Morduch Microfinance Promise

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Journal of Economic LiteratureVol. XXXVII (Decmber 1999), pp. 1569–1614

Morduch: The Microfinance Promise Journal of Economi c Liter ature, V ol. XXXVII (December 1999)

The Microfinance PromiseJonathan Morduch1

1. Introduction

ABOUT ONE billion people globally live in households with per capita in-comes of under one dollar per day. Thepolicymakers and practitioners who havebeen trying to improve the lives of thatbillion face an uphill battle. Reports of bureaucratic sprawl and unchecked cor-ruption abound. And many now believethat government assistance to the pooroften creates dependency and disincen-tives that make matters worse, not bet-ter. Moreover, despite decades of aid,communities and families appear to be

increasingly fractured, offering a fragilefoundation on which to build.

Amid the dispiriting news, excite-ment is building about a set of unusual

financial institutions prospering in dis-tant corners of the world—especially Bolivia, Bangladesh, and Indonesia. Thehope is that much poverty can be allevi-ated—and that economic and socialstructures can be transformed funda-mentally—by providing financial services to low-income households. Theseinstitutions, united under the banner of microfinance, share a commitment toserving clients that have been excluded

from the formal banking sector. Almostall of the borrowers do so to financeself-employment activities, and many start by taking loans as small as $75, re-paid over several months or a year. Only a few programs require borrowers toput up collateral, enabling would-be en-trepreneurs with few assets to escapepositions as poorly paid wage laborersor farmers.

Some of the programs serve just ahandful of borrowers while others servemillions. In the past two decades, a diverse assortment of new programs hasbeen set up in Africa, Asia, Latin Amer-ica, Canada, and roughly 300 U.S. sitesfrom New York to San Diego (The Econo- mist 1997). Globally, there are now about 8 to 10 million households servedby microfinance programs, and somepractitioners are pushing to expand to

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1 Princeton University. [email protected]. I have benefited from comments fromHarold Alderman, Anne Case, Jonathan Conning,Peter Fidler, Karla Hoff, Margaret Madajewicz,John Pencavel, Mark Schreiner, Jay Rosengard,J.D. von Pischke, and three anonymous referees. Ihave also benefited from discussions with AbhijitBanerjee, David Cutler, Don Johnston, AlbertPark, Mark Pitt, Marguerite Robinson, ScottRozelle, Michael Woolcock, and seminar partici-pants at Brown University, HIID, and the OhioState University. Aimee Chin and Milissa Day provided excellent research assis tance. Part of the re-

search was funded by the Harvard Institute forInternational Development, and I appreciate thesupport of Jeffrey Sachs and David Bloom. I alsoappreciate the hospitality of the Bank Rakyat In-donesia in Jakarta in August 1996 and of Grameen,BRAC, and ASA staff in Bangladesh in the sum-mer of 1997. The paper was largely completedduring a year as a National Fellow at the HooverInstitution, Stanford University. The revision was completed with support from the Mac-Arthur Foundation. An earlier version of the pa-per was circulated under the title “The Microfi-nance Revolution.” The paper reflects my viewsonly.


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100 million poor households by 2005.As James Wolfensohn, the president of the World Bank, has been quick topoint out, helping 100 million house-holds means that as many as 500–600

million poor people could benefit. In-creasing activity in the United Statescan be expected as banks turn to mi-crofinance encouraged by new teethadded to the Community ReinvestmentAct of 1977 (Timothy O’Brien 1998).

The programs point to innovationslike “group-lending” contracts and new attitudes about subsidies as the keys totheir successes. Group-lending con-tracts effectively make a borrower’s

neighbors co-signers to loans, mitigat-ing problems created by informationalasymmetries between lender and bor-rower. Neighbors now have incentivesto monitor each other and to excluderisky borrowers from participation, pro-moting repayments even in the absenceof collateral requirements. The con-tracts have caught the attention of eco-nomic theorists, and they have broughtglobal recognition to the group-lending

model of Bangladesh’s Grameen Bank.2The lack of public discord is striking.

Microfinance appears to offer a “win- win” solution, where both financial in-stitutions and poor clients profit. Thefirst installment of a recent five-part se-ries in the San Francisco Examiner, forexample, begins with stories about four women helped by microfinance: a tex-tile distributor in Ahmedabad, India; a

street vendor in Cairo, Egypt; an artistin Albuquerque, New Mexico; and a

furniture maker in Northern California.The story continues:

From ancient slums and impoverished vil-lages in the developing world to the tired in-ner cities and frayed suburbs of America’seconomic fringes, these and millions of other women are all part of a revolution. Somemight call it a capitalist revolution . . . Aslittle as $25 or $50 in the developing world,perhaps $500 or $5000 in the United States,these microloans make huge differences inpeople’s lives . . . Many Third World bank-ers are finding that lending to the poor is not just a good thing to do but is also profitable.(Brill 1999)

Advocates who lean left highlight the“bottom-up” aspects, attention to com-

munity, focus on women, and, most im-portantly, the aim to help the under-served. It is no coincidence that the riseof microfinance parallels the rise of non-governmental organizations (NGOs) inpolicy circles and the newfound attentionto “social capital” by academics (e.g.,Robert Putnam 1993). Those who leanright highlight the prospect of alleviat-ing poverty while providing incentivesto work, the nongovernmental leadership,

the use of mechanisms disciplined by market forces, and the general suspicionof ongoing subsidization.

There are good reasons for excite-ment about the promise of microfi-nance, especially given the politicalcontext, but there are also good reasonsfor caution. Alleviating poverty throughbanking is an old idea with a checkeredpast. Poverty alleviation through theprovision of subsidized credit was a cen-terpiece of many countries’ develop-ment strategies from the early 1950sthrough the 1980s, but these experi-ences were nearly all disasters. Loan re-payment rates often dropped well below 50 percent; costs of subsidies ballooned;and much credit was diverted to the po-litically powerful, away from the in-tended recipients (Dale Adams, DouglasGraham, and J. D. von Pischke 1984).

2 Recent theoretical studies of microfinance in-clude Joseph Stiglitz 1990; Hal Varian 1990; Timo-thy Besley and Stephen Coate 1995; AbhijitBanerjee, Besley, and Timothy Guinnane 1992;Maitreesh Ghatak 1998; Mansoora Rashid andRobert Townsend 1993; Beatriz Armendariz deAghion and Morduch 1998; Armendariz and Chris-tian Gollier 1997; Margaret Madajewicz 1998;Aliou Diagne 1998; Bruce Wydick 1999; JonathanConning 1997; Edward S. Prescott 1997; and LoïcSadoulet 1997.

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What is new? Although very few pro-grams require collateral, the major new programs report loan repayment ratesthat are in almost all cases above 95percent. The programs have also proven

able to reach poor individuals, particu-larly women, that have been difficult toreach through alternative approaches.Nowhere is this more striking than inBangladesh, a predominantly Muslimcountry traditionally viewed as cultur-ally conservative and male-dominated.The programs there together serveclose to five million borrowers, the vastmajority of whom are women, and, inaddition to providing loans, some of the

programs also offer education on healthissues, gender roles, and legal rights.The new programs also break from thepast by eschewing heavy government involvement and by paying close attentionto the incentives that drive efficientperformance.

But things are happening fast—andgetting much faster. In 1997, a highprofile consortium of policymakers,charitable foundations, and practitioners

started a drive to raise over $20 billionfor microfinance start-ups in the next ten years (Microcredit Summit Report 1997 ).Most of those funds are being mobi-lized and channeled to new, untestedinstitutions, and existing resources arebeing reallocated from traditional pov-erty alleviation programs to microfi-nance. With donor funding pouring in,practitioners have limited incentives to

step back and question exactly how and where monies will be best spent.The evidence described below, how-

ever, suggests that the greatest promiseof microfinance is so far unmet, and theboldest claims do not withstand closescrutiny. High repayment rates haveseldom translated into profits as adver-tised. As Section 4 shows, most pro-grams continue to be subsidized di-rectly through grants and indirectly

through soft terms on loans from do-nors. Moreover, the programs that arebreaking even financially are not thosecelebrated for serving the poorest cli-ents. A recent survey shows that even

poverty-focused programs with a “com-mitment” to achieving financial sustain-ability cover only about 70 percent of their full costs (MicroBanking Bulletin1998). While many hope that weak fi-nancial performances will improve overtime, even established poverty-focusedprograms like the Grameen Bank wouldhave trouble making ends meet withoutongoing subsidies.

The continuing dependence on subsi-

dies has given donors a strong voice,but, ironically, they have used it topreach against ongoing subsidization.The fear of repeating past mistakes haspushed donors to argue that subsidiza-tion should be used only to cover start-up costs. But if money spent to supportmicrofinance helps to meet social objec-tives in ways not possible through alter-native programs like workfare or directfood aid, why not continue subsidizing

microfinance? Would the world be bet-ter off if programs like the GrameenBank were forced to shut their doors?

Answering the questions requiresstudies of social impacts and informa-tion on client profiles by income andoccupation. Those arguing from theanti-subsidy (“win-win”) position haveshown little interest in collecting thesedata, however. One defense is that, as-

suming that the “win-win” position iscorrect (i.e., that raising real interestrates to levels approaching 40 percentper year will not seriously underminethe depth of outreach), financial viabil-ity should be sufficient to show socialimpact. But the assertion is strong, andthe broader argument packs little punch without evidence to back it up.

Poverty-focused programs counterthat shifting all costs onto clients would

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likely undermine social objectives, butby the same token there is not yet di-rect evidence on this either. Anecdotesabound about dramatic social and eco-nomic impacts, but there have been few

impact evaluations with carefully cho-sen treatment and control groups (or with control groups of any sort), andthose that exist yield a mixed picture of impacts. Nor has there been much solidempirical work on the sensitivity of credit demand to the interest rate, noron the extent to which subsidized pro-grams generate externalities for non-borrowers. Part of the problem is thatthe programs themselves also have little

incentive to complete impact studies.Data collection efforts can be costly anddistracting, and results threaten to un-dermine the rhetorical strength of theanecdotal evidence.

The indirect evidence at least lendssupport to those wary of the anti-sub-sidy argument. Without better data, av-erage loan size is typically used to proxy for poverty levels (under the assump-tion that only poorer households will be

willing to take the smallest loans). Thetypical borrower from financially self-sufficient programs has a loan balanceof around $430—with loan sizes oftenmuch higher (MicroBanking Bulletin1998). In low-income countries, bor-rowers at that level tend to be amongthe “better off” poor or are even slightly above the poverty line. Expanding fi-nancial services in this way can foster

economic efficiency—and, perhaps,economic growth along the lines of Valerie Bencivenga and Bruce D. Smith(1991)—but it will do little directly toaffect the vast majority of poor house-holds. In contrast, Section 4.1 showsthat the typical client from (subsidized)programs focused sharply on poverty al-leviation has a loan balance close to just$100.

Important next steps are being taken

by practitioners and researchers whoare moving beyond the terms of early conversations (e.g., Gary Woller, Chris-topher Dunford, and Warner Wood- worth 1999). The promise of microfi-

nance was founded on innovation: new management structures, new contracts,and new attitudes. The leading pro-grams came about by trial and error.Once the mechanisms worked reason-ably well, standardization and replica-tion became top priorities, with contin-ued innovation only around the edges.As a result, most programs are not opti-mally designed nor necessarily offeringthe most desirable financial products.

While the group-lending contract is themost celebrated innovation in microfi-nance, all programs use a variety of other innovations that may well be asimportant, especially various forms of dynamic incentives and repaymentschedules. In this sense, economic the-ory on microfinance (which focusesnearly exclusively on group contracts) isalso ahead of the evidence. A portion of donor money would be well spent quan-

tifying the roles of these overlappingmechanisms and supporting efforts todetermine less expensive combinationsof mechanisms to serve poor clients in varying contexts. New managementstructures, like the stripped-down struc-ture of Bangladesh’s Association for So-cial Advancement, may allow sharp cost-cutting. New products, like the flexiblesavings plan of Bangladesh’s SafeSave,

may provide an alternative route to fi-nancial sustainability while helping poorhouseholds. The enduring lesson of mi-crofinance is that mechanisms matter:the full promise of microfinance canonly be realized by returning to theearly commitments to experimentation,innovation, and evaluation.

The next section describes leadingprograms. Section 3 considers theoret-ical perspectives. Section 4 turns to



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financial sustainability, and Section 5takes up issues surrounding the costs andbenefits of subsidization. Section 6 de-scribes econometric evaluations of im-pacts, and Section 7 turns from credit

to saving. The final section concludes with consideration of microfinancein the broader context of economicdevelopment.

2. New Approaches

Received wisdom has long been thatlending to poor households is doomedto failure: costs are too high, risks aretoo great, savings propensities are too

low, and few households have much toput up as collateral. Not long ago, thenorm was heavily subsidized credit provided by government banks with repay-ment rates of 70–80 percent at best. InBangladesh, for example, loans targetedto poor households by traditional bankshad repayment rates of 51.6 percent in1980. By 1988–89, a year of bad flood-ing, the repayment rate had fallen to18.8 percent (M. A. Khalily and Richard

Meyer 1993). Similarly, by 1986 repay-ment rates sank to 41 percent for subsi-dized credit delivered as part of India’shigh-profile Integrated Rural Develop-ment Program (Robert Pulley 1989).These programs offered heavily subsi-dized credit on the premise that poorhouseholds cannot afford to borrow athigh interest rates.

But the costs quickly mounted andthe programs soon bogged down gov-ernment budgets, giving little incentivefor banks to expand. Moreover, many bank managers were forced to reduceinterest rates on deposits in order tocompensate for the low rates on loans.In equilibrium, little in the way of sav-ings was collected, little credit was de-livered, and default rates accelerated asborrowers began to perceive that thebanks would not last long. The repeated

failures appeared to confirm suspicionsthat poor households are neither credit- worthy nor able to save much. More-over, subsidized credit was often diverted to politically-favored non-poor

households (Adams and von Pischke1992). Despite good intentions, many programs proved costly and did little tohelp the intended beneficiaries.

The experience of Bangladesh’s Gra-meen Bank turned this around, and now a broad range of financial institutionsoffer alternative microfinance models with varying philosophies and targetgroups. Other pioneers described below include BancoSol of Bolivia, the Bank

Rakyat Indonesia, the Bank Kredit Deasof Indonesia, and the village banksstarted by the Foundation for Interna-tional Community Assistance (FINCA).The programs below were chosen withan eye to illustrating the diversity of mechanisms in use, and Table 1 high-lights particular mechanisms. The func-tioning of the mechanisms is describedfurther in Section 3.3

2.1 The Grameen Bank, BangladeshThe idea for the Grameen Bank did

not come down from the academy, norfrom ideas that started in high-incomecountries and then spread broadly.4

3 Sections 4.1 and 5.1 describe summary statis-tics on a broad variety of programs. See also MariaOtero and Elisabeth Rhyne (1994); MicroBankingBulletin (1998); Ernst Brugger and Sarath Rajapa-tirana (1995); David Hulme and Paul Mosley (1996); and Elaine Edgcomb, Joyce Klein, and

Peggy Clark (1996).4 Part of the inspiration came from observingcredit cooperatives in Bangladesh, and, interest-ingly, these had European roots. The late nine-teenth century in Europe saw the blossoming of credit cooperatives designed to help low-incomehouseholds save and get credit. The cooperativesstarted by Frederick Raiffeisen grew to serve 1.4million in Germany by 1910, with replications inIreland and northern Italy (Guinnane 1994 and1997; Aidan Hollis and Arthur Sweetman 1997). Inthe 1880s the government of Madras in South In-dia, then under British rule, looked to the Germanexperiences for solutions in addressing poverty in



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Programs that have been set up inNorth Carolina, New York City, Chi-

cago, Boston, and Washington, D.C.cite Grameen as an inspiration. In addi-

tion, Grameen’s group lending modelhas been replicated in Bolivia, Chile,

China, Ethiopia, Honduras, India, Ma-laysia, Mali, the Philippines, Sri Lanka,

India. By 1912, over four hundred thousand poorIndians belonged to the new credit cooperatives,and by 1946 membership exceeded 9 million (R.Bedi 1992, cited in Michael Woolcock 1998). Thecooperatives took hold in the State of Bengal, theeastern part of which became East Pakistan at in-dependence in 1947 and is now Bangladesh. Inthe early 1900s, the credit cooperatives of Bengal were so wel l-known that Edward Filene, the Bos-

ton merchant whose department stores still bearhis name, spent time in India, learning about thecooperatives in order to later set up similar pro-grams in Boston, New York, and Providence(Shelly Tenenbaum 1993). The credit cooperativeseventually lost steam in Bangladesh, but the no-tion of group-lending had established itself and,after experimentation and modification, becameone basis for the Grameen model.

TABLE 1CHARACTERISTICS OF SELECTED LEADING MICROFINANCE PROGRAMS

GrameenBank,

Bangladesh

Banco-Sol,

Bolivia

BankRakyat

Indonesia

Unit Desa

BadanKreditDesa,

Indonesia

FINCA Village

banks2 million

borrowers;Membership 2.4 million 81,503 16 million 765,586 89,986

depositorsAverage loan balance $134 $909 $1007 $71 $191Typical loan term 1 year 4–12 3–24 3 months 4 months

months monthsPercent female members 95% 61% 23% — 95%Mostly rural? Urban? rural urban mostly rural mostly

rural ruralGroup-lending contracts? yes yes no no noCollateral required? no no yes no no Voluntary savings

emphasized? no yes yes no yesProgressive lending? yes yes yes yes yesRegular repayment

schedules weekly flexible flexible flexible weekly Target clients for lending poor largely non-poor poor poor

non-poorCurrently financially

sustainable? no yes yes yes noNominal interest rate on 20% 47.5– 32–43% 55% 36–48% loans (per year) 50.5%Annual consumer price

inflation, 1996 2.7% 12.4% 8.0% 8.0% —

Sources: Grameen Bank: through August 1998, www.grameen.com; loan size is from December 1996, calculatedby author. BancoSol: through December 1998, from Jean Steege, ACCION International, personal communica-tion. Interest rates include commission and are for loans denominated in bolivianos; base rates on dollar loansare 25–31%. BRI and BKD: through December 1994 (BKD) and December 1996 (BRI), from BRI annual dataand Don Johnston, personal communication. BRI interest rates are effective rates. FINCA: through July 1998, www.villagebanking.org. Inflation rate: World BankWorld Development Indicators 1998.



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Tanzania, Thailand, the U.S., and Viet-nam. When Bill Clinton was still gover-nor, it was Muhammad Yunus, founderof the Grameen Bank (and a Vander-bilt-trained economist), who was called

on to help set up the Good Faith Fundin Arkansas, one of the early microfi-nance organizations in the U.S. AsYunus (1995) describes the beginning:

Bangladesh had a terrible famine in 1974. I was teaching economics in a Bangladesh uni - ver sity at that time. You can guess how diff i-cult it is to teach the elegant theories of eco-nomics when people are dying of hunger allaround you. Those theories appeared likecruel jokes. I became a drop-out from formaleconomics. I wanted to learn economicsfrom the poor in the village next door to theuniversity campus.

Yunus found that most villagers wereunable to obtain credit at reasonablerates, so he began by lending themmoney from his own pocket, allowingthe villagers to buy materials for proj-ects like weaving bamboo stools andmaking pots ( New York Times 1997).Ten years later, Yunus had set up the

bank, drawing on lessons from informalfinancial institutions to lend exclusively to groups of poor households. Commonloan uses include rice processing,livestock raising, and traditional crafts.

The groups form voluntarily, and, while loans are made to individuals, allin the group are held responsible forloan repayment. The groups consist of five borrowers each, with lending firstto two, then to the next two, and thento the fifth. These groups of five meettogether weekly with seven othergroups, so that bank staff meet withforty clients at a time. According to therules, if one member ever defaults, allin the group are denied subsequentloans. The contracts take advantage of local information and the “social assets”that are at the heart of local enforce-ment mechanisms. Those mechanisms

rely on informal insurance relationshipsand threats, ranging from social isola-tion to physical retribution, that facili-tate borrowing for households lackingcollateral (Besley and Coate 1995). The

programs thus combine the scale advan-tages of a standard bank with mecha-nisms long used in traditional, group-based modes of informal finance, suchas rotating savings and credit associa-tions (Besley, Coate, and Glenn Loury 1993).5

The Grameen Bank now has over twomillion borrowers, 95 percent of whomare women, receiving loans that total$30–40 million per month. Reported re-

cent repayment rates average 97–98percent, but as Section 4.2 describes,relevant rates average about 92 percentand have been substantially lower inrecent years.

Most loans are for one year with anominal interest rate of 20 percent(roughly a 15–16 percent real rate).Calculations described in Section 4.2suggest, however, that Grameen wouldhave had to charge a nominal rate of

around 32 percent in order to becomefully financially sustainable (holding thecurrent cost structure constant). Themanagement argues that such an in-crease would undermine the bank’s so-cial mission (Shahidur Khandker 1998),

5 In a rotating savings and credit association, agroup of participants puts contributions into a potthat is given to a single member. This is repeatedover time until each member has had a turn, with

order determined by list, lottery, or auction. Mostmicrofinance contracts build on the use of groupsbut mobilize capital from outside the area.ROSCA participants are often women, and in theU.S. involvement is active in new immigrant com-munities, including among Koreans, Vietnamese,Mexicans, Salvadorans, Guatemalans, Trinidadi-ans, Jamaicans, Barbadans, and Ethiopians. In- volvement had been act ive ear lier in the century among Japanese and Chinese Americans, but itis not common now (Light and Pham 1998).Rutherford (1998) and Armendariz and Morduch(1998) describe links of ROSCAs and microfinancemechanisms.



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but there is little solid evidence thatspeaks to the issue.

Grameen figures prominently as anearly innovator in microfinance and hasbeen particularly well studied. Assess-

ments of its financial performance aredescribed below in Section 4.2, of itscosts and benefits in Section 5.1, andof its social and economic impacts inSection 6.3.

2.2 BancoSol, Bolivia

Banco Solidario (BancoSol) of urbanBolivia also lends to groups but differsin many ways from Grameen.6 First, its

focus is sharply on banking, not on so-cial service. Second, loans are made toall group members simultaneously, andthe “solidarity groups” can be formed of three to seven members. The bank,though, is constantly evolving, and ithas started lending to individuals as well . By the end of 1998, 92 percent of the portfolio was in loans made to soli-darity groups and 98 percent of clients were in solidarity groups, but it is likely that those ratios will fall over time. By the end of 1998, 28 percent of the port-folio had some kind of guarantee beyond just a solidarity group.

Third, interest rates are relatively high. While 1998 inflation was below 5percent, loans denominated in bolivi-anos were made at an annual base rateof 48 percent, plus a 2.5 percent com-mission charged up front. Clients with

solid performance records are offeredloans at 45 percent per year, but this isstill steep relative to Grameen (but notrelative to the typical moneylender, who may charge as much as 10 percentper month). About 70–80 percent of

loans are denominated in dollars, how-ever, and these loans cost clients 24–30percent per year, with a 1 percent feeup front.

Fourth, as a result of these rates, the

bank does not rely on subsidies, mak-ing a respectable return on lending.BancoSol reports returns on equity of nearly 30 percent at the end of 1998and returns on assets of about 4.5 per-cent, figures that are impressive relativeto Wall Street investments—althoughadjustments for risk will alter the pic-ture. Fifth, repayment schedules areflexible, allowing some borrowers tomake weekly repayments and others to

do so only monthly. Sixth, loan dura-tions are also flexible. At the end of 1998, about 10 percent had durationsbetween one and four months, 24 per-cent had durations of four to sevenmonths, 23 percent had durations of seven to ten months, 19 percent haddurations of ten to thirteen months,and the balance stretched toward two years.

Seventh, borrowers are better off

than in Bangladesh and loans are larger, with average loan balances exceeding$900, roughly nine times larger than forGrameen (although first loans may startas low as $100). Thus while BancoSolserves poor clients, a recent study findsthat typical clients are among the “rich-est of the poor” and are clustered justabove the poverty line (where poverty is based on access to a set of basic

needs like shelter and education; SergioNavajas et al. 1998). Partly this may bedue to the “maturation” of clients frompoor borrowers into less poor borrow-ers, but the profile of clients also looks very different from that of the ma-ture clients of typical South Asianprograms.

The stress on the financial side hasmade BancoSol one of the key forcesin the Bolivian banking system. The

6 The financial information is from Jean Steege,ACCION International, personal communication,January 1999. Claudio Gonzalez-Vega et al. (1997)provide more detail on BancoSol. Further infor-mation can also be found at http://www.accion.org.



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institution started as an NGO(PRODEM) in 1987, became a bank in1992, and, by the end of 1998, served81,503 low-income clients. That scalegives it about 40 percent of borrowers

in the entire Bolivian banking system.Part of the success is due to impres-sive repayment performance, althoughdifficulties are beginning to emerge.Unlike most other microfinance institu-tions, BancoSol reports overdues usingconservative standards: if a loan repay-ment is overdue for one day, the entireunpaid balance is considered at risk(even when the planned payment wasonly scheduled to be a partial repay-

ment). By these standards, 2.03 percentof the portfolio was at risk at the end of 1997. But by the end of 1998, the frac-tion increased to 4.89 percent, a trendthat parallels a general weakeningthroughout the Bolivian banking systemand which may signal the negativeeffects of increasing competition.BancoSol’s successes have spawnedcompetition from NGOs, new nonbankfinancial institutions, and even formal

banks with new loan windows for low-income clients. The effect has been arapid increase in credit supply, and a weakening of repayment incentives thatmay foreshadow problems to comeelsewhere (see Section 3.3).

Still, BancoSol stands as a financialsuccess, and the model has been repli-cated—profitably—by nine of the eigh-teen other Latin American affiliates of

ACCION International, an NGO basedin Somerville, Massachusetts. ACCIONalso serves over one thousand clients inthe U.S., spread over the six programs.Average loan sizes range from $1366 inNew Mexico to $3883 in Chicago, andoverall nearly 40 percent of the clientsare female. As of December 1996, pay-ments past due by at least thirty daysaveraged 15.5 percent but ranged ashigh as 21.2 percent in New York and

32.3 percent in New Mexico.7 ACCION’sother affiliates, including six in the UnitedStates, have not, however, achieved fi-nancial sustainability. The largest im-pediments for U.S. programs appear to

be a mixed record of repayment, andusury laws that prevent microfinance in-stitutions from charging interest ratesthat cover costs (Pham 1996).

2.3 Rakyat Indonesia

Like BancoSol, the Bank Rakyat In-donesia unit desa system is financially self-sufficient and also lends to “betteroff” poor and nonpoor households, withaverage loan sizes of $1007 during

1996. Unlike BancoSol and Grameen,however, BRI does not use a grouplending mechanism. And, unlike nearly all other programs, the bank requiresindividual borrowers to put up collat-eral, so the very poorest borrowers areexcluded, but operations remain small-scale and “collateral” is often definedloosely, allowing staff some discretion toincrease loan size for reliable borrowers who may not be able to fully back loans

with assets. Even in the wake of the re-cent financial crisis in Indonesia, repay-ment rates for BRI were 97.8 percent inMarch 1998 (Paul McGuire 1998).

The bank has centered on achievingcost reductions by setting up a network

7 Data are from ACCION (1997) and hold as of December 1996. Five of the six U.S. affiliates haveonly been operating since 1994, and the group as a whole serves only 1,695 clients (but with capitalsecured for expansion). A range of microfinance

institutions operate in the U.S. Among the oldestand best-established are Chicago’s South ShoreBank and Boston’s Working Capital. The Cal-Meadow Foundation has recently provided fund-ing for several microfinance programs in Canada.Microfinance participation in the U.S. is heavily minority-based, with a high ethnic concentration.For example, 90 percent of the urban clients of Boston’s Working Capital are minorities (and 66percent are female). Loans start at $500. Clientstend to be better educated and have more job ex-perience than average welfare recipients, and just29 percent of Working Capital’s borrowers werebelow the poverty line (Working Capital 1997).



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of branches and posts (with an averageof five staff members each) and now serves about 2 million borrowers and 16million depositors. (The importance of savings to BRI is highlighted below in

Section 7.) Loan officers get to know clients over time, starting borrowers off with small loans and increasing loansize conditional on repayment perfor-mance. Annualized interest rates are 34percent in general and 24 percent if loans are paid with no delay (roughly 25percent and 15 percent in real terms—before the recent financial crisis).

Like BancoSol, BRI also does not seeitself as a social service organization,

and it does not provide clients withtraining or guidance—it aims to earn aprofit and sees microfinance as goodbusiness (Marguerite Robinson 1992).Indeed, in 1995, the unit desa programof the Bank Rakyat Indonesia earned$175 million in profits on their loans tolow-income households. More striking,the program’s repayment rates—andprofits—on loans to poor householdshave exceeded the performance of loans

made to corporate clients by other partsof the bank. A recent calculation sug-gests that if the BRI unit desa programdid not have to cross-subsidize the restof the bank, they could have brokeneven in 1995 while charging a nominalinterest rate of just 17.5 percent per year on loans (around a 7 percent realrate; Jacob Yaron, McDonald Benjamin,and Stephanie Charitonenko 1998).

2.4 Kredit Desa, IndonesiaThe Bank Kredit Desa system

(BKDs) in rural Indonesia, a sister insti-tution to BRI, is much less well-known.The program dates back to 1929, al-though much of the capital was wipedout by the hyper-inflation of the middle1960s (Don Johnston 1996). Like BRI,loans are made to individuals and theoperation is financially viable. At the end

of 1994, the BKDs generated profits of $4.73 million on $30 million of net loansoutstanding to 765,586 borrowers.8

Like Grameen-style programs, theBKDs lend to the poorest households,

and scale is small, with an emphasis onpetty traders and an average loan size of $71 in 1994. The term of loans is gener-ally 10–12 weeks with weekly repay-ment and interest of 10 percent on theprincipal. Christen et al. (1995) calcu-late that this translates to a 55 percentnominal annual rate and a 46 percentreal rate in 1993. Loan losses in 1994 were just under 4 percent of loansoutstanding (Johnston 1996).

Also as in most microfinance programs,loans do not require collateral. The in-novation of the BKDs is to allocatefunds through village-level managementcommissions led by village heads. This works in Indonesia since there is a clearsystem of authority that stretches fromJakarta down to the villages. The BKDspiggy-back on this structure, and themanagement commissions thus build inmany of the advantages of group lend-

ing (most importantly, exploiting localinformation and enforcement mecha-nisms) while retaining an individual-lending approach. The commissions areable to exclude the worst credit risksbut appear to be relatively democraticin their allocations. Through the late1990s, most BKDs have had excesscapital for lending and hold balances inBRI accounts. The BKDs are now su-

pervised by BRI, and successful BKDborrowers can graduate naturally tolarger-scale lending from BRI units.

2.5 Village Banks

Prospects for replicating the BKDsoutside of Indonesia are limited, how-ever. A more promising, exportable

8 Figures are calculated from Johnston (1996)and data provided by BRI in August 1996.



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village-based structure is provided by the network of village banks started inthe mid-1980s in Latin America by John Hatch and his associates at theFoundation for International Commu-

nity Assistance (FINCA). The villagebanking model has now been replicatedin over 3000 sites in 25 countries by NGOs like CARE, Catholic Relief Ser- vices, Freedom from Hunger, and Savethe Children. FINCA programs aloneserve nearly 90,000 clients in countriesas diverse as Peru, Haiti, Malawi,Uganda, and Kyrgyzstan, as well as inMaryland, Virginia, and Washington,D.C.

The NGOs help set up village finan-cial institutions in partnership with lo-cal groups, allowing substantial localautonomy over loan decisions and man-agement. Freedom from Hunger, forexample, then facilitates a relationshipbetween the village banks and local com-mercial banks with the aim to createsustainable institutional structures.

The village banks tend to serve apoor, predominantly female clientele

similar to that served by the GrameenBank. In the standard model, the spon-soring agency makes an initial loan tothe village bank and its 30–50 members.Loans are then made to members, start-ing at around $50 with a four monthterm, with subsequent loan sizes tied tothe amount that members have on de-posit with the bank (they must typically have saved at least 20 percent of the

loan value). The initial loan from thesponsoring agency is kept in an “exter-nal account,” and interest income isused to cover costs. The deposits of members are held in an “internal ac-count” that can be drawn down as de-positors need. The original aim was tobuild up internal accounts so that exter-nal funding could be withdrawn withinthree years, but in practice growingcredit demands and slow savings accu-

mulation have limited those aspirations(Candace Nelson et al. 1995).

Like the Indonesian BKDs, the vil-lage banks successfully harness local in-formation and peer pressure without us-

ing small groups along BancoSol orGrameen lines. And, as with the BKDs,sustainability is an aim, with nominal in-terest rates as high as 4 percent permonth. Most village banks, however,still require substantial subsidies tocover capital costs. Section 4.1 showsevidence that village banks as a groupcover just 70 percent of total costs onaverage. Partly, this is because many vil-lage banks have been set up in areas

that are particularly difficult to serve(e.g., rural Mali and Burkina Faso), andthe focus has been on outreach ratherthan scale. Worldwide, the number of clients is measured in the tens of thou-sands, rather than the millions servedby the Grameen Bank and BRI.

3. Microfinance Mechanisms

The five programs above highlight

the diversity of approaches spawned by the common idea of lending to low-income households. Group lending hastaken most of the spotlight, and theidea has had immediate appeal for eco-nomic theorists and for policymakers with a vision of building programsaround households’ “social” assets, even when physical assets are few. But itsrole has been exaggerated: group lend-ing is not the only mechanism that dif-

ferentiates microfinance contracts fromstandard loan contracts.9 The programsdescribed above also use dynamic in-centives, regular repayment schedules,and collateral substitutes to help main-tain high repayment rates. Lending to

9 Ghatak and Guinnane (1999) provide an excel-lent review of group-lending contracts. MonicaHuppi and Gershon Feder (1990) provide an early perspective. Armendariz and Morduch (1998) de-scribe the functioning of alternative mechanisms.



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women can also be a benefit from afinancial perspective.

As shown in Table 1, just two of thefive use explicit group-lending con-tracts, but all lend in increasing

amounts over time (“progressive” lend-ing), offer terms that are substantially better than alternative credit sources,and cut off borrowers in default. Mostalso require weekly or semi-weekly re-payments, beginning soon after loan re-ceipt. While we lack good evidence onthe relative importance of these mecha-nisms, there is increasing anecdotal evi-dence on limits to group lending per se(e.g., the village studies from Bangla-

desh in Aminur Rahman 1998; ImranMatin 1997; Woolcock 1999; Sanae Ito1998; and Pankaj Jain 1996). This sec-tion highlights what is known (or oughtto be known) about the diversity of technologies that underlie repaymentrates and screening mechanisms.

3.1 Peer Selection

Group lending has many advantages,

beginning with mitigation of problemscreated by adverse selection. The key isthat group-lending schemes provide in-centives for similar types to group to-gether. Ghatak (1999) shows how thissorting process can be instrumental inimproving repayment rates, allowing forlower interest rates, and raising social welfare. His insight is that a group-lending contract provides a way to pricediscriminate that is impossible with an

individual-lending contract.10To see this, imagine two types of po-

tential investors. Both types are riskneutral, but one type is “risky” and theother is “safe”; the risky type fails moreoften than the safe type, but the risky types have higher returns when success-ful. The bank knows the fraction of

each type in the population, but it isunable to determine which specific investors are of which type. Investors,though, have perfect information abouteach other.

Both types want to invest in a project with an uncertain outcome that requiresone unit of capital. If they choose not toundertake the project, they can earn wage income m. The risky investors havea probability of success pr and net re-turn Rr . The safe investors have a prob-ability of success p s and net return R s. When either type fails, the return is zero.Returns are statistically independent.

Risky types are less likely to be suc-

cessful ( pr m.Neither type has assets to put up as

collateral, so the investors pay the bank

nothing if the projects fail. To breakeven, the bank must set the interestrate high enough to cover its per-loancapital cost, ρ. If both types borrow, theequilibrium interest rate under compe-tition will then be set so that rp– = ρ, where p– is the average probability of success in the population. Since thebank can’t distinguish between borrow-ers, all investors will face interest rate,

r . As a result, safe types have lower ex-pected returns than risky types—sinceR __

− rp s m. If the safe types enter,

the risky types will too.But the safe types will stay out of the

market if R __

− rp s


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will rise so that rpr = ρ. Risky types driveout the safe. The risky types lose theimplicit cross-subsidization by the safetypes, while the safe types lose access tocapital. This second-best scenario is in-

efficient since only the risky types bor-row, even though the safe types alsohave socially valuable projects.

Can a group-lending scheme improveon this outcome? If it does, it mustbring the safe types back into the mar-ket. For simplicity, consider groups of two people, with each group formed voluntarily. Individuals invest indepen-dently, but the contract is written tocreate joint liability. Imagine a contract

such that each borrower pays nothing if her project fails, and an amount r ∗ if her project is successful. In addition,the successful borrower pays a joint-liability payment c∗ if the other mem-ber of the group fails.11 The expectednet return of a safe type teamed with arisky type is then R

__ − p s(r ∗ + (1 − pr )c∗),

with similar calculations for exclusively safe and exclusively risky groups.

Will the groups be homogeneous or

mixed? Since safe types are always pre-ferred as partners (since their prob-ability of failure is lower), the questionbecomes: will the risky types be willingto make a large enough transfer to thesafe types such that both risky and safetypes do better together? By comparingexpected returns under alternative sce-narios, we can calculate that a safe type will require a transfer of at least p

s( p s −

pr )c∗

to agree to form a partner-ship with a risky type. Will risky typesbe willing to pay that much? Their ex-

pected net gain from joining with a safetype is as much as pr ( p s − pr )c∗. But since pr 1.4r ∗.

Efficiency gains result if the differenceis large enough to induce the safe typesback into the market. When this hap-pens, average repayment rates rise, andthe bank can afford to maintain a lowerinterest rate r ∗ while not losing money.

11 In typical contracts, group members are re-sponsible for helping to pay off the loan in diffi-culty, rather than having to pay a fixed penalty fora group member’s default. While clients lack col-lateral, they are assumed to have a large enoughincome flow to cover these costs if needed. Inpractice this may impose a constraint on loan sizesince individuals may have increasing difficulty paying c∗ + r ∗ when loan sizes grow large.

12 Ghatak (1998) extends the results to groupslarger than 2, a continuum of types, and prefer-ences against risk. See also Varian (1990) and Ar-mendariz and Gollier (1997) on related issues of efficiency and sorting.



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3.2 Peer Monitoring

Group lending may also providebenefits by inducing borrowers not totake risks that undermine the bank’s

profitability (Stiglitz 1990; Besley andCoate 1995). This can be seen by slightly modifying the framework inSection 3.1 to consider moral hazard.Instead, consider identical risk averseborrowers with utility functions u( x).

Each borrower may do either risky orsafe activities, and each activity againrequires the same capital cost. Thebank, as above, has imperfect informa-tion about borrowers—in particular,

here it cannot tell whether the borrow-ers have done the safe or risky activity.Moral hazard is thus a prime concern. When projects fail , borrowers have a re-turn of zero, and a borrower’s utility level when projects fail is normalized tozero as well.

We start with the standard individual-lending contract. Borrowers either haveexpected utility p s u(R s − r ) or pr u(Rr − r ),depending on whether they do the safe

or risky activity. If everyone did thesafe activity, the bank could charge aninterest rate of r = ρ /p s and break even.But, since the bank cannot see whichactivity is chosen (and thus cannot con-tract on it), borrowers may fare betterdoing the risky activity and getting ex-pected utility E[U sr ] = pr u(Rr − ρ /p s). Thebank then loses money. Thus, the bankraises interest rates to r = ρ / pr . Now theborrower gets expected utility of E[U rr ] = pr u(Rr − ρ /pr ), and she is clearly worse off than with a lower interestrate. In fact, if the borrower couldsomehow commit to doing the safe ac-tivity, she could be better off—with ex-pected utility E[U ss] = p s u(R s − ρ /p s). Thusthe borrower prefers E[U sr ] to E[U ss] toE[U rr ], but the information problemand inability to commit means that shealways gets the worst outcome, E[U rr ].

How can a group-lending contractimprove matters? The key is that it cancreate a mechanism that gives borrow-ers an incentive to choose the safe ac-tivity. Again consider groups of two bor-

rowers and group-lending contracts likethose in Section 3.1 above. The borrow-ers in each group have the ability toenforce contracts between each other,and they jointly decide which typesof activities to undertake. Now theirproblem is to choose between both do-ing the safe activity, yielding each bor-rower expected utility of p s2 u(R s − r ∗) + p s(1 − p s) u(R s − r ∗ − c∗), or doing therisky activity with expected utility

pr 2 u(Rr − r ∗) + pr (1 − pr ) u(Rr − r ∗ − c∗). If the joint-liability payment c∗ is set highenough, borrowers will always choose todo the safe activity (Stiglitz 1990).

This is good for the bank, but it sad-dles borrowers with extra risk. Thebank, though, knows borrowers will now do the safe activity, and it earns extraincome from the joint-liability pay-ments. The bank can thus afford tolower the interest rate to offset the

burden.Thus, through exploiting the ability

of neighbors to enforce contracts andmonitor each other—even when thebank can do neither—the group-lendingcontract again offers a way to lowerequilibrium interest rates, raise expectedutility, and raise expected repaymentrates.

3.3 Dynamic Incentives

A third mechanism for securing highrepayment rates with high monitoringcosts involves exploiting dynamic incen-tives (Besley 1995, p. 2187). Programstypically begin by lending just smallamounts and then increasing loan sizeupon satisfactory repayment. The re-peated nature of the interactions—andthe credible threat to cut off any futurelending when loans are not repaid—can



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be exploited to overcome informationproblems and improve efficiency, whether lending is group-based orindividual-based.13

Incentives are enhanced further if

borrowers can anticipate a stream of in-creasingly larger loans. (Hulme andMosley 1996 term this “progressivelending,” and the ACCION networkcalls it “step lending.”) As above, keep-ing interest rates relatively low is criti-cal, since the advantage of microfinanceprograms lies in their offering servicesat rates that are more attractive thancompetitors’ rates. Thus, the Bank Rak- yat Indonesia (BRI) and BancoSol

charge high rates, but they keep levels well below rates that moneylenderstraditionally charge.

However, competition will diminishthe power of the dynamic incentivesagainst moral hazard—a problem thatboth the Bank Rakyat Indonesia andBancoSol are starting to feel as othercommercial banks see the potentialprofitability of their model. In practice,though, real competition has yet to be

felt by most microfinance institutions(perhaps because so few are actually turning a profit). As competition grows,the need for a centralized credit ratingagency will also grow.

Dynamic incentives will also workbetter in areas with relatively low mo-bility. In urban areas, for example, where households come and go, it may not be easy to catch defaulters who

move across town and start borrowingagain with a clean slate at a differentbranch or program. BRI has facedgreater trouble securing repayments intheir urban programs than in their ruralones, which may be due to greaterurban mobility.

Relying on dynamic incentives alsoruns into problems common to all finiterepeated games. If the lending relation-ship has a clear end, borrowers have in-centives to default in the final period.

Anticipating that, the lender will notlend in the final period, giving borrow-ers incentives to default in the penulti-mate period—and so forth until the en-tire mechanism unravels. Thus, unlessthere is substantial uncertainty aboutthe end date—or if “graduation” from oneprogram to the next is well-established(ad infinitum), dynamic incentives havelimited scope on their own.

One quite different advantage of pro-

gressive lending is the ability to testborrowers with small loans at the start.This feature allows lenders to developrelationships with clients over time andto screen out the worst prospects beforeexpanding loan scale (Parikshit Ghoshand Debraj Ray 1997).

Dynamic incentives can also help toexplain advantages found in lending to women. Credit programs like those of the Grameen Bank and the Bangladesh

Rural Advancement Committee (BRAC)did not begin with a focus on women.In 1980–83, women made up 39 percentand 34 percent of their respective mem-berships, but by 1991–92, BRAC’smembership was 74 percent female andGrameen’s was 94 percent female (AnneMarie Goetz and Rina Sen Gupta 1995).As Table 2 shows, many other programsalso focus on lending to women, and it

appears to confer financial advantageson the programs. At Grameen, for ex-ample, 15.3 percent of male borrowers were “struggling” in 1991 (i.e., missingsome payments before the final duedate) while this was true for just 1.3percent of women (Khandker, BaquiKhalily, and Zahed Kahn 1995).

The decision to focus on women hassome obvious advantages. The lowermobility of women may be a plus where

13 See the general theoretical treatment in Bol-ton and Scharfstein (1990) and the application tomicrofinance contracts in Armendariz and Mor-duch (1998).



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ex post moral hazard is a problem (i.e., where there is a fear that clients will“take the money and run”). Also, where

women have fewer alternative borrow-ing possibilities than men, dynamicincentives will be heightened.14

Thus, ironically, the financial successof many programs with a focus on women may spring partly from the lackof economic access of women, while, atthe same time, promotion of economicaccess is a principal social objective(Syed Hashemi, Sidney Ruth Schuler,and Ann P. Riley 1996).

3.4 Regular Repayment Schedules

One of the least remarked upon—butmost unusual—features of most microfi-

nance credit contracts is that repay-ments must start nearly immediately af-ter disbursement. In a traditional loancontract, the borrower gets the money,invests it, and then repays in full withinterest at the end of the term. But atGrameen-style banks, terms for a year-long loan are likely to be determined by adding up the principal and interest duein total, dividing by 50, and starting weekly collections a couple of weeks af-ter the disbursement. Programs likeBancoSol and BRI tend to be more flex-ible in the formula, but even they donot stray far from the idea of collectingregular repayments in small amounts.

The advantages are several. Regularrepayment schedules screen out undis-ciplined borrowers. They give early warning to loan officers and peer groupmembers about emerging problems.

TABLE 2PERFORMANCE INDICATORS OF MICROFINANCE PROGRAMS

ObservationsAverage loanbalance ($)

Avg. loan as% of GNPper capita

Averageoperational

sustainability

Averagefinancial

sustainability

Sustainability All microfinance institutions 72 415 34 105 83 Fully sustainable 34 428 39 139 113 Lending method Individual lending 30 842 76 120 92 Solidarity groups 20 451 35 103 89 Village bank 22 94 11 91 69Target Group Low end 37 133 13 88 72 Broad 28 564 48 122 100 High end 7 2971 359 121 76 Age

3 to 6 years 15 301 44 98 84 7 or more years 40 374 27 123 98

Source: Statistical appendix to MicroBanking Bulletin (1998). Village banks have a “B” data quality; all others aregraded “A”. Portfolio at risk is the amount in arrears for 90 days or more as a percentage of the loan portfolio.Averages exclude data for the top and bottom deciles.

14 Rahman (1998) describes complementary cul-tural forces based on women’s “culturally pat-terned behavior.” Female Grameen Bank borrow-ers in Rahman’s study area, for example, are foundto be much more sensitive to verbal hostility heaped on by fellow members and bank workers when repayment dif ficulties arise . The stigma isexacerbated by the public collection of paymentsat weekly group meetings. According to Rahman(1998), women are especially sensitive since theirmisfortune reflects poorly on the entire household(and lineage), while men have an easier time shak-ing it off.



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And they allow the bank to get hold of cash flows before they are consumed orotherwise diverted, a point developedby Stuart Rutherford (1998).

More striking, because the repaymentprocess begins before investments bearfruit, weekly repayments necessitatethat the household has an additional in-come source on which to rely. Thus, in-sisting on weekly repayments meansthat the bank is effectively lendingpartly against the household’s steady,diversified income stream, not just therisky project. This confers advantagesfor the bank and for diversified house-holds. But it means that microfinancehas yet to make real inroads in areas fo-cused sharply on highly seasonal occu-pations like agricultural cultivation.Seasonality thus poses one of the largestchallenges to the spread of microfi-nance in areas centered on rainfedagriculture, areas that include some of the poorest regions of South Asia andAfrica.

3.5 Collateral Substitutes

While few programs require collat-eral, many have substitutes. For exam-

ple, programs following the Grameenmodel require that borrowers contrib-ute to an “emergency fund” in theamount of 0.5 percent of every unit bor-rowed (beyond a given scale). Theemergency fund provides insurance incases of default, death, disability, etc.,in amounts proportional to the length of membership. An additional 5 percent of the loan is taken out as a “group tax”that goes into a group fund account. Upto half of the fund can be used by groupmembers (with unanimous consent).Typically, it is disbursed among thegroup as zero-interest loans with fixedterms. Until October 1995, GrameenBank members could not withdraw these funds from the bank, even uponleaving. These “forced savings” can now be withdrawn upon leaving, but only af-ter the banks have taken out what they

TABLE 2 (Cont.)

Avg. returnon equity

Avg. percent of portfolio at risk

Avg. percentfemale clients

Avg. number of active borrowers

Sustainability All microfinance institutions –8.5 3.3 65 9,035 Fully sustainable 9.3 2.6 61 12,926 Lending method Individual lending –5.0 3.1 53 15,226 Solidarity groups –3.0 4.1 49 7,252 Village bank –17.4 2.8 92 7,833Target Group Low end –16.2 3.8 74 7,953 Broad 1.2 3.0 60 12,282 High end –6.2 1.9 34 1,891 Age

3 to 6 years –6.8 2.2 71 9,921 7 or more years –2.4 4.1 63 16,557



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are owed. Thus, in effect, the fundsserve as a form of partial collateral.

The Bank Rakyat Indonesia’s unitdesa program is one of the few pro-grams to require collateral explicitly. Its

advocates, however, emphasize insteadthe role of dynamic incentives in gener-ating repayments (Richard Patten andJay Rosengard 1991; Robinson 1992). Itis impossible, though, to determine eas-ily which incentive mechanism is mostimportant in driving repayment rates. While bank officials point out that col-lateral is almost never collected, thisdoes not signal its lack of importance asan incentive device. If the threat of col-

lection is believable, there should befew instances when collateral is actually collected.

BancoSol also stresses the role of solidarity groups in assuring repay-ments, but as its clients have prosperedat varying rates, lending approacheshave diversified as well. As noted inSection 2.2, by the end of 1998, 28 per-cent of its portfolio had some kind of guarantee beyond the solidarity group.

3.6 Empirical Research Agenda

Do the mechanisms above function asadvertised? Is there evidence of assorta-tive matching through group lending aspostulated by Ghatak (1999)? Are fu-ture loan terms predicted by laggedperformance, as suggested by the the-ory of dynamic incentives? Extendingthe theory further, does the group-lend-

ing contract heighten default prob-abilities for the entire group when somemembers run into difficulties, as pre-dicted by Besley and Coate (1995)?Does group lending lead to excessivemonitoring and excessive pressure toundertake “safe” projects rather thanriskier and more lucrative projects(Banerjee, Besley, and Guinnane1992)? Is the group-lending structureless flexible than individual lending for

borrowers in growing businesses andthose that outstrip the pace of theirpeers (Madajewicz 1997; Woolcock1998)? Are weekly meetings particularly costly (for both borrowers and bank

staff) in areas of low population density and at busy agricultural seasons? Do so-cial programs enhance economic perfor-mance? When default occurs, do bankstaff follow the letter of the law and cutoff good clients with the misfortune tobe in groups with unlucky neighbors?Or is renegotiation common (Hashemiand Sidney Schuler 1997; Matin 1997;Armendariz and Morduch 1998)?

Most of the theoretical propositions

are supported with anecdotes from par-ticular programs, but they have notbeen established as empirical regulari-ties. Better research is needed to sharpenboth the growing body of microfinancetheory and ongoing policy dialogues.

Empirical understandings of microfi-nance will also be aided by studies thatquantify the roles of the various mecha-nisms in driving microfinance perfor-mance. The difficulty in these inquiries is

that most programs use the same lend-ing model in all branches. Thus, there isno variation off of which to estimate theefficacy of particular mechanisms. Well-designed experiments would help (e.g.,individual-lending contracts to some of the sample, group-lending contracts toothers; weekly repayments for some,monthly or quarterly schedules for others).

Lacking well-designed experiments, a

collection of studies instead presentsregressions in which repayment ratesare explained by proxies for forces be-hind particular mechanisms. The vari-ation thus arises from features of theeconomic environment that affect theefficacy of particular program features:How good are information flows? How competitive are credit markets? How strong are informal enforcement mech-anisms? The variation in answers to



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these questions allows econometric esti-mation, but the evidence is indirect andsubject to multiple interpretations sincethe strength of information flows, mar-kets, and enforcement mechanisms is

unlikely to matter only through theform of credit contract. In addition, se-lection biases of the sort raised in Sec-tion 6.1 are likely to apply. Still, someresults are provocative.

For example, Wydick (1999) reportson a survey of an ACCION Interna-tional affiliate in western Guatemalatailored to elicit information aboutgroups. He finds that improvements inrepayment rates are associated with

variables that proxy for the abil ity tomonitor and enforce group relation-ships, such as knowledge of the weekly sales of fellow group members. Hefinds little impact, though, of social ties per se : friends do not make more reli-able group members than others. In fact,members are sometimes softer on theirfriends, worsening average repaymentrates.

Mark Wenner (1995) investigates re-

payment rates in 25 village banks inCosta Rica affiliated with FINCA. Hefinds active screening that successfully excludes the worst credit risks, workingin a more straightforward way than inthe simple model of peer selection inSection 3.1 above. He also finds thatdelinquency rates are higher in betteroff towns. This lends support to the the-ory of dynamic incentives: where bor-

rowers have better alternatives, they arelikely to value the programs less, andthis drives up default rates.

The result is echoed by ManoharSharma and Manfred Zeller (1996) in theirstudy of three programs in Bangladesh(but not Grameen). They find that re-payment rates are higher in remotecommunities—i.e., those with fewer al-ternative credit programs. Khandker etal. (1995, Table 7.2), however, find the

opposite in considering other Bangla-desh banks (including Grameen). Bothdrop-out rates and repayment rates in-crease in better-developed villages.This may be a product of improved li-

quidity and better business opportuni-ties in better-off villages, but it mightalso reflect selection bias.

These bits of evidence show thatgroup lending is a varied enterprise andthat there is much to microfinance beyond group lending. Narrowing the gapbetween theory and evidence will be animportant step toward improving andevaluating programs.

4. Profitability and FinancialSustainability

Microfinance discussions pay surpris-ingly little attention to particular mech-anisms relative to how much attentionis paid to purely financial matters. Ac-cordingly, this section considers fi-nances, and social issues are taken upagain in Section 5.

How well in the end have microfi-

nance programs met their financialpromise? A recent survey finds 34 prof-itable programs among a group of 72 with a “commitment” to financial sus-tainability (MicroBanking Bulletin1998). This does not imply, however,that half of all programs worldwide areself-sufficient. The hundreds of pro-grams outside the base 72 continue todepend on the generosity of donors(e.g., Grameen Bank and most of itsreplicators do not make the list of 72,although BancoSol and BRI do). Someexperts estimate that no more than 1percent of NGO programs worldwideare currently financially sustainable—and perhaps another 5 percent of NGOprograms will ever cross the hurdle.15

15 The figures are based on an informal polltaken by Richard Rosenberg at a microfinanceconference (personal communication, Nov. 1998).



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The other 95 percent of programs inoperation will either fold or continuerequiring subsidies, either because theircosts are high or because they choose tocap interest rates rather than to pass

costs on to their clients. Although subsi-dies remain integral, donors and practi-tioners have been reluctant to discussoptimal subsidies to alleviate poverty,perhaps for fear of appearing retro-grade in light of the disastrous experi-ences with subsidized government-runprograms. Instead, rhetoric privilegesfinancial sustainability.

4.1 International Evidence

Table 2 gives financial indicators forthe 72 programs in the MicroBankingBulletin survey.16 The 72 programs havebeen divided into non-exclusive catego-ries by age, lending method, targetgroup, and level of sustainability.17

(There is considerable overlap, for ex-ample, between the village bank cate-gory and the group targeting “low end”borrowers.)

The groups, divided by lending

method and target group, demonstratethe diversity of programs marching be-hind the microfinance banner. Averageloan balances range from $94 to $842 when comparing village banks to thosethat lend exclusively to individuals. Thefocus on women varies from 92 percentto 53 percent. The target group cate-gory makes the comparison starker,

with average loan balances varying from$133 to $2971. Averages for the 34 fully sustainable institutions are not, how-ever, substantially different from theoverall sample in terms of average loan

balance or the percentage of femaleclients.Sustainability is generally considered

at two levels. The first is operational sustainability. This refers to the ability of institutions to generate enough reve-nue to cover operating costs—but notnecessarily the full cost of capital. If unable to do this, capital holdings aredepleted over time. The second level of concern is financial sustainability. This

is defined by whether or not the in-stitution requires subsidized inputs inorder to operate. If the institution isnot financially sustainable, it cannotsurvive if it has to obtain all inputs (es-pecially capital) at market, rather thanconcessional, rates.

Most of the programs in the survey have crossed the operational sustain-ability hurdle. The only exceptions arethe village banks and those with low

end targets, both of which generateabout 90 percent of the requiredincome.18

Many fewer, however, can cover fullcapital costs as well. Overall, programsgenerate 83 percent of the required in-come and the village bank/low end tar-get groups generate about 70 percent.Strikingly, the handful of programs thatfocus on “high end” clients are just as

heavily subsidized as those on the low end. Similarly, the financial perfor-mance of programs with individual

16 The project started as a collaboration with the

American Economic Association’s Economics In-stitute in Boulder, Colorado.17 Those with low end target groups have aver-

age loan balances under $150 or loans as a per-centage of GNP per capita under 20 percent (they include, for example, FINCA programs). Those with broad targets have average balances that are20–85 percent of GNP per capita (and includeBancoSol and the BRI unit desa system). The highend programs make average loans greater than 120percent of GNP per capita. The solidarity groupmethodology is based on groups with 3–5 borrow-ers (like BancoSol). The village banks have groups with over five borrowers .

18 See Mark Schreiner (1997) and Khandker(1998) for discussions of alternative views of sus-tainability. Unlike other reported figures, thosehere make adjustments to account for subsidies oncapital costs, the erosion of the value of equity dueto inflation, and adequate provisioning for non-re-coverable loans. To the extent possible, the figuresare comparable to data for standard commercialenterprises.



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loans is roughly equivalent to that of programs using solidarity groups, eventhough the former serve a clientele thatis more than twice as rich.

The greatest financial progress has

been made by broad-based programslike BancoSol and BRI that serve cli-ents across the range. Financial pro-gress also improves with age (althoughcomparisons of young and old groupscan only be suggestive as their orienta-tions tend to differ).19

The returns to equity echo the dataon financial sustainability. The numbersgive profits relative to the equity putinto the programs. The table shows that

this is not a place to make big bucks. While average returns to equity of 9.3percent for the financially-sustainableprograms are respectable, they do notcompete well with alternative invest-ments and often carry considerable risk.At the same time, social returns may well be high even if financial returnsare modest (or negative). On average,the broad-based programs, for example,cover all costs and serve a large pool of

clients with modest incomes, most of whom are women. Wall Street wouldsurely pass by the investment opportu-nity, but socially-minded investorsmight find the trade-off favorable.

If returns to equity could be in-creased through more effective leverag-ing of equity, however, Wall Street mighteventually be willing to take a look. In-creasing leverage is thus the cutting

edge for financially-minded microfinanceadvocates, and it has taken microfi-nance discussions to places far fromtheir original focus on how to make$100 loans to Bolivian street vendors.

If donors tire of footing the bill formicrofinance, achieving financial sus-tainability and increasing returns to eq-uity is the only game to play. The issue is: will donors tire if social returns can be

proven to justify the costs? Answeringthe question puts impact studies and cost–benefit analyses high on the researchagenda. It also requires paying close at-tention to the basis of self-reportedclaims about financial performance.

4.2 The Grameen Bank Example

The data above have been adjusted tobring them into rough conformity withstandard accounting practices. This is

not typical: microfinance statistics areoften calculated in idiosyncratic waysand are vulnerable to misinterpretation.The Grameen Bank has been relatively open with its data, and it provides a fullset of accounts in its annual reports.

Table 3 provides evidence on theGrameen Bank’s performance between1985 and 1996.20 The table shows Gra-meen’s rapid increase in scale, with thesize of the average annual loan portfolio

increasing from $10 million in 1985 to$271 million by 1996. Membership hasexpanded 12 times over the sameperiod, reaching 2.06 million by 1996.

The bank reports repayment ratesabove 98 percent and steady profits—and this is widely reported (e.g., NewYork Times 1997). All accounting defi-nitions are not standard, however. Thereported overdue rates are calculated

by Grameen as the value of loans over-due greater than one year, divided by

19 None of the U.S. programs that I know of areprofitable, and some are very far from financialsustainability, held back by legal caps on interestrates (Michael Chu 1996). None of the U.S. pro-grams are included in the MicroBanking Bulletinsurvey.

20 The base data are drawn from Grameen Bankannual reports. This section draws on Morduch(1999). Summaries of Grameen’s financial perfor-mance through 1994 can be found in Hashemi andSchuler (1997) and Khandker, Khalily, and Kahn(1995). Schreiner (1997) provides alternative cal-culations of subsidy dependence with illustrationsfrom Grameen. The adjustments here capture themost critical issues, but they are not comprehen-sive—for example, no adjustment is made for theerosion of equity due to inflation.



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the current portfolio. A problem is thatthe current portfolio tends to be muchlarger than the portfolio that existed when the overdue loans were firstmade. With the portfolio expanding 27times between 1985 and 1996, reporteddefault rates are considerably lowerthan standard calculation of arrears

(which instead immediately capturesthe share of the portfolio “at risk”). Theadjusted rates replace the denominator with the size of the portfolio at the timethat the loans were made.

Doing so can make a big difference:overall, overdues averaged 7.8 percentbetween 1985 and 1996, rather than thereported 1.6 percent. The rate is stillimpressive relative to the performanceof government development banks, but

it is high enough to start creating finan-cial difficulties. More dramatically, thebank reported an overdue rate of 0.8percent in 1994, while at the same timeI estimate that 15 percent of the loansmade that year were unrecovered.

Similarly, reported profits differ con-siderably from adjusted profits in Table

3. The main adjustment is to make ade-quate provision for loan losses. Until re-cently, the bank had been slow to writeoff losses, and the adjusted rates ensurethat in each year the bank writes off amodest 3.5 percent of its portfolio (still,considerably less than the 7.8 percentaverage overdue rate). The result islosses of nearly $18 million between1985 and 1996, rather than the bank’sreported $1.5 million in profits.

TABLE 3GRAMEEN BANK: SELECTED FINANCIAL INDICATORS

(Millions of 1996 U.S. dollars)

1985 1990 1992 1994 1996

1985–1996

averageSize Average annual loans outstanding 10.0 58.3 83.8 211.5 271.3 108 Members (thousands) 172 870 1,424 2,013 2,060 1,101Overdues rates (%) Reported overdues rate 2.8 3.3 2.5 0.8 13.9 1.6A

Adjusted overdues rate 3.8 6.2 1.9 15.0 — 7.8A

Profits Reported profits 0.02 0.09 –0.15 0.56 0.46 1.5B

Adjusted profits –0.33 –1.51 –3.06 –0.93 –2.28 –17.8B

Subsidies Direct grants 0.0 2.3 1.7 2.0 2.1 16.4B

Value of access to soft loans 1.1 7.0 5.8 9.0 12.7 80.5B

Value of access to equity 0.0 0.4 2.7 8.0 8.8 47.3B

Subsidy per 100 units outstanding 11 21 16 7 9 11Interest rates (%) Average nominal on-lending rate 16.8 11.1 15.8 16.7 15.9 15.9 Average real on-lending rate 5.9 3.0 11.6 13.1 10.1 10.1 Benchmark cost of capital Average nominal cost of capital

15.07.9

15.02.2

13.52.1

9.45.5

10.33.4

11.33.7

Subsidy dependence index 80 263 106 45 65 74 Avg. nominal “break-even” rate 30.2 40.2 32.6 24.2 26.2 25.7

Source: Morduch (1999) based on data from various years of the Grameen Bank Annual Report. Notes: A: average for 1985–94, weighted by portfolio size. B: Sum for 1985–96.



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Grants from donors are consideredpart of income in the profit calcula-tions. If the bank had to rely only onincome from lending and investments,it would have instead suffered losses of

$34 million between 1985 and 1996.The bulk of the bank’s subsidies en-ter through soft loans, however. Gra-meen paid an average of 3.7 percent onborrowed capital (a –1.7 percent realrate). Had it not had access to conces-sional rates, it would have had to pay considerably more. Here, an alternativebenchmark capital cost measure is ap-proximated as the Bangladesh depositrate from IMF International Financial

Statistics (1996) plus a 3 percent adjust-ment for transactions costs. The differ-ence in rates yields a total value of ac-cess to soft loans of $80.5 millionbetween 1985 and 1996. An additionalimplicit subsidy of $47.3 million was re-ceived by Grameen through access toequity which was used to generatereturns below opportunity costs.

Although subsidies have increasedover time in absolute quantities, the

bank’s scale has grown even morequickly. As a result, the annual subsidy per dollar outstanding has fallen sub-stantially, leveling off at about ten centson the dollar.

The subsidy dependence index sum-marizes the subsidy data by yielding anestimate of the percentage increase inthe interest rate required in order forthe bank to operate without subsidies of

any kind (Yaron 1992). The result for1985–96 indicates that in the early 1990s Grameen would have had to in-crease nominal interest rates on its gen-eral loan product from 20 percent toabove 50 percent. Overall, the averagebreak-even rate is 32 percent (the aver-age on-lending rate is lower than 20percent since about one quarter of theportfolio is comprised of housing loansoffered at 8 percent interest per year).

While borrowers would not be happy, itis not obvious that they would defect.Clients of the Bangladesh Rural Ad- vancement Committee, a Grameencompetitor with a similar client base,

are already paying 30 percent nominalbase interest rates, for example.Alternatively, radically stripping

down administrative costs would provide breathing room. In the early 1990ssalary and personnel costs accountedfor half of Grameen’s total costs, whileinterest costs were held below 25 per-cent. Decreasing wages has been impos-sible since they are linked to govern-ment wage scales, so the emphasis has

had to be on increasing efficiency. By 1996, salary and personnel costs wereroughly equal to interest costs (Mor-duch 1999). Training costs have alsobeen high. One study found that in1991, 54 percent of female trainees and30 percent of male trainees dropped outbefore taking up first positions withGrameen—and much of Grameen’s di-rect grants are funneled to supportingtraining efforts (Khandker, Khalily, and

Kahn 1995).The Association for Social Advance-

ment (ASA), another large microfinancepresence in Bangladesh, demonstrates amore radical approach to cost control.They have streamlined record keepingand simplified operations so that, forexample, only one loan type is offered— versus Grameen’s choice of generalloans, housing loans, collective loans,

seasonal loans, and, more recently,lease/loan arrangements. ASA thus feelscomfortable hiring staff with fewer for-mal qualifications than Grameen, andstaff retention is aided. ASA has alsoeliminated mid-level branch offices andhas centered nearly exclusively on thelarger groups of forty village members,rather than the five-member subgroups.

The Grameen Bank’s current path, pur-suing cross-subsidization and alternative



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income generation projects (includingan internet provision service and otherfor-profit spin-offs) is appealing in themedium term, but it has its own perils:the bank’s mission risks getting diluted,

and profitable sectors are vulnerable tocompetition over time.Grameen’s self-reported successes

have been exaggerated, but even if thebank is not the economic miracle thatmany have claimed, it is not obviousthat its failure to reach financial self-sufficiency is in itself a problem. Aslong as benefits sufficiently exceedcosts and donors remain committed tothe cause, Grameen could hold up as a

wise social investment.

5. Costs and Benefits of Credit Subsidies

Nearly all programs espouse financialsustainability as a key principle. At thesame time, nearly all programs rely onsubsidies of one sort or another. Thesesubsidies are typically viewed as tem-porary aids that help programs over-come start-up costs, not as ongoing pro-

gram features. It is the familiar “infantindustry” argument for protection.

The anti-subsidy stance springs froma series of worries. First, donors can befickle, and programs that aim to existinto the future feel the need for inde-pendence. Second, donor budgets arelimited, restricting the scale of opera-tions to the size of the dole. Self-suffi-cient programs, on the other hand, canexpand to meet demand. Third, subsi-dized programs run the risk of becom-ing inefficient without hard bottomlines. Fourth, in the past subsidies haveended up in the wrong hands, ratherthan helping poor households.

The view that subsidies should just betemporary has meant that calculatingthe costs and benefits of subsidies hasnot been an important part of microfi-nance practice, and there have been no

careful cost-benefit studies to date. Butthe fact is that subsidies are an ongoingreality: some “infants” are getting old.Moreover, many of the worries aboutproblems associated with subsidies can

likely be overcome.21

It is true that donors can be fickle,but governments will remain committedto poverty alleviation well after interna-tional agencies have moved on to thenext Big Idea. If subsidized microfi-nance proves to deliver more bang forthe buck than other social investments,should subsidies be turned down?

Scale certainly matters, but often asmall well-targeted program may do

more to alleviate measured poverty thana large, poorly-targeted program. Con-sider this example from Morduch(2000). Assume that the typical client ina subsidized program has an income of,say, 50 percent of the poverty line, while the typical cl ient of a sustainable(high interest rate) program has an in-come of 90 percent of the poverty line.To clarify the comparison, assume thatthe net impacts on income per borrower

are identical for the programs (afterrepaying loans with interest).

Minimizing poverty as measured by the commonly-used “squared poverty gap” of James Foster, Joel Greer, andErik Thorbecke (1984), for example,suggests that raising the poorer bor-rower’s income by one dollar has fivetimes greater impact than doing thesame for the less poor borrower. If the

sustainable program has 63,000 clients(roughly the size of Bolivia’s BancoSolin the early 1990s), the subsidized pro-gram would need to reach just 12,600clients to have an equivalent impact. The

21 This section draws heavily on Morduch(2000). Adams, Graham, and von Pischke (1982)present a well-argued alternative perspective.Schreiner (1997) presents a framework for consid-ering cost-effectiveness applied to BancoSol andthe Grameen Bank.



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comparison is too simple, but it amply illustrates how social weights and depthof outreach can outweigh concerns withscale.

The third issue, the danger of slip-

ping into inefficiency, has been demon-strated many times over by large publicbanks in low-income countries. But thekey to efficiency is the maintenance of hard budget constraints, not necessarily profits. Several donors already use strictand explicit performance targets whenlending to microfinance institutions,conditioning future tranches on perfor-mances to date. The lessons can be ap-plied more widely and used to promote

efficiency and improve targeting in abroader range of subsidized programs.

5.1 Simple Cost–Benefit Ratios

How should costs and benefits becompared? A simple gauge can beformed by dividing the value of subsi-dies by a measure of benefits accruingto borrowers. For example, Khandker(1998) reports a cost–benefit ratio of 0.91 with respect to improvements in

household consumption via borrowingby women from the Grameen Bank.This means that it costs society 91 centsfor every dollar of benefit to clients. Asimilar calculation leads to a cost–bene-fit ratio of 1.48 for borrowing by men.The ratio is higher, since lending tomen appears to have a smaller impacton household consumption (Mark Pittand Khandker 1998), but Khandker

stresses that even the ratio for maleborrowers compares favorably to alter-native poverty alleviation programs inBangladesh, like the World Food Pro-gramme’s Food-for-Work scheme (cost–benefit ratio = 1.71) and CARE’s simi-lar program (cost–benefit ratio = 2.62).The microfinance programs of theBangladesh Rural Advancement Com-mittee (BRAC) compare less favorably,however. Khandker (1998) reports ra-

tios of 3.53 and 2.59 for borrowing fromBRAC by women and men, respectively.

These calculations provide an impor-tant first-cut at taking costs and bene-fits seriously. They suggest that invest-

ing in microfinance is not a universal winner, but some programs beat alter-natives. Like all quick calculations,though, they rest on a series of simplifi-cations. Most immediately, only mea-surable benefits can be considered, thusexcluding much-discussed social im-pacts like “gender empowerment.”Other limits hinge on how the measur-able impacts are quantified. For exam-ple, the 0.91 ratio for lending t

Documents

Morduch Microfinance Promise