The Wage Impact of the Marielitos: A Reappraisal

Version3.1;10/4/152:30PM

The Wage Impact of the Marielitos: A Reappraisal

George J. Borjas Harvard University

October 2015

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George J. Borjas

ABSTRACT

ThispaperbringsanewperspectivetotheanalysisoftheMarielsupplyshock,revisiting

thequestionandthedataarmedwiththeaccumulatedinsightsfromthevastliteratureon

theeconomicimpactofimmigration.Acruciallessonfromthisliteratureisthatany

credibleattempttomeasurethewageimpactofimmigrationmustcarefullymatchthe

skillsoftheimmigrantswiththoseofthepre-existingworkers.TheMarielitoswere

disproportionatelylow-skill;atleast60percentwerehighschooldropouts.Areappraisal

oftheMarielevidence,specificallyexaminingtheevolutionofwagesinthelow-skillgroup

mostlikelytobeaffected,quicklyoverturnsthefindingthatMarieldidnotaffectMiami’s

wagestructure.TheabsolutewageofhighschooldropoutsinMiamidroppeddramatically,

asdidthewageofhighschooldropoutsrelativetothatofeitherhighschoolgraduatesor

collegegraduates.ThedropintherelativewageoftheleasteducatedMiamianswas

substantial(10to30percent),implyinganelasticityofwageswithrespecttothenumber

ofworkersbetween-0.5and-1.5.Theanalysisalsodocumentsthesensitivityofthe

estimatedwageimpacttothechoiceofaplacebo.Themeasuredimpactismuchsmaller

whentheplaceboconsistsofcitieswherepre-Marielemploymentgrowthwasweak

relativetoMiami.

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George J. Borjas* I. Introduction

Thestudyofhowimmigrationaffectslabormarketconditionshasbeenacentral

concerninlaboreconomicsfornearlythreedecades.Thesignificanceofthequestionarises

notonlybecauseofthepolicyissuesinvolved,butalsobecausethestudyofhowlabor

marketsrespondtosupplyshockscanteachusmuchabouthowlabormarketswork.Inan

importantsense,examininghowimmigrationaffectsthewagestructureconfrontsdirectly

oneofthefundamentalquestionsineconomics:Whatmakespricesgoupanddown?

DavidCard’s(1990)classicstudyofthelabormarketimpactoftheMarielsupply

shockstandsasalandmarkinthisliterature.OnApril20,1980,FidelCastrodeclaredthat

CubannationalswishingtomovetotheUnitedStatescouldleavefreelyfromtheportof

Mariel,andaround125,000Cubansquicklyacceptedtheoffer.TheCardstudywasoneof

thepioneeringattemptstoexploittheinsightthatacarefulstudyofnaturalexperiments,

suchastheexogenoussupplyshockstimulatedbyCastro’sseeminglyrandomdecisionto

“letthepeoplego,”canhelpidentifyparametersofsignificanteconomicinterest.In

particular,theMarielsupplyshockwouldletusmeasurethewageelasticitythatshows

howthewageofnativeworkersrespondstoanexogenousincreaseinsupply.

Card’sempiricalanalysisoftheMiamilabormarket,whencomparedtoconditions

inotherlabormarketsthatservedasacontrolgroupor“placebo,”indicatedthatnothing

muchhappenedtoMiamidespitetheverylargenumberofMarielitos.Nativewagesdidnot

godownintheshortrunaswouldhavebeenpredictedbythetextbookmodelofa

competitivelabormarket.Andunemployment,evenforgroupswithlowaverageskills,

remainedunchangedrelativetowhatwashappeningintheplacebocities.Card’sstudyhas

*HarvardUniversity,NationalBureauofEconomicResearch,andIZA.Iamparticularlygratefulto

AlbertoAbadieandLarryKatzforveryproductivediscussionsoftheissuesexaminedinthispaperandformanyvaluablecommentsandsuggestions.IhavealsobenefittedfromthereactionsandadviceofJoshAngrist,FranBlau,BrianCadena,KirkDoran,RichardFreeman,DanielHamermesh,GordonHanson,AlanKrueger,JoanLlull,JoanMonras,PanuPoutvaara,MartaTienda,andSteveTrejo.Ialoneamresponsibleforallerrors.

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beenextremelyinfluential,bothintermsofitsprominentroleinpolicydiscussionsandits

methodologicalapproach.1

Duringthe1980sand1990s,aparallel(butnon-experimental)literatureattempted

toestimatethelabormarketimpactofimmigrationbyessentiallycorrelatingwagesand

immigrationacrosscities(Grossman,1982;Borjas,1987;AltonjiandCard,1991).These

spatialcorrelationshavebeencriticizedfortworeasons:(1)immigrantsaremorelikelyto

settleinhigh-wagecities,sothattheendogeneityofsupplyshocksinducesaspurious

positivecorrelationbetweenimmigrationandwages;and(2)nativeworkersandfirms

respondtosupplyshocksbyresettlinginareasthatofferbetteropportunities,effectively

diffusingtheimpactofimmigrationacrossthenationallabormarket.

Card’sMarielstudyisimpervioustobothofthesecriticisms.Thefactthatthe

MarielitossettledinMiamihadlittletodowithpre-existingwageopportunities,andmuch

todowiththefactthatCastrosuddenlydecidedtoallowtheboatlifttooccurandthatthe

Cuban-AmericanswhoorganizedtheflotillalivedinSouthFlorida.2Similarly,thevery

shortrunnatureofCard’sempiricalexercise,effectivelylookingattheimpactof

immigrationjustafewyearsafterthesupplyshock,meansthatweshouldbemeasuring

theshort-runelasticity,anelasticitythatisnotyetcontaminatedbylabormarket

adjustmentsandthateconomictheorypredictstobenegative.

AngristandKrueger’s(1999)analysisofthe“TheMarielBoatliftThatDidNot

Happen”providesthemostimportantconceptualcriticismofCard’sstudytodate:3

Inthesummerof1994,tensofthousandsofCubansboardedboatsdestinedforMiamiinanattempttoemigratetotheUnitedStatesinasecondMarielBoatliftthatpromisedtobealmostaslargeasthefirstone...Wishingtoavoidthepoliticalfalloutthataccompaniedtheearlierboatlift,theClintonAdministrationintercededandorderedtheNavytodivertthewould-be

1StudiesthatexamineexogenoussupplyshocksthatareclearlyinfluencedbytheCardanalysis

includeHunt(1992),CarringtonanddeLima(1996),Friedberg(2001),Saiz(2003),BorjasandDoran(2012),Glitz(2012),Pinottietal(2013),andDustmann,Schönberg,andStuhler(2015).

2Boththe1990and2000censusesreportthatalmosttwo-thirdsoftheCubanimmigrantswholikelywerepartoftheMarielinfluxstillresidedintheMiamimetropolitanarea.

3Therehavealsobeenmanydiscussionsofthestatisticalinferencedifficultiesraisedbythistypeofanalysis;seeBertrand,Duflo,andMullainathan(2004),DonaldandLang(2007),andAydemirandKırdar(2013).

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immigrantstoabaseinGuantanamoBay.OnlyasmallfractionoftheCubanémigréseverreachedtheshoresofMiami.Hence,wecallthisevent,"TheMarielBoatliftThatDidNotHappen"(AngristandKrueger,1999,p.1328;emphasisadded).

AngristandKruegerreproducedthemethodologicaldesignofCard’sMarielarticle

bycomparingthelabormarketinMiamibeforeandafter1994withthesamesetofplacebo

cities.Itturnedoutthatthispotentialsupplyshockmadethingsmuchworseforsome

natives.Forexample,theblackunemploymentrateinMiamiincreasedfrom10to14

percent,atatimethattheaggregateeconomywasboomingandunemploymentwas

droppingintheplacebocities.

Theusualinterpretationwouldhavetobethata“phantommenace”ofnon-existent

workersharmedMiami’sAfrican-Americanworkforce.Itobviouslymakesnosenseto

makesuchaclaim,butthisraisesanimportantquestion:Doestheevidencefromthe

Marielboatliftthatdidhappenreallyindicatethatimmigrationhadnoimpact?AsAngrist

andKrueger(1999,p.1329)conclude,“Sincetherewasnoimmigrationshockin1994,this

illustratesthatdifferentlabormarkettrendscangeneratespuriousfindingsinresearchof

thistype.”

Inretrospect,however,theAngrist-Kruegerclaimthat“onlyasmallfractionofthe

CubanémigréseverreachedtheshoresofMiami,”writtenbeforetheavailabilityofthe

2000census,wasnotaccurate.AsIwillshowshortly,PresidentClinton’sdecisionto

reroutethepotentialmigrantstoGuantanamoseemedtoonlydelayasizablesupplyshock

ofaround50,000Cubansbyonlyayearorso.Asaresult,itmaybedifficulttoinfermuch

fromthecomparisonoftheMarielsupplyshocktothe1994eventthatendedupbringing

manyimmigrantstotheMiamimetropolitanarea.

ThispaperprovidesareappraisaloftheevidenceofhowtheMiamilabormarket

respondedtotheinfluxofMarielitos.Thepaperisnotareplicationoftheearlierstudies.

Instead,Iapproachandexaminethesequestionsfromafreshperspective,buildingonwhat

wehavelearnedfromthe30yearsofresearchonthelabormarketimpactofimmigration.

Onecrucialinsightfromthisresearchisthatanycredibleattempttomeasuretheimpact

mustcarefullymatchtheskillsoftheimmigrantswiththeskillsofthepre-existing

workforce.Borjas(2003),inthestudythatintroducedtheapproachofcorrelatingwages

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andimmigrationacrossskillgroupsinthenationallabormarket,foundasignificant

negativecorrelationbetweenthewagegrowthofspecificskillgroups,definedbyeducation

andage,andthesizeoftheimmigration-inducedsupplyshockintothosegroups.

Theanalysisoftheavailablemicrodatausingthisnewperspectiveprovidesavery

differentpictureofwhathappenedafterMariel.Asiswellknown,theMarielitoswere

disproportionatelylow-skill;around60percentwerehighschooldropoutsandonly10

percentwerecollegegraduates.Atthetime,aboutaquarterofMiami’spre-existing

workerslackedahighschooldiploma.Asaresult,eventhoughtheMarielsupplyshock

increasedthenumberofworkersinMiamiby8percent,itincreasedthenumberofhigh

schooldropoutsbyalmost20percent.

Theunbalancednatureofthissupplyshockobviouslysuggeststhatweshouldlook

atwhathappenedtothewageofhighschooldropoutsinMiamibeforeandafterMariel.

Remarkably,thistrivialcomparisonwasnotmadeinCard’s(1990)studyand,tothebestof

myknowledge,hasnotyetbeenconducted.4Byfocusingonthisveryspecificskillgroup,

thefindingthattheMarielsupplyshockdidnothaveanyconsequencesforpre-existing

workersimmediatelydisappears.Infact,theabsolutewageofhighschooldropoutsin

Miamidroppeddramatically,asdidthewageofhighschooldropoutsrelativetothatof

eitherhighschoolgraduatesorcollegegraduates.Thedropinthelow-skillwagebetween

1979and1985wassubstantial,perhapsasmuchas30percent.

Theevidencereportedinthispaperprovidesanentirelynewperspectiveofhow

theMiamilabormarketrespondedtoanexogenoussupplyshock.Atleastintheshortrun,

thelabormarketrespondedpreciselyinthewaythatthe“textbook”modelpredicts:an

increaseinthenumberofpotentialworkersloweredthewageofthoseworkerswhofaced

themostcompetitionfromthenewimmigrants.Itseemsthattheshort-runlabordemand

curve,evenintheMiamioftheearly1980s,wasdownwardslopingafterall.

4Table7inCard(1980)reportswageandemploymentchangesforthesubsampleofblackhigh

schooldropouts,butdoesnotreportanyotherpre-postMarieldifferencesfortheleasteducatedworkers.Card’sfindingthattheblackwageinMiamideclinedafterMariel,whichheattributestocyclicalfluctuations,willbediscussedbelow.Inanunpublishedonlineappendix,Monras(2014)attemptstoreplicatesomeofCard’sresultsandalsoexamineswagetrendsinthesampleofworkerswhohaveatmostahighschooldiploma.Monras’sevidenceisverysuggestiveofthefindingsreportedinthispaper.

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II. Data ThemigrationoflargenumbersofCubanstotheUnitedStatesbeganshortlyafter

FidelCastro’scommunisttakeoveronJanuary1,1959.Bytheyear2010,over1.3million

Cubanshademigrated.

Thefirstlarge-scaledatasetthatpreciselyidentifiesanimmigrant’syearofarrival

isthe2000decennialcensus.Priorto2000,thecensusmicrodatareportedtheyearof

arrivalinintervals(e.g.,1960-1964).Imergedthedatafromvariouscensusesandthe

AmericanCommunitySurveys(ACS)toconstructamortality-adjustednumberofCuban

immigrantsforeacharrivalyearbetween1955and2010.5Forexample,Iusedthe1970

censustoestimatethenumberofCubanimmigrantswhoarrivedintheUnitedStates

between1960and1964,andthenusedthedetailedyear-of-migrationinformationinthe

2000censustoallocatethoseearlyimmigrantstospecificyearswithinthe5-yearband.

Figure1showsthetrendinthenumberofCubansmigratingtotheUnitedStates.

Severalpatternsemergefromthetimeseries.First,itiseasytoseetheimmediate

impactofthecommunisttakeoveroftheisland.In1958,only8,000Cubansmigratedtothe

UnitedStates.By1961and1962,52,000Cubansweremigratingannually.6TheCuban

MissileCrisisabruptlystoppedthisflowinOctober1962,andittookseveralyearsfor

otherescaperoutestoopenup.Bythelate1960s,thenumberofCubansmovingtothe

UnitedStateswasagainnearthelevelreachedbeforetheMissileCrisis.

Thehugespikein1980,ofcourse,istheMarielsupplyshock.Between1978and

1980,thenumberofnewCubanimmigrantsincreased17-fold,from6,500to110,000.The

figureshowsyetanotherspikein1994and1995,coincidingwiththeperiodofAngristand

Krueger’s(1999)“MarielBoatliftThatDidNotHappen.”Thecensusdataclearlyindicates

thatsomehowthe“phantom”CubansfromthatboatliftendedupintheUnitedStates,

makingthissupplyshockaLittleMariel.Althoughthenumberof“LittleMarielitos”palesin

comparisontothenumberofactualMarielitos,itisstillquitelarge;thenumberofmigrants

arrivingin1995wassimilartothatoftheearlyCubanwavesinthe1960s.Itisalsoevident

5Inprinciple,thecalculationalsoadjustsforpotentialout-migrationofCubanimmigrants.Isuspect,

however,thatthenumberofCubanswhochosetoreturnistriviallysmall(althoughalargernumbermighthavemigratedelsewhere).

6Fulldisclosure:Iamadatapointinthe1962flow.

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thattherehasbeenasteadyincreaseinthenumberofCubanmigrantssincetheearly

1980s.By2010,about40,000Cubanswerearrivingannually.

OnelastdetailisworthnotingabouttheCubanmigration:Adisproportionately

largenumberoftheimmigrantsendedupresidingintheMiamimetropolitanarea.The

fractionofCubanimmigrantsresidinginMiamiwas50percentinthe1980census,58

percentinthe1990census,and60percentinthe2000census.RegardingtheMarielitos

themselves,62.6percentoftheMarielitosresidedinMiamiin1990and63.4percentstill

residedtherein2000.

Themaindatasetsusedintheempiricalanalysisarethe1977-1993March

SupplementsoftheCurrentPopulationSurveys(CPS).7Thesesurveysreporttheannual

wageandsalaryincomeaswellasthenumberofweeksworkedbyarespondentinthe

previouscalendaryear.Thewageanalysiswillberestrictedtomenaged25-59,whoare

notself-employed,whoarenotenrolledinschool,andwhoreportpositiveannualearnings,

positiveweeksworked,andpositiveusualhoursworked.8Theagerestrictionensuresthat

aworker’sobservedearningsarenotcontaminatedbytransitoryfluctuationsthatoccur

duringthetransitionsfromschooltoworkandfromworktoretirement.

The1977-1993periodthatwillbeanalyzedthroughoutmuchofthepaperis

selectedfortworeasons.First,althoughtheMarchCPSdatafilesareavailablesince1962,

theMiamimetropolitanareacanonlybeconsistentlyidentifiedinthe1973-2004surveys.

Beginningwiththe1977survey,theCPSbegantoidentify44metropolitanareas(including

Miami)thatcanbeusedintheempiricalanalysis.9Second,myanalysisofwagetrendswill

7TheMarchsurveysareknownastheAnnualSocialandEconomicSupplements(ASEC).Thedata

wasdownloadedfromtheIntegratedPublicUseMicrodataSeries(IPUMS)websiteonAugust22,2015.Card(1990)usedtheCPSOutgoingRotationGroups(ORG).IwillshowbelowthattheevidencefromtheORGdataleadstoasimilarinference:somethingdidindeedhappentothelow-skilllabormarketinpost-MarielMiami.

8Inaddition,Iexcludepersonswhoresideingroupquartersorhaveanegativesampleweight.Itistemptingtoincreasesamplesizebyincludingworkingwomeninthestudy,butfemalelaborforceparticipationwasincreasingveryrapidlyinthe1980s,sothatwagetrendsarelikelytobeaffectedbytheselectionthatmarkswomen’sentryintothelabormarket.Thelaborforceparticipationrateofwomen(aged18-64)increasedfrom52.1to72.5percentbetween1980and1990inMiami,andfrom49.2to71.2percentinallotherurbanareas.

9TheMiami-Hialeahmetropolitanareaisnotidentifiedatallbefore1973,andiscombinedwiththeFortLauderdalemetropolitanareaafter2004.The1973-1976surveysidentifyonly34metropolitanareas,andoneofthem(NewYorkCity)isnotconsistentlydefinedthroughouttheperiod;theNassau-SuffolkmetropolitanareaispooledwiththeNewYorkCitymetroareain1976.

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stopwiththe1993surveytoavoidcontaminationfromtheLittleMarielsupplyshockof

1994and1995.

TheCPSdidnotreportaperson’scountryofbirthbefore1994,sothatitisnot

possibletomeasurethewageimpactoftheMarielsupplyshockonthenative-born

population.Iinsteadexaminetheimpactonnon-Hispanicmen(whereHispanic

backgroundisdeterminedbyaperson’sanswertotheHispanicethnicityquestion),a

samplerestrictionthatcomesclosetoidentifyingMiami’snative-bornpopulationatthe

time.Forexample,the1980census,conducteddaysbeforetheMarielsupplyshock,

reportsthat40.7percentofMiami’smaleworkforcewasforeign-born,with65.1percentof

theimmigrantsborninCubaandanother11.2percentborninotherLatinAmerican

countries.

Thelabormarketoutcomeexaminedthroughoutthestudywillbetheworker’slog

weeklyearnings,whereweeklyearningsaredefinedbytheratioofannualincomeinthe

previouscalendaryeartothenumberofweeksworked.IusetheConsumerPriceIndex

(CPI)forallurbanconsumerstodeflatetheearningsdata(1980=100).10Forexpositional

consistencyandunlessotherwisenoted,wheneverIrefertoaparticularcalendaryear

hereafter,itwillbetheyearinwhichearningswereactuallyreceivedbyaworker,as

opposedtotheCPSsurveyyear.11

Beforeproceedingtoanexaminationofwagetrends,itisimportanttodocument

whatweknowabouttheskilldistributionoftheMarielitos.Asnotedearlier,theMariel

supplyshockbeganafewdaysafterthe1980censusenumeration,sothatthefirstlarge

surveythatcontainsalargesampleoftheMarielitosthemselvesisthe1990census.

Nevertheless,afewCPSsupplementsconductedinthe1980s(includingApril1983,June

1986,andJune1988)provideinformationona(very)smallsampleofCubanimmigrants

whoarrivedatthetimeofMariel.

10Tominimizetheproblemofoutlyingobservations,Iexcludeallworkerswhoearnlessthan$1.50

anhourormorethan$40anhour(in1980dollars).Thisrestrictionapproximatelydropsworkersinthetopandbottom1percentoftheearningsdistribution.Ireplicatedtheanalysisusingtheloghourlywageasanalternativemeasureofaworker’sincome,andtheresultsaresimilartothosereportedinthispaper.

11Forexample,adiscussionoftheearningsofworkersin1985referstothedatadrawnfromthe1986MarchCPS.

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Table1presentstheeducationdistributionofthesampleofadultCubanimmigrants

whoarrivedin1980(orin1980-1981,dependingonthedataset)andwhowere

enumeratedinvarioussurveyssometimebetween1983and2000.Thecalculationincludes

theentirepopulationofMarielitos(workersandnon-workers,aswellasmenandwomen)

whowereatleast18yearsoldasof1980.

ThecrucialimplicationofthetableisthattheMarielsupplyshockconsistedof

workerswhowereveryunskilled,witharemarkablylargefractionoftheMarielitosbeing

highschooldropouts.12Despitethevariationinsamplesizeandthealmost20-yearspanin

thesurveysreportedinthetable,thefractionofMarielitoswholackedahighschool

diplomahoversaround60percent.Table1alsoshowsthataverysmallfractionofthese

immigrantswerecollegegraduates(around10percent).

ItisinsightfultocomparetheeducationdistributionoftheMarielitoswiththatof

thepre-existingworkforce.ThelastrowofTable1showsthat“only”26.7percentoflabor

forceparticipantsintheMiamimetropolitanareawerehighschooldropouts.Infact,

Miami’sworkforcewasremarkablybalancedintermsofitsskilldistribution,with20to30

percentofworkersineachofthefoureducationgroups.13

Table2summarizeswhatweknowaboutthemagnitudeoftheMarielsupplyshock.

Therewere176,300highschooldropoutsinMiami’slaborforcejustpriortoMariel(outof

atotalof659,400).Accordingtothe1990census,60,100Cubanworkersmigrated(as

adults)eitherin1980or1981.Ifwemakeaslightadjustmentforthesmallnumberwho

enteredthecountryin1981,Marielincreasedthesizeofthelaborforceby55,700persons,

ofwhichalmost60percentwerehighschooldropouts.14AlthoughtheMarielsupplyshock

12ThefactthatmostoftheadultMarielitoslackedahighschooldiplomadoesnotnecessarilyimply

thattheydidnotcompletecompulsoryschoolinginCuba.ThereisalsoapossibilitythattheskillsoftheMarielitoswerefurther“downgraded”uponarrival,asinDustmann,Frattini,andPreston(2013),sothateventhoseimmigrantswithahighschooldiplomawerestillcompetingwiththeleasteducatedworkersinthepre-existingMiamiworkforce.

13Thepre-existingworkforceincludesalllaborforceparticipantsinMiami,regardlessofwheretheywerebornortheirethnicity.Thefractionofnon-Hispanicworkerswhowerehighschooldropoutswasalsoveryhigh(19.8percent).

14The2000censusindicatesthatapproximately92.8percentoftheCubanimmigrantswhoenteredthecountryineither1980or1981actuallyenteredin1980.ItisalsoimportanttonotethatthesupplyshockwasprobablyslightlylargerthanindicatedinTable2becausethecalculationdoesnotaccountformortalitythrough1990.

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increasedMiami’sworkforceby8.4percentandincreasedthenumberofthemost

educatedworkersby3to5percent,thesizeofthelow-skilllaborforcerosebya

remarkable18percent.Moreover,thissupplyshockoccurredalmostovernight(Stabile

andScheina,2015).ThefirstMarielitosarrivedinFloridaonApril23,1980.TheCoast

Guardreportsthatover100,000refugeeshadreachedtheFloridashoresbyJune3.

III. Descriptive Evidence TheverylowskillsoftheMarielitosindicatesthatweshouldperhapsfocusour

attentiononthelabormarketoutcomesoftheleasteducatedworkersinMiamitogeta

first-ordersenseofwhetherthesupplyshockhadanyimpactonMiami’swagestructure.In

fact,theliteraturesparkedbyBorjas(2003)suggeststhatitisimportantto“match”the

immigrantstocorrespondingnativeworkersbyskillgroups.Educationalattainmentisa

skillcategorythatwouldseemtobeextremelyrelevantinanexaminationoftheMariel

supplyshock.

AnyempiricalstudyoftheimpactofMarielencountersanimmediatedataproblem:

ThenumberofworkersenumeratedbytheCPSintheMiamilabormarketissmall,

introducingalotofrandomnoiseintoanycalculation.Inparticular,thenumberofnon-

HispanicmenwhosatisfythesamplerestrictionsandwhoareemployedintheMiamiarea

wasaround90-100perCPScross-sectioninthe1980s,withaboutaquarterconsistingof

highschooldropouts.Thesamplesizeproblem,however,becomesparticularlyacutewith

the1991survey,whenthenumberofnon-HispanicmensampledinMiamifallsabruptly

(byalmostathird),andthenumberofhighschooldropoutsdropstothesingledigits.This

changeinsamplesizesuggeststhattheevidenceisprobablymostcrediblewhenwe

examineoutcomesduringthefirstdecadeafterMariel.

Nevertheless,itisinstructivetostartbyreportingtheevidencefromthemost

straightforwardcalculationofthepotentialwageimpactthatusesalltheavailabledata.It

turnsoutthateventhemostcursoryexaminationofthewagetrendsrevealsaremarkable

patternthatimmediatelyoverturnstheconventionalwisdomaboutMariel:Something

indeeddidhappentothewagestructureinMiamiafter1980.Itseems,infact,asifthe

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Marielitosmayhavehadalargeandadversewageimpactonthewageofcomparable

Miamiansafterall.

Toeasilyillustratethekeyfindingofthispaper,Isimplycalculatetheaveragelog

weeklywageofhighschooldropoutsinMiamieachyearbetween1972and2003,the

periodforwhichtheMarchCPShasaconsistenttimeseriesfortheMiamimetropolitan

area.Figure2illustratesthewagetrend,usinga3-yearmovingaveragetosmoothoutthe

noiseinthetimeseries.Thefigurealsoillustratesthetrendforsimilarlyeducatednon-

HispanicmenworkingoutsideMiami.Itisimportanttoemphasizethatthissimpleexercise

doesnotadjusttheCPSdatainanywaywhatsoever(otherthantakingamovingaverage),

sothatitprovidesaverytransparentindicationofwhathappenedtowagesinMiamipre-

andpost-Mariel.

ItisobviousthatdespitethesimilarityinwagetrendsbetweenMiamiandtherest

oftheUnitedStatespriorto1980,somethinghappenedin1980thatcausedthetwowage

seriestodiverge.BeforeMariel,thelogwageofhighschooldropoutsinMiamiwas0.10log

pointsbelowthatofworkersintherestofthecountry.By1985,thegaphadwidenedto

0.42logpoints,implyingthatwhatevercausedthedivergencehadloweredtherelative

wageoflow-skillworkersinMiamibyaround30percent.Notethatthelow-skillwagein

Miamifullyrecoveredby1990,onlytobe“hammered”againin1995,coincidentallythe

timeoftheLittleMarielsupplyshock.By2002,thewagegapbetweenhighschooldropouts

inMiamiandelsewherehadreturnedtoitspre-Marielnormalofaround0.11logpoints.

Ofcourse,thedistinctivewagetrendinMiamimaynotappearquiteasdistinctive

whencontrastedwithwhathappenedinotherspecificcities.ThecomparisonofMiamito

anaggregateoftheU.S.labormarketmaybemaskingalotofthevariationthatinfluences

particularplacesandthatdisappearswhenaveragedout.Itis,therefore,importantto

createacontrolgroupofcomparablecitiesunaffectedbytheMarielsupplyshockto

determineifthewagetrendsevidentinMiamiwereduetomacroeconomicfactorsthat

affectedothersimilarcommunitiesaswell.Beginningwiththe1977survey,theMarchCPS

dataidentifies43metropolitanareasthatcanbecombinedinsomefashiontoconstructa

sortofplacebo.Card(1980,p.249;emphasisadded)describestheconstructionofhis

controlgroupasfollows:

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Forcomparativepurposes,Ihaveassembledsimilardata…infourothercities:Atlanta,LosAngeles,Houston,andTampa-St.Petersburg.ThesefourcitieswereselectedbothbecausetheyhadrelativelylargepopulationsofblacksandHispanicsandbecausetheyexhibitedapatternofeconomicgrowthsimilartothatinMiamioverthelate1970sandearly1980s.Acomparisonofemploymentgrowthrates…suggeststhateconomicconditionswereverysimilarinMiamiandtheaverageofthefourcomparisoncitiesbetween1976and1984.

ItisimportanttoemphasizethatthefourcitiesintheCardplacebowerechosen

partlybasedonemploymenttrendsobservedaftertheMarielsupplyshock.Putdifferently,

ifMarielworsenedemploymentconditionsinMiami,theCardplaceboiscomparingthe

pooreroutcomesofworkersinMiamitotheoutcomesofworkersincitieswheresome

otherfactorworsenedtheiropportunitiesaswell.Itisobviouslyfarpreferableto

exogenizethechoiceofaplacebobycomparingcitiesthatwereroughlysimilarpriortothe

treatment,ratherthanbeingsimilarafteroneofthemwas“injected”withaverylarge

supplyshock.

ThevariouspanelsofFigure3illustratethewagetrendsinMiamiandseveral

potentialplacebosbetween1976and1992.Thetoppanelshowsthatthelogwageofhigh

schooldropoutsdeclineddramaticallyafter1980whencomparedtowhathappenedinthe

citiesthatmakeuptheCardplacebo.Ofcourse,trendsinabsolutewagesreflectmany

factorsthatarespecifictolocallabormarkets,sothatitispossiblethattheseupsand

downscaptureidiosyncraticshiftsthataffectedallworkersinMiami.TheMarielsupply

shock,however,specificallytargetedtheleasteducatedworkersandthebottomtwo

panelsofthefigureshowthattherelativewageofhighschooldropoutsinMiami—relative

toeithercollegegraduatesorhighschoolgraduates—alsodeclineddramaticallyafter

Mariel,andalsorecoveredby1990.15Insum,thewagetrendsobservedinMiami—relative

tothoseseeninthecitiesthatmakeuptheCardplacebo—consistentlyindicatethatthe

15ThetimeseriesofthewageofhighschooldropoutsinMiamirelativetohighschoolgraduateshas

adataquirkthatisworthnoting:HighschooldropoutsearnedslightlymorethanhighschoolgraduatespriortoMariel.ThisanomalyarisesbecausetheaveragewageofhighschoolgraduatessampledbytheCPSinMiamiin1979isunusuallylow,andthisdataanomalycarriesovertoneighboringyearsbecauseofthemovingaveragecalculation.Allthefindingsinthispaperareinvarianttodroppingthe1979observation.Thefigurealsoshowsthatthewageofhighschooldropoutsagainexceedsthatofhighschoolgraduatesafter1990.Asnotedearlier,however,thereisaprecipitousdropinthenumberofhighschooldropoutssampledinMiamiafter1990.

13

economicwell-beingoftheleasteducatedworkersinMiamitookadownwardturnshortly

after1980,reacheditsnadiraround1985-1986,anddidnotrecoverfullyuntil1990.

Asnotedabove,thecitiesintheCardplacebodonotmakeupapropercontrol

groupbecausetheywerechosen,inpart,sothatpost-Marielemploymentconditionsinthe

placebocitiesresembledthoseinMiami.Todeterminethesetofcitiesthathadcomparable

employmentgrowthpriortoMariel,Ipooledthe1977and1978cross-sectionsoftheCPS,

andalsopooledthe1979and1980cross-sections.16Notethatthe1980CPSdata,collected

inMarch,isnotaffectedbythesupplyshock,astheMarielitosdidnotbegintoarriveuntil

lateApril.Ithenusedthetwopooledcross-sectionstocalculatethelogoftheratioofthe

totalnumberofworkersin1979-1980tothenumberofworkersin1977-1978.Column1

ofTable3reportstheemploymentgrowthrateforeachofthe44metropolitanareas,

rankedbythegrowthrate.

ItisevidentthatMiami’spre-Marielemploymentconditionswerequiterobust,

ranking6thintherateofemploymentgrowth.NotethatallthecitiesthatmakeuptheCard

placebohadlowergrowthratesthanMiamibetween1977and1980.Infact,theaverage

employmentgrowthrateinthosefourcities(weightedbyaverageemployment)was6.9

percent,lessthanhalfthe15.3percentgrowthrateinMiami.

IusetherankingsreportedinTable3toconstructanewplacebo,whichIcallthe

“employmentplacebo,”bysimplychoosingthefourcitiesthatweremostsimilartoMiami

priorto1980.Specifically,theemploymentplaceboconsistsofthefourcities(Anaheim,

Rochester,Nassau-Suffolk,andSanJose)rankedjustaboveandjustbelowMiami.

Figure3clearlyshowsthattherelativedeclineinthewageoflow-educatedworkers

inMiamiismuchlargerwhenwecompareMiamitocitiesthathadcomparable

employmentgrowththantothecitiesthatmakeuptheCardplacebo.Between1979and

1985,forinstance,thewageofhighschooldropoutsinMiamirelativetotheCardplacebo

fellbyabout0.28logpoints(or24percent),butthedeclinewasabout0.48logpoints(38

percent)whencomparedtothecitiesintheemploymentplacebo.Thisdifference,ofcourse,

isnotsurprising.Thecomparisonofpost-MarieleconomicconditionsinMiamitothatof

16Theseyearsrefertothesurveyyearsandnotthecalendaryearswhereearningsareobserved.A

personisemployedifheorsheworksintheCPSreferenceweek.

14

citieswhereemploymentconditionsarealsopoorbyconstructioninevitablyhidessomeof

theimpactoftheMarielitos.

Inshort,thechoiceofaplaceboplaysacrucialroleindeterminingthewageimpact

ofMariel.Thefactthatthereare43metropolitanareasfromwhichtoselecta4-citycontrol

group(anumberthatisitselfarbitrary)impliesthatthereareatotalof123,410potential

placebos.Inviewoftheverylargenumberofchoices,itmightbereasonabletoexpecta

hugedispersionintheestimatedwageeffectoftheMarielitosacrossthe123,410potential

comparisonsthatcanbemade.Iwillreportbelowthedistributionofestimatedwage

impactsacrossallpotentialfour-cityplacebosandshowthatthewageimpactofMarielis

significantlylargerwhentheplacebocontainscitiesthatbetterresembledMiami’s

economicconditionsbefore1980.

Analternativewayofchoosingaplaceboistoemploythe“syntheticcontrol”

statisticalmethoddevelopedbyAbadie,Diamond,andHainmueller(2010).Themethod

essentially“searches”acrossallpotentialplacebocitiesandderivesaweightthataverages

citiestocreateanewsyntheticcity.Thissyntheticcityistheonethatbestresemblesthe

pre-MarielMiamilabormarket.Thesyntheticcontrolapproachhastwobeneficial

properties.First,itprecludestheresearcherfrommakingarbitrarydecisionsaboutwhat

theproperplaceboshouldbe.Second,theweightsattachedtothepotentialplacebocities

canbebasedonseveraleconomiccharacteristics.17

Idefineda“syntheticplacebo”byusingthreesuchcharacteristics:therateof

employmentgrowthinthe4-yearperiodpriortoMariel(i.e.,thevariableusedtodefinethe

employmentplacebo);theconcurrentrateofemploymentgrowthforhighschool

dropouts;andtheconcurrentrateofwagegrowthforhighschooldropouts.Thelasttwo

columnsofTable3reporttheseadditionalcharacteristics,showingthatMiamialsohada

robustlow-skilllabormarketpriortoMariel.Miamirankedsixthinthegrowthoflow-skill

employmentand13thintherateofwagegrowth.

Figure3alsoillustratesthewagetrendsinthe“city”thatmakesupthesynthetic

placebo.Aswillbeseenthroughoutthepaper,sometimesthetrendsfromthesynthetic

17Thesyntheticcontrolmethodstillrequirestheresearchertospecifythevectorofvariables(in

additiontothelabormarketoutcomeofinterest)thatshouldbesimilarbetweenMiamiandthesyntheticcityinthepre-treatmentperiod.

15

placeboresemblethosefromtheCardplacebo;sometimestheyresemblethosefromthe

employmentplacebo,andsometimestheyresembleneither.Muchdependsonthelabor

marketcharacteristicbeingexamined.

Itisinterestingtoexaminetheweightsimpliedbythesyntheticcontrolmethod(see

AppendixTableA-1foralisting).Whenthelabormarketinterestofoutcomeisthelog

wageofhighschooldropouts,thesyntheticcontrolmethodassignsthelargestweightsto

KansasCity(withaweightof0.56),Anaheim(0.27),Sacramento(0.041),andSanDiego

(0.013).Theappendixtablealsoreportstheweightsassignedbythesyntheticcontrol

methodintheregressionanalysisreportedbelow.Themetropolitanareaswiththelargest

weightsareAnaheim(0.372),SanDiego(0.239),Rochester(0.159),andSanJose(0.043).

BylookingattherankingofallthesecitiesinTable3,itisobviousthatthesyntheticcontrol

methodconsistentlyselectsmetropolitanareasthathadrobustlabormarketspriorto

Mariel(generatingsomeoverlapbetweenthecitiesthatmakeupthesyntheticcontroland

thecitiesintheemploymentplacebo).Figure3documentsthatacomparisonofwage

trendsbetweenMiamiandthesyntheticplaceboagainsuggeststhattheMiamiexperience

wasunique.

ThewagecomparisonsbetweenMiamiandthevariousplacebos,however,donot

precludethepossibilitythatothercitiesinothertimeperiodshaveexperiencedequally

steepwagecuts.Perhapstherearemanydocumentedcasesofsimilartransitoryand

numericallylargewagereductionsinothercitiesthatareattributabletosamplingerroror

tofactorsthathavenothingtodowithMariel.

Itiseasytoestablishthatthesteepdropinthelow-skillwageinpost-MarielMiami

wasaveryunusualevent.Theaveragewageofhigh-schooldropoutsinMiamifellby

around35percentbetween1976-1979and1981-1986.Wecancalculatethecomparable

wagechangeineveryothermetropolitanareaforallequivalenttimeperiodsbetween

1976and2003andseeiftheMiamiexperienceatthetimeofMarielstandsout.18

Obviously,if35-percentwagecutshappenfrequently,itwouldbehardertoclaimthat

18Garthwaite,Gross,andNotowidigdo(2014)conductasimilarexercisetoexaminethedistributionoftheimpactofanexperimentinhealthinsuranceavailabilityonemploymentlock.NotethatIextendthesampleperiodthrough2003todeterminehowthesteepwagedropobservedamonglow-skillMiamiansintheearly1980scomparestotheexperienceofcomparableworkersinallothermetropolitanareasoveratwo-decadeperiod.

16

Miami’sexperiencehadmuchtodowiththeMarielitos.Perhapssomethingelsewasgoing

on—a“somethingelse”thatoccursfrequentlyenoughinlocallabormarkets—thatjust

happenedtocoincidewiththetimingofCastro’sdecision.

ToassesshowMiami’spost-Marielexperiencecomparestothatoftheentire

distributionofwagechanges,Icalculatedthewagechangebetweeneverysingle“pre-

treatment”periodτ(1976-1979,1977-1980,…,1993-1996)andthecorresponding“post-

treatment”periodτ′(1981-1986,1982-1987,…,1998-2003).Notethattoreplicatethe

Marielexperiment,Iskipayearbetweenthe4-yearpre-treatmentspanandthe6-year

post-treatmentspan.Iconductedthiscalculationforeachmetropolitanarea,leadingtoa

totalof774possible“events”outsideMiami(43metropolitanareasand18potential

treatmentyearsbetween1980and1997).Ialsocalculatedthechangeinthelogwageof

theothereducationgroupsforallcity-yearpermutations.

ThetoppanelofFigure4illustratesthefrequencydistributionofallobserved

changesinthewageofhighschooldropoutsoutsideMiami.Table4reportssummary

statisticsfromthevariousdistributionscreatedbythisempiricalexercise.

Between1977-1979and1981-1986,thelogwageofhighschooldropoutsinMiami

fellby0.439logpoints(or35.5percent).ItisvisuallyobviousfromFigure4thatsucha

largewagedropwasanunusualevent.Themeanobservedwagechangeacrossallcity-

yearpermutationswasonlyabout-0.10logpoints.TheMarielexperienceranksinthe1.8th

percentileofthedistributionofallobservedwagechangesbetween1976and2003across

allmetropolitanareas.Similarly,thefrequencydistributionofobservedwagechangesfor

highschooldropoutsinthe1980treatmentyearshowsthatthewagedropobservedin

Miamiwasthelargestwagedropobservedamongallmetropolitanareas.

Equallyimportant,thisexerciserevealsthatmoreeducatedworkersinMiamidid

notexperienceasubstantialwagedecline(seethebottompanelofFigure4).Although

therehavebeenrecentclaimsthatperhapshighschooldropoutsandhighschoolgraduates

areperfectsubstitutesandshouldbepooledtoformthe“lowskill”workforce(moreon

thisinthenextsection),thedataclearlycontradictsthisconjecture.Themeanwagechange

inthelogwageofhighschoolgraduatesacrossallcity-yearpermutationsintheyears1977

through2001was-0.061,andMiami’sMarielexperiencerankedinthe66thpercentile.The

17

valueobservedintheMiamimetropolitanareaatthetimeofMarielwas-0.021,ranking

42ndoutofthe44metropolitanareasinthedistributionfortreatmentyear1980.

Inshort,somethinguniquehappenedtotheeconomicwellbeingofhighschool

dropoutsinMiamiintheearly1980s,butnottohighschoolgraduatesortoworkerswith

evenmoreeducation.TheeventthatshockedthewagestructureinMiamiatthetimeof

Mariel,whateverithappenedtobe,happensrarelyanditsadverseconsequenceswere

targetedverynarrowlyonworkerswholackedahighschooldiploma.

IV. Robustness of the Descriptive Evidence

Giventhestrikingpicturethattherawdatagivesaboutthelabormarketimpactof

theMarielitos,andgiventheverycontentiousdebateoverimmigrationpolicybothinthe

UnitedStatesandabroad,itisimportanttoestablishthattheevidencepresentedinthe

previoussectionisrobust.

Thissectionaddressesseveraldistinctquestionstoevaluatethesensitivityofthe

results.Forexample,wasthedeclineinthewageofhighschooldropoutsintheMiamiof

theearly1980srecordedbyothercontemporaneousdatasets,suchastheCPSOutgoing

RotationGroups(ORG)?Afterall,thetrendsinwageinequalityobservedintheORG

sometimesdiffermarkedlyfromthoseobservedintheMarchCPS.

Similarly,istheevidencerobusttoalternativedefinitionsofthelow-skill

workforce?Thedescriptiveanalysis,motivatedbytheeducationdistributionofthe

Marielitos,usedthesampleofhighschooldropoutstodefinethelow-skillworkforce.Are

thewagetrendssimilarifwedefinedalow-skillworkerdifferentlyorifweexaminedthe

shapeofMiami’swagedistribution?

1.ResultsfromtheCPS-ORG

Itiswellknown(Autor,Katz,andKearney,2008;Lemieux,2006)thatwagetrends

recordedbytheMarchCPSsometimesdifferfromthe“comparable”wagetrendsrecorded

bytheCPSOutgoingRotationGroups.UnliketheMarchCPS,whichmeasuresannual

earningsinthecalendaryearpriortothesurvey,theORGgivesameasureofthehourly

wageforrespondentswhoarepaidbythehourandoftheusualweeklywageforallother

18

workers.TheORGtimeseriesbeginsin1979,sothatthepre-treatmentperiodonly

containsoneyearofdata.FollowingAutor,Katz,andKearney(2008),Iextendthepre-

treatmentperiodbyusingtheroughlycomparable(thoughsmaller)MayCPSsupplements

for1977and1978. 19

ItisimportanttoemphasizethatthedifferencesinwagetrendsbetweentheMarch

CPSandtheORGarisepartlybecausethetwosurveysmeasuredifferentconceptsof

income.TheMarchCPSreportstotalearningsfromalljobsheldinthepreviouscalendar

year.TheORGmeasuresthewageinthemainjobheldbyapersonintheweekpriortothe

survey(ifworking).TheORGdoesnotprovideanyearningsinformationforpersonswho

happennottobeworkingonthatparticularweek,whereastheMarchCPSwouldcapture

theearningslossesassociatedwithjoblessperiods.Fromtheperspectiveofdetermining

thelabormarketimpactoftheMarielsupplyshock,itwouldseemthatthemore

encompassingmeasureoflabormarketoutcomesintheMarchCPSisfarpreferable.

Beforeproceedingtoexaminethepotentialdisparitiesinwagetrendsacrossthe

twosurveys,itisconvenienttofirstadjustthedatafordifferencesintheagedistributionof

workersindifferenttimeperiodsandindifferentmetropolitanareas.Tomaketheanalysis

transparent,Iusedasimpleregressionmodeltocalculatetheage-adjustedmeanwageofa

skillgroupinaparticularmarket.Specifically,Iestimatedthefollowingindividual-level

earningsregressionseparatelyineachCPScross-section:20

(1) logwirst=θr+Aiγt+ε,

wherewirstistheweeklywageofworkeriincityrineducationgroupsattimet;θrisa

vectoroffixedeffectsindicatingcityofresidence;andAiisavectoroffixedeffectsgiving

19Iusethe1979-2001ORGfilesarchivedattheNationalBureauofEconomicResearch.Becausethe

Maysupplementsbefore1977providelimitedinformationonmetropolitanareaofresidence,thewageseriesintheORGbeginsin1977whilethecomparableseriesintheMarchCPSbeginsin1976.ThewagemeasureusedintheORGanalysisistherecodedusualearningsperweek(earnwke).

20Ofcourse,theregressionsareestimatedseparatelyintheMarchCPSandtheORG.

19

theworker’sage.21Thefixedeffectsθrdeflatethelogweeklywageforregionalwage

differences.Theaverageresidualfromthisregressionforcell(r,s,t)givestheage-adjusted

meanwageofthatcell.Unlessotherwisespecified,Iuseage-adjustedwagesforthe

remainderofthepaper.22

Figure5illustratesthewagetrendscalculatedintheORGdataforMiamiandfor

thethreeplacebosdefinedintheprevioussection.23Itisagainvisuallyevidentthat

somethinghappenedtothelow-skilllabormarketinMiamiintheearly1980s,particularly

whentheMiamitrendiscomparedtoeithertheemploymentorsyntheticplacebos.The

useoftheCardplacebointheORGdataoftenmasksmuchofwhatwentoninpost-Mariel

Miami.

Forexample,thewageofhighschooldropoutsinMiamifellby0.22logpoints

between1979and1985.Figure5indicatesthatthecomparablewagefellby0.17log

pointsintheCardplacebo,andby-0.10logpointsineithertheemploymentorsynthetic

placebos.TheuseoftheCardplacebowouldimplythatMarielloweredthewageofhigh

schooldropoutsinMiamibyonlyabout5percent,whileboththeemploymentand

syntheticplaceboswouldimplyanimpactofaround12percent.Evenmoresothanthe

MarchCPSdata,theORGshowsthecrucialrolethatthechoiceofaplaceboplaysinany

measurementofthewageimpactoftheMarielitos.

2.Othermeasuresofskills

Somerecentstudiescontendthatmuchofthewageimpactofimmigration

disappearswhenthelow-skillgroupisdefinedinanalternativeway.Card(2009),for

example,arguesthathighschooldropoutsandhighschoolgraduatesareperfect

substitutes.24Thepoolingofthesetwogroupsintoaverylargelow-skillworkforce

21Iusedsevenagegroupstocreatethefixedeffects(25-29,30-34,35-39,40-44,45-49,50-54,and

55-59).

22Itisworthnotingthatthewagetrendsintheage-adjusteddataimpliedbytheMarchCPSlookalmostidenticaltotherawtrendsdocumentedinFigure2.

23ThelastcolumnofAppendixTableA-1showstheweightsattachedtothedifferentmetropolitanareasbythesyntheticplacebomethodintheORGdata.ThelargestweightswereattachedtoAnaheim(0.396),SanDiego(0.234),andRochester(0.164).

24SeealsoOttavianoandPeri(2012)andManacordaandManning(2012).

20

inevitablydilutesthedisparateimpactoflow-skillimmigrationontheleastskilledworkers,

andhelpsto“buildin”aconclusionthatrecentimmigrationcouldnothavehadmuchofan

impactonthewagestructure(Borjas,Freeman,andKatz,1997).

Puttingasidewhetherthetwogroupsareorarenotperfectsubstitutesforthe

moment,itisnonethelessimportanttoascertainiftheevidencethatMarielseemstohave

hadasubstantialwageimpactdisappearswhensuchanaggregationisconducted.Before

proceeding,however,itisworthemphasizingthattherawdatainFigure4indicatedthat

whilethewageofhighschooldropoutsinMiamifelldramaticallyafterMariel,thewageof

highschoolgraduatesdidnot(infact,itroserelativetowhathappenedelsewhere).The

twoeducationgroupswerealmostequallysizedinpre-MarielMiami,sothatthe

aggregationwillagaininevitablydilutetheimpactofMarielontheleast-educatedworkers.

Figure6usestheMarchCPSdatatoillustratethebasictrendsinthelogweekly

wageofthepooledgroupofhighschooldropoutsandhighschoolgraduates.Despitethe

factthattheaggregationattenuatessomeofthewageeffect,thefigureagainshowsa

differencebetweenwhathappenedtothisaggregatedlow-skillworkforceinMiamiand

elsewhere.Forexample,thewageofthepooledgroupofhighschooldropoutsand

graduatesfellby12percentinMiamiintheearly1980s,butbyonly5percentinthecities

thatmakeuptheemploymentplaceboand7percentinthesyntheticplacebo.

Itisimportanttonotethattheobservedwagetrendsrejecttheconjecturethatthe

twoeducationgroupsshouldbepooled.IfwestartwithanestedCESproductionfunction

andifwealsoassumethatwagesareequaltothevalueofmarginalproduct,itiswell

knownthattheelasticityofsubstitutionbetweenhighschooldropouts(group1)andhigh

schoolgraduates(group2)canbeestimatedbytheregression:

(2) log

w1

w2

⎛⎝⎜

⎞⎠⎟= λ− 1

σlog

L1

L2

⎛⎝⎜

⎞⎠⎟

,

wherewiisthewageofgroupi;Ligivesthenumberofworkersinthatgroup;andσisthe

elasticityofsubstitution.Thetypicalstudyexploitsvariationinfactorpricesandfactor

21

quantitiesacrossregionsorovertime(orboth)toestimateσ.Theinterceptλisafunction

oftechnologicalparameters,andneednotbeeitherregion-ortime-invariant.

Thevisualevidence(aswellastheregressionevidencepresentedinsubsequent

sections)suggeststhatthereislittleneedtotakethe“detour”ofestimatingequation(2)to

determineifhighschooldropoutsandhighschoolgraduatesareperfectsubstitutes.Ifwe

taketheCESframeworkseriously,equation(2)impliesthatthewageratioofthetwo

groupswillbeuncorrelatedwiththequantityratioonlyifσequalsinfinity.However,the

dataconsistentlyindicatesthatthewageofhighschooldropoutsinMiamirelativetothat

ofhighschoolgraduatesfelldramaticallyaftertheMarielsupplyshock.Thisdropinthe

relativewageofhighschooldropoutsisobviouslyinconsistentwiththehypothesisthatthe

twogroupsareperfectsubstitutes.Infact,aswehaveseenandwillseeagainbelow,the

impactofMarielonthewageofhighschooldropoutsisconsistentlynegative,whilethe

impactonhighschoolgraduatesismostlypositive.

The“experimental”wayofshowingthatthetwogroupsarenotproductiveclonesis

farmoreconvincingthanthetypicalregressionapproachusedtoestimateσ.Itiswell

knownthattherelativedemandforlow-skilllaborfellinrecentdecades,sothatthe

interceptλinequation(2)isnotconstantovertime.Weobviouslydonotknowhowtonet

outthisdemandshiftinatime-seriesdataset(suchastheonethatcouldbeconstructed

fromtheCPS),sothatassumptionsmustbemadeabouttheshapeoftheunobservedtrend

inrelativedemand.25Borjas,Grogger,andHanson(2012)showthatestimatesoftheslope

coefficientinequation(2)areextremelysensitivetotheseextraneousassumptions.The

estimateofσcanbemadepositive,zero,orevennegativebyassumingdifferentfunctional

formsfortheunobservedtrend,regardlessofwhethertheunderlyingwagedataareatime

25SeeKatzandMurphy(1992)andAutor,Katz,andKearney(2008).GoldinandKatz(2010)argue

thatthe“preferred”specificationfortheregressionmodelshouldincludealineartrendaswellasapost-1992splinetoaccountfortheseunobservedshiftsintherelativedemandofhighschooldropoutsandhighschoolgraduates.Ifone“buysinto”thesefunctionalformassumptions,theestimateof(-1/σ)usingtheGoldin-KatzannualCPSdatafrom1963through2005is-0.135(withastandarderrorof0.027),rejectingthehypothesisthatthetwogroupsareperfectsubstitutes(seeBorjas,Grogger,andHanson,2012).

22

seriesorexploitgeographicvariation.26TheMarielevidencethatsuggeststhetwogroups

arenotperfectsubstitutesisnotvulnerabletothiscriticism.

Finally,itisinstructivetoshowthatthewageofMiami’smostdisadvantaged

workersbehaveddifferentlyintheearly1980sevenifwedispensecompletelywiththeuse

ofeducationalattainmenttodefinethelow-skillworkforce.ItturnsoutthatMiamialso

experiencedawideningofitswagedistributionatthetime.Themosttransparentwayof

documentingthiswideningisbyexaminingwhathappenedtothespreadofthe

distributionoflogweeklyearningsinthevariouscities.

Figure7usestheMarchCPStoillustratethetrendinboththewageoftheworkerat

the20thpercentileaswellastheinterquantilerange,whichIdefineasthedifferenceinthe

logweeklywagebetweentheworkeratthe20thpercentileandtheworkeratthe80th

percentile.Thetrendsarevisuallystriking.Itisevidentthattheeconomicwellbeingof

Miamiansinthebottomtailofthewagedistributiontookabeatingpost-Mariel.Muchof

thedeclineseemedtooccurinthefirstfewyearsafterMariel,atwhichpointboththe

absoluteandrelativepositionoflow-skillworkersbegantorecover.

3.Implicationsfortheblack-whitewagegap

JustdayspriortotheMarielsupplyshock,the1980censusreportedthat25.2

percentofMiami’s(male)workforcewasAfrican-American.Therewas,however,asizable

disparityintheblackshareamongeducationgroups;itwas42.5percentforhighschool

dropouts,butonly6.0percentforcollegegraduates.Thisimbalanceintheskill

distributionsofblackandwhiteworkersinpre-MarielMiamisuggeststhatalargesupply

shockoflow-skillimmigrantswouldlikelyhaveadisproportionatelylargereffectonthe

blackworkforce,andcouldwidentheaveragewagegapbetweenblackandwhiteworkers.

TheimpactofMarielonMiami’sblackworkforceisofparticularinterestbecause

racialriotsravagedpartsofthecitywithinamonthaftertheMarielboatliftbegan,leaving

18deadand400injured.Theconditionsonthegroundwerevolatile,andtheriotswere

26Thetypicalregressionapproachalsofacesaseriousconceptualdifficulty:Whatexactlyisthe

exogenousforcethatgenerateschangesinrelativequantitiesthatsomehowcausechangesinrelativewages?Despitetheclassicsupply-demandendogeneityproblemwiththisregressionframework,theissuehasbeenalmostuniversallyignoredintheliterature.

23

theconsequenceofalonglistofaccumulatedgrievances,particularlytheacquittaloffour

whitepoliceofficerschargedwithmanslaughterwhenanAfrican-Americanmandiedafter

ahigh-speedchase.But,notably,oneofthegrievancescitedbyahistoryofthoseriotswas

“thedisplacementofblacksbyCubansfromjobsandotheropportunities”(Vogeland

Stowers,1991,p.120).

Figure8illustratesthetrendintheblack-whitewagegapinMiamiandtheplacebos

usingboththeMarchCPSandtheORGfiles.Itisobviousthattherelativeblackwage

declinedsharplyafterMariel.27TheMarchCPSdata,forexample,indicatesthattheblack

relativewageinMiamifellbyalmost20percentagepointsbetween1979and1985,

showingaverydifferenttrendthanwhatoccurredelsewhere.

ItisinterestingtonotethattheoriginalCardstudy,whichusedtheORGfiles,

suggeststhepossibilitythattheAfrican-AmericanworkforceinMiamiwasparticularly

affectedbytheMarielsupplyshock.Card(1990,Table3,p.250)reportsthattheblack

wageinMiamifellby11percentagepointsbetween1979and1983,ascomparedtoadrop

ofonly5percentagepointsinthecomparisoncities.Thissuggestiveevidence,however,

wasdismissed:“ThedatadosuggestarelativedownturninblackwagesinMiamiduring

1982-83.Itseemslikely,however,thatthisdownturnreflectsanunusuallyseverecyclical

effectassociatedwiththe1982-83recession.”Figure7showsthatthedownturninblack

wageswasnotatransitorycyclicaldeviation.Infact,thebottompanelofthefigureshows

thattheORGdatawouldhaverevealedacontinuingdeclineintheeconomicfortunesof

Miami’sblackworkershadtheCardstudyexaminedthedatabeyonditsstoppingpointof

mid-1985.

Inshort,itseemsasiftheimpactoftheMarielitosonrelativewagesacross

educationgroupssubstantiallyworsenedtherelativeeconomicstatusofthetypical

African-AmericaninMiamirelativetohiscounterpartintheplacebocities.This

disproportionateimpactoflow-skillimmigrationontheAfrican-Americanworkforceis

consistentwiththeevidencereportedinBorjas,Grogger,andHanson(2010).

27Thecalculationofthesyntheticplacebowasnotconductedfortheblack-whitewagegapintheMarchCPSbecausethemethodologyrequiresaperfectlybalancedpanelovertherelevantsampleperiod.Unfortunately,therewereover10city-yearpermutationsinthedatathatdidnotsampleanyblackworkers.Therewereonly3city-yearpermutationswithoutblackworkersintheORG(andtheywereallin1977or1978).Iusedadjacent-yeardatatoimputethemissinginformationfortheORG.

24

ItwouldbeofgreatinteresttoalsoexaminetherelativetrendsinHispanicwages,

butthenatureoftheavailabledatawouldmakethatcomparisonuninformative.A

replicationoftheanalysisillustratedinFigure8fortheHispanicpopulation(notshownfor

thesakeofbrevity)wouldshowsteadywagedeclinesforHispanicworkersthroughoutthe

entireperiodinMiamiandinthevariousplacebos.The1980sand1990swereaperiodof

substantialHispanicimmigrationintomanyareasofthecountry,andthatinfluxincluded

millionsofundocumentedimmigrantswhoarealsodisproportionatelylikelytobehigh

schooldropouts.Manyoftheplacebocitiesalsoreceivedlargenumbersoflow-skill

Hispanicimmigrants,dilutingtheireffectivenessasacontrolgroup.Moreover,theCPSdata

doesnotallowustocreateasampleof“pre-existing”Hispanicworkers,sothatthe

observedtrendintheHispanicwageislargelyreflectingthechangingcompositionofthe

Hispanicworkforceduetothepersistentinflowoflargenumbersofimmigrants.

V. Regression Results Toestimatethepost-treatmenteffectoftheMarielsupplyshockrelativetothe

variousplacebos,Iusethemeanage-adjustedwageofhighschooldropoutsincityrattime

t,denotedby logwrt .Thiswagebecomesthedependentvariableinatraditionaldifference-

in-differencesregressionmodel:

(3) logwrt = θr + θt +β(Miami× Post-Mariel)+ ε,

whereθrisavectorofcityfixedeffects;θtisavectorofyearfixedeffects;“Miami”

obviouslyrepresentsadummyvariableindicatingtheMiami-Hialeahmetropolitanarea;

and“Post-Mariel”indicatesiftimetoccursafter1980.

Theregressionusesannualobservationsbetweent=1977andt=1992,butexcludes

1980,theyearofthesupplyshock.28ThecitiesrincludedintheregressionareMiamiand

thecitiesinaspecificplacebo.Forexample,iftheMiamiexperienceisbeingcomparedto

thatofcitiesintheemploymentplacebo,therewouldbefivecitiesinthedata,andeachof

28ThistimespanallowsmetoestimatetheidenticalregressionmodelinboththeMarchCPSandORGsamples.

25

thesecitieswouldbeobserved15timesbetween1977and1992,foratotalof75

observations.TheregressioncomparingMiamitothesyntheticplaceboissimilarinspirit,

butthereareonlytwo“cities”inthisregression:Miamiandthesyntheticcity,foratotalof

30observations.

ToallowthewageimpactofMarieltovaryovertime,the“post-Mariel”variablein

equation(3)isavectoroffixedeffectsindicatingwhethertheobservationrefersto1981-

1983,1984-1986,1987-1989,or1990-1992.Table5reportstheestimatedcoefficientsin

thevectorβforvariousspecificationsoftheregressionmodelusingtheMarchCPSdata.

Thetablealsoreportsrobuststandarderrorsthatcorrectforheteroscedasticity.Itislikely

thatthereisserialcorrelationinoutcomesatthecitylevelthatwouldrequirefurther

adjustmentsforvalidstatisticalinference,butitiswellknown(CameronandMiller,2015)

thatclusteredstandarderrorsaredownwardbiasedwhentherearefewclustersinthe

data.

ConsiderinitiallytheregressionsreportedinPanelAofthetable,wherethe

dependentvariableistheage-adjustedlogweeklywageofhighschooldropoutsincityrat

timet.Thevariouscolumnsofthetableusealternativeplacebos:theCardplacebo,the

employmentplacebo,thesyntheticplacebo,aswellasanaggregateplacebocomposedof

allother43metropolitanareas.Thevariousrowsreportthecoefficientsinthevector

β indicatinghowthewageimpactvariesduringthepost-Marielperiod.Thetrendinthese

coefficientspresumablycapturesthewageeffectastheMiamilabormarketadjusts,and

movesfromthe“short”tothe“long”run.

ItisevidentthatthecoefficientβestimatedimmediatelyafterMarielisnegative,

indicatinganabsolutedeclineinthewageoflow-skillworkersintheaftermathofthe

supplyshock.However,theeffectismuchsmallerwhenIusetheCardplacebothanwhenI

useeithertheemploymentorsyntheticplacebo.Theimmediatewagecutusingtheoriginal

Cardplacebois-0.137(0.093),whilethewagecutimpliedbytheemploymentplacebois

twiceaslarge,withapointestimateof-0.289(0.090),andthewagecutimpliedbythe

syntheticplacebois-0.210(0.086).Itseems,therefore,thatthewageofhighschool

dropoutsinMiamifellby20to25percentintheimmediateshortrun(1981-1983).

Remarkably,thiswageeffectincreasesinthenextthreeyears,sothatthewageforhigh

26

schooldropoutsfellby40percentwithin5years(usingeithertheemploymentor

syntheticplacebos).Thewageeffectthenbeginstoweaken,andessentiallydisappearsby

the1990-1992period,whenthecoefficientinthesyntheticplaceboregressionis0.021

(0.096).

PanelsBandCofthetablereplicatetheanalysisusingthetwoalternativemeasures

ofrelativewages.Bothpanelssuggestthattherelativewageoftheleasteducatedworkers

typicallyfellimmediatelyafterthesupplyshock,withthewageofhighschooldropouts

fallingbyasmuchas30percentrelativetohighschoolgraduates.Aswiththeabsolute

wageresults,therelativewageeffectalsodisappearsbytheearly1990s.

Table6reportsthecoefficientsfromcomparableregressionsusingtheORGdata.

TheimmediateeffectonthewageofhighschooldropoutsimpliedbytheORGisroughly

similartothatimpliedbytheMarchCPSwhenIuseeithertheemploymentplaceboorthe

syntheticplacebo.Thelogwageofhighschooldropoutsfellby20to25percentinthe

MarchCPSdataandby15to20percentintheORG.Thereisoneinterestingdifferencein

theORGregressionresults:ThewageeffectoftheMarielitosdoesnoteventuallydisappear.

Boththeemploymentandsyntheticplacebosindicatethatthelogwageofhighschool

dropoutsinMiamiis10to20percentbelowthatofcomparableworkersintheplacebo

citiesevenadecadeyearsafterMariel(althoughtheeffectisnotsignificantwiththe

employmentplacebo).

DespitetheregressionfindingthattheMarielsupplyshockharmedlow-skill

workersintheshortrun,theoverallevidencemaynotbeconsistentwiththetextbook

modeloffactordemand.Theevidenceconsistentlysuggeststhattheadversewageeffectof

theMarielitosinitiallyincreasedovertimebeforeeventuallydisappearing.Thisishardto

squarewiththetheoreticalpredictionthatthewageeffectwouldbelargestrightafterthe

supplyshockandwouldweakenasthecapitalstockadjustedovertime.Onepossible

explanationmaybethatemployersarereluctanttocutwagesforpre-existingworkers,so

thattheimmigration-inducedwagecutscomeintoplay“slowly”asturnoverinthelowskill

labormarketallowsfirmstotakeadvantageofthechangedsituation.

Equallyimportant,theadjustmentsinducedbytheMarielsupplyshockprobably

involvedmuchmorethantheincreaseinthecapitalstockthatplaysthecentralroleinthe

neoclassicalmodeloflabordemand.AssuggestedbytheracialunrestthatshookMiami

27

soonafterMariel,thepoliticalandsocialupheavalcreatedbyCastro’sdecisiontoopenup

theportofMarielaffectedMiami’seconomyinwaysthatextendfarbeyondwhatour

modelscapture(PortesandStepick,1994).Putdifferently,theceterisparibusassumption

doesnotreallyapply.Giventheseundocumentedandunknownreactions,itisdifficultto

saymuchaboutthedynamicsofthewageeffectfromtheevidencegeneratedbytheMariel

supplyshock.

Wealsodonotfullyunderstandthefactorsresponsiblefortheeventual

disappearanceoftherelativewageeffect(atleastintheMarchCPS).Economictheory

impliesthatitistheaveragewageinthelabormarketthatwillreturntoitspre-Mariel

leveliftheproductionfunctionislinearhomogeneous(Borjas,2014).Therelativewage

effectwillnotgoawayunlesstherehasalsobeenachangeintherelativequantitiesoflow-

andhigh-skilllabor.Card(1990,p.255)citesevidencethatinsinuatesapossiblesupply

response:“TheBoatliftmayhaveactuallyheldbacklong-runpopulationgrowthin

Miami…thepopulationofDadeCountyin1986wasaboutequaltothepre-Boatlift

projectionoftheUniversityofFloridaBureauofEconomicandBusiness.”Although

suggestive,thisslowdowninpopulationgrowthcannotexplaintheabsenceofalong-term

relativewageeffectunlesstheslowdownalsoresultedinarelative“exodus”oflow-skill

workersfromtheMiamilabormarket.

Finally,Table7summarizesregressioncoefficientsfrommodelsthatdefinethelow-

skillworkforceinalternativeways.Tosimplifythepresentation,Iestimatedtheregression

modelinequation(3)usingonlytheyearsbetween1977and1986(excluding1980),and

theshort-runwageeffectreportedinthetableissimplytheinteractionbetweenthe

indicatorfortheMiamimetropolitanareaandtheindicatorforapost-1980observation.

Althoughthereisobviouslyalotofvariationintheestimatedcoefficients(andstatistical

significance),thethrustoftheevidencesuggestsanegativeshort-runimpactregardlessof

whetherwelookatthelogwageofhighschooldropouts,thelogwageofthepooledgroup

ofhighschooldropoutsandhighschoolgraduates,theinterquantilerange,ortheblack-

28

whitewagegap.TheMarielsupplyshocktypicallyharmedworkersatthebottomendof

thewagedistribution.29

Theuseofeithertheemploymentplaceboorthesyntheticplaceboindicatesthatthe

wageofhighschooldropoutsinMiamifellby10to30percent(dependingonthedataset

used)duringthefirst6yearsafterMariel.AsInotedearlier,thesupplyshockincreasedthe

numberofhighschooldropoutsbyaround20percent,sothattheimpliedwageelasticity

(dlogw/dlogL)isbetween-0.5and-1.5.

Eitheroftheseelasticityestimatesisfarhigherthanthetypicalwageeffect

estimatedin(non-experimental)cross-cityregressionsthatlinkwagestoimmigration,an

effectthatoftenclustersaroundanegligiblenumber.Theyarealsohigherthanthewage

elasticitiesestimatedbycorrelatingwagesandimmigrationacrossskillgroupsinthe

nationallabormarket(Borjas2003),anelasticitythatclustersaround-0.3to-0.4.

Interestingly,theestimatesareclosetothosereportedinMonras(2015)andLlull(2015),

whousenewinstruments(includingthePesoCrisisinMexico,naturaldisasters,armed

conflicts,andchangesinpoliticalconditions)tocorrectfortheendogeneityofmigration

flows.Monrasreportsawageelasticityof-0.7andLlull’sestimatesclusteraround-1.2.

Thereareobviouslymanycaveatsthatneedtobeconsideredregardingthe

specificationoftheregressionmodelsandthesmallsamplesintheCPSdatabeforewefully

buyintoanelasticityestimateofbetween-0.5and-1.5.Nevertheless,thekeyimplicationof

theevidenceisunambiguous.ThewageofhighschooldropoutsintheMiamilabormarket

fellsignificantlyaftertheMarielsupplyshock.Anyattemptatrationalizingthisfactasdue

tosomethingotherthantheMarielitoswillneedtospecifypreciselywhatthoseother

factorswere.

29Ialsoestimatedspecificationsoftheregressionmodelthatuseddifferentvectorsofvariablesto

predictthesyntheticplacebo.Averygeneralspecification,forexample,includedthetotalgrowthrateofemploymentinthemetropolitanarea,theemploymentandwagegrowthratesforeachofthefoureducationgroups,thepercentoftheworkforcethatwasblack,andthepercentthatwasHispanic.Theestimatedshort-runwageeffectwas-0.148(0.059)intheMarchCPSand-0.134(0.079)intheORG.Theweightingalgorithmintheseexpandedregressions,particularlywhenincludingthepercentHispanicvariable,oftenassignedverylargeweightstoSanDiego.

29

VI. The Choice of a Placebo Theevidencereportedintheprevioussectionssuggeststhatthechoiceofaplacebo

matters.Theshort-runimpactoftheMarielsupplyshock(i.e.,theimpactonwages

between1981and1986)wasgenerallymorenegativeandstatisticallysignificantwhenI

usedeithertheemploymentorsyntheticplacebothanwhenIusedtheCardplacebo.Itis

usefultodocumentinaverysimplewayhowitispossibleto“cherrypick”placebosto

buildinaparticularempiricalfinding.Iillustratethisvariationbyestimatingtheshort-run

wageeffectusingthedifference-in-differencesregressionmodelinequation(3)ineachof

the123,410possiblefour-cityplacebos.BecauseIamfocusingontheshort-runwage

impact,theregressionsonlyemploytheobservationsbetween1977and1986(withthe

1980observationexcludedthroughout).

ThetwopanelsofFigure9illustratethefrequencydistributionofestimatedeffects

whenthedependentvariableisthelogwageofhighschooldropouts,whileTable8reports

summarystatisticsforthevariousdistributions.Forcomparisonpurposes,thebottom

rowsofthetablereporttheactualestimatedwageimpact(andstandarderror)whenusing

theCard,employment,andsyntheticplacebos.

Considerthedistributionofestimatedeffectsonthewageofhighschooldropoutsin

theMarchCPSdata.Themeaneffectis-0.243,whichisfarsmallerthantheestimate

obtainedfromeithertheemploymentplacebo(-0.374)orthesyntheticplacebo(-0.335).

Nevertheless,mostofthepotentialplaceboswouldstillsuggestthatthewageeffectis

significant:over98percentoftheestimatedeffectshaveat-statisticabove1.6.

Note,however,thatifthesetofplaceboswererestrictedsothattheaverage

employmentgrowthinthefourplacebocitieswasroughlysimilartothatofpre-Mariel

Miami,themeanwageeffectrisesto-0.282.Similarly,ifwelookatthestillsmallersubset

ofplaceboswhereeachcityintheplacebohadasimilarpre-Marielemploymentgrowthas

Miami,theestimatedwageeffectbecomesevenstronger;themeancoefficientis-0.333,

andallofthosecoefficientsarestatisticallysignificant.Putdifferently,thecloserwegettoa

placebothatseemstoreplicatethepre-existingemploymentconditionsinMiami,themore

likelywearetofindthattheMarielitoshadanumericallysizableandastatistically

significantwageeffectonlow-skillMiamians.AsTable8shows,thesamegeneraltrendis

impliedbythefrequencydistributionofwageeffectscomputedintheORGdata.

30

Thistypeofunusualexerciseshowstheimportancethatthechoiceofaplacebo

playsingeneratingestimatesoftheimpactofnaturalexperiments.Itmightbeprudentto

withholddrawingmanysubstantiveinferencesfromsuchexperimentsuntilweseehow

the“preferred”estimateofthepolicyimpactcomparestothedistributionofpotential

impacts.30

Itisinstructivetoconcludebyextendingthesyntheticcontrolapproachtoshowthe

distributionofwageeffectsimpliedbyanintriguingcounterfactualexercise.Whatwould

thedistributionofestimatedwageeffectslooklikeifwe“actedasif”acityhadexperienced

ashockinyeart,andsimplycalculatedthepre-postwagechangeattributabletothis

imaginarysupplyshock?

Tobemorespecific,supposewedefineapre-treatmentperiodof3yearsandapost-

treatmentperiodof6years.WecanimaginethatthecityofAkronwashitbyaphantom

supplyshockin1988.WecanthencalculatethewagechangeexperiencedbyAkron

between1985-1987and1989-2004,andcontrastthiswageeffectwithwhathappenedto

wagesinthesyntheticplaceboimpliedbythepre-existingconditionsinAkron.31

Presumably,thewageeffectresultingfromthisexerciseshouldbenearzerosimply

becauseFidelCastrodidnotsuddenlydecidetorelocateover100,000CubanstoAkronin

1988.However,other(random)thingsmayhavehappenedinpost-1988Akronthatwe

knownothingaboutandthatmayhavechangedtherelativewageoflow-skillworkersin

thatcityrelativetothesyntheticplacebo.

Wecanobviouslycarryoutthisexerciseforeverysinglepermutationofacity

receivinganimaginarysupplyshockandeverysinglepre-postperiodallowedbythedata

between1977and2003.Togeneratethesyntheticcontrol,Iusedthecity’srateoftotal

employmentgrowthinthe4-yearperiodpriortothetreatment,andtheratesof

employmentandwagegrowthforthespecificeducationgroupbeingexamined.Thetop

panelofFigure10illustratesthedistributionoftheestimatedwageeffectsofthese

30Thereis,infact,astrongnegativecorrelationbetweenthewageeffectestimatedinplacebopand

themeanrateofemploymentgrowthinthecitiesthatformthatplacebo.

31TobeconsistentwiththeanalysisoftheMarielsupplyshock,thepre-treatmentemploymentgrowthismeasuredinthefour-yearperiodpriortothehypotheticalshock,or1985-1988intheAkronexamplediscussedinthetext.

31

hypotheticalshocksusingthelogwageofhighschooldropoutsasthedependentvariable,

andTable9summarizessomeofthecharacteristicsoftheresultingdistributions.Thedata

reportedinTable9,ofcourse,allowapermutationinferenceanalysisofthewageeffectof

theMarielsupplyshock.

Thereisobviouslyalotofdispersionintheestimatedwageeffectsacrossallthese

hypotheticalshocks.Asexpected,themeaneffectiszero.Itisimportanttoemphasize,

however,thattheMarchCPSimpliesthatthewageeffectinducedbytherealMarielsupply

shockinMiamiwas-0.335(0.090),whichisinthe3rdpercentileofthecounterfactual

distributionwhereeachimaginaryshockiseffectivelybeingcomparedtothe“best”

possibleplaceboforthatcityatthattime.Ifwenarrowdownthecomparisontothe1980

treatmentyear,theMarieleffectisbythemostnegativeacrossallmetropolitanareas.

Itisalsoinstructivetodocumentthewageimpactontheothereducationgroups

resultingfromthiscounterfactualexercise.AsthelastthreecolumnsofTable9show,the

meaneffectsacrossallcity-yearpermutationsarealwaysnearzero,andtheeffect

observedinMiamiatthetimeofMarielistypicallynotsignificantlydifferentfromzero.

Nevertheless,asthebottompanelofFigure9illustrates,theimpactofMarielonthewage

ofhighschoolgraduatesispositive,againrejectingtheconjecturethathighschool

graduatesandhighschooldropoutsareperfectsubstitutes.

Finally,Figure11illustratesthedynamicsoftheestimatedwageeffectresulting

fromtheMarielsupplyshockinMiami,andfromthehypotheticalsupplyshocksinallother

metropolitanareasinthe1980treatmentyear.Specifically,Iusethesyntheticcontrol

methodandcalculateforeachmetropolitanareaineachyearthrough1992thepre-post

differencebetweenthewageofhighschooldropoutsinaspecificmetropolitanareaandin

itssyntheticplacebo.Thecalculateddoubledifference,ofcourse,impliesthateachpointin

thefiguremeasuretheimpactofthesupplyshockonthewageofhighschooldropoutsas

oftimet.Forexample,thetrendintheMiamiwageeffectimpliedbytheMarchCPSdata

indicatesthatthewageofhighschooldropoutsinMiamirelativetothesyntheticplacebois

around30percentlowerin1985thanitwasin1979.Notethatthetrendforthewage

effectintheMiamimetropolitanareafromashockintreatmentyear1980formsalower

“envelope”fortheentiredistributionofpotentialwageeffectsresultingfrom

contemporaneoussupplyshocksinallothermetropolitanareas.Thisexerciseagainshows

32

thatthewageeffectoftheMarielitosdisappearsafteradecadeintheMarchCPSdata,but

persistsintheORG.

Insum,theMarielsupplyshockhadaveryspecifictargetandithitthattargetwith

impressivelaser-likeprecision:TheMarielitoshadasubstantialdepressingeffectonthe

earningsoftheleasteducatedworkersinMiami.

VII. Conclusion Card’s(1990)classicpaperonthelabormarketimpactoftheMarielsupplyshock

standsasalandmarkstudyinlaboreconomics.Hisfindingthatthesupplyshockseemedto

havelittleeffectonthelabormarketopportunitiesofnativeworkershasprofoundly

influencedwhatwethinkweknowabouttheeconomicconsequencesofimmigration.The

eleganceofthemethodologicalapproach—theexploitationofafascinatingnatural

experimenttoestimateaparameterofgreateconomicinterest—hasalsoinfluencedthe

waythatmanyappliedeconomistsframetheirquestions,organizethedata,andsearchfor

ananswer.

ThispaperbringsanewperspectivetotheanalysisoftheMarielsupplyshock.I

revisitthequestionandthedataarmedwiththeinsightsprovidedbythreedecadesof

researchontheeconomicimpactofimmigration.Onekeylessonfromthisvoluminous

literatureisthattheeffectofimmigrationonthewagestructuredependscruciallyonthe

differencesbetweentheskilldistributionsofimmigrantsandnatives.Thedirecteffectof

immigrationismostlikelytobefeltbythoseworkerswhohadsimilarcapabilitiesasthe

Marielitos.

ItiswellknownthattheMarielsupplyshockwascomposedofdisproportionately

low-skillworkers,andatleast60percentwerehighschooldropouts.Remarkably,noneof

thepreviousexaminationsoftheMarielexperiencedocumentedwhathappenedtothepre-

existinggroupofhighschooldropoutsinMiami,agroupthatcomposedoveraquarterof

thecity’sworkforce.GiventheliteraturesparkedbyBorjas(2003),itseemsobviousthata

crucialcomponentofanyanalysisoftheMarielsupplyshockshouldfocusonthelabor

marketoutcomesoftheselow-skillworkers.

33

Theexaminationofwagetrendsamonghighschooldropoutsquicklyoverturnsthe

“stylizedfact”thatthesupplyshockdidnotaffectMiami’swagestructure.Infact,the

absolutewageofhighschooldropoutsdroppeddramatically,asdidtheirwagerelativeto

thatofeitherhighschoolgraduatesorcollegegraduates.Thedropintheaveragewageof

theleastskilledMiamiansbetween1977-1979and1981-1986wassubstantial,between

10and30percent(dependingonwhethertheanalysisusestheCPS-ORGortheMarchCPS

data).Infact,theexaminationofwagetrendsineverysinglecityidentifiedbytheCPS

throughouttheperiodshowsthatthesteeppost-MarielwagedropexperiencedbyMiami’s

low-skillworkforcewasaveryunusualevent.

Thereappraisalpresentedinthispaperalsostrikinglyillustratesthatthe

researcher’schoiceofaplaceboisanimportantcomponentofanysuchempiricalexercise,

andthatpickingthe“wrong”placebocaneasilyleadtoaweakermeasuredimpactof

immigration.Theanalysisdocumentedtheimportanceofplacebochoicebyestimatingthe

impactofMarielacrossallpotential(four-city)placebosallowedbythedata.The

distributionofestimatedwageeffectsisveryinformative.Themeasuredwageimpactof

thesupplyshockislargestwhenthecomparisongroupconsistsofcitiesthathadasimilar

rateofpre-MarielemploymentgrowthasMiami.Themethodologicalapproachof

estimatingtheentiredistributionofpotentialeffectsacrossallpossibleplaceboscanbea

usefulcomponentofstudiesthatexaminetheconsequencesofnaturalexperiments.

Theempiricalevidencealsohasmanylessonsforthevastliteraturethatpurportsto

measurethewageimpactofimmigration.Forinstance,manystudiesmeasuretheeffectby

estimatingspatialcorrelationsbetweenwagesandthenumberofimmigrantsina

particularlocality.Thesespatialcorrelations,manyofwhichclusteraroundzero,are

plaguedbothbyendogeneityproblems(i.e.immigrantssettleinhigh-wageregions)andby

nativeadjustments(i.e.,firmsandworkersmayrespondtothesupplyshockbyrelocating

toothercities).ThefactthatthespatialcorrelationimpliedbytheMarielsupplyshockis

stronglynegativesuggeststhattheexistingnon-experimentalliteraturehasnot

successfullypurgedthosestatisticaldifficulties.Thereisstillsomewaytogobeforenon-

experimentalspatialcorrelationscanbepresumedtoestimateaparameterofeconomic

interest.

34

Theevidencealsohaspotentiallyimportantimplicationsforestimatesofthe

economicbenefitsfromimmigration.Thebenefitthataccruestothenativepopulation,or

the“immigrationsurplus,”istheflipsideofthewageimpactofimmigration.Infact,itis

wellknownthatthegreaterthewageimpact,thegreatertheimmigrationsurplus.Borjas

(2014,p.151)estimatesthecurrentsurplustobearound0.24percentofGDP(oraround

$43billionannually).Thefactthattherewasamuchlargerreductionintheearningsofthe

workersmostlikelytobeaffectedbytheMarielitosthanwaspreviouslybelievedsuggests

thatwemayalsoneedtoreassessexistingestimatesoftheimmigrationsurplus.That

surpluscouldeasilybetwiceorthreetimesaslargeiftheMarielcontextcorrectly

measuresthewageimpact.

Ithasbeenaquarter-centurysincethepublicationofCard’sMarielstudy.More

likelythannot,thatanalysishasbeenreplicatedoftenaspartofanempiricalexerciseinan

econometricsorlaboreconomicsclass.Thereappraisaloftheevidenceprovidedinthis

paperteachesanimportantlesson.Althoughreplicationobviouslyservesanextremely

usefulroleintheadvancementofappliedscience,thereismuchtobegainedbyrevisiting

manyofthosepersistentoldquestionswithanewperspective,aperspectivethatusesthe

insightsaccumulatedovertheyears.Ifnothingelse,thereappraisaloftheMarielevidence

showsthateventhemostcursoryreexaminationofsomeolddatawithsomenewideascan

revealtrendsthatradicallychangewhatwethinkweknow.

35

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Miami.Berkeley,CA:UniversityofCaliforniaPress.Saiz,Albert.2003.“RoomintheKitchenfortheMeltingPot:ImmigrationandRental

Prices.”ReviewofEconomicsandStatistics85:502-521.Stabile,BenedictL.,andRobertL.Scheina.2015.“U.S.CoastGuardOperations

Duringthe1980CubanExodus,”U.S.CoastGuardwebsite,accessedSeptember30,2015.

Vogel,RonaldK.,andGenieN.L.Stowers.1991.“Miami:MinorityEmpowermentandRegimeChange,”inH.V.SavitchandJohnClaytonThomas,eds.,BigCityPoliticsinTransition.NewYork:SagePublications.

38

Figure1.NumberofCubanimmigrants,byyearofmigration,1955-2010

Notes:Thespecificyearofmigration(through1999)isfirstreportedinthe2000census.Thecountsareadjustedformortalityandout-migrationbyusinginformationonthenumberofarrivalsprovidedbythe1970through1990censuses;seethetextfordetails.The2000-2008countsaredrawnfromthepooled2009-2011AmericanCommunitySurveys(ACS),whilethe2009-2010countsaredrawnfromthe2012ACS.

0"

10,000"

20,000"

30,000"

40,000"

50,000"

60,000"

70,000"

80,000"

90,000"

100,000"

110,000"

120,000"

1950" 1960" 1970" 1980" 1990" 2000" 2010"

Num

ber'o

f'immigrants'

Year'of'migra1on'

39

Figure2.Logwageofhighschooldropouts,1972-2003

Notes:Thelogweeklywageisa3-yearmovingaverageoftheunadjustedaveragelogwageofhighschooldropoutsineachgeographicarea.ThedataaredrawnfromtheMarchCPSfiles.

5"

5.1"

5.2"

5.3"

5.4"

5.5"

5.6"

5.7"

5.8"

5.9"

1970" 1975" 1980" 1985" 1990" 1995" 2000" 2005"

Log$weekly$wage$

Year$

Miami

Outside Miami

40

Figure3.Thetrendinthewageoflow-skillworkers,1976-1992

A. Log weekly wage of high school dropouts

B. Log wage of high school dropouts relative to college graduates

C. Log wage of high school dropouts relative to high school graduates

Notes:Thefiguresusea3-yearmovingaverageoftheage-adjustedaveragelogwageofhighschooldropouts,highschoolgraduates,andcollegegraduatesineachspecificgeographicarea.ThedataaredrawnfromtheMarchCPSfiles.

5"

5.1"

5.2"

5.3"

5.4"

5.5"

5.6"

5.7"

5.8"

5.9"

1976" 1978" 1980" 1982" 1984" 1986" 1988" 1990" 1992"

Log$weekly$wage$

Year$

Miami

Synthetic placebo

Card placebo

Employment placebo

!1.2%

!1%

!0.8%

!0.6%

!0.4%

!0.2%

1976% 1978% 1980% 1982% 1984% 1986% 1988% 1990% 1992%

Log$wage$gap$

Year$

Miami

Synthetic placebo

Card placebo

Employment placebo

!0.7%

!0.6%

!0.5%

!0.4%

!0.3%

!0.2%

!0.1%

0%

0.1%

0.2%

1976% 1978% 1980% 1982% 1984% 1986% 1988% 1990% 1992%

Log$wage$gap$

Year$

Miami Synthetic placebo

Card placebo

Employment placebo

41

Figure4.Distributionofpre-postwagechanges,1976-2003

A. Log wages of high school dropouts

Across all city-year permutations 1980 treatment year

B. Log wage of high school graduates

Across all city-year permutations 1980 treatment year

Notes:Thepre-treatmentperiodlasts4years;thepost-treatmentperiodlasts6years;andtheyearofthetreatmentisexcludedfromthecalculation.ThedataaredrawnfromtheMarchCPSfiles.

Mariel Mariel

Mariel Mariel

42

Figure5.Thetrendinthewageoflow-skillworkersintheORG,1977-1992

A. Log weekly wage of high school dropouts

B. Log wage of high school dropouts relative to college graduates

C. Log wage of high school dropouts relative to high school graduates

Notes:Thefiguresusea3-yearmovingaverageoftheage-adjustedaveragelogwageofhighschooldropouts,highschoolgraduates,andcollegegraduatesineachspecificgeographicarea.

!0.6%

!0.5%

!0.4%

!0.3%

!0.2%

!0.1%

1976% 1978% 1980% 1982% 1984% 1986% 1988% 1990% 1992%

Log$weekly$wage$

Year$

Miami

Synthetic placebo

Card placebo

Employment placebo

!1#

!0.9#

!0.8#

!0.7#

!0.6#

!0.5#

!0.4#

!0.3#

1976# 1978# 1980# 1982# 1984# 1986# 1988# 1990# 1992#

Log$wage$gap$

Year$

Miami

Synthetic placebo

Card placebo

Employment placebo

!0.5%

!0.4%

!0.3%

!0.2%

!0.1%

0%

1976% 1978% 1980% 1982% 1984% 1986% 1988% 1990% 1992%

Log$wage$gap$

Year$

Miami

Synthetic placebo

Card placebo

Employment placebo

43

Figure6.Wagetrendsinpooledgroupofhighschooldropoutsandhighschoolgraduates,MarchCPS,1977-1992

A.Logwageofpooledhighschooldropoutsandhighschoolgraduates

B.Logwageofpooledhighschooldropoutsandgraduatesrelativetocollegegraduates

Notes:Thefiguresusea3-yearmovingaverageoftheage-adjustedaveragelogwageofthepooledgroupofhighschooldropoutsandhighschoolgraduates,andofcollegegraduatesineachspecificgeographicarea.

!0.4%

!0.3%

!0.2%

!0.1%

1976% 1978% 1980% 1982% 1984% 1986% 1988% 1990% 1992%

Log$wage$gap$

Year$

Miami

Synthetic placebo

Card placebo

Employment placebo

!0.9%

!0.8%

!0.7%

!0.6%

!0.5%

!0.4%

!0.3%

!0.2%

1976% 1978% 1980% 1982% 1984% 1986% 1988% 1990% 1992%

Log$wage$gap$

Year$

Miami

Synthetic placebo

Card placebo

Employment placebo

44

Figure7.Trendsinthespreadofthelogweeklywagedistribution,MarchCPS,1977-1992

A.Logwageofworkeratthe20thpercentile

B.Differenceinthelogwageofworkersatthe20thand80thpercentiles

Notes:Thefiguresusea3-yearmovingaverageoftheage-adjustedlogweeklywageineachspecificgeographicareaforeachspecificpercentile.

!0.7%

!0.6%

!0.5%

!0.4%

!0.3%

!0.2%

1976% 1978% 1980% 1982% 1984% 1986% 1988% 1990% 1992%

Log$wage$gap$

Year$

Miami

Synthetic placebo

Card placebo

Employment placebo

!1.3%

!1.2%

!1.1%

!1%

!0.9%

!0.8%

!0.7%

!0.6%

1976% 1978% 1980% 1982% 1984% 1986% 1988% 1990% 1992%

Log$wage$gap$

Year$

Miami

Synthetic placebo

Card placebo

Employment placebo

45

Figure8.Trendsintheblack-whitewagedifferential,1976-1992A.MarchCPS

B.CPS-ORG

Notes:Thefiguresusea3-yearmovingaverageofthedifferenceintheage-adjustedaveragelogwagebetweenblackandwhiteworkersineachspecificgeographicarea.

!0.8%

!0.7%

!0.6%

!0.5%

!0.4%

!0.3%

!0.2%

!0.1%

1976% 1978% 1980% 1982% 1984% 1986% 1988% 1990% 1992%

Log$wage$gap$

Year$

Miami

Card placebo

Employment placebo

-0.7

-0.6

-0.5

-0.4

-0.3

-0.2

-0.1

1976 1978 1980 1982 1984 1986 1988 1990 1992

Logwagegap

Year

Miami

Card placebo

Employment placebo Synthetic placebo

46

Figure9.Distributionofshort-runimpactsacrossallpossiblefour-cityplacebos,1977-1986

A.MarchCPS

B.CPS-ORG

Notes:Thefigureshowsthedistributionoftheinteractiontermfromthedifference-in-differencesregressionmodelinequation(3)resultingfromcomparingMiamitoallpossible123,410placebosintheMarchCPSdata.Theregressionsuseannualobservationsforeachcityintheperiod1977-1986(1980excluded),andthecoefficientsmeasuretheimpactinthe“shortrun”(i.e.,1981-1986).Allregressionswereweightedbythenumberofobservationsusedtocalculatethemeanwageofhighschooldropoutsincityrattimet.

Employmentplacebo

Cardplacebo

Syntheticplacebo

Employmentplacebo Card

placebo

Syntheticplacebo

47

Figure10.Distributionofhypotheticalshort-runimpactsrelativetosyntheticplacebo,assumingasupplyshockhitseachcity-yearpermutation

A. Log wage of high school dropouts

March CPS CPS-ORG

B. Log wage of high school graduates

March CPS CPS-ORG

Notes:Eachyearbetween1980and1995isassumedtobeapotentialtreatmentyear.Thepre-treatmentperiodlasts3years;thepost-treatmentperiodlasts6years.Thewageeffectisestimatedfromadifference-in-differencesregressionmodelthatexcludestheyearofthetreatment.ThefrequencydistributionsdonotincludeanyofthewageeffectsestimatedintheMiamimetropolitanarea.

Mariel Mariel

MarielMariel

48

Figure11.Effectofhypotheticalsupplyshockin1980onlogwageofhighschooldropoutsineachmetropolitanarea,relativetosyntheticplacebo

A.MarchCPS

B.CPS-ORG

Notes:Theexercisetracesthewageeffectofasupplyshockintreatmentyear1980ineachofthe44metropolitanareas.Thewageeffectisdefinedasthedifference-in-differencesΔwrt-Δwr0,whereΔwrtgivesthelogwagegapbetweencityranditssyntheticplaceboattimet;andΔwr0givestheequivalentaveragelogwagegapinpre-treatmentyears1977-1979.Beginningin1980,theillustratedwageeffectsrepresenta3-yearmovingaverage.

-0.8

-0.6

-0.4

-0.2

0

0.2

0.4

0.6

0.8

1976 1978 1980 1982 1984 1986 1988 1990 1992

Es#m

ated

logwageeff

ect

Year

Miami

-0.4

-0.3

-0.2

-0.1

0

0.1

0.2

0.3

0.4

1976 1978 1980 1982 1984 1986 1988 1990 1992

Es#m

ated

logwageeff

ect

Year

Miami

49

Table1.EducationdistributionofadultMarielitos

Yearsofeducation Sample: <12 12 13-15 ≥16 SamplesizeMarielitos: April1983CPS 57.9 25.6 3.5 13.1 31 June1986CPS 55.2 28.0 6.4 9.6 31 June1988CPS 58.7 26.1 4.4 10.9 46 1990Census 64.8 15.8 12.9 6.5 4,234 1994CPS-ORG 61.4 20.5 9.8 8.3 143 2000Census 59.9 20.0 12.7 7.4 3,301

Miami’s pre-existing labor force:

1980 Census 26.7 28.4 26.0 18.8 32,971 Notes:ThestatisticsarecalculatedinthesampleofpersonsborninCubawhomigratedtotheUnitedStatesatthetimeofMarielandwere18yearsoldin1980.IntheApril1983CPSand2000census,theMarielitosareidentifiedaspersonsborninCubawhomigratedtotheUnitedStatesin1980.Inallothersamples,theMarielitosareidentifiedasCubanswhoenteredthecountryin1980or1981.Thepre-existinglaborforceofMiamiincludesbothnativesandimmigrants.

50

Table2.ThesizeoftheMarielsupplyshock Education group:

Size of Miami’s labor force in 1980 (1000s)

Number of Marielitos in labor

force (1000s)

Percent increase in supply

High school dropouts 176.3 32.5 18.4 High school graduates 187.5 10.1 5.4 Some college 171.5 8.8 5.1 College graduates 124.1 4.2 3.4

All workers 659.4 55.7 8.4 Notes:Thepre-existingnumberofnativeworkersinMiamiiscalculatedfromthe1980census;thenumberofMarielitoworkers(atleast18yearsoldatthetimeofMariel)iscalculatedfromthe1990census,andasmalladjustmentismadebecausethe1990censusreportsthenumberofCubanimmigrantswhoenteredthecountryin1980or1981.

51

Table3.RatesofemploymentandwagegrowthbeforeMariel

Rank MetropolitanareaEmployment

growth:allworkersEmploymentgrowth:highschooldropouts

Wagegrowth:highschooldropouts

1 SanDiego,CA 0.194 0.067 -0.0932 Greensboro-WinstonSalem,NC 0.182 -0.063 -0.3073 KansasCity,MO/KS 0.179 0.052 -0.1914 Anaheim-SantaAna-GardenGrove,CA 0.162 0.257 0.0675 Rochester,NY 0.153 -0.172 0.0656 Miami-Hialeah,FL 0.153 0.086 0.0147 Nassau-Suffolk,NY 0.151 0.056 -0.0578 SanJose,CA 0.137 0.130 0.1249 Albany-Schenectady-Troy,NY 0.130 0.065 0.05810 Boston,MA 0.121 -0.100 -0.00811 Milwaukee,WI 0.121 -0.006 0.04012 Indianapolis,IN 0.115 0.071 -0.03213 Seattle-Everett,WA 0.110 -0.079 -0.05114 Norfolk-VirginiaBeach-NewportNews,VA 0.103 0.052 0.11115 Philadelphia,PA/NJ 0.102 -0.033 0.00216 Newark,NJ 0.092 -0.116 -0.08917 Tampa-St.Petersburg-Clearwater,FL 0.083 0.068 0.12918 Denver-Boulder-Longmont,CO 0.082 -0.139 -0.01219 Houston-Brazoria,TX 0.078 0.090 0.00420 Sacramento,CA 0.078 0.152 -0.00421 Dallas-FortWorth,TX 0.076 0.062 -0.03722 Portland-Vancouver,OR/WA 0.071 -0.074 -0.01523 Riverside-SanBernardino,CA 0.071 -0.017 0.29824 Atlanta,GA 0.069 -0.087 -0.06225 Cincinnati-Hamilton,OH/KY/IN 0.063 0.038 -0.06826 Washington,DC/MD/VA 0.061 0.028 0.08227 Detroit,MI 0.060 -0.099 -0.01028 FortWorth-Arlington,TX 0.058 -0.006 -0.03329 LosAngeles-LongBeach,CA 0.056 0.075 -0.11230 Columbus,OH 0.048 -0.324 -0.01631 Buffalo-NiagaraFalls,NY 0.039 0.040 -0.14332 Chicago-Gary-LakeIL 0.025 -0.082 -0.01733 St.Louis,MO/IL 0.019 -0.060 -0.02334 Bergen-Passaic,NJ 0.015 -0.051 0.01135 Baltimore,MD 0.012 -0.108 -0.01636 Minneapolis-St.Paul,MN 0.007 -0.050 -0.01037 Cleveland,OH 0.001 -0.071 -0.01738 NewYork,NY 0.000 -0.146 0.06939 Pittsburg,PA -0.013 -0.111 0.12740 Birmingham,AL -0.020 -0.172 -0.09041 SanFrancisco-Oakland-Vallejo,CA -0.027 -0.200 -0.10242 Gary-Hammond-EastChicago,IN -0.029 0.119 0.04243 NewOrleans,LA -0.046 -0.313 -0.03844 Akron,OH -0.110 -0.351 -0.004Notes:Therateofemploymentgrowthisthelogratioofaverageemploymentin1979-1980toaverageemploymentin1977-1978,calculatedusingtheMarchCPSfromthe1977-1980surveyyears.Therateofwagegrowthisthedifferenceinthe(age-adjusted)logweeklywagebetween1978-1979and1976-1977.

52

Table4.Distributionofwagechangeswithinmetroareasacrossallpotentialcity-yearpermutations,1976-2003

Dependent variable: Log wage of education group Characteristics of distribution: < 12 years 12 years 13-15 years ≥ 16 years Value for Mariel -0.439 -0.025 -0.116 -0.062 Distribution across all city-year permutations

Mean of distribution outside Miami -0.100 -0.061 -0.024 0.006 Percentile of Mariel effect 1.8 65.6 19.0 20.7

Distribution in treatment year 1980:

Mean of distribution outside Miami -0.170 -0.152 -0.092 -0.043 Ranking of Mariel effect 1/44 42/44 14/44 17/44 Notes:Thesummarystatisticsarecalculatedfromthedistributionofwagechangesbetweenthepre-andpost-periodforallmetropolitanareas(excludingMiami)forallpossiblepermutationsinthe1976-2003MarchCPSdata.Thepre-treatmentperiodlasts4years;thepost-treatmentperiodlasts6years;andtheyearofthetreatmentisexcludedfromthecalculation.Thedistributionshave774observations.

53

Table5.Difference-in-differencesimpactoftheMarielitosonthewageofhighschooldropouts,MarchCPS

Dependent variable and treatment period

Card placebo

Employment placebo

Synthetic placebo

All cities

A. Log wage of high school dropouts 1981-1983 -0.137 -0.289 -0.210 -0.135 (0.093) (0.090) (0.086) (0.080) 1984-1986 -0.364 -0.495 -0.461 -0.378 (0.080) (0.071) (0.077) (0.033) 1987-1989 -0.216 -0.251 -0.210 -0.192 (0.085) (0.071) (0.068) (0.058) 1990-1992 0.188 0.096 0.021 0.188

(0.158) (0.136) (0.096) (0.111) B. Log wage relative to college graduates

1981-1983 -0.168 -0.390 -0.269 -0.180 (0.187) (0.164) (0.193) (0.170) 1984-1986 -0.387 -0.593 -0.552 -0.453 (0.159) (0.154) (0.193) (0.135) 1987-1989 -0.340 -0.482 -0.387 -0.357 (0.154) (0.159) (0.195) (0.132) 1990-1992 0.180 0.084 0.191 0.192 (0.223) (0.200) (0.141) (0.180)

C. Log wage relative to high school graduates

1981-1983 -0.276 -0.420 -0.383 -0.285 (0.131) (0.146) (0.104) (0.136) 1984-1986 -0.490 -0.627 -0.620 -0.470 (0.114) (0.093) (0.097) (0.094) 1987-1989 -0.344 -0.325 -0.298 -0.254 (0.098) (0.071) (0.041) (0.082) 1990-1992 0.067 0.016 -0.102 0.122 (0.195) (0.144) (0.101) (0.143)

Notes:Robuststandarderrorsarereportedinparentheses.Thedataconsistofannualobservationsforeachcitybetween1977and1992(1980excluded).Allregressionsincludevectorsofcityandyearfixedeffects.ThetablereportstheinteractioncoefficientsbetweenadummyvariableindicatingifthemetropolitanareaisMiamiandthetimingofthepost-Marielperiod.TheregressionsthatusetheCardoremploymentplaceboshave75observations;theregressionsthatusethesyntheticplacebohave30observations;andtheregressionsinthelastcolumnhave658observations.TheregressionsinPanelAareweightedbythenumberofobservationssizeusedtocalculatethedependentvariable.TheregressionsinPanelsBandCareweightedby(n1ns)/(n1+ns),wheren1isthenumberofobservationsusedtocalculatethemeanwageofhighschooldropoutsincityrattimet,andnsistherespectivenumberofobservationsusedtocalculatethemeanwageofthemorehighlyeducatedgroup.Theregressionsthatusethesyntheticplaceboarenotweighted.

54

Table6.Difference-in-differencesimpactoftheMarielitosonthewageofhighschooldropouts,CPS-ORG

Dependent variable and treatment period

Card placebo

Employment placebo

Synthetic placebo

All cities

A. Log wage of high school dropouts 1981-1983 -0.068 -0.153 -0.240 -0.092 (0.027) (0.060) (0.082) (0.027) 1984-1986 -0.032 -0.097 -0.203 -0.075 (0.039) (0.066) (0.078) (0.028) 1987-1989 -0.061 -0.206 -0.241 -0.137 (0.031) (0.055) (0.075) (0.018) 1990-1992 0.005 -0.105 -0.182 -0.051

(0.058) (0.078) (0.075) (0.041) B. Log wage relative to college graduates

1981-1983 -0.020 -0.171 -0.302 -0.066 (0.059) (0.114) (0.117) (0.069) 1984-1986 -0.018 -0.130 -0.275 -0.067 (0.056) (0.096) (0.109) (0.057) 1987-1989 -0.048 -0.291 -0.377 -0.152 (0.055) (0.111) (0.112) (0.061) 1990-1992 -0.017 -0.173 -0.283 -0.074 (0.086) (0.127) (0.115) (0.077)

C. Log wage relative to high school graduates

1981-1983 -0.141 -0.188 -0.320 -0.130 (0.033) (0.072) (0.088) (0.041) 1984-1986 -0.084 -0.122 -0.242 -0.092 (0.070) (0.094) (0.096) (0.060) 1987-1989 -0.081 -0.173 -0.222 -0.108 (0.041) (0.061) (0.077) (0.039) 1990-1992 0.023 -0.082 -0.184 -0.033 (0.069) (0.062) (0.076) (0.061)

Notes:Robuststandarderrorsarereportedinparentheses.Thedataconsistofannualobservationsforeachcitybetween1977and1992(1980excluded).Allregressionsincludevectorsofcityandyearfixedeffects.ThetablereportstheinteractioncoefficientsbetweenadummyvariableindicatingifthemetropolitanareaisMiamiandthetimingofthepost-Marielperiod.TheregressionsthatusetheCardoremploymentplaceboshave75observations;theregressionsthatusethesyntheticplacebohave30observations;andtheregressionsinthelastcolumnhave660observations.TheregressionsinPanelAareweightedbythesamplesizeusedtocalculatethedependentvariable.TheregressionsinPanelsBandCareweightedby(n1ns)/(n1+ns),wheren1isthenumberofobservationsusedtocalculatethemeanwageofhighschooldropoutsincityrattimet,andnsistherespectivenumberofobservationsusedtocalculatethemeanwageofthemorehighlyeducatedgroup.Theregressionsthatusethesyntheticplaceboarenotweighted.

55

Table7.Difference-in-differencesshort-runimpactsoftheMarielitos Sample

Card placebo

Employment placebo

Synthetic placebo

All cities

A. Coefficients from March CPS

1. Log wage of high school dropouts -0.237 -0.374 -0.335 -0.237 (0.088) (0.078) (0.090) (0.076) 2. Log wage of “pooled” high school -0.030 -0.064 -0.035 -0.039

dropouts and graduates (0.049) (0.063) (0.082) (0.059) 3. Interquantile range (20th – 80th percentile) -0.062 -0.029 -0.024 -0.044 (0.108) (0.096) (0.098) (0.100) 4. Black/white relative wage -0.107 -0.221 --- -0.092

(0.072) (0.098) (0.061) B. Coefficients from CPS-ORG

1. Log wage of high school dropouts -0.054 -0.130 -0.227 -0.087 (0.026) (0.049) (0.071) (0.022)

2. Log wage of pooled high school -0.003 -0.052 -0.050 -0.036

dropouts and graduates (0.018) (0.019) (0.022) (0.014) 3. Interquantile range (20th – 80th percentile) 0.017 -0.031 -0.063 -0.037 (0.041) (0.051) (0.059) (0.040) 4. Black/white relative wage -0.134 -0.135 -0.110 -0.127

(0.037) (0.051) (0.045) (0.037) Notes:Robuststandarderrorsarereportedinparentheses.Thedataconsistofannualobservationsforeachcitybetween1977and1986(1980excluded).Allregressionsincludevectorsofcityandyearfixedeffects.ThetablereportstheinteractioncoefficientsbetweenadummyvariableindicatingifthemetropolitanareaisMiamiandiftheobservationisdrawnfromthepost-Marielperiod.TheregressionsthatusetheCardoremploymentplaceboshave45observations;theregressionsthatusethesyntheticplacebohave18observations;andtheregressionsinthelastcolumnhave396observations.SeethenotestoTable6foradescriptionoftheweightingusedintheregressions.

56

Table8.Thedistributionofestimatedshort-runwageeffectsonthelogweeklywageofhighschooldropoutsacrossallfour-cityplacebos,1977-1986

Characteristics of distribution: March CPS CPS-ORG Mean -0.243 -0.089 Standard deviation 0.047 0.023 Statistical significance

Fraction of t-statistics above |1.6| 0.984 0.947 Fraction of t-statistics above |2.0| 0.939 0.845

Average employment growth of placebo cities within 0.5 standard deviations of Miami (N = 5,740)

Mean -0.282 -0.105 Fraction of t-statistics above |1.6| 0.998 0.933 Fraction of t-statistics above |2.0| 0.980 0.812

Employment growth for each placebo city within 0.5 standard deviations of Miami (N = 126)

Mean -0.333 -0.098 Fraction of t-statistics above |1.6| 1.000 0.833 Fraction of t-statistics above |2.0| 1.000 0.619

Actual impact using the Card placebo:

Coefficient -0.237 -0.054 Robust standard error (0.088) (0.026)

Actual impact using the employment placebo: Coefficient -0.374 -0.130 Robust standard error (0.078) (0.049)

Actual impact using the synthetic placebo: Coefficient -0.335 -0.227 Robust standard error (0.090) (0.071)

Notes:ThetablereportsthedistributionoftheinteractioncoefficientbetweenadummyvariableindicatingifthemetropolitanareaisMiamiandiftheobservationisdrawnfromthepost-Marielperiod.Theregressionswereestimatedseparatelyinallpossible123,410four-cityplacebos.Theregressionsuseannualobservationsforeachcityfrom1977through1986(excluding1980).Allregressionshave45observationsandareweightedbythesamplesizeusedtocalculatethemeanlogage-adjustedwageofhighschooldropoutsincityrattimet.

57

Table9.Distributionofwageeffectsrelativetothesyntheticplaceboforhypotheticalsupplyshocks

Dependent variable: Log wage of education group Characteristics of distribution: < 12 years 12 years 13-15 years ≥ 16 years A. March CPS Mean effect -0.003 -0.000 -0.006 -0.000 Standard deviation 0.163 0.071 0.099 0.072 Fraction of t-statistics above |1.6| 0.250 0.301 0.262 0.278 Fraction of t-statistics above |2.0| 0.167 0.205 0.185 0.182 Mariel wage impact with synthetic control:

Coefficient -0.335 0.114 -0.042 0.104 Robust standard error (0.090) (0.076) (0.116) (0.086)

Placement of Mariel effect:

Percentile in distribution across all years 3.0 94.8 33.2 93.2 Rank in 1980 treatment year 1/44 44/44 14/43 43/44

B. CPS-ORG Mean effect 0.001 0.000 0.002 -0.002 Standard deviation 0.104 0.049 0.065 0.053 Fraction of t-statistics above |1.6| 0.253 0.306 0.292 0.328 Fraction of t-statistics above |2.0| 0.154 0.218 0.194 0.214 Mariel wage impact with synthetic control:

Coefficient -0.227 0.042 0.071 0.052 Robust standard error (0.072) (0.021) (0.057) (0.061)

Placement of Mariel effect:

Percentile in distribution across all years 1.8 81.6 89.4 84.8 Rank in 1980 treatment year 1/44 37/44 38/44 36/44

Notes:Thepre-treatmentperiodlasts3years;thepost-treatmentperiodlasts6years.Eachregressionexcludestheyearofthetreatmentandhas18observations.Thereare774hypotheticalshocksdistributedacross43metropolitanareas(outsideMiami)fortreatmentyearsbetween1980and1997.Thepredictorsusedtocreatethesyntheticplaceboarethecity’srateoftotalemploymentgrowth,theratesofemploymentandwagegrowthfortheparticulareducationgroupinthe4-yearperiodprecedingthetreatmentyear.

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AppendixTableA-1.Weightsdefiningthesyntheticcontrol

MeasureofwageofhighschooldropoutsRank Metropolitanarea Actuallogweeklywage Age-adjustedlogweeklywage MarchCPS MarchCPS CPS-ORG1 SanDiego,CA 0.015 0.239 0.2342 Greensboro-WinstonSalem,NC 0.000 0.006 0.0003 KansasCity,MO/KS 0.560 0.010 0.0164 Anaheim-SantaAna-GardenGrove,CA 0.203 0.372 0.3965 Rochester,NY 0.004 0.159 0.1646 Miami-Hialeah,FL --- --- ---7 Nassau-Suffolk,NY 0.013 0.011 0.0138 SanJose,CA 0.009 0.043 0.0079 Albany-Schenectady-Troy,NY 0.006 0.012 0.01010 Boston,MA 0.005 0.008 0.01011 Milwaukee,WI 0.005 0.009 0.01012 Indianapolis,IN 0.008 0.007 0.00713 Seattle-Everett,WA 0.005 0.006 0.00814 Norfolk-VirginiaBeach-NewportNews,VA 0.005 0.008 0.00715 Philadelphia,PA/NJ 0.005 0.006 0.00816 Newark,NJ 0.004 0.005 0.00617 Tampa-St.Petersburg-Clearwater,FL 0.005 0.006 0.00618 Denver-Boulder-Longmont,CO 0.004 0.005 0.00619 Houston-Brazoria,TX 0.007 0.005 0.00520 Sacramento,CA 0.041 0.005 0.00221 Dallas-FortWorth,TX 0.007 0.005 0.00522 Portland-Vancouver,OR/WA 0.004 0.005 0.00523 Riverside-SanBernardino,CA 0.002 0.000 0.00724 Atlanta,GA 0.004 0.004 0.00525 Cincinnati-Hamilton,OH/KY/IN 0.007 0.004 0.00526 Washington,DC/MD/VA 0.005 0.004 0.00527 Detroit,MI 0.004 0.004 0.00528 FortWorth-Arlington,TX 0.005 0.004 0.00529 LosAngeles-LongBeach,CA 0.007 0.004 0.00430 Columbus,OH 0.002 0.004 0.00331 Buffalo-NiagaraFalls,NY 0.006 0.003 0.00432 Chicago-Gary-LakeIL 0.004 0.003 0.00433 St.Louis,MO/IL 0.004 0.003 0.00334 Bergen-Passaic,NJ 0.003 0.003 0.00335 Baltimore,MD 0.004 0.003 0.00336 Minneapolis-St.Paul,MN 0.004 0.003 0.00337 Cleveland,OH 0.003 0.003 0.00338 NewYork,NY 0.003 0.003 0.00339 Pittsburg,PA 0.002 0.003 0.00340 Birmingham,AL 0.003 0.002 0.00241 SanFrancisco-Oakland-Vallejo,CA 0.003 0.002 0.00242 Gary-Hammond-EastChicago,IN 0.004 0.002 0.00243 NewOrleans,LA 0.002 0.002 0.00144 Akron,OH 0.001 0.001 0.001Notes:Themetropolitanareasarerankedbythe1977-1980rateofemploymentgrowth.

Documents

The Wage Impact of the Marielitos: A Reappraisal