1

ToxicTruth:LeadExposureandFertilityChoices

KarenClay(CarnegieMellonandNBER)

MargaritaPortnykh(CarnegieMellon)

EdsonSevernini(CarnegieMellonandIZA)

Firstdraft:May2017

Thisdraft:August2017

Abstract

Evidencefromtheepidemiologyliteraturesuggeststhatexposuretoleadimpairsthe

reproductivesystemofbothmalesandfemales,leadingtolowerfecundity(i.e.the

physiologicalabilitytohavechildren).Itisunclear,however,whetherthiswouldcausea

decreaseinfertility(i.e.theactualproductionofoffspring).Householdscouldtakeactions

toavoidleadexposureand/ortoremediateundesirableconsequencesofsomeexposure.

InthisstudyweexaminetheimpactofleadonfertilityinU.S.countiesovertheperiod

1978-1988,whenairborneleadconcentrationdecreasedconsiderably.Weleveragethe

implementationofCleanAirActregulationsandthe1944InterstateHighwaySystemPlan

withinafixed-effectinstrumentalvariableapproach,andfindtwomainresults.First,

exposuretoairborneleadcausesareductiononthenumberofbirthsandbirthrates,

indicatingthatavoidanceand/orcompensatorybehaviormightnotfullyoffsetthe

pathologiceffectsoflead.Second,suchareductioninfertilityratesseemssmallerforhigh-

educatedhouseholds(thosewithmotherswithhighschoolorhighereducation),

suggestingthatsomeactionsmayattenuatethepotentiallyharmfuleffectsoflead,andthat

therelationshipbetweenleadandfertilityisnotpurelyepidemiological.

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Introduction

Thelatestevidencefromepidemiologypointsoutthatexposuretoleadimpairsthe

reproductivesystemofbothmalesandfemales,potentiallyreducingthefecundityof

couples(e.g.Lancranjanetal.1975,Wani,Ara,andUsmani2015)1.Formales,leadseems

tounderminethereproductivefunctionbyreducingspermcount,volume,anddensity,or

changingspermmotilityandmorphology(e.g.HauserandSokol2008).Forfemales,lead

exposureisassociatedwithdelaysinpubertaldevelopment,irregularmenstruation,

spontaneousabortions,subfertility,andintheextremeinfertility(e.g.Mendola,Messer,

andRappazzo2008).Itisunclear,however,whetherthesepotentiallyharmfuleffectsof

leadwouldcauseareductioninfertility.Indeed,householdsmightmakedefensive

investments:theymaytakeactionstoavoidexposuresuchaslivinginhouseswithnolead

painting,and/ortomitigatetheeffectsofexposuresuchasusingassistedreproductive

technologies.Inthisstudyweestimatethecausaleffectofexposuretoairborneleadon

fertilityrates,andinvestigatewhetheravoidanceand/orcompensatorybehaviormay

attenuatethoseundesirableconsequences.

Toexaminetheimpactofexposuretoleadonfertilityrates,weusemonthlycounty-level

dataderivedfromthebirthandmortalityrecordsoftheU.S.NationalVitalStatistics

System,andfromreadingsoftheU.S.EnvironmentalProtectionAgency’snetworkof

airborneleadmonitoringstationsacrossthenationovertheperiod1978-1988.

Identificationinthissettingisknowntobechallengingbecauseofendogenoussorting

relatedtohouseholdpreferencesforairquality(e.g.ChayandGreenstone2003,2005,

BanzhafandWalsh2008),avoidancebehavior(e.g.Neidell2004,2009,MorettiandNeidell

2011),andremediationinvestments(e.g.Deschenes,Greenstone,andShapiro2017).Thus,

weuseafixed-effectinstrumentalvariableapproach,leveragingtheimplementationof

federalCleanAirAct(CAA)regulationsregardingthephase-outofleadingasoline,and

nonattainmentdesignationsassociatedwithviolationsoftheNationalAmbientAirQuality

1Again,fecundityisthephysiologicalabilitytohavechildrenandfertilityistheactualproductionofoffspring.

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Standards(NAAQS)forparticulatematter(PM).

Thephaseoutofleadingasolinehadtwoimportantmilestones:(i)startinginOctober

1979,refinerieswererequiredtoproduceaquarterlyaverageofnomorethan0.8grams

pergallon(gpg)amongthetotalgasolineoutput;(ii)fromJuly1985onwards,thestandard

wasreducedto0.5gramsperleadedgallon(gplg).Leadwaseventuallybannedasafuel

additiveintheU.S.beginningin1996.Inouranalysis,thosetwomilestonesareinteracted

withanindicatorforwhetheracountywasplannedtoreceiveahighwayfromthe1944

InterstateHighwaySystemPlan,whichwasdesignedprimarilyformilitarypurposes.The

impactofthephaseoutofleadingasolineonairborneleadshouldbefeltmorestronglyin

countieswithahigherprobabilityofhavingahighwayrunningthroughthem.Thetwo

milestonesandtheirinteractionswiththe“1944plan”provideusfourinstrumental

variables.ThelastonecomesfromthecompliancewiththeNAAQSforPM.Followingthe

1977CAAAmendments,in1978EPApublishedalistofallnonattainmentareasforthefirst

time.TheAmendmentsalsorequiredcountiesinviolationwiththePMstandardtocomply

byJanuary1983.BecauseleadismeasuredasaportionofPM,ourfifthinstrumentwas

definedtobeadummyvariableindicatingnonattainmentstatusforPMin1978interacted

withtheperiodstartinginJanuary1983.

Wehavetwomainfindings.First,theIVestimatesfortheimpactofleadexposureon

numberofbirthsandfertilityrates(numberofbirthsper1000females16-39yearsold)

arenegativeandstatisticallysignificant.TheOLSestimatesaremuchsmallerinmagnitude,

suggestingapositivebiaspotentiallyarisingfromendogenoussorting,avoidancebehavior,

and/orremediation.Indeed,householdswithhigherpreferenceforairqualitymaysort

intocleanerareastoofferabetterqualityoflifetotheirchildren,butconcernsaboutthe

overallqualityoftheiroffspringmightalsomakethemmorelikelytofavorqualityover

quantityofchildren.Thisbroadpictureiscorroboratedbyestimatesusinganother

measureofleadexposureinmorerecentyears.Leveragingleadconcentrationinsoilas

measuredbytheU.S.GeologicalSurvey(USGS)inthelate2000s,whichcouldreflect

depositionofpreviousairbornelead,andthe1944interstatehighwayinstrument,we

reportqualitativelysimilarresultsinthe2000s.

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Oursecondfindingismorerevealingintermsofthemechanismsbehindtheestimated

reductioninfertilityrates.Iftherelationshipbetweenleadexposureandfertilitywas

purelyepidemiological,thenwewouldobservenodifferentialcausaleffectsbasedon

mother’seducation.Nevertheless,whenwesplitthesampleintohigheducation(mothers

withhighschoolorhighereducation)versusloweducation(motherswithlessthanhigh

school),wefindthatthereductioninbirthratesisstrongerforlow-educatedhouseholds.

Thisfindingisconsistentwithmoreinformedorwealthierhouseholdsavoidinglead

exposureand/ormakinginvestmentstocompensateforthepotentiallylowerfecundity

associatedwithsomeleadexposure.Avoidanceand/orcompensatorybehaviorrequireat

leastpartialknowledgeoftheeffectsofleadexposureandofthechangesinlead

concentrationovertime.Becauseitismorelikelythathighlyeducatedhouseholdswere

moreinformedthanlowereducatedhouseholds,moreeducatedindividualsmighthave

respondedrelativelymoretothephaseoutofleadingasolineandcompliancewiththe

NAAQSforPM.Atthesametime,educationcouldbeaproxyforincome.Sinceengagingin

defensiveinvestmentsiscostly,moreeducatedfamiliesaremorelikelytohavemore

resourcestoovercome(atleastpartially)thenegativeeffectoflead.Itisimportantto

notice,however,thatavoidancebehaviorshouldbemorelimitedinthiscontext.Itmaybe

relativelycheaptorepaintorrenovateahousebuiltbefore1978–whenthefederal

governmentbannedconsumerusesoflead-containingpaint–toattenuatelead-paint

hazards,butitmightbemuchmoreexpensivetoavoidexposuretoairborneleadbecausea

householdwouldhavetoliveinaneighborhoodwithlowerconcentrations.Thatmightbe

areasonwhyweobservesomeeffectsofairborneleadonfertilityratesevenfor

householdswithmoreeducatedmothers.

Thisstudymakestwomaincontributionstotheliterature.First,itprovidesthefirstcausal

estimatesoftheimpactofexposuretoairborneleadonfertility.Therelationshipbetween

exposuretoleadandfecundity/fertilityiswellestablishedintheepidemiological

literature,buttheevidenceismostlyobservationalandfocusedoncasestudies(e.g.Hauser

andSokol2008,Mendola,Messer,andRappazzo2008,WuandChen2011,andWani,Ara,

andUsmani2015).Second,itpresentsevidenceconsistentwithmoreinformedhouseholds

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avoidingleadexposureand/ormakingremediatinginvestmentstocompensateforthe

potentiallowerfecundity,suggestingthatbehavioralresponsesalsoplayanimportantrole

inexplainingtheeffectsofpollutiononfertility.Besidesthesekeycontributions,thisstudy

addstoagrowingbodyofworkinvestigatingimpactsofenvironmentalinsultson

economicoutcomes(e.g.ChayandGreenstone2003,2005,CurrieandNeidell2005,Currie

andWalker2011,Currieetal.2014,Currieetal.2015,andSchlenkerandWalker2016),in

particularthecausaleffectsofleadexposureoneducation(Aizeretal.,forthcoming)and

crime(Reyes2007,2015).

Thispaperisorganizedasfollows.Afterthisintroduction,section2providesaconceptual

frameworkhighlightingtheepidemiologicalandeconomiclinksbetweenexposuretolead

exposureandfertility.Section3discussesourempiricalstrategy,alongwithimportant

backgroundinformationbehindourinstrumentalvariablesapproach.Section4describes

thedatausedinouranalysis,andsection5reportsourresults.Lastly,section6presents

someconcludingremarks.

2.ConceptualFramework

2.1.TheEpidemiologyofLeadExposureandFertility

Leadwasidentifiedasanabortifacientandacauseofmaleinfertilityandimpotenceduring

thedaysoftheRomanEmpire.However,itwasthepioneeringstudyofLancranjanetal.

(1975)thatfocusedattentionontherolethatchemicalsmightplayinmalefactor

infertility.Theseinvestigatorsstudiedreproductiveoutcomesinmenwhoworkedonthe

productionlineandcomparedthemtomenworkingintheofficeofabatteryplantin

EasternEurope.Theyreportedadose-relatedsuppressionofspermatogenesis,normalor

decreasedserumtestosterone,andinappropriatelynormalurinarygonadotropinsinthe

faceoflowtestosteronelevelsinmenwithhigherbloodleadlevels.

Inrecentdecades,agrowingbodyofevidencehasemphasizedthehazardouseffectsof

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highdosesofleadexposure(see,forexample,reviewsbyNeedleman2004,Patrick2006,

Flora,Gupta,andTiwari2012,andWani,Ara,andUsmani2015).Thescientificcommunity

hasalsonoticedthatthetoxicityoflower-doseleadexposurecancausesomenegative

physicalproblems,whichlackobviousclinicalsignsandthusareeasilyneglected.For

example,apossiblenegativeeffectofthemiddle-lowlevelsofleadexposureonthechange

infemalehormonesystemsmayleadtofemaleinfertility.

Someepidemiologicalhumanstudiesfocusingmainlyonsemenquality,endocrine

function,andbirthratesinoccupationallyexposedsubjectsshowedthatexposureto

concentrationsofinorganicleadimpairedthemalereproductivefunctionbyreducing

spermcount,volume,anddensity,orchangingspermmotilityandmorphology(see,for

example,reviewsbySallmen2001,Sheineretal.2003,andHauserandSokol2008).In

women,abodyofexperimentalevidencealsoindicatesthatleadathighdosesistoxicto

reproductivefunction(see,forexample,reviewsbyMendola,Messer,andRappazzo2008,

andWuandChen2011).Clinicalreports,mostofthemfromthefirsthalfofthetwentieth

century,describeanincreasedincidenceinspontaneousabortionamongfemalelead

workersaswellasinthewivesofmaleleadworkers.Theevidenceappearsthatwomen

withelevatedleadexposurefromoccupationalsettingsareatincreasedriskofdeveloping

infertilitycomparedwithwomenwithnosuchexposure.Recentepidemiologicalstudies

alsofoundthatreproductiveimpairmentsmaydevelopinwomenevenwithlow-to-

moderateleadlevels,includingintrauterinegrowthretardation,pretermdelivery,and

spontaneousabortion.

Tosummarizethelatestevidence,thereproductivesystemofbothmalesandfemalesis

affectedbylead(see,forexample,reviewbyWani,Ara,andUsmani2015).Inmalessperm

countisreducedandotherchangesoccurinthevolumeofspermwhenbloodleadlevels

exceed40μg/dL.Activitieslikemotilityandthegeneralmorphologyofspermarealso

affectedatthislevel.Theproblemswiththereproductivityoffemalesduetoleadexposure

aremoresevere.Toxiclevelsofleadcanleadtomiscarriages,prematurity,lowbirth

weight,andproblemswithdevelopmentduringchildhood.

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2.2.TheEconomicsofLeadExposureandFertility

FollowingBecker (1960) andBecker and Lewis (1973),we consider householdsmaking

fertility choices. Estimating the relationship between lead pollution and fertility is

complicated for at least two reasons related to defensive investment. First, optimizing

individuals may compensate for increases in pollution by reducing their exposure to

protecttheirhealth(e.g.Neidell2004,2009,MorettiandNeidell2011).Second,households

may engage in activities to remediate the effects of pollution exposure (e.g. Deschenes,

Greenstone,andShapiro2017).

Tofixideasonmeasuringandinterpretingtheeffectofleadpollutiononfertility,assume

thefollowingshort-termfertilityproductionfunction:

f=f(lead,avoid,remed,W,S)(1)

where f isameasureof fertility, lead isairborne lead levels,avoid isavoidancebehavior,

andremedisremediationactivities.Wareotherenvironmentalfactorsthatdirectlyaffect

fertility, such as weather, allergens, and other pollutants. S are all other behavioral,

socioeconomic,andgeneticfactorsaffectingfertility.Wecanrearrangethetotalderivative

ofthefertilityproductionfunction(1)togivethefollowingexpressionforthepartialeffect

ofambientpollutiononfertility:

δf/δlead=df/dlead-(δf/δavoid*δavoid/δlead)-(δf/δremed*δremed/δlead)(2)

Thisexpressionisusefulbecauseitunderscoresthatthepartialderivativeoffertilitywith

respecttoairborneleadpollutionisequaltothesumofthetotalderivative,theproductof

the partial derivative of fertilitywith respect to avoidance behavior (assumed to have a

negative sign) and thepartial derivative of avoidancebehaviorwith respect to pollution

(assumedtohaveapositivesign),andtheproductofthepartialderivativeoffertilitywith

respect to remediation (assumed to have a negative sign) and the partial derivative of

remediation with respect to pollution (assumed to have a positive sign). In general,

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complete data on defensive behavior is unavailable, so most empirical investigations of

pollution on fertility (e.g., REFS) reveal df/dlead, rather than δf/δlead. As equation (2)

demonstrates, the total derivative is an underestimate of the desired partial derivative.

Indeed, it is possible that virtually all of the response to a change in pollution comes

throughchangesindefensivebehaviorandthatthereislittleimpactonfertilityoutcomes;

in this case, an exclusive focus on the total derivative would lead to a substantial

understatementofthefertilityeffectofpollution.Thefullimpactthereforerequireseither

estimationofeachelementofthesecondandthirdtermsofequation(2),whichisalmost

alwaysinfeasible,orisolatingδf/δleadusinginstrumentalvariablesthatareorthogonalto

avoidanceandremediationbehavior.

Insteadofdirectlyobservingdefensiveinvestmenttoestimateδf/δlead, thestrategyused

in this paper is to use instruments that shift lead levels but are unrelated to both

avoidance/remediation behavior and other unobserved determinants of fertility. As

describedintheintroduction,weusethephase-outofleadingasoline,theenforcementof

theNAAQSforparticulatematter,andtheirinteractionswiththe1944interstatehighway

plan as instruments for lead levels to obtain estimates ofδf/δlead.While it is likely that

consumersmighthavehadsomeinformationabouttheharmfuleffectsofleadingasoline

even before the phase-out due to the labels “unleaded” versus “regular” in gas station

pumps,itisunlikelytheywereinformedabouttheamountofleadinthe“regular”gasoline,

whichwasthepolicyparameterthatchangedduringthephase-out.Householdsmighthave

hadlessinformationontheenforcementofNAAQSbecauseonlyheavyemitterfirmswere

dealingwiththeregulators;hence,lackofsaliencemighthavebeenanissue.Inaddition,it

ishighlyunlikelythathouseholdswouldhaveaclearideaaboutthe1944plan,whichwas

developed primarily for military purposes. Therefore, we will be assuming that those

instrumentsallowustouncoverδf/δlead.

Although defenses used both before and after pollution is ingested (i.e., averting and

mitigatingactivities)areindistinguishableinsuchaninstrumentalvariableanalysis,from

thepointofviewofpolicymakingthedistinctionbetweenthemisrelevant.Therefore,we

explore the heterogeneity of δf/δlead with respect to a proxy for household income –

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mother’s education. Fertilization treatments are generally expensive, so rich households

mightbeabletoremediatetheeffectsofleadexposuremorethanpoorhouseholds.Thatis,

abs[(δf/δlead)|rich]≤abs[(δf/δlead)|poor].

3.EmpiricalStrategy

3.1.AirborneLeadandFertility

Toestimatethecausaleffectofleadpollutiononfertility,weadoptaninstrumentvariable

approach.Theequationofinterestis

𝑌!"# = 𝛼 + 𝛽𝐿𝑒𝑎𝑑!"# + 𝑋!"#! 𝛾 + 𝜂! + 𝜃! + 𝜆! + 𝑍!! 𝛿! + 𝜀!"# ,

where𝑌!"#isanoutcomevariableforcountyc,monthm,andyeary,Leadisleadpollution

measuredbyEPAmonitoringstations,Xisasetoftime-varyingcontrolvariables,𝜂! isaset

ofcountyfixedeffects,𝜃!isasetmonthfixedeffectstodealwiththeseasonalpatternsof

thevariablesofinterest,𝜆!isasetofyearfixedeffects,Zrepresentslatitudeandlongitude,

whichareinteractedwithyearfixedeffectstocontrolforunobservableeconomicand

meteorologicalconditionsknowntovaryovertime,and𝜀isanerrorterm.

Ourcoefficientofinterestis𝛽.Becausewecannotcontrolforalltime-varyingfactors

affectingtheoutcomevariablesandcorrelatedwithLeadsuchaspreferencesforair

quality,itislikelythat𝛽!"#isbiasedandinconsistent.Inordertoprovideacausal

interpretationfor𝛽,weproceedwithaninstrumentalvariableapproach.Weexploitthe

rolloutoftheCleanAirAct(CAA)regulationstodefineanumberofinstruments.

AmongtheCAAregulationspushedforwardbyEPA,thephasedownofleadingasoline

figuredprominently2.Initially,EPAscheduledperformancestandardsrequiringrefineries

todecreasetheaverageleadcontentofallgasoline–leadedandunleadedpooled–

beginningin1975.ThesestandardswerepostponeduntilOctober1979,whenrefineries

2ThisdiscussionwasheavilydrawnfromNewellandRogers(2003).

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wererequiredtoproduceaquarterlyaverageofnomorethan0.8gramspergallon(gpg).

Theregulationsetanaverageleadconcentrationamongtotalgasolineoutputto

deliberatelyprovidedrefinerswiththeincentivetoincreaseunleadedproduction.Bythe

early1980sgasolineleadlevelshaddeclinedbyabout80percent(seeFigure1).Then,EPA

decidedtoreviewandtightenthestandards,andleadlimitswererecalculatedasan

averageofleadinleadedgasonly,asunleadedfuelwasbythenawell-establishedproduct.

Thenewrulesspecificallylimitedtheallowablecontentofleadinleadedgasolinetoa

quarterlyaverageof1.1gramsperleadedgallon(gplg).From1983to1985theEPA

conductedanextensivecost-benefitanalysisofadramaticreductionintheleadstandardto

0.1gplgby1988.Asaresult,inJuly1985thestandardwasreducedto0.5gplg,and

beginningin1986theallowablecontentofleadinleadedgasolinewasreducedto0.1gplg.

LeadwaseventuallybannedasafueladditiveintheU.S.beginningin1996.

Basedontheregulationsdescribedabove,wedefinefourinstrumentalvariables:(i)a

dummyvariablefortheperiodOctober1979–June1985,whenthe0.8gpgstandardswere

inplace,(ii)adummyvariablefortheperiodstartinginJuly1985,whenthestandards

werechangedandtightenedto0.5gplg,andinteractionsbetween(i)and(ii)andan

indicatorvariableforwhetheracountywouldberunthroughbyhighwaysplannedbythe

1944InterstateHighwaySystemMap(seeFigure2).

FollowingBaum-Snow(2007)andMichaels(2008),weusetheadventoftheU.S.Interstate

HighwaySystemasapolicyexperiment.In1941,PresidentRooseveltappointedaNational

InterregionalHighwayCommittee.ThiscommitteewasheadedbytheCommissionerof

PublicRoads,andappearstohavebeenprofessional,ratherthanpolitical(U.S.Department

Transportation,FederalHighwayAdministration,2002).Thehighwaysweredesignedto

addressthreepolicygoals(Michaels,2008).First,theyintendedtoimprovetheconnection

betweenmajormetropolitanareasintheU.S.Second,theywereplannedtoserveU.S.

nationaldefense.Andfinally,theyweredesignedtoconnectwithmajorroutesinCanada

andMexico.Asaconsequence–butnotanobjective–manyruralcountieswerealso

connectedtotheInterstateHighwaySystem.Ruralcountiescrossedbythehighwayswere

arguablyexogenouslyaffected.

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CongressactedontheserecommendationsintheFederal-AidHighwayActof1944.Inour

analysis,werefertotheplanrecommendedbythatcommitteeasthe“1944plan”(again,

seeFigure2).TheconstructionoftheInterstateHighwaySystembeganafterfundingwas

approvedin1956,andby1975thesystemwasmostlycomplete,spanningover40,000

miles.Politicalagentsmayhavechangedthehighwaysroutesinresponsetoeconomicand

demographicconditionsinruralcounties,contrarytotheoriginalplanners’intent.Thatis

thereasonwhyweusethehighwaylocationfromtheoriginalplanofroutesproposedin

1944inouranalysis.

ThelastinstrumentalvariableisrelatedtotheCAAregulationsforcriteriapollutants.The

nation'sfirstFederaleffortsatcontrollingairpollutionbeganin1963withpassageofthe

CAA.Fouramendmentsfollowedin1967,1970,1977and1990.The1967Amendments

directedthepreviousDepartmentofHealth,EducationandWelfaretoidentifyregional

areaswithcommonairmassesthroughoutthenation[AirQualityControlRegions

(AQCR's)].By1970,57AQCR'swerenamed.Laterthatyear,34additionalareaswere

announced.

The1970AmendmentsauthorizedtheAdministratorofthenewlycreatedEPAtoidentify

additionalareas,butonlyattheStates’initiative.AsofJanuary1972,247AQCR'swere

listed.The1977AmendmentsgavetheEPAtheauthoritytodesignateareasnonattainment

withoutaState’srequest.AfterEPA'sinitialdesignationofareasas

attainment/unclassifiableornonattainmentin1978,however,subsequentdesignations

couldbemadeonlyataState’srequest.Inthatsameyear,EPApublished,forthefirsttime,

alistofallnonattainmentareas.

Forallcriteriapollutants,theCAAAmendmentsof1977requiredthateachnonattainment

areahadtoreachattainment“asexpeditiouslyaspracticable,but,inthecaseofnational

primaryambientairqualitystandards,notlaterthanDecember31,1982.”Becauseleadis

measuredasaportionoftotalsuspendedparticles(TSP),andparticulatematterhadbeen

regulatedsince1971,wedefinethefifthinstrumentalvariableinouranalysistobea

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dummyvariableindicatingnonattainmentstatusforTSPin1978interactedwiththe

periodstartinginJanuary1983.

Giventhesefiveinstrumentalvariables,ourfirststageequationis

𝐿𝑒𝑎𝑑!"# = 𝛼 + 𝜋!𝐿𝑒𝑎𝑑𝑃ℎ𝑎𝑠𝑒𝐷𝑜𝑤𝑛_0.8𝑔𝑝𝑔!"

+ 𝜋!𝐿𝑒𝑎𝑑𝑃ℎ𝑎𝑠𝑒𝐷𝑜𝑤𝑛_0.5𝑔𝑝𝑙𝑔!"

+ 𝜋!(𝐿𝑃𝐷_0.8𝑔𝑝𝑔!" ∗ 𝐻𝑊𝑃𝑙𝑎𝑛1944!)

+ 𝜋!(𝐿𝑃𝐷!.!!"#!!" ∗ 𝐻𝑊𝑃𝑙𝑎𝑛1944!)

+ 𝜋!(𝐴𝑡𝑡𝑎𝑖𝑛𝑚𝑒𝑛𝑡!" ∗ 𝐶𝐴𝐴𝑁𝐴𝑆_𝑇𝑆𝑃1978!)

+ 𝑋!"#! 𝛾 + 𝜂! + 𝜃! + 𝜆! + 𝑍!! 𝛿! + 𝜀!"# ,

whereLeadPhaseDown_0.8gpgisadummyvariablefortheperiodOctober1979–June

1985,whenrefinerieswererequiredtoproduceaquarterlyaverageofnomorethan0.8

gramspergallon(gpg)amongtotalgasolineoutput.LeadPhaseDown_0.8gpgisadummy

variablefortheperiodstartinginJuly1985,whenthestandardsweretightenedto0.5gplg,

andbeginningin1986to0.1gplg.Again,gplg–gramsperleadedgallon–referstothenew

rulesspecificallylimitingtheallowablecontentofleadinleadedgasolineonly.

HWPlan1944isanindicatorforwhetheracountywouldberunthroughbyahighwayas

plannedinthe1944InterstateHighwaySystemMap.TheinteractionswithHWPlan1944

aresupposedtocapturetheintention-to-treateffectassociatedwithpotentialexposureto

leadingasolineburnedandemittedinhighways.Attainmentisanindicatorfortheperiod

startinginJanuary1983,whencountiesoutofattainmentregardingTSPstandardswere

supposedtocomplywithCAAregulations,asrequiredbythe1977Amendments.

CAANAS_TSP1978isadummyvariableforwhetheracountywasdesignatedin

nonattainmentwiththeTSPstandards,aspublishedbyEPAforthefirsttimein1978.

CAANASstandsforCleanAirActNon-AttainmentStatus.

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3.2.SoilLeadandFertility

Tosupplementouranalysisofairborneleadexposureonfertilityduring1978-1988we

alsostudytheeffectsofsoilleadexposureonfertilityinmorerecentyears.Aswehavedata

onsoilleadconcentrationonlyinsingleyearforeachcountyweestimatethefollowing

crosssectionalmodel:

𝑌! = 𝛼 + 𝛽𝑆𝑜𝑖𝑙𝐿𝑒𝑎𝑑! + 𝑋! 𝛾 + 𝜂! + 𝜀! ,

where𝑌! istheoutcomeofinterest(fertilityormortalitymeasures),SoilLead-leadinsoil,

𝑋! -variouscountylevelcontrols,suchasclimate,countyspecificdemographicand

macroeconomicscharacteristics,etc.𝜂!-statefixedeffects.Asbefore,weestimatethis

equationusinginstrumentalvariablestrategy,usingFederal-AidHighwayActof1944asan

instrumentforSoilLead.

4.Data

4.1.LeadData

OurleadpollutiondatawereobtainedbyaFOIArequestatEPA.Weconsideronly

monitorslocatedinthecitylimitstobettermeasureexposuretoleadofcityresidentsand

nottofocusonpollutionmeasurednearindustrialfacilitiesthatmighthavefewpeople

livingnearby.

Thenumberofleadmonitorsvariesovertime.Itgraduallyincreasesuntil1979thenit

remainsrelativelystableuntil1986-1988,afterthatthenumbersharplydeclines.Lead

measurementsareavailableonceeverythreemonthsbefore1978.After1978thelead

measurementsareavailablemonthly.Forthesereasonsweuse1978-1988asatimeperiod

ofourstudy.

Wefocusourattentiononcountiesforwhichwehaveatleastoneleadmonitor.To

constructourleadmeasuresweaggregatemonitor’sreadingstoacountylevel,bytaking

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themeanofallmonitorsinthecounty.Asaresult,wehavean(unbalanced)panelof302

countiesobservedmonthlyover1978-1988.

Thereisabigdeclineinleadlevelduring1978-1988asdemonstratedinFigure3.The

averageleadlevelin1978is0.55µg/m3vs0.12µg/m3inthe1988,thelastyearofour

study.

Figure4plotsthedeclineinleadlevelsovertimeforcountieswiththehighwayasplanned

inthe1944InterstateHighwaySystemMapandcountieswithoutthehighway.The

airborneleadlevelisinitiallyhigherinthecountieswithhighway.During1980-1986there

isagraduallydeclineinlead,andafter1980leadlevelisactuallylowerinthecountieswith

highway.

SoilLeaddataarefromtheU.S.GeologicalSurvey(USGS)conductedinthelate2000s.Soils

samplesarecollectedfromadepthof0to5cm.Thereareabout2100countiesinour

analisys.

4.2.FertilityData

FertilityoutcomesdataarefromtheVitalStatisticsoftheUnitedStates.Thesefilescontain

detailedinformationon100%ofthebirthsinmostcountiesand50%ofthebirthsinthe

remainingcounties.Themonthlybirthcountsaredefinedbycountyofresidence.

Tostudytheeffectofleadonfertilityandchildren’squalitywefocusonthefollowing

outcomes:birthcountsandbirthratebycounty-by-month,andbirthweightandgestation

weeks.Birthratesareconstructedbydividingbirthscountsbypopulationinthatcounty3.

Wealsoconstructthesemeasuresseparatelyformotherswithhighschooleducationand

3Anotherwaytoconstructbirthratewouldbedividebirthcountsbyfemalepopulationbetween15and44yearsofage.

15

motherswithmorethanhighschooleducation(morethan12yearofschooling).Figure1

showsthechangeinnumberofbirthsovertime.Thenumberofbirthswererelatively

stablein1978-1980.After1980thenumberofbirthsisincreasingreachingthepeakof817

in1988.

Figure5plotsthenumberofbirthsovertimeincountieswithhighwayplansof1944

InterstateHighwaySystemMapvscountieswhichwerenotsupposetogetahighway

basedonthe1944plan.Therearefewerbirthsinthecountieswithouthighway.Thatis

notsurprising,asthesearesmallerandmoreruralcounties.Thenumberofbirthsis

relativelyconstantinthesecounties,around200birthspermonth,whereasthenumberof

birthshasincreasedfrom500tomorethan800incountieswithplannedhighway.

4.3.OtherControls

Weuseothercontrolsinouranalysisaswell.Temperatureandprecipitationdataaretaken

fromPRISMClimateData.Wehaveaveragemonthlytemperatureandprecipitation.We

alsoincludecountyincomeandpopulationwhicharetakenfromtheCensus.

4.4.SummaryStatistics

Table1showsthesummarystatisticsforthemainvariablesusedinouranalysis.PanelA

reportsthemeansandstandarddeviationsforthevariableusedinthepaneldataanalysis

oftheeffectsofairborneleadonfertilityovertheperiod1978-1988.Column1presentsthe

summarystatisticsforallpeopleinoursampleof302countiesovertheperiod1978-1988.

Column2and3showthemeansandstandarddeviationsforthefirstandthelastyearin

oursample:1978and1988.Averageairborneleadis0.30withastandarddeviationof

0.45.Therehasbeenasignificantdeclineintheairborneleadoverthestudyperiod.The

leaslevelwasonaverage0.62in1978,andithasdeclinedto0.11in1988.Theaverage

birthratepermonthpercountyis11.42birthper1000women.Theaveragebirthrateis

higheramongpeoplewithlessthanhighschooleducationthanamongindividualswith

highschoolormore:11.42vs9.27birthsper1000women.Birthratewashigherin1978

16

thanin1988:11.37vs10.36.Averagenumberofbirthsofbirthpercountypermonthis

604.11.PanelBpresentsthemeansandstandarddeviationsforthemainvariablesusedin

thecrosssectionalanalysis.Averageleadinsoilis21.11.Averageannualbirthrateis67.84,

andaverageinfantmortalityrateis7.17.

5.Results

First,wepresenttheresultsforairborneleadexposureeffectsonfertilityusingpanel

datasetofUScountiesovertheperiod1978-1988.Second,weshowtheresultsfromthe

crosssectionalanalysisoftheeffectofleadinsoilonfertility.

5.1.EffectsofAirborneLeadonFertility

Inthissectionwereportpreliminaryresultsregardingtheeffectsofleadexposureon

fertilitychoices.Table2aand2bshowtheeffectofleadonfertilityestimatedusingOLS

andourIVapproach.

Table2apresentstheresultsforthebirthrates.PanelAshowstheeffectsestimatedby

OLS,PanelBpresentstheestimatesusingourIVapproach,andPanelCreportsthefirst

stagefortheIVestimation.Incolumn1wedonotincludeanyadditionalcontrols,in

column2wecontrolforcounty,monthandyearXlatitudeandyearXlongitudefixedeffects

aswellasmacroeconomicindicators,suchaslogofemploymentandlogofpercapita

income.Incolumn3weadditionallycontrolforclimatecharacteristics(temperature,

precipitation,andtheirsquares),and,finally,incolumn4weincludeanextensivesetof

individualmother’sandchild’scharacteristics(mother’seducation,mothers’age,marital

status,indicatorforwhetherthebirthwasgivenatahospital,dummyforwhetherthe

physicianwaspresent,dummyfortwinbirths,etc).

BothOLSandIVestimatedeffectsarenegativeandstatisticallysignificantlydifferentfrom

zero,suggestingthatthedeclineinleadincreasesthenumberofbirths.Thoseeffectsdo

notchangemuchwhenweincludeadditionalcontrols.EstimatedcoefficientsinIV

17

specificationsareconsiderablylargerthancorrespondingOLSestimates.Foraone

standarddeviationdecreaseinlead(0.45)IVestimatesimplyanincreaseinthebirthrate

byaroundone(=2.311*0.45),whichisaconsiderableeffectgiventhatthemeanbirthrate

inoursampleisaround11andthestandarddeviationisaround4.

OLSestimatesaremuchsmaller,suggestingthattheyarebiasedtowardszero.We

conjecturethatthismightcomefromhouseholdswithhigherpreferenceforairquality

sortingintocleanerareasthatofferabetterqualityoflifetotheirchildren.Atthesame

time,suchhouseholdsbeingmoreconcernedaboutoverallqualityoftheiroffspringinthe

quality-quantitytradeoffmightprefertohavefewerchildrenaswell.

Table2bpresentstheeffectofleadonothermeasuresoffertility:numberofbirths,logof

numberofbirths,andlogofbirthrate.Theestimatedeffectsareagainnegativeregardless

ofthemeasureusedandsimilarinmagnitudes.

Table3presentstheresultsfortheeffectofleadonfertilityacrossthetwogroups:low

educatedhouseholds(thosewithmotherswithlessthanhighschooleducation)and

educatedhouseholds(thosewithmotherswithhighschooleducationormore).PanelA

presentstheestimatesusingOLS,PanelBshowstheestimatesusingoutIVapproach.OLS

estimatesarepositive,butsmallandnotstatisticallysignificant.IVestimatesarenegative,

largeinmagnitude,andallbutonearestatisticallysignificantlydifferentfromzero.

Moreover,theestimatedeffectforthesampleofhouseholdswithlesseducation(column5)

inmuchlargerthantheeffectformoreeducatedhouseholds(column6).Foraone

standarddeviationincreaseinlead(0.45),thebirthrateamongloweducatedfamilies

woulddeclineby1.45(=0.45*3.233),whereastheeffectforhigheducatedfamiliesis

smaller:0.9(=0.45*2.011).Columns7and8useanothermeasureoffertility:logofbirth

rate,buttheresultsshowthesimilarpattern:loweducatedfamiliesareaffectedmoreby

highleadconcentrationsthanhigheducatedfamilies.Overall,thesefindingssupportthe

defensiveexpenditureconjectureandprovidetheevidencethattherelationshipbetween

leadexposureandfertilityisnotpurelyepidemiological.

18

5.2.EffectsofSoilLeadonFertility

Table4showstheeffectofleadinsoilonbirthratemeasuredin2005fordifferentsetof

controls.Column1presentstheestimatedeffectonlycontrollingforstatefixedeffectsto

accountforunobservedstatespecificvariables,incolumn2wefurtherincludecounty

specificclimatevariables,column3addsdemographiccontrols,column4additionally

controlsforeconomicscharacteristicsofthecounties,incolumn5weaddcounty-specific

housingstock,andcolumn6includesallpreviouscontrolsandaddsthecounty‘s

nonattainmentstatusforotherpollutantsandshareofdemocraticvotes.Theestimated

effectsarenegativeinstatisticallysignificantacrossallspecifications.Foraonestandard

deviationincreaseinlead(12.26),thefertilityrateonaveragedeclinesby3.66

(=12.26*0.299),whichis¼ofthestandarddeviationofthebirthratein2005.TableA4in

theappendixshowstheresultsforotheryearsaswell:2003,2004,2005,2006and2007.

Theeffectsaresimilarinmagnitudes.

Table5presentsthedifferentialeffectofleadinsoilforcountieswithashareofindividuals

withatleasthighschooleducationhigherthanamedianshare(84.3).Columns1through5

showtheeffectsusingthesamestructureasintable4:fromthelessrestrictive

specificationtothemostrestrictiveone.Overall,weestimateanegativeeffectofleadon

birthrate,butthisnegativeeffectgetssmallerincountieswithmorehighschoolgraduates

whichparallelsourfindingthatmoreeducatedhouseholdsareaffectedlessbylead

pollution.

Table6presentsthecrosssectionalresultsfortheeffectofsoilleadonmortalityin2005.

Overall,weestimatepositivecoefficients,suggestingthatanincreaseinsoilleadlevelis

associatedwithhighermortality.Acrossdifferentspecifications,theestimatedeffectsare

ofsimilarmagnitudes,however,somearenotstatisticallysignificantlydifferentfromzero.

Table6Ainappendixpresentstheresultsthemostrestrictivespecification(similartothe

specificationusedincolumn5inTable6)forotheryears:2003-2007.

19

6.ConcludingRemarks

Evidencefromtheepidemiologyliteraturesuggeststhatexposuretoleadimpairsthe

reproductivesystemofbothmalesandfemales,andunderminesbraindevelopmentwhich

mayleadtolowerIQscores,poorerlanguagefunction,poorerattention,andviolent

behavior.Inthisstudyweinvestigatetheseeffectsempiricallyovertheperiod1978-1988,

whenairborneleadconcentrationdecreasedconsiderably.Weleveragethe

implementationofCleanAirActregulationsandthe1944InterstateHighwaySystemPlan

withinafixed-effectinstrumentalvariableapproach,andfindtwomainresults.First,an

exposuretoleadseemstocauseareductioninthenumberofbirthsandbirthratesfora

typicalU.S.county.Second,wepresentsuggestiveevidenceofhouseholds’engagementin

defensiveinvestmenttocountertheadverseeffectsofpollutiononfertility,theestimated

negativeeffectofleadonfertilitybeingsmallerforthefamilieswithmoreeducated

mothers.

20

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23

FiguresandTablesFigure1.LeadContentinLeadedGasoline(U.S.average)

Source:NewellandRogers(2003).

Figure2.RoutesoftheRecommendedInterregionalHighwaySystem–“1944Plan”

Source:Michaels(2008).

24

Figure3:LeadandNumberofBirthOverTime

Notes:Figureshows lead levelsandnumberofbirths/1000over timeduringourstudyperiod1978-1988.Two vertical lines show the time of the two policies we are using in our analysis: October 1979, whenrefinerieswererequiredtoproduceaquarterlyaverageofnomorethan0.8gramspergallon(gpg)amongtotalgasolineoutputandJuly1985,whenthestandardsweretightenedto0.5gplg.Figure4-LeadOverTime:CountieswithandwithoutHighway

Notes: Figure shows lead levels over time in counties with and without highway as planned in the 1944InterstateHighwaySystemMapduringourstudyperiod1978-1988.Twoverticallinesshowthetimeofthetwootherpoliciesweareusinginouranalysis: October1979,whenrefinerieswererequiredtoproduceaquarterly average of nomore than 0.8 gramsper gallon (gpg) among total gasoline output and July 1985,whenthestandardsweretightenedto0.5gplg.

25

Figure5-NumberofBirthsOverTime:CountieswithandwithoutHighway

Notes:Figureshowsnumberofbirths levelsovertimeincountieswithandwithouthighwayasplannedinthe1944 InterstateHighwaySystemMapduringour studyperiod1978-1988.Twovertical lines show thetimeofthetwootherpoliciesweareusinginouranalysis:October1979,whenrefinerieswererequiredtoproduceaquarterlyaverageofnomorethan0.8gramspergallon(gpg)amongtotalgasolineoutputandJuly1985,whenthestandardsweretightenedto0.5gplg.

26

Table1:SummaryStatisticsVariables 1978-1988 1978 1988Lead 0.30 0.62 0.11

(0.45) (0.57) (0.31)

BirthRate 11.17 11.37 10.36

(3.77) (4.66) (4.08)

BirthRateHSdrop 11.42 13.02 9.97

(7.57) (8.52) (6.76)

BirthRateHS+ 9.27 9.29 8.64

(4.49) (5.33) (4.51)

#Births 604.11 451.14 936.58

(1164.70) (804.52) (1650.50)

#BirthsHSdrop 86.59 76.16 158.06

(207.00) (168.54) (463.72)

#BirthsHS+ 322.37 250.64 564.57 (510.32) (351.78) (965.39)AnnualSummaryStatistics:2005LeadinSoil 21.11

(12.26) BirthRate2005 67.84

(13.37)

IMR2005 7.17 (8.50)

Notes:Toppanel shows themeanandstandarddeviations inparenthesesforourmainvariablesusedintheanalysisforthewhole timeperiod1978-1988 aswell as for the first and thelast year of study. Bottom panel presents the mean andstandard deviations (in parentheses) for our cross sectionalanalysesusingdatafor2005.

27

Table2a:AirborneLeadandFertilityPanelA. (1) (2) (3) (4)

BirthRate BirthRate BirthRate BirthRate

VARIABLES OLS OLS OLS OLS Lead -0.559*** -0.137** -0.168** -0.169**

(0.178) (0.065) (0.074) (0.075)

Observations 24,700 24,700 24,700 24,700R-squared 0.008 0.883 0.887 0.888PanelB. (5) (6) (7) (8)

BirthRate BirthRate BirthRate BirthRateVARIABLES IV IV IV IV Lead -2.821*** -2.611*** -2.554*** -2.311***

(0.299) (0.953) (0.944) (0.870)

Observations 24,700 24,700 24,700 24,700R-squared -0.121 -0.297 -0.229 -0.129FirstStageF 60.02 29.99 22.49 22.44PanelC. (9) (10) (11) (12)

Lead Lead Lead Lead

VARIABLES 1stStageIV 1stStageIV 1stStageIV 1stStageIV 𝐴𝑡𝑡𝑎𝑖𝑛𝑚𝑒𝑛𝑡X𝐶𝐴𝐴𝑁𝐴𝑆_𝑇𝑆𝑃1978 -0.039* -0.072* -0.072* -0.082**

(0.022) (0.038) (0.038) (0.036)

𝐿𝑃𝐷0.8𝑔𝑝𝑔X𝐻𝑊𝑃𝑙𝑎𝑛1944 0.078* -0.083* -0.083* -0.085**

(0.043) (0.043) (0.042) (0.041)

𝐿𝑃𝐷0.5gplgX𝐻𝑊𝑃𝑙𝑎𝑛1944 0.012 -0.137** -0.139** -0.139**

(0.029) (0.063) (0.063) (0.066)

𝐿𝑒𝑎𝑑𝑃h𝑎𝑠𝑒𝐷𝑜𝑤𝑛0.8𝑔𝑝𝑔 -0.458*** 0.006 -0.005 -0.003

(0.069) (0.040) (0.040) (0.037)

𝐿𝑒𝑎𝑑𝑃h𝑎𝑠𝑒𝐷𝑜𝑤𝑛0.5𝑔𝑝𝑙𝑔 -0.636*** -0.040 -0.047 -0.046

(0.064) (0.054) (0.054) (0.054)

FirstStageF 60.02 29.99 22.49 22.44

FixedEffects No Yes Yes YesEconomicVariables No Yes Yes YesClimateVariables No No Yes YesMotherandChildCharacteristics No No No Yes

Observations 24,700 24,700 24,700 24,700R-squared 0.284 0.520 0.527 0.529Notes:Alldependentvariablesmeasuredninemonths in the future.BirthRate is thenumberofchildrenborndividedbyfemalepopulation16-39ageold.TableshowstheresultsforOLSandIVusinginstrumentsdiscussedintheidentificationsection.FixedEffectsarecounty,monthandyearbylatitudeandyearbylongitudefixedeffects.EconomicVariablesarelogofemploymentandlogof per capita income. Climate variables are temperature and precipitation and their squares.

28

MotherandChildCharacteristicsaremother’seducation,mothers’age,maritalstatus,indicatorforwhetherthebirthwasgivenatahospital,dummyforwhetherthephysicianwaspresent,dummyfor twin births, skin color of a child, dummy for previous dead child, dummy for previous childalive,controlsforthestartofprenatalcare.Regressionsareweightedbynumberoffemales16-39age old. Standard errors are clustered at the county level and are in parentheses. *, **, and ***indicatestatisticalsignificanceatthe10,5,and1percentlevels.

29

Table2b:AirborneLeadandFertility (1) (1) (2) (2) (3) (3)

#Births #Births

Log(#Births)

Log(#Births)

Log(BirthRate)

Log(BirthRate)

VARIABLES OLS IV OLS IV OLS IV Lead -181.64* -1,184.5* -0.014** -0.250*** -0.015** -0.171***

(100.61) (658.04) (0.006) (0.087) (0.006) (0.064)

FixedEffects Yes Yes Yes Yes Yes YesEconomicVariables Yes Yes Yes Yes Yes YesClimateVariables Yes Yes Yes Yes Yes YesMotherandChildCharacteristics Yes Yes Yes Yes Yes Yes

Observations 24,700 24,700 24,700 24,700 24,700 24,700R-squared 0.990 -0.397 0.986 -0.059 0.833 -0.019FirstStageF 22.44 22.44 22.44Notes:Alldependentvariablesmeasuredninemonthsinthefuture.#Birthsisthenumberofchildrenborn.BirthRateisthenumberofchildrenborndividedbyfemalepopulationaged16-39.TableshowstheresultsforOLSandIVusinginstrumentsdiscussedintheidentificationsection.FixedEffectsarecounty,monthandyearbylatitudeandyearbylongitudefixedeffects.EconomicVariablesarelogofemploymentandlogofpercapita income. Climate variables are temperature and precipitation and their squares. Mother and ChildCharacteristicsaremother’seducation,mothers’age,maritalstatus,indicatorforwhetherthebirthwasgivenat a hospital, dummy forwhether thephysicianwaspresent, dummy for twinbirths, skin color of a child,dummy for previous dead child, dummy for previous child alive, controls for the start of prenatal care.Regressionsareweightedbynumberof females16-39ageold.Standarderrorsareclusteredat thecountylevelandareinparentheses.*,**,and***indicatestatisticalsignificanceatthe10,5,and1percentlevels.

30

Table3:AirborneLeadandFertilitybyEducation (1) (2) (3) (4)

BirthRateHSdrop

BirthRateHS+

Log(BirthRate)HSdrop

Log(BirthRate)HS+

VARIABLES OLS OLS OLS OLS Lead 0.106 0.023 0.125 0.101*

(0.169) (0.068) (0.091) (0.057)

Observations 24,700 24,700 24,700 24,700R-squared 0.834 0.895 0.880 0.900 (5) (6) (7) (8)

BirthRateHSdrop

BirthRateHS+

Log(BirthRate)HSdrop

Log(BirthRate)HS+

VARIABLES IV IV IV IV

Lead -3.233** -2.011* -0.832*** -.7735748

(1.256) (1.135) (0.322) (.4996966)

EconomicsVars Yes Yes Yes YesClimateVars Yes Yes Yes YesDemographicVars Yes Yes Yes YesYear,Month,CountyFEs Yes Yes Yes Yes

Observations 24,700 24,700 24,700 24,700R-squared -0.068 -0.059 -0.040 -0.033FirstStageF 18.43 23.31 18.43 23.31Notes:Columns1,3and5,7presenttheresultsforpeoplewithlessthanhighschooleducation.Columns2,4and6,8reporttheresultsforpeoplewithcompletedhighschoolormore.(morethan12yearsofschooling).Alldependentvariablesmeasuredninemonthsinthefuture.Birthrateisnumberofbirthsdividedbyfemalepopulationaged16-39. All specifications include controls for economics and climatevariable,mother andchild characteristics, as well as year, month, county, year by latitude, year by longitude fixed effects.Regressionsareweightedbyfemalepopulationage16-39.Standarderrorsareclusteredatthecountylevelandareinparentheses.*,**,and***indicatestatisticalsignificanceatthe10,5,and1percentlevels.

31

Table4:LeadinSoilandFertility

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

Birth Rate Birth Rate Birth Rate Birth Rate Birth Rate Birth Rate

VARIABLES

IV IV IV IV IV IV Soil Lead

-0.151 -0.239*** -0.273*** -0.272*** -0.295*** -0.299***

(0.100) (0.089) (0.080) (0.089) (0.111) (0.110)

State FEs

Yes Yes Yes Yes Yes Yes Climate Variables

Yes Yes Yes Yes Yes

Demographic Variables

Yes Yes Yes Yes Economic Variables

Yes Yes Yes

Housing Variables

Yes Yes Other Controls

Yes

Observations

2,113 2,112 2,112 2,100 2,100 2,100 R-squared

0.395 0.429 0.871 0.878 0.871 0.870

First Stage F

65.58 81.52 24.29 19.95 14.03 14.42 Notes:Tableshowscrosssectionalresultsfor2005.BirthRateisthenumberofchildrenbornin2005dividedbyfemalepopulationaged15-45.ClimateVariablesaretemperatureandprecipitationandtheirsquares,aswell as number of heating and cooling degree days in a particular county. Demographic Variables arefollowing:shareofwhitepeople,percentofforeignpeople,shareofpeoplewithcompletedhighschool,shareofpeoplewithcompletedcollege,shareofpeopleindifferentagegroups:below5,5-9,10-14,15-19,20-24,25-29, 30-34, 35-39, 40-44, 45-49, 50-54, 55-59, 60-64. Economics variables are income, employment,percentofpeoplebelowpovertylevel.HousingControlsincludeshareofhousesbuildbefore1939,between1940and1949,between1950and1959,between1960and1969,between1970and1979,between1980and1989,between1990and1999,between2000and2004,numberoftotalhousesbuild,mediumnumberofroomsin2005-2009perhouse.Othercontrolsincludeshareofdemocraticvotesandnonattainmentstatusforanypollutant.

32

Table5:LeadinSoilandFertilitybyEducation

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

BirthRate BirthRate BirthRate BirthRate BirthRate BirthRate

VARIABLES

IV IV IV IV IV IV SoilLead

0.084 -0.050 -0.274*** -0.250*** -0.272*** -0.280***

(0.094) (0.084) (0.076) (0.078) (0.096) (0.096)

SoilLeadX -0.196*** -0.162*** 0.000 -0.021 -0.019 -0.016 (shareHS>84.3)

(0.023) (0.023) (0.018) (0.020) (0.021) (0.021)

ClimateVariables

Yes Yes Yes Yes Yes

DemographicVariables

Yes Yes Yes YesEconomicVariables

Yes Yes Yes

HousingVariables

Yes YesOtherControls

Yes

Observations

2,113 2,112 2,112 2,100 2,100 2,100 R-squared

0.418 0.466 0.871 0.881 0.875 0.873

FirstStageF

34.87 42.93 12.56 11.12 7.926 8.150 Notes:Tableshowscrosssectionalresultsfor2005.SoilLeadX(shareHS>84.3)showsdifferentialeffectsforcountieswith the share of high school graduates higher than 84.3%,which is themedian value for 2005-2009.BirthRate is thenumberofchildrenborn in2005dividedby femalepopulationaged15-45.ClimateVariables are temperature and precipitation and their squares, as well as number of heating and coolingdegreedays inaparticular county.DemographicVariablesare following: shareofwhitepeople,percentofforeignpeople,shareofpeoplewithcompletedhighschool,shareofpeoplewithcompletedcollege,shareofpeopleindifferentagegroups:below5,5-9,10-14,15-19,20-24,25-29,30-34,35-39,40-44,45-49,50-54,55-59,60-64.Economicsvariablesareincome,employment,percentofpeoplebelowpovertylevel.HousingControls include share of houses build before 1939, between 1940 and 1949, between 1950 and 1959,between 1960 and 1969, between 1970 and 1979, between 1980 and 1989, between 1990 and 1999,between2000and2004,numberof totalhousesbuild,mediumnumberofroomsin2005-2009perhouse.Othercontrolsincludeshareofdemocraticvotesandnonattainmentstatusforanypollutant.

33

Table6:LeadinSoilandInfantMortality

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

IMR IMR IMR IMR IMR IMR

VARIABLES

IV IV IV IV IV IV SoilLead

0.070** 0.040 0.087* 0.073 0.068 0.066

(0.030) (0.027) (0.050) (0.055) (0.064) (0.063)

StateFEs

Yes Yes Yes Yes Yes YesClimateVariables

Yes Yes Yes Yes Yes

DemographicVariables

Yes Yes Yes YesEconomicVariables

Yes Yes Yes

HousingVariables

Yes YesOtherControls

Yes

Observations

2,120 2,119 2,119 2,106 2,106 2,106 R-squared

0.148 0.202 0.263 0.294 0.306 0.308

FirstStageF

73.32 86.33 25.89 22.37 16.34 16.79 Notes:Tabelsshowscrosssectionalresults for2005.IMRistheinfantmortalityrate.ClimateVariablesaretemperatureandprecipitationandtheirsquares,aswellasnumberofheatingandcoolingdegreedaysinaparticular county. Demographic Variables are following: share of white people, percent of foreign people,share of people with completed high school, share of people with completed college, share of people indifferentagegroups:below5,5-9,10-14,15-19,20-24,25-29,30-34,35-39,40-44,45-49,50-54,55-59,60-64. Economicsvariablesareincome,employment,percentofpeoplebelowpoverty level.HousingControlsincludeshareofhousesbuildbefore1939,between1940and1949,between1950and1959,between1960and1969, between1970 and1979, between1980 and1989, between1990 and1999, between2000 and2004, number of total houses build, medium number of rooms in 2005-2009 per house. Other controlsincludeshareofdemocraticvotesandnonattainmentstatusforanypollutant.

34

AppendixTablesTableA4:LeadinSoilandFertilityOverTime

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

BirthRate BirthRate BirthRate BirthRate BirthRate

2003 2004 2005 2006 2007VARIABLES

IV IV IV IV IV

SoilLead

-0.147* -0.253** -0.299*** -0.281** -0.133

(8.390) (10.071) (10.967) (11.251) (9.521)

StateFEs

Yes Yes Yes Yes YesClimateVariables Yes Yes Yes Yes YesDemographicVariables Yes Yes Yes Yes YesEconomicVariables Yes Yes Yes Yes YesHousingVariables Yes Yes Yes Yes YesOtherControls Yes Yes Yes Yes Yes

Observations

2,105 2,104 2,100 2,103 2,106R-squared

0.919 0.887 0.870 0.866 0.903

FirstStageF

14.45 14.44 14.42 14.44 14.45Notes:Tableshowscrosssectionalresultsfor2003-2007.BirthRateisthenumberofchildrenbornin2007divided by female population aged 15-45. Climate Variables are temperature and precipitation and theirsquares,aswellasnumberofheatingandcoolingdegreedaysinaparticularcounty.DemographicVariablesarefollowing:shareofwhitepeople,percentofforeignpeople,shareofpeoplewithcompletedhighschool,shareofpeoplewithcompletedcollege,shareofpeopleindifferentagegroups:below5,5-9,10-14,15-19,20-24,25-29,30-34,35-39,40-44,45-49,50-54,55-59,60-64.Economicsvariablesareincome,employment,percentofpeoplebelowpovertylevel.HousingControlsincludeshareofhousesbuildbefore1939,between1940and1949,between1950and1959,between1960and1969,between1970and1979,between1980and1989,between1990and1999,between2000and2004,numberoftotalhousesbuild,mediumnumberofroomsin2005-2009perhouse.Othercontrolsincludeshareofdemocraticvotesandnonattainmentstatusforanypollutant.

35

TableA6:LeadinSoilandMortalityOverTime

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

IMR IMR IMR IMR IMR

2003 2004 2005 2006 2007VARIABLES

IV IV IV IV IV

SoilLead

-0.004 -0.031 0.066 -0.038 0.103

(0.061) (0.061) (0.063) (0.057) (0.066)

StateFEs

Yes Yes Yes Yes YesClimateVariables Yes Yes Yes Yes YesDemographicVariables Yes Yes Yes Yes YesEconomicVariables Yes Yes Yes Yes YesHousingVariables Yes Yes Yes Yes YesOtherControls Yes Yes Yes Yes Yes

Observations

2,106 2,106 2,106 2,106 2,106R-squared

0.355 0.345 0.308 0.355 0.191

FirstStageF

16.79 16.79 16.79 16.79 16.79Notes:Tableshowscrosssectionalresultsfor2003-2007.Mortalityisthenumberofcdeathinyeartdividedbynumberofbirthinthesameyear.ClimateVariablesaretemperatureandprecipitationandtheirsquares,as well as number of heating and cooling degree days in a particular county. Demographic Variables arefollowing:shareofwhitepeople,percentofforeignpeople,shareofpeoplewithcompletedhighschool,shareofpeoplewithcompletedcollege,shareofpeopleindifferentagegroups:below5,5-9,10-14,15-19,20-24,25-29, 30-34, 35-39, 40-44, 45-49, 50-54, 55-59, 60-64. Economics variables are income, employment,percentofpeoplebelowpovertylevel.HousingControlsincludeshareofhousesbuildbefore1939,between1940and1949,between1950and1959,between1960and1969,between1970and1979,between1980and1989,between1990and1999,between2000and2004,numberoftotalhousesbuild,mediumnumberofroomsin2005-2009perhouse.Othercontrolsincludeshareofdemocraticvotesandnonattainmentstatusforanypollutant.