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Labour Economics
journalhomepage:www.elsevier.com/locate/labeco
Local labor demand and participation in social insurance programs
Asbjørn Goul Andersen, Simen Markussen
∗, Knut Røed
1The Ragnar Frisch Centre for Economic Research, Gaustadalléen 21, Oslo 0349, Norway
a r t i c le i n f o
JEL codes:
J23 J58 J65 H55 Keywords:
Disability insurance Program substitution Shift-share analysis Unemployment
a b s t r a ct
BasedonadministrativedatafromNorway,weexplorethe“grayarea” betweentherolesofunemployment- andtemporarydisability-insurancesbyexamininghowparticipationinthesetwoprogramtypesisaffectedby locallabordemandconditions.Locallabordemandisidentifiedbymeansofashift-shareinstrumentalvariables strategy,whereinitiallocalindustry-compositionisinteractedwithsubsequentnationalindustry-specificem- ploymentfluctuations.Ourresultsindicatethatlocallabordemandhasalargenegativeeffectonthepropensity toclaimdisabilityinsurance,which,forsomegroups,isremarkablysimilartoitseffectonthepropensityto claimunemploymentinsurance.Basedonthisfinding,wequestionwhetheritismeaningfultomaintainasharp distinctionbetweenthesetwoprograms.
1. Introduction
Socialinsuranceprogramsaretypicallydesignedsuchthattheydis- tinguishsharplybetweenunemploymentanddisabilityasthefounda- tionforclaims.Isthisdistinctionmeaningful?Forthemajorityofshorter spellsofunemploymentorsickness,theanswerisprobablyyes.Mostun- employmentinsuranceclaimsreflectlabormarketfrictions– itsimply takessometimeforpersonswhohavebecomeunemployedtofinda goodjobmatch.Andmostsicknessinsuranceclaimsariseduetosome short-termailmentwithnoconsequencesforfutureemploymentoppor- tunities.However,associalinsurancespellsbecomelonger,theultimate causesbehindtheclaimsoftenbecomemoreambiguous.Apersonmay beunemployedbecause,e.g.,amusculoskeletaldiseaseoralightmen- taldisordermakesitdifficulttocompeteforjobs.Andapersonmaybe considereddisabledbecauseexpectedproductivityistoolowtoensure realisticjobopportunities.Long-termsocialinsuranceclaimsmayalso resultfromacombinationofseverallabormarketbarriers,andalthough aclaimantisdeclaredeitherunemployedordisabled,(s)hemayinre- alitybeunemployedwithrespecttoonejob,disabledwithrespectto another,andperhapsunwillingwithrespecttoathird.Healthproblems mayof coursemakeitdifficulttoperformsome kindoftasks, while beingirrelevantforothers.
Existing empiricalevidenceindicates asignificant degree of sub- stitution between unemployment- and disability-relatedsocial insur- anceprogramutilization(Blacketal.,2002;AutorandDuggan,2003;
∗Correspondingauthor.
E-mailaddress:[email protected](S.Markussen).
1 ThisresearchhasreceivedsupportfromtheNorwegianMinistryofLaborandSocialAffairsthroughtheproject“Unemploymentindisguise.” Administrative registersmadeavailablebyStatisticsNorwayhavebeenessential.WethanktheEditorandananonymousrefereeforconstructivecommentsandsuggestions
Regeetal.,2009;Bratsberg etal., 2013;Maestasetal.,2015,2018; Charlesetal.,2018),andpointstoaconsiderableremainingworkca- pacityamongmarginaldisabilityinsuranceclaimants(Maestasetal., 2013; KostølandMogstad, 2014; Borghanset al.,2014; French and Song,2014).Theprobabilityofbecomingadisabilitybenefitclaimant risessharplyinresponseto(exogenous)jobloss.Andalthoughthepos- itiverelationshipbetweenlayoff anddisabilityrisktosomeextentre- flectsagenuineadversehealtheffectofjobloss,theimpactsidentifiedin theempiricalliteraturearesimplytoolargetomakethisplausibleasthe soleexplanation.InarecentUSstudy,Maestasetal.(2018)estimatethat 8.9%ofallawardsofSocialSecurityDisabilityInsurance(SSDI)benefits during2008–2012wasdirectlyinducedbytheGreatRecession.Based onNorwegianadministrativedatamergedwithrecordsonmasslayoffs identifiedfrombankruptcycourtproceedings,Bratsbergetal.(2013)es- timatethatmen’sriskofclaimingpermanentdisabilitybenefitsoverthe nextfewyearsmorethandoublesinresponsetoajobloss.Andcondi- tionalonhavingbeenlaidoff,theprobabilityofbecomingadisability benefitclaimantrisessteeplywiththelocalrateofunemployment.
Someoftheeffectsidentifiedintheliteraturearelikelytobecontext- dependent.Forexample,asaresultofindividualjobloss,itisproba- blethathealthproblemsthatweretoleratedwithinanexistingemploy- mentrelationshipbecomeabarrierinasearchfornewemployment.
AspointedoutbyAutorandDuggan(2003),jobdisplacementcanbe viewedasanegativeshocktothevalueofcontinuedlabormarketpar- ticipation.EmpiricalevidencefromNorwayalsoconfirmsthatdisplace- mentleadstosignificantearningslosses(Huttunenetal.,2011).Hence,
https://doi.org/10.1016/j.labeco.2019.101767
Received4July2019;Receivedinrevisedform12September2019;Accepted16September2019 Availableonline21September2019
0927-5371/© 2019TheAuthors.PublishedbyElsevierB.V.ThisisanopenaccessarticleundertheCCBY-NC-NDlicense.
(http://creativecommons.org/licenses/by-nc-nd/4.0/)
Fig.1. Fractionofadultpopulationwithhealth-relatedand unemployment-relatedbenefitsbytheendofeachyear1992–
2017.Source:KannandSutterud(2017,updatedin2018).
whileanexistingjobispreferredoverinactivity,itispossiblethatadis- abilitybenefitapplicationispreferredoversearchfornewemployment.
Inthepresentpaper,weexplorethegrayareabetweenunemploy- mentanddisabilityinmoredetailbyexamininghowtheparticipation indifferent typesofsocial insuranceprogramsandsubsequentlabor marketoutcomesarecausallyaffectedbylocalemploymentopportuni- ties.Ratherthanfocusingspecificallyonpersonsexposedtoindividual shocks,suchasajobloss,westudytheinfluenceoflabordemandon programparticipationpropensitiesforalladultindividuals.Inaddition, weexaminehowthesensitivityofprogramparticipationtolocallabor demandfluctuationsvarieswithrespecttoinitiallabormarketstate.
Norwayis a countrywithrelatively large fractionson disability- relatedsocialinsuranceprograms,butrelativelyfewonunemployment- relatedprograms.Overthepastdecades,therehasalsobeenasystem- aticshiftinthecaseloadawayfromunemployment-programstoward disability-programs.ThesepointsareclearlyillustratedinFig.1,which showsthefractionsoftheadultpopulationinNorwayclaimingthetwo typesofbenefitsyear-by-yearsince1992.Particularlyduringthe1990s, therewasaconsiderableincreaseindisability-relatedsocialinsurance claimsaccompaniedbyadeclineinunemployment-relatedclaims.And basedonthemostrecentnumbers,therearenowmorethanfourpersons ondisabilityinsuranceforeachpersononunemploymentinsurance.
Empiricalevidenceindicatesthatwhetheragivenlabormarketprob- lemisinterpretedbythesocialinsurerasahealthproblemorasanun- employmentproblemmayhaverealconsequencesintermsoflaterlabor marketoutcomes,asunemploymentprogramstendtobelessgenerous andalsomuchmoreactivation-orientedthandisabilityprograms.For example,Schreiner(2019)showsthatalocalsocialinsuranceoffice’s overalltendencytointerpretyouthproblemsashealth-relatedrather thanunemployment-relatedhasaconsiderablenegativeimpactonthe youths’futurelabormarketoutcomes.
Inthepresentpaper,weuseNorwegianadministrativeregisterdata toempiricallyassesstheinfluenceoflocallabordemandconditionson unemployment-anddisability-relatedsocialinsuranceclaims,respec- tively.Todothis,wedividethecountryintocommutingzones,andex- aminehowthecaseloadsofthetwoprogramtypesareassociatedwith locallabor demandconditionsbasedonvariationacrosscommuting- zone-by-yearcells.Torepresentasourceofexogenousvariationinlocal labordemand,weuseaBartik-typeshift-shareinstrumentthatinteracts theinitiallocal structureof employmentacross industriesatvarious pointsintime,withthesubsequentnational fluctuationsinindustry- specificemployment.Inrelationtotheexistingliterature,wemaketwo
novelcontributions.Thefirstisthatweidentifytheinfluenceoflabor demandfluctuationsforrepresentativepopulations,withoutrelyingon largeindividualoraggregateeconomicshocks;henceourresultsshould scorehighonexternalvalidity.Thesecondisthatweofferadirectcom- parisonoftheinfluencethatlabordemandexertsonthecaseloadsof disability-andunemployment-relatedsocialinsurances.Thisgivesusa naturalscaleagainstwhichtheeffectsondisabilityinsuranceprogram participationcanbemeasured.
Ourfindingsconfirmthatthereisindeedaconsiderablegrayarea between unemployment–anddisability-relatedinsurance claims. Al- thoughtheimpactoflocallabordemandconditionsontheprobabilityof claimingunemployment-relatedeconomicsupportislargerthanthecor- respondingimpactontheprobabilityofclaimingdisability-relatedsup- port,thelatterisfarfromnegligible,particularlywhenwetakeintoac- countthattransitionsintodisabilityinsurancetendtobehighlypersis- tent.Forexample,consideringthepopulationofnewlyemployedwork- ers,weestimate thatthefractionclaiminganunemployment-related benefitthreeyearslaterdecreaseswith0.83percentagepointsforev- erydemand-initiatedpercentagepointincreaseintheoveralllocalem- ploymentrate,whilethefractionclaimingadisability-relatedbenefit decreases by0.25percentage points.Conversely, havingalready en- teredunemploymentordisabilityinsurance,thesameone-percentage pointincreaseinlocallabordemandisestimatedtoincreasethefrac- tionhavingreturnedtoworkafterthreeyearsby3.0percentagepoints forunemploymententrantsandby1.9percentagepointsfordisability insuranceentrants.Hence,theinfluenceoflabordemandisconsiderable forthecaseloadsofbothprograms.
2. Institutions
TheNorwegiansocialinsurancesystemmakesadistinctionbetween unemployment-related andhealth/disability-relatedneedsforincome support;seeTable1.Unemployedindividualsmayclaimunemployment insurance(UI) ifpastearningsexceedacertainthreshold,ormeans- tested social assistance(SA);in both casesconditionalon activejob searchandwillingnesstoacceptanysuitable joboffer.Ifdeemedto beinneedofadditionalqualificationorplacementservicesforreasons otherthanahealthproblem,itisalsopossibletoparticipateinactive labormarketprograms(ALMP)orinamorecomprehensive“qualifica- tionprogram” (QP)offeringafulltimeactivitywithsomeincomesup- port.Unemploymentinsuranceprovidesareplacementrateof62.4%up toanearningslevelcorrespondingtoapproximately108%ofaverage
Table1 IncomesupportprogramstargetedatunemployedjobseekersandpersonswithdisabilityorhealthproblemsinNorway. MaineligibilityrequirementsReplacementlevelMaximumduration Unemployment-relatedinsuranceprograms Unemploymentinsurance(UI)i)Laborearningsinthepreviouscalendaryearexceed1.5B(or3Boverthepast threeyears) ii)Willingnesstosearchactivelyfornewemploymentandacceptsuitablejoboffers
62.4%ofpreviouslaborearningsforprevious annualearningsupto6B2years Socialassistance(SA)i)Willingnesstosearchactivelyfornewemploymentandacceptsuitablejoboffers ii)NocoveragebyothersocialinsuranceprogramsCoverageofbasicneedsonly.Means-tested againsthouseholdincomeandwealth. Nolimit Qualificationprogram(QP)i)Willingnesstoworkorparticipateinafull-timeprogram ii)Workcapacityseverelyreducedbycausesthatdonotqualifyfordisability insurance
2Bperyear2years Activelabormarketprogram(ALMP)i)Willingnesstoworkorparticipateinafull-timeprogram ii)ParticipationinofferedactivityApproximately1Bperyear(taxfree),plus documentedparticipation-relatedexpensesNospecificlimit Health/disability-relatedinsuranceprograms Temporarydisabilityinsurance(TDI)i)Workcapacityreducedbyatleast50%duetohealthproblems ii)Willingnesstoparticipateinprogramsaimedatrehabilitation66%ofpreviousearningsforpreviousearningsup to6B.Minimumbenefitof2B.3years Permanentdisabilityinsurance(PDI)i)Workcapacityreducedbyatleast50%duetohealthproblems ii)Norealisticprospectsforreturntowork66%ofpreviousearningsforpreviousearningsup to6B.Minimumbenefitof2B.Nolimit Note:Bisshortcutforthe“Basicamount”,whichisanimportantmonetaryparameterintheNorwegiansocialinsurancesystem.In2019itisapproximatelyNOK100,000,whichisaround18%ofaverage full-time-full-yearearningsinNorway.Thetabledescribesthecurrent(2019)system.Someoftheparametershavebeensubjectedtochangesduringtheperiodcoveredbythispaper.
full-time-full-yearearningsinNorway;seeTable1.UIbenefitsarecon- ditionedontheunemploymentspellbeinginvoluntary,however,and ifaUIapplicantquitapreviousjobvoluntarilyorwasfiredforcause, thereisa12-weekembargoperiodonUIentitlements.
Personswhoareinneedofincomesupportduetodisabilityorother health problemsmayclaimtemporaryor permanentdisabilityinsur- ance(DI).Foremployees,thereisfirstaone-yearentitlementtosick- pay(with100%replacement),andduringthisperioditisalsoillegal tofiretheworkerwithreferencetothesickness(employmentprotec- tionregulationsapply).Afteroneyearofabsence,itisallowedtofirea workerwhoisunabletoreturntoregularworkduetosickness.Itisthen possible fortheworkertoapplyfortemporaryorpermanentdisabil- itybenefits,withatypicalreplacementratioaround66%.Personswho arenotemployedcanapplyfordisabilityinsurancedirectly,andthere isnorequirementofpreviousemploymenteither.Forpersonswithout previousworkexperience,thebenefitlevelissettoafixedminimum level;seeTable1.Forallapplicants,thepreconditionisthatthework capacityisreducedbyatleast50%asadirectconsequenceofdisabil- ity/impairment.Thismustbecertifiedbyanauthorizedphysician,but thefinaldecisionismadebythesocialsecurityadministration(SSA).In mostcases,DIclaimantswillfirstbeenrolledintothetemporarydisabil- ityinsuranceprogram(TDI),which(currently)hasamaximumduration ofthreeyears.Duringthisperiod,variousrehabilitationmeasureswill beconsideredandpossiblytriedout.WhenTDIbenefitsareexhausted, manyclaimantsmoveontothepermanentdisabilityinsurance(PDI) program,fromwhichthereisalmostnoprospectsforreturningfullyto thelabormarket.ForamorethoroughdescriptionoftheNorwegianDI system,seeFevangetal.(2017).
Atthefaceofit,theseinsurancesthuscoverincomelossescaused byverydifferentcircumstances.However,withrespecttotheDIeligi- bilityassessmentof whetherornot theworkcapacityis reducedby at least 50%due tohealth problems, thelegislationallows theSSA to take the applicant’s current realistic work opportunities into ac- count.Thisrepresentsapossiblechannelwherebylabordemandcon- ditionsmayinfluencetheassessmentofdisabilityinsuranceeligibility.
Schreiner(2019)presentsevidencethatthereisconsiderableroomfor caseworkerjudgement,andthatscreeningpracticesvaryconsiderable acrosstimeandspace.
Itisnotablethatwhileeligibilitytounemploymentinsuranceiscon- ditionalon(andproportionalto)previouslaborearnings,disabilityin- surancecanbeclaimedevenwithoutpreviousworkexperience.Fordis- abilityclaimants,thereisalsoaminimumbenefitlevel,currentlycor- respondingtoapproximately36%ofaveragefull-time-full-yearearn- ingsinNorway.Giventheapparentscopeforphysicianandcaseworker judgementregardingtheassessmentof thereduced workcapacity, it appearsplausiblethattheassignmentofindividualstothedifferentpro- gramstosomeextentisinfluencedbythedegreeofeconomiccoverage theyprovide.
3. Dataanddescriptiveevidence
Ourempiricalanalysisisbasedonadministrativeregisterscovering allresidentsinNorwayovertheperiodfrom1999through2016.The primarypurposeofouranalysisistoidentifyandestimatethecausal influenceof labor demand conditionson theprobability of claiming unemployment-relatedanddisability-relatedsocialinsurancebenefits.
Inordertodothat,weneedexogenousvariationinlabordemandcon- ditions.Suchvariationclearlyexistsacrosslocallabormarketsaswell asovertime.However,itisnotgenerallyobserved.Naturalcandidates forrepresentinglabordemandfluctuationsinanempiricalmodelare thelocalemploymentorunemploymentrates(orothermeasuresofla- bormarkettightness).However,thesearedeterminedthroughthein- tersectionofdemandandsupply;hence,theycannotbeuseddirectly asexplanatoryvariablesinamodelintendedtoisolatetheinfluenceof labordemand.Acrossspaceandtime,therewillbeasortofmechanic relationshipbetweentheratesofsocialinsuranceprogramparticipation
andtherateofemployment(asthesestatestosomeextentaremutu- allyexclusive);butwithoutadditionalinformationwecannotidentify thedirectionofcausality.Forexample,ifweobservethatalocallabor marketatsomepointintimehasaparticularlylowemploymentrate andahighrateofdisabilityprogramparticipation,westilldon’tknow whetheritisthelowemploymentratethatcausesthehighdisability rateorviceversa.
Todealwiththis simultaneityproblem, wewill usea shift-share strategy in which we interactnational industry-specific employment fluctuationswithsomeinitialspatialdifferences inindustrycomposi- tion.Instrumentsofthistypehavebeenusedfrequentlyinthelitera- ture;see,e.g., Bartik(1991),BlanchardandKatz(1992),Boundand Holzer (2000), Autor and Duggan (2003), and Bartik (2015). They isolate the employment fluctuations following directly from the na- tionalexpansion andcontractionof particular industries,caused by, say,changesintechnology,tradeliberalization(orexchangeratefluc- tuations),publicexpenditures,orconsumerdemand.Thecentraliden- tifyingassumptionisthenthattheinitialindustrysharesdonotpre- dictfutureoutcomesthroughotherchannelsthanthosereflectedinthe nationalfluctuations;seeGoldsmith-Pinkhametal.(2019).Toopera- tionalizethis empiricalstrategyin thecontextof ourdata, we need tostructurethedataintermsofbase-years(usedtodefinetheinitial industrycomposition)andoutcome-years.Asexplainedinmoredetail below,wewillinthemainpartoftheanalysisdothisbyallowinga three-yeartime-periodbetweenbase-yearsandoutcome-years.Inaddi- tion,weneedtodefinelocallabormarkets.BasedonBhuller(2009), wedividethecountryinto46suchlocalmarkets,orcommutingzones.
Theoverallvariationin labordemand exploitedinouranalysisthus comesfrom690combinationsof15differentbase-yearsand46differ- entcommutingzones.WealsoneedtoassignallemployeesinNorway toparticularindustries.Suchinformationisavailableinadministrative registers,basedonafive-digitindustrycode.Intotal,thereare648dif- ferentindustriesinNorway.However,manyoftheseareverysmall,and perhapslocatedonlyinafewcommutingzones,hence,weaggregatein- dustriessuchthatallindustry-categorieshaveatleast5,000employees onaverageatanannualbasis.Thisisdonebyfirstincludingallfive-digit codeswithatleast5,000employees,thendoingthesameforfour-digit codes,andsoon.Asaresult,weendupwith171uniqueindustries.
Fig.A1inAppendixAprovidesacompactdescriptionofthelongitu- dinalandcross-sectionalvariationinemploymentacrossindustriesin Norway.Withaprominentexceptionfortheoilandgasindustry,there hasbeenconsiderabledeclineintheemploymentshareofproduction industriesoverthe1999–2016period.Astheimportanceofthesein- dustriesalsovaryalotacrosscommutingzones,thisis animportant exogenoussourceofvariationinlabordemandconditions.Thelargest growthinemploymenthascomeintheconstructionindustriesandin theservicesectorsrelatedtohealthandeducation.Fortheseindustries, thevariationinemploymentsharesismuchsmaller,yetfarfromnegli- gible.
Tostudytheinfluenceoflabordemandonsocialinsuranceprogram participation,wecombineinformationfromseveraladministrativereg- isterstoassignunique monthlylabor market statestoall adult(age 18–61)residentsin Norway.Our analysisfocuses onfourstates;i.e., employment,participationinadisability-relatedsocialinsurancepro- gram,participationinanunemployment-relatedprogram,andeduca- tion,respectively.Inordertocharacterizeeachperson’smaineconomic activity,thestatesaredefinedasmutuallyexclusive.Incaseswherepeo- pleapparentlyhavebelongedtomultiplestateswithinthesamemonth, uniquenessisachievedapplyingahierarchy,whichranksstatesafter theirpresumeddistancetothelabormarket.Thisimpliesthathealth- relatedbenefitclaimsareprioritizedoverunemployment,whichisagain prioritizedovereducation,andfinallyemployment.Thishierarchyhas theadditionaladvantageofprioritizingdatasourceswherethemonthly informationisconsideredmostreliable.Thedefinitionoflabormarket statesisdescribedinmoredetailinAppendixB.
Weconstructtwotypesofdatasets.Thefirstcontainsthecomplete stockofindividuals,withafine-grainedrecordoflabormarketstatesby Januaryeachyear.Thesedataareagaindividedintodifferentgroups dependingoninitialstate.Thesecondtypeofdatasetcontains,foreach year,newentrantsintoeitheremployment,unemployment-relatedin- come support,ortemporary disabilityinsurance.Anewentrant toa particularstateisdefinedasbeinginthatstateinagivenmonth,while nothavingbelongedtothatstateduringthepreviousthreemonths.By focusingonentrants,wedirectattentiondirectlytothosewhosesub- sequentlabormarket performancepresumablyismost sensitivewith respecttolabordemandconditions.
ThestructureofthedatasetsisillustratedinTable2.Intotal,there arealmost38millionobservationsdividedbetween3.6millionindi- viduals,and66%oftheseobservationsstartoutwithemploymentin thebase-year;seeColumnI.Amongthem,87%arestillinemployment threeyearslater,2%havebecomeunemployed,and3%havebecome disabled;seeColumnIV.Employmentislessstableforthenewlyem- ployed(ColumnV),andtheirriskofbecomingunemployedordisabled isalsomuchhigher.
Althoughthedatacontaininformationaboutindividualoutcomes, thevariationinlabor demandconditionscomesfromthe690differ- ent combinations of base-years and commuting zones. Hence, most of theanalysis can be donebasedon aggregates computed foreach commuting-zone-by-yearcell.Beforewepresentourempiricalmodel, weprovideadescriptivepictureoftherelationshipbetweenfractions belongingtothethreekeystatesofemployment,unemployment,and disabilityinsuranceintherespectivebase-years.Forthispurpose,we buildonthedatacontainingalladultsdescribedinTable2,ColumnI.
TheuppertwopanelsofFig.2firstshowthatthereisastrongnegative relationshipbetweenlocalemploymentratesandbothunemployment- (panel (a))anddisability-related(panel (b))insuranceclaims.Thisis not surprising, given that such claims by construction implies non- employment. Therelationshipsarenotentirelymechanic,though,as approximately20%ofthepopulationdoesnotbelongtoanyofthree statesofunemployment,disability,andemployment;seeTable2.The fourlowerpanelsillustratethatthecross-sectionalvariation(panels(c) and(d))inallthreeratesaremuchlargerthanthelongitudinalvariation (panels(e)and(f)).Theyalsoindicatethatwhilelongitudinalvariation inemploymentismoststrongly(negatively)associatedwithparticipa- tion inunemployment-related insuranceprograms, itscross-sectional variation ismost stronglyassociated withparticipation indisability- relatedprograms.
Panel(a)inFig.3thenfocusesmoredirectlyontherelationshipbe- tweentheratesofunemployment-relatedanddisability-relatedclaims.
Atthefaceofit,thereisapositiverelationshipbetweenthesetworates atthecommuting-zone-by-yearlevel;seetheupwards-slopingstapled regressionline.However,whenweinsteadlookattherelationshipsbe- tweenthetwocaseloadsamonglocalareaswithsimilaremployment rates,acompletelydifferentpatternemerges.Then,thereisaconspic- uousnegativerelationshipbetweentheratesofunemploymentanddis- ability.Again,itisworthnotingthatthispatternisnotpurelymechanic.
Toillustratethispoint,panels(b)and(c)inFig.3showthecorrespond- ingrelationshipsbetweentherespectivelocalfractionsofsocialinsur- anceprogramparticipationandthefractionbelongingto“other” non- employmentstates,basedonexactlythesamegroupingofemployment ratesasusedinpanel(a).2Inthesegraphs,thesystematicandtidypat- ternsdisplayedinpanel(a)appeartobecompletelyabsent.Although thisdescriptiveevidenceisfarfromconclusive,itmaypointtowardtwo suppositions;first,thatunemploymentanddisabilityprogramparticipa- tionaredrivenbysomecommondeterminant(e.g.,cyclicalfluctuations intheleveloflabordemand),andsecond,that,giventheleveloflabor
2“Other” non-employmentstatesincludeeducation,homemaking,periods spentoutsidethecountry,andinactivity.
Table2
Dataanddescriptivestatistics.
The complete stock by January each year Entrants to…
All Employed Unemployed Disabled Employ-ment Unemployment Temp. disability
I II III IV V VI VII
N 37 939 858 25 554 728 1 280 145 3 791 759 4 469 054 1 919 349 688 913
Female 0.49 0.44 0.43 0.57 0.53 0.45 0.55
Age 38.2 40.6 35.5 44.2 29.5 33.6 39.7
Educational attainment
Compulsory 0.36 0.30 0.60 0.66 0.33 0.50 0.54
High school 0.33 0.35 0.27 0.22 0.37 0.31 0.29
College 0.30 0.33 0.13 0.12 0.29 0.15 0.16
Labor earnings last year (B) 4.4 6.0 1.8 0.7 2.8 2.4 2.2
Immigrant low-income country 0.10 0.09 0.25 0.08 0.11 0.21 0.11
Immigrant high-income country 0.01 0.00 0.01 0.00 0.01 0.01 0.00
State in base-year
Employed 0.66 1.00 0.00 0.00 1.00 0.00 0.00
Unemployed 0.04 0.00 1.00 0.00 0.00 1.00 0.00
Disability insurance 0.09 0.00 0.00 1.00 0.00 0.00 1.00
In education 0.15 0.00 0.00 0.00 0.00 0.00 0.00
State in outcome-year (three years later)
Employed 0.69 0.87 0.48 0.10 0.70 0.59 0.28
Unemployed 0.03 0.02 0.23 0.02 0.05 0.16 0.04
Disability insurance 0.12 0.03 0.14 0.82 0.04 0.11 0.59
In education 0.10 0.05 0.06 0.01 0.15 0.07 0.02
Note:Theentityofobservationisperson-year.AllresidentsinNorwayareincludedforeachbase-year1999–2013,providedthattheyarebetween 18and58yearsofageintherespectivebase-years(columnI)andthattheysatisfytheinitialstatecriteriaindicatedinthecolumnheads(columns II-VII).IncolumnsI-IV(thestocksamples),base-yearstateisrecordedinJanuaryeachyear.IncolumnsV-VII(theentrantsamples),base-year stateisrecordedinthemonthofentry.Thestateintheoutcome-yearisinbothcasesrecordedexactlythreeyearslater.Theunemployedand disabilityinsurancestatescorrespondtothecategorizationusedinTable1,suchthatunemploymentcomprisesUI,SA,QP,andALMP,and disabilityinsurancecomprisesTDIandPDI.
demand,thereisanimportantelementofsubstitutionbetweenthetwo programtypes.
4. Empiricalstrategy
Toestablishmoreconclusiveevidenceregardingthe“grayarea” be- tweenunemploymentanddisabilityinsurances,wenowsetupamore formalstatisticalmodelaimedatidentifyingandestimatingtheinflu- encethatlabor demandactuallyhasonthetwocaseloads.Usingthe sevendifferentsamplesdescribedinTable2,weexaminefourdiffer- entoutcomes,alldefinedatthecommuting-zone-by-yearlevel:i)the fractioninemployment,ii)thefractioninunemployment-relatedinsur- ance,iii)thefractionindisability-relatedinsurance,andiv)thefraction ineducation.
Todescribeourregressionmodels,weneedsomenotation.Letthe subscriptbindicatethebase-yearandlettindicatetheoutcome-year.
Inthestocksample,thebase-yearobservationsaredefinedintermsof theJanuaryrecordseachyear(1999–2013),whereasintheentrantsam- plesitisdefinedintermsofrecordscorrespondingtothemonthofentry.
Theoutcome-yearobservationsareinthemainpartofouranalysismea- suredexactlythreeyearslater(2002–2016).However,inAppendixD, wealsopresentresultsforoutcome-yearsmeasuredfromjustoneand uptosevenyearsafterthebase-year.Thesubscriptzindicatescommut- ingzone,whichalwaysreferstothecommutingzoneoccupiedinthe base-year.
Let𝑦𝑠𝑧𝑡bethefractionoftherespectivebase-yearpopulationincom- mutingzonezthatbelongstoastatesintheoutcomeyeart.Abstracting fromtheobviousproblemthatlocallabordemandisintrinsicallyunob- served,wewouldhavelikedtoregresseachoutcomeonthelevelof labordemand,whilecontrollingforinitialconditionsandthecomposi- tionofindividualsunderstudy;i.e.:
𝑦𝑠𝑧𝑡=𝐲′𝐳𝐛𝛑+𝐱′𝐳𝐛𝛄+𝛽𝐿𝐷𝑧𝑡+𝜀𝑧𝑡, (1) where𝐿𝐷𝑧𝑡is ameasureoflocallabor demandincommutingzonez intheoutcome-yeart,𝐲𝐳𝐛isavectorcontainingthestate-specificpopu- lationsharesmeasuredinthebase-year,includingthebase-yearvalue
ofthedependentvariable(𝑦𝑠𝑧𝑏),and𝐱𝐳𝐛isavectorofaverageindividual characteristicswithinthecommutingzone’sbase-yearsample(gender, age,education,immigrantstatus,andearnings;allmeasuredin(orprior to)thebase-year).3
Ourprimaryinterestliesintheimpactoflocallabordemand;i.e., 𝐿𝐷𝑧𝑡.However,aspointedoutabove,labordemandisunobserved.A naturalproxyforlabordemandistheoverallemploymentrateinthe commutingzoneatthetimeofoutcomemeasurement.However,inor- dertoisolatetheexogenousfluctuationsduetovariationsinlaborde- mand,weneedavalidinstrument;i.e.,weneedavariablethataffects thelocalemploymentratethroughachanneloflabordemand,butoth- erwisesatisfiesanexclusionrestrictionwithrespecttoEq.(1).Weuse aBartikinstrumentofthefollowingkind
𝑧𝑧𝑡=
∑𝐽
𝑗=1𝑤𝑧𝑏𝑗(𝐿𝑡𝑗−𝐿𝑏𝑗)
𝑁𝑧𝑏 , (2)
where𝑤𝑧𝑏𝑗iscommutingzonez’sfractionofemployeeswithinindustry jinbase-yearb,(𝐿𝑡𝑗−𝐿𝑏𝑗)isthetotalchangeinthenumberofemploy- eesinindustryjfromthebase-yeartotheoutcome-yearinthewhole
3To control appropriately for variations in initial conditions across commuting-zone-by-yearcells,thevector𝐲𝐳𝐛containsamorefine-grainedstate spacethantheoutcomevariables;i.e.,thefractionsbelongingtoi)full-timeem- ployment,ii)part-timeemployment,iii)self-employment,iv)parentalleave,v) sick-pay,vi)unemploymentinsuranceorparticipationinactivelabormarket program,vii)socialassistanceorqualificationprogram),viii)temporarydis- abilityinsurance,andix)permanentdisabilityinsurance(seetheAppendixB foramoredetaileddescriptionofthestate-space).Thevector𝐱𝐳𝐛containsthe followingvariables:i)thefractionoffemales,ii)thefractionwithhigh-school (uppersecondary)education,iii)thefractionwithcollege/universityeduca- tion,iv)thefractionsbelongingtodifferent5-yearageintervals,v)thefraction ofimmigrantsfromlow-incomecountries,vi)thefractionofimmigrantsfrom high-incomecountries,andvii)averagelaborearningsintheyearpriortothe base-year.
Fig.2. Observedbase-yearemploymentrates, andratesof participationin unemployment- related anddisability related insurance pro- grams.
Note: Panels(a) and (b) contain 690 data- points showing the indicated rates across commuting-zones-by-year.Panels(c)and(d) contain46data-pointsshowingtheindicated year-averages across commuting zones. Pan- els(e)and(f)contain15data-pointsshowing theindicatingcommuting-zoneaveragesacross baes-years(1999–2013).Thedottedlinesshow (unweighted) linearregression linesthrough therespectivedata-points.
country,and𝑁𝑧𝑏isthesizeoftheadultpopulationincommutingzone zinthebase-year.
Theinstrument𝑧𝑧𝑡isthusthepredictedchangeinthelocalemploy- mentratefromthebase-year totheoutcome-year,based onthena- tionalchangesintheindustry-specificemploymentpatternsonly,and measuredrelativetothesizeofthebase-yearpopulation.Takenatface value,theinstrumentin(2)alsoincorporatesnationalchangesinthe overallemploymentrate,which maystemfrom fluctuationsinlabor supplyaswellasdemand.Hence,toensurethattheidentifyinginforma- tionprovidedbytheinstrumentencompassestheidiosyncraticchanges relatedtoindustry-compositiononly,wewillcontrolforoutcome-year fixedeffects.Inaddition,wecontrolforcommuting-zonefixedeffects toensurethatanystablecorrelationbetweentheinitialindustrystruc-
tureandlaborsupplybehavioracrosscommutingzonesisnotpicked upbytheinstrument.Finally,sincethelocalemploymentrateinstru- mentedby𝑧𝑧𝑡maydeviatefromtheemploymentrateobservedwithin thesamplesunderstudy,wealsocontrolforthebase-yearvalueofthe instrumentedemploymentrate.
Thebaselinetwo-stageleastsquares(2SLS)modelsweestimatethus havethefollowingform:
𝑦𝑧𝑡=𝛼𝑡+𝛿𝑧+𝐲′𝐳𝐛𝛑+𝜆𝑒𝑧𝑏+𝛽 ̂𝑒𝑧𝑡+𝐱′𝐳𝐛𝛄+𝜀𝑧𝑡, (3) where𝛼𝑡aretheyear-fixedeffects,𝛿𝑧 arethecommuting-zone-fixedef- fectsand𝑒𝑧𝑏istheemploymentrate(age25–60)incommutingzonezin
Fig.3.Cross-plotsoffractionsbelongingtodifferent statesinthebase-year.Commuting-zone-by-yearcells.
Note:There are690data-points ineachpanel, and eachdata-pointshowstheindicatedratesinapartic- ularcommutingzoneinaparticularyear.Thedashed regressionlinesshowthelinearregressionthroughall points,whereasthesolidlinesshowthe(unweighted) linearregressionsthroughpoints satisfying theem- ploymentconditionsindicatedinthelegend.
thebase-year.4and̂𝑒𝑧𝑡isthecorrespondingpredictedemploymentrate fortheoutcome-yearbasedonthefirststageequation
𝑒𝑧𝑡=𝜙𝑡+𝜑𝑧+𝐲′𝐳𝐛𝛕+𝜃𝑒𝑧𝑏+𝐱′𝐳𝐛𝛋+𝜇𝑧𝑧𝑡+𝜁𝑧𝑡. (4) Weestimatethemodelusingthe690commuting-zone-by-yearob- servations,withweightsreflectingthenumberofindividualobserva- tionsbehindeachdatapoint.
Whilewebuildonthismodelinthepresentationofresultsinthe nextsection,weshowinSection6andinAppendixEthattheresults arerobustwithrespecttoanumberofalternativespecifications.These includetheuseofalternativecontrolvariables(e.g.,allowingforlocal lineartimetrends)andtheuseofamodifiedinstrumentwherethein- fluenceofowncommutingzoneinnationaltrendsisremoved(i.e.,a
4 Notethatthebase-yearemploymentrate𝑒𝑧𝑏=
∑𝐽 𝑗=1𝑤𝑧𝑏𝑗𝐿𝑏𝑗
𝑁𝑧𝑏 ;conf.Eq.(2).
“leave-out” Bartikinstrument).Theyalsoincludetheuseofindividual data(instead ofcommuting-zone-by-yearcells),which allowsforthe inclusionofindividual-fixedeffects.Therobustnessanalysisalsoincor- poratesestimationofadifferentmodel,wheretheyearsusedtocompute initialindustryweightsarekeptconstantacrossdifferentbase-years,fa- cilitatingtheinclusionofcommuting-zone-by-weight-construction-year fixedeffects.Finally,wepresenta“placebo” analysiswhereweusepast insteadoffutureoutcomesasdependentvariablesinthebaselinemodel.
5. Mainresults
Acriticalpreconditionforthisempiricalstrategytoworkisthatthere isasufficientlystrongfirststage;i.e.,thatthenationalfluctuationsin industry-compositionreallyhaveasubstantialimpactonlocalemploy- mentpatterns.Fig.4,panel(a)firstassessesthisgraphically,byplotting therealizedchangeinlocalemploymentrate𝑒𝑧𝑡againstitsprediction
Fig.4. Crossplotsofpredictedandobservedchangeinlocalemploymentratesfromthebase-yeartotheoutcome-year.Commuting-zone-by-yearcells.
Note:Panel(a)showspredictionswithoutanycontrolvariables,whereaspanel(b)showspredictionswithcontrolsforregionandyear.Circlesizesareproportional tothenumberofobservationsbehindeachdata-point.
Table3
FirststageestimatesandF-tests.
The complete stock by January each year Entrants to…
All Employed Unem-ployed Disabled Employment Unemployment Temp. disability
I II III IV V VI VII
Local employment rate 0.118 ∗∗∗(0.032)) 0.128 ∗∗∗(0.037) 0.158 ∗∗∗(0.041) 0.125 ∗∗∗(0.038) 0.152 ∗∗∗(0.041) 0.156 ∗∗∗(0.041) 0.124 ∗∗∗(0.035)
F-statistic excluded instrument 13.39 11.92 15.11 10.76 13.69 14.46 12.63
R sq. adj. 0.968 0.975 0.971 0.973 0.971 0.971 0.977
# Observations 690 690 690 690 690 690 690
# Person-years 37 939 858 25 554 728 1 280 145 3 791 759 4 469 054 1 919 349 688 913
Note:EachcoefficientinthistableisaresultofaseparateweightedfirststageregressionbasedonEq.(4).Standarderrorsareclusteredatcommuting-zone.∗/∗∗/∗∗∗ indicatesstatisticalsignificanceatthe10/5/1percentlevels.
̂𝑒𝑧𝑡.Therelationshipindeedappearsstronglypositive.However,asar- guedabove,inthemodelweneedtocontrolforbothyear-fixedand commuting-zonefixedeffectstoensurethatweisolatetheinfluences oflabordemand;hencethevariationactuallyexploitedinthemodelis thevariationremainingafterhavingcontrolledforthesefactors.Thisis illustratedinFig.4,panel(b).Therelationshipthenbecomesconsider- ablyweaker,butstillpositive.
Table3presentsthefirststageestimationresultsfromEq.(4).They showthattheinstrumentissufficientlystrongforvalidstatisticalin- ferencewithinallthesamplesdescribedinTable2.Havingconfirmed sufficientstrengthoftheinstrument,wenowturntothemainresults;
seeTable4.Forcomparison,wepresentcorrespondingordinaryleast squares(OLS) estimatesinAppendixC.Inmostcases,the2SLSesti- matesareabitlargerthantheOLSestimates.There aretworeasons whyOLSand2SLSestimatesmaydiffer.The firstisdirectly related tothesimultaneityproblemdiscussedabove,i.e.thattheresidualin Eq.(3)iscorrelatedwiththelocalemploymentrate.Asaparticularly highemploymentratemayindicatesomefavorablelaborsupplydevel- opmentsintheregion,thisislikelytoexaggeratetheinfluenceoflabor demand.Thesecondreasonisthattheobservedemploymentrateisan imperfectmeasureoflabordemand,andthussubjectedtomeasurement error.ThiswilltendtobiastheOLSestimatestowardzero.Inourcase,
itappearsthat thelattersourceof biasin most casesdominatesthe former.
Returningtothe2SLSestimatesinTable4,ColumnIfirstprovides the results obtainedfor thefullstock sample. Asexpected, theesti- matedeffectontheemploymentrateinthefullsampleisapproximately equalto1.Thisparticularresultisalmosttautological,asthepopula- tionbehindthisestimateisalmostthesameasthepopulationbehindthe firststage.However,theestimatesregardingthestatesthatthehigher employmentratesubstitutesforareofmore substantiveinterest.We notethata1-percentagepointdemand-drivenincreaseinthelocalem- ploymentratereducesthelocalunemploymentrateby0.68percentage points,andtherateofdisabilityinsuranceprogramparticipationby0.23 percentagepoints.Theestimatesalsoindicateaslightreductioninthe probabilityofbeingineducation,butthiseffectisnotstatisticallysig- nificant.
Itmayalsobeof someinteresttosee howtheeffectsreportedin ColumnIvaryacrossdifferentdemographicandeducationalgroups.To shedlightonthis,wehaveestimatedthemodelseparatelyfor4differ- entagegroupsandfor12differentcombinationsofageandeducational attainment.Foreaseofcomparison,wepresenttheresultsfromthisex- ercisegraphically;seeFig.5.Itisclearthattheeffectsoflabordemand fluctuationsarelargestfortheyoung,andamongthem,thereisaten-
Table4
Secondstageestimates:Effectsoflocallabordemandonthefractionsbelongingtodifferentstatesinoutcome-year.Byinitialstate.
The complete stock by January each year Entrants to…
All Employed Unemployed Disabled Employment Unemployment Temp. disability
I II III IV V VI VII
Employment 1.057 ∗∗∗
(0.115) 0.712 ∗∗∗
(0.144) 3.519 ∗∗∗
(0.363) 0.614 ∗∗
(0.260) 1.659 ∗∗∗
(0.293) 3.032 ∗∗∗
(0.411) 1.911 ∗∗ (0.748) Unemployment-related
insurance
− 0.683 ∗∗∗ (0.096)
− 0.609 ∗∗∗ (0.090)
− 2.203 ∗∗∗ (0.544)
0.056 (0.089)
− 0.826 ∗∗∗ (0.152)
− 2.074 ∗∗∗ (0.482)
− 0.043 (0.212) Disability insurance − 0.231 ∗∗∗
(0.065)
− 0.017 (0.062)
− 0.858 ∗∗ (0.373)
− 1.028 ∗∗∗ (0.345)
− 0.248 ∗∗∗ (0.082)
− 0.853 ∗∗∗ (0.219)
− 2.127 ∗∗∗ (0.799)
Education − 0.147
(0.115)
− 0.082 (0.096)
− 0.045 (0.180)
0.038 (0.050)
− 0.462 (0.291)
0.153 (0.162)
0.010 (0.162)
# Observations 690 690 690 690 690 690 690
# Person-years 37 939 858 25 554 728 1 280 145 3 791 759 4 469 054 1 919 349 688 913 Note:Eachcoefficientinthistableisaresultofaseparateweighted2SLSregressionbasedonEqs.(3)and(4).Standarderrorsareclusteredatcommuting zone.∗/∗∗/∗∗∗indicatesstatisticalsignificanceatthe10/5/1percentlevels.
Fig.5. Secondstageestimates:Effectsoflocallabordemandontheprobabilityofbelongingtodifferentstatesinoutcome-year.Completestocksamplebyageand educationalattainment.
Note:Theagegroupingisshownonthehorizontalaxis.Thethreeeducationalgroupsindicatedinthelegendaredefinedasfollows:Comp.edu:compulsoryeducation onlyorincompletehigh-schooleducation;HS:highschool(uppersecondary)education;College:College/Universitydegree.Eachcoefficientisaresultofaseparate weighted2SLSregressionbasedonEqs.(3)and(4).Pointestimatesareshownwith95%confidenceintervals.
dencythattheeffectsarelargestforthosewithleasteducation.Itisalso fortheuneducatedyoungpeoplethatweseethestrongestevidencethat labordemandconditionsinfluencedisabilityprogramparticipation.Ef- fectsoncontinuededucationarealmostexclusivelyconcentratedamong theyoung.
Asitturnsout,itisnotprimarilyageoreducationalattainmentper sethatdeterminesthesizeoflabordemandeffects,butrathertheini- tialstate,whichishighlycorrelatedwithageandeducation.Moving ontotheresultsthatareconditionedontheinitialstate(Tables3and
4,columnsII-IV),wenotethattheeffectsoflabordemandaresystem- aticallylargerforunemployed jobseekers. Forthem, a1percentage pointdemand-driven increasein thelocal employmentrateoverthe nextthreeyearsisestimatedtoincreasesemploymentpropensityby3.5 percentagepoints(ColumnIII).Mostofthiseffectcomesfromreduced unemploymentpropensity(−2.2percentagepoints).However,itisno- tablethattheprobabilityofhavingmovedontodisabilityinsuranceis alsoreducedalmostinlinewiththeincreaseinlabordemand(−0.86 percentagepoints).Themuchsmallereffectsestimatedforthosewhoal-
Fig.D1.Estimatedeffectsoflocallabordemandontheprobabilityofbelongingtodifferentstatesinoutcome-year.Byinitialbase-yearstateandoutcome-year (from1to7yearsafterthebase-year)
Note:Eachcoefficientisaresultofaseparateweighted2SLSregressionbasedonEqs.(3)and(4).Pointestimatesareshownwith95%confidenceintervals.
readybelongedtoadisabilitystateinthebase-year(ColumnIV)reflect thatthemajorityofthemactuallybelongedtothestateofpermanent disabilityinsurance,whichtendstobeanabsorbingstateinNorway.
Yet,itisnotablethattheprobabilityofremaininginadisabilityinsur- ancestateafterthreeyearsfluctuatesapproximatelyoneforonewith demand-drivenvariationsintheemploymentrate.5
ColumnsV-VIIpresentstheestimationresultsforthethreeentrant (flow) samples;i.e. thegroupof peoplethat hadjustbecomeeither employed,unemployed,oratemporarydisabilityclaimantinthebase- year.Withinall theseentrantgroups,theprobability ofemployment three years later is highly dependent on local labor demand condi- tions.Itisnotablethatthelabordemandsensitivityofnewentrantsto unemployment-anddisability-relatedprogramsismuchmoresimilar thanitisforthetwostocks.Whilea1percentagepointdemand-driven increaseinlocallabordemandisestimatedtoraisetheprobabilityof beingemployedthreeyearslaterby3percentagepointsforthenewly unemployed,itraisesitby2percentagepointsforthenewlydisabled.
Thechoiceofathree-yeardistancebetweenthebase-yearandthe outcome-yearisabitarbitrary.Itrepresentsacompromisebetweenen- suringappropriatelocalindustryweights(whichrequiresarelatively shortdistance)andensuringsufficientvariationinlabordemandcon- ditions(whichrequires arelativelylong distance).Forthe complete stocksample,thechoiceofdistancebetweenbase-yearandoutcome- yearshouldnothaveanyimpactonpointestimates,asthebase-year isnon-informativewithrespecttotheinitialstate.Forthesamplesthat areconditionedonaparticularstate,ontheotherhand,thechoiceof distanceis potentiallysubstantivelyimportant,aslongerdistance at-
5 Whenweestimatemodelsseparatelyfordifferentage-andeducationgroups conditionaloninitialstate,thesystematicrelationshipbetweentheeffectsoflabor demandandage/educationillustratedinFig.5disappears(notshown).
tenuates theinfluenceoftheinitialstate.InAppendixD,wepresent completeestimationresultsforalternativechoicesoftheoutcomeyear, fromonetosevenyearsafterthebase-year.Asexpected,theestimates arequitestableforthecompletestocksample,aswellasforthesam- plesthatarebasedoninitialstatesthatonaveragetendtobepersistent (thestocksamplesofemployedanddisabilityinsuranceclaimants).For theothersamples,thereisatendencyfortheestimatedlabordemand effectstobelargestthecloserintimetheoutcomeismeasuredrelative tothe(precarious)initialstate.Thisisparticularlyevidentforthetwo unemploymentsamples,whosemembersareknowntobelookingfor jobsinthebase-year.
6. Robustness
Toexaminetherobustnessofourestimationresults,wepresent,in AppendixE,completeresultsforoutcomesmeasuredthreeyearsafter thebase-year,basedonfivealternativespecificationsofthe2SLSmodel inEqs.(3)and(4).First,weexaminethesensitivitywithrespecttothe inclusionofthecontrolvariablescontainedin𝐱𝐳𝐛and𝐲𝐳𝐛(meanindi- vidualcovariatesandthedistributionofinitial states),byestimating themodelwithoutanyofthesecontrols.Thisisofparticularinterestin relationtothemodelsthatareconditionedonaninitialstate,asthecom- positionofentrantstothevariouslabormarketstatesmaydependon labor demandconditions.Byexcluding/includingindividualcontrols, wecanassesstheresults’sensitivitywithrespecttothispotentialsource ofdisturbance.
Second,weexaminerobustnesswithrespecttotheinclusionofre- gionaltrendsinemploymentthatarenotdrivenbydemand,butpoten- tiallycorrelatedtoinitialindustryweights.Wedothisbyextendingthe baselinemodeltoincludecommuting-zone-specificlineartimetrends.
Third,asweinthebaselinemodelhaveincludedeachcommuting- zone’s ownemploymentin thenationaltrendsused toconstructthe
Fig.E1. Robustnessanalysis.Estimatedsecondstagecoefficientswith95%confidenceintervals.
Note:Thestandarderrorsusedtocomputeconfidenceintervalsareclusteredonregion(inmodelswithaggregatedata)andonregionandindividuals(inthemodels withindividualdata.
Bartikinstrument,itcouldbearguedthatthenationaltrendsarenot completelyexogenous.Itispossibletodealwiththisproblembyusing ofa“leave-out” Bartikinstrument;i.e.,aninstrumentwherethenational industry-specificemploymenttrendsarecomputed withoutincluding thefocalcommutingzone.However,theexpansionofemploymentin oneregionmaybecausallyrelatedtocontractioninanother,e.g.,be- causealargeproductionunithaschangedlocation.Itisthereforenot obviouswhichstrategyprovidesthebestfoundationforcausalanaly- sis.Wethus includeamodelbuiltona“leave-out” instrumentinthe robustnessanalysis.Thisleave-outinstrumentisconstructedbysubsti- tutingEq.(2)withthefollowing:
𝑧∗𝑧𝑡=
∑𝐽 𝑗=1
𝑤𝑧𝑏𝑗
1−𝑤𝑧𝑏𝑗(𝐿𝑡𝑗,−𝑧−𝐿𝑡𝑗,−𝑧)
𝑁𝑧𝑏 , (5)
wherethe–zsubscriptindicatesthatthevariabledoesnotincludecom- mutingzonez.
Fourth,aswe haveestimatedthemodelbasedonaggregate data (commuting-zone-by-yearcells),itcouldbe arguedthatwehavenot exploitedindividualdataefficiently.Inarobustnessexercise,wethus useindividualobservations,allowingforamoreflexibleuse ofindi- vidualcontrolsandinitialstates.Theoutcomevariablesthentakethe formof0–1(dummy)variablesindicatingwhetherornotthepersonbe- longedtothestateinquestionintheoutcomeyear,andstandarderrors arecomputedwithatwo-waycluster(individualsandregion).Thevec- tor𝐱𝐳𝐛isreplacedby𝐱𝐳𝐛𝐢,whichcontainstheindividualcovariates,and the𝐲𝐳𝐛isreplacedby𝐲𝐳𝐛𝐢,whichcontainsdummyvariablesindicating theinitialstateforeachperson.
Fifth,basedonindividualdata,weestimateamodelwithperson- fixed effects. While this is relatively straightforward in the stock-
samples,wheremostpersonsareincludedwith15observations(one foreachbase-year),itisabitmorechallengingintheentrysamples, asmanyindividualsdonotexperiencemorethanoneentryintoapar- ticularstate.Thisimpliesthatmodelswithindividual-fixedeffectsare estimatedwithconsiderableuncertaintyforthesesamples.
AscanbeseenfromFig.E1inAppendixE,themainmessagecoming outoftheseexercisesisthattheresultsareindeedrobustwithrespectto modelspecification.Althoughsomeofthepointestimatesvaryslightly frommodeltomodel,noneofthemainresultsdiscussedabovewould havebeensubstantivelychangedhadwereliedonadifferentversionof themodel.
ApotentialconcernrelatedtoallthemodelsbasedonEqs.(3)and (4)isthatthetimevariationinlocalindustryweightswithincommut- ingzonesmayinduceasimultaneityproblemintothemodel,asthese weightsmaybecorrelatedtotheerrorterminEq.(3);conferthediscus- sioninGoldsmith-Pinkhametal.(2019).Itisobviouslynotpossibleto includecommuting-zone-by-base-yeardummyvariables,asthiswould exhaustalltheidentifyinginformationinthedata.Thestabilityofthe resultswithrespecttotheinclusionoflocallineartimetrendsisreassur- inginthisrespect.However,itisalsopossibletodealwiththisconcern more directly;i.e.,bykeepinglocal industryweightsconstantacross differentbase-years,andthenincludedummyvariablesforeachcombi- nationofcommutingzoneandyearofweightconstruction.Theresults fromsuchamodelarereportedinAppendixTableE1,andtheyconfirm robustnessofourmainfindingsalsowithrespecttothisspecification.
Asafinalcheckonempiricalstrategy,wereportinAppendixEthe resultsfromaplaceboversionofourbaselinemodel,wherewehave substitutedoutcomesobservedthreeyearsbeforethebase-yearforthe outcomesobservedthreeyearsafter.Byconstruction,labordemandde- velopmentsinthethree-yearperiodafterthebaseyearcannothavehad