of income, as expected,

have declined (Zohir, 2001).

With respect to social outcomes, Mahmud showed that in relation to control or other

participants, regular participants incurred more household expenditures. Their children

have higher access to education. Simen Mahmud provides an analysis of the impact of

credit on women empowerment, as defined by mobility, contraceptive use, household

income control, expenditure decision and self-perception. She showed that mobility of the

female regular participants has increased. The percentage of contraceptive use was

estimated at 75 per cent for the regular participants as compared to 68 per cent for the

non-participants. She showed that the role of female in crop-production related expendi-

tures has increased, reducing gender inequality in production decisions. Finally there has

been an increase in the status of female regular participants in the family, relations with

spouse, and self-esteem in relation to occasional participants.

Sen as a member of the research team provided an excellent analysis of the relationship

between micro-credit and poverty reduction. He used three poverty indices—head count,

poverty gap and FGT. Using the time series data for the period 1997–2000, he showed that

there has been a positive change in poverty reduction. Extent of poverty reduction was

more pronounced for the regular participants than the occasional and non-participants.

Based on head-count, poverty declined by 12.4 per cent, and 13.6 per cent based on

poverty gap for this group. In contrast, poverty reduction was 6.9 per cent based on head-

count and 10.7 per cent based on poverty gap for the non-participants. This means that

micro-credit contributed to a net increase in poverty reduction by 5.5 per cent based on

head-counts (difference between head-count ratios of regular and non-participants) and

about 3 per cent based on poverty gap (difference between poverty gap of regular

participants and non-participants) in two years. Such reduction is quite significant

considering the fact that there was a large-scale devastating flood in 1998–99, whose

costs fell principally on poor households. The regular participants in microfinance

programmes possess higher ability to cope with adverse impact of natural calamity.

Sen, however, showed that impact of small microfinance programmes on poverty

reduction was more pronounced than that of leading microfinance institutions like

PROSHIKA, ASA and Grameen Bank. This is probably because of more focused and

well-monitored microfinance programme in small areas of operation.



Although the PKSF study provides an in-depth analysis of the impact of microfinance

programmes on desirable outcomes, the study has some weaknesses. First, it fails to tackle

the issue of fungibility. Second, it did not control for the government development

interventions and formal credit market in impact analysis. The study could have been more

useful had the descriptive analyses been supplemented by sound econometric analysis.

USE OF DIVERSE METHODOLOGIES: COMMON FINDINGS BUT THECRITICAL ISSUE STILL UNRESOLVED

The major studies that I have reviewed used different methodologies with varied features.

The findings are broadly common even when studied with different methodology. Quasi-

experimental design was adopted in each of the studies reviewed. But in most of the cases,

no comparative analysis of the control and treatment groups was provided.

The World Bank study (Khandker, 1998) has tackled the issues of endogeneity and

selection bias soundly through using rigorous econometric techniques. Fixed effect

methods were used to determine impact outcomes. This makes the estimates unbiased

and efficient. Findings are robust. But the issue of fungibility remained a problem in the

study. The methodology used by Pitt and Khandker is somewhat complex, and not easily

perceived (Rahman, 2001).

The Peru study (Dunn and Arbuckle, 2000) used a different methodology—the House-

hold Economic Portfolio framework for analysis of the impact. Econometric application

was not extensive. As the study was based on panel data, the authors used paired-difference

tests and analysis of covariance. But the framework provides an interesting approach to

tackle the issues of fungibility and selection bias. Moreover, the use of panel data, as argued

by the authors, resolved the issue of selection bias and fungibility.

The quasi-experimental design, as argued by Rahman (1998), could be less effective in

the absence of finding out non-programme villages because of depth of microfinance

programmes in Bangladesh. The situation was partly experienced by Zohir (2001) and

Husain (1998). Both of them used disaggregated target participants by length of member-

ship as proxy for non-participant control group. Zohir used participants with less than one

year of membership as proxy for non-participant group because the members belonging to

this group did not get any micro credit. Such disaggregation tackles the concern as

expressed by Rahman, and at the same time makes it possible to measure impact of

different loan size. This is one contribution in the area of empirical methodology that

Zohir (2001) and Husain (1998) have made.

The study of BRAC–RBP is quite extensive but lacks rigour, as it is basically descriptive

in nature. Occasionally the analysis was supplemented by case studies and econometric

estimates of parameters. Because of the case analysis, a greater understanding of the

impact and the process through which RDP impacts desirable outcomes is available.

Multiple regression technique was used in a limited way only to find out the determinants

of assets accumulation and consumption expenditures, but did not control for endogeneity.

As such, econometric estimates of the parameters are probably not robust.

Since BRAC conducted two major impact studies in the 90s, the authors of the second

impact study could have extensively analysed the effect of RDP credit at the household

and individual levels using panel data. Panel data was not fully utilized. However, both the

impact studies of BRAC provided a comprehensive set of information on the nature and

process of impact of RDP credit and other inputs on poverty reduction. The findings could



be made more credible with more use of econometric techniques. Case studies offer

insight into the process of impact.

Finally the PKSF study contained both descriptive and econometric analyses. The

strength of the study is its disaggregated analysis, and showed that effective inferences on

impact outcomes could be made even without a well-defined and sound non-participation

control group. Participating poor households were classified into regular participation,

complete dropout, recent dropout, occasional participation, new members and non-

participating control households. Such disaggregation enabled the authors to provide

deeper analysis of the nature and the process of impact of micro credit at the household

and individual levels. By and large, a multiple regression technique was used for

parameter estimates. As the study was conducted over a three-year period, the authors

in most cases used panel data for analysis.

How different are the results? The results are basically similar. Micro-credit does matter

in poverty reduction. The extent of poverty reduction because of micro credit has been

estimated to be around 5 per cent for the participating households. This is more or less

consistent in all the three major studies conducted in Bangladesh. Micro-credit does have a

positive impact on income, consumption expenditures, self-employment, female labour,

and asset accumulation as evident from the studies conducted in Bangladesh. The impact

was more pronounced for the female borrowers.

The findings of micro-credit impact in Peru are mixed. Micro-credit made an impact on

enterprise profit, and increase in income and more diversification of income at the

household level. But no impact at the household level was found on household assets

and children’s education. These results are different from Bangladesh. This has been

basically due to the economic recession that Peru experienced in 1997–98. Micro-credit

borrowers could sustain more than the non-participating households. That means, extreme

externalities and/or natural calamities may outweigh the extent of positive impact of micro

credit at the household level. When it does, it also affects the process of empowerment of

women.

In the Peru study, by and large, there was no positive impact of micro credit at the

individual level. But in the Bangladesh studies, there are evidences of positive impact of

credit at the individual level. Credit has empowered rural women, increased mobility and

provided decision-making authority in material well-being, contraceptive use, and

increased self-esteem. These findings are common in Bangladesh (for example,

Farashuddin et al., 1998; Hashemi et al., 1996; Pitt et al., 2003).

Although the findings that emerged from the review of major studies are more or less

similar, the validity of the impact remains a question since neither of the studies could

tackle the issue of fungibility, and separate out the effects of informal, formal and micro-

credit at the household level. This is particularly an issue in impact studies conducted in

Bangladesh when more than one-third of the micro-credit borrowers borrow from informal

market, and about one-sixth borrow from the formal credit market (Khandker, 1998a;

Zohir et al., 2001; Halder, 1998; Khalily et al., 2000; Khalily, 1995). None of the three

major studies conducted in Bangladesh could address the issue of access of poor

households to multiple sources of credit in assessing impact of micro credit at the

household level. As a result, the findings of the studies may always be questionable.

For example, all the three major studies reported that micro credit did have impact on

consumption expenditures, but it is not clear whether it was due to borrowing from

informal sources or formal sources or from increase in income due to micro-credit

intervention.



The issue of fungibility is more important than the issues of selection bias and

endogeneity in accurate assessment of impact of microfinance. The issue of selection

bias is resolved with the use of panel data. Even in the cross-sectional studies, it can as

well be efficiently resolved with appropriate identification of the household and individual

characteristics in the econometric models. The issue of endogeneity, as long as it is

recognized, is tackled through application of appropriate econometric techniques.

Although difficult, fungibility is not intractable. It ought to be handled in impact studies.

Disaggregated analysis by access to different sources of credit like households with micro-

credit only, households with micro-credit and formal bank credit only, households with

micro-credit and informal credit only and households with access to all sources of credit

may enable to derive implication of microfinance quite clearly. Both descriptive and case

studies as well as econometric approaches can be applied in such a situation. Similarly, as

used by Khandker and Faruquee, 2001, considering credit as endogenous, predicted value

of credit along with instrumental variables can be used in the function of welfare

outcomes. Finally, household economic portfolio approach may also be applied to control

for fungibility.

RURAL FINANCIAL MARKET AND INSTITUTIONAL EFFICIENCY:

MOSTLY FORGOTTEN PART IN IMPACT STUDIES

Amidst euphoria over positive impact of micro-credit on poverty reduction and improve-

ment in quality life of the poor households, the forgotten part has been development of

rural financial markets and institutional efficiency of microfinance institutions. Robinson

noted two approaches to microfinance—impact approach and financial system approach.

Impact approach deals with impact analysis on the demand side. The financial system

approach focuses on efficient allocation of resources, institutional development, cost-

effective operation, financial resource mobilization, and sustainability of microfinance

institutions within the legal framework.

The advocates of the ‘impact approach’ tend to argue that sustainability of MFIs will

undermine the poverty-focus. They probably fail to recognize the fact that provision of

microfinance for the poor households will discontinue when MFIs become non-sustainable

and/or when cheap funds will not be available. Sustainability perception makes MFIs cost-

effective and competitive, and is likely to ensure continuity in the provision for micro-

finance for the poor households. Ultimately, poor households will be the beneficiaries.

IMPACT OF MICROFINANCE ON INSTITUTIONAL SUSTAINABILITY

Sustainability is loosely defined as the ability of the MFIs to pay for cost out of its revenue

generated. This state is referred to as financial sustainability. Any MFI that generates

positive profit is financially sustainable. As most MFIs are heavily subsidized, financial

sustainability does not reflect real profit. As such, professionals tend to argue that

sustainability should account for opportunity cost of cheap funds. This is usually referred

to as economic sustainability.

High transaction cost of providing financial services at the doorsteps of borrowers and

limited size of operation (limited to number of clients) make the process of ensuring

sustainability difficult. But sustainability can be achieved through expansion of loan



volume, diversification of loan portfolios, increase in cost efficiency and loan productivity,

training of clients and employees, institutional development, and increase in lending

interest rate to cover transaction cost of optimum loan production.

There are only a few studies that have addressed institutional efficiency from the

perspective of rural financial market development in Bangladesh (for example, Khandker

et al., 1995; Khalily et al., 2000; Yaron, 1992; Schreiner, 2001). Khandker et al. (1995)

showed that although transaction cost of providing financial services is high because of

loan size, Grameen branches demonstrated increasing cost efficiency. Similar findings

were found for BRAC in Khandker and Khalily (1996). Khalily et al. showed higher

degree of cost efficiency for Grameen Bank and ASA in Bangladesh. Yaron (1992) noted

declining cost of loan production due to expansion in outreach and increase in loan size.

Consequently, Grameen Bank, ASA and BRAC are financially profitable. Schreiner found

Grameen Bank cost effective. Subsidy occupies a significant position in the analyses.

None of the leading MFIs (Grameen Bank, ASA and BRAC) is economically sustainable.

The process could perhaps be improved had there been lesser degree of dependency on

cheap funds and legal entity of the MFIs.

Impact of Cheap Fund on Operating Cost

Cheap funds do have adverse impact on the behaviour of MFIs as in formal financial

markets. Borrowers of micro-credit pay a higher interest rate. Therefore, they are not

subsidized. Actually institutions are subsidized. This subsidy influences behavior of top

management. It is well documented in the literature that cheap funds distort efficient

allocation of funding, increases default cost and operating costs and affect viability of

lenders (Adams et al., 1984; Von Pischke et al., 1983).

None of the MFIs has any ownership structure that will provide sufficient incentives for

the management or CEO. With the exception of Grameen Bank, no MFI is equity-based;

even in the Grameen Bank the management does not have any equity interest. In the

absence of ownership-based incentive structure, what is the utility function of the CEOs or

top executives? Such question is quite relevant from the perspective of making the MFIs

competitive and efficient.

It is well documented in the literature that top management will have expense

preference behavior in the non-equity-based organizations. This will be more relevant

when cheap funds dominate organizational finance. In a study, Khalily and Imam (2001)

showed that average salary per employee for the more subsidy-dependent MFIs is higher

than that of less-subsidy dependent MFIs. This has happened not because of more donor-

dependency but because of subsidized finance and non equity-based interest of the top

management. In the process, sustainability takes a long walk.

Impact of Microfinance on Rural Formal Financial Markets and Local Economy

No study has been conducted on impact of microfinance on rural formal financial market

development. As such, true impact of microfinance on growth and development of formal

financial markets as well as rural economy is unknown. There will be several plausible

impacts of microfinance on rural formal financial markets and local economy.

First, rural deposits with formal banks will increase directly because of increase in net

member-savings. In Bangladesh, rural formal deposits increased from Taka 46.2 billion in



1990–91 to Taka 173.8 billion in 2000–02 (Table 2), while net member-savings in 2000–

01 was Taka 24.2 billion. This is direct impact. Second, deposits wil probably increase

rural deposits mobilization because of income impact of micro-credit. A total of Taka 365

billion has been disbursed as micro credit in Bangladesh during the past decade. This is

likely to have impact on rural deposits mobilization in formal financial market. Third,

formal bank credit deepening is likely to increase, ceteris paribus. Credit deepening (rural

advances as percentage of rural deposits) decreased from from 1.06 in 1990–91 to 0.576 in

2000–01, although absolute amount of rural deposits and rural advances increased. That

means, a significant portion of rural deposits is being transferred to urban areas. As such,

expected rate of impact on rural economy will be lesser. Fourth, the provision for

microfinance and the production technology used by MFIs do have a positive impact on

the loan portfolio. Formal banks could not lend to assetless poor households because their

traditional collateral-based production technology was not appropriate. But the micro-

finance experience of MFIs is likely to introduce formal banks to new collateral-less

group-based production technology. This technology has enabled them to direct micro

loans to poor households. In 2000–01, formal banks disbursed a total of 42.2 billion

including Taka 6.9 billion for small and micro loans (Table 3).

These plausible impacts together would have impact on viability or sustainability of

formal rural bank branches as well as local economic development. These are wider

impacts. Real impact depends on direction of impact in each of the cases as mentioned

above. Johnson has argued for assessing wider impact of microfinance on financial

markets (1998) and has executed that approach in her article in this volume.

Efficient Use of Financial Resources: Social Cost–Benefit

of MicroFinance Programme

Microfinance is not the only intervention for poverty reduction. There are other interven-

tions. They are formal bank rural credit, food-for-works programmes, and vulnerable

Table 2. Distribution of rural bank branches and deposit mobilization

1990–91 2000–01

Total No. of Rural Bank Branches 3685 3693

Rural deposits (Billion Taka) 46.24 173.85

Rural Advances (Billion Taka) 49.26 100.29

Ratio of Advances-Deposits 1.065 0.576

Average rural deposits per branch (Taka Million) 12.44 47.24

Source: Bangladesh Bank and author’s own calculation.

Table 3. Rural credit in rural financial markets in Bangladesh (Taka in Billion)

Year Agricultural Small and Total Small and microcredit micro credit credit credit as % of Total

1998–99 32.45 7.52 39.97 18.81

1999–00 34.74 5.54 40.28 13.76

2000–01 36.30 6.70 43.00 15.58

Source: Bangladesh Bank and author’s own calculation.



group development. What programmes are more effective? This question has not been

addressed in most of the studies. Khandker (1998a) has systematically addressed the

question. He compared the costs–benefits of Grameen Bank and BRAC with that of other

interventions (BKB, RAKUB, Food-for-Works programmes). Social cost is the net

subsidy derived from cheap funds. Benefits were derived for BRAC and Grameen Bank

based on marginal returns to borrowing. Khandker calculated the marginal return based on

marginal return to consumption. He estimated, using two-stage least-squares regression,

marginal return to formal borrowing. For the food for-work programmes, cost of one ton of

grain was considered as cost while income transfer was considered as benefit. Social

costs–benefits of different interventions for poverty reduction are reported in Table 4.

Grameen Bank was the most cost-effective programme generating higher social benefit.

Two agricultural development banks (BKB and RAKUB) were the most costly pro-

gramme. The cost–benefit ratios for the banks were 4.88 and 3.26 respectively, as against

1.48 for Grameen Bank and 2.59 for BRAC. However, the least cost-effective was food-

for-works programme. Nevertheless, the programme cannot be considered, as argued by

the author, as the most effective anti-poverty programme as it does not reach all targeted

poor households and it does not create opportunities to poor households for self-employ-

ment. Thus, despite the fact that transaction cost of microfinance programme is very high,

the programme is most effective in terms of social benefits generated.

SUMMARYAND CONCLUSION

During the past decades, quite a large number of studies were conducted on the impact of

micro-credit at the household, individual and institutional levels. But most of the studies

were focused on inter-and intra-household impact. Impact assessment of credit is difficult

for several reasons: (i) selection bias; (ii) endogeneity; and (iii) fungibility of money.

Given these problems, an appropriate methodology is required to tackle these problems. In

the literature, three major approaches are found—econometric, descriptive and case

studies. Descriptive and case studies provide good understanding of the nature and process

of impact-creation of micro-credit. No major implications can be derived for any policy

implications, as these studies do not generate any sound estimate of the extent or degree of

impact-outcomes. In this context, econometric approach is superior. But not all the

econometric studies tackled all the three problems of impact assessment. Khandker used a

maximum likelihood method to jointly determine the demand for credit and impact

Table 4. Social cost–benefit of alternative interventions forpoverty reduction

Programme Cost–benefit ratio

Grameen Bank 1.48

BRAC 2.59

BKB 4.88

RAKUB 3.26

Vulnerable Group Development 1.54

Food-for-Work (Care) 2.62

Food-for-Work (World Food Programme) 1.71

Source: Khandker, 1998a.



outcomes of micro-credit in Bangladesh. The major limitation was the failure to tackle the

problem of fungibility of money. Dunn and Arbuckle (2001) used a household economic

portfolio framework to econometrically estimate impact-outcomes in Peru. The approach

tackles the problem of fungibility in a limited way.

The findings of the econometric, descriptive and case studies conducted in Bangladesh

on the impact assessment of micro-credit are quite consistent in terms of direction of

impact. The results of the descriptive and case studies are consistent when they are also

derived from the econometric studies. At the household level, positive impacts are found

on poverty reduction, income change, consumption expenditure, net worth, assets accu-

mulation, children’s schooling at the household level, and women’s empowerment at the

individual level. Around 5 per cent of the participating households rose annually above

poverty line. Women were more empowered than before because of their increasing

command over financial resources, participation in the investment, children’s education,

contraceptive use, increasing mobility and self-esteem. These results are consistently

found in all the studies.

The findings of the Peru study were not similar. Micro-credit, through increase in

enterprise profits, contributed to increase in income and income diversification and

consumption expenditures. Participating households could sustain themselves better in

severe economic recession than the non-participating households. At the individual level,

the findings were mixed. Females had control over financial decisions but did not achieve

self-esteem and respect from others. These results suggest increasing ability of the

participating households to cope with adverse economic situations, and perhaps the

nature, process and extent of impact-outcomes may vary because of socio-cultural factors.

Microfinance is not the only anti-poverty strategy. There are others like food-for-works

programmes and small loan programmes of formal banks. Which strategy should be

pursued for effective poverty reduction? This requires cost–benefit analysis of alternative

interventions. Descriptive and case studies fall short of addressing this question. Econo-

metric approach provides better result, as it requires econometric-estimates of marginal

and average return to borrowing. Khandker’s study is the only one that estimated the cost–

benefit ratio of alternative anti-poverty interventions. He showed that microfinance

programmes are more cost-effective in relation to social benefits than those of public-

sector agricultural development banks. Hence, micro finance programmes like Grameen

Bank and BRAC generate higher positive welfare gains.

There is no doubt that demand-side analysis of the impact assessment studies show

positive impact on poverty reduction and the household and individual level outcomes.

However, these findings have implication for continuity of the programmes. But long run

sustaining financing of poverty reduction programmes requires sustainability of the micro

finance institutions. This has been to a great extent forgotten in the impact studies. This

may be costly. MFIs are subsidized. Subsidy influences the behavior of lenders, but not of

the borrowers. Khalily and others showed that top management of more subsidized

institutions have higher expenditure preferences than the less subsidized institutions. Lack

of ownership contributes to this. As such, institutional sustainability is affected. Resources

are inefficiently allocated. More subsidized institutions are far short of sustainability,

aggravated by their high transaction costs of lending. However, empirical evidences

extensively support the notion that MFIs can, if properly managed, operate profitably and

efficiently.

Because of different methodologies used in different studies and different approach to

modeling, the parameter estimates are different. In all the major studies, the extent of



impact varies but the results are same in terms of direction of impact. What are the

implications of these findings? It adds to the knowledge that micro-credit positively

contributes to poverty reduction, and MFIs can operate profitably and with higher degree

of cost efficiency.

The users of impact findings are basically government, international agencies, profes-

sionals, donors, MFIs and regulators. Hulme has rightly argued that impact studies do

matter to the donors, not to the MFIs. However, government and international agencies

would be more interested for its policy decisions on the extent of poverty reduction and the

process through which microfinance contributes to such poverty reduction.

There may be several potential implications of the impact findings at the household and

individual levels for the government. First, microenterprises are the basic process through

which micro-credit contributes to household and individual level impacts. The nature of

enterprises invested in may have forward linkages with ample opportunities for employ-

ment creation. On the other hand, the nature of investment, for example trading, may not

have sustainable impact. As such, an analysis of the impact through microenterprise-

investment may have policy implications for promotion of desired type of microenter-

prises with potentials for growth. Second, since poverty reduction is the end-outcome of

microfinance programme, government and international agencies would be interested in

the estimates of the extent of poverty reduction due to microfinance. This will enable the

government to expand necessary complementary support policies (like socio-economic

infrastructures) to ameliorate returns to micro-credit investment. Third, the MFIs, because

of their effective network and the approach, have proved effective in enhancing the level of

women’s empowerment and children’s education in rural areas. Hence, the government

may take lessons from such experiences and strengthen its social institutions for higher

level of utility of the government programmes for women empowerment and expansion of

education-facilities for the rural poor. In addition, it may strengthen the efforts of MFIs in

improving level of women’s empowerment and child education.

In recent years, impact studies on the demand side have used panel data. This resolves

the issue of selection bias and makes the life of researchers simple. But the fungibility

issue really puts the impact findings on the line. Validity of the quantification of impacts is

not free from any question. Which methodology is appropriate and how different are the

results? This can be done only through applying different approaches on the same data set.

Impact studies on the demand side are costly. As such, policymakers and professionals

would expect the impact assessment to be accurate for any policy decisions. Impact

assessments on the demand side have two major possible implications—knowledge

creation, and cost–benefit analysis of microfinance as an anti-poverty strategy. Money

has changed the lives of poor households and hard-working poor women. Not all

dimensions influenced by money or micro-credit are quantifiable. As such, quantitative

approaches do not provide complete assessment of impact-outcomes. The knowledge-

creation impact studies should adopt both quantitative and case study approaches for

meaningful insights. Mosley (1997) has rightly argued for intensive case study for better

understanding of the nature of impact and of the causal process through which micro-

credit influences outcomes.

Microfinance experiences on the supply side have generated several important

findings—collateral-less group-based production technology minimizes default cost and

institutions are able to operate profitably with higher degree of member savings

mobilization. These findings do have implications for the development of rural financial

markets. First, formal banks may adopt microfinance production technology to improve its



efficiency and performance. Formal lenders in a limited way have taken a lesson from

MFIs regarding production technology. Now formal banks produce collateral-free small

and micro loans to the poor households and small farmers in Bangladesh. Second, formal

banks may also introduce innovative savings schemes to mobilize savings from the poor

households. Third, in the absence of efficient formal financial markets, the government of

Bangladesh within some regulatory framework can allow the MFIs to emerge as formal

institutions to operate in rural financial markets. This will enable the rural households to

have access to a wide set of financial services. Fourth, a formal process of inter-linkage

between MFIs and formal banks should be introduced to offer financial services to the

rural households at least cost.

Quite a large number of impact studies have been conducted in Bangladesh. We have

more knowledge about intra- and inter-household level impact of micro-credit. But

knowledge is more or less absent on the knowledge-creation of impact studies on the

supply side. Impact should be viewed in a broader context. Macro economy and financial

market developments should be at the forefront of the future impact research. While

micro-credit positively impacts household well-being, there should not be any distortion

on the supply side. Otherwise, history will repeat. Cheap funds will destroy financial

markets and institutions as they have in the case of public sector banks in Bangladesh. This

should be the lesson for future rural financial market development and sustainable

institutional development for continuity in the provision for financial services for the

‘hard-working’ poor households.

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