The Profit Orientation of Microfinance Institutions and Effective

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THEPROFITORIENTATIONOFMICROFINANCEINSTITUTIONS

ANDEFFECTIVEINTERESTRATES

PeterW.Roberts*

GoizuetaBusinessSchool

EmoryUniversity

1300CliftonRoad,Atlanta,GA,30322

404‐727‐8585

404‐727‐6313

[email protected]

*TheauthorisgratefulforthehelpfulcommentsprovidedbyDavidKyle,AnandSwaminathanandPeterThompson.

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THEPROFITORIENTATIONOFMICROFINANCEINSTITUTIONS

ANDEFFECTIVEINTERESTRATES

Sincethearrivaloffor‐profitmicrofinanceinstitutions(MFIs),commentatorshavebeenasking

whetherthesectorbenefitsbyMFIsadoptingastrongerprofitorientation.Weaddressthis

questionbyanalyzingtheiradoptionofthefor‐profitlegalform,appointingprivatesector

representationandbankingacumentoMFIboards,andparticipationinmoreextensivefor‐profit

networks.Theresultsconsistentlyindicatethatastrongerfor‐profitorientationcorrespondswith

highereffectiveinterestratesforMFIclients.However,theseeffectsdonotleadtogreater

profitabilityandthereforesustainabilitybecausethesevariablesarealsoassociatedwithincreases

inthemajorelementsofanMFI’scosts.

KeyWords:microfinance,global,interestrates,nonprofit

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“SomeFearProfitMotivetoTrumpPovertyEffortsinMicrofinance”–NewYorkTimesheadline,August28,2009

1.INTRODUCTION

Microfinanceinstitutions(MFIs)arebankingorganizationswhoseprimarypurposeisthatof

providingfinancialservicestopoorandotherwisemarginalizedclients(Mersland&Strøm,2010).

Collectively,themicrofinancesectorislaudedformodifyingstandardbankingpracticesinorderto

effectivelyextendcredittothepoorandindoingsohelpingtoelevatetheirstandardsofliving.

Morespecifically,theinnovationsthatledtothemodernmicrofinancemovementovercametwo

problemspreviouslythoughttoprohibitlendingtothepoor:smallloansizesandlittleorno

collateral(Armendariz&Morduch,2005).

Therecentevolutionofthemicrofinancesectorcanbeviewedintermsoftherapidgrowth

inthenumberofactiveMFIs,increasesinthevolumeofbusinesstheyconduct,abroaderrangeof

financialservicesonoffer,andchangesinthetypesandmotivationsofMFIs.Inthislatterrespect,an

importantmarkerinthesector’sevolutionisthearrivalofprofit‐orientedMFIs.Althoughlaudedby

manyascritically‐importantforthematurationofthesector,theseMFIsalsousheredindebates

aboutwhetheritispossibletoeffectivelyblendnonprofitidealsandfor‐profitorientationsand

practices(Morduch,2000).

Morepractically,thesedebatesarerootedinquestionsaboutwhetherMFIswithstronger

profitorientationsarebetterabletosustainablyaddresstheneedsofpoorborrowers.Some

commentatorsclearlyplaceemphasisontheanti‐povertyorientationofMFIs:“thefirstgoalofMFIs

istoreachmoreclientsinthepoorerstrataofthepopulation,andthesecondgoalisfinancial

sustainability(Mersland&Strøm,2008a,pg.663).”However,itisalsobelievedthatalargenumber

of(especiallynonprofit)MFIsarenotearningsufficientincometocovertheirfullcostsofoperation

andexpansionandmustthereforerelyonsubsidies–intheformofgrantsanddonations–to

sustainthemselves.Concernsaboutthereliabilityofthesefundingsourcesmakesthefinancial

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viabilityofMFIsamajorconcernforsectorparticipants(Mersland&Strøm,2010).

Inthisrespect,profit‐orientedMFIsarepartofthemovementtowardamore‘businesslike’

microfinancesector.Withheightenedbusinessacumenandastrongermarketorientation,profit‐

orientedMFIsaresupposedtosetmoreappropriateloanpricesanddelivergreaterefficiencies,

andthushaveaneasiertimeattractingneededinvestmentintothesector.Thisshould,inturn,

allowthesocialimpactsthattheygeneratetobemoresustainable(Hermes&Lensink,2007).

Thearrivalofprofit‐orientedMFIsalsoraisesconcernsaboutMFIstradingoffsocialfor

financialperformance.Incontrast,agreaterfocusonprofitabilitymightpushconcernsaboutthe

well‐beingofpoorclientstothebackburner.Whiletheseconcernsclearlyapplytofor‐profitMFIs,

theyalsoapplytononprofitMFIswhereattentiontosustainabilityareleadingsometoemphasize

thegenerationoffinancialsurplus,evenifthatsurplusisneverdistributedtooutsideshareholders.

Inbothcases,manyworrythatwewillseeMFIsabandoningthepoorestclientsinsearchofmore

reliableprofitstreams–somethingcommentatorscall“missiondrift”(Copestake,2007).

EvenMFIsthatremainfocusedonthepoorestclientsmightalterthemixofcostsand

benefitsthattheyofferastheystriveforenhancedprofitability(Yunus,2011).Weaddressthis

latterquestionbyexaminingtheimpactofMFIshavingastrongerprofitorientationontheeffective

interestrateschargedtoclients.Whilethisisnottheonlyvariablethatmatterstomicrofinance

clients(Cull,Demirguc‐Kunt,&Morduch,2009),itdoescapturetheeffectivepriceofcreditaccess.

Weexaminedifferencesbetweentheeffectiveinterestrateschargedbynonprofitversus

for‐profitMFIs.However,wealsorecognizethattheprofitorientationofanMFIextendsbeyondits

decisiontooperateasafor‐profitorganization.Itisalsomanifestedinthemoresubtlechoicesand

commitmentsthatanMFImakes.Inparticular,weexaminethecompositionofMFIgoverning

boardstoascertainwhethertheycontainprivate‐sectorrepresentationand/orindividualswith

bankingacumen.Wealsoexaminetheextenttowhichthenetworksupportorganizations(Cook&

Isern,2004,pp.,pg.3)thatanMFIparticipatesinarethemselvespopulatedbynumerousotherfor‐

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profitMFIs.Intheend,ouranalysespaintasomewhatsoberingpictureoftheinfluenceofa

strongerprofitorientationontheeffectiveinterestrateschargedtoMFIclients.Eachofthesethree

variablesisassociatedwithhighereffectiveinterestrates.However,theseincreasesdonot

manifestinhigherMFIprofitabilityandthereforesustainabilitybecausetheMFIsthataremore

profitorientedalsotendtohavehighercosts.

2.PROFITORIENTATIONOFMICROFINANCEINSTITUTIONS

Thecollectivepushtoseeamoreprofit‐orientedmicrofinancesectorismostevidentinthe

relativelyhighincidenceoffor‐profitMFIsaroundtheworld.In2009,490ofthe1,169MFIs(42%)

intheMIXMarketdatabasewerefor‐profitMFIs.Theycollectivelycontrolledroughlytwo‐thirdsof

themorethan$65billioninassetsdeployedinthatyear.Clearly,adoptingafor‐profitlegalform

suggestsastrongerprofitorientation.However,thedecisiontooperateasafor‐profitorganization

isnottheonlychoicethatindicatestheprofitorientationofMFIs.Infact,Mersland&Strøm

(2008b)recentlyconcludedthatMFIownership(e.g.,shareholderversusNGO)isnotparticularly

relevantindeterminingitssocialorcommercialorientation.Rather,asCulletal.(2009)suggest,

“earningprofitsdoesnotimplybeinga‘for‐profit’bank.”NonprofitMFIscananddoearnpositive

profitsthataresimplynotdistributedtoshareholdersbutarere‐investedinactivitiesthatfurther

servicetheirclients.Therefore,wealsolookatseveralotherorganizationalchoicesthatplausibly

correspondwithanMFI’sprofitorientation.

Appointingindividualstotheboardofdirectorsrepresentsanimportantstrategicdecision

forMFIs.Advicefromandoversightbytheseboardmembershaveconsequencesfordecisions

takenwithinanMFI.Thoseinterestedinadoptingbestpracticesfromthefor‐profitworldandfrom

thetraditionalbankingsectormightthereforetendtoappointindividualstotheirboardswhobring

experiencefromthesedomains.Morespecifically,appointingindividualsfromtheprivatesector,as

opposedtothegovernmentorNGOsectors,indicatesadesiretobeinfluencedinthisdirection.The

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samecanbesaidaboutappointingindividualswithbankingacumen.Thus,havingprivatesector

representationandbankingacumenontheboardsuggestsastrongerprofitorientation.

AnotherwaythatMFIsdeepentheircommitmenttoaprofitorientationisbyparticipating

innetworkscomprisedofotherfor‐profitsMFIs.Sociologicalandmanagerialresearchonnetworks

indicatesthatthebehaviorandperformanceoforganizationsisinfluencedbythenetworksin

whichtheyparticipate(Brass,Galaskiewicz,Greve,&Tsai,2004).Fromanorganizationallearning

perspective,thetiesthatmakeuporganizationalnetworksareconduitsthroughwhichknowledge

andideasflows.Thiseffectisevidentinastatementtakenfromthewebsiteofoneprominent

microfinancenetwork:“MicroFinanceNetwork(MFN)isaninternationalassociationofleading

microfinanceinstitutions.ThroughtheMFN,31membersfrom27countriesshareideas,

experiences,andinnovativesolutionstothechallengestheyfaceinsearchofcontinuousgrowthand

progress.MFNmembersseektobemodelsofwhatispossibleintheindustry(www.mfnetwork.org).”

Thelatteraspirationpointstoasecondcontrolaspectofnetworks.Thepredominantparticipants

inanorganizationalnetworktendtodefinethenormsandpracticesinthatnetwork(Owen‐Smith

&Powell,2004).IfotherMFIsthatpopulatemicrofinancenetworksarelargelyfor‐profitMFIs,then

theorientationsandideasthattendtoflowthroughthosenetworkswillsupportandreinforcea

strongerprofitorientationamongnetworkparticipants.Thissuggeststhatparticipatingin

networkscomprisedofmorefor‐profitMFIssuggestsastrongerprofitorientation.

AssumingthesevariablesindicatetheprofitorientationofanMFI,thequestionbecomes

howthisorientationinfluencesbehaviorandperformance.Theoptimisticviewisthatsocial

impactswillbeimprovedbyincorporatingmoremarketdisciplineandcommercialacumenintothe

traditionallynon‐profitmicrofinancesector.Inotherwords,“thelureofprofit,economistsassume,

motivatesallentrepreneursandmanagersandfostersefficientdecisionmakingbyprivatefirms

(Weisbrod,1998,p.70).”Thepessimisticviewsuggeststhatthisorientationiseitherdistractingof

detractingfromthepursuitofpovertyreductionasanorganizationalgoal.Afterall,“anonprofit

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organizationhaslittleincentivetoskimponqualityofoutputorotherwisetakeadvantageofpoorly

informedcustomers(Weisbrod,1998,p.70).”Intheformercase,afocusonprofitstendstolead

MFIsawayfromthecommitmentthatimprovestheirabilitytoeffectivelylendtothepoorwhilethe

lattersuggeststhatadesiretoimproveprofitabilitywillleadtodeliberatechoicestocutservicesor

raiseinterestratestomeetthedemandsofhigherprofitability.

Themiddlegroundbetweenthesetwopositions(andthusthenullhypothesisinallthat

follows)suggeststhatdebatesabouttheimplicationsofprofit‐seekingarequiteirrelevant.

MerslandandStrom’s(2008a)analysisfoundthattheimpactofanMFI’sadoptingafor‐profit

orientationonitsperformanceiseffectivelynull.Thiscentristpositionisbasedonthebeliefthat

nonprofitandprofit‐orientedMFIscanbeequallyconcernedwithbothalleviatingpovertyand

financialsustainability:“Apriori,onewouldconsiderthatSHFsaremoreprofit‐orientedthan

NGOs.Similarly,thatNGOsshouldcaremoreaboutreachingthepoorestclientsthanSHFs…

However,analternativehypothesismaybethatSHFsandNGOsdonotperformdifferently,because

theymayusethesamebusinessmodeltocompeteandservecustomersinthemicrofinancemarket

(Mersland&Strøm,2008b).”

Giventheunsettleddebatesandtherelativepaucityofsystematicempiricalanalysis

(Hermes&Lensink,2007,pg.F2),thefollowingsectionsprovideacomprehensiveanalysisofthe

implicationsforeffectiveinterestratesofanMFIhavingastrongerprofitorientation.

3.DATAANDSAMPLE

OuranalysiscombinestwodifferentMIXdatasources(www.mixmarket.org):theirarchiveofMFI

financialinformationandtheirmorerecentSocialPerformanceReports.Theselatterreports

capturedetailedinformationaboutspecificchoicesandconfigurationsthatpertaintoanMFI’s

socialorientation.The358MFIsinoursampleallcompletedSocialPerformanceReportsin2008or

2009andhadcorrespondingfinancialdatafor2009.Toassesstherepresentativenessofthis

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sample,wecompareittothebroadersampleofallMFIsinthe2009MIXfinancialinformationfile

andfindittobebroadlycomparable(seetable1).

Table1abouthere

OuranalysisfocusesononevariablethathasdirectimplicationsfortheclientsofMFIs–the

effectiveinterestratechargedonthefundsthattheyborrow.Followingacceptedpractice

(Gonzalez,2010),oureffectiveinterestratevariableisrealtotalearnedinterestincomeandfees

dividedbytheaveragegrossloanportfolio.AmongthesampledMFIs,theaverageeffectiveinterest

rateis28.06%.

TheMIXdataalsoreporttheprofitstatusofeachMFI.Weusethisinformationtocreatea

‘For‐profitMFI’dummyvariablesettooneforMFIsthatoperateasfor‐profitorganizations.

Accordingtotable1,35%ofthesampledMFIsarefor‐profitorganizations.TheMIXSocial

PerformanceReportsaskrespondentsseveralquestionsaboutthecompositionoftheirboards.

Twoquestionsaresalientforthisanalysis.ThefirstaskswhetheranMFI’sboardhasprivatesector

representationandthesecondaskswhetherbankingacumenispresentontheboard.Weusethis

informationtocreatetwoadditionaldummyvariables:‘Privatesectoronboard’and‘Banking

acumenonboard’.

Finally,theMIXwebsitereportsonthecompositionofroughly100networksupport

organizationsthatworkwithMFIsaroundtheworld.Thesenetworks“facilitateandprovide

supporttoorganizationsthatarecommittedtodeliveringfinancialservicestothepoor,”andcanbe

national,regionalorinternationalinorientation(Cook&Isern,2004,pp.,pg.3).Theyrangeinsize

fromfourtomorethan150membersandprovidearangeofservicestotheirmembers,including

financialandtechnicalservices,knowledgemanagement,researchanddevelopmentandpolicy

advocacy.AfterrecordingthenamesofallMFIsparticipatingineachnetwork,wecountthetotal

numberoffor‐profitMFIsthatafocalMFIistiedtobysharednetworkaffiliation.Themaximum

numberoffor‐profittiesis56andsowedividetheobservednumberoftiesforeachsampledMFI

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by56toobtainanormalizedvariablethatrangesfromzero(notiestofor‐profitMFIs)toone(the

maximumnumberofobservedties).

Differingsocialandeconomicconditionsacrosscountriesandregionshaveimplicationsfor

thesupplyofanddemandformicro‐lending(Ahlin,Lin,&Maio,2011).Wecontrolforlocating

acrossthesixregionsisolatedintheMIXdatabases–Africa,EastAsiaandthePacific,Eastern

EuropeandCentralAsia,LatinAmericaandTheCaribbean,MiddleEastandNorthAfricaandSouth

Asia–withaseriesofregionfixedeffects.Atthecountrylevel,weaccountforlocaleconomicand

politicalproblemsbytakingtheaverageofthesixdimensionsoftheWorldBank’sWorldwide

GovernanceIndicator(http://info.worldbank.org/governance/wgi/index.asp):voiceand

accountability,politicalstabilityandabsenceofviolence,governmenteffectiveness,regulatory

quality,ruleoflawandcontrolofcorruption.Becausetotalpopulationinfluencesthedemandfor

microcredit,wealsocontrolforthenaturallogofeachcountry’stotalpopulationin2009.

Prevailinginterestratesshouldalsobeinfluencedbythedegreeofmicrofinancesector

competition.Followingalargebodyoforganizationalecologyresearch(Hannan&Freeman,1989),

weproxyforthedegreeofcompetitionbycountingthenumberofMFIsactiveineachcountryin

2009(asreportedintheMIXdatabase).Theoverallcountrangesfromalowofone(inTunisia)toa

highof163(inIndia).Giventhedebatesaboutthedifferentialcompetitivenessoffor‐profitand

nonprofitMFIs,wedecomposethisvariableintofor‐profitandnonprofitdensitymeasures.In

doingso,weseethatsomecountries,likeIndia,havelargenumbersofbothfor‐profits(62)and

nonprofits(95).Mexicohasmanyfor‐profits(55)butrelativelyfewnonprofits(ten).Ontheother

hand,Bangladeshhasmanynonprofits(70)butrelativelyfewfor‐profits(3).

Duetoeconomiesofscaleandexperienceeffects,largerandolderMFIsshouldbemore

efficient(Gonzalez,2007).Wethereforeaccountforthesize(naturallogofassets)andage(natural

logoftheyearssinceanMFIstarteditsmicrofinanceoperations)ofeachMFI.Thereisalsointerest

intheroleplayedbyregulationinshapingthebehaviorandperformanceofMFIs(Cull,Demirguc‐

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Kunt,&Morduch,2011).Weincludeadummyvariablesettooneforbanksthatreportedbeing

undertheinfluenceofaregulatoryauthorityin2009.

MFIsalsovaryinthecomplexityandscopeoftheirofferings.Inthisregard,twovariables

thatmightinfluencethecostandperformanceofMFIsaretheextenttowhichtheyalsoengagein

deposit‐takingactivitiesandtheiroutreachlevels.Tocapturetheformereffect,weincludea

variablethatmeasuresthesavingsdeposits‐to‐assetsratioforeachMFI.Weproxyforthedegreeof

outreach(intermsofnumberofindividualstouched)byincludinganotherdummyvariablesetto

oneforMFIsthatarereportedintheMIXdatabaseashavingeithermediumorlargeoutreach

levels.

Commentatorsalsonotethatcostsandthereforeinterestratescanbeinfluencedbyseveral

variablesassociatedwiththedegreeofdifficultyassociatedwithprovidingmicroloansacross

differentclientsegments(Mersland&Strøm,2010,pp.,pg.35).Absentdirectmeasuresofthe

extenttowhichanMFItargetsmarginalizedclients,acceptedproxiesincludeaverageloansize,

targetingwomenborrowersandtargetingindividualsinruralareas(Cull,etal.,2009).Ouraverage

loansizevariableisthemedianloansizeaspercentageofcountrygrossnationalincomepercapita

(Gonzalez,2010).ThefractionofwomenborrowersisreportedinMIXastheshareofoutstanding

loansheldbywomenborrowers.TheSocialPerformanceReportsaskrespondentswhethertheir

MFItargetsruralclients.Weusethisinformationtocreateanotherdummyvariable.Finally,

publishedmissionstatementsprovidesomeindicationoftheextenttowhichpovertyalleviationis

acentralconcernforanMFI.WeexaminethemissionstatementofeachMFIandisolatethosethat

explicitlymentionpoorclientsorpovertyalleviation.

OurfinalcontrolvariablerelatestothelendingmodeladoptedbyeachMFI.Following

HermesandLensink’s(2007)discussionofgroup(orjointliability)lending,weincludeavariable

thatindicateswhetheranMFIemploysindividual,asopposedtogrouporvillagelendingpractices.

Table2reportsdescriptivestatisticsfor,andpair‐wisecorrelationsamongallofthe

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variablesinouranalysis.

Table2abouthere

4.ANALYSISANDRESULTS

Webeginbyenteringthecontrolvariablesintoanordinaryleastsquaresregressionmodel

(seemodel1intable3).Thesignificantcoefficientsrevealaninterestingasymmetrybetweenthe

estimatedeffectsoffor‐profitversusnonprofitcompetition.Thelatternegativeeffectisconsistent

withexpectations.GreatercompetitionfromlargernumbersofnonprofitMFIsdrivesdown

effectiveinterestrates.However,theestimatedeffectisoppositeforthefor‐profitcompetition

variable.Werevisitthesetworesults–whicharerobustacrossthevariousmodelsthatwe

estimate–intheconcludingsectionofthepaper.TheMFIsizevariablehastheexpectednegative

effectoninterestrates.Asexpected,MFIsthatoffermorecost‐effectivelargerloansalsocharge

lowerinterestrates.Ontheotherhand,interestratesaresignificantlyhigheramongtheMFIsthat

havemediumorlargeoutreachlevels,thosethattargetwomenclients,andthosethatemphasize

poverty‐reductionintheirmissionstatements.

Table3abouthere

WeareprimarilyinterestedintheorganizationalchoicesmadebyMFIsthatindicatea

strongercommitmenttoprofitability:adoptingthefor‐profitstatus,havingprivate‐sector

representationandbankingacumenonboards,andhavingmoreextensivetiestootherfor‐profit

MFIs.Model2introducesthesevariablesintotheeffectiveinterestratemodel.1Thefor‐profitMFI

variableispositivebutnotstatisticallysignificantatconventionallevels(p=.0.11).Moreover,each

ofthethreeboardandnetworkvariablesinflateseffectiveinterestrates.Havingprivatesector

1Givenconcernsaboutmulticollinearity,wecheckedthevarianceinflationfactors(VIFs)andfoundthehighest(5.02)tobewithintheacceptablerange.Wealsoestimatedfourseparatemodelsthatenteredeachoftheprofit‐orientationsvariablesindividuallyandobtainedthesameresults.Finally,weestimatedan(unreported)modelthatremovedoutlierobservations(i.e.,thoseforwhichtheresidualismorethantwostandarddeviationsawayfromzero)andobtainedthesamepatternofresults.

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representationontheboardcorrespondswithanestimatedincreaseintheeffectiveinterestrateof

3.53percentagepoints.Ensuringthattheboardhasbankingacumencorrespondswithalarger

4.06percentagepointincrease.Finally,increasingtiestootherfor‐profitMFIsfromzerotothe

maximumlevelcorrespondstoa6.97percentagepointincreaseineffectiveinterestrates.2

Giventhesimilarmagnitudesoftheestimatedboardandnetworkeffects,weperformedan

F‐testtoassessthenullhypothesisthattheircoefficientestimatesareequal.Thistestcannotreject

thenullhypothesisofequaleffects(F=0.57;p=0.57).Wethereforesumthethreevariablesintoa

singleindexthatreflectstheoverallprofitorientationofeachMFI.Thisvariablerangesfromalow

ofzero(ineightobservations)toahighof2.96,andaverages1.44.Closerinspectionshowsthatthis

profitorientationvariableissignificantlyhigheramongthefor‐profitMFIs;averaging1.71

comparedto1.29forthenonprofitMFIs(t=5.33;p=0.00).Whentheoverallprofitorientationindex

issubstitutedintomodel2,itseffectispositiveandsignificant;aunitincreasecorrespondingtoa

4.05percentagepointincreaseineffectiveinterestrates(seemodel3).

SomeresearchersexpressconcernsaboutdataqualityinmodelsevaluatingMFI

performance(Mersland&Strøm,2010).Wethereforeestimatedan(unreported)variantofmodel

3basedonthe310MFIsthatreceivedfourorfivestarsfordataqualityfromMIX.Theresultsare

virtuallyidenticaltothosereportedinmodel3.Two‐thirdsofthenonprofitMFIsinthissampleare

NGOs,withcreditunions/cooperativesandnon‐bankfinancialinstitutionscomprisingthe

remainingthird.Roughly80%ofthefor‐profitMFIsarenon‐bankfinancialinstitutions.The

remainingfor‐profitMFIsareeitherbanksorruralbanks.3Toensurethatourresultsarenotan

artifactofthelegalformadoptedbythesampledMFIs,werananother(unreported)modelthat

2Toassesswhetherthenetworktieseffectsimplyreflectstheoveralldegreeofconnectedness,wecreatedasecondnetworkvariablethatrangesfromzerotooneasanMFImovesfromhavingnotiestoothernon‐profitMFIstoonewhenithasthemaximumnumberofobservedties(131).Inanunreportedmodel,thecoefficientonthisnewvariableisnegativeandinsignificant(=‐1.55;p=0.68)whilethemagnitudeandsignificanceofthefor‐profittievariableremainspositiveandmarginallysignificant(=7.89;p=0.03).3 ThisdistributionoflegalformsinthissampleisqualitativelysimilartothatreportedbyCulletal(2009).

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includesdummyvariablesforeachlegalform.Again,theresultsreportedinmodel3arereplicated.

Finally,toensurethattheestimatedeffectsoftheprofitorientationvariablesarerobust,we

estimatedavariantofmodel3thatreplacesallregionandcountrycontrolvariableswithasetof

countryfixedeffects(seemodel4).Becauseweonlyincludeobservationsfromcountriesthathave

atleastthreesampledMFIs,thisreducesthesampleto339MFIs.Again,theresultsfrommodel3

arereplicated.Inthismodelaunitincreaseintheprofitorientationvariablecorrespondswitha

3.60percentagepointincreaseineffectiveinterestrateschargedtoMFIclients.

OneofourbasicpremisesisthattheorganizationalchoicesthatMFIsmaketoincorporatea

strongerprofitorientationcanhaveimplicationsaboveandbeyondthatofadoptingthefor‐profit

form.GivenpressuresonnonprofitMFIstoactmoreliketheirmarket‐orientedfor‐profit

counterparts,thesechoicesshouldalsoinfluencetheirbehaviorandperformance.Model5(intable

4)re‐estimatesmodel3usingthesub‐sampleofnonprofitMFIsandshowsasimilarpatternof

effects.Thistime,aunitincreaseintheprofitorientationvariableisassociatedwithamore

substantial5.00percentagepointincreaseineffectiveinterestrates.Inthesub‐sampleof127for‐

profitMFIs,theeffectofastrongerprofitorientationisstillpositive,althoughnolongerstatistically

significant.Itseemsthatthemoredamagingeffectsofastrongerprofitorientation(intermsof

higherinterestrateschargedtoclients)areconfinedtononprofitMFIs,althoughitisinstructiveto

observethatamongthefor‐profitMFIs,thevariablesthatoughttocorrelatewithimproved

businessandbankingacumendonothelptolowertheinterestratevariable.

Table4abouthere

Manyoftheclaimsabouttheimportanceofastrongerprofitorientationrelatestothe

abilityofMFIstoencouragemoreinvestmenttoflowintothesector.Insupportofthisclaim,table

2showsthatfor‐profitMFIstendtobelargerthantheirnonprofitcounterpartsandtendtooperate

inmorepopulouscountries.Extendingthislineofthought,itisplausiblethatthestrongerprofit

orientationismoresuitedtolargerMFIsize.Wemightthereforeexpecttoseetheeffectsofthe

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profitorientationvariablesdisappearorreverseinthesub‐sampleofMFIsthatareabovethe

mediansamplesize.Inmodel7,wedoseeareductionintheestimatedeffectsizeoftheprofit

orientationvariable.Relativetothesub‐sampleofsmallerMFIs,theadverseeffectofastronger

profitorientationisroughlyhalved;producinga2.23percentagepointincreasecomparedtoa5.44

percentagepointincreaseinthesmallerMFIsub‐sample.However,althoughtheadverseeffectof

theprofitorientationvariableoninterestratesislesspronounceditisstillsignificant.

(a)CostsandSustainability

EffectiveinterestratesarethesumofprofitsearnedplusthreemajorcomponentsofanMFI’scosts:

operatingexpenses,financialexpensesandlossesduetoloanimpairment.Wecontinueour

analysisbylookingathowthevariablesinmodel3alsoinfluencethesethreecostcomponents.

Operatingexpensesarelargelyafunctionofsalariesandstaffproductivity(Gonzalez,2010).Thus,

theoperatingexpensevariablethatweanalyzeisthesumofthesenon‐financialexpenses(plus

depreciationandamortizationandotheradministrativeexpenses)dividedbytheaveragegross

loanportfolio(Mersland&Strøm,2008a).Thevariablethatcapturesfinancialexpensesis

calculatedasthetotalfinancialexpensesrelativetotheaveragegrossloanportfolio.Finally,the

loanlossesvariableisthesimilarratioofthevalueofloanswritten‐offdividedbytheaveragegross

loanportfolio.

Giventheobviousinterdependenceamongthesethreecostvariables,weestimatethe

effectsofourcovariatesinaseemingly‐unrelatedregressionframework(Zellner,1962).The

resultsfromthissystemofequations–presentedasmodel8intable5–suggestthatmostofthe

systematicvarianceinMFIcostspertainstooperatingexpenses.Havingmorenonprofit

competitioninacountrycorrespondswithloweroperatingexpenseratios.Thefor‐profitMFI

competitionvariablehasnodiscernibleeffect.TheMFIsizevariablehasanegativeandsignificant

effectonoperatingexpenses,corroboratingexpectationsabouteconomiesofscaleintheMFI

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sector.Thereisalsoevidenceofthedocumentedtrade‐offbetweenfocusingonpovertyalleviation

andcostefficiency(Hermes,Lensink,&Meesters,2011).Theestimatedeffectsoftargetingwomen

borrowersandemphasizingpovertyreductioninthemissionstatementarepositiveandsignificant

intheoperatingexpensesequation.Ontheotherhand,thedecisiontotargetruralclientshasa

marginallynegativeeffect,perhapsduetolowerlandandlaborcostsinless‐developedareas.

Finally,takinginmoredeposits,andtherebyincreasingorganizationalcomplexity,corresponds

withhigheraverageoperatingexpenses.

Table5abouthere

Turningtothevariablesofinterest,theprofitorientationvariableisassociatedwith

significantlyhigheroperatingexpenses(=5.77)andhigherloanimpairmentexpenses(=0.67).Its

effectonfinancialexpensesisalsopositivebutnotsignificant.Theestimatedeffectofthefor‐profit

MFIvariableisalsopositiveinallthreeequations,albeitonlymarginallysignificantinthefinancial

expensesequation.Thus,thereisnoevidenceoftheexpectedefficiencybenefitsofadoptinga

strongerprofitorientation.ThesefindingsareconsistentwithHudonandTraça(2011),whofind

thatMFIsthatreceivehigherlevelsofsubsidies–whichareprobablythelessprofit‐orientedMFIs

inthissample–areactuallymoreefficient.Moregenerally,thepatternreinforcesacorefindingof

MerslandandStrom(2008b),whofindnoevidencethatshareholder‐ownedMFIsare

systematicallymorecost‐effectivethantheirNGOcounterparts.

OnejustificationforthehigherinterestrateschargedbyMFIswhodemonstrateastronger

commitmenttoprofitabilityrelatestotheneedforMFIstobefinanciallysustainable.Intheory,by

providingmorebusinessacumenandmarketdiscipline,astrongerprofitorientationreducesthe

needforMFIstorelyonsubsidies.Instead,higherinterestratesand/orlowercostsallowthemto

earnthesurplusesthatallowthemtosustainoperationsontheirownterms.

AnMFI’sfinancialself‐sufficiencyratioequalsitsnetincomedividedbyitstotalcosts.

ValuesgreaterthanoneindicatethatanMFIisabletocoveritscostsandthereforesustainitself

16

overtime.WecreateadummyvariablesettooneforMFIswithfinancialself‐sufficiencyratios

greaterthanoneandanalyzeitscovariatesinalogisticregressionmodel.Arguably,thesearethe

MFIsthatgeneratedenoughprofitin2009tosustainthemselvesovertime.Thesignificant

coefficientsinmodel10(intable6)suggestthatgreatercompetitionfromotherfor‐profitMFIs

increasestheprobabilitythananMFIisfinanciallyself‐sustaining.Whetherornotavariableleads

tosignificantfinancialsustainabilitydifferencesdependsontheextenttowhichtheestimated

interestrateandcosteffectsoffsetoneanother.Inthisrespect,thefactthatcompetitionfromother

for‐profitMFIsincreasesthelikelihoodthatanMFIwillbefinanciallyself‐sustainingisexplainedby

thefactthatitsestimatedimpactoninterestrates(=0.27inmodel3)isgreaterthatthe

correspondingeffectsoncosts(consistentlynullacrossthethreeequationsinmodel9).Onthe

otherhand,emphasizingwomeninlendingportfoliosandpoverty‐alleviationinmission

statementsbothreducethelikelihoodthatanMFIisfinanciallyself‐sustaining.MFIsthatplace

greateremphasisonwomentendtohavehigheroperatingcosts(=18.90intheoperating

expensesequationinmodel9)thatarenotfullyaccountedforbytherelativelyhigherinterestrates

thattheychargetheirclients(=9.11inmodel3).Thisleadstotheoverallnegativeeffectonthe

probabilityofbeingfinanciallyself‐sustaining.AsimilarsetofobservationsappliestoMFIsthat

emphasizepovertyintheirmissionstatements.

Table6abouthere

Theprofitorientationvariableexertsnosignificanteffectonsustainability.Thisoverallnull

effectisexplainedbythefactthatthepositiveeffectoninterestratescharged(=4.05inmodel3)

ismorethanfullyoffsetbyitsadverseeffectsonoperatingexpensesandloanimpairmentexpenses

(=5.77and=0.23respectivelyinmodel9).Similarly(althoughestimatedwithlessprovision)for‐

profitMFIstendtochargehigherinterestratesbutalsooperatewithhigherexpenses,especially

financialexpenses.

17

5.DISCUSSIONANDCONCLUSION

“AreviewofmicrofinancepolicyreportsrevealsthatmostofthemhighlightthestrengthsofSHFsandtheweaknessesofNGOs.Inparticular,theyemphasisthatNGOsarelesscommercialandprofessionalbecausetheylackownerswiththepecuniaryincentivetomonitormanagement(Mersland&Strøm,2008b).”

Asthemicrofinancesectormatures,morequestionswillbeaskedaboutwhetheritisevolvingina

waythatadvantagesthepoorestpeopleontheplanet.Inparticular,weexpectthat“theroleof

fully‐commercial,profit‐seekinginstitutionsinprovidingsuchmicrofinanceloans[willcontinueto

be]controversial(Cull,etal.,2009).”Profit‐orientedMFIsareexpectedtobemoreefficientbut

thendistributemoreoftheirearnedsurplustooutsideshareholders.Nonprofitsareexpectedtobe

lessconcernedaboutgeneratingsurplusforownersbutalsolessoperationallyefficient.

Thebaselineexpectationsabouttheeffectsofastrongerprofitorientation–whichhave

beenchallengedelsewhere–arenotatallsupportedinthisanalysis.Thevariablesthatsuggesta

strongerprofitorientationdonotloweranyofthemajorcomponentsofanMFI’scost.Nordothey

significantlyimproveMFIsustainability.Theonlythingthatwecanconcludeisthattheeffective

interestrateschargedbyMFIswithstrongerprofitorientationsaresignificantlyhigheronaverage.

Inlightofthepersistentcommentaryregardingtheneedforamoremarket‐basedorientationin

thesector,thisoffersasomewhatsoberingaccountoftheimplicationsofMFIshavingstrongerfor‐

profitorientations.

Theeffectsrevealedinthisanalysissuggeststhatadvisoryinputsfromindividualswith

private‐sectorbackgrounds,withtraditionalbankingacumenorexperiencerunningfor‐profitMFIs

donothelpMFIsnavigatethetrade‐offsbetweenefficientservicedeliveryontheonehandand

organizationalsustainabilityontheother.TheyalsoreinforceanobservationmadebyArmendariz

andMorduch(2005),whonotehow“pioneeringmodelsgrewoutofexperimentationinlow‐

incomecountries…ratherthanfromadaptationsofstandardbankingmodelsinrichercountries.”

18

Itseemsthattheinsightsthatarerequiredtoachievepovertyalleviationalongwithfinancial

sustainabilitywillsimilarlynotcomefromtheimportationofadvicefromthosefamiliarwith

standardbankingmodels.

Thevariablesthatindicateastrongerprofitorientationneverseemtoproducetheexpected

benefitsforMFIclients.So,weconcludethepaperbyjoiningothersinstressingthat“ratherthan

concentratingonanMFIs‘commercialization,’attentionshouldbefocusedonhowtoreducecosts

perclient(Mersland&Strøm,2010,pg.35).”Giventhestrongcorrespondencebetweenvariables

thatsystematicallyinfluencebothMFIcostsandeffectiveinterestrates,itseemsthatdiscussionsof

howtostimulatestrongerprofitorientationsshouldbereplacedwiththosewhichmoredirectly

addressMFIefficiency.Forinstance,considerationmightbegiventohowonemightinducemore

nonprofitcompetition,ortoeffectivelyscalingefficientandeffectiveMFIs–bothnonprofitandfor‐

profit–asbothofthesevariablesseemtoreduceoperatingcostsandlowereffectiveinterestrates

(thelatterwithincreasedprofitability).

Otherfindingsfromtables3and4warrantfurtherscrutiny.Consider,forexample,the

asymmetriceffectsofthelevelsoffor‐profitandnonprofitcompetition.Theresultsthatpertainto

nonprofitcompetitionareconsistentwithourunderstandingofhowmarketsaresupposedto

operate.GreaternumbersofsuppliersforceMFIstobecomemorecostefficientinordertoattract

clients.Thecombinationofcompetitionandinducedefficienciesdrivesdowneffectiveinterest

rates.Thisisthespecificdynamicthatcommentatorswanttoseewithinthesector.However,the

correspondingeffectsofincreasednumbersoffor‐profitMFIsarecounter‐intuitive.Here,larger

numberstendtocorrespondwithsignificantlyhighereffectiveinterestrates(forallMFIsandfor

thesub‐sampleofnonprofitMFIs)andhigherMFIprofitability.Thisresultissorobustinthesedata

thatitseemsoddtoequatetheincreasednumbersoffor‐profitMFIswithincreasedMFI

competition.Theseasymmetriccompetitiveeffectsareclearlyworthyoffurtheranalysis.Inthe

meantime,wemustquestionthenetbenefitofinducinggreaterparticipationofMFIswithstronger

19

profitorientations.Inadditiontotheiradversedirecteffectsoninterestrates,theirproliferationin

acountryleadstoevenfurtherinterestrateincreases.

Inclosing,weproposethatthiskindofresearchallowspractitionersandcommentatorsto

lookbeneathbroadgeneralizationsaboutthedirectionofthemicrofinancesectorandappreciate

thediversityinobservedoutcomesthatareattributabletothemorespecificchoicesthatbothfor‐

profitandnonprofitMFIsmake.Inthisrespect,itmaynotbethatimportanttodeterminewhether,

onaverage,theMFIsectorisexperiencewhatsomearecallingmissiondrift.Itmaynotevenbe

importanttoascertainwhether,onaverage,for‐profitandnonprofitMFIsaremakingdifferent

choicesandtrade‐offs.Whatisimportantistheknowledgeofhowthespecificdecisionstakenby

MFIsareabletomoreorlesseffectivelymeetthetwinchallengesofaddressingpovertywhile

sustainingandscalingtheseimpacts.

Thatsaid,wemustalsostresstheneedforanappropriateinterpretationofthesecross‐

sectionalresults.Allwecansayforsureisthatin2009,MFIsthatdisplayedstrongerprofit

orientationstendedtochargehighereffectiverateswhileoperatingathighercost.Thesefindings

aregermanetothosethatseektoofferadviceonwhatkindsofMFIstendtoproducewhatkindsof

performanceoutcomesandsocialimpacts.Theyarealsoimportanttothoseresponsiblefor

directingfundstowardmoreimpactfulandsustainableMFIs.Here,onemightstresstheneedfor

thosewithavailablefunds–evenfundsthatseekmarketreturns–lookpastthefor‐profitversus

nonprofitdistinctionandlooktolendtoMFIsthatareoperatingefficientlyandpricing

competitively.However,ourresultsaresilentonthecausaleffectsofanindividualMFImoving

toward(orawayfrom)astrongerfor‐profitorientation.Addressingthiskindofquestion,whichis

clearlypartofthepolicyquestionsthatpertaintohowexistingMFIsmightbetterservetheir

clients,requiresalongitudinalanalysisofMFI’sthatswitchtobecomefor‐profitorganizations,that

changethecompositionoftheirboards,orthatchangetheextenttowhichtheirnetworksare

dominatedbyfor‐profitMFIs.Giventhebenefitsassociatedwithisolatingsuchexogenousimpacts

20

onMFIbehaviorandperformance,thiskindofdataandanalysiswillbemostuseful,andwillsurely

addrigortothedebatesaddressedinthispaper.

21

TABLE1.CURRENTSAMPLE

Sample

AllMIXMarket(2009)

N 358 1,169Shareoffor‐profitMFIs 35% 42%Averageassets(log) 16.34 15.84Averageeffectiveinterestrate 28.06 25.38

22

TABLE2.DESCRIPTIVESANDCORRELATIONS

Mean (0) (1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12) (13) (14) (15) (16) (17)(0)Effectiveinterestrate 28.06 (1)Countryproblems 65.38 ‐0.15 (2)Countrypopulation(log) 3.27 ‐0.03 ‐0.12 (3)For‐ProfitMFIsincountry 15.93 0.17 ‐0.19 0.67 (4)NonprofitMFIsincountry 25.37 ‐0.27 0.00 0.59 0.51 (8)Assets(log) 16.34 ‐0.30 ‐0.02 0.09 0.10 0.18 (9)Age(log) 2.43 ‐0.06 ‐0.05 ‐0.10 ‐0.15 0.02 0.22 (5)Regulated 0.54 ‐0.17 0.06 0.06 0.15 ‐0.05 0.35 ‐0.18 (6)DepositstoAssets 0.15 ‐0.20 0.19 0.05 0.06 0.06 0.31 0.18 0.20 (7)Medium/LargeOutreach 0.60 0.00 0.03 0.16 0.22 0.15 0.66 0.09 0.21 0.10 (10)Averageloansize(log) 0.33 ‐0.35 0.20 ‐0.30 ‐0.23 ‐0.20 0.29 0.01 0.25 0.27 ‐0.05 (11)Fractionwomenborrowers 0.62 0.29 ‐0.11 0.32 0.32 0.33 ‐0.07 0.02 ‐0.23 ‐0.23 0.21 ‐0.50 (12)Poor/povertyinmission 0.44 0.16 ‐0.02 0.25 0.17 0.18 0.00 ‐0.08 ‐0.08 ‐0.12 0.22 ‐0.24 0.33 (13)Targetruralclients 0.77 ‐0.06 0.09 ‐0.18 ‐0.08 0.00 0.12 0.14 0.00 ‐0.04 0.12 0.00 0.04 0.08 (14)Lendtoindividuals 0.88 ‐0.12 0.15 ‐0.28 ‐0.24 ‐0.20 0.10 0.08 0.11 0.14 ‐0.13 0.25 ‐0.36 ‐0.24 0.06 (15)For‐profitMFI 0.35 ‐0.01 ‐0.01 0.18 0.31 0.03 0.25 ‐0.30 0.50 0.11 0.12 0.20 ‐0.15 ‐0.09 ‐0.17 0.08 (16)Privatesectoronboard 0.36 0.11 0.02 0.12 0.19 0.08 0.09 ‐0.20 0.14 ‐0.11 0.24 ‐0.03 0.17 0.10 ‐0.07 ‐0.08 0.18 (17)Bankingacumenonboard 0.82 0.17 ‐0.03 0.17 0.20 0.02 0.18 ‐0.12 0.18 ‐0.06 0.25 ‐0.09 0.13 0.08 ‐0.08 ‐0.04 0.22 0.28 (18)Tiestofor‐profitMFIs(norm) 0.26 0.18 ‐0.13 ‐0.02 0.25 0.02 0.32 0.08 0.20 ‐0.08 0.28 ‐0.05 0.14 0.00 0.06 ‐0.02 0.14 0.11 0.13

23

TABLE3.EFFECTIVEINTERESTRATESCHARGEDBYMICROFINANCEINSTITUTIONS

Model1(Controls)

Model2(Profit

Orientation)

Model3(SingleIndex)

Model4(Country

FixedEffects)Countryproblems 0.01

(0.05)0.01(0.05)

0.01(0.05)

‐

Countrypopulation(log) 0.76(0.70)

1.08(0.69)

1.02(0.68)

‐

For‐ProfitMFIsincountry 0.33**(0.05)

0.25**(0.05)

0.27**(0.05)

‐

NonprofitMFIsincountry ‐0.26**(0.04)

‐0.23**(0.04)

‐0.24**(0.04)

‐

Assets(log) ‐1.96**(0.59)

‐2.52**(0.59)

‐2.40**(0.58)

‐1.21*(0.55)

Age(log) 0.21(1.01)

0.46(1.03)

0.61(1.02)

0.98(0.97)

Regulated ‐0.74(1.48)

‐2.26(1.53)

‐2.13(1.52)

‐2.92¥(1.57)

DepositstoAssets ‐3.39(3.10)

‐1.20(3.04)

‐1.31(3.03)

‐2.67(3.10)

Medium/LargeOutreach 5.02**(1.92)

3.97*(1.89)

3.92*(1.88)

‐0.44(1.73)

Averageloansize(log) ‐8.61**(2.50)

‐8.47**(2.45)

‐8.76**(2.43)

‐8.65**(2.60)

Fractionwomenborrowers 11.26**(3.01)

8.85*(2.93)

9.11*(2.96)

9.91**(2.97)

Poor/povertyinmission 3.86**(1.31)

4.14**(1.27)

4.14**(1.27)

2.72*(1.21)

Targetruralclients ‐1.86(1.43)

‐0.65(1.41)

‐0.67(1.41)

‐1.18(1.34)

Lendtoindividuals ‐0.13(2.02)

‐0.86(1.97)

‐0.83(1.96)

0.52(1.80)

For‐profitMFI ‐ 2.49

(1.55)2.46(1.55)

2.42(1.55)

Profitorientation

‐ ‐ 4.05**(0.88)

3.60**(0.86)

‐Privatesectoronboard ‐ 3.53**(1.31)

‐ ‐

‐Bankingacumenonboard ‐ 4.06*(1.62)

‐ ‐

‐Tiestofor‐profitMFIs(norm) ‐ 6.97*(2.93)

‐ ‐

Fixedregioneffects (yes) (yes) (yes) (no)Fixedcountryeffects (no) (no) (no) (yes) N 358 358 358 339AdjustedR2 0.48 0.51 0.51 0.65**p<0.01;*p<0.05;¥p<0.10

24

TABLE4.MODERATINGFACTORS:FOR‐PROFITSTATUSANDSIZE

Model5(NonprofitMFIs)

Model6(For‐ProfitMFIs)

Model7(LargerMFIs)

Model8(SmallerMFIs)

Countryproblems ‐0.04(0.06)

0.11(0.09)

0.01(0.06)

0.04(0.07)


0.92(1.33)

0.37(0.85)

2.14*(1.05)

For‐ProfitMFIsincountry 0.12¥(0.07)

0.40**(0.09)

0.37**(0.06)

0.10(0.09)


‐0.26**(0.06)

‐0.27**(0.04)

‐0.19**(0.07)

Assets(log) ‐2.39**(0.82)

‐2.50**(0.85)

‐1.59¥(0.81)

‐2.44*(1.18)

Age(log) 0.62(1.36)

1.46(1.69)

1.76(1.25)

‐1.02(1.60)


‐5.19(3.25)

‐2.88(1.93)

‐3.13(2.46)

DepositstoAssets ‐2.76(4.31)

‐1.54(4.69)

2.52(3.48)

‐11.53*(5.60)

Medium/LargeOutreach 3.89(2.45)

2.99(3.43)

1.58(2.73)

5.84*(2.94)

Averageloansize(log) ‐11.43**(4.15)

‐8.04**(3.16)

‐9.12**(2.61)

‐14.86**(4.78)

Fractionwomenborrowers 7.44*(3.76)

4.46(5.99)

8.40*(3.84)

9.92*(4.79)

Poor/povertyinmission 2.26(1.60)

6.23**(2.23)

3.28*(1.50)

4.55*(2.06)

Targetruralclients ‐2.02(1.88)

2.09(2.20)

1.93(1.71)

‐2.67(2.30)


4.15(4.07)

‐2.88(2.61)

0.83(2.97)

For‐profitMFI ‐ ‐ 2.75

(1.85)3.29(2.65)

Profitorientation

5.00**(1.14)

1.51(1.48)

2.23*(1.09)

5.44**(1.40)

Fixedregioneffects (yes) (yes) (yes) (yes) N 231 127 179 179AdjustedR2 0.50 0.57 0.53 0.50

**p<0.01;*p<0.05;¥p<0.10

25

TABLE5.THREEELEMENTSOFMFICOSTS

Model9aOperatingExpenses

FinancialExpenses

Loan

ImpairmentCountryproblems ‐0.24*

(0.11)‐0.06¥(0.03)

0.03(0.02)

Countrypopulation(log) 3.04*(1.52)

0.32(0.42)

0.06(0.26)

For‐ProfitMFIsincountry ‐0.03(0.12)

0.01(0.03)

‐0.02(0.02)


‐0.03(0.02)

‐0.01(0.01)

Assets(log) ‐6.38**(1.30)

0.12(0.36)

0.01(0.22)

Age(log) ‐2.75(2.27)

‐0.02(0.63)

0.33(0.39)


‐0.48(0.95)

‐0.00(0.58)

DepositstoAssets 16.67**(6.78)

1.49(1.88)

‐2.32*(1.15)


‐1.12(1.17)

0.12(0.71)

Averageloansize(log) ‐4.05(5.42)

0.70(1.50)

0.59(0.92)

Fractionwomenborrowers 18.90**(6.62)

1.60(1.84)

0.90(1.12)

Poor/povertyinmission 11.83**(2.84)

‐0.07(0.79)

0.09(0.48)

Targetruralclients ‐5.22¥(3.16)

1.29(0.87)

‐0.61(0.54)


‐0.85(1.22)

1.20(0.74)

For‐profitMFI 3.47

(3.46)1.86¥(0.96)

0.23(0.59)

Profitorientation

5.77**(1.97)

0.55(0.55)

0.67*(0.33)

Fixedregioneffects (yes) (yes) (yes) N 358 “R2” 0.37 0.09 0.12

**p<0.01;*p<0.05;¥p<0.10 aSeeminglyunrelatedregressionmodel

26

TABLE6.SELF‐SUFFICIENCY(SUSTAINABILITY)

Model10aSustainabilityPr(F.S.S.>1)

Countryproblems 0.01(0.01)


For‐ProfitMFIsincountry 0.04**(0.01)

NonprofitMFIsincountry 0.00(0.01)

Assets(log) 0.21(0.15)

Age(log) 0.50*(0.25)

Regulated 0.01(0.37)

DepositstoAssets 1.85*(0.95)


Averageloansize(log) ‐0.49(0.59)

Fractionwomenborrowers ‐1.46*(0.74)

Poor/povertyinmission ‐0.66*(0.31)

Targetruralclients 0.34(0.34)


For‐profitMFI 0.06

(0.37)Profitorientation

‐0.14(0.21)

Fixedregioneffects (yes)N 358Log‐Likelihood ‐168.78

**p<0.01;*p<0.05;¥p<0.10aLogisticregressionmodel

27

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The Profit Orientation of Microfinance Institutions and Effective