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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.