THEPROFITORIENTATIONOFMICROFINANCEINSTITUTIONS
ANDEFFECTIVEINTERESTRATES
PeterW.Roberts*
GoizuetaBusinessSchool
EmoryUniversity
1300CliftonRoad,Atlanta,GA,30322
404‐727‐8585
404‐727‐6313
[email protected]
*TheauthorisgratefulforthehelpfulcommentsprovidedbyDavidKyle,AnandSwaminathanand
PeterThompson.
1 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
2 “SomeFearProfitMotivetoTrumpPovertyEffortsinMicrofinance”–NewYorkTimes
headline,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
3 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‐
4 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
5 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
6 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
7 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
8 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‐
9 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
10 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)andfoundthe
highest(5.02)tobewithintheacceptablerange.Wealsoestimatedfourseparatemodelsthatenteredeachof
theprofit‐orientationsvariablesindividuallyandobtainedthesameresults.Finally,weestimatedan
(unreported)modelthatremovedoutlierobservations(i.e.,thoseforwhichtheresidualismorethantwo
standarddeviationsawayfromzero)andobtainedthesamepatternofresults.
11 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,wecreateda
secondnetworkvariablethatrangesfromzerotooneasanMFImovesfromhavingnotiestoothernon‐
profitMFIstoonewhenithasthemaximumnumberofobservedties(131).Inanunreportedmodel,the
coefficientonthisnewvariableisnegativeandinsignificant(=‐1.55;p=0.68)whilethemagnitudeand
significanceofthefor‐profittievariableremainspositiveandmarginallysignificant(=7.89;p=0.03).
3
ThisdistributionoflegalformsinthissampleisqualitativelysimilartothatreportedbyCulletal(2009). 12 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
13 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
14 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
15 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.
16 5.DISCUSSIONANDCONCLUSION
“Areviewofmicrofinancepolicyreportsrevealsthatmostofthemhighlightthe
strengthsofSHFsandtheweaknessesofNGOs.Inparticular,theyemphasisthatNGOs
arelesscommercialandprofessionalbecausetheylackownerswiththepecuniary
incentivetomonitormanagement(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.”
17 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
18 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
19 onMFIbehaviorandperformance,thiskindofdataandanalysiswillbemostuseful,andwillsurely
addrigortothedebatesaddressedinthispaper.
20 TABLE1.CURRENTSAMPLE
N
Shareoffor‐profitMFIs
Averageassets(log)
Averageeffectiveinterestrate
Sample
358
35%
16.34
28.06
AllMIX
Market
(2009)
1,169
42%
15.84
25.38
21 TABLE2.DESCRIPTIVESANDCORRELATIONS
(0)Effectiveinterestrate
(1)Countryproblems
(2)Countrypopulation(log)
(3)For‐ProfitMFIsincountry
(4)NonprofitMFIsincountry
(8)Assets(log)
(9)Age(log)
(5)Regulated
(6)DepositstoAssets
(7)Medium/LargeOutreach
(10)Averageloansize(log)
(11)Fractionwomenborrowers
(12)Poor/povertyinmission
(13)Targetruralclients
(14)Lendtoindividuals
(15)For‐profitMFI
(16)Privatesectoronboard
(17)Bankingacumenonboard
(18)Tiestofor‐profitMFIs(norm)
Mean
28.06
65.38
3.27
15.93
25.37
16.34
2.43
0.54
0.15
0.60
0.33
0.62
0.44
0.77
0.88
0.35
0.36
0.82
0.26
(0)
‐0.15
‐0.03
0.17
‐0.27
‐0.30
‐0.06
‐0.17
‐0.20
0.00
‐0.35
0.29
0.16
‐0.06
‐0.12
‐0.01
0.11
0.17
0.18
(1)
‐0.12
‐0.19
0.00
‐0.02
‐0.05
0.06
0.19
0.03
0.20
‐0.11
‐0.02
0.09
0.15
‐0.01
0.02
‐0.03
‐0.13
(2)
0.67
0.59
0.09
‐0.10
0.06
0.05
0.16
‐0.30
0.32
0.25
‐0.18
‐0.28
0.18
0.12
0.17
‐0.02
(3)
0.51
0.10
‐0.15
0.15
0.06
0.22
‐0.23
0.32
0.17
‐0.08
‐0.24
0.31
0.19
0.20
0.25
(4)
0.18
0.02
‐0.05
0.06
0.15
‐0.20
0.33
0.18
0.00
‐0.20
0.03
0.08
0.02
0.02
(5)
0.22
0.35
0.31
0.66
0.29
‐0.07
0.00
0.12
0.10
0.25
0.09
0.18
0.32
(6)
‐0.18
0.18
0.09
0.01
0.02
‐0.08
0.14
0.08
‐0.30
‐0.20
‐0.12
0.08
(7)
0.20
0.21
0.25
‐0.23
‐0.08
0.00
0.11
0.50
0.14
0.18
0.20
(8)
0.10
0.27
‐0.23
‐0.12
‐0.04
0.14
0.11
‐0.11
‐0.06
‐0.08
(9)
‐0.05
0.21
0.22
0.12
‐0.13
0.12
0.24
0.25
0.28
(10)
‐0.50
‐0.24
0.00
0.25
0.20
‐0.03
‐0.09
‐0.05
(11)
0.33
0.04
‐0.36
‐0.15
0.17
0.13
0.14
(12)
0.08
‐0.24
‐0.09
0.10
0.08
0.00
(13)
0.06
‐0.17
‐0.07
‐0.08
0.06
(14)
0.08
‐0.08
‐0.04
‐0.02
(15)
0.18
0.22
0.14
(16)
0.28
0.11
(17)
0.13
22 TABLE3.EFFECTIVEINTERESTRATESCHARGEDBYMICROFINANCEINSTITUTIONS
Model1
Model2
Model3
Model4
(Controls)
(Profit
(Single
(Country
Orientation) Index) FixedEffects)
Countryproblems
0.01
0.01
0.01
‐
(0.05)
(0.05)
(0.05)
Countrypopulation(log)
0.76
1.08
1.02
‐
(0.70)
(0.69)
(0.68)
0.25**
0.27**
‐
For‐ProfitMFIsincountry
0.33**
(0.05)
(0.05)
(0.05)
NonprofitMFIsincountry
‐0.26**
‐0.23**
‐0.24**
‐
(0.04)
(0.04)
(0.04)
‐2.52**
‐2.40**
‐1.21*
Assets(log)
‐1.96**
(0.59)
(0.59)
(0.58)
(0.55)
Age(log)
0.21
0.46
0.61
0.98
(1.01)
(1.03)
(1.02)
(0.97)
Regulated
‐0.74
‐2.26
‐2.13
‐2.92¥
(1.57)
(1.48)
(1.53)
(1.52)
DepositstoAssets
‐3.39
‐1.20
‐1.31
‐2.67
(3.10)
(3.04)
(3.03)
(3.10)
3.97*
3.92*
‐0.44
Medium/LargeOutreach
5.02**
(1.92)
(1.89)
(1.88)
(1.73)
‐8.47**
‐8.76**
‐8.65**
Averageloansize(log)
‐8.61**
(2.50)
(2.45)
(2.43)
(2.60)
**
*
*
8.85
9.11
9.91**
Fractionwomenborrowers
11.26
(3.01)
(2.93)
(2.96)
(2.97)
4.14**
4.14**
2.72*
Poor/povertyinmission
3.86**
(1.31)
(1.27)
(1.27)
(1.21)
Targetruralclients
‐1.86
‐0.65
‐0.67
‐1.18
(1.43)
(1.41)
(1.41)
(1.34)
Lendtoindividuals
‐0.13
‐0.86
‐0.83
0.52
(2.02)
(1.97)
(1.96)
(1.80)
For‐profitMFI
‐
2.49
2.46
2.42
(1.55)
(1.55)
(1.55)
3.60**
Profitorientation
‐
‐
4.05**
(0.88)
(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
339
0.48
0.51
0.51
0.65
AdjustedR2
**p<0.01;*p<0.05;¥p<0.10
23 TABLE4.MODERATINGFACTORS:FOR‐PROFITSTATUSANDSIZE
Model5
Model6
Model7 Model8
(Nonprofit (For‐Profit (Larger (Smaller
MFIs)
MFIs)
MFIs)
MFIs)
Countryproblems
‐0.04
0.11
0.01
0.04
(0.06)
(0.09)
(0.06)
(0.07)
Countrypopulation(log)
1.16
0.92
0.37
2.14*
(0.82)
(1.33)
(0.85)
(1.05)
0.40**
0.37**
0.10
For‐ProfitMFIsincountry
0.12¥
(0.07)
(0.09)
(0.06)
(0.09)
‐0.26**
‐0.27**
‐0.19**
NonprofitMFIsincountry
‐0.17**
(0.06)
(0.06)
(0.04)
(0.07)
‐2.50**
‐1.59¥
‐2.44*
Assets(log)
‐2.39**
(0.82)
(0.85)
(0.81)
(1.18)
Age(log)
0.62
1.46
1.76
‐1.02
(1.36)
(1.69)
(1.25)
(1.60)
Regulated
‐0.55
‐5.19
‐2.88
‐3.13
(1.93)
(3.25)
(1.93)
(2.46)
DepositstoAssets
‐2.76
‐1.54
2.52
‐11.53*
(5.60)
(4.31)
(4.69)
(3.48)
Medium/LargeOutreach
3.89
2.99
1.58
5.84*
(2.94)
(2.45)
(3.43)
(2.73)
‐8.04**
‐9.12** ‐14.86**
Averageloansize(log)
‐11.43**
(4.15)
(3.16)
(2.61)
(4.78)
*
*
4.46
8.40
9.92*
Fractionwomenborrowers
7.44
(3.76)
(5.99)
(3.84)
(4.79)
3.28*
4.55*
Poor/povertyinmission
2.26
6.23**
(2.23)
(1.50)
(2.06)
(1.60)
Targetruralclients
‐2.02
2.09
1.93
‐2.67
(1.88)
(2.20)
(1.71)
(2.30)
Lendtoindividuals
‐2.31
4.15
‐2.88
0.83
(2.27)
(4.07)
(2.61)
(2.97)
For‐profitMFI
‐
‐
2.75
3.29
(1.85)
(2.65)
1.51
2.23*
5.44**
Profitorientation
5.00**
(1.14)
(1.48)
(1.09)
(1.40)
Fixedregioneffects
(yes)
(yes)
(yes)
(yes)
N
231
127
179
179
0.50
0.57
0.53
0.50
AdjustedR2
**p<0.01;*p<0.05;¥p<0.10
24 TABLE5.THREEELEMENTSOFMFICOSTS
Model9a
Operating Financial
Loan
Expenses Expenses Impairment
‐0.06¥
0.03
Countryproblems
‐0.24*
(0.11)
(0.03)
(0.02)
0.32
0.06
Countrypopulation(log)
3.04*
(1.52)
(0.42)
(0.26)
For‐ProfitMFIsincountry
‐0.03
0.01
‐0.02
(0.12)
(0.03)
(0.02)
‐0.03
‐0.01
NonprofitMFIsincountry
‐0.35**
(0.08)
(0.02)
(0.01)
0.12
0.01
Assets(log)
‐6.38**
(1.30)
(0.36)
(0.22)
Age(log)
‐2.75
‐0.02
0.33
(2.27)
(0.63)
(0.39)
Regulated
‐2.38
‐0.48
‐0.00
(3.41)
(0.95)
(0.58)
1.49
‐2.32*
DepositstoAssets
16.67**
(6.78)
(1.88)
(1.15)
Medium/LargeOutreach
3.02
‐1.12
0.12
(4.21)
(1.17)
(0.71)
Averageloansize(log)
‐4.05
0.70
0.59
(5.42)
(1.50)
(0.92)
1.60
0.90
Fractionwomenborrowers
18.90**
(6.62)
(1.84)
(1.12)
‐0.07
0.09
Poor/povertyinmission
11.83**
(2.84)
(0.79)
(0.48)
1.29
‐0.61
Targetruralclients
‐5.22¥
(3.16)
(0.87)
(0.54)
Lendtoindividuals
‐5.05
‐0.85
1.20
(4.38)
(1.22)
(0.74)
¥
1.86
0.23
For‐profitMFI
3.47
(3.46)
(0.96)
(0.59)
0.55
0.67*
Profitorientation
5.77**
(1.97)
(0.55)
(0.33)
Fixedregioneffects
(yes)
(yes)
(yes)
N
358
0.37
0.09
0.12
“R2”
**p<0.01;*p<0.05;¥p<0.10
aSeeminglyunrelatedregressionmodel
25 TABLE6.SELF‐SUFFICIENCY(SUSTAINABILITY)
Model10a
Sustainability
Pr(F.S.S.>1)
Countryproblems
0.01
(0.01)
Countrypopulation(log)
0.01
(0.16)
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)
Medium/LargeOutreach
0.20
(0.46)
Averageloansize(log)
‐0.49
(0.59)
Fractionwomenborrowers
‐1.46*
(0.74)
Poor/povertyinmission
‐0.66*
(0.31)
Targetruralclients
0.34
(0.34)
Lendtoindividuals
‐0.64
(0.48)
For‐profitMFI
0.06
(0.37)
Profitorientation
‐0.14
(0.21)
Fixedregioneffects
(yes)
N
358
Log‐Likelihood
‐168.78
**p<0.01;*p<0.05;¥p<0.10
aLogisticregressionmodel
26 REFERENCES
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