Economic and Political Weekly March 9, 2002 955

If we can come up with a system whichallows everybody access to credit whileensuring excellent repayment – I can giveyou a guarantee that poverty will not lastlong.

Muhammad Yunus (1994)

This summit is to celebrate the success ofmillions of determined women who havetransformed their lives from extreme pov-erty to dignified self-sufficiency throughmicro-credit programmes… This summitis about creating a process that will sendpoverty to the museum... We will createa poverty-free world.

Muhammad Yunus, speaking at theMicro-credit Summit, Washington,

February 1997; reproduced in Yunus(1999: 245-46)

This paper is an enquiry into theclaim that NGO-led micro-credit isan effective and financially viable

alternative to the existing methods of ad-dressing rural poverty through the provi-sion of credit. The emergence of micro-credit as an alternative in recent years hasquestioned the fundamentals of the ruralcredit system in developing countries forchannelling credit to the poor. Followingthis, transformation – even substitution –of the existing rural credit system with amicro-credit-based system is being recom-mended and followed. In this paper, wereview the performance of the NGO-ledmicro-credit system on the basis of a setof selected indicators. These indicatorsare: targeting the poor, increase in earningsand asset holding of the poor, employment

generation and skill improvement, andfinancial viability.

We are aware that given the multi-dimensional nature of poverty, an attemptto understand the impact of any programmeor institution on poverty would require astudy of a number of indicators. However,in the literature on micro-credit, povertymainly refers to income poverty. We havefollowed the same connotation in this paperand have chosen the performance indica-tors accordingly. We have also incorpo-rated the indicator of financial viability.The issue of financial viability has beena matter of wide criticism in recent yearsin the context of state-led credit institutions.Hence we feel that it is important to analyseit in the case of NGO-led micro-creditinstitutions, which are being recommendedas the alternative to state-led institutionsin several developing countries.

For analysing these indicators, we usethe available empirical evidence on a setof selected NGO-led micro-credit-basedprogrammes and institutions being imple-mented across several developing coun-tries. We place this evidence in a compara-tive perspective with the available evi-dence on some of the existing state-ledand credit-based poverty alleviationprogrammes and institutions in India. Weare aware that state-led institutions aimedat channelling credit to the poor do notfunction on the same lines as the micro-credit institutions. However, there aresimilarities in their objectives and certainoperational features, such as the nature ofactivities supported and size of loansprovided, for undertaking a meaningfulcomparison.

The paper is divided into four sections.In Section I, we bring out the context inwhich the NGO-led micro-credit alternativehas emerged in the literature and in policymaking. In Section II, we discuss theconcept and features of micro-credit insti-tutions, beginning with Grameen Bank. InSection III, we review the available em-pirical evidence on micro-creditprogrammes and institutions in compari-son with state-led credit-based povertyalleviation programmes and institutions inIndia based on the selected indicators. Wealso discuss the issues involved in theexpansion and replication of Grameen-type programmes and institutions acrossvarious countries. Finally, in Section IV,we provide a summary of the findings fromthe review.

IIIIIIntroductionIntroductionIntroductionIntroductionIntroduction

Credit is important in the lives of therural poor in a developing economy. Asthe distribution of land in the countrysideremains skewed, the majority of the ruralpopulation is left with an inadequate re-source base for production. Faced with aweak social security system to fall backupon, this section of landless or near-land-less rural population is forced to dependupon credit for its livelihood. It was thisunderstanding that led various developingcountries to make credit an integral partof their poverty alleviation programmes.The conception and implementation of suchprogrammes were often based on the broadprinciples of social banking in severaldeveloping countries including India.

Micro-Credit and Rural PovertyAn Analysis of Empirical Evidence

This paper reviews empirical evidence on NGO-led micro-credit programmes in severaldeveloping countries, and compares them with state-led poverty alleviation schemes in India.

The study shows that micro-credit programmes have been able to bring about a marginalimprovement in the beneficiaries’ income. However, the beneficiaries have not gained much

by way of technological improvements, given the emphasis on ‘survival skill’. Also, inBangladesh the practice of repayment of Grameen Bank loans by making fresh loans from

moneylenders has resulted in the creation of ‘debt cycles’.

PALLAVI CHAVAN, R RAMAKUMAR

Economic and Political Weekly March 9, 2002956

Social banking can be described as “theelevation of the entitlements of previ-ously disadvantaged groups to formalcredit even if this may entail a weakeningof the conventional banking practices”[Copestake et al 1984].1 Under this policy,the initiative and direct involvement ofthe state was central to the developmentof the banking system. In India, this policyled to nationalisation of major commercialbanks in 1969, adoption of the directedlending programme, development of creditinstitutions such as Regional Rural Banks(RRBs), and implementation of the Inte-grated Rural Development Programme(IRDP), a credit-based poverty alleviationprogramme implemented through com-mercial banks. These policy measuresresulted in widening the “geographicalspread and functional reach” of commer-cial banks in rural areas in the period thatfollowed the nationalisation of banks[Shetty 1997: 253]. Further, there was alsosome improvement in the access of ruralpoor – consisting largely of marginal andsmall peasants and the landless rural labourforce – to bank credit at concessional rates[Chavan 2001].

In the process of pursuing the broaderobjectives of social banking, however,certain weaknesses crept into the systemof banking in general and rural bankingin particular. First, it was argued that thoughthe efforts were aimed at improving thedistribution of formal credit among thelandless and near-landless rural popula-tion through schemes such as IRDP, bankcredit largely remained concentrated in thehands of the landed population [Nagaraj1981]. Secondly, it was argued that thebanking system could not fully adapt tothe task of poverty alleviation on accountof the lack of provision of consumptioncredit.2 Finally, the system of directedlending was criticised as it resulted in thecreation of non-profit making assets onaccount of poor repayment of loans [RBI1991].

This is not the place to probe into thereasons behind these weaknesses. How-ever, they had a certain bearing on the factthat development of the banking systemremained isolated and was not made partof a broader socio-economic transforma-tion in the countryside. Land reform, forexample, was the most important stepneeded for such a transformation. Landremained inequitably distributed, and in-equities in the access to credit followedthe inequities in land distribution. Thiswas because borrowers needed land as

collateral in order to secure access to credit[Swami 1979]. Further, in the absence ofdecentralised planning and administrationof poverty alleviation programmes throughinstitutions such as the panchayats, therewere problems in targeting the poor ben-eficiaries [RBI 1990, Osmani 1989,Swaminathan 1990].3

With increasing criticism of the state-ledformal credit system and its utilisation forpoverty alleviation, in recent years coun-tries have moved towards new mecha-nisms of lending such as micro-credit.Micro-credit has been claimed to be asolution to most of the problems thatoriginated out of the state’s efforts toalleviate poverty using the instrument ofcredit [Yunus 1999].

IIIIIIIIIIMicro-Credit: ConceptMicro-Credit: ConceptMicro-Credit: ConceptMicro-Credit: ConceptMicro-Credit: Concept

and Featuresand Featuresand Featuresand Featuresand Features

The implementation of any formal lend-ing programme directed towards the pooris often beset by three importantdifficulties.4 The first is the problem ofexact targeting, which would ensure thatthere are no type I or type II errors5 [Corniaand Stewart 1991]. Secondly, it faces thescreening problem of distinguishing thegood (creditworthy) from the bad (not-so-creditworthy) borrowers. This is be-cause the poor borrowers do not generallymaintain any accounts of their past busi-ness activity or furnish any documentedbusiness plan for which they are seekingloan. Thirdly, these agencies may not beable to monitor and ensure productiveusage of the loans. Further, if the loanrepayment runs into a problem, theymay not be able to take legal actionagainst the borrowers, often on accountof the absence of any collateral. Here, theproblem is of enforcing the repayment ofloans. Costs incurred to take care of thelast two problems mainly comprise the‘transactions costs’ of lending. On accountof a high level of transactions costs in-curred in lending to the poor, formallending agencies often leave the poorunbanked [Yunus 1999]. The scheme ofmicro-credit that has emerged with theestablishment of Grameen Bank has aimedat addressing these problems in certaininnovative ways.6

Micro-credit, as defined by GrameenBank, symbolises small loans extended tothe poor for undertaking self-employmentprojects that would generate income andenable them to provide for themselves and

their families.7 The defining criteria usedare thus the size of loans8 and the targetedpopulation comprising micro-entrepre-neurs, particularly women micro-entrepre-neurs, from low-income households. Theseloans are generally offered without anycollateral.

The scheme of micro-credit as conceivedby Grameen Bank has been based oninnovative financial practices. It attemptsto resolve the problem of targeting men-tioned earlier either directly by specifyingthe member’s eligibility requirement onthe basis of asset ownership or indirectlyby making the loan amount small andlaying down other conditions, such asattendance at the weekly member meet-ings, so that the non-poor are discouragedfrom borrowing [Hulme and Mosley1996a].9

It attempts to overcome the screeningproblem through group formation.10 Theconcept of group borrowing is driven bythe idea that solidarity among like-mindedpeople living in similar social and eco-nomic conditions is crucial to the successof this programme. This group can be usedto understand the character and proposedloan use of each of the members. More-over, the loans are given only for activitiesthat cannot go wrong in terms of repay-ment of the loan or it turning into a badinvestment [Hulme and Mosley 1996a].These are activities such as poultry raising,paddy husking, cattle fattening, rice andother seasonal crop trading, handloomweaving and grocery shop keeping.

Finally, the problem of monitoring theloan usage and enforcement is taken careof individually as well as through thegroup.11 The bank insists on putting theloan to the use specified by the borrowerstrictly within a period of seven days.Further, it follows a system of weeklyrepayment of small amounts. This is doneas “parting with large amount of cash atthe end of a loan period is often psycho-logically trying for the borrowers” [Yunus1999: 61].

With such innovative practices,Grameen Bank has risen to fame for itsperformance in targeting and repaymentrates. Following its example, several otherinstitutions have been set up for provi-ding micro-credit in Bangladesh and inmany developing countries. Apart fromthe state-controlled Bank Rakyat Indo-nesia and Badan Kredit Kecamatan inIndonesia, all such institutions, such asBRAC (Bangladesh), Banco Sol (Bolivia),SANASA (Sri Lanka) and Muzdi Fund

Economic and Political Weekly March 9, 2002 957

(Malawi), are non-governmental in nature(NGOs) and depend for funding on inter-national donors such as IFAD, SIDA,OECF, OXFAM and CARE.

IIIIIIIIIIIIIIIEvaluationEvaluationEvaluationEvaluationEvaluation

In this section, we attempt to review theperformance of a selected set of NGO-ledmicro-credit programmes and institutionsthat provide credit for poverty alleviationin developing countries. As mentionedearlier, we adopt a comparative approachfor analysing the performance of thesemicro-credit programmes and institutionsvis-à-vis the state-led programmes andinstitutions in India.

For this analysis, we have selectedGrameen Bank, BRAC, and TRDEP ofBangladesh, BancoSol of Bolivia, PTCCSof Sri Lanka, the Muzdi Fund and SACAof Malawi and the KREP Juhudi Schemeand KIE-ISP of Kenya. The state-ledpoverty alleviation programmes and insti-tutions chosen for comparison from Indiaare the Integrated Rural DevelopmentProgramme (IRDP)12 and regional ruralbanks (RRBs)13 .

An important constraint in such ananalysis has been the limited number ofstudies that evaluate the actual impact ofthe NGO-led micro-credit programmes onthe earnings and employment of the ben-eficiaries. Most of the available studiesnarrowly focus on their “programmaticsuccess” [Rahman 1999: 67], where theprincipal variables studied are the numberof beneficiaries, amount of credit disbursed,recovery rate, and profit flows amongothers.

The performance indicators used in thisreview are discussed below.Targeting the poor: As we shall show inthis section, micro-credit programmes andinstitutions have generally performed betterthan the state-led institutions for creditprovision in reaching the targeted poorpopulation.

The performance of IRDP in targetinghas been found to be strikingly poor [Dreze1990, Swaminathan 1990, Kurian 1987,Nabard 1984 and GoI 1985, cited in Guhan1986]. An expert committee of the Re-serve Bank of India (RBI) on IRDP foundthat, in many states, even the necessarypreliminary surveys of the families belowthe poverty line had not been conducted[RBI 1993]. It also found that the atten-dance at village assemblies, where the

beneficiaries were selected, was extremelypoor. Independent evaluations by Nabardand the Planning Commission estimatedthat on an average, the percentage ofineligible beneficiaries in IRDP were about15-26 per cent; in some places it was evenestimated to be between 40 per cent and50 per cent [Nabard 1984, GoI 1985, citedin Guhan 1986]. Dreze (1990) argued thatonly one among the eight households inthe poorest decile (the ‘unambiguouslypoor’ population) received any benefit fromIRDP. The average beneficiary income inhis study village was twice as high as thecut-off income specified under theprogramme. He also found that none of thelandless households in the village receivedany benefit through IRDP.

Swaminathan’s (1990) study villageswere in two states, West Bengal and TamilNadu. She found significant differences inthe targeting efficiency of IRDP in thesestates. In West Bengal, only 7.5 per centof the sampled beneficiaries were noteligible for assistance. By contrast, in TamilNadu, 24-27 per cent of the beneficiarieswere not eligible for assistance. Undersome specific categories, this leakageextended even up to 50 per cent in TamilNadu.

By absolute contrast, Grameen Bank hasreported high success in reaching its tar-geted population. According to Hossain(1988), only 4.2 per cent of borrowers inthe Grameen Bank were outside the targetgroup (those with less than 0.5 acres ofland). Osmani (1991), after a review ofstudies, pointed out that most of the ben-eficiaries belonged to the bottom 40 percent of the income scale. About 95 per centof the loans from Grameen Bank reachedthe target group and only 5 per cent wentto non-target groups. Another importantachievement in targeting for Grameen Bankwas the high percentage of women amongthe borrowers. In 1998, women consti-

tuted 94 per cent of the bank’s borrowers[Yunus 1999].

Mosley and Hulme (1998), in their cross-country analysis, found that success intargeting varied significantly betweendifferent programmes (Table 1). Theyexamined the impact on poverty of 13major credit provision programmes andinstitutions across seven countries, includ-ing RRBs from India. Among thoseprogrammes that had a declared policy oftargeting, all had achieved a poor to non-poor ratio of over 90 per cent, except RRBsin India, which had a ratio of only 38 percent.14

Notwithstanding its success in targeting,an ‘exclusion problem’ has been reportedeven in the case of Grameen Bank [Osmani1989]. As per the findings of the Bangla-desh Agricultural Survey, in 1983-84 about66 per cent of households with less than0.5 acres of land (the declared target groupfor Grameen Bank) in Bangladesh wereprimarily agricultural labour households(ibid.). This proportion should have re-flected in their share among the beneficia-ries of Grameen Bank. However, Hossain(1988) found that only 20 per cent ofbeneficiaries had agricultural labour astheir principal/secondary occupation be-fore they joined the bank. Among these,only 8.4 per cent had agricultural labouras their principal occupation.Increase in earnings and asset holdingsof the poor: There are several method-ological problems in handling the issue ofearnings. Any study about earnings andassets is beset with several difficulties,such as under-reporting, recall bias inrecording incomes from previous yearsand inaccurate evaluation of earnings inkind. In the absence of properly main-tained accounts in the case of small house-hold enterprises, commonly observed inrural areas, the problem of income mea-surement is likely to be more acute.

Table 1: Proportion of Poor among Beneficiaries, Selected Credit ProgrammesTable 1: Proportion of Poor among Beneficiaries, Selected Credit ProgrammesTable 1: Proportion of Poor among Beneficiaries, Selected Credit ProgrammesTable 1: Proportion of Poor among Beneficiaries, Selected Credit ProgrammesTable 1: Proportion of Poor among Beneficiaries, Selected Credit Programmes and Institutions, 1992 and Institutions, 1992 and Institutions, 1992 and Institutions, 1992 and Institutions, 1992

Agency Number of Percentage of BorrowersBorrowers below Poverty Line

Bolivia: BancoSol 51,000 29Bangladesh: Grameen Bank 1,050,000 95+Bangladesh: BRAC 598,000 95+Bangladesh: TRDEP 25,000 90+Sri Lanka: PTCCS 702,000 52India: RRBs 12,000,000 44Kenya: KREP Juhudi 2,400 -Kenya: KIE-ISP 1,700 0Malawi: SACA 400,062 7Malawi: Mudzi Fund 223 -

Source: Compiled from Mosley and Hulme (1998), Table 1.

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It has been pointed out by Swaminathan(1990) that the methodology of calculatingincome changes requires accurate estimatesof base year as well as final year incomes.A reliable method can be to calculateincome mobility of households given thatone has income data collected during thetwo corresponding years. We found thatonly Swaminathan’s study adopted sucha methodology. Using panel data set fora village in Tamil Nadu between 1977(before IRDP) and 1985 (after IRDP), shefound that the overall share of productiveassets in total wealth remained unchangedover the period. There was no differencein the patterns of income mobility betweenbeneficiaries and non-beneficiaries be-tween 1977 and 1985. She concluded thatthe income impact of IRDP loans on thebeneficiaries was only marginally posi-tive.15

Other studies, following mostly the recallmethods for past-income calculations, havefound that there was only a marginal risein income for IRDP beneficiaries. Kurian(1987), reporting results from a country-wide survey of IRDP beneficiaries, foundthat about 84 per cent of the householdsenjoyed a positive increment in incomeafter a period of two years. Within these,about 38 per cent of the households en-joyed an increase in income of about 50per cent.16 In another review of IRDP,Guhan (1986: 32) reached the conclusionthat IRDP “channelled funds on a hithertounprecedented scale for creating supple-mentary incomes amongst the relativelypoor in rural areas all over India”. How-ever, he pointed out that it “failed togenerate incomes to the expected levels”(ibid p 31).

Studies on Grameen Bank have, ingeneral, shown a positive change in theincome of the beneficiaries [Hossain 1988,Hulme and Mosley 1996a, Todd 1996,Khandkar and Chowdhary 1996]. How-ever, all these studies use the recall methodand therefore, their results are likely tosuffer from memory bias. Further, unlikestudies on IRDP, studies on Grameen Bankhave not attempted to isolate the incomeflows from assets acquired through loans.On account of the second problem, wehave relied more on studies that havecompared beneficiary income with a con-trol group income, rather than its ownincome at an earlier period.

Based on his field survey, Hossain (1988)found that Grameen Bank borrowers in the‘project villages’ had higher income thanthe target group (those owning less than

0.5 acres of land) in the ‘control villages’by about 43 per cent.17 Further, theirincome level was higher by 28 per centthan target group members in the ‘projectvillages’ who did not borrow from GrameenBank. The difference was highest for theabsolutely landless beneficiaries followedby the marginal landowners. In anotherstudy, Todd (1996) reported a positiveincome impact on the women borrowersfrom her study area.

Apart from the gains in income, studiesfrom Bangladesh found that there wassmoothing of income and consumption forborrower households due to micro-credit[Morduch 1998, Zaman 1999, Khandkar1998, cited in FAO 2000]. While Khandkarfound that increase in and smoothing ofconsumption occurred together, inMorduch’s study, smoothing of consump-tion was not accompanied by an increase.

The period of retaining assets was longerfor Grameen Bank participants than forIRDP beneficiaries [Kurian 1987, Rath1985, Hossain 1988]. In the case of IRDP,the share of households not keeping assetsgained through IRDP for more than twoyears varied from 25 per cent to 50 per cent[Kurian 1987, Rath 1985]. However, in thecase of Grameen Bank, Hossain (1988)found that there was a threefold increasewithin a period of 27 months in the amountof working capital employed by members’enterprises started with Grameen loans.Further, it was also found that the numberof cattle owned by the members increasedby 26 per cent every year (ibid).

The literature on the impact of RRBloans on the income of the borrowers isrelatively limited. The only available es-timate used for the present analysis hasbeen obtained from a study by Hulme andMosley (1996a, 1996b) and Mosley and

Hulme (1998). They undertook a compari-son of income ‘before and after’ takingloans from RRBs. They compared incomelevels of a borrower group of 100 with acontrol group of 50 for each credit insti-tution.18

From these two studies, we have pre-sented in Table 2 the figures of averageannual change in family income19 ofborrowers and the control sample. Amongthe programmes that they studied, benefi-ciaries of RRBs recorded the highest annualchange in family income during 1988-92.20 When compared with the percent-age change in income of borrowers fromthe control group, RRB beneficiariesrecorded a rise of 191 per cent. Table 2also gives information regarding thechange in income over the previous year(as a per- centage of the control group)for all borrowers and for borrowersbelow the poverty line. We find that theincrease in incomes for those below thepoverty line was one of the highest forRRBs at 133 per cent with only BRACexceeding it.

However, the increase in incomes for thepoorest beneficiaries of RRBs was notimpressive. Mosley (1996a) studied theimpact of RRBs on different income classesof beneficiaries. He found that though “thedifference between the income change ofbeneficiaries (of RRB) and the controlgroup is positive,…amongst borrowersbelow the poverty line it is on an averagenegative” (pp 260-61). About 34 per centof the poor borrowers in his sample “crossedthe poverty line”21 in a period of one year,which accounted for about 12 per cent ofthe whole sample.

Based on the studies reviewed, weconclude that both NGO-led micro-creditand state-led credit institutions have led

Table 2: Impact of Loans on Family Incomes of BeneficiariesTable 2: Impact of Loans on Family Incomes of BeneficiariesTable 2: Impact of Loans on Family Incomes of BeneficiariesTable 2: Impact of Loans on Family Incomes of BeneficiariesTable 2: Impact of Loans on Family Incomes of Beneficiaries

Agency Annual Average Change in Change in Average Rise in IncomeFamily Income, 1988-92 Income of in the Year Prior to Survey

(in Per Cent) Borrowers (as Per Cent of Control Group)to Control

Borrowers Control Sample Sample All Borrowers(in Per Cent) Borrowers Poverty Line

(1) (2) (3) (4)= (2/3) (5) (6)

Bolivia: BancoSol 28.1 14.5 193 270 101Bangladesh: Grameen Bank - - - 131 126Bangladesh: BRAC 19.8 13.8 143 143 134Bangladesh: TRDEP 38.7 30.6 126 138 133Sri Lanka: PTCCS 15.6 9.9 157 157 123India: RRBs 46.0 24.0 191 202 133Kenya: KREP Juhudi 1.5 1.1 133 133 103Kenya: KIE-ISP 0.5 0.4 125 125 -Malawi: SACA 2.8 1.6 175 175 -Malawi: Mudzi Fund 1.4 1.2 117 117 101

Source: Hulme and Mosley (1996a), Table 4.1 and Table 8.1.

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to positive but only marginal increases inthe earnings of their beneficiaries. How-ever, given the methodological problemsassociated with studies on income changes,more empirical evidence is required inorder to substantiate such a conclusion.Employment generation and skill improve-ment: Before examining the question ofemployment generation, it would be usefulto consider the debates about the benefitsof generating self-employment and wageemployment. Scholars have taken twoextreme positions on this issue. Dandekar(1986), Rath (1985) and Dreze (1990) haveargued that the generation of wage em-ployment through large-scale publicworks is the most effective strategy for thealleviation of poverty. Contrary to this,others like Dantwala (1986) have sup-ported the strategy of generating self-employment opportunities towards achie-ving this aim. While the latter school fo-cuses on rationales, such as self-reliance,the former school has pointed out thatmarket uncertainty and heavy debts canerode the self-reliance of poor entrepre-neurs as well as their entitlement to em-ployment [Dreze 1990].

Osmani (1989) has taken a more bal-anced position on this issue. He has arguedthat the choice between self- and wage-employment is contingent on the previouscharacter of employment of the beneficia-ries. He has cited studies on GrameenBank, which have found that most of theborrowers after taking loans have followedtheir pre-loan occupations. This is largelyin line with the Grameen Bank philosophythat people can do those activities better,which they have been accustomed to beforetaking the loans. Thus it follows thatborrowers who have some entrepreneurialexperience can handle self-employmentventures better than others and wouldsucceed in raising their income levels.Rightly enough, studies on Grameen ben-eficiaries have shown that relatively suc-cessful borrowers have had some priorknowledge of the market [Hossain 1988].Conversely, those who have no experiencein self-employment, such as agriculturallabourers, are likely to be benefited lessby this system of credit. Hence there willbe need for promoting wage-employmentprogrammes for this section of the ruralpopulation.

The focus of Grameen Bank, as notedearlier, has been on the generation of self/family-employment. Studies indicated thatthe number of days of family employmentincreased slightly for micro-credit benefi-

ciaries after receiving the loans [Hossain1988, Mosley 1996b, Montgomery andBhattacharya 1996]. Hossain (1988) foundthat 20 per cent of the borrowers of thebank were earlier unemployed. There wasa small movement away from agriculturallabour towards vocations like poultryfarming, livestock raising, processing andmanufacturing, trading and shopkeeping.On average, the number of days of family-employment per month went up by 11 to15 days.22 In the case of BancoSol inBolivia, only 38 per cent of the borrowersexperienced an increase in employmentdays after taking the loans [Mosley 1996b].The remaining 62 per cent of the borrowerseither experienced a decrease or no changein employment days. Further, a majorityof those who got more employment werefrom the higher income classes [Mosley1996b]. For SANASA in Sri Lanka, Hulme,Montgomery and Bhattacharya (1996)found that for non-agricultural loans, theincrease in family employment was only0.7 persons per enterprise. However, therewas an increase in employment of fourpersons per household in the case of paddyloans (ibid).

Studies indicated that micro-enterprisescompletely failed in generating non-fam-ily employment. From their cross-countrystudies, Hulme and Mosley (1996a) reportthat between the borrowers and the controlgroup of non-borrowers, there was a dif-ference of only one employee per enter-prise. In the case of SANASA, only 8 percent of the borrowers reported increase inthe number of paid employees in theiractivity [Hulme, Montgomery andBhattacharya 1996]. The average increasein employment was one employee perenterprise for non-farm loans and 4.5employees per household for crop loans.Buckley (1996), reporting a study on KREPJuhudi credit scheme in Kenya, found thatthe increase in employment from theseschemes was less than 0.5 employees perenterprise. In the case of RRB loans inIndia, the average increase was reportedto be only 0.6 employees per enterprise[Mosley 1996a].

This takes us to the issue of technologyused in these enterprises. Hulme andMosley (1996a) found that the percentageof borrowers who invested in new tech-nology was only 33 per cent in their “highimpact schemes” and 7.5 per cent in “lowimpact schemes”.23 In the case of RRBs,12 per cent of the borrowers invested innew technology, while in BRAC andBancoSol, this proportion was 8 per cent

and 26 per cent respectively. Those whoadopted new technology were found toreap higher benefits than others under allschemes. In Kenya, under the Juhudi-supported enterprises, a majority of theborrowers sought credit solely forworking capital to undertake “what theyknew best” [Buckley 1996: 325]. Fromthese studies, it appears that the numberof borrowers adopting new technologyunder the micro-credit schemes have beenfew in number.

One important reason for the poor adop-tion of new technology is the absence ofany skilled training to borrowers under themicro-credit schemes. Imparting skills iscrucial for undertaking new investmentsand adopting new technology. The phi-losophy guiding Grameen Bank is that thepoor do not need to be given any skill toutilise the loans as they have an inherentskill, which Mohammed Yunus calls “sur-vival skill” [Yunus 1999: 140]. It is thepresence of this inherent skill that “keepsthem alive even when they are poor” (ibid).Hence it is believed that the provision ofcredit per se would transform the borrow-ers into able entrepreneurs. In our opinion,this repudiates the importance of mod-ern skills and technology. Credit pro-vided by micro-credit programmes on thisprinciple may provide temporary incomerelief to the beneficiaries but would keepthem in a perpetual state of technologicalbackwardness. It is only through a sus-tained transfer of modern technologyalong with credit that such programmescan be of help in dealing with the problemof poverty.Financial viability: Of the various factorsthat determine the financial viability of acredit institution, we have selected threefactors for the present analysis. They arecosts of default, administrative costs anddependence on subsidies.

Costs of DefaultCosts of DefaultCosts of DefaultCosts of DefaultCosts of Default

Minimising the costs of default is crucialfor the sustainability of any credit provi-sion programme or institution. The de-fault rates of IRDP and RRB loans inIndia have been very high. In the caseof IRDP, the default rate on advancesgranted by public sector banks as apercentage of demand increased from 58.7per cent as in 1991 to 69.1 per cent in 1993[RBI 1993]. In her field study in WestBengal (in 1988-89), Swaminathan (1990)found that the local bank branch reporteda default rate on IRDP loans of 45 per cent.

Economic and Political Weekly March 9, 2002960

About 75 per cent of borrowers in thevillage did not have any overdue at the timeof survey. In her field study in Tamil Nadu(in 1985), she found that only 12.5 per centof the borrowers had fully repaid the loans(ibid).

The default rate among the respondentborrowers of Grameen Bank was only 3.3per cent in 1985 [Hossain 1988]. This levelwas maintained during the nineties [Yunus1999].

Mosley (1996a) analysed default ratesfor RRB loans and found that during1983-91, the average default rate was 47.5per cent. The six-month arrears rate ofRRBs in 1992 was the highest among the13 institutions that Mosley and Hulme(1998) examined across different coun-tries (Table 3).24 While RRBs had a six-month arrears rate of 42 per cent, thesame for Grameen Bank was 4.5 percent and for BRAC 3 per cent. In the caseof RRBs, between 1982 and 1992, therewas a fall in the overdue rates, from 50.0per cent to 32.9 per cent of total lending(ibid).

However, there have been two majorarguments against low default rates onGrameen Bank loans. First, sizewise de-composition of the repayment rates indi-cates that low default rates have beenconfined to loans of very small size[Hossain 1988]. Default rates tended toincrease with the increase in the loan size(ibid). Default rates among the first-timeand the second-time borrowers were 0.4and 1.2 per cent respectively. For the third-time borrowers, this rate increased to 6.6per cent and in the case of fourth-timeborrowers, it further rose to 9.5 per cent(ibid). The number of people with nooverdue installments decreased from 96.7per cent for the first-time borrowers to 61.0per cent for the third-time borrowers and32.9 per cent for the fourth-timer borrow-ers (ibid).

Secondly, studies have found that theprompt and regular repayment of loaninstallments has largely occurred throughcross-financing from other informalsources of credit and not through the returnsfrom the investment undertaken with theloan. There are two important studies thatbring out this aspect of the operation ofGrameen Bank. Rahman (1999), in a studyin Tangail district, has pointed out thatmost of the timely repayments were notmade out of incomes flowing from assetsgained, but through further borrowing fromprivate moneylenders. Many borrowers inRahman’s village repaid Grameen Bank

loans through short-term loans frommoneylenders “with a promise to the lenderthat the borrower will return the amount(usually with interest) after receiving thenew loan from the Grameen Bank” (ibid,p 78). This meant that the borrowers begana new Grameen loan “with a deficit on thecapital”. This, according to Rahman, ledto the creation of “debt cycles” for theborrowers (ibid).

In another important study in Madhupurthana in northern Bangladesh, Sinha andMatin (1998) found that 94 per cent ofmicro-credit borrowing households in theirvillage were also indebted to informal sourcesof credit. Target group households (withless than 0.5 acres of land) depended onone informal sector loan every 10 weeks,while the frequency was 12 weeks in thecase of non-target group households.They noted that “most of the informalloans repaid with Grameen loans weretaken to repay earlier Grameen loans” (ibid,p 70-71). Among the target group house-holds, 45 per cent of the amount of infor-mal sector loans was utilised for repayingloans taken from micro-credit institutions,including Grameen Bank. Among the non-target group households, this share was 15per cent. Sinha and Matin concluded that,

High levels of cross-financing deplete thecapital of the loan, and reduce the valueof the new loan that is used to repay orservice the old. The process turns into a‘vicious cycle’ as smaller investments intodirectly productive enterprises yield lessreturns, thus requiring even higher loansthe next time to repay the original loan.It erodes the profitability of any enterprise,especially if a high interest loan is takenfrom the informal market [Sinha and Matin1998: 72].

Administrative CostsAdministrative CostsAdministrative CostsAdministrative CostsAdministrative Costs

Information about the administrativecosts25 incurred by credit institutions isprovided by Hulme and Mosley (1996a)(Table 4). During 1988-92, the adminis-trative costs (as a percentage of totalportfolio) were the lowest for RRBs (onaverage 8.1 per cent per annum). ForGrameen Bank and BRAC, they were 12.3per cent and 40.0 per cent respectively forthe same period. Over the years, the ad-ministrative costs for Grameen Bank ap-peared to have increased. Total adminis-trative costs increased from 4 per cent oftotal liability to about 7 per cent between1984 and 1986 [Hossain 1988]. As a shareof the portfolio or the amount of loans, it

Table 3: Default Rate, Cost of Credit and Subsidy Dependence IndexTable 3: Default Rate, Cost of Credit and Subsidy Dependence IndexTable 3: Default Rate, Cost of Credit and Subsidy Dependence IndexTable 3: Default Rate, Cost of Credit and Subsidy Dependence IndexTable 3: Default Rate, Cost of Credit and Subsidy Dependence Index

Agency 6-Month Arrears Real Interest Rates SDIRate (Per Cent) (Per Cent) (1988-92 Average)

Bolivia: BancoSol 0.6 45 135Bangladesh: Grameen Bank 4.5 15 142Bangladesh: BRAC 3.0 11 199Bangladesh: TRDEP 0.0 - 199Sri Lanka: PTCCS 4.0 11 226India: RRBs 42.0 3 133Kenya: KREP Juhudi 8.9 9 217Kenya: KIE-ISP 20.2 -1 267Malawi: SACA 27.8 7 398Malawi: Mudzi Fund 43.4 8 1884

Source: Compiled from Mosley and Hulme (1998), Table 1.

Table 4: Components of Cost StructureTable 4: Components of Cost StructureTable 4: Components of Cost StructureTable 4: Components of Cost StructureTable 4: Components of Cost Structure(average levels as percentage of total portfolio, per annum)

Agency Cost Componentsi a a1 a2 a3 a4 p

Bolivia: BancoSol 8 28 17 4.5 4 3 1Bangladesh: Grameen Bank 3.5 12.3 4.3 6 2 1 5Bangladesh: BRAC 0 40 16 5 2 14 3Bangladesh: TRDEP 0 100 16 5 2 77 -Sri Lanka: PTCCS 1 17 - - - - 4India: RRBs 9.7 8.1 6 - - 2 42Kenya: KREP Juhudi 0 33 19 3 9 2 9Kenya: KIE-ISP 0 27 9 - 6 12 20Malawi: SACA 0 11 8 - - 3 28Malawi: Mudzi Fund 0 722 238 1.5 67 415 43

Notes: i – Borrowing interest rate; a – Total administrative costs; a1 – Loan supervision costs; a2 –Insurance costs; a3 – Research, training and support of other institutions; a4 – Other costs; p – Costsof default; a1, a2, a3 and a4 are components of a.

Source: Hulme and Mosley (1996a), Table 3.2.

Economic and Political Weekly March 9, 2002 961

increased from 8.6 per cent to 18.1 per centduring the same period.26

Comparison of administrative costswith costs of default for various financialinstitutions indicated that these two movedin inverse direction. High rates of repay-ment helped these banks achieve higherprofit levels every year. However, in orderto maintain such high rates of repayment,these banks had to invest considerableresources in administering the loans. Theexistence of high administrative costsof micro-credit institutions has beennoted in many studies [Bhat and Tang1998].27 What might appear paradoxicalhas been the co-existence of high admini-strative costs and high levels of profit.The answer to this paradox can be foundin the fixation of interest rates by theseinstitutions. Interest rates for micro-credit were fixed high in order to com-pensate for high transaction costs orcuts in subsidies. The nominal interestrate on the loans from Grameen Bankwas kept stable at 16 per cent per annumtill 1991. It was subsequently raised to20 per cent. This was 8 per cent higherthan the market rate in Bangladesh [Rahman1999].

The real rate of interest on Grameenloans, as noted by Osmani (1989), wasabout 18 per cent compared with 12-15 percent charged by the state agencies in the1980s. In their study, Mosley and Hulme(1998) also found that the real rates ofinterest for micro-credit institutions weregenerally higher than those charged by thestate-sponsored programmes and institu-tions (Table 3). During 1992, the realinterest rate on Grameen Bank loans was15 per cent, while for RRBs it was only3 per cent.

We argue that high rate of interest onloans is effectively a burden on the in-comes of the poor. Further, given the lowcapital intensity of investments madethrough micro-credit and the resultantlow profit margins, high rates of interestdampen the possibility of any significantsavings on the part of the poor borrowers.As the poor largely borrow for meetingconsumption-related requirements, theburden of high interest rates is felt evenmore strongly by them. Among GrameenBank borrowers in their study village, Sinhaand Matin (1998) noted that 34 per centof the loans from micro-credit institutionswere spent for household food consump-tion and 32 per cent in repaying othermicro-credit loans. Such a high levy, in ouropinion, is a barrier for poor households

in raising their income levels and beingable to save.

Rahman argued that high costs of creditamounted to transferring high administra-tive costs onto the poor borrowers [Rahman1999]. He identified this shift as the majorcause for the existence of “debt cycles”,which were discussed in the last sub-sec-tion. Rahman also pointed out that when-ever Grameen Bank increased the salaryof its staff, the increase in cost was shiftedto the borrowers through raising interestrates (ibid).

Subsidy DependenceSubsidy DependenceSubsidy DependenceSubsidy DependenceSubsidy Dependence

Most of the rural credit programmes andinstitutions are subsidised. In the case ofstate-led programmes, this subsidy is borneby the government while in the case ofNGO-led institutions, it is mainly borneby domestic and international privatedonors. We have compared these lendinginstitutions on the basis of their depen-dence on subsidies; the dependence hasbeen captured by an index called theSubsidy Dependence Index (SDI), devel-oped by Yaron (1992). SDI represents theper centage increase required in the on-lending rate such that the dependence onsubsidies can be completely eliminated fora given institution.28

The SDI calculated by Hulme and Mosley(1996a) for credit institutions is given inTable 3. As seen from the table, SDI wasover 100 per cent for all institutions. Amongother institutions, RRBs had the least SDIof 133 per cent. For Grameen Bank, thiswas higher at 142 per cent (ibid).

High dependence on subsidies has beenanother route – other than increasing in-terest rates – through which micro-creditagencies have been able to evade thenegative impact of high administrativecosts. During the late 1980s, if subsidieshad been removed, Grameen Bank wouldhave incurred losses [Hossain 1988]. In1986, the loss thus incurred on creditoperations was 5.7 per cent of the out-standing loans. The SDI of Grameen Bankhas risen over the years [Khandker et al1995]. Moreover, the periods that havewitnessed a decline in SDI have been theperiods of increasing rates of interest (ibid).In other words, heavy dependence onsubsidies has been an intrinsic feature ofthe micro-credit institutions.29 Based onthe foregoing analysis, it can be con-cluded that the financial viability ofmicro-credit institutions has been fragilein nature.

Grameen-Type Models: SomeGrameen-Type Models: SomeGrameen-Type Models: SomeGrameen-Type Models: SomeGrameen-Type Models: SomeIssues in Expansion andIssues in Expansion andIssues in Expansion andIssues in Expansion andIssues in Expansion and

ReplicationReplicationReplicationReplicationReplication

In relation to the expansion and repli-cation of NGO-led micro-credit institu-tions, two questions need to be answered.First, is the model of micro-credit set byGrameen Bank viable in Bangladesh itselfafter it expands its operation? In otherwords, can Grameen Bank, once expandedinto a macro-level programme, avoid thedrawbacks of a large-scale credit-basedpoverty alleviation programme like IRDPand institutionalise itself into a sustainablescheme for poverty alleviation? As Osmani(1989: 2) has put it, “the issue is not howwell the Grameen Bank has done so far… [it] is how well this strategy is likelyto work as a major anti-poverty programme,once its scale is expanded many times…”.Secondly, is this model replicable in othercountries, like India, as an effectiveprogramme for credit-based poverty alle-viation? Let us attempt to probe into thesequestions.

First, we argue that the relatively smallerscale of operation of Grameen Bank hasbeen its greatest advantage in evading theproblems encountered in a large-scale creditprovision programme or institution. Acomparison of the magnitude of opera-tions of Grameen Bank and state-led creditinstitutions in India reveals the limitedscale of operation of the former. In 1992,Grameen Bank had just 1.05 millionborrowers. In the case of RRBs, the num-ber of borrowers was 12 million in 1992[Mosley and Hulme 1998].30 In the1990s, Grameen Bank expanded itsoperations – in terms of the number ofbeneficiaries and disbursement of credit– in Bangladesh. By November 2000, ithad branches in 40,212 villages, whichspread across 46.7 per cent of the totalvillages in Bangladesh.31 The number ofborrowers of Grameen Bank had increasedto 2.4 million by November 2000. Bycontrast, by March 2000, the borrowersfrom RRBs numbered 11.8 million [RBI2000a: 9]. In other words, the number ofborrowers of Grameen Bank formed onlyabout 20 per cent of the borrowers ofRRBs.

Regarding the amount disbursed, tillApril 2000, Grameen Bank had disburseda cumulative amount (for a period of 25years) of taka 1,36,986 million (equivalentto about $ 3,228 million).32 If we considerthe year 1987-88, when the IRDP advancespeaked, we find that advances during that

Economic and Political Weekly March 9, 2002962

single year were around Rs 17,790 millionat current prices (roughly equivalent to$ 1,271 million). This formed around 39per cent of the cumulative amount dis-bursed by Grameen Bank till 2000.33 Thedata presented here need not be used fora strict comparison of the two programmes.We have presented these figures only toindicate the scale of operation of GrameenBank vis-à-vis the state-led creditprogrammes in India. Evidently, the scaleof operation of Grameen Bank has beensmaller than the state-led programmes andinstitutions.

The implementation of a poverty alle-viation programme is commonly beset withcertain “mismatches” [Osmani 1991].34

The drawbacks encountered in the case ofIRDP also had a bearing on such mis-matches among other factors [Osmani1991, Swaminathan 1990, Nagaraj 1999].One way to reduce the mismatches is theadoption of local level planning in theimplementation and monitoring of thepoverty alleviation programmes [Nagaraj1999, RBI 1990]. Local-level planningcan be described as the identification,mobilisation and allocation of all the re-sources at the local level. In this context,it may be noted that a relatively betterperformance of IRDP was observed inWest Bengal, where the programme wasimplemented through panchayats[Swaminathan 1990].

We argue that the small scale of opera-tion of Grameen Bank has acted in itsfavour, helping to keep any mismatch ofsupply and demand at a lower level. Aninstitution such as Grameen Bank, by virtueof being an NGO, is more likely to functionin an uncoordinated fashion with otherinstitutions involved in the provision ofcredit as well as institutions constitutedfor planning of other resources in therural economy. Hence local-level plan-ning, as defined earlier, may be difficultto implement in a social security systembuilt on the basis of NGOs such asGrameen Bank. As a result, the kind ofmismatches observed for IRDP may bedifficult to avoid for micro-credit pro-grammes and institutions, such asGrameen Bank, once they expand theirscale of operation.

Secondly, as noted earlier, the finan-cial viability of Grameen Bank has beenfragile even at a smaller scale of opera-tion. An expansion in scale is likely toresult in a rise in transaction costs lead-ing to an increase in its reliance onsubsidies.

IVIVIVIVIVConclusionsConclusionsConclusionsConclusionsConclusions

This paper reviewed the available em-pirical evidence on NGO-led micro-creditprogrammes and institutions implementedacross various developing countries. Theobjective was to judge the performance ofthese programmes and institutions on thebasis of a set of four indicators in com-parison with the state-led credit-basedpoverty alleviation programmes andinstitutions, such as, the IRDP and RRBsin India.

The review indicated that NGO-ledmicro-credit programmes and institutions,such as Grameen Bank, have been success-ful in reaching their target groups of poormore effectively than the state-ledprogrammes and institutions. However,even these have not been free of the “ex-clusion problem” in targeting. With duerecognition of the methodologial prob-lems involved in accounting incomechange, the study led to the conclusion thatmicro-credit programmes and institutionshave generated a positive change in theincomes of beneficiaries, but this changehas only been marginal. A similar resulthas been noted in the case of IRDP andRRBs in India.

Micro-credit programmes and institu-tions have generated a positive impact onthe number of days of family employment.However, their performance in the genera-tion of wage employment has been poor.Further, given the principle of “survivalskill” that has driven institutions, such asGrameen Bank, there has not been anydiscernible contribution to the improve-ment of skills and technology adopted bythe beneficiaries. Hence the availableevidence indicates that Grameen-type creditprogrammes and institutions, at their cur-rently small scale of operation, have madea ‘minimalist impact on the earnings andemployment generation for the rural poor.

The micro-credit programmes and insti-tutions have been operating profitably onaccount of remarkably high repayment rateson loans. The repayment rate in the caseof Grameen Bank, for example, was ashigh as 97 per cent in 1998. Such repay-ment has been made possible by incurringhigh administrative costs. The negativeeffect of these costs on the profit levelshas been counterbalanced, first by raisinginterest rates on loans, and second, byrelying more on subsidies. This exposesthe fragile financial health of suchprogrammes and institutions.

We conclude that NGO-led micro-creditprogrammes and institutions given theirsmall scale of operation have been suc-cessful in targeting and generating profits.With an increase in their scale, however,they may experience similar constraints intargeting as large-scale poverty alleviationprogrammes like IRDP. Further, on ac-count of an increase in their costs ofoperation, their dependence on subsidiesis likely to grow, weakening their financialviability. However, claims such as theseneed to be substantiated with the help ofcarefully obtained empirical evidence onmicro-credit programmes and institutionsin the years to come.

This is not to say that credit is the solemeans of addressing the problem of ruralpoverty. An improvement in the livingconditions of the rural poor requires amongother things, agrarian reforms, democraticdecentralisation, public action towardsbetter educational and health facilities andthe maintenance of a public food distri-bution network for the poor.

A Note on Micro-Credit PolicyA Note on Micro-Credit PolicyA Note on Micro-Credit PolicyA Note on Micro-Credit PolicyA Note on Micro-Credit Policyin Indiain Indiain Indiain Indiain India

There are certain fundamental differ-ences between the current policy on micro-credit in India and that in other developingcountries, such as Bangladesh.

Table 5: Number of Self-Help Groups Formed by Public Banks and Loans Provided,Table 5: Number of Self-Help Groups Formed by Public Banks and Loans Provided,Table 5: Number of Self-Help Groups Formed by Public Banks and Loans Provided,Table 5: Number of Self-Help Groups Formed by Public Banks and Loans Provided,Table 5: Number of Self-Help Groups Formed by Public Banks and Loans Provided,India, 1992-93 to 2000-01India, 1992-93 to 2000-01India, 1992-93 to 2000-01India, 1992-93 to 2000-01India, 1992-93 to 2000-01

Year Number of SHGs Bank Loans Provided Refinance(Rs Crore) (Rs Crore)

1992-93 255 0.29 0.271993-94 620 0.65 0.461994-95 2122 2.44 2.131995-96 4757 6.06 5.661996-97 8598 11.84 10.651997-98 14317 23.70 21.391998-99 32995 57.07 52.091999-00 94645 192.98 150.132000-01 213213 480.87 400.74

Source: Annual Report, 2000-01, Table 7.1, Nabard, Mumbai.

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Contrary to the Grameen-type modelstried out in other countries, Indian bankingpolicy has attempted to involve the publicbanking network in the provision of micro-credit to the poor through self help groups(SHG). A paper by Nabard has referred tothe Indian policy on micro-credit as “re-lationship banking”, against “parallelbanking” in other countries [Jayaraman2001: 18). Public banks adopt the ap-proach of group lending and peer moni-toring for lending to the SHGs. Such apolicy has three variants that differ in themode of linkage between the banks andborrowers; all three have been encouragedby Nabard for the provision of rural creditin India (ibid).

In variant I, the public bank acts as a selfhelp group promoting institution (SHPI),“takes initiatives in forming the groups,nurtures them over a period of time andthen provides credit to them after satisfy-ing itself about their maturity to absorbcredit”.35 In variant II, public banks andborrowers (SHGs) are linked throughfacilitating agencies, which are eitherNGOs working locally or governmentagencies. 36 It differs from variant I as theformation and nurturing of the SHGs is theresponsibility of the facilitating agency.Direct loans are provided to the groupafter the banks gain confidence about theviability of lending to the group. In variantIII, both the facilitating and intermediatingfunctions are played by the NGOs. Thefunctions of forming groups, nurturingthem and providing credit to them areperformed by NGOs, while banks confinethemselves to providing credit to NGOs.According to Nabard, this variant is prac-tised in regions where the banks “are notin a position to even finance SHGs pro-moted and nurtured by other agencies”.37

Data on SHGs show that the number ofSHGs formed through public banks hasgrown rapidly in the 1990s; their numberhas risen sharply in the second half of thelast decade (Table 5). Among the threevariants, variant II has been the mostnumerous [Puhazhendi and Satyasai 2000].Nearly 70 per cent of all the SHGs wereof the kind of variant II, while 16 per centand 14 per cent of the groups belonged tovariants III and I respectively. Neverthe-less, an evaluation paper by Nabard makesthe case that variant III “is likely to befound more convenient by banks for creditlinkage in the coming years, when verylarge number of SHGs would be requiredto be linked by small sized branches ofbanks” (ibid, p 17).

In the light of the above approach to thesupply of micro-credit in India, certainissues need to be discussed. First, the supplyof micro-credit takes place through thevast institutional network of rural bankingin the country built during the post-banknationalisation period. The utilisation ofthis network for experimenting in an in-novative method of lending needs to beappreciated.

Secondly, studies indicate that adoptingthe method of group lending through SHGscould reduce the lending and supervisioncosts of public banks [Puhazhendi 1995]and raise repayment rates [Karmakar 1999,Puhazhendhi and Satyasai 2000]. How-ever, as the available studies till date arelimited in number, more field studies arerequired to pass any judgment on theoutcome of the SHG experiment.

Thirdly, the utilisation of the publicbanking network for the supply of micro-credit does not necessarily mean the con-tinuation of public regulation or account-ability in its operations. It has been pointedout that it is “desirable and appropriate tosupport evolution of a self-regulatorymechanism for micro-finance institutions,such as NGOs (MFIs), which would pre-scribe codes of conduct and groundrules” [RBI, 2001: 307]. Hence the degreeof accountability of NGO-led micro-credit institutions in India still remainsunclear.

Fourthly, the supply of credit throughpublic banks may not ensure that the interestrates in SHG loans will not exceed theceiling fixed by the RBI for small loans.In fact, RBI’s Monetary and Credit Policyfor 1999-2000 has stated that “while smallloans directly given by banks will continueto be subject to the interest rate ceiling asprescribed by the RBI from time to time,interest rates applicable to loans given bybanks to micro-credit organisations or bythese organisations to their members/ben-eficiaries will be left to their discretion”[RBI 1999a: 13]. Interest rates are fixedin such a manner that they provide a marginto the banks as well as to the NGOs. Theempirical evidence has shown that theserates have been higher than the ratescharged on loans directly taken from banks[Karmakar 1999, Puhazhendhi andSatyasai 2000].

NotesNotesNotesNotesNotes[We are grateful to C L Dadhich, V K Rama-chandran, S L Shetty and Madhura Swaminathanfor their comments and useful discussions. A draftversion of this paper was presented at the third

annual conference on Money and Finance at theIndira Gandhi Institute of Development Research,Mumbai. We thank the participants of theconference, especially Malabika Roy, for theircomments. Errors and omissions, if any, are ours.]

1 The conventional bank practices are aimed athigh recovery rates, caution in lendingdecisions, commercial stability through depositmobilisation [Copestake et al, 1984, Wigginsand Rajendran 1987].

2 We are grateful to S L Shetty for pointing thisout to us during discussions.

3 Shetty (1997) has argued that some of theweaknesses, such as the poor profitability underthe banking system was not purely on accountof directed lending, as often argued, but hada bearing also on the defaults on loans takenby bigger borrowers. He has also argued thatin order to overcome the weaknesses in thedevelopment of public sector banking,“periodic evaluation” and adoption ofcorrective steps were required. Though anumber of committees were set up to reviewthe operation of the banking system in theperiod following bank nationalisation in India,their recommendations were often not followedup as desired (ibid p 254).

4 For a detailed discussion of these difficulties,see Hulme and Mosley (1996a).

5 This implies that under no circumstances arethe poor excluded from the benefits of theprogramme (Type I) while the non-poor canbecome its beneficiaries (Type II).

6 Grameen Bank is a statutory financial institutionestablished in Bangladesh in 1983. In 1999,the government and the borrowers held 12 and88 per cent of its paid-up capital respectively[Karmakar 1999].

7 Source: <http://www.grameenfoundation.org>8 The smallness of the size of loans differs from

country to country. In India, for example, aceiling of Rs 25,000 has been fixed for definingmicro-credit [RBI 1999].

9 The asset eligibility criterion of the bankspecifies that the member should be from ahousehold having less than half an acre ofcultivated land or assets of the value equivalentto less than one acre of medium quality land[Hossain 1988].

10 In order to seek loans from Grameen Bank,borrowers have to approach the bank in agroup consisting of five members. Of the five,only two are given loans at the first stage. Aftermonitoring the repayment behaviour of thesetwo for some time (generally, a month), thenext two are provided loans and finally the lastperson, who is the chairperson of the group,gets his/her loan. Thus the behaviour of everymember of the group is monitored rigorouslyat every stage by the bank staff [Yunus 1999].

11 The group helps in monitoring and enforcingrepayment from each of the members. If anymember defaults he/she faces penalty in theform of ostracism and loss of social standing.Thus it is evident that though the loans areoffered without any personal collateral, theyinvolve social collateral [Hulme and Mosley1996a]. Further, a repeat loan is not sanctionedtill the accounts of all the group members aresettled [Hossain 1988].

12 IRDP has been the most important povertyalleviation programme of the government of

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India, which was initiated in 1980. It providesa combination of loan and subsidy to ruralfamilies (an identified target group of ruralpoor belonging to families below povertyline) for acquiring suitable incomegenerating assets and self-employmentopportunities to enable them to cross thepoverty line. In terms of magnitude, thishas been one of the largest programmes ofits type in the world for the alleviation ofpoverty [GoI, Ninth Plan 1997].

13 RRBs are state owned banks in India, establishedin 1975, functioning exclusively in the ruralareas to provide credit to small and marginalfarmers, agricultural labourers, artisans andsmall entrepreneurs at cheap interest rates(RRB Act, 1976, cited in Maheswari, 1995).

14 Those who achieved more than 90 per centtargeting were Grameen Bank, BRAC,TRDEP and Malawi Mudzi Fund. Mosley’ssurvey was conducted in 1992, before itwas declared by the government that RRBscould give 40 per cent of their loans to thenon-poor.

15 Jean Dreze (1990) pointed out that the sizeof loans from IRDP was not high enough toensure a high income gain. After calculatingthe possible gains from IRDP loans, Drezefound that even if one assumed a high marginalproductivity of capital for the assets, theresultant increase in income for thebeneficiaries was only marginal.

16 This finding, however, has been disputed byOsmani (1989) on two grounds. Firstly, Kuriancalculated income levels without netting theloan amount borrowed (liable to be repaid) andsecondly, it was not clear if he adjusted theincome figures into constant prices beforecomparing between the two periods. Osmanihas argued that if simple adjustments weremade for these two factors, the increase inincome might remain an illusion.

17 Hossain conducted a census-type survey of 15villages, which had Grameen branches in 1985.These villages were divided into ‘projectvillages’ and ‘control villages’. ‘Projectvillages’ were villages with Grameen Bankbranches that were more than three years old.‘Control villages’ were those with GrameenBank branches that were less than three yearsold. ‘Control villages’ were selected such thatthey were similar to ‘project villages’ in landdistribution and occupational structure[Hossain 1988: 14].

18 The control group in Hulme and Mosley (1996a,p 11) were “selected to be as similar as possibleto the borrower group except for thecharacteristic of not having received a loanfrom a case study institution”.

19 These incomes are real incomes, deflated bythe difference in inflation rates between thenational currency and the US dollar [Hulmeand Mosley 1996a].

20 However, this figure needs to be interpretedwith caution because, as can be seen fromTable 2, the same was also observed in caseof the control group during this period.

21 Mosley used the poverty line as suggested byDutt and Ravallion (1994, cited in Mosley1996a).

22 These figures should be interpreted with cautionbecause, as Hossain (1988) admits, it is difficultto calculate the number of days of employment

without undertaking a survey of regularemployment.

23 ‘High impact’ schemes were those for whichthe growth in the income of borrowers wasmore than 50 per cent of that of the controlgroup [Hulme and Mosley 1996a].

24 Six month arrears rate has been defined as thevalue of loans, which are six months or morein arrears, as a proportion of total value ofloan portfolio [Hulme and Mosley, 1996a,p 43, 82].

25 Administrative costs constitute a major portionof total transaction costs of a credit institution.Transaction costs include costs of information,negotiations, monitoring and enforcement ofcontracts [Bardhan 1989].

26 To a certain extent, this was due to the salaryincrease effected for the Grameen Bank staffin 1985. However, a major part of this cost,as noted by Hossain (1988), was due toexpansion activities of the bank, such asopening of new branches.

27 Bhat and Tang (1998) argued that the inabilityto reduce administrative costs lied at the rootof Grameen Bank and other micro-creditinstitutions failing to grow into financiallyself-sufficient lending organisations. Rahman(1999) drew attention to how Grameen Bankincurred high administrative costs to ensurehigh repayment rates: “…the loan operationpolicy emphasises a strong supervisory measureto ensure borrower’s use of their loans forincome generation and to pay instalments fromtheir earned incomes. In this system, the groupchairperson and the bank’s centre chiefs wereobliged to supervise the loan use immediatelyafter the loan was disbursed. Upon theirsatisfactory investigation, they reported it tothe bank worker. The bank worker then hadto inspect the investment and verified thereport of the group with a written descriptionof the investment to the branch manager. Inaddition, the investment of the borrower wasfurther supervised by the responsible branchmanager and programme officer from the areaoffice” (p 75).

28 SDI has a lower bound of –100 per cent, butno upper bound [Yaron 1992]. SDI of zeroindicates full self-sustainability for aninstitution. SDI of 100 indicates that a doublingof lending rate is required for a completeelimination of subsidies (ibid).

29 Though not related to the issue of financialviability, an important matter associated withthe dependence on subsidies is the role ofdonor agencies. The preferences of suchagencies are likely to exert a strong influenceon the operation of the micro-credit agencies.It is pointed out that in order to ensure aidfrom its donors, these agencies are likely toadopt measures that may pay off in the shortrun [Petras 1997]. If the aim is to institutionalisethe social security net, such as establishinginstitutions providing finance against poverty,long-term planning is called for. NGOs withtheir dependence on aid from external agenciesmay not be suitable towards achieving this end.

30 In the long list of “replications of GrameenBank” given in et al (1995), none could boasta membership of over 14,000 (see AppendixC in the original).

31 See http://www.grameen-info.org/bank/supdates.html for the data on Grameen Bank.

The data for the total number of villages inBangladesh (86,038) was obtained from aWeb site of the government of Bangladeshh t tp : / /www.bang ladeshgov .o rg / r eb /about_reb.htm.

32 Cumulative amount disbursed refers to thecumulative amount disbursed by the bankfor all the years of its operation from 1976,when the bank started off by lending $27to 42 people in a village in Bangladesh. Seeh t t p : / w w w . g r a m e e n - i n f o . o r g / b a n k /lookbs.html.

33 During the 1990s, the advances through IRDPhave fallen in India as a consequence of thefinancial liberalisation measures [Rama-chandran and Swaminathan 2000, Chavan2001]. For the sake of comparison, if wetake the advances through IRDP in 1998-99,it was Rs 21,730 million at current prices(roughly equivalent to $ 517 million), whichformed about 16 per cent of the cumulativeamount disbursed by Grameen Bank till2000.

34 Tracing common links from different countries,Osmani (1991) has highlighted the neglect ofthree types of matching that underlie the “basiceconomics of a massive self-employmentprogramme”. They are (1) matching betweenthe structure of output and the existing orprospective pattern of demand for that output,produced by the supply of an asset; (2) matchingbetween the structure and quantum of assetsacquired by the household and its existing orprospective supply of assets; and (2) matchingbetween the type of assets and the pre-existingresources of a household. The empiricalevidence of such mismatches in imple-mentation can be found in Swaminathan(1990). Regarding the first mismatch, shefound that in West Bengal, IRDP schemessupplied too many cycle-rickshaws for thebeneficiaries, while there existed aninsufficient demand for their services. TheIRDP schemes’ failure to supply a sufficientnumber of high-yielding and cross-bred milchcattle to all, leading to supply of low qualitybreeds was an example of the second mismatch.As an example for the third mismatch, shefound that households were given cattle andsheep, when they did not own or have accessto any grazing land.

35 See http://www.nabard.org/roles/mcid/shglinkbank.htm.

36 Some examples of government agenciesacting as a facilitator for the formation ofSHGs are the District Rural DevelopmentAgency (DRDA) in Andhra Pradesh, by theDistrict Women Development Agency(DWDA) in Rajasthan and zilla parishads inKarnataka. For details, see Jayaraman (2001,p 31-32).

37 See http://www.nabard.org/roles/mcid/shglinkbank.htm.

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