High Hopes: Experimental Evidence on Saving and H School ... · The mobile money revolution in Kenya and other parts of the developing world has allowed some geographical barriers

High Hopes: Experimental Evidence on Saving and the Transition to High School in Kenya

James HabyarimanaWilliam Jack

Working Paper Series | No. 4 | January 2018

Georgetown University Initiative on Innovation, Development and Evaluation Department of Economics and the McCourt School of Public Policy 306 Reiss Building | Washington, DC 20057 https://gui2de.georgetown.edu/

HighHopes:ExperimentalEvidenceonSavingandtheTransitiontoHighSchoolinKenya1

JamesHabyarimana2andWilliamJack3

January,2018

Abstract

Wereportresultsofarandomizedcontroltrialinwhichparentsofprimaryschoolleaverswereencouragedtoopenaconvenientbankaccountoperatedoveramobilemoneyplatform.Alocksavingsaccount(LSA)wasrandomlypromotedtohalfthetreatmentgroup.Treatmentboostedaccounttake-upby25percentagepoints.Intent-to-treatestimatesshowthatbeingofferedeitheraccountincreasedsavingsonthemobilephone.Totalfinancialsavingsincreasedby3-4times,suggestingaccesstothemobilebankaccountcrowdedinotherformsofsavings.Highschoolenrollmentwas5-6percentagepointshigher–representingaonethirdincreaseforcompliers.

1ThankstoEmilyKayser,AlexBerg,SarahBaran,AlexWendo,andMarthaMutuaforprojectimplementationinKenya,andPitchayaIndravudh,AmirJilani,LayaneElHor,andAliHamzaforresearchassistance.2McCourtSchoolofPublicPolicy,GeorgetownUniversity3DepartmentofEconomics,GeorgetownUniversity

2

1.Introduction

Despitetherecentlargeexpansioninsecondaryschoolenrollment,stillmorethanonein

fivechildrenofsecondaryschoolagearenotenrolled(UNESCO2015).Suchlowenrolment

ratescouldbeduetolowperceivedbenefits(Jensen2010),howeverhighcostshavebeen

foundtobebindinginanumberofcontexts(seeGarlick(2013),Blimpo,Gajigoand

Pugatch(2015),MuralidharanandPrakash(2016),Brudevold-Newman(2017)).Asin

otherdomains(Tarozzi,etal.(2014)),inwhichliquidityconstraintslimitdemand,without

accesstofinancethehopeofgoingtohighschoolisjustthat,ahighhope.4Inthispaper,

weexaminetheextenttowhichfinancialinclusioncanhelpparentsandthechildren

achievesuchgoals.

Accesstoversatileandaffordablefinancialservices,includingpayments,saving,credit,and

insurance,iswidelyseenasanimportantcomponentofstrategiestolifthouseholdsoutof

poverty.5Indeed,theWorldBank’sGlobalFindexreport,basedondatacollectedin

interviewswith150,000adultsacross140countries,concludesthat“Financialinclusionis

criticalinreducingpovertyandachievinginclusiveeconomicgrowth.Whenpeoplecan

participateinthefinancialsystem,theyarebetterabletostartandexpandbusinesses,

investintheirchildren’seducation,andabsorbfinancialshocks.”(Demirguc-Kuntetal

2015).Thisstudyaddstoagrowingbodyofexperimentalevidenceinsupportofalink

betweenaccesstofinancialservicesandproductivityenhancinginvestments.6

Despitearecentexpansioninfinancialinclusion,accesstofinancialservicesinthe

developingworldremainslow,andutilizationconditionalonaccessisoftenlimited.Dupas

etal.(2012)documentbothsupplysideanddemandsidereasons,includinglackof

infrastructure,unreliableservice,hightransactionfees,andlowlevelsoftrustinfinancial

institutions.ThemobilemoneyrevolutioninKenyaandotherpartsofthedeveloping

worldhasallowedsomegeographicalbarrierstoaccesstobeovercome.

4Ozier(forthcoming)usesaregressiondiscontinuitydesigntoshowthatattendanceofsecondaryschoolinKenyaincreasescognitiveachievement.5SeeDupasandRobinson(2013a),BruhnandLove(2014),Prina(2015)andBurgessandPande(2005)forrecentworkonthemicroeconomicimpactsoffinancialaccessondownstreamoutcomes.6Seeforexample,Coleetal(2017),Coleetal(2013),GineandYang(2009),Karlanetal(2014)andMobarakandRozenzweig(2013)ontheroleoffinancialaccessandagriculturalproductiondecisions.

3

Inthispaperwestudytheimpactofaccesstoaconvenientsavingstechnologythatuses

Kenya’smostsuccessfulanddominantmobilemoneyplatform,M-PESA,7operatedbythe

country’slargestmobilenetworkoperator,Safaricom.Launchedin2007primarilyasa

mechanismtoexecutedomesticremittances,M-PESAisnowusedbyover90percentof

Kenyanhouseholds,and,consistentwiththeconclusionsoftheFindexreport,hasbeen

showntohavehadimportantimpactsonrisksharing,poverty,andlaborallocation(Jack

andSuri,2014,andSuriandJack,2016),simplyasaresultoftheremittanceandpayments

functionality.

InNovember2012,themobilenetworkoperatorandalocalbankintroducedamobile

bankaccount(MBA)knownas“M-Shwari”,8thatprovidesmoresophisticatedbanking

services,includingsavingsandcredit,overtheM-PESAplatform.Savingsbalancesearn

interestonaslidingscaleofbetween2%and5%APR,whileone-monthloansattracta

7.5%fee.9Acommitmentsavingsdevice,intheformofalocksavingsaccount(LSA),was

addedtotheMBAsuiteofservicesinJune,2014.10BalancesontheLSAearnabonusof1%

additionalinterest,whichisforfeitediffundsarewithdrawnpriortoanagreedtermof

betweenoneandsixmonths,andearlywithdrawalsareonlybeavailableaftera48-hour

waitingperiod.

WeexaminetheimpactofaccesstotheMBA,andtotheLSA,inaspecificcontextinwhich

userscanbeexpectedtohavesimilarsavingsobjectives.Inparticular,wepromotetheuse

ofthefinancialserviceswithparentsofchildrenhalfwaythroughtheirfinalyearof

primaryschool,andwithafocusontheimportanceofsavingforthetransitiontohigh

schoolsixmonthslater.

Whileschoolfeesinpublicprimaryschools(upto8thgrade)wereofficiallyabolishedin

2003andinpublicsecondaryschools(9thto12thgrades)in2008,parentsstillfacecostsof

supplies,uniforms,andtransportassociatedwiththetransitiontosecondaryschool,as

7“M”isformobile,and“pesa”ismoneyorcashinSwahili.Individualaccountsareheldbythemobilephoneoperator,whichinturndepositscustomers’accountbalancesinasmallnumberofaccounts,underthecompany’sname,withcommercialbanks.8“Shwari”means“calm”inSwahili.9Annualinflationin2014inKenyawasabout7percent.10ToopenanLSA,acustomermusthavethemorebasicMBA,throughwhichtheLSAisaccessed.

4

wellasfeesforextratutoringandacademicsupport.Also,attendanceatprivateboarding

anddayschoolsiscommoninKenya,andindeedincreasedsignificantlyafterfeesfor

publicschoolswerereduced(LucasandMbiti(2012);WorldBank,2009).

Werandomizedpromotionofthetwosavingsinterventions(theMBAandtheLSA)to

parents,plusacontrol,attheschoollevel.Parentsinallgroupswereinformedaboutthe

importanceofcontinuededucation,assupportedbytheMinistryofEducation,andof

savingforthetransitiontosecondaryschool.Weuseadministrativedatafromthemobile

networkoperatorandthebank,alongwithsurveydata,tomeasurechangesinsavings

behaviorandschoolingdecisionsacrossexperimentalgroups.

Karlanetal.(2011)andKastandPomeranz(2014)pointtoproblemsofattentionand

focus,motivatingtheideathatreminderscanbeeffectivetoolstoincreasesavingrates.In

lightofsuchfindings,orthogonaltothesavingsaccounttreatments,werandomizedthe

opportunitytoreceiveSMSmessagesthatwouldremindparticipantstosavein

anticipationofthecostsofhighschool.However,wefindnoeffectoftheremindersonany

savingorbehavioralindicators,suggestingthatattentionchallengesdidnotrepresenta

bindingconstraint,oratleastthattheSMSinterventionasdelivereddidnotrelaxit.11

NearlyallparentshadanM-PESAaccount,oraccesstooneintheirhouseholds,atbaseline,

andwhileroughly25%hadanMBA,virtuallynonehadanLSAatthetime.Afterthe

encouragement,take-upoftheMBAwascloserto60%inthetwotreatmentgroups,while

take-upoftheLSAremainedclosetozerointhecontrolandMBAgroups,butwas28%in

thegrouptowhichitwaspromoted.

Anumberofempiricalstudieshavehighlightedtheimportanceofcommitmentdevicesin

boostingsavingsinthecontextofhyperbolicdiscounting.12Howeverinthecurrentstudy,

whileLSAswereopenedandusedbyanon-trivialshareoftheLSAtreatmentgroup,we

findnosystematicdifferencesinimpactbetweenthetwotreatmentgroups.13Thus,like

11TheSMSreminderresultsareavailableonrequest,butwedonotdiscussthemfurtherinthispaper.12See,forexample,Ashraf,KarlanandYin(2006),Bernheim,RayandYeltekin(2011)andBrune,Giné,GoldbergandYang(2012).13ThismighthavebeenatleastpartlyduetoalessthanseamlessLSAinterface.LSAholders,mostofwhomusedfeaturephones,hadtorememberandenteraUSSDshortcode(*234#6),insteadofbeingabletoaccesstheaccountfromtheM-PESAmenu.

5

attentiondeficitchallenges,commitmentproblemsmightnotbeespeciallybindinginthe

currentcontext.Ontheotherhand,accesstotheMBA,withorwithouttheLSA,had

importanteffectscomparedtothecontrolgroup,eventhoughvirtuallyallcontrolgroup

membersusedM-PESA,themobilemoneytransfer(butnotbanking)service.

First,usingtheadministrativedata,wefindthatsavingsheldonmobilephonesbyparents

inthetwotreatmentgroupsshowsmallbutstatisticallysignificantintent-to-treat

increasesoverthesix-monthperiodrelativetothecontrolgroup.However,thisaverage

effectmasksthefactthatthebalancesofabout66%ofindividualsinthetwotreatment

groupschangedbylessthan50KSh(50UScents)overtheperiod,14comparedwithabout

62%ofthoseinthecontrol.Theshareofdissaverswassimilaracrossallgroups(14-15%),

buttheshareofindividualswhosavedmorethan50KShwas5-6percentagepointshigher

inthetreatmentgroups.

Wealsoestimateeffectsonabroadermeasureoffinancialsavings,includingtraditional

bankaccounts,informalsavingsgroups,andcash,whichshowlargerITTimpacts.Once

again,alargeshareofrespondents–about50%-reportzerochangeinfinancialassets.

However,ofthosewithnon-zerochanges,mostreportdeclinesinfinancialholdingsover

theperiod,whichincludedthewidelycelebratedChristmasfestiveseason,duringwhich

certainunusualexpenses(travelandotherfestivity-relatedconsumption)mightbe

incurred.While5-10%ofindividualsineachgroupreportpositivesavings,30-40%report

dis-savingovertheperiod.Butdis-savingbythedis-saversistwiceashighforthoseinthe

controlgroupasforthoseinthetreatmentgroups.Accesstofinancialservicesmightthus

militateagainstcertaintemptations,consistentwiththefindingsofDupasandRobinson

(2013b),Banerjeeetal.(2015)andforasurveyarticle,EvansandPopova(2014).

Localaveragetreatmenteffectestimatesofchangesinfinancialsavingsareeconomically

meaningful,suggestingthatthosewhoopenedmobilesavingsaccountsinresponsetothe

experimentsaved$US40-50morethantheyotherwisewouldhave.Assignmenttoeither

treatmentarmalsoincreasedaccesstoandutilizationofcredit–weobservea50percent

increase,attheextensivemargin,ofutilizationofcredit.Thesekindsofsavingsrates,and14Fiftyshillingsisabout3%oftheaveragelevelofsavingsbythosewhosaved,and5%oftheaveragedissavingbythosewhodissaved.

6

creditresponses,couldconceivablymakeadifferencetoschoolenrollmentdecisions,in

lightofthemediancostoftransitiontohighschoolreportedatbaselineofaround$US380

acrossallgroups.

Indeed,ourendlinesurveyshowslargeimpactsofassignmenttothesavingsarmson

secondaryschoolenrollmentinJanuary2015.Seventy-twopercentofcontrolgroup

respondentsreportedthattheirchildrenenteredhighschoolin2015,immediately

followingtheintervention,whileinthetreatmentgroups,about78percentwereenrolled.

Correspondingly,theTOTestimatessuggestthatamongstthe25percentofthesample

whowouldnototherwisehaveopenedanMBAaccount,doingsoincreasedthelikelihood

ofenrollmentfromabout62%tonearly83%-anincreaseinenrollmentofone-third.The

TOTimpactoftheLSAwassimilar,increasingtheenrollmentrateofchildrenofparents

whowouldotherwisenothaveopenedacommitmentsavingsaccountfromabout65%to

83%.

Toexplorethemechanismsthatcouldunderlietheselargeenrollmenteffects,wefirst

modeltheimpactofactualsavingsonthelikelihoodofenrollinginsecondaryschool,

instrumentingwithtreatmentassignment.Wefindweakevidencethathigherlevelsof

mobilesavingareassociatedwiththetransitiontohighschool,andstrongerevidencethat

increasesinbalancesintheMBAitselfboostenrollment.Puttingmoneyinthebank,not

justonthephone,appearstobeeffective.

Next,weinvestigateimpactsoftreatmentassignmentonanumberofintermediary

outcomes,includingtestscoresintheprimaryschoolexitexamination,thesourceof

financeusedtocoverthecostsofhighschool,andthetypeofhighschoolattended.

However,wefindlittleevidenceoftreatmenteffectsonthesevariables.

Ourresultssuggestthataccesstoaconvenientfinancialservicewitharelativelysmall

depositinterestratecanbeinstrumentalingeneratinghigherlevelsofsavings,andatleast

inthisexperimentalcontext,inpromotingenrollmentinhighschool.Ourresultsare

consistentwitharecentrandomizedstudybyLipscombandSchechter(2017)where

individualsofferedmobilesavingsaccountsaremorelikelytopurchasesubsidized

desludgingservicesinSenegal.Thenextsectiondocumentsourrecruitmentactivitiesand

7

baselinedata.Section3reportsoveralltreatmenteffectsonsavings,whilesection4

documentssavingspatternsandheterogeneousresponses,andsection5reportsimpacts

onschoolingoutcomes.Section6concludes.

2.Recruitmentanddata

InJuneandJulyof2014,halfwaythroughtheKenyanschoolyear,wevisited337primary

schoolsinthreecounties,15andconductedmeetingsattendedbyatotalof4,802parentsof

eighth-gradestudents,ofwhom4,673consentedtotakepartinthestudy.Ofthosewho

consentedtotakepart4,082,or85percent,hadamobilephonewithanM-PESAaccount.

Ofthese,some4,020(98.5%)gaveAdministrativeDataSharingconsent(ADSconsent)–

thatis,theyconsentedtoallowthemobilenetworkoperatorandthebanktosharetheir

administrativeaccountdatawiththeresearchteam.

Randomizingattheschoollevel,wepromotedadoptionanduseofthemobilebankaccount

(MBA)amongstonegroupofparents,andoftheLockSavingsAccount(LSA)amongst

another.Thenumberofparentsandschools(inparentheses)ineachofthethreeprimary

experimentalcellsareshowninTable1,includingincolumn(1)allthosewhoconsentedto

takepart,incolumn(2)thosewhoalsogaveADSconsent,andincolumn(3)thosein

column(2)whowereinterviewedatendline.

Parentmeetingswereheldattheschools,duringwhichmembersofallexperimental

groups,includingthecontrol,werepresentedwiththesameinformationaboutthe

importanceofcontinuededucation,andofsavingforthetransitiontosecondaryschool.

Aspartofthebaselinesurvey,weaskedparentstorecordtheexpectedcostofsending

theirchildtosecondaryschool,andtosetanassociatedsavingsgoalwiththiscostinmind.

ThoseintheMBAtreatmentgroupwereshownhowtoopenbothanM-PESAaccountand

15ThecountieswereKisumu,Nyeri,andKilifi.AnotherRCTwasbeingadministeredindependentlybythesamePIsinthesamesetofprimaryschools.ThatprojectexaminedtheimpactofvariousinterventionsaimedatimprovingthedeliveryofschoolWASH(water,sanitationandhygiene)services,andinvolvedstudentsingradesbeloweighthgrade.Therandomizationsinthetwostudieswereorthogonal.

8

anMBA(iftheydidn’talreadyhavethem),andhowtheycouldbeused.ThoseintheLSA

groupwereinstructedadditionallyonhowtoopenandoperatetheLSA.16

Table2,panelsA,B,andC,reportbalancetestsforbaselinerespondent,child,andschool

level,characteristicsrespectivelyacrosstheexperimentalgroups.Forthoseself-reported

characteristicsinthebaselinesurvey,weusethesampleof4,673whoconsentedtotake

part.Forinformationonvariablesthatcouldonlybediscernedfromtheadministrative

phonedata,weusethesmallersampleof4,020whograntedADSconsent.17Table3

presentsbaselinecharacteristicsbyeachofthetwosavingstreatmentgroupsandthe

control,andpairwiseandthree-waybalancetests.

Sixty-eightpercentoftheparentsatthemeetingswerewomen,andtheaverageageof

respondentswas44.Sixty-twopercenthadcompletedprimaryschool,butonly19percent

hadfinishedsecondaryschool.Ninety-threepercentownedamobilephone,only2percent

didn’thaveaccesstoone,andnearlyallofthe90percentofthesamplewithaSafaricom

SIMcardalsohadanM-PESAaccount.Therewerenearly5childrenperhousehold,halfof

whomweregirls.Everyonereportedexpectingtheirchildrentogoontosecondaryschool,

andtheaverageexpectedcostofdoingsowasaboutUSD400,themedianvalueofwhich

wasUSD380.Schoollevelattributesarealsoreported,andarebalanced.

Werevisitedtheprimaryschoolsandsuccessfullyconductedface-to-faceendlinesurveys

of3,994ofthe4,673originalsampleofrecruitedparents.Wefollowedthisupwithphone

surveysof854oftheremainingparticipants,foratotalre-contactrateof85.5percent.The

re-contactrateamongstthosewhogaveADSconsentwas87.5percent.

16UponopeningaLockSavingsAccount,acustomerchoosesthematurityoftheaccount,anintegernumberofmonths,afterwhichthefundscanbeaccessedwithoutpenalty.However,inourstudy,weworkedwiththebanktoallowaparticulardatetobespecified,andactivelyencouragedrespondentsintheLSAtreatmentgrouptochooseamaturitydateofJanuary5th,2015,fortworeasons.First,studentstypicallybeginsecondaryschoolneartheendofJanuaryeachyear,sohavingthefundsavailableafewweeksaheadofthestartofclassescouldhavebeenvaluableinfinancingthetransition.Andsecond,amaturitydateafterChristmas–apopularholidayandgift-givingtimeinmuchofKenya(althoughlesssoinKilifi,whichhasasizeableMuslimpopulation)–wouldensurethatfundswouldbeavailableforschoolingexpenses,unlesstheyhadbeenwithdrawnwithpenalty.Ofthe399respondentsintheLSAarmwhoopenedLSAs,306choseamaturitydateofJanuary5th,2015.

17Similarly,inourregressionsinvolvingbothbaselineandendlinedata,weusethesampleof4,673individualswhoconsentedtotakethebaselinesurvey,withattritedvaluestreatedasmissing.Inanyregressionsinwhichweuseadministrativedata(withorwithoutbaselineorendlinesurveydata),weuseinformationonthesmallersampleof4,020,againtreatingattritedindividualsasmissing.

9

Table3reportsattritionbyexperimentalarmamongstboththefullbaselinesample,and

forthosewhogaveADSconsent.Inbothcases,attritionrateswere3-5percentagepoints

higherinthetreatmentgroupsthaninthecontrol.InouranalysisbelowwereportManski

boundsontreatmenteffectstoaccountforthedifferentialratesofre-contact.

Take-upratesofmobilefinancialservicesacrossthethreesavingsarmsarereportedin

Table4usingadministrativedatafromthe4,020respondentswhogaveADSconsent.We

reportratesatwhichMBAsandLSAswereopenedineachofthethreeexperimental

groupsasofJanuary5th,2015,sixmonthsaftertheintervention.About34%ofthecontrol

grouphadanMBAbythattime,whilethesharesofthetwotreatmentgroupswithan

accountwere24-25percentagepointshigher.Virtuallyno-oneinthecontrolorMBA

treatmentgrouphadanLSAbyearly2015,while27%oftheLSAtreatmentgroupdid.

Thus,ourencouragementdesignhadnon-negligibleimpactsonadoptionofthetwobank

products,asintended.

Belowwereportimpactsoftheexperimentalinterventionsonanumberofoutcomes.In

thissection,wediscusstheseoutcomesandtheirmeasurementinmoredetail,

distinguishingbetweensavingsoutcomesontheonehand,andthoserelatedtoschooling

decisionsandbehaviorontheotherhand.

Wemeasure“mobilesavings”usingadministrativedataasthenetchangeintotalbalances

heldonindividuals’M-PESAaccounts,regularMBAaccounts,andLSAaccounts.Alongwith

theLSA,theMBAincludedbothatransactionalsavingsaccountaswellasaloanaccount.

Wethusreportbothgrosssavings(thetotalchangeinbalancesonallmobilesavings

accounts)andnetsavings(grosssavingsminusnetincreaseinoutstandingdebtinthe

MBAloanaccounts).18

Intheendlinesurveysweaskedindividualstoestimatethechangeinvalueofanyother

financialassetstheyheld,includingmobilemoneyaccountsheldwithothermobile

operators,otherbankaccounts,depositswithSACCOs,ROSCAs,etc.,andcashheldathome

18EligibilityforloansontheMBAisbasedonacreditscoregeneratedfromdataonusageofmobilephone,mobilemoney,andMBAactivitylevels.Loanproceedsaretransferredtothecustomer’sM-PESAaccount,andtheliabilityrecordedinherloanaccountwiththebank.

10

orwithfriends.Addingthesesavingstomobilesavingsgivesusavalueofwhatwereferto

as“financialsavings”.19

Ourprimaryschoolingoutcomeofinterestisenrollmentinhighschool,whichweelicitin

theendlinesurvey.Weaskparentsiftheirchildhadbeenenrolledinhighschoolbythe

timeofthesurvey(whichtookplaceatleastonemonthafterthebeginningoftheschool

year),whatkindofschool(private/public,co-ed/singlesex,andwhetheritisanational,

county,district,orlocalschool),thecostofattendance,andotherattributes.Wealso

collectinformationonresultsoftheend-of-primaryschoolexaminations,whichdetermine

eligibilityforentranceintothedifferenttypesofsecondaryschool,alongwithparents’

expectationsabouttheirchild’sperformance,andparentaldecision-makingroles.

Theparentsofchildrenwhoenrolledinhighschoolwereaskedhowtheyfinancedthe

costsofthetransition,withoptionsincludingdrawingonfinancialsavings,thesaleof

assets,andborrowingfromfriendsandrelativesorfrommoreformalsources.

3.Impactsonsavings

Inthissection,wepresentourmainresultsonparentalsavingsoverthecourseofthe

secondhalfoftheirchild’sfinalyearofprimaryschool.Wheninvestigatingtheimpactof

havingaccesstotheMBA,weadopttwoapproaches:firstweuseassignmenttoeitherthe

MBAorLSAtreatmentgroup,comparedwithassignmenttothecontrolgroup;andsecond,

wecomparethoseassignedjusttotheMBAtreatmentgrouponlywiththecontrol.When

estimatingtheimpactofthelocksavingsaccount,wecomparethoseassignedtotheLSA

treatmentwiththecontrolgroupontheonehand,andwiththeMBAtreatmentgroupon

theother.Thelastcomparisonallowsustodeterminewhatmarginaleffect,ifany,access

tothecommitmentdevicehadonsavingbehavior.

19Wealsoaskedrespondentstoreporttheirownership,purchase,andsalesofrealassetsoverthesix-monthperiodbetweenrecruitmentandthebeginningoftheschoolyear,includingitemssuchaslivestock,householddurables,andotheritems.Thismeasurehasveryhighvarianceandweexpectsuffersfromconsiderablemeasurementerror,dueinparttothedifficultyrespondentslikelyhadinestimatingthevalueofassetsheldatbaseline.

11

Threedimensionsofsavingaredistinguishedinthetables:grossvsnet(toaccountfor

loanstakenoutontheMBAplatform);mobilevsfinancial;andshort-term(thatis,until

January5th,2014,justbeforethebeginningofthenewschoolyear)and“long-term”(until

January31st,bywhichtimehighschooltransitionalexpensesareexpectedtohavebeen

incurred).20Withinthecategoryofmobilesavings,wealsoestimateimpactsonsavings

balancesheldatthebank,thatisintheMBAorLSA,butnotontheM-PESAaccount,asit

reflectsamoveintointerestbearingdepositswithinthemoreformalbankingsector.

(a) Impactsonmobilesavings

Table5presentsestimatesoftreatmenteffectsonshort-termsavingsheldonmobile

accounts,ITTestimatesintheupperpanel,andtheTOTestimatesinstrumentingwith

treatmentassignmentinthelowerpartofthetable.Thefirstfourcolumnsmeasure

impactsongrosssavings,andthemiddlefouronnetsavings.Thefinalfourcolumnsshow

changesingrossbalancesheldatthebank,aggregatedacrossboththeMBAandLSA

accounts.

InColumn(1),theaveragetreatmenteffectsofaccesstotheMBAacrossbothgroupsare

reported.TheITTandTOTestimatesarebothpositive,butimprecise.InColumn(2),

thoseassignedtotheLSAarmareexcluded,andtheimpactofassignmenttotheMBA

treatmentgroupcomparedwiththecontrolisestimated.Beingencouragedtoopen,and

actuallyopening,anMBAhaveeffectsonmobilesavingsthataresignificantatthe10

percentlevel.Thosewhocomplywiththetreatmentaccumulate1,093KSh(aboutUSD11)

morethattheywouldhaveotherwise.Forcomparison,thecorrespondinglevelofsavings

ofcomparablecompliersinthecontrolgroup,reportedinthelowerpartofthetable,is253

KSh.Treatmentgroupcompliersthussaveaboutfourtimesasmuchontheirphonesas

similarindividualsinthecontrolgroup.Theinterest-bearingbankaccountitselfseemsto

20Ourdistinctionbetweenshort-andlong-termfinancialsavingsisimperfect.Wecanusetheadministrativedatatocalculatemobilesavingsuptoanyenddate;butthenon-mobilecomponentoffinancialsavingsisreportedasofthetimeoftheendlinesurvey,onetotwomonthslater,anddoesnotdifferentiatebetweenresourcesaccumulateduptoJanuary5thandJanuary31st.Thusshort-termtotalfinancialsavingsareinfactamixofchangesinshort-termmobileandlongertermnon-mobilebalances.

12

beboostsavings,eventhoughtheinterestrateislow,andsavingonM-PESAisjustas

convenient.21

ExcludingtheMBAgroup,impactsofassignmenttotheLSAgroupvis-à-visthecontrol

(Column(3))aresmallerandinsignificant.ThefourthcolumncomparestheMBAandLSA

groupsdirectly,excludingthecontrol.AlthoughthepointestimatesonLSAassignment

andtreatmentarebothnegative,theyareinsignificant,anditisnotpossibletodistinguish

betweentheeffectsoftheLSAandtheMBA.

NetmobilesavingsinColumns(5)to(8)exhibitverysimilareffectsizeswiththesame

statisticalproperties,althoughtheTOTestimateusingbothtreatmentgroups,ofthe

impactofopeninganaccount,shownincolumn(5),cannowbedistinguishedfromzeroat

the10percentlevel.

Finally,Columns(9)to(12)showaclearshiftofsavingsintotheformalbankaccount.

ComparingthepointestimatesinColumns(1)to(3),whichareabouthalfthesizeofthose

inColumns(9)-(11),wecaninferthatroughlyhalftheincreaseinbankbalancesisdueto

“new”savings,whilehalfisduetoashiftfromthemobilemoneyaccounttothebank

account.

InAppendixTable1wereportLeeBoundsontheestimatesinTable5,accountingfor

attritionfromtheendlinesurvey.Notsurprisingly,therangeofcoefficientsoftenincludes

zero,butingeneralthemagnitudessuggestattritionisunlikelytohavebiasedourresults

toaquantitativelylargedegree.

Table6reportsthesamesetofregressionsfor“long-term”mobile-phonesavings,upto

January31.AllcoefficientsinColumns(1)through(8)aremuchsmallerandhighly

insignificant.ItthusappearsthattotheextentexposuretotheMBAand/orLSA

treatmentsincreasedmobilesavings,theseincrementsweredepletedinthe2to3weeks

beforethebeginningofthenewschoolyear.Evenso,columns(9)through(12)suggest

thatamongstthosebalancesthatweremaintainedonmobileaccounts,ashiftfromthe

21Thiscouldbedueatleastinparttothedesiretobuildupahistoryofbanksaving,soastobecomeeligibleforalargerloan,althoughthecreditscoretakesintoconsiderationM-PESAbalancesaswellasthoseontheMBA.

13

mobilemoneyplatform,M-PESA,totheformalbankaccountscanbeobserved.TheTOT

estimatessuggestthatbeinginducedtoopenanMBAincreasedbankaccountsavingby

between1,000and1,500KSh(USD10-15),andbeinginducedtoopenanLSAincreased

thembyabout500KSh(USD5).

Beingsubjecttothemobilebankaccountencouragementthrougheitherarmalso

increasedthelikelihoodthatparentswouldtakeoutaloanontheplatform.Thisis

importantasitprovidesanadditionalsourceoffinancingforeducationexpenditures,

althoughunderstandingwhetheraccesstocreditcrowdsoutsavingisofcoursealsoof

interest.Table7showsthatbetweenrecruitmentandJanuary5th,2015,parentsineachof

thetreatmentgroupswerebetween3and5percentagepointsmorelikelytodrawonan

MBAloan,comparedwithan8percentrateinthecontrolgroup(seeColumns(1)-(4)).

TheTOTestimatessuggestthatbetween12and18percentofuserswhoopenedan

accountasaresultoftheencouragementtookadvantageofthecreditoption.Similarly,the

averagenumberofloanswashigherinthetreatmentgroups(Columns(5)-(8)),andthe

amountsborrowedwerehigher,butestimatedwithlessprecision(Columns(9)-(12)).

(b) Financialsavings

Itisimportanttoassesstheimpactofaccesstobankaccountsoverthemobileplatformon

abroadermeasureofsavings,soastodistinguishbetweensimpleshiftsinassetholdings

andincreasesinaccumulatedresources.Tothisend,wecombineourdataonmobile

savingswithinformationprovidedintheendlinesurveyonotherfinancialsavings,suchas

holdingsinotherbankaccounts,“underthemattress”savings,SACCO(savingsandcredit

cooperative)andChama(micro-savingsgroups)accountbalances,advancepurchases,and

savingswithfamilyorotherentities.

Asmentionedabove,oneshort-comingofourdataisthatthesenon-mobilefinancial

savingsamountswereelicitedatthetimeoftheendlinesurvey,whichtookplacein

February/March,afterthebeginningoftheschoolyear.Weknowalreadyfromthemobile

savingsthatsignificantactivityoccurredduringthemonthofJanuary,asbalanceson

mobileaccountsweredepleted.Thesamecouldofcoursebetrueforotherfinancialassets.

14

Wethusconstructtwooutcomemeasures,inadditiontothenon-mobilefinancialsavings

variable.Inthefirst,weaddnon-mobilesavingsreportedintheendlinesurveytoshort-

termmobilesavingsaccruedthroughJanuary5th,drawnfromadministrativedata;andin

thesecond,weaddreportednon-mobilesavingstolong-termmobilesavings,accrued

throughJanuary31st.

IftheobservedmovementsoutofmobilesavingsinJanuarywerematchedone-for-oneby

increasesinnon-mobilefinancialbalances,thenthecombinationofthelatterwithmobile

savingsthroughJanuary31stwouldprovideareliableindicatorofbothshort-andlong-

termfinancialsavings.Ontheotherhand,itseemsunlikelythatfamilieswouldnecessarily

engageinthiskindofrebalancingbehaviorspecificallyinthemonthofJanuary.

Ifinsteadtheevolutionofusers’non-mobilesavingsbalancesfollowedasimilarpatternto

thatoftheirmobilesavingsaccounts,thenthesumofnon-mobilesavingsandmobile

savingsonJanuary31stwouldprovideareasonableestimateoflongtermsavings,while

thesumofnon-mobilebalancesandmobilesavingsonJanuary5thwouldunder-estimate

short-termsavings.Wemightfurtherspeculatethat,undertheassumptionthatthetwo

kindsofsavingsmoveintandem,thattotalshort-termfinancialsavingscouldbecalculated

asthesumofmobilesavingsasofJanuary5thandnon-financialsavingsmultipliedbythe

ratioofshort-tolong-termmobilesavings.

Table8reportsITTandTOTestimatesoftheimpactoftreatmentonnon-mobilesavings

(Columns(1)through(4))andfinancialsavingsasmeasuredbythesumofnon-mobile

savingsandmobilesavingsthroughJanuary5th(Columns(5)through(8))andmobile

savingsthroughJanuary31st(Columns(9)through(12)).Imprecisionhampersourability

todiscernstatisticallysignificanteffects,althoughthepointestimatesinallcasesare

positiveandeconomicallymeaningful.

FocusingfirstonColumns(5)through(8),whichreportwhatarelikelyunder-estimatesof

totalshort-termfinancialsavingsgrossofloanproceeds,wedocumentmeaningful

responsestoassignmenttobothtreatmentgroups,withITTestimatesofbetween940and

over1,400KSh.ThecorrespondingTOTestimatesareintherangeof3,600tonearly4,800

KSh(aboutUSD50).Comparedwiththe(negative)estimatedsavingsofcompliersinthe

15

referencegroup,theseestimatessuggestthatforthosewhoopenanaccountinresponseto

eithertheMBAorLSAencouragement,theincentivetodissavethroughJanuary5this

effectivelyeliminated.

FromTables5and6,theratioofthepointestimatesofshort-tolong-termmobilesavings

impactsofthetwotreatmentgroupscombined,forexample,isabout15.Ifnon-mobile

financialsavingsweretofollowasimilartemporalpatterntomobilesavings,theshort-

termimpactoftreatmentonthetreatedwouldbeseveralhundreddollars–enoughto

covermostifnotallofthecostoftransitionofhighschool.

4.Savingspatternsandheterogeneousresponses

Tobetterunderstandthepatternofsavingsacrossindividuals,Figures1and2illustrate

thepatternsofshort-termgrossmobilesavingsbehaviorandshort-termfinancialsavings

behavior(asdefinedabove)ofmembersofthecontrolgroupandthecombinedMBAand

LSAtreatmentgroups.22About15percentofindividualsineachgroupexhibitmobile

dissaving,whilefully40percentshowreductionsinfinancialsavings.Ontheotherhand,

about20percentshowpositivemobilesavings,andasimilarshareshowpositivefinancial

savings.

Thetreatmenteffectsarereflectedindifferencesbetweenthecumulativesavings

behaviors,althoughpoint-wiseinterpretationdependsonastrongmonotonicity

assumption.Nonetheless,undersuchanassumption,wewouldinferthatindividualsinthe

combinedtreatmentgroupswhowouldotherwisehavesavedapositiveamountontheir

phones,savemore;andthosewhootherwisewouldhavereducedtheirmobilebalances,

reducethemless.

Whenitcomestothebroaderconceptoffinancialsavingshowever,alltheactionappears

tobeamongstthedis-savers.Againassumingmonotonicity,exposuretotheMBAand/or

22Inthecontrolgroup,thegraphisconstructedbyfirstorderingindividualsbythenetchangeinbalancesintherelevantaccounts.Foralargeshare,thischangeiszero.Forthosewithnegativechanges,wecalculatethecumulativereductionmovingtotheleft,andforthosewithpositivechanges,thecumulativeincreaseiscalculatedmovingtotheright.Theresultingvaluesarenormalizedbythenumberofindividualsinthecontrolgroup.AsimilarexerciseisperformedforthoseinthecombinedCBAandLSAtreatmentgroups.

16

LSAappearstoinducenochangeinpositivefinancialsavingbehavior,butmeaningful

reductionsindissavingfromfinancialassets.

TheseobservationsarequantifiedinthequantileregressionsreportedinTable9.Inthe

firstthreecolumnsweobservepositiveimpactsofassignmentatthe10thand90th

percentilesofthedistributions,withstatisticalsignificanceatthetopend.Theeffectatthe

medianiszero.Forfinancialsavings(columns4-6),theestimatesatthemedianandthe

90thpercentileareallsmall,buttheimpactsatthebottomendarelarge,andinthecaseof

LSAtreatmentarm,highlysignificant.

Table10reportsmarginalresultsoforderedlogitregressionsexploringtheimpactof

treatmentassignmentonthelikelihoodofanindividualsavinganegative,zero,orpositive

amountoverthesix-monthperiod.Usingthepredictedprobabilityestimatesforeach

outcome,wefindthatassignmenttotheMBApromotionreducesthelikelihoodof

dissavingbyjustunder4percentagepointsandincreasesthelikelihoodofpositivesavings

by4percentagepoints.AssignmenttotheLSApromotionreducesthelikelihoodof

dissavingbyjustover5percentagepointsandincreasesthelikelihoodofpositivesavings

bynearly6percentagepoints.

Tables11through13reportestimatesofheterogeneoustreatmenteffectsalonganumber

ofdimensions.First,weaskiftheidentityofthesurveyrespondent,inparticularwhether

s/heistheprimaryfinancialdecision-makerinthehousehold,isassociatedwithany

differenceinimpact.Whenconsideringgrossornetmobilesavings(Columns(1)and(2)),

theinteractioneffectbetweendecision-makerstatusandtreatmentassignmentisvery

smallandinsignificant.Theeffectsonfinancialsavings(Column(4))aresimilarly

imprecise.However,thereappearstobeasignificantlylargerimpactoftreatmenton

savingsinthebankaccountitselfwhentherespondentisthedecision-maker.Thiscould

reflecttheimportanceofin-personexplanationaboutthefeaturesoftheMBAandLSA.

Table12askswhethertheimpactofaccesstoformalbankingservicesdiffersfor

householdsinwhichwomenaretheprimarydecisionmakersregardingfinancialmatters.

WereportITTestimatesoftheimpactofassignmenttoeithertreatmentarmonbothgross

andnetmobilesavingsusingadministrativedata.WhileaccesstoM-PESAitselfhasbeen

17

showntobeespeciallybeneficialforpoorruralwomeninKenya(seeSuriandJack,2016),

inthecurrentexperimentalsettingwefindreasonablystrongevidencetoindicatethatthe

savingsofhouseholdsinwhichthemalemadefinancialdecisionsweremoreresponsiveto

improvedaccesstodigitalfinancialservicesthanwerethoseofhouseholdsinwhich

womenheldtheelectronicpursestrings.

Finally,Table13asksifhouseholdsinwhichtheparentsassessedtheirchildrentohave

above-averageschoolperformancerespondeddifferentlytoothers,perhapsbecausethe

prospectofsecondaryschoolenrollmentwasmoresalient,andthereturnstofurther

schoolinglarger.Infacthowever,thereislittleevidenceofheterogeneityonthis

dimension.

5.Impactsonschooling

Intheendlinesurvey,whichtookplaceafterthebeginningofthefollowingschoolyear,we

collectedinformationfromrespondentsregardingtheirchildren’senrollmentinsecondary

school.Columns(1)through(3)ofTable14reportITTandTOTestimatesoftheimpactof

thetwotreatmentscombined,andseparately.Seventy-twopercentofparentsinthe

controlgroupreportedthattheirchildrenwereenrolledinsecondaryschool.PanelA

reportsITTimpactsof5-6percentagepoints,whichtranslateintoTOTeffectsofbetween

18and24points.Comparedwithcompliersinthecontrolgroup,about60percentof

whomweestimateenrolledinsecondaryschool,theseTOTestimatessuggestthatopening

abankaccountisassociatedwitha27to40percentboosttoenrollment,whichreached83

percentforbothgroups.

Toinvestigatetheselargeimpactsonthetransitiontohighschool,weaskifthe

inducementtosavemorecausallyincreasestheprobabilityofenrolling.Inparticular,in

Table15weregressenrollmentoutcomesonactualmobilesavings,instrumentingwith

assignmenttotreatment.Columns(1)through(4)followthesamepatternasinprevious

tables,thefirstthreecomparingoutcomesineitherbothoroneofthetreatmentgroups

withthecontrol,andthefourthcomparingoutcomesintheLSAgroupwiththoseinthe

18

MBAtreatment.SavingsaremeasuredinthousandsofKenyanshillings(tensofUS

dollars).

ThecoefficientsongrossornetmobilesavingsinColumns(1)-(3)ofPanelsAandBare

uniformlypositive,althoughmostlyimpreciselyestimated,butpointtowardsa20-30

percentagepointincreaseinthelikelihoodofenrollinginsecondaryschoolforevery

thousandshillingincreaseinbalances.Thereisagainnoapparentdifferencebetweenthe

MBAandLSAeffects(Column(4)).PanelCshowsamorerobustrelationshipbetween

increasesinbankaccountbalancesandschoolenrollment,suggestingoncemorea

substantiveimpactoftheuseofformalbankingservicesonparentalbehavior.

InPanelD,theimpactofhighertotalfinancialsavingsonenrollmentisassessed,usingthe

definitionofendlinenon-mobilefinancialsavingsplusshort-termmobilesavingsasof

January5th.Theseregressionssufferfromweakinstrumentation,andyieldsmallerbutstill

positive,ifimpreciseestimatesoftheimpactofadditionalsavingonhighschool

enrollment.

Whatmechanismliesbehindtheselargeeffectsonschoolenrollment?Weinvestigatea

numberoffinancialindicatorstoprobethisquestion.InTable16wereportITTandTOT

estimatesoftreatmentonthecostofhighschoolreportedatendline(thecostfornon-

enrolleesistreatedaszero).IntheITT,thoseintheLSAgroupappeartohavechosen

schoolsthatwereonaverageabout10percentlesscostlythanthoseinthecontroland

MBAgroups,significantatthe10percentlevel(Columns(3)and(4)).TheTOTestimates

oncompliersaresomefourtimesaslarge,andare25percentofthecostofschools

attendedbycomparisongroupcompliers–thatis,similarindividualsinthecontroland

MBAgroups.TheimpactofassignmenttotheMBAgroupismuchsmallerandstatistically

insignificant.However,thefactthatourenrollmenteffectswerelargerforassignmentto

theMBAgroupsuggestscautioninattributingthoseenrollmenteffectstoselective

targetingoflowercostschools.

Wenextaskedrespondentshowtheyfinancedthecostsofhighschool,asreportedinTable

17.Ofcourse,responsesareonlyrecordedforrespondentswithenrolledchildren,sothe

reportedmeansinTable17reflectbothselectionandtreatmenteffects.Onlyoneofthe12

19

coefficientsissignificant(andthenatthe10percentlevel),andallareeconomically

irrelevant,sotreatmentassignmentappearsnottohaveaffectedhowparentsfinance

school.

Finally,weaskiftreatmentassignment,ortake-upofMBAandLSAaccounts,couldbe

associatedwithstudentsfocusingmoreonafuturethatincludedattendanceathighschool,

higheraspirations,andgreatereffortintheirfinalexamsatthecompletionofprimary

school.23Self-reportedexamscores,howevershownosignificantrelationshiptotreatment

assignment(Table18).

6.Conclusions

Financialinclusionthroughmobiletechnologycouldholdpromiseforexpandingthe

opportunitiesofthepoortosaveandinvest.Inthispaper,wehavefoundthatatleastfor

parentsoffinalyearprimaryschoolchildreninKenya,promotingmobilephone-based

savingsaccountsappearstohaveledtoincreasesinsavingsheldonthemobilephone,and

tolargerincreasesinfinancialsavingsaggregatedacrossinstruments.

Incontrasttosomeearlierstudies,wefindlittleevidencethatincreasesinsavingaredue

toattentionproblemsontheonehand,asourSMSreminderinterventionhadlittleeffect,

ortocommitmentissuesontheother,sincethemarginalimpactofalockedsavings

accountoverandaboveasimplebankaccountwasgenerallyeconomicallyandstatistically

insignificant.Instead,the(admittedlylow)interest-bearingfeatureofthebankaccount,

andtheaccesstoshort-termcreditthatitprovided,bothdeliveredoveraneasilyaccessible

platform,werelikelyenoughtonudgepeopletowardssavingmore,oratanyratedissaving

less.

Amongsttheroughlyone-quarterofoursamplewhoopenedaccountsinresponsetothe

encouragementtreatment,mobilesavingsoverasix-monthperiodincreasedbyabout

USD10.Undersomereasonableimputationassumptionsregardingnon-mobilefinancial

assets,ourresultssuggestthattotalfinancialsavingsbythosewhorespondedtothe

23AllschoolstudentsinKenyatakeanationalexaminationattheendofprimaryschool,resultsonwhichdeterminethekindsofsecondaryschoolstheywillbeeligibletoattend.

20

encouragementcouldhaveincreasedenoughtocovermostofthecostsoftransitioning

fromprimaryschooltohighschool.

Indeed,ourmoststrikingresultisthattreatmentassignmentisassociatedwithhigher

ratesofhighschoolenrollment,ontheorderof5-6percentagepointsonanITTbasis,and

18-24pointsfortheTOT.Theprecisemechanismsbywhichtheseimpactsaremediated

arelesseasytopindown.Accountingforendogeneity,highersavings,especiallyinthe

mobilebankaccount,appeartoincreaseenrollmentinhighschool,but,notwithstanding

issuesoffungibility,parentsdon’tnecessarilyreportusingthesavingstopaytuitionand

othercosts.Thereislimitedevidencethattreatmentgrouphouseholdschoseless

expensiveschoolsfortheirchildren,andnoevidencethatfinancialinclusionaffects

aspirationsinawaythatmightinducestudentstoachievehigherend-of-primaryschool

testscores.

Nonetheless,accesstoamobilebankaccount,bymovingtheneedleofsecondaryschool

enrollment,appearstobeaninnovationthatcouldbrightentheprospectsoflargenumbers

ofchildren,givingthemhighhopesforthefuture.

21

References

Ashraf,Nava,DeanKarlanandWesleyYin(2006):“TyingOdysseustothemast:evidence

fromacommitmentsavingsproductinthePhilippines,”QuarterlyJournalofEconomics,pp.

635-672.

Banerjee,Abhijit,EstherDuflo,RachelGlennersterandCynthiaKinnan(2015):“The

miracleofmicrofinance?Evidencefromarandomizedevaluation,”AmericanEconomic

Journal:AppliedEconomics,7(1):22-53.

Blimpo,M.P.,O.Gajigo,andT.Pugatch(2015):“FinancialConstraintsandGirls’Sec-

ondaryEducation:EvidencefromSchoolFeeEliminationintheGambia,”IZADiscussion

Paper,(No.9129).

Berheim,B.Douglas,DebrajRayandSevinYeltekin(2015):“Povertyandself-control,”

Econometrica,83(5),pp.1877-1911.

Brudevold-Newman,Andrew(2017):“TheImpactsofFreeSecondaryEducation:Evidence

fromKenya.”WorkingPaper.

Bruhn,MiriamandInessaLove(2014):“TheRealImpactofImprovedAccesstoFi-nance:

EvidencefromMexico.”JournalofFinance59(3):2807–2833.

Brune,Lasse,XavierGiné,JessicaGoldbergandDeanYang(2016):“FacilitatingSavingsfor

Agriculture:FieldExperimentalEvidencefromMalawi,”EconomicDevelopmentand

CulturalChange,UniversityofChicagoPress,vol.64(2),pp.187-220.

Burgess,RobinandRohiniPande(2005):“DoRuralBanksMatter?Evidencefromthe

IndianSocialBankingExperiment.”AmericanEconomicReview95(3),780–795.

ColeS.,Giné,X.Tobacman,J.Topalova,P.Townsend,R.andVickery.J(2013):“Barriersto

householdriskmanagement:EvidencefromIndia.”AmericanEconomicJournal:Applied

Economics5:104–35.

ShawnCole,XavierGiné,JamesVickery(2017):“HowDoesRiskManagementInfluence

ProductionDecisions?EvidencefromaFieldExperiment.”TheReviewofFinancialStudies,

Volume30,Issue6,Pages1935–1970

22

DeanKarlan,MargaretMcConnell,SendhilMullainathan,JonathanZinman(2016):“Getting

totheTopofMind:HowRemindersIncreaseSaving,”ManagementScience62(12),pp.

3393-3411.https://doi.org/10.1287/mnsc.2015.2296

Demirguç–Kunt,Asli,LeoraKlapper,andDorotheSinger(2015).“TheGlobalFindex

Database2014:MeasuringFinancialInclusionaroundtheWorld.”WorldBankPol-icy

ResearchWorkingPaper#7255.

Dupas,Pascaline,SarahGreen,AnthonyKeats,andJonathanRobinson(2012):“Challenges

tobankingtheruralpoor:EvidencefromKenya’sWesternProvince,”

http://www.nber.org/chapters/c13363.pdf

Dupas,PascalineandJonathanRobinson(2013a):“Savingsconstraintsand

microenterprisedevelopment:EvidencefromafieldexperimentinKenya,”American

EconomicJournal:AppliedEconomics,5(1),pp.163-192.

Dupas,PascalineandJonathanRobinson(2013b):“WhyDon’tthePoorSaveMore?

EvidencefromHealthSavingsExperiments.”AmericanEconomicReview103(4):1138–

1171.

Evans,DavidK.;Popova,Anna(2014):“Cashtransfersandtemptationgoods:areviewof

globalevidence,”PolicyResearchworkingpaper;no.WPS6886;ImpactEvaluationseries;

no.IE127.Washington,DC:WorldBankGroup.

http://documents.worldbank.org/curated/en/617631468001808739/Cash-transfers-and-temptation-

goods-a-review-of-global-evidence

Garlick,R.(2013):“HowPriceSensitiveisPrimaryandSecondarySchoolEnrollment?

EvidencefromNationwideTuitionFeeReformsinSouthAfrica,”WorkingPaper.

Giné,Xavier,DeanKarlanandJonathanZinman(2010):“Putyourmoneywhereyoubuttis:

Acommitmentcontractforsmokingcessation,”AmericanEconomicJournal:Applied

Economics,2(4),pp.213-235.

Giné,X.,andYang.D.(2009):“Insurance,credit,andtechnologyadoption:Field

experimentalevidencefromMalawi.”JournalofDevelopmentEconomics89:1–11.

23

Jensen,R.(2010):“The(Perceived)ReturnstoEducationandtheDemandforSchooling.”

QuarterlyJournalofEconomics,125(2),515–48.

Karlan,Dean,AishwaryaLakshmiRatan,andJonathanZinman(2014):“Savingsbyandfor

thePoor:AResearchReviewandAgenda.”ReviewofIncomeandWealth60(1):36–78.

Karlan,D.,Osei,R.Osei-Akoto,I.andUdryC.(2014):“Agriculturaldecisionsafterrelaxing

creditandriskconstraints.”QuarterlyJournalofEconomics129:597–652

Kast,FelipeandDinaPomeranz(2014)."SavingMoretoBorrowLess:Experimental

EvidencefromAccesstoFormalSavingsAccountsinChile."NBERW.P.20239.

Lipscomb,MollyandLauraSchecter(2017):“MobilePaymentSystems:TheImpactof

EarmarkedSavingsonSanitationPurchases.”WorkingPaper,UniversityofVirginia

Lucas,AdrienneandIsaacMbiti(2012):“Access,sorting,andachievement:Theshort-run

effectsoffreeprimaryeducationinKenya,”AmericanEconomicJournal:AppliedEconomics,

4(4),pp.226-253.

Mobarak,A.M.,andRosenzweig.M.(2013):“Sellingformalinsurancetotheinformally

insured.”WorkingPaper,YaleUniversity.

Muralidharan,Karthik,&Prakash,Nishith(2016):“CyclingtoSchool:IncreasingSecondary

SchoolEnrollmentforGirlsinIndia.”WorkingPaper19305

Ohba,Asayo(2011):“TheabolitionofsecondaryschoolfeesinKenya:Responsesbythe

poor,”InternationalJournalofEducationalDevelopment,Vol31(4),pp.402-408.

Ozier,O.(Forthcoming):“TheImpactofSecondarySchoolinginKenya:ARegression

DiscontinuityAnalysis,”JournalofHumanResources.

Prina,Silvia(2015):“BankingthePoorviaSavingsAccounts:EvidencefromaField

Experiment.”JournalofDevelopmentEconomics115:16–31.

Tarozzi, Alessandro, Aprajit Mahajan, Brian Blackburn, Dan Kopf, Lakshmi Krishnan, and Joanne Yoong. (2014): "Micro-loans, Insecticide-Treated Bednets, and Malaria: Evidence from a Randomized Controlled Trial in Orissa, India." American Economic Review, 104(7): 1909-41.

24

UNESCOInstituteforStatisticsglobaldatabases.(2015).

WorldBank(2009):“AbolishingschoolfeesinAfrica:LessonsfromEthiopia,Ghana,Kenya,

Malawi,andMozambique,”WorldBank,incollaborationwiththeUnitedNationsChildren’s

Fund(UNICEF),WashingtonDC.

25

Table1:Design

Baseline

BaselinewithADSconsent

EndlinewithADSconsent

Control 1,688 1,441 1,300

(111) (110) (110)

MBA 1,431 1,227 1,056

(110) (108) (108)

LSA 1,554 1,352 1,163

(116) (113) (113)

Total 4,673 4,020 3,519

(337) (331) (331)

Cellentriesarenumberofparentsinterviewed.Numberofschoolspercellinbrackets.

26

Table2A:Balancetest(Respondent)

MeansbyTreatmentArms DifferenceinMeans

Control MBA LSA Overall

CvsMBA

CvsLSA

MBAvsLSA

Gender-Female 0.70 0.70 0.66 0.68 0.00 0.04* 0.04

(0.01) (0.02) (0.02) (0.01) (0.02) (0.02) (0.02)

Age 43.57 43.04 44.33 43.66 0.53 -0.76 -1.29***

(0.34) (0.34) (0.32) (0.20) (0.48) (0.47) (0.47)

IsprimarydecisionmakerinHH 0.41 0.41 0.41 0.41 -0.01 0.00 0.00

(0.02) (0.02) (0.02) (0.01) (0.03) (0.02) (0.03)

Hascompletedprimaryschooling 0.61 0.65 0.60 0.62 -0.04 0.01 0.05

(0.03) (0.03) (0.03) (0.02) (0.04) (0.04) (0.04)

Hascompletedsecondaryschooling

0.20 0.19 0.19 0.19 0.00 0.01 0.00

(0.01) (0.01) (0.01) (0.01) (0.02) (0.02) (0.02)

Hasaformaljob 0.11 0.09 0.10 0.10 0.01 0.01 -0.01

(0.01) (0.01) (0.01) (0.01) (0.01) (0.01) (0.01)

Ownsamobilephone 0.91 0.93 0.95 0.93 -0.02 -0.04* -0.01

(0.02) (0.01) (0.01) (0.01) (0.02) (0.02) (0.02)

Canaccessamobilephone 0.98 0.99 0.98 0.98 -0.01* 0.00 0.01

(0.00) (0.00) (0.00) (0.00) (0.01) (0.01) (0.01)

HasaSafaricomSIM(allsample) 0.89 0.91 0.92 0.90 -0.02 -0.04* -0.01

(0.02) (0.02) (0.01) (0.01) (0.02) (0.02) (0.02)

GaveAdmin.DataSharing(ADS)consent(amongSafaricomSIMowners)

0.93 0.92 0.92 0.92 0.01 0.01 0.01

(0.01) (0.02) (0.03) (0.01) (0.02) (0.03) (0.03)

HasaSafaricomSIM(sampleexcl.Kilifi)

0.97 0.97 0.97 0.97 0.00 0.00 0.00

(0.01) (0.01) (0.01) (0.00) (0.01) (0.01) (0.01)

HasaSafaricomSIM(Kilifisample) 0.75 0.76 0.85 0.79 -0.01 -0.10** -0.08*

(0.03) (0.04) (0.03) (0.02) (0.05) (0.04) (0.05)

HasM-PESA 0.85 0.88 0.89 0.87 -0.03 -0.04* -0.01

(0.02) (0.02) (0.02) (0.01) (0.03) (0.02) (0.02)

HasM-PESA(amongSafaricomSIMowners)

0.96 0.97 0.97 0.96 -0.01 -0.01 0.00

(0.01) (0.01) (0.01) (0.00) (0.01) (0.01) (0.01)

N 1688 1431 1554 4673 3119 3242 2985

27

Table2B:Balancetest(ChildrenandSchooling)


Control MBA LSA Overall Cvs

MBACvsLSA

MBAvsLSA

Nb.ofchildreninHH 4.85 4.72 5.05 4.88 0.13 -0.20 -0.33*

(0.14) (0.12) (0.14) (0.08) (0.18) (0.19) (0.18)

Shareofgirlsamongchildren 0.51 0.51 0.49 0.51 0.00 0.02 0.02

(0.01) (0.01) (0.02) (0.01) (0.02) (0.02) (0.02)

Shareexpectedtoattendsecondaryschool

1.00 1.00 1.00 1.00 0.00 0.00** 0.00

(0.00) (0.00) (0.00) (0.00) (0.00) (0.00) (0.00)

Sharewithaboveaveragegrades 0.31 0.30 0.29 0.30 0.01 0.02 0.01

(0.02) (0.02) (0.02) (0.01) (0.03) (0.03) (0.02)

Logexpectationofsecondaryschoolexpenses

10.47 10.48 10.44 10.46 -0.02 0.03 0.05

(0.04) (0.03) (0.03) (0.02) (0.05) (0.05) (0.05)

N 1688 1431 1554 4673 3119 3242 2985

Table2C:Balancetest(Schools)


Control MBA LSA Overall

CvsMBA

CvsLSA

MBAvsLSA

No.ofPermanentClassrooms,Usable

10.80 11.16 11.22 11.05 -0.36 -0.42 -0.06

(0.49) (0.61) (0.51) (0.31) (0.78) (0.71) (0.79)

AgeofSchool 47.16 45.02 46.24 46.20 2.14 0.92 -1.22

(2.28) (1.56) (2.14) (1.19) (2.76) (3.12) (2.64)

EnrollmentTotal(AllStudents) 539.56 483.91 546.97 524.95 55.66 -7.41 -63.06

(34.96) (34.55) (35.61) (20.35) (49.05) (49.80) (49.51)

PupilTeacherRatio 37.00 35.22 38.01 36.79 1.78 -1.02 -2.79

(1.42) (1.67) (1.44) (0.87) (2.19) (2.02) (2.20)

%studentswhoattendedsecondaryschool(amonglastyeargraduates)

69.32 71.58 68.43 69.72 -2.26 0.89 3.15

(2.74) (2.66) (3.10) (1.65) (3.81) (4.13) (4.07)

N 1688 1431 1554 4673 3119 3242 2985

28

Table3:Attrition

FullSample FullSamplewithADSConsent

MBATreatment 0.035** 0.049***

(0.014) (0.014)

LSATreatment 0.033** 0.042***

(0.016) (0.015)

AdjustedR-squared 0.02 0.01

ControlGroupMean 0.127 0.098

Nb.NotFound 679 501

Observations 4673 4020

Column(1):Attritionforbaselinesample

Column(2):AttritionforbaselinewithADSconsent

Standarderrorsclusteredbyschool.

Estimationstratifiesoncountyandwealth

*p<0.10,**p<.05,***p<.01

Table4:TakeupofMBAandLSAbytreatmentgroup

MBATake-up LSATake-up

MBATreatment 0.246*** -0.008

(0.025) (0.007)

LSATreatment 0.241*** 0.268***

(0.023) (0.022)

ControlGroupMean 0.336 0.015


Take-upratesreportedfromadministrativedataonJan.5th2015.

SamplerestrictedtothosewithADSconsent

Standarderrorsclusteredbyschool.Estimationstratifiesoncountyandwealth

*p<0.1,**p<0.05,***p<0.01

29

Table5:MobileSavings(January5th)

GrossMobileSavings NetMobileSavings GrossCBASavings (1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)PanelA:ITTEstimates

MBA/LSAtreat 200 205 357***

(125) (125) (78)

MBATreatment 272* 278* 435***

(164) (164) (112)

LSATreatment 132 -116 134 -119 282*** -115 (144) (181) (145) (182) (97) (137)

AdjustedR-Squared 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.01 0.01 0.01 0.00PanelB:TOTEstimates

MBATake-up 824 1093* 841* 1120* 1468*** 1752***

(508) (650) (508) (651) (321) (439)

LSAtake-up 490 -413 498 -425 1045*** -410 (535) (642) (537) (646) (356) (488)

F-Statisticforweakidentification 149 102 154 155 149 102 154 155 149 102 154 155AdjustedR-squared 0.00 -0.00 0.00 -0.00 0.00 -0.00 0.00 -0.00 -0.02 -0.04 0.01 -0.00Ref.GroupCompliers'mean 399 354 225 1161 399 354 275 1270 0 0 -147 1407ReferenceGroupMean 253 253 253 543 294 294 294 590 21 21 21 467ReferenceGroup Control Control Control MBA Control Control Control MBA Control Control Control MBA

TreatmentInstrumentUsed Both MBA LSA LSA Both MBA LSA LSA Both MBA LSA LSA

ArmsExcludedfromSample None LSA MBA Control None LSA MBA Control None LSA MBA Control

Observations 4020 2668 2793 2579 4020 2668 2793 2579 4020 2668 2793 2579

GrossMobileSavings=M-PESAsavings+MBAsavings+LSAsavings NetMobileSavings=M-PESAsavings+MBAsavings+LSAsavings-MBALoans GrossCBASavings=MBAsavings+LSAsavings SamplerestrictedtothosewithADSconsent Standarderrorsclusteredbyschool.Estimationstratifiesoncountyandwealth *p<0.1,**p<0.05,***p<0.01

30

Table6:MobileSavings(January31st)

GrossMobileSavings NetMobileSavings GrossCBASavings (1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)PanelA:ITTEstimates

MBA/LSAtreat 13 17 256***

(147) (147) (68)

MBATreatment 57 64 374***

(185) (186) (108)

LSATreatment -19 -75 -17 -78 144** -205* (159) (177) (159) (178) (66) (116)


MBATake-up 53 231 70 257 1053*** 1506***

(602) (739) (602) (742) (282) (437)

LSAtake-up -71 -266 -63 -278 533** -730* (588) (626) (587) (633) (252) (410)

F-Statisticforweakidentification 149 102 154 155 149 102 154 155 149 102 154 155AdjustedR-squared 0.00 0.00 0.00 -0.00 0.00 0.00 0.00 -0.00 -0.01 -0.03 -0.00 -0.01ReferenceGroupCompliers'mean 780 819 552 920 780 819 602 1029 0 0 -284 1117ReferenceGroupMean 476 476 476 552 517 517 517 598 24 24 24 409ReferenceGroup Control Control Control MBA Control Control Control MBA Control Control Control MBA



Observations 4020 2668 2793 2579 4020 2668 2793 2579 4020 2668 2793 2579

GrossMobileSavings=M-PESAsavings+MBAsavings+LSAsavings NetMobileSavings=M-PESAsavings+MBAsavings+LSAsavings-MBALoans GrossCBASavings=MBAsavings+LSAsavings SamplerestrictedtothosewithADSconsent Standarderrorsclusteredbyschool.Estimationstratifiesoncountyandwealth *p<0.1,**p<0.05,***p<0.01

31

Table7:Credit AtleastoneMBALoan NumberofMBALoans TotalAmountofMBALoans (1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)

PanelA:ITTEstimates

MBA/LSAtreat 0.04*** 0.40*** 187.02

(0.01) (0.12) (114.58)

MBATreatment 0.05*** 0.45*** 190.29

(0.01) (0.15) (129.43)

LSATreatment 0.03*** -0.01 0.34** -0.11 180.88 -14.47 (0.01) (0.01) (0.14) (0.16) (144.18) (153.21)


MBATake-up 0.16*** 0.18*** 1.64*** 1.82*** 768.64* 765.73

(0.04) (0.04) (0.45) (0.55) (461.85) (508.44)

LSAtake-up 0.12*** -0.05 1.26** -0.37 670.27 -51.52 (0.04) (0.05) (0.51) (0.59) (531.34) (544.08)

F-Statisticforweakidentification 149 102 154 155 149 102 154 155 149 102 154 155AdjustedR-squared 0.12 0.13 0.06 -0.02 0.07 0.08 0.05 -0.01 0.03 0.03 0.02 0.00Ref.GroupCompliers'mean 0 0 0.13 0.30 0 0 0.99 2.62 0 0 380 1375ReferenceGroupMean 0.08 0.08 0.08 0.12 0.75 0.75 0.75 1.19 415 415 415 604ReferenceGroup Control Control Control MBA Control Control Control MBA Control Control Control MBA



Observations 4020 2668 2793 2579 4020 2668 2793 2579 4020 2668 2793 2579

Standarderrorsclusteredbyschool.Estimationstratifiesoncountyandwealth SamplerestrictedtothoseADSconsent LoanvariablescalculatedtillJan5th *p<0.1,**p<0.05,***p<0.01

32

Table8:FinancialSavings

NonMobileGrossFinancialSavings GrossFinancialSavings(Jan5) GrossFinancialSavings(Jan31) (1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)PanelA:ITTEstimates

MBA/LSAtreat 950 1196* 1017 (613) (624) (631)

MBATreatment 604 940 728 (647) (659) (661)

LSATreatment 1253 712 1408* 555 1271 605 (779) (751) (796) (771) (806) (768)

AdjustedR-Squared 0.00 0.00 0.00 0.00 0.00 0.00 0.00 -0.00 0.00 0.00 0.00 -0.00PanelB:TOTEstimates MBATake-up 3642 2327 4586* 3623 3898 2807

(2365) (2512) (2408) (2564) (2426) (2563)

LSAtake-up 4308 2365 4841* 1843 4370 2008 (2705) (2504) (2769) (2567) (2800) (2559)

F-Statisticforweakidentification 154 100 162 160 154 100 162 160 154 100 162 160

AdjustedR-squared -0.01 -0.00 0.00 0.00 -0.01 -0.01 -0.00 0.00 -0.01 -0.00 -0.00 0.00Ref.GroupCompliers'mean -4422 -3982 -6124 -4562 -3999 -3592 -5937 -3283 -3656 -3143 -5635 -3557ReferenceGroupMean -3752 -3752 -3752 -3262 -3470 -3470 -3470 -2619 -3257 -3257 -3257 -2617ReferenceGroup Control Control Control MBA Control Control Control MBA Control Control Control MBATreatmentInstrumentUsed Both MBA LSA LSA Both MBA LSA LSA Both MBA LSA LSAArmsExcludedfromSample None LSA MBA Control None LSA MBA Control None LSA MBA ControlObservations 3519 2356 2463 2219 3519 2356 2463 2219 3519 2356 2463 2219Sample:RestrictedtothosewithADSconsentandfoundatendline.Allmissingvaluesaretreatedaszeros Standarderrorsclusteredbyschool.Estimationstratifiesoncountyandwealth UsingGrossMobileSavingsfromAdmindatatillJan5forColumn5-8,andtillJan31tillforColumn9-12 NonMobileGrossFinancialSavings=BankAccount+MattressesSavings+SACCO+CHAMA+Advancedpurchases+Family+otherGrossFinancialSavings(Jan5)=NonMobileGrossFinancialSavings+GrossMobileSavingsAdmin(Jan5th) GrossFinancialSavings(Jan31)=NonMobileGrossFinancialSavings+GrossMobileSavingsAdmin(Jan31st)

33

Table9:MobileSavings-QuantileRegressions

GrossMobileSavings GrossFinancialSavings

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

MBATreatment 131 0 383* 2907 3 -317

(201) (0) (218) (2291) (35) (628)

LSATreatment 236 0 397** 4984*** 3 -60

(156) (0) (202) (1570) (40) (565)

ControlGroupMean 253 253 253 -3470 -3470 -3470

Quantile 0.1 0.5 0.9 0.1 0.5 0.9

Observations 4020 4020 4020 3519 3519 3519

GrossMobileSavings(Jan5)=M-PESAsavings+MBAsavings+LSAsavingsNetMobileSavings(Jan5)=M-PESAsavings+MBAsavings+LSAsavings-MBALoansGrossCBASavings(Jan5)=MBAsavings+LSAsavings

SamplerestrictedtothosewithADSconsent

Standarderrorsclusteredbyschool.Estimationstratifiesoncountyandwealth

*p<0.1,**p<0.05,***p<0.01

Table10:OrdinalLogitMargins-Gross&NetMobileSavings

OrdinalVar:GrossMobileSavings OrdinalVar:NetMobileSavings

MBA

DependentVariable=1 -0.035** -0.032**

(0.016) (0.016)

DependentVariable=2 -0.004* -0.005*

(0.002) (0.003)

DependentVariable=3 0.039** 0.037**

(0.018) (0.019)

LSA

DependentVariable=1 -0.052*** -0.053***

(0.016) (0.016)

DependentVariable=2 -0.006** -0.008***

(0.002) (0.003)

DependentVariable=3 0.058*** 0.061***

(0.018) (0.018)

PseudoR-squared 0.002 0.0023


*p<0.1,**p<0.05,***p<0.01OrdinalDep.Variable:=1ifsavingsnegative,=2ifsavingszeroand=3ifsavingspositive

34

Table11:MobileSavingsbydecisionmakingrespondent(ITT)

GrossMobileSavings NetMobileSavings GrossCBASavings

GrossFinancialSavings(Jan5)

MBA/LSAtreat 229 228 125** 550

(236) (237) (51) (1365)Respondentisthedecision-maker 173 192 -15 -546

(178) (179) (41) (1131)MBA/LSAxRespondentisthedecision-maker -36 -30 270*** 661

(262) (263) (88) (1466)R-Squared 0 0 0.01 0

AdjustedR-Squared 0 0 0.01 0ControlGroupMean 256 297 21 -3406

Observations 4000 4000 4000 3508

GrossMobileSavings(Jan5)=M-PESAsavings+MBAsavings+LSAsavings

NetMobileSavings(Jan5)=M-PESAsavings+MBAsavings+LSAsavings-MBALoans GrossCBASavings(Jan5)=MBAsavings+LSAsavings

GrossFinancialSavings(Jan5)=NonMobileGrossFinancialSavings+GrossMobileSavings(Jan5th)

SamplerestrictedtothosewithADSconsentfor(1),(2)and(3),samplerestrictedtothosewithADSconsentandfoundatendlinefor(4)Standarderrorsclusteredbyschool.Estimationstratifiesoncountyandwealth

*p<0.1,**p<0.05,***p<0.01

35

Table12:MobileSavingsandFemaleDecision-maker

GrossMobileSavings NetMobileSavings GrossCBASavings GrossFinancialSavings(Jan5)

MBA/LSAtreat 333** 337** 388*** 1307*

(151) (152) (93) (750)

Femaledecision-maker 202 193 59 982

(209) (209) (64) (822)

MBA/LSAxFemaledecision-maker -527* -526* -122 -346

(268) (268) (147) (1018)

R-Squared 0.00 0.00 0.01 0.00

AdjustedR-Squared 0.00 0.00 0.01 0.00

ControlGroupMean 253 294 21 -3470

Observations 4020 4020 4020 3519



GrossFinancialSavings(Jan5)=NonMobileGrossFinancialSavings+GrossMobileSavings(Jan5th) SamplerestrictedtothosewithADSconsentfor(1),(2)and(3),samplerestrictedtothosewithADSconsentandfoundatendlinefor(4)Standarderrorsclusteredbyschool.Estimationstratifiesoncountyandwealth

*p<0.1,**p<0.05,***p<0.01

36

Table13:MobileSavingsandexpectationsofaboveaverageschoolperformance

GrossMobileSavings NetMobileSavings GrossCBASavings GrossFinancialSavings

MBA/LSAtreat 196 205 321*** 1557**

(132) (133) (81) (682)

Expectsaboveavg.schoolperformance 51 92 5 591

(205) (205) (73) (794)MBA/LSAxExpectsaboveavg.schoolperformance

-34 -48 122 -1414

(294) (295) (186) (1277)

R-Squared 0.00 0.00 0.01 0.00


ControlGroupMean 256 297 21 -3406

Observations 3976 3976 3976 3487



GrossFinancialSavings(Jan5)=NonMobileGrossFinancialSavings+GrossMobileSavings(Jan5th) SamplerestrictedtothosewithADSconsentfor(1),(2)and(3),samplerestrictedtothosewithADSconsentandfoundatendlinefor(4)Standarderrorsclusteredbyschool.Estimationstratifiesoncountyandwealth

*p<0.1,**p<0.05,***p<0.01

37

Table14:Take-upofMBA/LSAandSecondarySchoolEnrollment

(1) (2) (3) (4)

PanelA:ITTEstimates

MBA/LSAtreat 0.06***

(0.02)

MBATreatment 0.06***

(0.02)

LSATreatment 0.05** -0.01

(0.02) (0.02)


PanelB:TOTEstimates

MBATake-up 0.21*** 0.24***

(0.07) (0.08)

LSAtake-up 0.18** -0.04

(0.08) (0.07)

F-Statisticforweakidentification 167 108 169 166

AdjustedR-squared 0.06 0.04 0.09 0.09

ReferenceGroupCompliers'mean 0.62 0.59 0.65 0.94

ReferenceGroupMean 0.72 0.72 0.72 0.81

ReferenceGroup Control Control Control MBA

TreatmentInstrumentUsed Both MBA LSA LSA

ArmsExcludedfromSample None LSA MBA Control

Observations 3761 2521 2630 2371

Standarderrorsclusteredbyschool.EstimationstratifiesoncountyandwealthSamplerestrictedtothosewithADSconsentandfoundattheendline*p<0.1,**p<0.05,***p<0.01

38

Table15:SavingsandSecondarySchoolEnrollment(TOT)

(1) (2) (3) (4)

PanelA

GrossMobileSavings 0.24 0.20 0.37 0.07

(0.16) (0.12) (0.47) (0.15)


AdjustedR-squared -5.99 -3.90 -11.09 -0.54

PanelB

NetMobileSavings 0.24 0.19* 0.36 0.07

(0.16) (0.12) (0.44) (0.15)F-Statisticforweakidentification 3 4 1 1


PanelC

GrossCBASavings 0.14** 0.13** 0.16* 0.08

(0.06) (0.05) (0.09) (0.17)



PanelD GrossFinancialSavings(Jan5) 0.06 0.09 0.04 -0.02

(0.05) (0.10) (0.04) (0.04)



Observations 3761 2521 2630 2371

ReferenceGroup Control Control Control MBA

TreatmentInstrumentUsed Both MBA LSA LSA

ArmsExcludedfromSample None LSA MBA Control

GrossMobileSavings(Jan5th)=M-PESAsavings+MBAsavings+LSAsavings NetMobileSavings(Jan5th)=M-PESAsavings+MBAsavings+LSAsavings-MBALoansGrossCBASavings(Jan5th)=MBAsavings+LSAsavings

GrossFinancialSavings(Jan5)=NonMobileGrossFinancialSavings+GrossMobileSavings(Jan5th)SamplerestrictedtothosewithADSconsentandfoundattheendlineStandarderrorsclusteredbyschool.EstimationstratifiesoncountyandwealthGross,Net,CBAandFinancialsavingsaremeasuredinunitsofthousandsofKSh

*p<0.1,**p<0.05,***p<0.01

39

Table16:RealizedCostofSchool

TotalSchoolCost(incurred+expected)

(1) (2) (3) (4)

PanelA:ITTEstimates

MBA/LSAtreat -1953

(1830)

MBATreat 330

(2194)

LSATreat -3692* -3736*

(1968) (2093)


PanelB:TOTEstimates

MBAtake-up -7488 1272

(7114) (8415)

LSAtake-up -12691*-

12409* (6941) (7141)


AdjustedR-squared -0.02 0.01 -0.00 -0.01Ref.GroupCompliers'mean 33906 31340 44976 45160

ReferenceGroup Control Control Control MBAReferenceGroupMean 31729 31729 31729 32103

TreatmentInstrumentUsed Both MBA LSA LSAArmsExcludedfromSample None LSA MBA Control

Observations 3519 2356 2463 2219

Standarderrorsclusteredbyschool.EstimationstratifiesoncountyandwealthSample:EveryonewhogaveBaselineandAdminDataSharing(ADS)consentandwasfoundattheendline

*p<0.1**p<0.05***p<0.01

40

Table17:FinancingSchool

SavedMoney

BorrowingMoney

SoldFarmprod.orlivestock

SoldHHitems

Giftitemsormoney

other

MBATreat -0.02 0.01 0.01 -0.00 0.01 -0.00

(0.02) (0.02) (0.02) (0.00) (0.01) (0.01)

LSATreat -0.04* 0.01 0.03 -0.00 0.02 -0.01

(0.02) (0.02) (0.02) (0.00) (0.01) (0.01)

AdjustedR-Squared 0.03 0.03 0.03 -0.00 0.01 0.00

ReferenceGroupMean 0.48 0.24 0.24 0.00 0.09 0.09

Observations 3519 3519 3519 3519 3519 3519

Standarderrorsclusteredbyschool.Estimationstratifiesoncountyandwealth Sample:EveryonewhogaveBaselineandAdminDataSharing(ADS)consentandwasfoundattheendline

Table18:StandardizedTestScores

(1) (2) (3) (4)PanelA:ITTEstimates MBA/LSAtreat 0.01

(0.06) MBATreatment -0.01

(0.07) LSATreatment 0.05 0.05

(0.07) (0.07)AdjustedR-Squared 0.03 0.02 0.03 0.04PanelB:TOTEstimates MBATake-up 0.05 -0.03

(0.22) (0.24) LSAtake-up 0.15 0.17

(0.24) (0.21)F-Statisticforweakidentification 178 120 148 144AdjustedR-squared 0.03 0.02 0.04 0.04ReferenceGroupCompliers'mean 0.00 -0.03 0.01 0.00ReferenceGroupMean 0.00 0.00 0.00 0.00ReferenceGroup Control Control Control MBATreatmentInstrumentUsed Both MBA LSA LSAArmsExcludedfromSample None LSA MBA ControlObservations 3249 2218 2255 2025

Standarderrorsclusteredbyschool.EstimationstratifiesoncountyandwealthStandardizedtestscoresusingmeanandstandarddev.ofcontrolgroupSamplerestrictedtothosewithADSconsentandfoundattheendline*p<0.1,**p<0.05,***p<0.01

41

TableA2:LeeboundsforTable8(FinancialSavings)

NonMobileFinancialSavings GrossFinancialSavings(Jan5) GrossFinancialSavings(Jan31)

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)lower

-1325**-

1759***-931 714 -1071* -1389** -782 493 -1217** -1567** -899 554

(577) (665) (757) (4149) (596) (695) (772) (4163) (602) (698) (782) (4163)upper 2076*** 1632*** 2479*** 880 2469*** 2139*** 2768*** 673 2411*** 2049*** 2739*** 732

(536) (589) (698) (1405) (560) (634) (721) (1801) (559) (626) (725) (1756)ArmsExcludedfromSample None LSA MBA Control None LSA MBA Control None LSA MBA ControlObservations 4020 2668 2793 2579 4020 2668 2793 2579 4020 2668 2793 2579

Sample:RestrictedtothosewithbaselineandADSconsent. Standarderrorsclusteredbyschool.Estimationstratifiesoncountyandwealth

UsingGrossMobileSavingsfromAdmindatatillJan5forColumn5-8,andtillJan31tillforColumn9-12 NonMobileGrossFinancialSavings=BankAccount+MattressesSavings+SACCO+CHAMA+Advancedpurchases+Family+other

GrossFinancialSavings(Jan5)=NonMobileGrossFinancialSavings+GrossMobileSavingsAdmin(Jan5th) GrossFinancialSavings(Jan31)=NonMobileGrossFinancialSavings+GrossMobileSavingsAdmin(Jan31st)

TableA1:LeeboundsforTable5(MobileSavings)

GrossMobileSavings NetMobileSavings GrossCBASavings (1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)

lower -136 66 -236 -485** -135 73 -240 -492** 70 247 15 -410*** (217) (465) (167) (221) (218) (465) (167) (235) (129) (299) (66) (143)

upper 405*** 410 341** 31 408*** 416 343** 27 397*** 480*** 298*** -151 (156) (326) (140) (188) (156) (324) (141) (190) (76) (141) (79) (138)

ArmsExcludedfromSample None LSA MBA Control None LSA MBA Control None LSA MBA ControlObservations 4673 3119 3242 2985 4673 3119 3242 2985 4673 3119 3242 2985

GrossMobileSavings=M-PESAsavings+MBAsavings+LSAsavings NetMobileSavings=M-PESAsavings+MBAsavings+LSAsavings-MBALoans

GrossCBASavings=MBAsavings+LSAsavings

Samplerestrictedtothosewithbaselineconsent

Standarderrorsclusteredbyschool.Estimationstratifiesoncountyandwealth *p<0.1,**p<0.05,***p<0.01

42

Figure1:Cumulativeshort-termgrossmobilesavings

Figure2:Cumulativeshort-termfinancialsavings

Documents

High Hopes: Experimental Evidence on Saving and H School ... · The mobile money revolution in Kenya and other parts of the developing world has allowed some geographical barriers