depth of outreach and financial sustainability of microfinance institutions
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Depth of outreach and financial sustainability ofmicrofinance institutionsShakil Quayes aa Department of Economics, University of Massachusetts Lowell, One University Avenue,Lowell, MA 01854, USAPublished online: 17 Jun 2011.
To cite this article: Shakil Quayes (2012) Depth of outreach and financial sustainability of microfinance institutions, AppliedEconomics, 44:26, 3421-3433, DOI: 10.1080/00036846.2011.577016
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Applied Economics, 2012, 44, 3421–3433
Depth of outreach and financial
sustainability of microfinance
institutions
Shakil Quayes
Department of Economics, University of Massachusetts Lowell,
One University Avenue, Lowell, MA 01854, USA
E-mail: [email protected]
The primary justification for subsidizing Microfinance Institutions (MFIs)
is their enhancement of social welfare by extending credit to the poor
households. Therefore, recent emphasis on their financial self-sufficiency
has created concern, that this may adversely affect the mission of social
outreach. Utilizing data from 702 MFIs operating in 83 countries, this
study shows empirical evidence of a positive complementary relationship
between financial sustainability and depth of outreach.
Keywords: microfinance institution; depth of outreach; financial
sustainability
JEL Classification: G29; O12; O16
I. Introduction
Microcredit has emerged as a feasible financial
alternative for poor people with no access to credit
from formal financial institutions, where its objec-
tives include eradication of poverty by fostering small
scale entrepreneurship through simple access to
credit. It distinguishes itself from formal credit by
disbursing small loans to the poor, using various
innovative nontraditional loan configurations such as
loans without collateral, group lending, progressive
loan structure, immediate repayment arrangements,
regular repayment schedules and collateral substi-
tutes. The operational and institutional framework of
a typical Microfinance Institution (MFI) greatly
differs from that of a formal financial institution
such as a traditional commercial bank. With very few
exceptions, a MFI does not rely on deposits as its
primary source of funds, and in addition to disburs-
ing microcredit it also provides noncredit services
such as capacity building, marketing of products,
vocational training and information on civil rights
and health to its borrowers. The MFIs do not operate
like the government-supported development banks
that simply focus on the volume of credit disburse-
ment in a particular sector of the economy such as
agriculture. At the same time, MFIs are also different
from development banks as they practice market
approach to credit and attempt to operate on the
basis of self-sustainability. However, there has been a
recent tendency among some MFIs to restructure
themselves as commercial enterprises to be able to tap
into deposits as a source of funds.A large number of MFIs that are in operation
today heavily rely on donor agencies to provide them
with a steady flow of subsidies and funding on easy
terms. The amelioration of overall social welfare by
extending credit to the poor households is the
primary justification put forth by the donors for
subsidizing MFIs. Accordingly, donors have long
validated their assistance for small nongovernmental
organizations which they believe can achieve the
Applied Economics ISSN 0003–6846 print/ISSN 1466–4283 online � 2012 Taylor & Francis 3421http://www.informaworld.com
DOI: 10.1080/00036846.2011.577016
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deepest outreach to the very poor. However, recentemphasis on attainment of financial self-sufficiencyhas created some apprehension in the microcreditindustry, that it may adversely affect the mission ofsocial outreach of providing credit access to the poor.
The study utilizes a sample of 702 MFIs from83 countries, to explain the relationship between thedepth of outreach and financial sustainability, byemploying a novel approach of separating the MFIsinto high disclosure and low disclosure firms. Wedemonstrate empirical evidence of how depth ofoutreach and financial sustainability affect eachother, and also show a positive complementaryrelationship between financial sustainability anddepth of outreach for the high-disclosure MFIs.
This article is organized as follows. Section IIprovides an overview of the literature and Section IIIexplains the significance of outreach and financialperformance of MFIs and its importance to theirrespective donors and the policy makers. Section IVoutlines the selection process of the sample fromthe data source and provides a description of thevariables. Using a linear regression model and a Logitmodel, Section V demonstrates empirical evidence insupport of positive correlation between financialperformance and disclosure. Section VI develops asimultaneous equation model treating both outreachand financial performance as endogenous variablesand presents the empirical results. Finally, SectionVII provides conclusions and the policy implicationsof our results.
II. Literature Review
Initially it was expected that the MFIs would be ableto wean themselves off donor subsidies and achieveself-sufficiency as their rate of recovery of loans wasexcellent, but Morduch (1999) contends that the well-publicized high rate of recovery in the microcreditindustry has somehow failed to automatically trans-form the donor-dependent MFIs into independentself-sustaining organizations. Morduch (2000) is alsosceptical of the optimistic belief harboured in theindustry that sound banking practice includingfinancial sustainability will also ensure depth ofoutreach and alleviation of poverty. Furthermore,the goal of providing the poorest with access to credithas also delivered mixed results, and Navajas et al.(2000) shows that MFIs provide loans to householdsthat are near the poverty line, but most of them arealso the ‘richest’ amongst the poor. Similarly, Cull
et al. (2007) demonstrate that MFIs can concurrentlymaintain profitability and the depth of outreach, aslong as they don’t extend credit to the absolute poor.Finally, Conning (1999) emphasizes a possible trade-off between outreach and sustainability along withfinancial leverage and argues that MFIs seekinggreater depth of outreach and maintaining financialsustainability must charge higher interest and incurgreater cost of disbursing loans. However, bothempirical and anecdotal evidence demonstrates verysmall variability in interest rates across MFIs withinthe same country for the same loan product. In fact,repeated statements from field workers1 in themicrocredit industry support the notion of a higherrate of recovery from poor borrowers, negating thepossible tradeoff between depth of outreach andfinancial performance. Responding to some empiricalstudies showing evidence that financial performancecan adversely affect outreach, Paxton (2003) uses amodified poverty outreach index, to rebuff the notionthat a tradeoff exists between sustainability andoutreach.
To explain the possible tradeoff between outreachand financial performance, Navajas et al. (2000),Schreiner (2002), Rhyne (1998) and Von Pischke(1998) contend that greater transaction costs associ-ated with per dollar of small loans (disbursed topoorer people) render such loans to be less costeffective than disbursing larger loans. As a result,increased depth of outreach comes at a higher serviceand administrative cost, which translates into poorerfinancial performance. Schreiner (2002) describes asdepth of outreach and financial sustainability as twodesirable but polar opposite targets since depth ofoutreach implies increased service to the poor, whileemphasis on financial sustainability may force MFIsto either cut back on the disbursement of smallerloans or rely more on subsidies. But he also criticizesthe one dimensional approach of simply analysing thedepth of outreach, and provides a framework of thedifferent aspects of the social benefit pertaining tomicrofinance, and demonstrates how enhancedbreadth, length, and scope of outreach can compen-sate for lack of depth of outreach. Practitioners in theindustry argue that most small loans have identicalloan structures and hence require lower service costs.Furthermore, group loans and other innovative loanstructures reduce administrative and monitoringcosts. Lariviere and Martin (1999) and Paxton andCuevas (2002) note that such innovations that alle-viate inherent asymmetries in information in thelending process and the nature of member-basedMFIs reduces transaction costs. Adoption of
1 The author had an extended opportunity to conduct several informal interviews with field workers in Bangladesh.
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technology such as, wide use of cellular phones byeven the poor people has also facilitated branchlessbanking which has further reduced service costs.
On the question of repayment rate by the poor,Sharma and Zeller (1997) in Bangladesh, and Zeller(1998) in Madagascar, both find that repaymentperformance decreases with the level of poverty sincethe poorest people are more susceptible to economicshocks and invest in activities that have a lower rateof return. However, informal interviews with micro-credit practitioners in Bangladesh revealed persistentclaims that poor borrowers are very much disinclinedto default on their loans and have a relatively higherrate of repayment since they do not have any othersource of borrowing.
The recent commercialization in the microcreditindustry has added a new challenge for existingnonprofit MFIs since these new for-profit MFIsconcentrate on lending to the less poor as opposed tolending to the very poor as it augments their profitobjective. Accordingly, Aubert et al. (2009), Hisako(2009) and Weiss and Montgomery (2005) argue thatMFIs that were committed to lending to the verypoor have had to gradually decrease their depth ofoutreach and increase the share of large loans inresponse to competition from new profit orientedMFIs. Using a global survey of MFIs, McKim andHughart (2005) report that a majority (70%) of theMFIs of in this survey acknowledge reducing theirprimary focus on the target population of poorpeople.
It has been widely argued that extending greatercredit services to the poor implies administeringlarger number of small loans implying higher costsper unit of loan. In addition, it may also expose thelender to greater risk of default since poor borrowersare more susceptible to and less capable of dealingwith economic shocks. On the other hand, variousstudies show how innovations in lending structuresand lower cost of communication between lender andborrower can greatly reduce the cost of disbursingand monitoring small loans. It is also argued that allelse equal, poor borrowers have a higher rate ofrepayment. If the positive dynamics in lending to thepoor compensate for the increase in cost and riskassociated with such, then there would be no tradeoffbetween depth of outreach and financial sustainabil-ity, otherwise an emphasis on financial sustainabilitywould hamper the mission of outreach. Finally, if theper unit cost of disbursing and monitoring smallloans is less (due to innovations in loans structure andother dynamics of lending to the poor) than the perunit cost of larger loans and/or if poor borrowershave a relatively higher rate of repayment, then depthof outreach and financial sustainability would
positively reinforce each other. Manos and Yaron(2009) conclude that tradeoffs may exist betweenoutreach and sustainability in the short-run but alsomention that both can be improved in the long-run asa result of economy of scale, and utilizing improvedoperational modes and innovations. The main goal ofthis study is to delineate the dynamic relationshipbetween depth of outreach and financial sustainabil-ity after incorporating all the relevant factors.
III. Importance of Outreach and FinancialPerformance of MFIs
Outreach
Social outreach generally refers to either breadth ofoutreach or depth of outreach, while occasionally itmay also include outreach to women borrowers.Breadth of outreach is measured by the number ofpeople a MFI has extended credit to, or the numberof borrowers over a specific period of time. Outreachto women is measured by the number of womenborrowers as a fraction of the total number ofborrowers. Depth of outreach is defined as access ofcredit disbursement to poor people, wherein thepoorer the borrowers are the greater is the depth ofoutreach. The majority of the recipients of micro-credit are women and as such, lack of outreach towomen has not been a major concern for practi-tioners or researchers. With the rapid growth ofmicrocredit, breadth of outreach has also increasedboth at the industry level and also at the individualMFI level. As a result, depth of outreach has receivedmore attention from all quarters who are concernedabout the overall social outreach of microfinance,including policy makers. From the point of providingpoor people with access to credit, breadth of outreachcan be thought of as measuring the quantity ofmicrocredit while depth of outreach measures thequality of microcredit.
The major limitation of using depth of outreach isa lack of information in measuring the level ofpoverty of the recipients of credit. Ideally, one wouldlike to use the income level or wealth level of theindividual borrowers to measure the depth of out-reach. Since such information on income or wealth isusually not collected by an MFI, and it is not revealed(due to privacy concerns) by the MFI when they docollect such information, data on income or wealth isnot available to researchers. As a result, the mostwidely used measure for depth of outreach is averageloan balance per borrower. Although it is not aperfect measure of poverty level, it is an excellent
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proxy for depth of outreach as there is a strongpositive correlation between income level and the sizeof loans. In other words, the poorer the borrower is,the smaller the size of the loan. Hisako (2009) usesaverage loan size per borrower to measure depth ofoutreach (it is called wide outreach in their paper).Throughout the rest of this article, outreach (or socialoutreach) will imply depth of outreach unless wespecify it differently such as, breadth of outreach.
Financial performance
Most of the MFIs operate as nonprofit organizationsto facilitate the alleviation of poverty by extendingcredit to the poor, while others operate as profitmaximizing organizations without deviating toomuch from the goal of outreach to the poor.However, recently there has been a collective driveby funding agencies for MFIs to attain financialsustainability. The motivation for this increasedemphasis on the financial performance of the MFIsemphasis is twofold – first, donor agencies have avested interest in the efficient utilization of the fundsallocated, and second, requirement of financialefficiency is a necessary condition for futureself-sufficiency of MFIs and eventually weaningthemselves off external subsidies. The incentives forbetter financial performance on part of the nonprofitMFIs include attainment of self-sufficiency andreduced reliance on donor funds. Furthermore, itallows them to service their lines of credit in a timelymanner without jeopardizing future flow of funds.Hence, financial performance has developed into oneof the essential goals even for MFIs that haveoperated as nonprofit organizations.
Therefore, there has been a recent paradigm shift inthe microcredit industry, from subsidized creditdelivery programmes to financially self-sufficientinstitutions providing commercial microfinance.Robinson (2001) addresses this gradual transforma-tion in the microcredit industry where, MFIs achievesocial outreach and financial sustainability withoutrequiring any subsidies.2 As a result, all MFIs and themicrocredit industry in general are faced with thereality that policy makers, donors and investors areincreasingly emphasizing their financial performanceby eliminating their reliance on subsidies.
At the same time, we have also noticed a height-ened level of interest in commercialization by manyMFIs that were previously operating as nonprofitorganizations. Recently a significantly large numberof MFIs (especially in Latin America) have volun-tarily agreed to be under the purview of financial
regulation, to operate as for-profit financial institu-tions that are allowed to accept deposits. Accordingto Christen (2000) 53% of the MFIs operating inLatin America are classified as for-profit commercialfinancial institutions. Another landmark example ofcommercialization of microcredit is the sale of 30%of its holdings through an initial public offering in2007 by Banco Compartamos (a Mexican bank thatspecializes in microcredit), instantly taking its marketvalue to a staggering $1.6 billion (Rosenberg, 2007;Malkin, 2008). In a recent study, Cull et al. (2009)report that 57% of all MFIs and 54% of all nonprofitMFIs in their sample were profitable firms while 87%of all the borrowers were served by profitable firms,demonstrating the fact that earning positive profit ismore of a norm in the microcredit industry ratherthan an exception.
IV. Description of Data and Variables
The source of our data was Mix Market, a web-basedplatform which contains extensive financial andoutreach information for MFIs. The MFIs providecopies of their financial statements and outreachreports to Mix Market, which in turn converts theindividual local currency figures into United Satesdollars using the prevailing exchange rate. Next, theytransform the information from the financial state-ments and outreach reports into a list of standardizedfinancial and outreach variables that are publiclyavailable from their database. Hartarska andNadolnyak (2007), Hisako (2009) and Manos andYaron (2009) have used data from Mix Market. Thedata platform uses information from self-reportedfinancial statements and balance sheets from individ-ual MFIs, but most of these are audited and as suchthey are widely regarded as accurate and reliable. Inour empirical analysis we also differentiate betweenhigh-disclosure MFIs (which are deemed to providemore accurate information) and low-disclosure MFIsto account for better reliability of audited financialstatements. There are no other comparable interna-tional databases available, but one important draw-back of using data from Mix Market is that it doesnot include information on many MFIs that do notreport their information and as such, the MFIs listedon Mix Market are an incomplete list of MFIs.
There are instances when Mix Market has not beenable to compute some of these specific variables if therelevant information was not provided by the MFI.As a result, there are missing values reported for one
2 Two excellent examples of such MFIs are Bank Rakyat of Indonesia and BancoSol of Bolivia.
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or more variables for some of the MFIs. Althoughparticipation in the Mix Market database is volun-tary, many MFIs choose to consistently provide theirfinancial and outreach information to the database,and the information provided is believed to be fairlyreliable. All the variables used in the study are basedon financial statements outreach informationreported as of 2006, and all monetary values areexpressed in United Sates dollars.
Based on the level and quality of disclosure of theMFI, Mix Market uses a rating system, where thescore ranges from level 1 to level 5, as described3
below:
Level 1: General InformationLevel 2: Level 1 and Outreach and Impact Data(minimum 2 consecutive years of data)Level 3: Levels 1–2 and Financial Data (minimum 2consecutive years of data)Level 4: Levels 1–3 and Audited Financial Statements(minimum 2 consecutive years of audited financialstatements including Auditors’ opinion and notes)Level 5: Levels 1–4 and Adjusted Data (such asratings/evaluation, due diligence and other bench-marking assessment reports or studies)
The categories of low disclosure and high disclo-sure are determined on the basis of the disclosurescore assigned to the MFI by the Mix Market webplatform. It suffices to say that inferences drawn fromempirical results for the high-disclosure MFIs wouldbe more reliable as these MFIs provide auditedfinancial statements for at least 2 consecutive yearsthat are most recent. Keeping the variability in thequality of disclosure in view, we divide the MFIs intolow disclosure and high disclosure firms and showclear evidence of a positive impact of financialperformance on outreach for high-disclosure MFIs.Low disclosure firms have at least 2 years of financialdata available which are not necessarily auditedwhereas, high disclosure firms have at least 2consecutive years (or more) of audited financialstatements available. Despite wide disparity acrosscountries in terms of regulations and mandatorydisclosure rules, audited financial statements are ingeneral more reliable and accurate than un-auditedfinancial statements. Separating the high disclosurefirms provided us with a sub-sample of MFIs withmore accurate data, and allowed us to see if there wasany difference if we excluded the low disclosure firms.
At the time of data collection, there were 1126MFIs listed on the Mix Market database, of which275 MFIs provided limited or no financial and
outreach data, while another 122 had not yetprovided their annual reports for the year 2006. Asfinancial reports to Mix market is voluntary, someMFIs may have a longer lag in providing reportswhile others may simply cease to provide reports as aresult of closure of their operation. An additional 20MFIs had to be excluded from our sample since theydid not provide information on the average loanbalance per borrower (divided by gross nationalincome), an indispensible variable for our analysis.Out of the remaining 709 MFIs only seven have adisclosure level of 2, and these seven MFIs were alsodropped from our analysis. As a result, we have atotal of 702 MFIs from 83 countries in our samplethat have been used in our analysis, all of which havea disclosure level of 3 or higher. The list of MFIsincludes 35 MFIs that are registered as commercialbanks (some MFIs have chosen to register themselvesas commercial banks to be able to accept deposit butnevertheless operate primarily as an MFI), 102cooperatives and credit unions, 203 nonbank finan-cial institutions, 322 nongovernmental organizations,25 rural banks and 15 listed as other financialinstitutions. All MFIs included in our sample allocateat least 50% of their lending portfolio to micro-credit.
The central focus of this study is to demonstrateempirical evidence which can refute the claim that anemphasis on the financial performance of an MFI hasa negative impact on its outreach efforts. Unlessstated otherwise, outreach in this study refers todepth of outreach measured by the average loan sizeper borrower normalized by the respective grossnational income. We measure financial performanceby a dummy variable – Financial Sustainability whichtakes the value 1 if the operational self-sufficiency isgreater than or equal to 100%, and zero if less than100%. In the Mix Market data base, Operational self-sufficiency is defined as total financial revenue as apercentage of the sum of financial expense, operatingexpense and loan loss provision expense.
The gross loan portfolio is used to measure the sizeof the firm; it can increase either due to an increase inthe number of borrowers without any change in theaverage loan size per borrower, or with an increase inthe average loan size with no increase in the numberof borrowers. In the first case, the level of outreachwould remain unchanged while the level of outreachwould decline in the latter case. As a result, the size ofthe firm will either have no effect on outreach or itwill have a negative impact on outreach.
Since the primary goal of an MFI is to provideloans to the very poor, a larger level of equity would
3Reported verbatim from the Mix Market glossary.
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allow it to achieve a greater level of outreach,especially for the nonprofit MFIs. Following thesame thread of logic, debt to equity ratio can also beexpected have a positive effect on outreach.
The higher cost of disbursing and administeringsmaller loans are amongst the key reasons thatprevent formal financial institutions from being ableto provide microcredit to the poor. Therefore, ahigher total expense ratio would indicate a smalleraverage loan size and better outreach.
Following our logic for total expense ratio, onewould expect the cost per borrower to be positivelyrelated to outreach. However, group loans are smallerin size per borrower in comparison to other loansoffered by MFIs. Consequently, the cost per bor-rower for the smallest loans may be lower than largerloans. This may result in a positive correlationbetween loan size and cost per borrower. Otherwiseone would expect outreach to be positively correlatedwith cost per borrower.
Two-thirds of all the borrowers of microcreditfrom the MFIs in our sample are women, while amajority of the women borrowers take out smallerloans. Therefore, outreach would increase with ahigher proportion of women borrowers.
A total of 424 or 60% of all the MFIs in oursample would fall in the category of nonprofitorganizations; these are listed as nongovernmentalorganizations, cooperatives or credit unions. The restof the MFIs that operate as for profit organizationsare classified as banks, nonbank financial institutionsor rural banks. In general, we would expect thenonprofit MFIs to achieve better outreach than thefor-profit MFIs. At the same time, the for-profitMFIs can be expected to exhibit better financial
performance than the nonprofit MFIs. A dummyvariable, which takes the value of 1 if the MFI is anonprofit organization and 0 otherwise, is included inour model to capture the difference between the for-profit MFIs and nonprofit MFIs.
Table 1 provides a quick comparison of thesummary statistics of the variables used in ouranalysis between low-disclosure MFIs and high-disclosure MFIs and between not-for-profit MFIsand for-profit MFIs. Although the average loanbalance per borrower for the high disclosure firms issmaller (greater outreach) than that of low disclosurefirms, the difference is not statistically significant. Asa group, high-disclosure MFIs have better opera-tional self sufficiency than low-disclosure MFIs,which is statistically significant at the 5% level,despite having a higher total expense ratio (significantat 5%). This possibly indicates that better operationalself-sufficiency is positively correlated to better depthof outreach, or in the least, high-disclosure MFIs areable to achieve better financial performance than low-disclosure MFIs without sacrificing the mission ofoutreach. At the 5% level of significance, we alsoobserve that high-disclosure MFIs have higher equitylevel while low-disclosure MFIs have greater out-reach to women.
For-profit MFIs have better operational self-sufficiency and also greater average loan balanceper borrower than not-for-profit MFIs at the 1%level of significance. This conforms to other studiesthat have shown how profit-driven MFIs focus onfinancial performance at the expense of reducedoutreach. At the 1% level of significance for-profitMFIs have a larger loan portfolio, higher level ofequity and higher level of debt to equity ratio and
Table 1. Descriptive statistics
Variable All MFIs Low disclosure High disclosure Nonprofit For profit
Operational sustainability 1.1994 1.1595** 1.2175** 1.1728* 1.2401*Average loan per borrower 0.7314 0.8770 0.6654 0.5980** 0.9348**Gross loan portfolio 24.1423 17.4837 28.6149 11.5109* 45.9327*Total equity 5.8268 2.2848* 7.4328* 3.9439* 8.6985*Debt to equity ratio 7.6398 12.1881 5.5775 7.5171* 7.8268*Total expense ratio 0.2506 0.2370** 0.2567** 0.2478 0.2549Cost per borrower 155.54 147.46 159.21 121.44* 207.56*Women borrowers 0.6720 0.7136* 0.6531* 0.7258* 0.5899*Number of borrowers 62 595 37 289 74 070 48 692 83 800Years in operation 12.08 11.79 12.22 13.12* 10.49*Financially self-sufficient 554 154 400 319 235N 702 219 483 424 278
Notes: *Means that the mean of high-disclosure MFIs is different from the mean of low-disclosure MFIs or mean of nonprofitMFIs is different from the mean of for-profit MFIs at the at the 1% level of significance.**Means that the mean of high-disclosure MFIs is different from the mean of low-disclosure MFIs or mean of nonprofitMFIs is different from the mean of for-profit MFIs at the at the 5% level of significance.
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cost of loan per borrower in comparison to nonprofitMFIs, while not-for-profit MFIs have been in oper-ation for longer and have a greater outreach towomen.
The descriptive statistics provided in Table 1 showthat high-disclosure MFIs have a better operationalsustainability and a smaller average loan balance perborrower than low disclosure firms. This provides thefirst indication that financial sustainability can beattained without sacrificing outreach effort. We alsonotice that for-profit MFIs have better operationalsustainability than their nonprofit counterparts andhave a relatively larger average loan per borrower.Before going into the details of our analysis, it isimperative to refute the commonly held notion thatthe majority of the MFIs incur losses on a continuousbasis. Out of a total of 424 nonprofit MFIs, 319 or75% are financial self-sufficient, and the percentageof for-profit MFIs that are financially self-sufficient isnaturally higher at 85%.
V. Model and Empirical Results
The focus of our study is the impact of financialsustainability on the depth of outreach, measured bythe average size loans, where depth of outreachincreases with a decline in average loan size.Measurement of the depth of outreach can bespecified by the following equation
lnALBGi ¼ �þ �FSSi þ �1 lnGLPi þ �2 ln TEQi
þ �3DERi þ �4TERi þ �5 lnCPBi
þ �6WBRi þ "i ð1Þ
whereALBG Average Loan Balance per Borrower
divided by Gross National IncomeGLP Gross Loan Portfolio in US DollarsTEQ Total Equity in US DollarsDER Debt to Equity RatioTER Total Expense RatioCPB Cost of Loan per BorrowerWBR Number of Women Borrowers as a
fraction of Total Number of BorrowersFSS 1 if Firm is Financially Self-sufficient (i.e.
OSS� 100%) and zero otherwise, whereOSS is Operational Self-Sufficiency.
Our initial model is fraught with the endogeneityproblem that while depth of outreach is a function offinancial performance, financial performance mayalso depend on the level of outreach of an MFI.After estimating a Logit model where financial
performance is a function of outreach, we tackle theproblem of endogeneity by estimating a three-stageleast squares model where both outreach and finan-cial performance are included as dependent variables.While the three-stage least squares estimation takescare of endogeneity between outreach and financialperformance, this study did not explicitly addressother sources of possible endogeneity such as, theinteraction between disclosure and financial perfor-mance, or breadth of outreach and depth of outreach.In this study, we circumvent addressing these issues ofendogeneity and postpone such analysis as a futurecourse of research.
Table 2 presents the estimated coefficients from sixdifferent variations of the model depicted inEquation 1. The results shown in the first columnare based on our full sample that includes all 702MFIs. To differentiate between MFIs on the basis oftheir quality of disclosure of financial statements,columns 2 and 3 represent the low disclosure and highdisclosure firms, respectively. Columns 4, 5 and 6 showthe results for the full sample, low disclosure firms andhigh disclosure firms, respectively, after adding adummy variable to incorporate the distinctionbetween not-for-profit MFIs and for-profit MFIs.Since average loan balance is the inverse of outreach, anegative coefficient for financial sustainability willindicate a positive impact of financial performance onoutreach.
First, we run diagnostic tests to check for normal-ity of the residuals. Since the Shapiro–WilkW test fornormal data rejects the null hypothesis of normaldistribution, we resort to diagnostic plots for visualinspection of the seriousness of the problem if any.After generating a kernel density plot against anormal distribution, we conclude that the distributiondoes not deviate too much from normal distribution.We also graph a standardized normal probability plotof the residuals and a plot of the quantiles of theresiduals against quantiles of the normal distribution.Neither of these two plots indicates any seriousdeviation from normal distribution.
Next, we address our concern about possibleheteroscedasticity since the study uses a large cross-section sample of MFIs from 83 different countries.While Cameron and Trivedi’s decomposition of IM-test shows evidence against the null hypothesis thatvariance of the error terms is homogenous, theBreusch–Pagan/Cook–Weisberg test for heterosce-dasticity does not indicate any evidence againsthomoscedasticity. Therefore, we also ran diagnosticplots of the residuals to check for any severity inheteroscedasticity indicated by the IM test. Since thediagnostic plots do not exhibit any strong indicationof heteroscedasticity, we simply decide to retain our
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initial regression results and continue our analysiswithout having any concern about heteroscedasticity.
The Variance Inflation Factor (VIF) ranges from 1to infinity and VIFs greater than 10 are generally seenas indicative of severe multicollinearity. We computethe VIFs for all the independent variables in ourregression model and since none of them have a VIFgreater than 10 we rule out any serious problem ofmulticollinearity in our model.
The estimated coefficient for financial sustainabil-ity (FSS) for the full sample is negative but statisti-cally insignificant, indicating no evidence of anegative effect of financial performance on outreach.However, FSS has a negative effect on outreach thatis significant at the 10% level when we only includethe low-disclosure firms in our sample. On the otherhand, FSS has a statistically significant positiveimpact on the outreach efforts of an MFI if werestrict our attention to only the high disclosurefirms. Moving on to the regression output when weinclude the dummy variable for nonprofit MFIs,again we find that the coefficient for FSS is notsignificant for the full sample, has a positive sign forthe low disclosure firms, and a negative sign (signif-icant at the 1% level) for the high disclosure firms.The results from the high-disclosure MFIs can beinterpreted that financial self-sufficient MFIs areestimated to have a 30% smaller average loan balanceper borrower than MFIs which are not financial
self-sufficient. Therefore, increased financial sustain-ability can actually have a positive impact on thedepth of outreach, instead of being an impediment.
We now concentrate on column 6, to interpret theeffect of the other explanatory variables on the depthof outreach of an MFI. The estimated coefficient ofgross loan portfolio has a positive sign which isstatistically significant at the 1% level. This impliesthat the size of a firm has a negative impact onoutreach. Higher level of equity results in a betteroutreach, and this holds true for both low- and high-disclosure MFIs. Debt to equity ratio has a small butstatistically significant effect on the outreach of anMFI.
Total expense ratio has a positive impact on theoutreach efforts of an MFI. The coefficient of costper borrower is positive and statistically significant atthe 1% level, which indicates that lower costs areassociated with smaller-sized loans. On an average, a1% increase in the size of the loan is associated with a0.44% increase in costs. This may be due to the factthat the terms and conditions of small loans arestandardized and routine, and as such have a lowercost per borrower. Many group loans are also verysmall in size and require lower cost of monitoring onpart of the MFI management. In contrast, relativelylarger loans may entail higher administrative costsand result in a higher cost per borrower. This resultconfirms and reinforces the argument made by some
Table 2. Depth of outreach: ordinary least squares
Using dummy for nonprofit MFIs
Variable All MFIs Low disclosure High disclosure All MFIs Low disclosure High disclosure
Financial sustainability �0.0391(�0.42)
0.2098***(1.82)
�0.2678**(�2.08)
�0.0655(�0.79)
0.2140***(1.71)
�0.3006*(�2.85)
Gross loan portfolio 0.1815*(3.87)
0.0659(1.25)
0.2672*(3.91)
0.1591*(4.10)
0.0682(1.17)
0.2316*(4.50)
Total equity �0.2431*(�5.02)
�0.2663*(�5.01)
�0.2578*(�3.66)
�0.2357*(�5.83)
�0.2672*(�4.49)
�0.2434*(�4.51)
Debt to equity ratio �0.0050*(�4.28)
�0.0041*(�3.27)
�0.0072*(�4.28)
�0.0051*(�3.71)
�0.0040**(�2.48)
�0.0075*(�3.71)
Total expense ratio �3.5595*(�8.79)
�4.8936*(�9.77)
�2.9544*(�6.24)
�3.6581*(�14.47)
�4.8810*(�10.83)
�3.0876*(�10.41)
Cost per borrower 0.5140*(14.58)
0.6147*(11.08)
0.4470*(10.21)
0.5025*(16.16)
0.6178*(12.46)
0.4408*(11.45)
Women borrowers �1.0448*(�6.45)
�0.91297*(�3.47)
�1.0333*(�5.21)
�0.09374*(�6.41)
�0.9240*(�3.74)
�0.8695*(�5.02)
Nonprofit – – – �0.2968*(�4.33)
0.0461(0.36)
�0.3969*(�5.09)
Constant �1.0608*(�3.13)
0.4454(0.73)
�1.8178*(�3.80)
�0.6245***(�1.92)
0.3806(0.68)
�1.2732*(�3.03)
Adjusted R2 0.5199 0.6503 0.4783 0.5372 0.6489 0.5043
Notes: t-statistics are provided in parentheses below coefficient estimates.*, ** and *** denote significances at the 1, 5 and 10% levels, respectively.
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studies that innovations in loan structure lower theservice cost of disbursement and monitoring loans.
As most of the women borrowers are poor and takesmall-sized loans, the outreach of an MFI increaseswhen the proportion of women borrowers is higher.We also expected the not-for-profit MFIs to have ahigher level of outreach than their for-profit coun-terparts. The estimated coefficient for the dummyvariable, nonprofit is negative and statistically signif-icant at the 1% level, so our results confirm that not-for-profit MFIs have better outreach than for-profitMFIs. It implies that the estimated average loanper borrower of a nonprofit MFI is 40% smallerthan the average loan balance per borrower of afor-profit MFI.
A valid question to ask is whether outreach effortof an MFI has an effect on its financial sustainability.The increased emphasis on financial performance ofMFIs may force individual MFIs to reverse efforts tothe very poor and alter their pattern of lending, ifoutreach efforts have a negative impact on financialsustainability. It is therefore instructive to analysewhether outreach has an impact on the financialsustainability of an MFI.
To this end, we use the following Logit model toestimate the impact of outreach and other factors onfinancial self-sustainability of MFIs
PðFSSiÞ ¼ �þ �1 lnGLPi þ �2 ln TEQi þ �3DERi
þ �4TERi þ �5LLRi þ �6 lnNABi
þ � lnALBGi þ "i ð2Þ
where LLR is loan loss reserve ratio and NAB is thenumber of active borrowers.
The size of the firm can be expected to have apositive association with financial performance of anMFI. Intuitively, a larger level of total equity shouldhave a positive impact on financial performance anddisclosure, but it can also be argued that greaterequity may have a negative effect on financialperformance of an MFI.
An increase in the total expense ratio should have anegative effect on the profitability of a firm andtherefore, it is expected to have an adverse impact onfinancial sustainability. We believe that leverage,measured by debt to equity ratio will have anegative impact on the financial performance of anMFI. Loan loss reserve ratio defined as loanloss reserve as a fraction of loan portfolio, is anindicator of anticipated loss from defaults, and henceit should have an adverse effect on financialperformance.
On one hand, better depth of outreach or smallerloans result in a higher cost per dollar of loansdisbursed and should therefore have a negative
impact on the profitability of an MFI. But on theother hand, if borrowers of small loans have a betterrate repayment it would have a positive impact on itsprofitability. Therefore, if good repayment record bysmall borrowers more than compensates for thehigher cost of smaller loans, the depth of outreachwould have a positive impact on the financialsustainability of an MFI.
All other things equal, one would expect for-profitMFIs to have a better probability of attainingfinancial sustainability than not-for-profit MFIs.
The log-likelihood ratios (chi square with eightdegrees of freedom) which are all significant at the1% level are appropriately reported in Table 3. TheHosmer–Lemeshow goodness-of-fit test divides sub-jects into deciles based on predicted probabilities, andthen computes a chi-square from observed andexpected frequencies. It tests the null hypothesisthat there is no difference between the observed andpredicted values of the response variable. The test isnot significant for any of the three models [p-valuesfor the chi square tests are 0.15, 0.35 and 0.20 for thefull model, low-disclosure MFIs and high-disclosureMFIs, respectively] in this example, therefore wecannot reject the null hypothesis and say that all thethree models fit the data well.
As reported in Table 3, for all the MFIs in thesample, a 1% decrease in ALBG (or an increase in thedepth of outreach) increases the probability ofattaining self-sufficiency by 3.68%. The effect ofALBG on attainment of self-sufficiency is negativebut it not statistically significant for the low disclo-sure firms. When we consider only the high-disclosureMFIs, our results indicate that a 1% decrease in theaverage loan balance increases the probability offinancial sustainability by 6.36%. The results indicatethat depth of outreach has no impact on attainmentof financial sustainability for the low-disclosureMFIs, and increases the probability of better finan-cial performance of high-disclosure MFIs. As such,MFIs have no reason to curtail their outreach effortsin order to meet the demand for better financialperformance from the donor agencies.
Focusing our attention to the aspect of breadth ofoutreach, a 1% increase in the number of borrowersreduces the probability of attaining financial sustain-ability by 5.59% (while the estimated marginal effectfor the low disclosure firms is 4.08% and notsignificant, it is 5.46% for the high-disclosure firmsand statistically significant). Since the breadth ofoutreach apparently has an adverse impact on thefinancial performance of an MFI, increased emphasison financial performance may induce MFIs to rein intheir efforts to expand the breadth of their outreach.Expansion of credit to more borrowers is also
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associated with increase in number of branches formany MFIs that are rapidly branching out. This mayreconcile with the fact that increase in the breadth ofoutreach has a negative impact on financial perfor-mance despite the widely held belief of an absence oftradeoff between breadth of outreach and financialperformance. We leave detailed investigation of theinteraction between breadth of outreach and financialperformance to future research.
As expected, not-for-profit MFIs have a lowerprobability in attaining financial sustainability thanthe for-profit MFIs. The estimated coefficient fornonprofit, is positive but not statistically significantfor the low disclosure firms. When we look at thehigh disclosure firms, the nonprofit MFIs haveapproximately 7% lower probability in attainingfinancial sustainability than the for-profitMFIs. Therefore, for-profit MFIs have a higherprobability of attaining financial self-sufficiencyand the nonprofit MFIs have better depth ofoutreach. Finally, both total expense ratio and loanloss reserve ratio have a statistically significantnegative effect on the attainment of financialsustainability.
VI. Interaction Between Outreach andFinancial Performance
The empirical evidence from our analysis shows that
financial performance has a positive impact on the
depth of outreach of an MFI and at the same timedepth of outreach increases the probability of attain-
ing financial sustainability by an MFI. This is
especially true for the high-disclosure MFIs. To
incorporate the endogenous nature of the relationshipbetween the depth of outreach and financial perfor-
mance of an MFI, we construct a simple model of
simultaneous equations. As our final empirical exer-
cise, we estimate the endogenous model depicted byEquation 3a and 3b below, using a three-stage least
squares method, to capture any evidence of comple-
mentary relationship between depth of outreach and
financial self-sufficiency.
lnALBGi ¼ �0 þ �1FSSi þ �1 lnGLPi þ �2 ln TEQi
þ �3DERi þ �4TERi þ �5 lnCPBi
þ �1WBRi þ "i ð3aÞ
Table 3. Financial sustainability: logit model
All MFIs Low disclosure High disclosure
VariableEstimatedcoefficient
Marginaleffect
Estimatedcoefficient
Marginaleffect
Estimatedcoefficient
Marginaleffect
Gross loan portfolio 0.7237*(4.42)
0.1011*(4.54)
0.4839**(2.02)
0.0950**(2.05)
0.9974*(3.97)
0.1100*(4.04)
Total equity �0.0786(�0.67)
�0.0110(�0.67)
�0.0977(�0.59)
�0.0192(�0.59)
�0.2254(�1.11)
�0.0249(�1.10)
Debt to equity ratio �0.0078**(�2.11)
�0.0011**(�2.10)
�0.0049(�1.12)
�0.0010(�1.12)
�0.0237(�1.50)
�0.0026(�1.47)
Total expense ratio �4.2472*(�5.46)
�0.5931*(�5.36)
�3.9402*(�2.88)
�0.7732*(�2.86)
�4.3703*(�4.32)
�0.4820*(�4.13)
Loan loss reserve ratio �4.7152**(�2.52)
�0.6585**(�2.50)
�6.6184***(�1.78)
�1.2988***(�1.76)
�4.6407**(�2.06)
�0.5118**(�2.04)
Average loan balance/GNI �0.2632**(�2.12)
�0.0368**(�2.12)
0.1090(0.50)
�0.0214(0.50)
�0.5765*(�3.44)
�0.0636*(�3.50)
Number of active borrowers �0.4004*(�3.26)
�0.0559*(�3.30)
�0.2081(�1.05)
�0.0408(�1.05)
�0.4954*(�2.95)
�0.0546*(�3.02)
Nonprofit �0.4702**(�1.96)
�0.0637**(�2.04)
�0.3257(�0.79)
�0.0617(�0.82)
�0.6561**(�2.07)
�0.0711**(�2.15)
Constant �3.2504*(�2.98)
– �1.1691(�0.67)
– �4.4307*(�2.68)
–
LR �2a 121.95(0.00)
– 36.25(0.00)
– 87.66(0.00)
–
Hosmer–Lemeshow �2b 11.92(0.15)
– 9.64(0.35)
– 10.98(0.20)
–
Notes: t-statistics are provided in parentheses below coefficient estimates.aLog-likelihood ratio Chi square with eight degrees of freedom with p-values in parentheses.bHosmer–Lemeshow Chi square with eight degrees of freedom with p-values in parentheses.*, ** and *** denote significances at the 1, 5 and 10% levels, respectively.
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lnOSSi ¼ �0 þ �1 lnGLPi þ �2 ln TEQi þ �3DERi
þ �4TERi þ �5LLRi þ �2 lnALBGi
þ �2 lnNABi þ "i ð3bÞ
As reported in Table 4, the results for the full sample
show that size and cost per borrower have a statisti-
cally significant negative effect on outreach. Total
equity, debt to equity ratio, total expense ratio and the
fraction of women borrowers, each has a statistically
significant positive impact on the depth of outreach
that is statistically significant. At the 1% level of
significance, it also shows statistical evidence that a
financial a self-sufficient MFI has a better outreach
than an MFI which is not self-sufficient. At the same
time, the impact of outreach on financial performance
is positive and statistically significant at the 1% level.
For the low disclosure MFIs, the estimated coefficient
for financial self-sufficiency is negative and the coef-
ficient for average loan balance per borrower is
positive, but neither of these estimated coefficients is
significant at any reasonable level.Financial self-sufficiency has a negative coefficient
that is statistically significant at the 1% level for the
full sample and also for the high-disclosure MFIs.
This indicates that the depth of outreach is positively
affected by financial sustainability, and firms which
are operationally self-sufficient have a smaller aver-
age loan size than firms which are not. Furthermore,
depth of outreach has a positive impact on the
financial performance of high-disclosure firms. For
the high disclosure firms, a 1% increase in average
size of loans results in an estimated 0.55% reduction
in financial performance as measured by operational
self-sufficiency, whereas, financially self-sufficient
firms have an estimated 69% smaller loan size on
an average. Despite previous studies that have argued
about a tradeoff between depth of outreach and
financial performance, this study refutes any tradeoff
between the two. Using a large sample from 83
countries, we show that depth of outreach and
financial performance have a positive correlation
and reinforce each other when we incorporate the
dynamic interaction between the two and address the
nature of endogeneity.The result that cost per borrower increases by
0.47% with a 1% increase in loan size is consistent
Table 4. Depth of outreach and financial sustainability: three-stage least squares
All MFIs Low disclosure High disclosure
Dependent variable ALBG OSS ALBG OSS ALBG OSS
Financial self-sufficiency �0.6870*(�11.75)
– �0.0565(�0.47)
– �0.6885*(�8.82)
–
Average loan balance/GNI – �0.3254*(�2.89)
– 0.0647(0.34)
– �0.5482*(�6.44)
Gross loan portfolio 0.1795*(4.67)
0.1615**(2.40)
0.0870(1.53)
0.0588(0.58)
0.2435*(4.79)
0.2609(1.58)
Total equity �0.2304*(�5.77)
0.0125(0.57)
�0.2830*(�4.86)
�0.0091(�0.31)
�0.2331*(�4.38)
�0.0012(�0.05)
Debt to equity ratio �0.0059*(�4.37)
�0.0015***(�1.90)
�0.0044*(�2.74)
�0.0007(�0.74)
�0.0083*(�3.57)
�0.0029**(�2.55)
Total expense ratio �4.3665*(�18.46)
�1.3251*(�5.19)
�5.2968*(�12.08)
�0.4536(�0.72)
�3.6428*(�13.30)
�1.5230*(�8.98)
Cost per borrower 0.5361*(19.47)
– 0.6545*(13.65)
– 0.4724*(13.85)
–
Loan loss reserve ratio – �0.4764***(�1.82)
– �0.9835(�1.37)
– �0.3711***(�1.82)
Women borrowers �0.4387*(�3.25)
– �0.7999*(�3.38)
– �0.1027(�0.75)
–
Number of active borrowers – �0.1725**(�2.50)
– �0.0042(�0.03)
– �0.2584*(�5.06)
Nonprofit �0.3806*(�5.62)
�0.1783*(�3.13)
0.0288(0.23)
�0.0133(�0.20)
�0.4890*(�6.40)
�0.3135*(�5.82)
Constant �0.7580**(�2.36)
�0.8073**(�2.35)
0.3934(0.72)
�0.3506(�0.87)
�1.7296*(�4.21)
�1.4377*(�4.24)
�2 971.15 80.78 438.43 33.14 601.15 121.20
Notes: t-statistics are provided in parentheses below coefficient estimates.*, ** and *** denote significances at the 1, 5 and 10% levels, respectivley.
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with the argument (and the empirical results in thisstudy) that smaller loans have lower service costs andtherefore, depth of outreach will positively affectfinancial performance. Even after utilizing a three-stage least squares model to incorporate the inherentendogeneity, we find empirical evidence that breadthof outreach has a negative impact on financialperformance. This implies a possible tradeoff betweenbreadth of outreach and financial performance thatneeds to be addressed in future studies which incor-porates the effect of the cost of branches amongstother factors.
Not-for-profit MFIs have an average loan size thatis estimated to be 49% smaller than their for-profitcounterparts, whereas, for-profit MFIs have 31%better organizational self-sufficiency rate than theirnonprofit counterparts. These results corroborate toour earlier findings from single equation models. Allour results from the simultaneous equations modelare consistent with our initial results from the singleequation ordinary least squares model and Logitmodel.
The results from the three-stage least squarescorroborates with our earlier finding that nonprofitMFIs have better outreach and poorer financialperformance than for-profit MFIs. We also noticethat the tradeoff between breadth of outreach andfinancial performance is statistically significant onlyfor the high-disclosure MFIs, but not so for the low-disclosure firms, similar to the findings from theLogit model. We reiterate that the apparent tradeoffbetween financial sustainability and breadth of out-reach presents itself as an interesting topic of futureresearch.
Our results show statistical evidence of interdepen-dence between financial performance and depth ofoutreach. Furthermore, if we restrict our attention toonly the high-disclosure MFIs, there is empiricalevidence that financial sustainability has a positiveimpact on the depth of outreach, and improvement inthe depth of outreach in turn enhances the financialperformance of an MFI. Not only is there an absenceof tradeoff between financial sustainability and thedepth of outreach, this study shows that both depthof outreach and financial sustainability positivelycomplement each other.
VII. Conclusion
To our knowledge this is the first study that utilizes alarge and extensive sample of MFIs to investigate theimpact of financial sustainability on outreach,and demonstrates the complementary positiverelationship between depth of outreach and financial
self-sufficiency. Our initial results for the full sampleshow that financial sustainability has no impact onthe depth of outreach. However, when we divide thesample on the basis of disclosure level, our analysisuncovers evidence of a trade-off between outreachand financial sustainability for the low-disclosureMFIs, but shows that financial sustainability has apositive impact on the depth of outreach for the high-disclosure MFIs. Next, we find that an increase inthe depth of outreach increases the probability offinancial self-sufficiency for the high-disclosureMFIs, and has no impact for the low-disclosureMFIs. Finally, we estimate a three-stage least squaresmodel and show that depth of outreach and financialsustainability have negative relationship for the lowdisclosure firms, but they have a positive comple-mentary relationship for the high disclosure firms.Furthermore, we demonstrate that not-for-profitMFIs have better outreach but poorer financialperformance in comparison to for-profit MFIs. Theempirical results of this study show, that attainmentof financial sustainability is not an impediment tooutreach efforts, and it may actually facilitate greaterdepth of outreach.
Consequently, we do not need to be apprehensiveabout the recent emphasis on financial sustainabilitywhether it is self-imposed by MFIs or required bydonor agencies. Due to the positive nature of thecorrelation between outreach and financial perfor-mance, policy makers should consider encouragingthe recent drive towards attainment of self-sufficiencyby the MFIs.
The study used cross-section data for 1 year and assuch it is not possible to separate any managementefficiency or other organization specific variation. Asmore data is available for consecutive years, a panelstudy would provide us with richer results. It wouldalso be interesting to analyse possible tradeoffbetween breadth of outreach and financial sustain-ability and worthwhile to assess the relationshipbetween disclosure and financial performance.
Acknowledgements
Part of the work for this study was completed whilethe author was a visiting fellow at the Institute ofMicrofinance, Dhaka, Bangladesh.
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