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PolicyResearchWorkingPaper10946

Education,SocialNorms,andtheMarriagePenalty

EvidencefromSouthAsia

MaurizioBussolo

JonahRexer

MargaretTriyana

WORLDBANKGROUP

SouthAsiaRegion

OfficeoftheChiefEconomistOctober2024

PolicyResearchWorkingPaper10946

Abstract

Agrowingliteratureattributesgenderinequalityinlabormarketoutcomesinparttothereductioninfemalelaborsupplyafterchildbirth,thechildpenalty.However,ifsocialnormsconstrainmarriedwomen’sactivitiesout-sidethehome,thenmarriagecanindependentlyreduceemployment,evenintheabsencechildbearing.Giventhecorrelationintimingbetweenchildbirthandmarriage,con-ventionalestimatesofchildpenaltieswillconflatethesetwoeffects.ThepaperstudiesthemarriagepenaltyinSouthAsia,acontextfeaturingconservativegendernormsand

lowfemalelaborforceparticipation.Thestudyintroducesasplit-sample,pseudo-panelapproachthatallowsforthesep-arationofmarriageandchildpenaltiesevenintheabsenceofindividual-levelpaneldata.Marriagereduceswomen’slaborforceparticipationinSouthAsiaby12percentagepoints,whereasthemarginalpenaltyofchildbearingissmall.Consistentwiththecentralrolesofbothopportu-nitycostsandsocialnorms,themarriagepenaltyissmalleramongcohortswithhighereducationandlessconservativegenderattitudes.

ThispaperisaproductoftheOfficeoftheChiefEconomist,SouthAsiaRegion.ItispartofalargereffortbytheWorldBanktoprovideopenaccesstoitsresearchandmakeacontributiontodevelopmentpolicydiscussionsaroundtheworld.PolicyResearchWorkingPapersarealsopostedontheWebat

/prwp

.Theauthorsmaybecontactedatmbussolo@,jrexer@,andmtriyana@.

ThePolicyResearchWorkingPaperSeriesdisseminatesthefindingsofworkinprogresstoencouragetheexchangeofideasaboutdevelopmentissues.Anobjectiveoftheseriesistogetthefindingsoutquickly,evenifthepresentationsarelessthanfullypolished.Thepaperscarrythenamesoftheauthorsandshouldbecitedaccordingly.Thefindings,interpretations,andconclusionsexpressedinthispaperareentirelythoseoftheauthors.TheydonotnecessarilyrepresenttheviewsoftheInternationalBankforReconstructionandDevelopment/WorldBankanditsaffiliatedorganizations,orthoseoftheExecutiveDirectorsoftheWorldBankorthegovernmentstheyrepresent.

ProducedbytheResearchSupportTeam

Education,socialnorms,andthemarriagepenalty:EvidencefromSouthAsia

MaurizioBussolo*JonahRexer*MargaretTriyana*

Keywords:Femalelaborforceparticipation,Genderinequality,Genderattitude

JELcodes:O10,J12,J16,J22

*OfficeoftheChiefEconomist’sOfficeforSouthAsia,theWorldBankGroup.TheauthorsthankFranziskaOhnsorge,SoniaBhalotra,RachelHeath,JamesRowe,andChristopherToweforhelpfulsuggestionsandAndyWeichengJiangandYuruiHuforexcellentresearchassistance.Thefindings,interpretations,andconclusionsexpressedinthispaperareentirelythoseoftheauthors.TheydonotnecessarilyrepresenttheviewsoftheWorldBankanditsaffiliatedorganizations,orthoseoftheExecutiveDirectorsoftheWorldBankorthegovernmentstheyrepresent.

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1Introduction

Innearlyeverycountryintheworld,womenparticipateinthelaborforceatalowerratethanmen.Thepersistenceofthetraditionalspecializationofwomeninthehomeandmeninthemarketplaceisoneofthemostconsistentempiricalfactsinthesocialsciences.Muchofthisgaparisesfromthecostsofchild-rearing,whicharedisproportionatelybornebywomen.InAsia,womenspendaround5timesasmuchasmenonhouseholdtasks(VanderGaagetal.,2019).Thesharpdeclineinthelabormarketoutcomesofwomenrelativetomenaroundthebirthofthefirstchild–theso-called“childpenalty”–isacentraldriverofgenderinequalityinthelabormarketsacrosstheworld(Klevenetal.,2019).

However,childbearingtypicallyoccursconcurrentlywithotherkeyeventsoffamilyformation,inparticularmarriage.Conventionalestimatesofthechildpenaltyoftenignorethat,evenintheabsenceofchildren,theactofmarriageconfersnewresponsibilitiesandsocialnormsthatmayconstrainawoman’slaborsupply.Thesemaritalconstraints–the“marriagepenalty”–maybeconflatedwithchildbearingconstraintsinatypicalchildpenaltyestimation,giventhecorrelationintimebetweenthesetwoevents.

Insettingswheregenderrolesaredeeplyentrenched(Jayachandran,2020),marriedbutchildlesswomenmaybealreadyconfinedtodomesticresponsibilitiesevenwheretheyarenotyetconstrainedbytheburdensofchildcare.Thismarriagepenaltymayinpartexplainthemixedevidencegloballyontheimpactofaccesstochildcareonwomen’slaborsupply(Evansetal.,2021).InSouthAsiainparticular–aregionknownforbothconservativegendernormsandlowfemalelaborforceparticipation–theexperimentalevidenceinfavorofchildcareaccessisweak(Nandietal.,2020;Richardsonetal.,2018),suggestingchildcareresponsibilitiesarenotthemainconstrainttofemaleemployment.Similarly,Abrahametal.(2021)findnoevidenceofchildpenaltiesinIndia.Thisevidencepointstotheprimacyofmarriageoverchildpenaltiesinsettingswheregendernormsarestrict.

Still,muchlikethechildpenalty,themarriagepenaltymayhavediversecauses.Isamarriagepenaltyevidenceofconservativesocialnormsthatproscribemarriedwomen’sphysicalmobilityandworkoutsidethehome?Orisit,instead,areflectionoftheoptimalhouseholdspecializationbetweenmenandwomen,givenlimitedoutsideoptionsforwomen

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inthelabormarket,asinBecker(1993).InthecontextofSouthAsia,thispaperanswerstwoquestions:(i)howcanthemarriagepenaltybeseparatedfromthechildpenaltyintheabsenceofindividual-levelpaneldata,and(ii)whatdrivesthemarriagepenaltyinSouthAsia.Doesitrepresentoptimallaborsupplyoramisallocationoftalent?

Toanswerthesequestions,weusemultipleroundsofthenationallyrepresentativeDemographicandHealthSurveys(DHS)fromfourSouthAsiancountries–Bangladesh,India,Maldives,andNepal.Separatelyestimatingchildandmarriagepenaltiespresentsseveralchallenges.First,sincethetimingofthesemajorlifeeventsisendogenous,naivecomparisonsinthelabormarketoutcomesbetweenmarriedandunmarriedwomenorparentsandthechildlessarecontaminatedbyomittedvariables.Recentworkonchildpenaltieshasusedevent-studymethodstosolvethisidentificationproblem(Klevenetal.,2021,2019,2024).

However,evenifadesignexploitssharpchangesinlaborsupplyaroundmarriageorchildbirthforidentification,thesetwoeventsarecorrelatedintimeforagivenindividual.Assuch,estimatesofthemarriagepenaltyareobscuredbythepresenceofchildren,andestimatesofthechildpenaltyarelikewisecapturingatleastinpartamarriagepenalty.Onesolutionistouseindividual-levelpaneldata,whereawoman’semploymentstatusisobservedbeforeandafterbothmarriageandchildbirth.Here,event-studytechniquesreadilyapply,augmentingstandardspecificationswithtimingindicatorsforbotheventssimultaneously,withmarriageandchildbirthcoefficientsseparatelyidentifiedbyvariationacrosswomeninthetiminggapbetweenthesetwoevents(Klevenetal.,2023).

However,accesstosuchrichpaneldataisrare,particularlyindevelopingcountrysettings.Weproposeamethodthatallowsfortheseparationofthemarriagepenaltyfromthechildpenaltyinrepeatedcross-sectionaldata.FollowingKlevenetal.(2023),wegeneratepseudo-panelsbymatchingwomensurveyedintheyearoftheirmarriagewithyoungerunmarriedwomenandoldermarriedwomentoconstructpre-andpost-marriagecounterfactualemploymenttrends.Ourcontributionistorestrictthepoolofpotentialpost-marriagematchestowomenwithoutchildren(the“nochild”sample)inordertoisolatethemarriagepenaltyfromthechildpenalty.Wethenre-runthismatchingprocedureontheunrestrictedsampleofwomenwherechildrenmaybepresent(the“ignore

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child”sample).Comparingthesetwoquantitiesyieldstherelativemagnitudeofmarriagepenaltyaloneandthecombinedmarriageandchildpenalty.

WefindthatSouthAsianwomenreducetheirlaborforceparticipationby12percentagepoints(p.p.)followingmarriage,evenbeforechildbearing.Amongwomenwithchildren,thisrisesjust4p.pto16p.p.Assuch,75percentofthecombinedfamilyformationpenaltyisdrivenbymarriageitself,ratherthantheburdenofchildbearing,atleastinthefirstfiveyearsofmarriage.ThelargesteffectsareobservedinIndia,whilemoremutedeffectsareobservedinNepal,wherethemajorityofthecombinedpenaltyisdrivenbychildren.Dynamicevent-studyestimatesrevealflattrendsinemploymentstatusleadinguptothemarriagedate,andsharpdropsinemploymentinthefirstyearofmarriage.Thesetrendslendadditionalsupporttothenotionthattheseestimatesrepresentthecausaleffectofmarriage.Men,incontrast,enjoyamarriagepremium.Thispremiumdoesnotdependonthepresenceofchildren,consistentwiththeexistingliteratureshowingnochildpenaltiesformen(Klevenetal.,2023).

Themarriagepenaltymayrepresentanoptimalsolutiontoajointhouseholdmaximizationproblem.Ifwomenhavelimitedoutsideoptionsinthelabormarketrelativetotheirhusbands,thenspecializationinhome-basedtasksmightbeeconomicallyefficient,evenwithoutchildren.However,thevalueofwomen’shomeproductionisgreatlydiminishedwithoutchildren,suggestingaroleforsocialnormsindrivingthemarriagepenalty,particularlythosethatconstrainwomen’smobilityoutsidethehome(Anukritietal.,2020).Toadjudicatethesehypotheses,weuseheterogeneityanalysestotestthesourcesofthemarriagepenalty.DespitethefactthatgendernormsaremoreprogressiveinurbanareasinSouthAsia(Asheretal.,n.d.),wefindnosignificantdifferencebetweenurbanandruralmarriagepenalties.Thismayinpartreflectthenatureofurbanlabormarkets,whereemploymentopportunitiesareconcentratedoutsidethehome,addingadditionalconstraintstowomen’sparticipationinthecontextofconservativegenderattitudes(JalotaandHo,2024).

WethenturntotestingtheimpactofeducationandsocialnormsonmarriagepenaltiesinSouthAsiabyinteractingourpost-marriageindicatorwiththesecharacteristics.Wefindthateducatedwomenhavemuchsmallermarriagepenalties,withpost-secondary

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educationerasingnearlyhalfthebaselinemarriagepenalty.Atthesametime,educatedhusbandsexertaquantitativelysimilareffect.Becauseofpositiveassortativemating,spousaleducationlevelsarehighlycorrelated,necessitatingtheinclusionofbothinteractionsinasingleregression.Inthismodel,thewife’seducationremainssignificantwhilethecoefficientonthehusband’seducationfallstozero.

Interpretingtheseresultsthroughthelensofourhypotheses,wearguethatawoman’seducationaffectsbothhouseholdgendernormsandheroutsideemploymentoptions.Incontrast,herhusband’seducationaffectshouseholdnorms,butdoesnotdirectlyaffectheremploymentprospects.Thissuggeststhatoutsideoptionsatleastinpartplayaroleindeterminingthemarriagepenalty.Finally,wedirectlytesttheroleofgenderattitudesbyinteractingthemarriageindicatorwithDHSmeasuresofhouseholdgenderattitudes.Wefindstrongevidencethatwomeninhouseholdswithmoreliberalgendernormsexperiencesmallermarriagepenalties.Theeffectsofeducationandsocialnormsappeartobeindependent,suggestingthatbothopportunitycostsandsocialnormsplayaroleindrivingthemarriagepenalty.

Wecontributetothelargeandgrowingliteratureongenderinequality.Thespecializationofwomeninthehomeandmeninthemarketplacerelatestowomen’srealorperceivedcomparativeadvantageinthehome(Becker,1973).Underspecialization,womeninvestinhomespecifichumancapital,whilemeninvestinmarketspecifichumancapital,raisingwages.Empirically,marriedmenhavesubstantiallyhigherwagesthanunmarriedmen,evenaftercontrollingforhumancapitalandjobcharacteristics(HerschandStratton,2000),suggestingthatspecializationthroughmarriagemakesmenmoreproductive.Ourevidenceonmenisconsistentwiththisliterature.Nevertheless,despitesubstantialattentiontogenderinequalityinrecentyears,thereislimitedcausalevidenceabouttheimpactofmarriageonwomen’slabormarketoutcomes.Thispaperbeginstofillthatgap.

Despiterisingwomen’shumancapitalandnarrowinggendergapsineducationacrosstheworld,femalelaborforceparticipationremainslowinmanypartsoftheworld,includingSouthAsia.Onepotentialexplanationforlowfemalelaborforceparticipationisgendernorms,whichcangeneratespousaldisagreementovertheprovisionofthehouseholdpublicgood(Bertrandetal.,2016;Fernandezetal.,2004).Childpenaltieshavebeendocumented

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inhighandlowerincomesettingswithmagnitudesrangingfrom12to38percent(Kleven,2022;Klevenetal.,2019,2023).However,itcanplausiblybearguedthatwomenhaveacomparativeadvantageinchildcarerelativetotheirhusbands.Weshowthatevenbeforechildbirth,marriageitselfmightalreadyaffectfemalelaborforceparticipationinsettingswithdeeplyentrenchedgendernorms.Ourworkprovidessomeofthefirstevidenceonthemagnitudesofmarriagepenalties,ratherthanchildpenalties,andproposesamethodfordistinguishingbetweenthetwoincross-sectionaldata.Wealsodirectlylinkmarriagepenaltiestoskilllevels,outsideoptions,andsocialnorms.

Theremainderofthepaperisorganizedasfollows.Section2providesanoverviewofthedataandempiricalstrategy.Section3presentsourfindings,followedbyanexplorationofthedeterminantsofthemarriagepenaltyforwomeninSection4.Section5concludeswithpolicyimplications.

2DataandEmpiricalStrategy

2.1Data

WeusedatafromtheDemographicandHealthSurvey(DHS)fromBangladesh,India,Maldives,andNepalintheanalysis(TableA1).1Thesurveyswereconductedapproximatelyevery5yearsstartinginthe1990s.Thesenationallyrepresentativesurveysformarepeatedcrosssectionofreproductiveagewomenbetweentheagesof15and45.Themorerecentsurveysalsoincludedataonthemeninthehouseholds,sotherearefewerroundsofdataformen.Thefinalsamplecovers1,780,854womenand389,313menresidinginaround650,000householdsinalllevel1administrativeareasofthe4countries.

Thesurveysincludeage,education,urbanresidence,employmentstatus,andmaritalstatus.Forwomen,thesurveysincludeageatcohabitation,whichweuseastheageatmarriage,andbirthhistory,whichincludesthetimingofthefirstbirth.Importantly,thesesurveyscontaincompletehouseholdrosterswithdataonemploymentstatusforbothmarried

andunmarriedwomen,whichwillbeessentialtothepseudo-panelapproachbelow.

1OthercountriesinSouthAsiaareexcludedbecausetheDHSdatalacksufficientinformationonemploymentstatusforbothmarriedandunmarriedwomen.

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MorerecentroundsoftheDHSalsoincludequestionsondecisionmakingandattitudetowarddomesticviolence.Thedecisionmakingquestionsincludewhetherornotwomenareinvolvedindecisionsontheirownhealthcare,purchases,andvisitstofamily.Thedecisionmakingindexisthesumofallthedecisionmakingitemsinwhichthewomanisinvolvedindividuallyorjointly.Ahigherindexsuggestshigherdecisionmakingpowerforwomen.Thequestionsonattitudetowarddomesticviolenceincludewhetheritwouldbejustifiedforahusbandtobeathiswifeifshegoesoutwithouttellingherhusband,neglectsthechildren,argueswithherhusband,refusessex,andburnsthefood.Theindexfortheattitudetowarddomesticviolenceisthesumofalltheitemswithwhichthewomanagrees.Ahigherindexsuggestsahigheracceptanceofdomesticviolence.

2.2Empiricalstrategy

2.2.1Estimation

Weuseaneventstudyapproachbasedonsharpchangesinwomen’slabormarketoutcomesobservedaroundthetimeofmarriage,t=0,forindividualsatageaobservedincalendaryeary.Ideally,theestimationusesindividual-levelpaneldata,inwhichcaserelativetimeindicatorsformarriageandchildbirthcanbeincludedsimultaneously,alongwithindividualandyearfixedeffects,inasingleevent-studyregressionwherelabormarketparticipationistheoutcomeKlevenetal.(2023).

However,intheabsenceofsuchdata,followingKleven(2022),crosssectionaldatacanbeusedtocreatepseudo-paneldata.Formarriedindividuals,weobservetheageofmarriage,andthereforetheirlocationthepost-marriageeventspace,t≥0.Forunmarriedindividuals,wecannotobservetheirtimingofmarriage,andthereforeonlyobservethattheyareinthepre-marriageeventspace,t<0,butnottheirpreciselocationinthisspace.Thepseudo-panelapproachmatchesmarriedwomentounmarriedwomenwiththesamedemographiccharacteristicstoformapre-marriagecounterfactualestimateoftheoutcome,transformingthecrosssectionaldataintoapseudo-panelacrossthepreandpost-marriageeventspaces. Specifically,womaniisobservedintheyearofhermarriaget=0incalendaryearyatagea,withdemographiccharacteristicsXi.Sheismatchedtoasurrogateobservationinthe

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pre-marriageperiod,anunmarriedwomanjobservedinyeary?nwithagea?nandthesameobservedcharacteristicsXi=Xj.Then,foreachnupto5,thematchesatt?nareusedtoconstructthepre-marriagecounterfactualatthatperiod.Tomaximizethesample,wematchonaparsimonioussetofcharacteristics,includingthelevelofeducationandruralorurbanresidence.

Asimilarprocedureisthenappliedtowomenkinthepostmarriageeventspace,whoareobservedinyatt+nfornfrom1to5.Forthesepost-marriagematches,weadditionallyrequirethattheageatmarriageisthesameasindexwomani.Accordingly,apseudo-panelisconstructedforwomanitogeneratecounterfactualemploymentlevelsfor5yearsbeforeandaftermarriage.Furthermore,womanirepresentsallofthewomenwithXiobservedatt=0iny,whoenterhercohortas“referencewomen”andarematchedwiththesamecounterfactualwomenjandk.Wellcallthesegroups,indexedc,“marriagecohorts.”

Thesemarriagecohortsarethencollapsedattheeventyear-cohortleveltoobtainaveragelabormarketoutcomesforeachcohortforfiveyearspreandpostmarriage,aswellascohortcharacteristics.Theprocedureisthenrepeatedonthesampleofmen.Amarriagecohortc,then,isathree-elementvector,definedbyanageofmarriage,arural-urbanindicator,andaneducationlevel.Withineachcohort,ageaandbirthyear(birthcohort)bvarywithevent-timetbyconstruction,giventhatthepreandpostmarriagecomponentsofthemarriagecohortsareformedusingagesrelativetothereferencewoman.

Formarriagecohortcateventtimet,weestimatethefollowingregressionspecificationseparatelyforeachgenderg:

Y=αg+βgDct+δ+γ+ν(1)

WhereYistheoutcomeofinterest,thecohortaverageemploymentstatus.Dctisan

indicatorforpost-marriageeventperiods,andβgistheestimateofthemarriagepenaltyorpremium.Inourmainestimates,wepresentDctasacollapsedindicatorforallpost-marriageeventperiods,givingtheeventtime-averagedtreatmenteffect.However,wealsopresentevent-studyspecificationswhereweincludeleadsandlagsoftheeventyear(t?5uptot+5),allowingfordynamicpreandpostmarriagetrendsinemployment.

Inamarriagesinglecohort,thepreandpostmarriageindicatorsarecollinearwithage

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and/orbirthcohortfixedeffectsδa,andγbsincethemarriagecohortmatcheswereselectedbytheiragerelativetothereferencewoman.However,whenmanymarriagecohortsarestackedwithinagivensurveyround,thenagefixedeffectscanbeincludedintheregression,sinceageofmarriagevariesacrossmarriagecohorts.Thatis,withinagivenagethereisstillvariationacrossmarriagecohortsinthelocationinevent-time.

However,ageandbirthcohortremaincollinearforallmarriagecohortsinagivensurveyround(country-year).However,whenmultiplesurveyroundspercountryarestacked,birth

cohortfixedeffectsγcanbeincludedaswellastheageeffects.Alternatively,totakeinto

accountmultiplesurveysacrosscountries,countryandsurveyyearfixedeffectscouldalsobeincluded.Note,however,thatincross-countrypooledsample,country-year,age,andbirthcohortfixedeffectsarecollinear,andsoincludinganytwoofthesethreeyieldsequivalentestimates.2

Thesamplesizeineachcountryvaries,sotheanalysisisweightedbymarriagecohortsizesothatitisrepresentativeattheindividuallevel,andprovidesidenticalcoefficientestimatestoestimationonthemicrodataina“stacked”model.Standarderrorsareclusteredatthemarriagecohortlevel.

Wealsoconsiderseveralheterogeneityanalysestoinvestigatethemechanismsunderlyingthemarriagepenalty.Toexploretheroleofurbanresidence,thesameanalysisasinequation1isconductedontheurbanandruralsamplesseparately.Toexploretheroleofeducation,theanalysisincludesaninteractiontermbetweenwomen’shighereducationandthepost-marriageindicator.Aseparateregressionisruntoanalyzetheroleofhusband’seducationbyincludinganinteractiontermbetweenhusband’shighereducationandthepost-marriageindicator.Highereducation(orhusband’shighereducation)takesthevalueoneifwomen(ortheirhusbands)havemorethansecondaryeducation.Finally,weexploretheroleofsocialnormssimilarly,interactingthepost-marriageindicatorwithamarriagecohort-averagedgenderattitudesindex.

2Inpractice,weincludebirth-cohortandcountry-yearfixedeffects.

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2.2.2Identificationofthemarriagepenalty

Marriageandchildbirtharecorrelatedintimeacrossindividuals.Anaivepseudo-panelevent-studyregressionwouldlikelyconflatethesetwoeffects,particularlyastheshareofwomenwithchildrenriseswitht.Wethereforeproposeasplit-sampleapproachtoseparatethemarriagepenaltyfromthechildpenalty.Thefirstcase,the"nochildsample",restrictsthesampletowomenandmenwithoutchildren5yearsaftermarriagetoexploregendernorms.Thesecondcase,"theignorechildsample",matcheswomenandmeninthepostmarriageeventspacewithoutconsideringthepresenceofchildren.Thiscasecombinesthemarriageandchildpenalties(orpremium).

Ouranalysisreliesontwoidentificationassumptionstointerpretβasthecausaleffectofmarriageonemployment.First,theprecisetimingofmarriagemustbeuncorrelatedwithothershocksthatplausiblyinfluencelaborsupply.Oursplitsampleapproach,byconstruction,rulesoutchildbirthassuchaconfounder.However,otherconfounders,suchasrelocationinthecontextofpatrilocality,mightalsobecorrelatedwithmarriage.

Oursplit-sampleapproachalsogeneratesasecondidentificationassumption:thatthewomeninthe“nochild”samplearenotdiferentiallyselectedintheirpropensitytowork.Thisassumptionismorechallengingtosatisfy.Specifically,womenwhoremainchildlessuptot=5,particularlyinacontextofstrongpatriarchalnorms,arelikelytobethosewithahigherunobservedpropensitytowork.Assuch,thisintroducesatime-varyingbiasintheestimates,sincethisproblembecomesincreasinglysevereastrises:marriedwomenwithoutchildrenmanyyearsaftermarriageareparticularlyselected.However,sincethesewomenlikelyhaveahigherunobservedpropensitytowork,theresultsaswemovetowardtheendoftheeventwindowprobablyrepresentalowerboundonthetruemarriagepenalty.

2.2.3Summarystatistics

TableA2presentsmarriagecohort-levelsummarystatisticsforthewomeninthenochildandignorechildsamples.About20percentofwomeninthesampleareworking.Theaverageageofthecohortis20atthetimeofsurvey,almost40percentresideinurbanareas,almostathirdhavemorethansecondaryeducation.Theaverageageatmarriageis21andwomen

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marrymenwhoareonaverage3yearsolderthanthem.Onaverage,womenparticipatein0.3decisionsoutofamaximumof5.Womenagreetoanaverageof0.2statementsoutof5onwhenitwouldbejustifiedforamantobeathiswife.Thesecharacteristicsaresimilaracrossthetwosamples.

TableA3presentsthesummarystatisticsforthemenineachsample.Thesizeofthemalesampleis75to80percentofthefemalesample,sincewomenofchildbearingageareover-sampledintheDHS.About53percentofthemeninthesampleareworking.Theaverageageofthecohortis21,ayearolderthanthewomen’saverageage.Aboutaquarterofmenhavemorethansecondaryeducation,slightlylowerthanthewomen’sshare.

3Results

3.1Mainresults

TheresultsofthemainmarriagepenaltyestimationareinTable1.Themodelcollapsestheyearlyeventstudyindicatorsintopre-andpost-marriageperiods,withthefullsetofbirthcohortandcountry-yearfixedeffects.Thepost-marriagetreatmentindicatoristheninteractedwithabinaryvariableindicatingwhetherthecohortsexcludewomenwithchildren(the“nochildsample”)orallowforchildbirth(the“ignorechildsample”).

PanelAshowstheresultsforwomenacrosstheregion(column1)andthenthefourconstituentcountries(columns2-5).Onaverage,marriagereduceslaborforceparticipationby11.7percentagepointsacrossSouthAsiaamongchildle