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Decomposing Intergenerational Income Elasticity: The genderdifferentiated contribution of capital transmission in rural Philippines Leah Bevis and Christopher B. Barrett Cornell University August 2013 revision Comments greatly appreciated Abstract A growing empirical literature documents strong intergenerational income elasticity (IGE) worldwide while a parallel literature finds clear patterns of parent‐to‐child transmission of human capital. Although the latter pattern clearly helps explain the IGE, rarely do authors decompose the IGE into different pathways of intergenerational capital and productivity transmission, much less explore possible differences between daughters and sons in those patterns. Using longitudinal data from rural Philippines, we decompose IGE into five distinct pathways: the intergenerational transmissions of health, education, land, and spouse education capital, plus residual intergenerational correlation in productivity. We find that intergenerational human capital transmissions from mothers are stronger than from fathers. Although the naïve IGE estimates are statistically indistinguishable for sons and daughters, the pathways that generate these results differ strikingly. For sons, IGE is entirely explained by parent‐to‐child capital transmission. By contrast, strong income correlation exists between daughters and parents even after controlling for parent and child capital endowments, suggesting that it may be easier to promote equality of opportunity among males than among females in rural Philippines. Maternal education is the main parental capital driver of intergenerational income transmission, underscoring the long‐term payoff to promoting the education of girls, especially those from poor households. Acknowledgements We thank the NSF‐funded Food Systems and Poverty Reduction IGERT for financial support, IFPRI for making the data available, and workshop audiences at Calvin, Columbia, Cornell, and the 2013 Australasian Development Economics Meetings, Econometric Society Australasian Meetings, and Oxford Center for the Study of African Economies conference for helpful comments and questions. Special thanks go to Mabel Andalon, Sonia Bhaltora, Peter Brummund, Ravi Kanbur, Jordan Matsudaira, Catherine Porter, Agnes Quisumbing, Kazushi Takahashi and Yuji Tamura for their comments and suggestions on earlier drafts of this paper. Any remaining errors are our sole responsibility.

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DecomposingIntergenerationalIncomeElasticity:Thegender‐differentiatedcontributionofcapitaltransmission

inruralPhilippines

LeahBevisandChristopherB.BarrettCornellUniversity

August2013revisionCommentsgreatlyappreciated

AbstractAgrowingempiricalliteraturedocumentsstrongintergenerationalincomeelasticity(IGE)worldwidewhileaparallelliteraturefindsclearpatternsofparent‐to‐childtransmissionofhumancapital.AlthoughthelatterpatternclearlyhelpsexplaintheIGE,rarelydoauthorsdecomposetheIGEintodifferentpathwaysofintergenerationalcapitalandproductivitytransmission,muchlessexplorepossibledifferencesbetweendaughtersandsonsinthosepatterns.UsinglongitudinaldatafromruralPhilippines,wedecomposeIGEintofivedistinctpathways:theintergenerationaltransmissionsofhealth,education,land,andspouseeducationcapital,plusresidualintergenerationalcorrelationinproductivity.Wefindthatintergenerationalhumancapitaltransmissionsfrommothersarestrongerthanfromfathers.AlthoughthenaïveIGEestimatesarestatisticallyindistinguishableforsonsanddaughters,thepathwaysthatgeneratetheseresultsdifferstrikingly.Forsons,IGEisentirelyexplainedbyparent‐to‐childcapitaltransmission.Bycontrast,strongincomecorrelationexistsbetweendaughtersandparentsevenaftercontrollingforparentandchildcapitalendowments,suggestingthatitmaybeeasiertopromoteequalityofopportunityamongmalesthanamongfemalesinruralPhilippines.Maternaleducationisthemainparentalcapitaldriverofintergenerationalincometransmission,underscoringthelong‐termpayofftopromotingtheeducationofgirls,especiallythosefrompoorhouseholds. AcknowledgementsWethanktheNSF‐fundedFoodSystemsandPovertyReductionIGERTforfinancialsupport,IFPRIformakingthedataavailable,andworkshopaudiencesatCalvin,Columbia,Cornell,andthe2013AustralasianDevelopmentEconomicsMeetings,EconometricSocietyAustralasianMeetings,andOxfordCenterfortheStudyofAfricanEconomiesconferenceforhelpfulcommentsandquestions.SpecialthanksgotoMabelAndalon,SoniaBhaltora,PeterBrummund,RaviKanbur,JordanMatsudaira,CatherinePorter,AgnesQuisumbing,KazushiTakahashiandYujiTamurafortheircommentsandsuggestionsonearlierdraftsofthispaper.Anyremainingerrorsareoursoleresponsibility.

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1. Introduction

Intergenerationalincometransmissionestimatesmeasureacrucialcharacteristicofasociety:equalityofopportunity.Areallchildrenequallylikelytoforgeasuccessful(orunsuccessful)futurelivelihood–asreflectedbyzerocorrelationbetweenparents’andchildren’sincomes–orarechildrendestinedtostanduponthesamesocio‐economicrungsastheirparents,aswouldbetrueifincomeswereperfectlycorrelatedintergenerationally?Andifachild’sincomeishighlycorrelatedwithhisorherparents’,throughwhichmechanism(s)doesthistransmissionoccur?Dotheparents’productiveassetspasstothechildren,andifso,isithumancapitalembodiedineducationand/orhealth,orisitphysicalcapital,suchasagriculturallandthatiscentraltoincomegenerationinagrariancommunitiesinthedevelopingworld?Orisitinsteadtheproductivitywithwhichparentsandchildrenemploytheirwealth,perhapsduetoskillorsocialconnections,suchassocioeconomicmatchinginmarriage?Andarepatternsofintergenerationaltransmissiongenderneutralordomothersandfathersexertidentifiablydifferenteffectsontheirchildren’sadultwell‐being,anddodaughtersandsonsdependdifferentiallyonparentsfortheirownadultincomes?Weknowsurprisinglylittleempiricallyaboutthesemorenuancedquestionsabouttheunderlyingstructurebehindoft‐observedintergenerationalincomecorrelationsthatsuggestlimitedequalityofopportunity.Thatlacunamatters.Understandingthepathwaysthattiechildren’seconomicoutcomestothoseoftheirparentsallowspolicymakerstocraftpoliciesthatworktowardsprovidingallchildrenwithreasonablyequaleconomicopportunitiesinlife.Researchonthetopicgainsparticularpertinence,therefore,inthedevelopingworld,whereevidencesuggeststhatintergenerationalincometransmissionmaybeespeciallyhigh(Solon2002,Blanden2013),andwheretheeffectivetargetingofcostlypoliciesiscrucialtosuccessinpovertyreduction.Mosteconomistscouchparent‐to‐childincometransmissionintermsofintergenerationalincomeelasticity(IGE)estimatesgeneratedthroughregressionofchildren’sadultlogincomeontheirparents’logincome.Inequation1,thelogincomeofparentsinhouseholdjisgivenbyyj,thelogincomeofchildiinhouseholdjisgivenbyyij,andIGEisgivenbytheestimatedcoefficientb1:

yij=b0+b1yj+e (1)WhileIGEisaninterestingdescriptivemeasure,itobviouslydescribesonlystatisticalcorrelation;itdoesnotilluminatethepathwaysbetweenparentandchildincome.Understandingtherelativeimportanceamongthemultiplepotentialpathwaysiscrucialtothedesignofpoliciesdesignedtoreduceintergenerationalincometransmissionsoastoenhanceequalityofopportunity.Forinstance,perhapswealthierparentsinvestmorein(better)educationfortheirchildren,andapositivereturntoeducationraisesthesechildren’sadultincomesrelativetothoseofchildrenofpoorerparents.Orperhapswealthierparentstransfer(intervivosorviainheritance)land,moneyorotherphysicalassetstotheirchildren,andthisgreaterwealthleadsdirectlytohigheradultincomesforthesechildren.Inthefirstscenariobetterquality,freeeducationmightleveltheplaying

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fieldamongchildrenbornintohouseholdsofdifferenteconomicstatus,whileinthesecondscenarioamoreprogressiveinheritancetaxsystemorlandredistributionpolicymaybeappropriate.Orperhapsthereisnoappreciabledifferenceintheeducationalattainmentorproductiveassetholdingsofthechildrenofhigherincomehouseholds,andtheadultincomesofthechildrenofwealthierparentsaregreateronlybecauseoftheirsuperiorproductivity,whichiscorrelatedacrossgenerationsduetointer‐familialdifferencesingenetics,transferableskills,greaterfinancialliquidity,socialconnectionsorotherhard‐to‐observecharacteristics.Insuchacase,whereIGEarisesduetointrinsicheterogeneitythatiscorrelatedwithinfamilies,theremaynotbepolicyoptionsforeffectivelyincreasingequalityofopportunity.Incomeistheproductofcapitalstocksandtheproductivitywithwhichthosestocksareallocated.Wecanthereforecouchmostintergenerationalincomepathwaysintermsofintergenerationaltransmissionsofproductivecapitalsuchaseducation,health,orland.Assortativemarriage1mightbeviewedasanother,fourthcapitalpathway,ifparentsexertanyinfluenceovermarriagepatternsandcouples(atleastpartially)poolincomesorintra‐householdproductivityspilloversarise.Controllingforthesefourcapitaltransmissionpathways,anyresidualIGEconditionalonparentcapitalandspousalcharacteristicswouldsignalintergenerationalcorrelationinproductivityindependentofobservedhuman,physicalormaritalcapitalaccess.Weemphasize,however,thatintergenerationalcorrelationinproductivitynecessarilycapturesunobservedintergenerationalcapitaltransmission,andthusmayeasilybeoverestimated.Intergenerationalcapitaltransmissionsare,likeIGE,astatisticalmeasureofcorrelation.Knowingthatparenthealthorlandholdingsarecorrelatedwithchildhealthorlandholdingsdoesnotmakeclearthestructuralmechanismthatunderpinsthesetransmissions.Nonetheless,decomposingIGEestimatesintocomponentpathwayscanenhanceourunderstandingofintergenerationalincometransmission,ifonlybynarrowingdownthecandidatemechanismstoexploreforpolicypurposes.WhileIGEandintergenerationalcapitaltransmissionshaveeachbeenwelldocumentedwithintheirownliteratures(seesection2,below),fewstudieshaveattemptedtodecomposeIGEintotheconstituentcapitaltransmissionsbehindit.Thoseauthorswhodoattemptdecompositiontypicallyfocusonlyononemechanism,generatingestimatesthatmaybebiasedbyunobservedbutcorrelatedpathways(Erikssonetal2005,Piraino2007).Toourknowledge,decompositionofIGEintomultiplepathwayshasonlybeenattemptedinoneotherpaper,byBlandenetal.(2013)whostudymen’sintergenerationalmobilityinGreatBritainandtheUnitedStates(US).Inthispaper,weofferthefirstsuchdecompositionthatdistinguishesbetweendaughtersandsonsorthatexploresIGEinaruralareaofthedevelopingworld.Morespecifically,weconceptualizeIGEinBukidnon,thePhilippines,astheresultofintergenerationaltransmissionoffourdifferenttypesofcapital–education,health,land,andspouseeducation–andanyremaining,conditionalIGEduetointergenerationalcorrelationinproductivity.

1Assortativemarriagereferstothepropensityfornon‐randommatchingofmates.Ifpartnersmatcharoundattributesrelatedtoincomegenerationcapacity,thenthesedemographicpatternscouldmattertoIGE.

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InordertounderstandthecontributionofintergenerationalcapitaltransmissiontoIGE,wefirstexamineeachpathwayinturn.FirstwerunthenaïveIGEregressionin(1),instrumentingforparentalincomewithparentalexpendituresinordertobettercapturepermanentincome(onwhich,morebelow).Thenweexploretheassociationbetweenparentcapitallevelsandchildcapitallevels,allowingforcross‐capitaltransmissionsuchastherelationshipbetweenparenteducationandchildhealth.WenextdecomposeIGEintoparentcapitaltransmissionsandparentincometransmission.Weestimateallresultsseparatelyformalesandfemales,andsomeresultsseparatelyformigrantsandnon‐migrants(“splits”),whilecontrollingformeasurementerrorandlifecycleeffectsthatotherwisebiasIGEestimatesdownwards(Black&Devereux2010).ThenetresultisnotonlyanovelestimateofIGEinaruralareaofadevelopingcountry,butmoreimportantlyadecompositionthatfacilitatesincreasedfocusonthepathwaysthatmostimpedeequalityofopportunityinthissettingandtherevelationthatwhatappearstatisticallysimilarintergenerationalincometransmissionbetweendaughtersandsons,mothersandfathers,isinfactmarkedlydifferentintransmissionpathwaysbygender.Therestofthispaperproceedsasfollows.Section2providesbackgroundthroughabriefliteraturereview.Section3informallyexplainsthesimpleconceptualmodelbehindourempiricalanalysisandtheassociatedreducedformequationsforintergenerationcapitalandincometransmissionthatweestimate.Section4describesthePhilippinedataweuse.Section5explainstheestimationstrategy.Section6presentstheresultsforthecapitalandincometransmissionequations.Section7concludes.2.BackgroundMethodsofestimatingintergenerationalincomeelasticityhaveimprovedsteadilyovertime.OlderstudiesofIGEintheUStypicallyfoundIGEestimatesof0.2orless(Solon2002),signalingconsiderableequalityofopportunity.Suchfindings,however,wereusuallybiaseddownwardsbymeasurementerrorandlifecycleeffects(Behrman&Taubman1990,Solon2002,BlackandDevereux2010).CorrectingformeasurementerrorandlifecycleeffectsusingaverageparentincomeacrossmultipleyearscommonlyincreasesIGEestimatestoaround0.4intheUnitedKingdom(UK)andUS(Solon2002,Blanden2013),withlowerestimatesofaround0.1–0.2inCanadaandtheNordiccountriesofEurope(Corak&Heisz1999,Österbacka2001,Solon2002).Itispossible,however,thatmostexistingstudiesstillunder‐estimateIGEduetotheeffectsoftransitoryincomeandpriceshocksthatgeneratetemporaryvariationaroundpermanentincome.Unlikeclassicalmeasurementerror,errorduetotransitoryshocksislikelytopersistacrosstime,andlongerpanelsarethusrequiredtomitigatetheresultingattenuationbiasonestimatedincomecoefficients(Mazumder2005,Naschold&Barrett2011).Forexample,Mazumder(2005)showsthatIGEestimatesrosefrom0.45whenaveragingacross7yearsofUSsocialsecuritydatato0.61whenaveragingacross16years. Studiesofintergenerationalincometransmissionhavegenerallyfocusedonaparticulardemographic:malesinthedevelopedworld.Thedearthofstudiesinpoorercountriesis

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largelyduetolackofreliableincomedata(Núñez&Miranda2011,Black&Devereux2010).However,thefewstudiesthathaveinvestigatedincometransmissioninpoorcountriesusuallyfindrelativelyhighIGErates(Solon2002,Blanden2013).Conversely,thefewstudiesthathaveinvestigatedparenttodaughterIGE–inthedevelopedworld–havefoundcomparablylowerIGEratesfordaughtersthanforsons(Chadwick&Solon2002,Jänttietal2005).Raaumetal(2008)provideaframeworkforunderstandinghowIGEdiffersacrosssonsanddaughters,andattributemuchofthedifferencetoassortativemarriageandlaborsupplyresponseeffects.Onceestimated,thecrucialquestioniswhatgeneratestheseIGEs.Alargebodyofeconomicsresearchfromthe1990ssuggeststhateducationalachievementiscorrelatedwithinfamiliesandacrossgenerations(Thomas1996,Behrman1997,Behrmanetal2001).Asecondbodyoftheeconomics,nutritionandpublichealthliteraturesexploreshowparenteducationandparenthealtheachinfluencethehealthoutcomesofchildren(Thomasetal1991,Thomas1994,Bhalotra&Rawlings2011,forthcoming).Giventheincomereturnstobothhealthandeducation,theseintergenerationalhumancapitaltransmissionpathwaysseemlikelytoplayanimportantroleunderpinningIGEestimates(Alburg1998). SimilartothemethodusedinestimatingIGE,economistsoftencoucheducationtransmissionintermsofanestimatedregressioncoefficientrelatingparentalandchildeducationalattainmentmeasures.IntheUnitedStates,forexample,BehrmanandRosenzweig(2002)foundmedianestimatesof0.12yearsand0.15extrayearsofchildschoolingforeveryadditionalyearofmother’sandfather’sschooling,respectively.BehrmanandRosenzweig(2002)foundintergenerationaleducationcorrelationsof0.5‐0.7inLatinAmerica,andThomas(1996)foundcorrelationsof0.2‐0.4inSouthAfrica,dependingonraceandparentgender.Relativelyhighratesofintergenerationalschoolingtransmissioninpoorercountriesmaybeduetolowlevelsofparenteducation,poormacroeconomicconditionsandtoalackofgovernmentinvestmentinpubliceducation,allfoundtobesignificantlyrelatedtolowlevelsofschoolingmobility(Behrman&Rosenzweig2002,Corak&Heisz1999,Hertzetal2007). Healthtransmissionismoredifficulttoestimatethaneducationtransmission,giventhemultidimensionalnatureofhealth(Strauss&Thomas1998).Publishedestimatesofparent‐childlifespancorrelationfallbetween0.15and0.3(Yashin&Iachine1997).Erikssonetal(2005)findanaverageparent‐childmorbiditycorrelationofabitunder0.3.Mother’sbirthweightandnutritionalstatusisclearlyassociatedwithchildbirthweight(Currie&Moretti2007,Victoriaetal2008,Blacketal2008),andBhalotraandRawlings(2011)findpositiveassociationsbetweenmaternalandchildhealthoverarangeofindicatorsin38developingcountries.Heightisoftenconsideredthebestsinglemeasureofadulthealth“stock,”giventhatitcaptureshealthshocksfrominuterothroughearlyadulthood(Thomasetal1991,Thomas1994).Inthedevelopingworldespecially,wherestuntingduetomalnutritionanddiseaseiswidespread,heightmaybethemosttellingmeasureofaccumulatedhealth(Fogel2004,Costa1998,Dasgupta1997).

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Cross‐capitaltransmissionbetweeneducationandhealthisalsowelldocumented,themostcommonexamplebeingtheimpactofmaternaleducationonchildhealth.Thomasetal(1991)findthatmaternaleducationpositivelyaffectschildheight‐for‐age,andthatthisassociationappearstobeworkingthroughaccesstoinformation.Thomas(1994)findsthatinthreecountries(Brazil,GhanaandtheUS)maternaleducationhasalargerpositiveimpactondaughters’heightthanonsons’height,whiletheoppositeistrueforpaternaleducation. Giventhewell‐establishedliteratureonintergenerationaltransmissionofeducationandhealth,itisperhapssurprisingthatonlyafewstudieshaveattemptedtoestimatethecontributionofeithertransmissiontoIGE.Piraino(2007)estimatesthatintergenerationaleducationtransmissionaccountsforroughlyone‐thirdofIGEinItaly.Pekkarinenetal(2009)findthatmajoreducationalreforminFinlandreducedIGEby23percent,andAsadullah(2012)findsthatcontrollingforson’seducationreducesestimatedIGEinruralBangladesh.Erikssonetal(2005)findthataftercontrollingforchildhealthstatus,estimatedIGEinDenmarkdropsby28percentforsonsandby25percentfordaughters.Toourknowledge,onlyonepaperattemptstosimultaneouslyaccountformultipleintergenerationaltransmissionpathwaysbehindestimatedIGE.Blandenetal(2013)useadecompositionapproachtoinvestigatethecontributionofeducation,occupation,labormarketattachment,maritalstatusandhealthtoIGEformalechildrenintheUSandGreatBritain.TheyfindthateducationtransmissionisthepredominantpathwaybehindIGEintheUS,whileoccupationtransmissionisthepredominantpathwaybehindIGEinGreatBritain.TheirstudyillustratesthevariableimportanceoftransmissionpathwaysbehindIGEevenwithinculturallysimilar,developedcountriesandforchildrenofasinglegender.Itthushighlightstheneedtoinvestigatethesepathwaysinothercontexts.Giventheimportanceoflandinagrariansocieties,itseemslikelythatlandinheritancemayalsoplayaroleincreatingintergenerationalincomecorrelationsinmuchofthedevelopingworld.Forinstance,asignificantproportionofchildrenintheruralPhilippinesinheritlanduponmarriageoraparent’sdeath,thoughthispracticeisdecliningaslandbecomesscarcer(Estudilloetal2001b).Itseemsclearthatparentsfavorsonsoverdaughterswhenbequeathinglandtoprogeny,butinrecentyearsfavordaughtersoversonswheninvestingineducation(Estudilloetal2001a,Estudilloetal2001b).Estudilloetal(2001a)attributethelandinheritancepatterntothefactthatintheirstudyarealandisprimarilyusedforricecultivation,traditionallyamaledomain.Anumberofscholarshaveshownthatassortativemarriagecontributessignificantlytointergenerationalincomeelasticity(Raaumetal2008,Black&Devereux2010).ChadwickandSolon(2002)findthatintheUS(wherespousestypicallyhaveseparateincomes),theindividualearningsofahusbandorwifeareashighlycorrelatedwiththeearningsofhisorherin‐lawsaswiththeearningsofhisorherparents.Ermischetal(2006)estimatethatabout40percentoffamilyincomepersistenceintheUKandinGermanyresultsfromassortativemarriage.

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ItseemspossiblethattheeffectsofassortativemarriagemaybeparticularlyimportantinthePhilippines,wherevariousauthorsagreethatthereturnstoschoolingarehigherforwomenthanformen(Sakellariou2004,Quisumbingetal2004).ThismaybeinpartbecauseschoolingincreaseslaborforceparticipationbywomenmorethanformeninthePhilippines,orbecauseofarelativelylargegenderearningsgapinfavorofmenwithinpoorlyeducatedsubpopulations,whichnarrowsquicklywithinmoreeducatedsubpopulations(DeSilva&Bakhtiar2011,Sakellariou2004).DeSilvaandBakhtiar(2011)specifytwoadditionalavenuesthattheybelieveworkthroughthemarriagemarket.First,bettereducatedwomensecureforthemselveshigher‐earninghusbands.Second,well‐educatedwivesenhancethelaborproductivityoftheirhusbandsthroughtheexchangeofideas,mutuallearning,andintra‐householdspecialization.Thenarrativeofmigrationhashistoricallybeenoneofupwardindividualeconomicmobility.InboththeLewis(1954)andHarrisandTodaro(1970)models,agapbetweenexpectedruralandurbanearningsdrivesanindividualtomigrate.Itisworthasking,however,howmigrationisassociatedwithintergenerationaleconomicmobility,ifatall.Ismigrationanescapefromthesocio‐economiccircumstancesofone’sfamily,ordoesfamilyincomeandproductivecapitalpavetheroadformigrants,suchthatmigrationissimplyanothermechanismbehindintergenerationalincomecorrelation?Beegleetal(2011)findhighincomereturnstomigrationfromruralTanzania;yetindividualswhomigrateusuallycomefrombetterofffamilies.ThissuggeststhatmigrationmayworkasamechanismbehindIGEinruralTanzania.QuisumbingandMcNiven(2010)suggestthatmigrationmaybeusedasanescapefromfamilypovertyinruralPhilippines,buttheyalsofindthateducationincreasesone’slikelihoodofmigrating.Ifthereisintergenerationaltransmissionofeducation,thenitisunclearwhethermigrationincreasesordecreasestheassociationbetweenmigrantandparentincomeinthiscontext.AddingtothatambiguityisthefactthatPhilippinemigrants,especiallydaughters,commonlysendremittanceshometotheirfamilies,whichmayincreaseparent‐childincomecorrelationinthe“opposite”directionfromthatusuallysupposed.Insummary,itisclearthateducation,health,land,andspouse’seducationareoftenimportantpredictorsofincome,bothgenerallyinthedevelopingworldandspecificallyinthePhilippines(Maluccioetal2009,Estudilloetal2001a,Estudilloetal2001b,Quisumbing1994).Thesecapitallevelsareinfluencedbyparentcapital,bothdirectlyandthroughparentincomethatcanfosterinvestmentinchildren’scapitalaccumulation.Suchinfluencemaydifferacrosschildandparentgenderandalsoacrossspace,assomechildrenmovefurtherfromtheirparentsthanothers.Multivariatecapitaltransmissionthereforelikelyexplainsatleastpartofintergenerationalincomeelasticity,althoughtheremayberesidualIGEconditionalonallofthesefactors,whichwouldseemtoreflectintergenerationalcorrelationinproductivityduetofactorsotherthanthecontrolled‐forcapitalstocks.Moreover,howmucheachtransmissionpathwaycontributestoaggregateIGE,andwhetherthepowersofvariouspathwaysdifferacrosscategoriesofchildren(malevs.female,ormigrantvs.non‐migrant),isanopenquestion,unexploredinboththeintergenerationalincometransmissionliteratureandtheintergenerationalcapitaltransmissionliterature.Wecontributenewempiricalfindingstohelpbegintofillthatgap.

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3.ConceptualModelInordertoinformtheempiricalanalysisthatisthecorecontributionofthispaper,inthissectionweinformallylayoutasimple,conceptualmodelofintergenerationaltransmissionofdifferentformsofcapitalthatresultinintergenerationalcorrelationinincomes.Considerahouseholdmadeupofparentsandchildren.FollowinganapproachbegunbyBecker(1974)andBeckerandTomes(1979),weassumeparentsarealtruistic,andcollectivelymaximizeutilityovercurrentconsumptionandtheexpectedfutureincomelevelsoftheirchildren,constrainedbytheirowncurrentincome.Childgenderisexogenous,andparentsperceivethefutureincomesoftheirchildrentobegender‐specificfunctionsofchildeducation,health,landownership,andtheearningpotentialofthechild’sfuturespouse.Futureincomemayalsodependonchildren’sgeneticallyorsociallyheritableattributes,suchasabilityandsocialnetworks,thatarepositivelycorrelatedacrossgenerationswithinthefamilyandobservedbytheparentsbutunobservedbytheeconometrician.Parentsmaximizeutilityovercurrenthouseholdconsumptionandchildfutureincomebychoosingoptimallevelsofinvestmentinchildcapitalstocks,whichgeneratesintergenerationaltransmissionofeducation,health,landandspouseeducationcapitalstockstoeachoftheirchildren.2Thefirsttwopathwaysforhumancapitaltransmissionoccurduringachild’sformativeyearsathome;thelattertwousuallyoccurwhenachildleaveshisorherparent’shouse.Weassumethatthedecisiontoleavethehouseisexogenoustochildcharacteristics,sincemostchildreneventuallyestablishtheirownhousehold.However,weallowachild’sdecisiontomigrate(ratherthantoremaininthelocalareaofhisorherbirth)tobeendogenoustoparentandchildcapitallevels.Parentincome,whichconstrainsthemaximizationproblem,isitselfafunctionofthesameparentcapitallevelsthatcontributetochildincome:education,health,andland/assetownership.Householdsizealsoconstrainsthemaximizationproblem,andmayalsobeafunctionofparentcapitallevels,suchasmaternaleducation.Thus,intergenerationalcapitaltransmissionscanbeaffectedbyparentcapitalstocksin(atleast)threedistinctways.First,insomecasestheyaredirectlyconstrainedbyparentcapitalholdings.Forexample,parentswithextensivelandholdingsarebetterabletogivetheirchild(ren)landthanarelandlessparents.Similarly,anunhealthymotherwilloftentransmitpoorhealthtohernewborn,ceterisparibus.Second,parentalpreferencesandexpectationsmaythemselvesbeaffectedbyparentcapital(Jensen2010,Maertens2013).Forexample,apoorlyeducatedfathermaynotbelievethateducationisimportanttothefutureearningsofhischildrenandmightnotputintrinsicvalueontheireducation.Whilethismechanismisconceptuallydistinctfromthefirstone,itwillbeobservationallyequivalenttoanalysts,likeus,wholackdataonparents’

2Spousecapitaltransmissionreferstotheinfluenceparentshaveoverdeterminingtheirchild’sfuturespouse.Parentsmayraisetheirchildtopreferacertaintypeofspouse,theymaydirectlychoosetheirchild’sspouse,theymayprovidechildrenwithsocialnetworkswhichleadtoaparticulartypeofspouse,etc.

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subjectivevaluationofalternativeformsofchildcapital.Thesefirsttwomechanismswillinfluencechildcapitallevelsregardlessofparentincome.Parentexpectationsandpreferencesmayalsodependuponchildgender.Forinstance,parentsmayperceivethereturnstolandoreducationtodifferacrosschildgender,asfoundinthePhilippinesbyEstudilloetal(2001a).Parentperceptionsmayalsobeshapedbysocialnorms,whichoftenregardbirthorderandmaybedictatedbyethnicgroup(LaFerrara2007).Itisthereforeimportanttocontrolforthesefactorswhenattemptingtorecoverparent‐to‐childcapitaltransmissions.Third,intergenerationalcapitaltransmissionmaybeinfluencedbythefinancialliquidityeffectofparentcapitalonparentincome.Ifcapitalmarketsfunctionperfectly,parentsinvestinchildcapitaluntilthemarginalreturnsequaltheinterestrateonborrowing.Butinmanyplaces,perhapsespeciallyruralareasofthedevelopingworld,accesstocredittofinancelong‐terminvestmentsiscommonlylimited.Borrowingconstraintsincreasetheopportunitycostofinvestment.Asaresult,parentalcapitalstocksmayhaveastrongeffectonchildcapitalaccumulationbyobviatingliquidityconstraintsoninvestmentsinschoolingorhealthcarefortheirchildren(Loury1981).Ofcourse,ifparentincomehaslittleimpactonchildcapitallevels–forexample,inasocietywithhighqualitypublicschoolsandfreegovernmentclinics,orwithperfectlong‐termcreditmarkets–thismechanismmaybeweak.Theremaybecross‐capitaltransmissioneffectsas,forexample,whenparentaleducationpositivelyaffectschildhealthstatus.Thesecross‐capitaleffectscannotrepresentthefirst,directtransmissionpathway.Butinadditiontothepossibleeffectsofparentalcapitalinobviatingliquidityconstraints,theycanreflecteitherdifferencesinparentalpreferencesandexpectations–aneffectthatshouldbeindependentofparentalincome–orpossibleeffectsofparentalcapitalintheproductionofnontradablechildcapital,asinthecaseofmaternaleducationaffectingchildhealth.Soitisstilldifficulttoisolatetheeffectsofparentalpreferencesandexpectationswithoutimposingundulystrongassumptions.Furthermore,intergenerationalcorrelationinproductivitycanleadtointergenerationalcorrelationinincomesindependentofassetaccumulation.Soparentalincomecaninfluencechildadultincomethroughseveralcausalpathways,butacorrelationbetweenparentandchildincomemayalsoreflectunseenproductivityorevencapitaltransmissions.Accordingtothisframework,achild’sadultincomemaybecorrelatedwithparentincomethroughanyofmultiplemechanisms,someofwhichoperatethroughparentincome,othersofwhichdependonparentcapitallevelsindependentofparentalincome.ThisstandsincontrasttotheworkhorseregressionspecificationforestimatingIGE,equation1,whichignorestheinfluenceofparentcapitallevelsonchildincome.Beforeexaminingthereducedformequationsthatweestimate,recallthatincomeistheproductofone’scapitalandtheproductivitywithwhichoneappliesthatcapital.Thus,in

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ourconceptualmodel,parentj’sincome, ,stemsfromparenteducation, ,parenthealth, ,andparentland, ,allinteractedwithunobservableproductivity.Parentcapitallevelsinfluencechildcapitallevelsthroughdirecttransmissionandcross‐capitaltransmissionrelatedtoparentalexpectationsandpreferences,andalsothroughaffectingparentincomeusedtoinvestinchildcapitalformation.Childiinhouseholdjwillthusgrowuptoattainfixedquantitiesofhisorherowncapitallevels:education, ,health, ,land, ,andspouseeducationcapital, .Andfinally,likehisorherparents,thechildiwillearnandincome, ,thatresultsfromhisorhercapitallevelsandproductivity.Figure1illustratesthesetransmissionpathwaysvisually.Equations2‐5thenreflectintergenerationalcapitaltransmissionstochildifromhouseholdj,asweestimatethemintheBPSdata.Equation6reflectstherelationshipbetweenchildincomeandparentincomeconditionalonchildcapital,therebyreflectingchildproductivity,includinganyunobservedintergenerationalcapitaltransmission.Inallequations,thevector includescontrolsforhouseholdsizeandvariablesthatcontrolforsocialnorms(ethnicgroup,childhooddistrict,andsex‐specificbirthorderdummies).E θ θ θ (2)H θ θ θ (3)L θ θ θ (4)S θ θ θ (5)y λ λ λ (6)Substitutingequations2‐5intoequation6givesareducedformequationforchildincome,asinequation7.Additionallycontrollingforchildcapitalresultsinequation8,whichnestswithinitthepriortworeducedformrelationships.ThesespecificationsenableustoisolatetheintergenerationalcorrelationinproductivityindependentofintergenerationaltransmissionofvariousformsofproductivecapitalaswellseektounpackIGEestimates.y λ λ λ (7)y λ λ λ λ λ λ (8)Inequations2‐5,thecoefficient estimatestheeffectofparentalincomeonchildaccumulationofcapitaloftypec,reflectingliquidityeffectsonchildcapitalaccumulationbeyonddirectintergenerationalcapitaltransmissionorthatattributabletoparentalexpectationsandpreferencesalone.Thecoefficientθ estimatesthedirecttransmissiontochildcapitalcfromparentcapitalp.Notethatweallowexplicitlyforcross‐capitalinfluences,suchastheeffectofparentalhealthorlandholdingsonchildren’seducation.Becauseoneformofcapitalcannotbeconvertedtoanother,otherthanthroughincomeandresultinginvestment,intergenerationalcross‐capitaltransmissionmostlikelyreflectstheroleofparentalexpectationsandpreferenceswhenonecontrolsforparentalincome.Thisestimationstrategytherebypermitsustogetasenseastotherelativeimportanceof

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financialliquidity(the estimates),parentalexpectationsorpreferences,versusdirectintergenerationalassettransfersasmechanismsforchildcapitalaccumulation.Equation6explainschildadultincomeasafunctionofchildcapitalandparentalincome.Theparameter reflectstheimpactofparentalincomeindependentofitseffectonchildcapitalaccumulation,i.e.,theeffectofproductivitytransmissionplusanyunobservedcapitaltransmission.Estimatesofthisequationallowustotestthehypothesisthat 0,implyingtheabsenceofproductivitytransmissionandthatIGEoperatesentirelythroughparentalinvestmentinchildren’scapitalstocks.Theparametervectorλ representsthereturnstochildi’sstockofcapitalcinthisrestrictedspecification.Bycontrast,inequation7,theparentalincomecoefficient estimatesthecombinedinfluenceofparentincomeonultimatechildadultincome–thatis,thecumulativeeffectofparentalincomeonchildproductivecapitalaccumulationthroughrelaxedliquidityconstraints,independentofdirectintergenerationalcapitaltransmission,plusintergenerationalcorrelationinproductivity.Thecoefficientλ estimatesthecombinedinfluenceofalldirecttransmissionsfromparentcapitalponultimatechildincome.Estimatingequations6and7allowsustotestthehypothesisthat ,implyingthatparentalliquidityconstraintsdonotaffectchildcapitalaccumulation.Equation8isthemostgeneralspecification,whichallowsustotesttheexclusionaryrestrictionthatthevectorλ 0,signalingthatparentalcapitalhasnodirecteffectonchildincome,butonlyoperatesthroughchildcapitalaccumulationandproductivitytransmission.Ofcourseifthisistrue,equation7collapsesbacktoequation4.Thisyieldsthecomplementaryhypothesesthat andλ λ ,implyingthatintergenerationalproductivitytransmissionandthereturnstodifferentformsofchildcapitalareallinvarianttoparentalcapitalendowments.Therelativemagnitudesofthesecoefficientestimateshavedirectpolicyimplications.Ifthe incometransmissioncoefficientsaresignificantandlargethenchildcapitallevelsarenormalgoods,andinfrastructuresuchasbetterpublicschools,freehealthclinicsinruralareasormoreaggressivetaxpoliciescanmitigateintergenerationalcapitalaccumulation.If isalsolarge,suchpoliciesmightalsomitigateeventualintergenerationalincometransmission.Ofcourse,incometransmissioncoefficientscouldbelargebut small,reflectinglowreturnstohumancapital.Orincometransmissioncoefficientscouldbesmallbut large,signalinghighratesofintergenerationalcorrelationinproductivity.Ifincometransmissioncoefficientsand arebothsmall,however,andinsteadthedirectcapitaltransmissioncoefficientsarelarge,thenchangeinparentcapitallevelsmaybenecessarytoimprovesocialmobility,implyinganeedforprogramsthatreachoutspecificallytolow‐capitalparentsandtheirchildren.Thatiswhyitbecomesimportanttotesttheexclusionaryrestrictionthatparentcapitalexertsnoinfluenceonchildadultincomeindependentofparentalincome(theintergenerationalproductivitytransmissionparameter)andchildcapitalaccumulation(thereturnstocapitalparameters).4.Data

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ThedataweregatheredoverthecourseoftwodecadesinNorthernMindanaoDistrictinthePhilippines.Thefirstroundofdatawasgatheredoverfourwavesin1984/85,inarural,landlockedprovincecalledBukidnon.Thissurvey,underthePhilippinesCashCroppingProject,wasfocusedonhouseholdeffectsofagriculturalcommercialization.Itsampled510familiesfromruralBukidnon,almostallofwhomreliedheavilyonagriculturalincome.ThesecondroundofdatawasgatheredbytheInternationalFoodPolicyResearchInstitute(IFPRI)andtheResearchInstituteforMindanaoCulture(RIMCU)in2003/04,usingaquestionnairehighlysimilartotheonefrom1984/85.Thissurvey,calledtheBukidnonPanelSurvey(BPS)in2003/04,wasadministeredtothreetypesoffamilies.First,itinterviewedalloriginalhouseholdsstilllivingintheoriginalsurveyarea,atotalof311households(61percentoforiginalrespondents).Duringthissurvey,originalrespondentslistedallnon‐coresidentchildren,andalsoprovidedbasicinformationaboutmanyofthesechildrenincludinglocation,educationalattainment,andmaritalstatus.Alsoduringthissurvey,coresidentchildrenwereinterviewed.However,wedonotincludedatafromcoresidentchildreninthispaper,giventhattheyareneverhouseholdheadsandarenotearningincomeindependentlyfromtheirparents.3Second,itsampledatrandomuptotwonon‐coresidentchildrenneartheiroriginal(parent)household,atotalof261households.Werefertothesechildrenas“splits”fortherestofthepaper.Third,itsamplednon‐coresidentchildrenlivingfurtherawayfromtheirparenthousehold.Thesechildren,whowerefertoas“migrants,”werelivinginthethreeurbanareasinMindanao,orinmunicipalityseats,orinotherruralareasofBukidnon.About75percentofpotentialmigrantswereinterviewed,foratotalof257migranthouseholds.Thesplitandmigrantchildreninterviewedin2003and2004wereonaverage10.3yearsofagein1984,withastandarddeviationof5.7years.Fifty‐sixpercentwerefemales,and65percentofthosewhowouldlaterbecomemigrants(asopposedtosplits)werefemales.Allchildrenareeithersonsordaughtersofthe1984householdhead,withtheexceptionof3femalerelativesand1femalenon‐relative.Givenourassumptionsaboutthetimingofintergenerationalcapitaltransmissions,itisimportanttonotethatofthe402marriedchildren(92%),73%leftthehouseholdtheyeartheygotmarried,and84%leftwithin2yearsofgettingmarried.Ofthe89childrenwhoinheritedlandfromtheirparents,60%

3Ofthesonsanddaughterslistedinthe1984survey,4percentare“lost”inthe2003/2004surveys–mentionedneitherasco‐residingchildrennoraschildrenwhohavemovedoutofthehousehold.Ofthechildrenwhowerenotlost,29percentstillresidedwiththeirparentsin2003,41percenthadmovedoutoftheirparents’housebutwerenottrackedforinterview,and30percenthadmovedoutandweretrackedforinterview.Surprisingly,therewerenoinstancesofchildrenwhoremainedinthehouseholdandbecamehouseholdheads.Weusethelastcategoryofchildren(the30percentwhoweretrackedforinterview)inouranalysis.Theomissionofco‐residentchildrenmightslightlybiasdownwardscoefficientestimatesbasedonpercapitahouseholdincome,givenstrongerintra‐generationalautocorrelationthanintergenerationalcorrelationacrossperiods.Thisbiasisunavoidable,however,giventhatwehaveonlyhouseholdlevelincomedata.

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inheritedwithinayearofleavingtheirparent'shouse,and71%inheritedwithinayearofgettingmarried.Thus,ourassumptionsthatlandandspouseeducationtransmissionoccuraschildrenareleavingtheirchildhoodhomedoseemtohold.ForevenmoredetailsontheBPSdata,seeQuisumbing&McNiven(2009).Original(round1)familieswhowerefoundandre‐interviewedin2003arenotablydifferentin1984thanfamilieswhichwerenotfoundin2003.Theformeraresignificantlylarger,withmorechildren,andheadedbyindividualswhoareolderandmigratedtotheir1984locationearlier.Theyownmoreland,dependmoreheavilyonhome‐producedfood,incomefromcashcroppingandcorn,anddependlessheavilyonnon‐agriculturalsourcesofincomeandagriculturalwagelabor.Theyalsohavehigherincomeandexpenditurelevels.Mostofthesedifferencesaresignificantattheonepercentlevel,andallatthefivepercentlevel.Givensuchattritioneffects,theintergenerationaltransmissiontrendsdiscussedinthispapershouldbeconsideredspecifictothesampleoffamilieswhoremainedinBukidnonthrough2003.Whileitseemslikelythatfamily‐levelmigrationwouldchangesubsequentintergenerationaltransmissiontrends,suchanalysisisunfortunatelyimpossiblewiththesedata.Inthispaper,parentvariablesaretakenfromthe1984survey.Whileitwouldbeidealtotakesomeparentcharacteristics,suchaslandholdings,fromtheyearduringwhichchildrenfirstlefttheirparent’shousehold,thesedataarenotavailable.Childattributesduringchildhood,asexaminedinTable4,alsocomefromthe1984survey.Weusechildattributesinadulthood(suchaschildincome,childheight,andchildeducationalattainment)fromthe2003/04surveysofnon‐coresidentsplitandmigrantchildren.Table1displayssummarystatisticsformalechildren,femalechildren,splits(i.e.,non‐migrants)andmigrants.Aseriesoft‐testsshowsthatthereisnosignificantdifferenceinobservablecharacteristicsbetweenmigrantsandsplitsduringchildhood,exceptthatmalemigrantstendtobeofaslightlylowerbirthorder,averagingaroundthird‐bornwhilethemalesplitsaveragearound2.5‐born.Byadulthood,however,therearediscernibledifferencesbetweenmigrantsandsplits.Bothmaleandfemalemigrantsaresignificantlymoreeducated,havesignificantlygreaterincomes,andaresignificantlylesslikelytobemarriedthansplits.Thereisnodifferenceinheightacrossadultmigrantsandsplits.Sincet‐testssuggestthatmigrantsandsplitsaresimilarasyoungchildren,itseemsunlikelythatparentsinvestintheirchildren’scapitallevelsaccordingtofuturemigrantstatus.Wethusanalyzeintergenerationalcapitaltransmissionsseparatelyformalesandfemales,butnotseparatelyacrosssplitsandmigrants.Migrationhasoccurred,however,by2003whenchildrenaremarried,livingintheirnewhouses,andearningincome.Bythistimetherearediscernibledifferencesbetweensplitsandmigrants,anditseemsplausiblethatmigrantsmightexperiencedifferentintergenerationalincomemobilitytrendsthannon‐migrants.Forthisreason,weanalyzeanddecomposeIGEseparatelyformales,females,migrantsandsplits.Inthesefinalregressionswecontrolforgenderwhengroupingchildrenbymigrantstatus(sincegendercertainlyeffectsincome),butwedonotcontrolformigrantstatuswhengroupingchildrenbygender(sinceweconsidermigrantstatuspotentiallyendogenoustochildcapitallevels).

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Thereisnoapparentselectionbiasinthechoiceofsiblingswhoweretrackedin2003/2004.Anexaminationoftheirsex,age,health,educationlevels,andheightandweightz‐scoresshowsthatthechildrentrackedbytheBPSsurveywerenotsignificantlydifferentin1984thantheirsiblingsexceptbysex,ageandbirthorder(seeAppendix1).Trackedchildrenweresignificantlylesslikelytobemale,andwereofsignificantlygreaterageandhigherbirthorder.Sinceolderchildrenweremorelikelytohavemovedoutoftheirparents’houseby2003/2004,thedifferenceinageandbirthorderisexpectedanddoesnotimplyanydifferenceinothercharacteristics;itlikelyjustreflectslifecycleeffectsforwhichwecontrolanyway.Trackedchildrenaremoreoftenfemalechildrenlargelybecausefemalesmigratedmoreoftenthanmalechildren,andsoahigherproportionofthemigrantchildrentrackedin2004werefemale.Evenofthesplitchildrenclosertohome,however,slightlymorefemalechildrenweretrackedthanmalechildren,adifferencethatisstatisticallysignificantatthetenpercentlevel.Sincewepresentallresultsacrosssex,thisselectionissuedoesnotaffectanyofourresultsexceptinasmuchasitdecreasessamplesizeformalechildren.Throughoutthispaper,thevariableseducationandspouses’educationaremeasuredinyearsofschoolingcompleted,4landismeasuredinhectaresowned,andheightismeasuredincentimeters.Thebaselineheightofallfamilymembers(adultsandchildren)isanaverageoverfourroundsofanthropometricdatagatheredduring1984/5.The2003/4heightdataweregatheredagainthroughmeasurement,butinonlyoneround.Incomeandexpendituremeasuresareexpressedinlogterms,andrepresenttheaverageweeklyincome/expenditureoftheentireco‐residenthousehold.Bothvariableswereaggregatedfromanumberofdifferentmodules.In2003/4thesemodulesaccountedforincomefromand/orexpenditureson:landrental;agriculturallabor;majorcropproduction;fruitandvegetableproduction;wageemployment;non‐agriculturalbusinesses;inheritance;NGOorgovernmentbenefits;gambling;non‐landassetsales;livestock;foodpurchases.Allincomeandexpenditurevariablesaredeflatedbyprovince‐specificconsumerpriceindicesobtainedfromtheNationalStatisticsOfficeinManila.5Weuseheightastheindicatorforparentandchildhealthfortworeasons.First,heightisagoodmeasureofhealthstock,inthatitcapturesthefinaloutcomeofmanyyearsofvaryinghealthinvestmentsandhealthshocks(Thomas1994).Second,fullheightisattainedroughlysimultaneouslywiththecompletionofeducation,bothundertheauspicesofparentalguidanceandinvestment.Thus,itrepresentschildhoodhealthformation,heavilyweightingtheearliestyearsofliferatherthanlaterhealthconditionsattainedonceachildislivingseparatelyfromhisorherparents.4Ideally,onewouldincludemeasuresofchildcognitiveabilityorperformanceasyetanotherformofintergenerationalcapitaltransmission.Unfortunately,nosuchvariablesexistinthesedata.Thus,thetransmissionofcognitiveabilityiscapturedonlywithintheproductivitytransmissionmeasuredinequations13and15.5All1984familiesliveinoneprovince(Bukidnon),duringbothroundsofthepanel.MostgrownchildrenalsoliveinBukidnon,butby2004afewmigrantshavegoneasfarasMisamisOriental,aneighboringprovinceonthecoast.

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5.EstimationStrategyThroughoutthepaperweadjustformeasurementerrorinandtransitoryshockstoparentincomebyinstrumentingforparentincomewithparentexpenditure,whichbetterreflectspermanentincome.6,7Weinstrumentthisway,ratherthanaveragingmultipleperiods’incomeobservations,becausetheBPScontainsonlytworoundsofparentincomedata.Underclassicalmeasurementerror,butespeciallyunderthetime‐persistentmeasurementerrorthatislikelytoexistaroundpermanentincome(Mazumder2005,Naschold&Barrett2011),tworoundsofdatawillnotsignificantlymitigateattenuationbiasonincometransmissionorIGEestimates.Thisestimationstrategyeliminatesmeasurementerrorbiasinestimatedincomecoefficientsifmeasurementerroraroundpermanentincomeisorthogonaltomeasurementerroraroundexpenditure.Foranyrandomcomponentofmeasurementerror,forinstancemisreportingormisrecordingerror,suchorthogonalityseemslikely.Orthogonalitymayseemlesslikelytoholdforerrorduetotransitoryincomeshocks.Butwetestforandfindstrongevidenceofconsumptionsmoothingthatmakesthisassumptionplausible(seeAppendix2).Consistentwithpriorresultsintheliterature,instrumentingforsingleyearincomewithexpenditure,asaproxyforpermanentincome,resultsinasignificantlyhigherIGEestimatethandoesaveragingacrossjusttwoperiods.TableA4inAppendix2comparestheseestimatesfortheentiresampleofchildrenandforsub‐samplesselectedbygenderandmigrantstatus.Weuse1984parentincome/expendituremeasuresratherthan2003parentincome/expendituremeasures,forthreereasons.First,the1984measuresbetterpredictchildincomeandassetlevels.Second,wewishtocapturethecausalpathwaysbetweenparentandchildincome,andthecapitaltransmissionsthatwehypothesizeserveasthesepathwaysoccurprimarilyduringchildhoodandyoungadulthood.Thepermanentincomeofparentsin1984oughttoholdmoreinformationaboutthesepathwaysthanthepermanentincomeofparentsin2003.Third,2003parentexpendituresmay,tosome

6Notethatweinstrumentnottoaddressanendogeneityissue,whichwouldrequireaplausibleexclusionaryrestriction,butrathertoobviateanerror‐in‐variablesproblemthatwouldotherwiseleadtoattenuationbiasintheIGEestimates.Thisdoesimply,however,thatifparentexpenditureswereto(positively)affectfuturechildincomeinanywayexceptthroughcorrelationwithaparent’spermanent/structuralincome,thecoefficientestimateonparentincomemightbebiased(upwards)inallcapitalandincometransmissionregressions.Wethereforetestedtheexclusionaryrestrictionbyregressingchildincomeonbothparentincomeandparentexpenditure.In15of18cases,wecouldnotrejectthenullhypothesisthatparentexpenditurehadnoindependentcorrelationwithchildincomeinfavorofthealternatehypothesisofapositivecorrelation.Detailsofthesetestsareavailablebyrequest.Inthefewcaseswheretheexclusionaryrestrictiondoesnothold(notedinthetext),thenon‐adjustedandadjustedestimatesoftheparentincomecoefficientmaybeviewedaslowerandupperbounds,respectively,aroundthetrueIGEcoefficient.Thequalitativestoryisnonethelessconsistentwhicheverofthoseestimatesoneprefers.7Wepreferusingexpendituresasaninstrumenttousingexpendituresasaproxy(i.e.,usingexpendituresdirectlyratherthanincomepredictedoffofexpenditures)butthequalitativeresultsareunchangedifweuseitasaproxyinstead.

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extent,reflectremittancesfrommigrantandsplitchildren,andweareinterestedinisolatingthemechanismsbehindIGEthatflowfromparenttochildratherthantheotherwayaround.Theestimationofequations2‐8representstheprimarycontributionofthispaper.Becausecapitaltransmissionslikelyshareanerrorstructureforanygivenchild,wewouldnormallyestimateequations2‐5simultaneously,correctingforlikelymeasurementerrorinparentincomeusingThreeStageLeastSquares(3SLS).8However,becauseourregressorsareidenticalacrossall4transmissionequations,orderconditionsdonotholdforsimultaneousestimation,and3SLSisequivalenttoaseriesof4ordinaryleastsquaresestimations,instrumentingforparentincomewithparentexpenditure(OLS‐IV).Thisishowweestimatethefourtransmissionequations,whichappearinTables2and3,andalsohowweestimateEquations6‐8,whichappearinTables5‐8.Inallinstancesweclustererrorsattheparenthouseholdlevel.Becauselandinheritanceandspouseeducationcapitallevelsaredeterminedinthesameperiodasmigrantstatus(whichindicateswhetherachildmovesoutsideoftheirparents’barrio,orgeographicarea),wedonotcontrolformigrantstatusinequations4and5.Wetreatmigrantstatusasanintermediaryoutcome,itselfaconsequenceofparentcapitallevels.Ratherthanbeingaformofhumancapitalinandofitself,migrationchangesthereturntohumancapital,suchaseducation,byaffordingoneaccesstodifferentlabormarkets(Mudeetal2007).However,theestimationresultsarerobusttobothincludingmigrantstatusasacontrolvariableinequations4and5andalsoestimatingafifth“transmission”equationalongwithequations2‐5,whichgivesmigrantstatusasafunctionofparentcapitallevels(resultsavailableonrequest).Asmentionedearlier,decomposingIGEintoparent‐to‐childcapitaltransmissionsdoesnotnecessarilyilluminatethemechanismsbehindthesepathways.Knowingthatmother’seducationisassociatedwithanincreaseordecreaseinchildhealth,forinstance,doesnotilluminatethebehaviorsorcircumstanceswhichcreatesuchanassociation.Inordertobeginexplorationofsuchmechanism,weaddcontrolstothedecompositionsgivenbyEquations2‐52,afterestimatingthoseequationsontheirown.ThesecontrolsallowsomeinformedspeculationastothecausalmechanismsbehindimportantIGEpathways.Thesedetailsarediscussedinthesubsectionsthatfollow.6.ResultsTables2and3displayestimatesofintergenerationalhumanandphysicalcapitaltransmissionfordaughtersandsons,respectively.Theregressionsshownineachtablewereestimatedsimultaneouslyvia3SLS,instrumentingforparentincomewithparentexpenditure.Ineachtable,columns1and2reflecteducationandheighttransmission,

8Onemightalsohypothesizethataseparateerrorstructuresexistsforchildhoodtransmissions(thatofeducationandheight)andyoungadulttransmissions(thatoflandandspousecapital).Thisassumptionwouldsuggesttwoseparateestimationsofthe(sub)systemsofequations,whichleadstoalmostidenticalresultsasdisplayedinTables2and3.Wegowiththelessrestrictiveassumption.Theotherresultsareavailableuponrequest.

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respectively,andcolumns3and4estimatelandholdingandspouseeducationtransmission,respectively.Wediscusseachofthesecapitaltransmissionsinturn,andthenexamineanddecomposeintergenerationalincometransmission.TheparentcapitalvariablesinTables2and3arecorrelatedbutnotmulticollinear.Thetoleranceofeachparentcapitalvariable,withrespecttoallotherparentcapitalvariables,rangesfrom0.54to0.99,withameanvarianceinflationfactorof1.42.Furthermore,capitaltransmissionregressionsthatcontrolforoneparentcapitallevelatatime,asacheckontherobustnessoftherelativeassociationsbetweenparentandchildcapitallevelsinTables2and3,generateverysimilarresults(detailsavailablebyrequest).Whileseveralpointestimatesincreasewhenparentcapitallevelsarecontrolledforindividually–almostcertainlyduetoomittedvariablebias–therelativemagnitudesofcoefficientsbothwithinandacrosstransmissionequationsremainslargelyunchanged.EducationTransmissionParentalincomeexertsastatisticallysignificantpositiveeffectonlyondaughters’education,althoughtheeffectisnotstatisticallysignificantlygreaterfordaughtersthanforsons.Thepointestimatesarereasonablysimilar,1.6versus1.3yearsadditionaleducationforgirlsandboys,respectively,foreachdoublingofparentalincomeduringchildhood,butfarmorepreciselyestimatedfordaughtersthansons.9Notethatfreepublicprimaryschoolhadbeenlongestablishedby1984,whenround1oftheBPSwasconducted,andfreesecondaryschoolwasestablishedin1988.Theseresultssuggestthatdespitefreegovernmenteducation,childeducationappearsanormalgood,likelyduetothegreatermarginalvaluationofchildincomebypoorerparents,butwiththeeducation‐incomeassociationhavinggreatervariationforsonsthanfordaughters.Directintergenerationaleducationtransmissionclearlyoccurs,especiallyfrommotherstochildren.Themagnitudeoftheestimatedeffectofthemother’seducationistwotothreetimesthatofthefather’seducation(althoughthedifferenceisnotstatisticallysignificant)andstronglystatisticallysignificantlydifferentfromzero.Afather’seducationhasnostatisticallysignificanteffectonsons’education,butdoeshaveamarginallysignificanteffectondaughters’education.Thereis,however,nostatisticallysignificantdifferencebetweentheeffectofafather’seducationondaughtersandonsons.Curiously,mother’sheightisnegativelyandstatisticallysignificantlyrelatedtodaughter’seducation,whichmayreflectanincreasedneedfordaughterstoprovidedomesticworkgiventhehigherlabormarketopportunitycostoftallermothers’time.Unfortunately,thedatadonotallowustotestthathypothesis.HeightTransmissionControllingforparentalhumancapital,parentalincomehasnostatisticallysignificantrelationshipwithchildren’srealizedadultheight.Healthtransmissionthusappearsmore

9Moreover,thecoefficientestimateonparentalincomemaybebiasedupwardinthedaughters’educationequationbecausewerejecttheexclusionaryrestrictiononparentexpenditure,whichweusetoinstrumentforparentpermanent/structuralincome.Parentexpenditurehasapositivecorrelationwithdaughters’educationindependentofparentincome.

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directthanmediatedbyliquidityeffects.Aswithamother’seducation,mother’sheightpositivelyandsignificantlyimpactstheheightofbothsonsanddaughters.Father’sheighthasonlyasignificantimpactontheheightofsons.Fordaughters,theimpactofmother’sheightisclosetotentimesgreaterthanthatoffather’sheight,adifferencethatisstatisticallysignificant.Forsons,theimpactofmother’sheightisonly20percenthigherthanthatoffather’sheight,adifferencethatisnotstatisticallysignificant.Thenegative,(weakly)statisticallysignificantrelationshipbetweenmother’seducationanddaughter’sheightisstriking,aswasthenegativerelationshipbetweenmother’sheightanddaughter’seducation.Again,thiseffectmayrelatetomaternallaborsupply.Avarietyofauthorshaveshowedthatmaternallaborsupplyand/oramother’sfeedingpractices,bothofwhichmightbeassociatedwithamother’seducationorheight,caninfluencechilddevelopment(Leslie1989).Amoreeducatedmothermightbelesslikelytobreastfeedherchild,forexample.Indeed,inoursamplemother’seducationispositivelycorrelatedwithbottlefeeding.Blauetal(1996)findthatbothmother’slaborsupplyandmother’swagesarenegativelyassociatedwithbreast‐feedinginruralPhilippines.Theirresultsshow,however,thatincreasedmaternallaborsupplyactuallyimproveschildhoodhealthinthelongrun,withperhapsquestionableimpactsintheveryfirstmonths.Poordataonchildfeedingpracticespreventsusfromestimatingtheassociationbetweenmaternallaborsupplyorfeedingpracticesanddaughter’sheightin2003.However,Table4illustratestheassociationbetweenmaternallaborsupply,feedingpracticesandmother’sbirth‐ageonheight‐for‐agez‐scores(HAZ)forchildrenunderfiveyearsofagein1984.Notethatthisregressionincludesthosechildreninthe1984surveywhowerenotfollowedduringthe2003/4survey.Controllingforchildfeedingpracticesdoeschangethesignonmother’seducationfromnegativetopositivefordaughters,althoughthisisnottrueforsons.Theseresultsaresuggestiveonly,butleaveopenthepossibilitythatnegativeassociationsbetweenadaughter’shumancapitalandmother’sheightoreducationlevelmaybearesultofmaternallaborsupply.LandTransmissionItmayseemsurprisingtofindinsignificantlandtransmissiontobothsonsanddaughters,giventhattheBPSdataweregatheredinpredominantlyagriculturalcommunities.ThisresultisalmostcertainlyduetothesignificantlandreformundertakenbytheAquinogovernmentin1988,betweenthetwosurveyrounds.Duringthistime,landacrossthecountrywasredistributedfromlandownerstotenants.Officially,landownerswerenotallowedtoretainmorethanfivehectaresofland,andindeedintheBPSdatalandholdingsfellsharply,onaverage,forfamilieswhoheldoverfivehectaresoflandin1984.Familieswithfewerthanfivehectaresoflandin1984didgenerallygainlandoverthedecade,althoughat‐testfindstheincreasestatisticallyinsignificant.Thefactthatwedonotobservetransmissionbetweenparentlandholdingsin1984andeventualchildlandholdingsdoesnotnecessaryimplythatlandreformequalizedlandaccessinBukidnon.Ideally,wecouldexamineintergenerationallandtransmissionusingparentlandholdingsimmediatelybeforechildrenmovedawaytobegintheirownhousehold.Ninetypercentofchildreninthesampleleftafter1988,theprimaryyearof

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landreformimplementationbythegovernment.Ifthedistributionoflandholdingschangedsignificantlyenoughbetweenthe1984observationsandtheyearsinwhichchildrenestablishedtheirown(agricultural)households,thentheresultingmeasurementerrorcouldsignificantlyattenuateourestimateofthetrueintergenerationallandtransmissionrate.Asacheckonthatpossibility,weregress2003childlandholdingson2003parentlandholdingsandfindamuchhigher,statisticallysignificantcorrelationinthesepost‐landreformestimates(seeAppendix3).However,giventhat2003landholdingsandchildlandholdingsweremeasuredconcurrently,thiscannotreflectdirecttransfersfromparentto(adult)childandthuslikelyindicatesproductivitytransmission,marketconnections,and/orotherformsofintra‐familialcorrelatedunobservedheterogeneity.Thefactthattheestimatedlandtransmissionratefrom2003parentlandholdingsissignificantlygreaterforsonsthanfordaughtersmaystemfromdifferentlandinheritancecustoms(sonsarealmosttwiceaslikelyasdaughterstoinheritland,andinheritanaveragevalueovertwicethatofdaughters),butcouldalsojustreflectsons’greaterpropensitytofarm,resultinginstrongerintergenerationalcorrelationinunobservedheterogeneityduetoskill,marketaccess,etc.Lowlandtransmissionratesmayalsobeanaturalcharacteristicforagenerationthatisshiftingawayfromland‐basedoccupations.WhileoverhalfofparentsintheBPSdataownland,inboth1984and2003,only11percentofchildrenownlandin2003/4.Whilealmostallparentsworkedintheagriculturalsectorin1984,onlyaboutaquarteroftheadultchildrensurveyedin2003listagriculturalworkastheirprimaryoccupation.In1984,thewealthiest,tallest,andoftenmosteducatedparentswerethelandholdingparentswhogrewsugarorcorn,themostremunerativecropsintheregion.By2003,however,thewealthiestandmosteducatedchildrenheldprofessionaljobssuchasgovernmentofficialsorteachers.Theseprofessionalchildrenaremorelikelythanotherchildrentocomefromlandholdingfamilies,andtheyholdlandatslightlyhigherratesthanotherchildren.Yetlandisunnecessaryfortheirprimaryjob,amajortransitioninjustonegeneration.Expresseddifferently,in1984thebivariatecorrelationcoefficientbetweenparentlandholdingsandparentincomewas0.719.By2003thatcorrelationcoefficientforparentshadfallento0.639.Morestrikingly,thecoefficientbetweenchildlandholdingsandchildincomein2003wasjust0.275.Takahashi(2013)findssimilargenerationaltrendswhenitcomestooccupationandagriculturalincomeinruralPhilippines.Wecannotestablishthatgovernmentlandreformloweredintergenerationallandtransmissionratesorhelpedtocatalyzetherapidoccupationalshiftawayfromland‐basedincomeinBukidnon,butourresultsareconsistentwiththathypothesis.SpouseEducationParentincomeispositivelyandsignificantlyassociatedwiththeeducationalattainmentofadaughter’sspouse,andbutnotason’sspouse.Thisgenderdifferentialissignificantatthetenpercentlevel.Aswithhumancapitaltransmission,mother’seducationissignificantlyandpositivelyassociatedwithspouseeducationforbothsonsanddaughters,thoughthemagnitudeofthisimpactis(insignificantly)higherforsonsthanfordaughters.

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Father’seducationispositivelyandsignificantlyrelatedtotheeducationofadaughter’sspouse,butnottotheeducationofason’sspouse.Giventheillustratedexistenceofparent‐to‐childeducationtransmission,itseemspossiblethattheimpactofparenteducationonspouseeducationmightworkindependentlyoforthroughchildeducation.Controllingforchildeducationdirectlyinequation5suggeststhatthecorrelationofBukidnonparents’attributeswiththeeducationlevelsoftheirchild’sspouseworkspredominantlythroughavenuesotherthanthechild’sowneducation(seeAppendix4).Inparticular,theinfluenceoffather’seducationontheeducationlevelofson‐in‐lawsisalmostundiminishedaftercontrollingfordaughter’seducation,andtheinfluenceofmother’seducationontheeducationofdaughter‐in‐lawsisbarelyreducedbycontrollingforson’seducation.Thissuggestsmorematchingonsocialstatusandthroughassociatedsocialnetworksthatarecorrelatedwithparentalincomes,ratherthanstrictassortativematingbasedonpartners’educationalattainment.ThisfindingcontrastswiththeconclusionsofDeSilvaandBakhiar(2011),whousesimilarregressionstotestthevalidityofparenteducationasaninstrumentforchildeducationinthePhilippinecontext.TheysupportthetheoreticalvalidityofthisinstrumentbynotingthatinthePhilippines,familiesplayarelativelyminorroleinthechoiceofmarriagepartners;only30percentofthewomenintheirsamplewereintroducedtopartnersbyparentsorotherfamilymembers.Indeed,itmaybetruethatparentincomeandparenteducationplayalesserroleinthePhilippinemarriagemarketthaninothercountries.Thismakesourfindingsallthemorestriking,asitdoescertainlyappearthatdespitetheirlackofpersonalinvolvement,parenteducationand(fordaughters)parentincomearestillstronglyassociatedwithassorativematchinginthePhilippinesmarriagemarket,evenaftercontrollingforchildeducation.Takentogether,theresultsdisplayedinTables2and3suggestthatthetransmissionofmother’shumancapitalmaybelessgender‐specificandgenerallystrongerthanthetransmissionoffather’shumancapital.Quisumbing(1994)andEstudilloetal(2001b)foundsimilarpatternsofgender‐specificintergenerationalcapitaltransmissionsinthePhilippines.However,thereisnoclearpatternofwhichchildisfavoredbytransmissionsfrompaternalcapital.Whileafather’seducationhasastrongerimpactontheeducationofdaughtersthanonsons,afather’sheighthasastrongerimpactontheheightofsonsthandaughters.Anothergeneralresultisthatwhenwere‐estimateequations2‐5,droppingparentalincomeasanexplanatoryvariable(resultsavailablebyrequest),wefindfewqualitativechangesintheresultingestimates.Thisprovidesastrongindicationthatmostofobservedintergenerationalcapitaltransmissionisdrivenbyfirsttworeasonswepositabove–directheritabilityorparentalexpectations/preferences–andnotduetoparentalliquidityconstraintsoninvestmentinchildcapitalaccumulation.Wedosee,however,thatfailingtocontrolforparentincomeappearstoincreasethemagnitudeandsignificanceofthefollowingpositiverelationships:(i)theassociationbetweenparentlandholdingsandchildeducationofbothgenders,(ii)theassociationbetweenparentlandholdingsandthespouseeducationofdaughters,and(iii)theassociationbetweenparenteducationandson’s

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education.Inthefirsttwocases,itislikelythatparentlandholdingssimplycaptureproductivitytransmissionorevenliquidityconstraints,intheabsenceofparentincome.Thethirdcaseseemslogicalgiventhatparenteducationishighlycorrelatedwithparentincome,andclearlysons’educationisanormalgood(withhighvariation)withinthissample.IncomeTransmissionTheprecedingestimatesestablishthatintergenerationalcapitaltransmissionisstatisticallysignificantandofconsiderablemagnitudeinmanycases,especiallywithrespecttohumancapital.Thismotivatesthedecompositionofintergenerationalincometransmission(IGE)presentedinTables5‐8.ThesetablesgraduallydecomposeIGEaccordingtoequations6‐8fordaughters(Table5),sons(Table6),migrants(Table7)andnon‐migrants(Table8).Ineachtable,thenumberofobservationsusedinthelasttworegressionsisslightlylessthanthatinthefirstthreeregressionsduetomissingchildcapitalvariables,primarilyspouseeducationandheight.Coefficientestimatesarevirtuallyidenticalifonlytheexactsamecoreobservationsavailableforallspecificationsareusedineachcolumn(resultsavailablebyrequest).Giventhatmigrantscompriseanon‐randomselectionofthebroaderadultchildpopulation,andsincemigrantstatusmaybedeterminedbyfactorsthatalsoaffectincome,thecoefficientestimatesinTables7and8mightbebiased.Heckmancorrectionmodelestimates(availablebyrequest),however,findthecoefficientestimateonthemigrantselectioncovariatestatisticallyinsignificantinallcases,andfindalmostnochangeinothercoefficientestimates.SoprospectiveselectiononobservablesdoesnotseemtohaveanyappreciableeffectonIGEpatternsinthissample.OnemightalsowonderwhetherIGEvariessignificantlyacrossthepopulation,acrosspoorandwealthy1984families,forinstance.Whilesamplesizerestrictssuchinvestigations,ouranalysisusingparametric,semi‐parametric,andnon‐continuousmethodssuggeststhatthisisnotthecase(resultsavailablebyrequest).IGEappearstobefairlyconstantacrossthe1984incomedistribution.Thefirstcolumnofeachtable(5‐8)displaysnaïveIGEestimates,correspondingtoequation1.Theseregressionsinstrumentparentincomewithparentexpenditure,andcontrolonlyforchildageandparentagequadratically,inordertocontrolforlifecycleeffects.Thesecondcolumnsofeachtabledisplaythesameregression,butcontrollingadditionallyforlocation,ethnicity,householdsizeandgender‐specificbirthorder.(ThesesamecontrolswereusedinTables2and3.)TheIGEfiguresestimatedinthefirstcolumnsofTables5‐8–0.43to0.57–areconsistentwiththeexistingliterature.Takahashi(2013)estimatesIGEintheruralPhilippines,uncorrectedformeasurementerror,tobeapproximately0.22,similartoourownfindingswhenweuseuncorrectedOLSregressiontoestimateIGE(seeTableA4inAppendix2).Mazumder(2005)andBehrmanandTaubman(1990)findIGEestimatesofover0.5intheUSwhenmeasurementerrorisproperlycontrolledfor,andSalon(2002)compilesatableofIGEestimatesfromoutsidetheUSwhichrangefrom0.11to0.57.Blanden’s(2013)

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cross‐countrycomparativereviewlikewisereportsseveralIGEestimatesinthissamerange.WhiletheIGEestimateishighestfordaughtersandmigrants,thereisnostatisticallysignificantdifferenceinIGEacrossethergenderormigrantstatus.10Itisinterestingtonote,however,thattheR2ofcolumn1inTable5ismorethandoublethatofcolumn1inTable6,indicatingthatparentincomebetterexplainsdaughterincomethansonincome.Controllingforethnicity,location,householdsizeandbirthorderinthesecondcolumnofeachtableincreasestheR2forsonsbyafactorofseven,andfordaughtersbyafactorofalmostthree.Fromthesetwocolumnsalone,itseemsclearthatfamilycapital,incomeand/orproductivityplaysalargerroleininfluencingdaughters’adultincomethansons’adultincome,whichseemstobetterexplainedbyextra‐familialstructuralfactorssuchasethnicityandlocation.Whileonemightbetemptedtoassumethatthisdifferenceisduetothehigherproportionofdaughterswhomigrate(50percentofdaughtersasopposedto37percentofsons),theR2actuallyincreaseslessfromcolumn1tocolumn2forsplitsthanitdoesformigrants. Thethirdcolumnsofeachtableincludeparentcapitallevelsasadditionalregressors,followingequation7,illustratingtheinfluenceofparent‐to‐childcapitaltransmissionsonIGE.Mother’seducationandparentincomearebothstatisticallysignificantpredictorsofadaughter’sadultincome.Theimportanceofmother’seducationisunsurprisinggivenitsimportancetoadaughter’seducationandtotheeducationofadaughter’sspousethroughassortativemarriage.Whatisstrikingandperhapssurprising,however,isthatparentalincomeexertssuchstronginfluenceoverdaughters’adultincome,evencontrollingforparentalcapitalstocks.Wesuspectthatthispartlyreflectsthecomplexityofassortativemarriage,andthefactthatlimitedinformationonspouses’backgroundslimitsourabilitytocontrolformaritalmatchingonattributesotherthaneducation.Forexample,especiallysuccessfulfarmingfamiliesmaymarryoffdaughterstolocalmerchants’sonswhoinheritthefamilybusinessbutdonotaccumulatemucheducation.Inourspecifications,suchmechanismsappearasresidualcorrelationbetweenadultchildandparentalincomecontrollingforparentandchildcapitalstocks.Parentlandholdingsarealsoasignificant,butnegative,predictorofdaughter’sincome.Thisrelationship–whichdoesnotappearifweuseparent2003landholdingsinplaceofparent1984land(seeAppendix3,tableA5)–maystemfromgovernmentlandreform.Sincelandlessfamiliesoftengainedlandduringthereform,andfamilieswithoverfivehectaresoflandoftenlostland,1984landholdingsmaybenegativelycorrelatedwithsubsequentstandardsofliving,holdingotherfactorsconstant.Itiscurious,however,thatwedonotseeanegativeassociationbetween1984parentlandholdingsandson

10Thecoefficientestimateonparentalincomeincolumn1ofthesons’incomeequationmaybebiasedupward,however,becausewerejecttheexclusionaryrestrictiononparentexpenditure,whichhasapositivecorrelationwithsons’incomeindependentofparentincome.Thesameistrueforcolumn2ofthedaughters’incomeequation.

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landholdings.Perhapsthisreflectsthecustomthatlandisprovidedfirsttosons,andonlytodaughterswhensurplusisavailable.Forsons,mother’seducationandmother’sheightaretheonlystatisticallysignificantpredictorsofincome.(Ifwecontrolfor2003ratherthan1984parentland,parentlandisalsoasignificant,positivepredictorofsonincome.)Thenegativeimpactofmaternalheightonsonincomeispuzzling.Sincematernalheighthasasignificantlypositiveimpactonson’sheight,itwouldappearthatson’sheightisnotasignificantpredictorofson’sincome.Perhapsthisreflectsthedemographicandoccupationalshiftsdiscussedearlier.Mother’seducationistheonly(weakly)significantpredictorofmigrantincome,andnoparentcapitalvaluesaresignificantlyassociatedwithsplitincome.Thisfurthersuggeststhatparentcapitaltransmissionsarebasedonchildgenderratherthanonmigrantstatus.Thecoefficientestimateonparentincome,however,issignificantonlyforsplitsanddaughters,thoughlargeinmagnitudeformigrants.Infact,thiscoefficientincreasesinmagnitudefromcolumn1tocolumn3fordaughters,splitsandmigrants.Itdecreasesandbecomesstatisticallyinsignificantforsons,andbecomesstatisticallyinsignificantformigrants.Parentincomeisevenmoreimportanttodaughters’adultearningsandtonon‐migrantearningsonceonecontrolsforparentcapitalstocks,whiletheoppositeistruefortheadultearningsofsons.ThissuggestsastronggenderdifferentinIGEchannels.BycontrollingforchildcapitallevelsthemselvesinthefourthandfifthcolumnsofTables5‐8,followingequations6and8,weisolatethecontributionofintergenerationalproductivitytransmission(orperhapsintergenerationaltransmissionofunobservedformsofproductivecapital),asthecoefficientestimateonparentincome.Thesecoefficientestimatesaresignificantandlargefordaughtersandforsplits,andbothsmallandinsignificantforsonsandmigrants.Themagnitudeoftheparentincomecoefficientestimateisalmostbutnotquitethesameacrosscolumns4and5ofTable5,aspredictedinsection3.AWaldtestrejectsthenullthatthesecoefficientsareidenticalfordaughters(p=0.0413)andforsplits(p=0.0076),suggestingthatproductivitytransmissionisnotimpervioustoparentcapitallevels.Thesametestcannotrejectthepossibilitythesecoefficientsareequalformigrantsorsons,whichisunsurprisinggiventheinsignificanceofthecoefficientsbeingtested.Thefactthatthepointestimatesoftheeffectofparentincomeondaughters’adultincome(Table5)fallinmagnitudefromcolumn3tocolumns4and5,albeitnotsignificantly,suggeststhatparentincomeplaysaroleinshapingdaughterincomethroughinvestmentinchildcapitalaccumulation.Thisunderscoresthenormalgoodcharacteristicofbothdaughters’educationanddaughter’sspouseeducation,illustratedfirstinTable5.Thelargeandstatisticallysignificantpointestimatesonparentalincomeevencontrollingforchildandparentcapital,however,clearlyindicatearoleforproductivitytransmissioninshapingdaughters’adultincome.Conversely,thecoefficientsonparentincomeincolumns3‐5ofTable6suggestthatparentincomeandproductivitytransmissionplaylittleroleinshapingsons’adultincome.Thisdifferencebetweenincometransmissiontodaughtersandsonsisstatisticallysignificant,andimpliesdifferentpathwaysbehindsonanddaughterIGE.Thefindingisstrikingandnovelinthisliterature.

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Furthermore,thepointestimatesonparentincomeformigrants(Table7)fallsharplyinmagnitudefromcolumn3tocolumns4and5.Thesameestimateremainsstatisticallyindistinguishableacrosscolumns3,4,and5fornon‐migrants(Table8).Becausewesupposefromthestartthatparentstodonotinvestinchildcapitaldifferentlyacrossmigrantstatus,itseemsunreasonabletosupposethatparentsconsidermigrantcapitalinvestments(andnotsplitcapitalinvestments)asnormalgoods.Possiblythefallinmagnitudeformigrantsstemsfromthefactthatoverhalfofmigrants(65percent)arefemale.Thegenerallyhighpointestimatesonparentincomeforsplits,inallcolumnsofTable8,mayindicateafarhigherproductivitytransmissionforchildrenwhostayincloserphysicalproximitytotheirparents.ThelasttwocolumnsofTables5and6illustratethatchildlandholdingsareimportantpredictorsofchildadultincome,inspiteofthemarkedtransitiontowardnon‐farmoccupations.Oddly,giventhegenderednatureoflandinheritanceandfarminginthisregionofthePhilippines,theassociationbetweenlandholdingsandincomeissignificantlystrongerfordaughtersthanforsons.Alsocounter‐intuitiveisthefactthatmigrantsandsplitsexperiencesimilarreturnstoland,eventhoughmigrantsaremoreoftenworkingjobsthatdonotrelyonlandholdings.Spouseeducationisalsoanimportantpredictorofchildadultincome,thoughthemagnitudeofthiscoefficientisfourtimesgreaterforsonsthanfordaughters,andstatisticallysignificantlydifferentattheonepercentlevel.Thedifferencebetweentheinfluenceofspouseeducationonmigrantsandnon‐migrantsissignificantonlyatthetenpercentlevel.Owneducationisasignificantpredictorofincomeforallgroupsexceptsplits.Fordaughtersandmigrants,itisagreaterpredictorthanspouseeducation,buttheeducationofsonsislessstronglyassociatedwithincomethanistheeducationoftheirwives.AWaldtestrejectstheexclusionaryrestrictionimpliedbyequations13‐15forsons(p=0.0023)butnotfordaughters(p=0.1208).Inparticular,bothmother’sheightandfather’sheightremainnegativelyassociatedwithsonincomeincolumn5ofTable6.AndwhileparentcapitallevelsasawholearejointlyinsignificantinTable5,mother’sheightandmother’seducationremainindividuallysignificantlypositivelyassociatedwithdaughterincomeincolumn5ofTable5.AsecondWaldtestdoesrejecttheexclusionaryrestrictionwithrespecttomother’seducationandheightonly.AWaldtestrejectstheexclusionaryrestrictionimpliedbyequations13‐15forbothmigrantsandsplits.Itseemsprobablethat,likethecoefficientestimateonparentincome,thecoefficientestimatesonparenthumancapitallevelscapturetheimpactofsomesortofproductivityinheritanceorcorrelatedintergenerationaltransmissionofanomittedcapitalstock.Forexample,perhapsmother’seducationandheightaidadaughter’ssuccessinthemarriagemarketirrespectiveofthehusband’seducationlevel.Orperhapsbyincreasingason’sagriculturalproductivityandthusincreasinghischanceofworkingintheagriculturalsector,parentheightactuallydecreasesason’seconomicproductivitybydivertinghim

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fromthemoreremunerativenon‐farmsector.Thenegativeimpactsofbothfather’seducationandparentlandonmigrantincomearecuriousandbearfurtherinvestigation.TheRelativeExplanatoryPowerofDifferentPathwaysTheresultsdisplayedinTables5‐8donotallowustocomparetherelativeimportanceofvariousparentcapitallevels,sincethemagnitudeofregressioncoefficientsdependsuponregressorunitsofmeasure.Table9offersonerepresentationofthecomparativeexplanatorypowerofeachpathwayoftransmissionfromparentalcapitalstocks,fordaughters,sons,splitsandmigrants.Wegeneratedlowerandupperboundestimatesofthemagnitudebasedontwodistinctmethodsofestimation.ThefirstmethodestimatescontributionofagivenparentcapitalstockbyaddingonlythatvariabletothenaïveIGEregression(equation1,reflectedinthefirstcolumnsofTables5‐8)andnotingtheresultingchangein .Thisisanupperboundestimateofthemarginalcontributionto becausethesevariablesarenotorthogonaltootherparentalcapitalvariables.ThesecondmethoddropstherelevantparentcapitalvariablefromthefullIGEdecomposition(equation7,reflectedinthethirdcolumnsofTables5‐8).Thisgivesalowerboundestimateofthemarginalcontributionto ,forthesamereasonthatthefirstmethodgivesanupperboundestimate.InTable9wereporttheboundsoneachparentalcapitalstock’s(andresidualparentalincome,orproductivity’s)proportionalshareofthesumofthesemarginalchangesin .TheresultsinTable9largelymirrortheresultsshowninTables5‐8.Theprimaryresultoftheserelativecomparisonsisthatmaternalhumancapital,especiallymaternaleducation,clearlyappearsastheprimarycapitalpathwaybehindintergenerationalincometransmission.Forexample,maternaleducationexplainsover60%oftheexplainablevariationofmigrantincome.Thisresultunderscoresthelong‐termpayofftopromotingtheeducationofgirls,especiallythosefrompoorhouseholds.Paternaleducationappearstobeanimportantpathwayifonefailstocontrolformaternalattributes(upperboundestimate),butoncematernalattributesarecontrolledfor,paternalhumancapitalhasfarless(oftenno)explanatorypower.Thislikelyreflectsassortativemarriage.Similarly,maternalheighthasgreaterexplanatorypowerthanpaternalheight.AssuggestedbyTables5‐8,parentincomehashugeexplanatorypowerwhenitcomestotheadultincomeofdaughtersandsplits,explainingoverthree‐fourthsofthevariationindaughters’incomeand50percentofthevariationinsplits’income.Itismuchlessimportantforsonsandmigrants.Whileparentcapitallevelshavealargeexplanatorypowerwhenitcomestosons’income,theyarelessimportantfordaughters’income,signalingthatitmaybemoredifficulttoidentifyprospectiveinterventionpointstoequalizeopportunityforgirlsinruralPhilippines.Otherparentalhumancapitalvariablesalsohavesomeexplanatorypower.Maternalheightexplainsathirdofthevariationinsons’income.Paternalheightappearstohavegreaterexplanatorypowerwhenthesampleisbrokenbymigrantstatusratherthangender.7.Conclusions

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Thispaperdocumentshighintergenerationalincomeelasticity(IGE)intheruralPhilippinesandthenillustratesthatdecomposingIGEestimatesintoitsconstituentcapitalandproductivitytransmissionpathwaysisbothpossibleanduseful.ExaminingintergenerationalcapitaltransmissionandintergenerationalincomeelasticityjointlyenhancesourunderstandingofthemechanismsunderpinningIGEandallowsustocomparetheimportanceofparentincomeandparentcapitaltochildcapitalformation.Thispermitsidentificationofdomainsthatappearrelativelylessormoreimportanttopromotingequalityofopportunity,therebyenablingmorefocusedpolicy‐orientedresearchtoidentifywhichsortsofinstitutionalchangesorinterventionsaremosteffectiveinpromotinggreateropportunitiesforchildrenbornintopoorhouseholds.PerhapsthemostimportantconclusionthatcanbedrawnfromourresultsisofsharpgenderdifferencesinthepathwaysofintergenerationalincometransmissionintheruralPhilippines.AlthoughthenaïveIGEestimatesarestatisticallyindistinguishableforsonsanddaughters,thepathwaysthatgeneratetheseresultsdifferstrikingly.Parentincomeperseactuallyplaysnodirectroleinthetransmissionofparentincometosons.Rather,productivecapitalistransmittedacrossgenerations,especiallyintheformsofeducation,healthandlandholdings.Financialliquidityconstraintsarelessimportanttosons’productivecapitalaccumulationandadultincomethanareparentalcapitalendowments,whichmaytransmitdirectly(asinthecaseofheight,duetogeneticsandbehaviors)orviaparentalexpectationsandpreferences.Sons’educationandsons‐in‐law’seducationaretheonlytwochildcapitalstocksthatarestronglyandpositivelyaffectedbyparentincome,indicatingthat“soneducation”(whetherbiologicalormarriedin)isanormalgood.Bycontrast,whileintergenerationalcapitaltransmissioncompletelyexplainstheIGEforsons,parentalincomeexertsaverystrongindependenteffectondaughters’adultincomeandthateffectincreasesratherthanfallsasoneaddscontrolsforparentand/orchildcapitalstocks.Daughters’incomeappearsheavilyinfluencedbysuccessinthemarriagemarket,whichisinpartdrivenbyherowneducation(shapedinlargepartbymaternaleducation),andinpartdrivenbytheeffectsofparentincome.Daughters’adultincomealsoexhibitsconsiderableintergenerationalproductivitytransmission,possiblyrelatedtosocialnetworksandagainworkingthroughthemarriagemarket.Incontrast,parentincomeseemstoplayverylittleroleinobtaininga“valuable”wifeforsonsthroughthemarriagemarket;parentendowmentstransmitmoredirectlytoson’sendowments.Whileitissometimesdifficulttodistinguishpatternsdifferentiatedbygenderfromthoseaccordingtomigrantstatus,itisclearthatthepathwaysbehindIGEalsodifferformigrantsandnon‐migrants.Parentalinvestmentinmigrantcapitalseemsconstrainedbyparentliquidity,likethatofdaughtersandperhapsbecausesuchahighproportionofmigrantsaredaughters.Investmentinnon‐migrantsdoesnotappeartobeconstrainedinthesameway.Theproductivitytransmissiontonon‐migrantsismuchhigherthanthattomigrants,whichseemslogicalgiventhatchildrenwholiveclosetotheirparentscontinuetosharewiththemsocialnetworksandotherfactorsthataffectproductivity.Thevariabilityaroundproductivitytransmissionformigrantsisnotablyhigh,muchhigherthanforanyothergroup.Thismayimplyalargevariationinthebenefitsofsocialnetworksandotherfamily

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assetsavailabletomigrants,whichwouldbelogicalifboth“pull”and“push”factorsinfluenceachild’sdecisiontomigrate.Additionally,itseemsgenerallytruethatwhilemotherstransmithumancapitalrelativelyequallyandstatisticallysignificantlytobothsonsanddaughters,fathers’humancapitalislessimportanttochildreningeneralandoftenaffectsthecapitallevelofonlydaughtersoronlysons.Mothers’educationisparticularlyimportanttoeventualchildincomebecauseitisstronglyandpositivelyassociatedwithbothownandspouseeducation,eachofwhichis,inturn,stronglyassociatedwithchildadultincome.Thesefindingscarrysignificantpolicyimplications.Policiesfocusedonobviatingtheeffectsofparentincomeinequalityappearlikelytohaveapronouncedeffectonfemales’intergenerationaleconomicmobilitybutnegligibleeffectsontheintergenerationaleconomicmobilityofsonsinBPScommunities.Rather,forsons,theintergenerationaltransmissionofcapitallevels–especiallyineducationandland–mustbemitigatedinordertoenhanceequalityofopportunityacrossgenerations.TheAquinogovernment’ssignificantlandreformsofthelate1980smayhavehelpeddampenIGEbylimitingdirectlandtransfersacrossgenerations.Widespreadfreepublicschoolingthatpredatesourinitialsurveyroundmayalsohelpexplainthestatisticallyinsignificantroleofparentalincomeinexplainingdaughters’educationalattainment,althoughitisstillstronglyassociatedwithsons’educationalattainment.Thisdecompositionapproachtounderstandingtheintergenerationalelasticityofincomeshedsgreaterlightonthemultiple,parallelprocessesunderpinningeconomicmobilitythandosimplestatisticalassociationssuchasnaïveIGEestimatesorasimpleregressionofchildeducationonparenteducation.Whilethisanalysisnecessarilyfallsfarshortofidentifyingthecausalpathwaysthatmightmosteffectivelypermitpolicymakerstoenhanceequalityofopportunity,decomposingthedirectandincometransmissionavenuesallowsustonarrowtherangeofmechanismsworthexploringthroughmoremeticulousstructuralorexperimentalempiricalwork.8.References

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Figure 1: Conceptual Model of IGE Decomposition (naïve regression represented by dashed red line)

32

Table 1: Descriptive Statistics

Mean Value Sons

Mean Value Daughters

Mean Value Migrants

Mean Value Splits

Child Age (years) ‘84 10.8 10.0 9.9 10.7 Father Age (years) ‘84 39 40 40 39 Mother Age (years) ‘84 36 36 36 36 Household Size (persons) ‘84 7.2 7.0 7.0 7.0 Father’s Education (years) ‘84 5.6 5.9 5.6 5.9 Mother’s Education (years) ‘84 5.2 5.0 5.2 5.0 Father’s Height (cm) ‘84 161 161 161 160 Mother’s Height (cm) ‘84 151 150 150 151 Parent Landholdings (hectares) ‘84 2.6 2.3 2.6 2.3 Parent Weekly Real Income (Philippine Peso)’84 999 896 955 925 Mother’s Birth Age (years) ‘84 25 26 26 25 Child Birth Order (number, 1=eldest) ‘84 2.7 3.0 3.2 2.6 Child Height (cm)‘84 128 122 122 127 Child Height-for-Age (Z-score) ‘84 -2.3 -2.3 -2.3 -2.3 Child Education (years) ‘84 3.3 3.2 3.2 3.3 Child Age (years) ‘03 30 29 29 29 Mean Migrant Status (percent) ‘04 367% 50% Mean Female Status (percent) ’84/’03/’04 35% 48% Spouse Age (years) ‘03 29 32 32 29 Child Household Size (persons) ‘03 4.0 4.3 4.0 4.4 Child Education (years) ‘03 8.6 9.7 9.8 8.8 Spouse Education (years) ‘03 10.1 9.3 10.2 9.2 Child Height (cm) ‘03 163 150 154 156 Spouse Height (cm) ‘03 149 149 158 143 Child Landholdings (hectares) ‘03 0.3 0.1 0.2 0.2 Child Weekly Real Income (Philippine Peso) ‘03 1,493 1,519 1,974 1138

33

Table 2: Intergenerational Capital Transmissions for Daughters (OLS-IV) (1) (2) (3) (4) Daughter

Education Daughter Height

Daughter Landholdings

Daughter Spouse Education

Log Parent Income ‘84 1.642** 0.763 0.231 1.949** (0.702) (2.882) (0.169) (0.909) Parent Land ‘84 0.0727 -0.121 -0.00330 -0.0398 (0.0604) (0.408) (0.0192) (0.0995) Mother’s Education ‘84 0.348*** -0.578* -0.00206 0.159* (0.0807) (0.351) (0.0131) (0.0833) Father’s Education ‘84 0.149* 0.559 0.00871 0.258*** (0.0846) (0.359) (0.0143) (0.0860) Mother’s Height ‘84 -0.0837** 0.438*** -0.0102 -0.0158 (0.0352) (0.107) (0.00652) (0.0410) Father’s Height ‘84 0.0353 0.0460 -0.00635 0.00308 (0.0346) (0.195) (0.00626) (0.0421) Observations 244 240 244 226 R-squared 0.551 0.244 0.187 0.404

Robust standard errors in parentheses Controls include household size, gender-specific birth order dummies,

location (barrio) & ethnic groups dummies *** p<0.01, ** p<0.05, * p<0.1

Table 3: Intergenerational Capital Transmissions for Sons (OLS-IV)

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

Education Son

Height Son

Landholdings Son

Spouse Education Log Parent Income ‘84 1.311 -0.330 -0.132 -1.162 (1.211) (1.850) (0.389) (1.325) Parent Land ‘84 0.194 0.236 0.0752 0.224 (0.148) (0.241) (0.0674) (0.174) Mother’s Education ‘84 0.268** -0.190 0.0650** 0.321*** (0.120) (0.234) (0.0326) (0.121) Father’s Education ‘84 0.147 0.264 -0.0436 0.0505 (0.115) (0.206) (0.0462) (0.115) Mother’s Height ‘84 -0.00627 0.362*** 0.00531 0.0202 (0.0509) (0.0963) (0.0127) (0.0447) Father’s Height ‘84 -0.00461 0.296*** -0.0224 -0.00566 (0.0469) (0.0746) (0.0139) (0.0436) Observations 184 173 184 169 R-squared 0.461 0.442 0.255 0.356

Robust standard errors in parentheses Controls include household size, gender-specific birth order dummies,

location (barrio) & ethnic groups dummies *** p<0.01, ** p<0.05, * p<0.1

34

Table 4: Determining Height-for-Age (HAZ) in Children Under Five (OLS-IV) (1) (2) (3) (4) (5) (6) Daughter

HAZ Daughter

HAZ Daughter

HAZ Son

HAZ Son

HAZ Son

HAZ Parent Income ‘84 0.0178 -0.0363 -0.0131 0.125 0.512* 0.470 (0.417) (0.395) (0.402) (0.369) (0.307) (0.327) Parent Land ‘84 0.00211 0.00356 -0.0179 -0.00502 -0.0240 -0.0327 (0.0728) (0.0670) (0.0645) (0.0412) (0.0352) (0.0352) Mother’s Education -0.0288 0.0227 0.0183 -0.0187*** -0.00984** -0.0197 (0.0448) (0.0328) (0.0310) (0.00571) (0.00477) (0.0251) Father’s Education 0.0704 0.0312 0.0186 0.0357 0.0354 0.0301 (0.0668) (0.0422) (0.0384) (0.0354) (0.0345) (0.0325) Mother’s Height 0.0512** 0.0512*** 0.0614*** 0.0325* 0.0311** 0.0319** (0.0216) (0.0160) (0.0158) (0.0170) (0.0141) (0.0138) Father’s Height 0.0292 0.0353** 0.0355** 0.0638*** 0.0640*** 0.0635*** (0.0182) (0.0154) (0.0155) (0.0146) (0.0118) (0.0117) Ever Bottle-Fed -0.223 -0.276 -0.274 -0.250 (0.184) (0.179) (0.182) (0.182) Mother Birth Age 0.156** 0.0213 (0.0688) (0.0403) Mother Work Hours -0.0683*** -0.0474** (0.0202) (0.0193) Observations 315 291 291 360 345 344 R-squared 0.209 0.238 0.280 0.238 0.245 0.260

Robust standard errors in parentheses *** p<0.01, ** p<0.05, * p<0.1

Controls include household size, mother and father age, gender-specific birth order dummies, location (barrio) & ethnic groups dummies

35

Table 5: Decomposing Intergenerational Income Elasticity for Daughters (OLS-IV) (1) (2) (3) (4) (5) Income Income Income Income Income Parent Income ‘84 0.537*** 1.040*** 1.033*** 0.748** 0.779** (0.163) (0.278) (0.317) (0.302) (0.344) Parent Land ‘84 -0.0435* -0.0558** (0.0260) (0.0267) Mother’s Education 0.0529* 0.0614* (0.0316) (0.0357) Father’s Education -0.00447 -0.0325 (0.0276) (0.0275) Mother’s Height 0.0160 0.0359*** (0.0113) (0.0114) Father’s Height -0.00606 -0.00619 (0.0140) (0.0117) Own Education 0.0507 0.0632* (0.0331) (0.0346) Spouse Education 0.0380* 0.0356* (0.0200) (0.0193) Own Height -0.00366 -0.00605 (0.00806) (0.00730) Landholdings 0.271** 0.307*** (0.115) (0.112) Age Controls: Yes Yes Yes Yes Yes Additional Controls: No Yes Yes Yes Yes Observations 240 240 240 220 220 R-squared 0.114 0.333 0.356 0.402 0.433

Robust standard errors in parentheses Age controls include quadratic terms for child and father age

Additional controls include parent household size, gender-specific birth order dummies, location (barrio) & ethnic groups dummies

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

36

Table 6: Decomposing Intergenerational Income Elasticity for Sons (OLS-IV) (1) (2) (3) (4) (5) Income Income Income Income Income Parent Income ‘84 0.434*** 0.145 -0.182 -0.135 -0.00884 (0.146) (0.246) (0.410) (0.258) (0.385) Parent Land ‘84 0.0522 -0.0285 (0.0476) (0.0459) Mother’s Education 0.0753* 0.0511 (0.0396) (0.0382) Father’s Education 0.0334 -0.00327 (0.0438) (0.0312) Mother’s Height -0.0349** -0.0598*** (0.0168) (0.0186) Father’s Height -0.0175 -0.0245* (0.0159) (0.0132) Own Education 0.0458* 0.0367* (0.0242) (0.0223) Spouse Education 0.131*** 0.131*** (0.0251) (0.0229) Own Height -0.00124 0.0217 (0.0122) (0.0140) Landholdings 0.182*** 0.161*** (0.0560) (0.0605) Age Controls: Yes Yes Yes Yes Yes Additional Controls: No Yes Yes Yes Yes Observations 182 182 182 157 157 R-squared 0.050 0.351 0.407 0.545 0.594

Robust standard errors in parentheses Age controls include quadratic terms for child and father age

Additional controls include parent household size, gender-specific birth order dummies, location (barrio) & ethnic groups dummies

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

37

Table 7: Decomposing Intergenerational Income Elasticity for Migrants (OLS-IV) (1) (2) (3) (4) (5) Income Income Income Income Income Parent Income ‘84 0.574*** 0.617* 0.780 0.0728 0.0827 (0.197) (0.319) (0.508) (0.381) (0.586) Parent Land ‘84 -0.0608 -0.0324 (0.0465) (0.0473) Mother’s Education 0.0837* 0.0779** (0.0487) (0.0350) Father’s Education -0.0656 -0.0765** (0.0493) (0.0318) Mother’s Height 0.00519 0.0162 (0.0181) (0.0196) Father’s Height -0.0235 -0.0375** (0.0204) (0.0175) Own Education 0.0916* 0.0965* (0.0508) (0.0563) Spouse Education 0.0635* 0.0606* (0.0368) (0.0357) Own Height -0.00105 -0.00182 (0.00641) (0.00604) Landholdings 0.138** 0.104 (0.0683) (0.0732) Age Controls: Yes Yes Yes Yes Yes Additional Controls: No Yes Yes Yes Yes Observations 185 185 185 151 151 R-squared 0.047 0.358 0.356 0.542 0.581

Robust standard errors in parentheses Age controls include quadratic terms for child and father age

Additional controls include parent household size, gender-specific birth order dummies, location (barrio) & ethnic groups dummies

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

38

Table 8 Decomposing Intergenerational Income Elasticity for Splits (OLS-IV) (1) (2) (3) (4) (5) Income Income Income Income Income Parent Income ‘84 0.474*** 0.665*** 0.719*** 0.452*** 0.654*** (0.103) (0.163) (0.258) (0.167) (0.252) Parent Land ‘84 -0.0340 -0.0578 (0.0353) (0.0366) Mother’s Education 0.0368 0.0113 (0.0349) (0.0337) Father’s Education 0.00802 -0.00793 (0.0319) (0.0288) Mother’s Height -0.000835 -0.000551 (0.0118) (0.0127) Father’s Height -0.0144 -0.0127 (0.0108) (0.0108) Own Education 0.0322 0.0388 (0.0209) (0.0248) Spouse Education 0.0728*** 0.0749*** (0.0176) (0.0176) Own Height -0.0100 -0.00145 (0.0112) (0.0127) Landholdings 0.156 0.157 (0.104) (0.106) Age Controls: Yes Yes Yes Yes Yes Additional Controls: No Yes Yes Yes Yes Observations 237 237 237 226 226 R-squared 0.122 0.342 0.348 0.455 0.444

Robust standard errors in parentheses Age controls include quadratic terms for child and father age

Additional controls include parent household size, birth order dummies and a dummy for sex, location (barrio) & ethnic groups dummies

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

39

Table 9: Pathway Explanatory Power [Lower, Upper] Bounds on Proportion of 2Explained by Parent Capital Level

Sub-Sample

Productivity

Parent Land

Maternal Education

Paternal Education

Maternal Height

Paternal Height

Daughters [0.78,-] [0.00,0.01] [0.15,0.45] [0.00,0.41] [0.07,0.13] [0.00,0.01] Sons [0.12,-] [0,10,0.18] [0.22,0.37] [0.06,0.38] [0.14,0.31] [0.00, 0.10]

Migrants [0.03,-] [0.01,0.10] [0.63,0.68] [0.01,0.27] [0.00,0.04] [0.00,0.24] Splits [0.51,-] [0.00,0.07] [0.12,0.44] [0.06,0.54] [0.01,0.02] [0.02,0.22]

40

Appendix 1

A1: Sibling Attrition (Differences between Tracked & Non-Tracked Siblings) Variable

Mean for Tracked Siblings

Mean for Non-Tracked Siblings

T-test across Means

Male (dummy) 0.43 0.54 4.07*** Birth order (1=first, etc.) 2.87 3.54 5.85*** Age (years) 9.93 7.15 -8.66*** Education (years) 3.23 1.78 -9.07*** Height (cm) 125 110 -9.85*** Height-forage (z-score) -2.27 -2.32 -0.69 Weight-for-height (z-score) -0.29 -0.43 -1.25 Ever bottle-fed (dummy) 0.38 0.41 0.46 Months breastfed (months) 12.7 12.8 0.15 Days sick in last 2 weeks (days) 0.88 1.01 1.53*

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

41

Appendix 2 The BPS data display evidence of expenditure smoothing. Table A2 displays an OLS regression of 1984 parent income on household human and physical capital, parent age and parent occupation. Predicted income from this regression may be considered structural income, since the prediction is based on intransient household characteristics. Transitory income is thus constructed by subtracting this predicted income from observed income, and savings are constructed by subtracting observed expenditure from observed income. If savings increase with transitory income, then families in the BPS dataset practice expenditure smoothing. If no expenditure smoothing occurs in these data, we would expect there to be no positive association between savings and transitory income. However, a univariate OLS regression, displayed in Table A3, rejects the null hypothesis that no relationship exists between savings and transient income. Indeed, we cannot reject the null that savings change one-for-one with transitory income. These results remain true also when controlling for a quadratic term for transitory income. Sample households appear to smooth consumption, thereby reinforcing the value of our instrumentation approach to mitigating bias caused by measurement error and transitory income shocks. Consumption smoothing implies that transitory shocks to income in BPS communities, otherwise considered measurement error to structural income, the variable of interest, are not fully transmitted as transitory shocks to expenditure. Because error structures around observed income and observed expenditure are at most correlated but not identical, instrumenting for income with expenditure will mitigate the downward bias on IGE associated with measurement error around structural income of parents. Table A4 illustrates that indeed IGE estimates increase when we instrument this way (column 4). Averaging income across years (column 3), which usually mitigates bias effectively when panels include six or more rounds of data, results in a much lower estimate of IGE. In fact, the coefficient on average parent income appears to reflect the difference between the predictive power of ’84 parent and ’03 parent income, more than a mitigation of measurement error.

42

Table A2: OLS Regression of Parent Income in 1984 Parent Income 1984 Household size 165.1** (62.44) Land owned (hectares) -63.54* (32.54) Average net worth of all assets 0.0105*** (0.00143) Mother years of schooling 69.80** (31.34) Father years of schooling -30.86 (22.79) Mother height 7.504 (11.02) Father height -2.414 (8.242) Age of father -128.6** (54.54) Age of father squared 1.748** (0.660) Year father migrated to current location -3.136 (8.618) Constant 2,503 (2,470) Observations 214 R-squared 0.934

Standard errors in parentheses *** p<0.01, ** p<0.05, * p<0.1

Additional controls: dummies for location (barrio), father’s ethnicity, mother’s ethnicity, location of father’s birth, and family occupation;

counts by gender of household members within 4 age brackets (0-5, 6-10, 11-17, 18 & above)

Table A3: OLS Regression of Savings on Transitory Income (1) (2) Savings Savings Transitory Income 0.869*** 0.851*** (0.161) (0.157) Transitory Income Squared 0.00112*** (0.000325) Constant -155.9*** -217.0*** (37.67) (40.82) Observations 214 214 R-squared 0.121 0.167

Standard errors in parentheses *** p<0.01, ** p<0.05, * p<0.1

43

Table A4: IGE across Various Estimation Approaches Estimator:

(1) OLS

(2) OLS

(3) OLS

(4) IV

Dependent Variable: Log Child Inc Log Child Inc Log Child Inc Log Child Inc Independent Variable: Parent Inc ‘84 Parent Inc ‘03 Avg Parent Inc Parent Inc ‘84 Instrument: NA NA NA Parent Expen ‘84 IGE All Children: 0.287*** 0.168*** 0.262*** 0.500*** (0.0659) (0.0459) (0.0538) (0.120) Observations 422 411 423 422 R-squared 0.102 0.104 0.124 0.077 IGE Daughters: 0.345*** 0.145** 0.248*** 0.537*** (0.0778) (0.0573) (0.0633) (0.163) Observations 240 234 243 240 R-squared 0.133 0.106 0.131 0.114 IGE Sons: 0.184* 0.193*** 0.269*** 0.434*** (0.101) (0.0615) (0.0877) (0.146) Observations 182 177 180 182 R-squared 0.085 0.134 0.137 0.050 IGE Splits: 0.258*** 0.190*** 0.280*** 0.474*** (0.0708) (0.0433) (0.0571) (0.103) Observations 237 230 235 237 R-squared 0.154 0.184 0.196 0.122 IGE Migrants: 0.275** 0.135** 0.238*** 0.574*** (0.107) (0.0665) (0.0739) (0.197) Observations 185 181 188 185 R-squared 0.087 0.078 0.103 0.047

Robust standard errors in parentheses Father’s age and child’s age are controlled for quadratically in all regressions

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

44

Appendix 3

Table A5: Intergenerational Land Transmission Comparing 1984 and 2003 Parent Values (OLS-IV) (1) (2) (3) (4) Daughter

Landholdings Daughter

LandholdingsSon

Landholdings Son

Landholdings Log Parent Income ‘84 0.231 0.0575 -0.132 -0.657* (0.169) (0.146) (0.389) (0.375) Parent Land ‘84 -0.00330 0.0752 (0.0192) (0.0674) Parent Land ‘03 0.0390** 0.154*** (0.0166) (0.0505) Mother’s Education ‘84 -0.00206 -0.00999 0.0650** 0.0172 (0.0131) (0.0111) (0.0326) (0.0268) Father’s Education ‘84 0.00871 0.0136 -0.0436 0.0241 (0.0143) (0.0132) (0.0462) (0.0442) Mother’s Height ‘84 -0.0102 -0.0107* 0.00531 -0.0123 (0.00652) (0.00586) (0.0127) (0.0133) Father’s Height ‘84 -0.00635 -0.00724 -0.0224 -0.0342** (0.00626) (0.00567) (0.0139) (0.0142) Observations 244 244 184 184 R-squared 0.187 0.285 0.255 0.345

Robust standard errors in parentheses Controls include household size, gender-specific birth order dummies,

location (barrio) & ethnic groups dummies *** p<0.01, ** p<0.05, * p<0.1

45

Appendix 4

Table A6: Avenues for Spouse Education Capital Transmission (OLS-IV) (1) (2) (3) (4) Daughter

Spouse Education

Daughter Spouse

Education

Son Spouse

Education

Son Spouse

Education Log Parent Income ‘84 1.949** 1.765* -1.162 -2.138* (0.909) (0.948) (1.325) (1.260) Parent Land ‘84 -0.0398 -0.0385 0.224 0.162 (0.0995) (0.0998) (0.174) (0.157) Child Education 0.173* 0.493*** (0.0890) (0.0720) Mother’s Education ‘84 0.159* 0.105 0.321*** 0.272** (0.0833) (0.0841) (0.121) (0.116) Father’s Education ‘84 0.258*** 0.242*** 0.0505 -0.0253 (0.0860) (0.0849) (0.115) (0.100) Mother’s Height ‘84 -0.0158 -0.0184 0.0202 0.0312 (0.0410) (0.0405) (0.0447) (0.0367) Father’s Height ‘84 0.00308 0.0119 -0.00566 -0.00565 (0.0421) (0.0438) (0.0436) (0.0369) Observations 226 226 169 169 R-squared 0.404 0.421 0.356 0.480

Robust standard errors in parentheses Controls include household size, gender-specific birth order dummies,

location (barrio) & ethnic groups dummies *** p<0.01, ** p<0.05, * p<0.1