英文通货膨胀与劳动力市场：自下而上的视角

InflationandLaborMarkets:

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SophiaChen,DenizIgan,DoLee,PrachiMishra

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2024

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InflationandLaborMarkets:ABottom-UpView

PreparedbySophiaChen,DenizIgan,DoLee,andPrachiMishra*

AuthorizedfordistributionbyMariaSoledadMartinezPeriaOctober2024

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ABSTRACT:U.S.inflationsurgedin2021-22andhassincedeclined,drivenlargelybyasharpdropingoodsinflation,thoughservicesinflationremainselevated.Thispaperzoomsintoservicesinflation,usingproprietarymicrodataonwagestoexamineitsrelationshipwithservicesectorwagegrowthattheMetropolitanStatisticalArea(MSA)level.Weestimatethewage-pricepass-throughwithalocalprojectioninstrumentalvariablemodelthatexploitsvariationinlabormarkettightnessacrossMSAs.Ourfindingsrevealapositiveandsignificant

relationshipbetweenwagesandpricegrowth,withalag.Thissuggeststhattheeffectsoftightlabormarketsarepersistentandmayinfluencethepaceofprogressiontowardtheinflationtarget.

RECOMMENDEDCITATION:SophiaChen,DenizIgan,DoLee,andPrachiMishra.2024.“InflationandLaborMarkets:ABottom-UpView”.IMFWorkingPaperNo.2024/220.

JELClassificationNumbers:

E24,E31

Keywords:

Inflation;Wages;LaborMarketConditions

Author’sE-MailAddress:

ychen2@,deniz.igan@,dql204@,prachi.mishra@.in

*TheauthorsaregratefultoPhilipBarrett,NigelChalk,EraDabla-Norris,DavideFurceri,GitaGopinath,PierreOlivierGourinchas,DanielLeigh,BoLi,SoleMartinezPeria,PapaN'Diaye,andRodrigoValdezforvaluablediscussionsandinsightfulcommentsandsuggestions.

WORKINGPAPERS

InflationandLaborMarkets:

ABottom-UpView

PreparedbySophiaChen,DenizIgan,DoLee,andPrachiMishra1

1TheauthorsaregratefultoPhilipBarrett,NigelChalk,EraDabla-Norris,DavideFurceri,GitaGopinath,PierreOlivierGourinchas,DanielLeigh,BoLi,SoleMartinezPeria,PapaN'Diaye,andRodrigoValdezforvaluablediscussionsandinsightfulcommentsandsuggestions.

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1Introduction

U.S.inflationrosesharplyin2021-22,withyear-on-yearCPIinflationpeakingat9.0percentinJune2022(Figure1).ByAugust2024,the12-monthinflationratehaddroppedto2.5percent,withindicationsitmaycontinuefallinginthecomingmonths.Boththeriseanddeclinehavebeenequallydramatic.

Asdramaticasthemovementsinheadlineinflationhavebeen,thedivergencebetweenpricetrendsingoodsandserviceshasbeenequallystriking.Theinitialinflationsurgein2021wasdrivenbyaspikeingoodsprices(Figure2),resultingfromsupply-sidedisruptionsinglobalsupplychainsandenergyprices,alongwithapandemic-inducedshiftindemandfromservicestogoods.Servicesinflationbeganrisinglaterintheyearaslockdownseasedanddemandshiftedbackfromgoodstoservices.Whilegoodsinflationpeakedinearly2022anditssharpdeclinehaslargelydriventhefallinoverallinflation,servicesinflationpeakedonlyinearly2023andremainselevated.Thus,understandingthedriversofservicesinflationiscrucialtodecodingthepersistenceofinflation.

Inadditiontothedynamicsofgoodsandservicesinflation,thelabormarkethasbeencentraltotheinflationdebate.Forinstance,BernankeandBlanchard(2024b)arguethat,contrarytoinitialconcernsthatinflationwouldbedrivenbyoverlytightlabormarketsattheonsetofthepandemic,thesurgeininflationbeginningin2021waslargelyduetopriceshocks—suchassharpincreasesincommoditypricesandspecificgoodsshortages—ratherthanwagepressures.Incontrast,Balletal.(2022)attributeasignificantportionoftheinflationrisetolabormarketslack.Notably,thelabormarketremainstight,withthevacancy-to-unemploymentratio(V/U)at1.1inJuly2024(witha12-monthaverageof1.3),comparedto“normaltimes,”whentheV/Uwaswellbelowone.Althoughthelabormarket’scontributiontoheadlineCPIinflationhasdiminishedfromitspeak,itremainsthelargestestimatedcontributortoinflationabovetarget,whichcouldhavenegativeim-plicationsfortheoutlookonheadlineinflation.1

ThispapercontributestotheliteraturebyofferingoneofthefirstU.S.microdata-basedestimatesontheimpactofservicesectorwagegrowthonservicesinflationthroughthelocallabormarkettightnesschannel.WeutilizeproprietarymicrodatafromHomebase,apayrollserviceproviderforsmallbusinessesintheservicessector,whichcoversdetailedinformationonhoursandwagesfornearly9millionworkersacross1millionU.S.firms.ThesedataarecomplementedwithpricedatafromtheBureauofLaborStatistics(BLS).

Weestimatethewage-pricepass-throughattheMetropolitanStatisticalArea(MSA)level,exploringthelocallabormarkettightnesschannelusingalocalprojectioninstru-mentalvariable(LP-IV)approach.OurmethodologydrawsonkeyinsightsfromrecentliteratureontheregionalPhillipscurve.Byusingregionaldata,weavoidthechallengeofshiftinglong-runinflationexpectations,whichcandistortestimatesofthePhillipscurveslope.Italsoallowsustodifferentiatebetweendemandandsupplyshocks,sincecentralbankscannotcounterregionaldemandshockswithasinglenationalmonetarypolicyinstru-ment.2Toexploitvariationinregionaldemandshocks,weinstrumentwagegrowthwithashift-shareinstrumentbasedonlocallabormarkettightness.Similartothetradable-

1ThisisbasedonthedecompositionBalletal.(2022),extendedtothemostrecentperiod.

2SeeHazelletal.(2022)forareviewoftheliteratureandtheoreticalfoundationsoftheregionalPhillipscurve.

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demandinstrumentusedinHazelletal.(2022),thisinstrumentcapturestheideathatnationalvariationinthedemandforspecifictradablegoodswillhavevaryingeffectsonthelocaldemandfornon-tradablesectors,dependingonthelocalexposuretotheimpactedtradablesectors.

Weusethevacancy-to-unemploymentratioasourmeasureoflabormarkettightness,followingBalletal.(2022)andBlanchardetal.(2022).Beforethepandemic,theun-employmentratewasthemostcommonmeasureoflabormarkettightness,valuedforitssimplicityandavailability.However,severalresearchersspecializingininflationdynam-ics,includingFurmanandWilson(2021),BarnichonandShapiro(2022),andDomashandSummers(2022),havearguedthatthevacancy-to-unemploymentratiobetterreflectsla-bormarkettightnessinthepost-pandemiceconomy,wherelaborforceparticipationhasfluctuatedsignificantly.

Anfirstlookatthedatarevealsaninterestingpatternbetweenservicesinflationandservicesectorwagegrowthattheaggregatelevel(Figure3).Sincemid-2021,thesetwoserieshaveshownastrongcorrelationwithalag,closelyaligningwiththetimingoftheriseinheadlineinflation.3

Ourresultsindicateanimportantroleoflocallabormarkettightnessindrivingservicesinflationthroughservicesectorwagegrowth.Thefirststageshowsastrongpass-throughfromlocallabormarkettightnesstowagegrowth.Specifically,aone-log-pointincreaseinthelogvacancy-to-unemploymentratiocorrespondstoapeakeffectofa27percent-agepointincreaseinyear-on-yearservicewagegrowthovera10-monthhorizon.Thesecondstageindicatesthataone-percentage-pointincreaseinservicesectorwagegrowthcorrespondstoa0.32-percentage-pointincreaseinyear-on-yearservicesinflation(exclud-inghousing).Combined,theseresultssuggestthataone-log-pointincreaseinthelogvacancy-to-unemploymentratioisassociatedwithan8.8-percentage-pointincreaseinser-vicesinflation(excludinghousing)overa10-monthhorizon.Moreover,theestimatedeffectsarenon-linear,withahigherwage-pricepass-through,whenlabormarketsaretighter,ortheinitialvacancy-to-unemploymentratioishigher.Thesefindingsarerobusttoalter-nativespecificationsandarebroadlyconsistentwithevidencefrommoreaggregatedandlower-frequencydata.

Theseresultscarryimportanteconomicimplications.TheestimatesindicatethatlocallabormarkettightnesswasakeydriverofinflationbetweenQ32022andQ12023,account-ingforanaverageof68.7percentofservicesinflation(excludinghousing)acrossMSAsduringthisperiod.Ourfindingsalsoreinforcepriorevidencefromaggregatedata,showingthatthepricePhillipscurve—ortherelationshipbetweenwagesandlabormarketslack—issteeperundertighterlabormarketconditions.

Thesefindingshaveimportantimplicationsfortheongoingpolicydebate.Evenbeforethepost-pandemicinflationsurge,servicesinflationwastraditionallythemaindriverofoverallinflationintheUnitedStates.Servicespricegrowthtendstobemorepersistentthancoregoodsprices,largelyduetothehigherlaborintensityofservices,makingthemmore

sensitivetowagegrowth.Wagegrowth,inturn,isoneofthemostpersistentinputcosts,

3Thespikesinthewagegrowthseriesinearly2020andearly2021areconsistentwithaggregatedatafromtheCurrentEmploymentStatistics(CES)(Stewart,2022).Theyreflectchangesinthecompositionoftheworkforce.In2020,low-paidworkerswerelaidoff,pushingtheaveragehourlywageartificiallyhigh.In2021,astheeconomyreopened,employersfilledmanyofthesepositionsagain.

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reflectingthefrequencyofcontractresetsandotherlabormarketdynamics.Thepandemic’sdisproportionateimpactontheservicessector,particularlythedifficultyinrehiringworkerslaidoffduringlockdowns,hascontributedtooveralllabormarkettightness.Thishighlightsthecriticalroleofwagetrendsinservicesandtheirimpactonprices.Whilewagegrowthacceleratedsharplyafterthepandemic’sacutephaseandhasrecentlymoderated,ongoingwagepressuresarelikelyaspurchasingpowerhasyettoreturntopre-pandemiclevels.

Overall,ourresultssuggestthatapersistentlytightlabormarketwillexertpersistentpressureoninflation.Theeffectofthepass-throughfromwagestoservicepricestakesalmostafullyeartopeak.Thispressuremaycomplicatetheinflationoutlook,especiallyinanenvironmentpronetosupply-sideshocksduetogeopoliticaltensions.

Therestofthepaperisorganizedasfollows.Section2reviewstherapidly-expandingrelatedliterature.Section3providesanoverviewofthedataandmeasurements.Section4laysouttheempiricalstrategy.Section5presentsthefindings.Section6concludes.

2Relatedliterature

Ourpaperisrelatedtothegrowingliteraturethatseekstoexplaininflationdynamicsinthepost-pandemicperiod.Thisbodyofworkhasemphasizedtheimportanceofshockstoimportpricesandsupplychains,withanaturalfocusonthegoodssectorduetoitshighertradeability.Forinstance,Amitietal.(2022)showthatchangesinimportcompe-tition,alongwithareducedabilitytosubstitutebetweenlaborandintermediateinputs,contributedtotherecentsurgeininflation.Similarly,LaBelleandSantacreu(2022)high-lightthesignificantimpactofglobalsupplychaindisruptionsontheU.S.ProducerPriceIndex(PPI).

Aseparatestrandofliteraturehighlightstheimpactoftightdomesticlabormarketsonpricepressures.Balletal.(2022)findthatthehighvacancy-to-unemploymentratiosobservedin2021-2022canexplainasignificantportionoftheriseinmonthlycoreinflation.Theynotethat“thecontributionofV/Utotherisein12-monthinflationis2.0percentagepoints,nearlyathirdofthetotalinflationincrease.However,theriseinV/Uexplainsmore—nearlyone-half—oftheriseincoreinflationand,theeffectofV/Uisrisingovertime.”

Similarly,BenignoandEggertsson(2023)showthattheslopeofthePhillipscurvesteepenswhenthevacancy-to-unemploymentratioishigh.Theyconcludethatthere-centinflationsurgewasprimarilydrivenbyalaborshortage.Daoetal.(2024)findthattightlabormarketscontinuetocontributesignificantlytoinflationintheU.S.,makingitanexceptionamongalargesampleofadvancedandemergingmarketeconomies,whereinflationarypressurefromrelativepriceshockshassubsided,resultinginlowerinflation.BernankeandBlanchard(2024a)findanevenlargerquantitativeroleforV/UinexplainingpricepressuresintheUScomparedtoDaoetal.(2024).AccordingtoDaoetal.(2024),thisdifferencestemsfromtheirinclusionofV/Uintheirequationforcoreinflation,whiletheapproachofBernankeandBlanchard(2024a)focusessolelyontherelationshipbetweenV/Uandwageinflation.

Unliketheaforementionedpaperswhichusethevacancy-to-unemploymentratio,Crumpetal.(2022)relyontheunemploymentrateastheirmeasureoflabormarkettightnessandcomplementitwithmultiplemeasuresoflaborcompensation.Theyprojectunderlying

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inflationtoremainhighduetotightlabormarketsandstrongwagegrowth.4Consistentwiththesepapers,wefindastrongroleofthelabormarketindrivingrecentinflation.Akeydifferencebetweenourapproachandtheseexistingstudiesisthattheyexaminetime-seriesvariationinaggregateinflation,whileweexplorecross-sectionalvariationacrossgeographicalareas.WeprovideadetailedcomparisonoftheestimatesinSection5.

OurpaperisalsorelatedtostudiesthatestimatethePhillipscurveusingcross-sectionaldata(e.g.,Berajaetal.,2019;McLeayandTenreyro,2019;Hooperetal.,2020).Hazelletal.(2022)showthatusingregionaldatahelpsovercometheissueofshiftinglong-runinflationexpectations,whichcanconfoundtheeffectoflabormarketslack.Italsoallowsforacleardistinctionbetweendemandandsupplyshocks.TheyshowthattheslopeoftheregionalPhillipscurveissteeperthanthatofanaggregatePhillipscurvewhenlabormarketconditionsarepersistent.Mostestimationsinthisliteraturefocusonthepre-pandemicperiod.Forexample,Hazelletal.(2022)estimatetheslopeoftheregionalPhillipscurveusingdataacrossU.S.statesspanning1978-2018.AnexceptionisBarnichonandShapiro(2022),whoevaluatetheperformanceofvariousslackmeasuresinpredictingandexplaininginflationusingMSA-leveldatafrom1982to2022.Theyfindthatthevacancy-to-unemploymentratioandvacancyfillingcostproxiesoutperformotherlabormarketslackmeasures,suchastheunemploymentrate.However,theirfocusisPhillipscurve’spredictiveperformanceanddoesnotexaminethewage-pricepass-throughorestimatethecontributionoflabormarketslacktoinflation.

Thispaper’smaincontributiontotheliteratureistheuseofproprietarymicrodatatoexploretherelationshipbetweenservicesinflationandlabormarkettightness.Thisfocusiscrucial,asservicesinflationremainselevated,keepingheadlineinflationwellabovetheFederalReserve’s2percenttarget.Thecurrentdebatecentersonwhetherinflationhasplateauedatlevelsabove2percent,posingapotentialchallengefortheFed.AsBernankeandBlanchard(2024b)argue,theeffectsofoverheatedlabormarketscanbepersistent,withlabormarketfactorsincreasinglydrivinginflationastheinfluenceofgoodspriceswanes.Laborcostsrepresentalargershareoftotalcostsinservicescomparedtogoods,andstaggeredwagesettingfurtheramplifiestheroleoflabormarketsinsustaininginflation.Byusinghigh-frequencymicrodataandacross-sectionalPhillipscurveframework,wecanbetteridentifythekeydriversofpersistentservicesinflation.

3Dataandmeasurements

OurwagedatacomefromaproprietarydatasetprovidedbyHomebase,asoftwarecompanythatoffersscheduling,payrollreporting,andrelatedservicestobusinesses,primarilyintheretail,hospitality,andotherservicesectors.Thedatasetisbasedontimecardrecords,offeringdetailedinformationonworkhoursandwagesfromover80,000businessesandmorethan1millionemployeesacrosstheUnitedStates.Itincludesgranulardailyemployee-leveldataonhoursworked,wages,jobtypes,andlinkstothecorrespondingestablishmentsandparentfirms.Additionally,establishment-leveldetailsincludelocation(via5-digitzipcodes)andindustryclassification(via6-digitNAICScodes).Oursampleperiodspansfrom

4Underlyinginflationrepresentstheinflationcomponentthatsolelydependsonthelong-runtrendandthesequenceofcurrentandfutureunemploymentgaps.

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January2019toDecember2022.5WecalculateaveragewagesatthemonthlyfrequencyforeachMSA.

Thisdatasetisnotableforitshigh-frequency,granularcoverageofworkhoursandwageinformation,settingitapartfromotherU.S.labormarketdatasets.6TheHomebasedataset’sextensivecoverageoflow-wageworkersandin-personservicesisespeciallyvaluableforstudyingrecentwagedynamics,asthissegmentexperiencedparticularlystrongpost-pandemicwagegrowth(Autoretal.,2023;ChenandLee,2024).However,thedatasethaslimitations,suchastheexclusionofcertainsectorsandthelackofdataontips,benefits,andovertimepayments.Despitetheselimitations,employmenttrendsintheHomebasesamplecloselycorrelatewithofficialstatisticsfromtheCPSandCES.Additionally,changesinemploymentandearningsalignwellwithCESdataatthemonth-statelevel(DvorkinandIsaacson,2022;ChenandLee,2024).7WediscusstheexternalvalidityoftheHomebasedataindetailinSection5.

Forpricedata,weusetheConsumerPriceIndex(CPI)providedbytheBureauofLaborStatistics(BLS),whichoffersmonthlyorbi-monthlydataattheMSAlevel.ForMSAswithbi-monthlyCPIdata,weinterpolatelinearlytoobtainamonthlyfrequency.Ourprimaryfocusisonservicesexcludinghousing(i.e.,CPIitem’serviceslessrentofshelter’).Weconstructyear-on-yearinflationseriesattheMSA-monthlevel.WeemphasizeservicesinflationbecausenearlyallCPIservicesarenon-tradable(Johnson,2017).8Thisfocusisimportantbecausepricessetatthenationallevel—typicalfortradablegoods—resultinaflatterregionalPhillipscurve.Weexcludehousinginflationfromouranalysisbecauseitsdriverslikelydifferfromthoseaffectingnon-housingservices.Consistentwiththis,theliteraturehasfoundthathousinginflationexhibitsasubstantiallydifferentslopeinthePhillipscurvecomparedtonon-housingservices(Hazelletal.,2022;StockandWatson,2020),andthatremoteworkhasbeenasignificantdriverofpost-pandemichousingprices(Howardetal.,2023).

4Empiricalapproach

WeanalyzethedatausinganLP-IVapproach,asusedinJord`aetal.(2015)andJord`aetal.(2020).Localprojectionsareaflexibleandconvenientmethodforestimatingimpulseresponses(Jord`a,2005),requiringminimalassumptionsaboutthefunctionalformoftheresponses.TheLP-IVapproachestimatestheseimpulseresponsestoshocksusingtwo-stage

5Thesampleonpricesandwagesstartsayearearliertoallowforthecalculationofannualchanges.

6Forinstance,Compustatlacksdataonprivatefirms,theCensuslacksdetailedwageinformation,andboththeCurrentPopulationSurvey(CPS)andCurrentEmploymentStatistics(CES)lacksufficientgeo-graphicvariationforcross-sectionalanalyses.TheQuarterlyCensusofEmploymentandWages(QCEW)providestabulateddatabygeographicareaandindustrybutdoesnotoffermicrodata.

7TheCPS,co-sponsoredbytheCensusBureauandtheBLS,surveysabout60,000U.S.householdsandservesastheprimarysourceforofficialunemploymentstatistics.TheCES,sponsoredbytheBLS,surveysapproximately145,000U.S.businessesandgovernmentagenciesandprovidesofficialemploymentandwagestatistics.

8AccordingtoJohnson(2017),theonlythreeCPIitemcodesforservicesclassifiedastradableareRA04(Videocassettes,discs,andothermedia,includingrentals),TF09(unsampledmotorvehiclefees),andTG01(airlinefare).Hazelletal.(2022)constructanon-tradableinflationseriesusingBLSmicrodata,definingnon-tradablessimilarlytotheBLSserviceaggregationbutwithtwoexceptions:theyclassifyFoodAwayfromHomeasnon-tradableandexcludesometransportationitems(e.g.,airlinefare).

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leastsquares.Specifically,weestimate:

KK

+βhwi,t+wi,t−k+yi,t−k+γhXi,s,t+u

wherei,s,andtdenoteMSA,state,andmonth,respectively.h=1,....,Hdenotes

theestimationhorizon.WecontrolforlagsuptoK=3.αisatimefixedeffect.

ηisanMSAfixedeffect.Weclusterthestandarderrorsu,tattheMSAlevel.Our

inflationmeasure,yi,t,isyear-on-yearservicesinflation(excludinghousing)inMSAiinmonthtcalculatedasthelogarithmicdifferenceinthepricesforservicesexcludinghousing,

ln(prices)i,t−ln(prices)i,t−12.Hence,thedependentvariableyt−y,tcapturesthechange

ininflationoverahorizonofhmonthsfromtimettotimet+h.wi,tisourindependentvariableofinterest.Itisyear-on-yearwagegrowthintheservicessectorfromHomebasecalculatedasthelogarithmicdifference,ln(wage)i,t−ln(wage)i,t−12.

WeincludeavectorofcontrolsXi,s,tatthestate-yearlevel.Thisincludeslaborproduc-tivity(fromBLS)asaproxyforlocallabordemand,headlineinflationshocksdefinedasthedifferencebetweenyear-on-yearheadlineinflationandcoreinflationexcludingfoodandenergy,andresidualsfromregressionsofprevioushorizons(i.e.,from1toh−1).AccordingtoTeulingsandZubanov(2014),theseresidualsaccountforinformationbetweentimetandt+hthatarenotfullycontrolledbytheotherindependentvariables(whichareasoftimet).

Thecoefficientβhcapturestheimpulseresponseofinflationonwagegrowthoverthehorizonh.Werefertothiscoefficientasthewage-pricepass-through.Thecausalinter-pretationofthiscoefficientrestsonseveralgrounds.Empirically,wagesaretypicallylessflexiblethanprices,makingitunlikelythattheywillquicklyadjusttochangesininflation.Thisisalsoevidentinoursampleperiod.AsFigure3shows,theriseinwagesprecedestheriseininflation.9

Moreover,weinstrumentwagegrowthwithaBartikshocktolocallabormarketcondi-tions,followingBartik(1991).10Thisallowsustoisolatetheinflationarycomponentofwagegrowththatresultsfromlabormarketcompetition.Toachievethis,weconstructaBartikshockbasedonlocallabormarketconditions.Wemeasurelabormarketconditionsusingthevacancy-to-unemploymentratio(i.e.,thenumberofvacanciesdividedbythenumberofunemployedworkers),followingrecentstudies(e.g.,Balletal.,2022;Blanchardetal.,2022;BenignoandEggertsson,2023).Thisapproachispreferabletousingthetraditionalunemploymentgapmeasure,giventheupwardshiftintheBeveridgecurvepost-pandemic.TheBeveridgecurve,whichshowsthenumberofvacanciesperunemployedworker,hasshiftedupward,suggestingasimilarshiftinthetraditionalunemployment-basedPhillipscurve,whichimplieshigherinflationatanygivenunemploymentrate.Therefore,usingthevacancy-to-unemploymentratiobettercapturesthisdynamic.

Formally,theBartikshockinMSAcinmonthtisdefinedastheprojectedlogvacancy-to-unemploymentratio:

\\

Shocki,t=ln(V)i,t−ln(U)i,t,(2)

9Thelaggedresponseofinflationtowagegrowthisacommonidentificationassumptioninstructuralvectorautoregression(SVAR)estimations.See,forexample,BernankeandBlanchard(2024b).

10SeeSohetal.(2022)andChenandLee,2024forapplicationsofthismethodinthecontextofthepandemic.

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\

whereln(V)i,tiscalculatedas

ln(Vk,t)isthelognumberofvacanciesfor3-digitNAICSindustrykintimet.Weincludeallindustriesexcludingpublicadministration.ϕc,k,2015−2016istheaverageemploymentshareofindustrykinMSAiin2015-2016.Wedefineln(Uk,t)similarly.

Weuseindustry-leveldataonunemploymentfromtheCPSandvacancydatafromaproprietarydatasetprovidedbyIndeed.Indeedisaglobalsearchengineforjoblistingsthatcollectsjobpostingsfromvarioussources,includingjoblistingsites,employercareersites,andapplicanttrackingsystems.Duplicatedlistingsareremoved,soeachjobisshownonlyonce,evenifitappearsonmultipleplatforms.Ourfinaldatasetincludes142millionjobpostings,covering421occupationsbasedonISCO-08classificationsacross2.9millioncompaniesand576countiesintheUS.

TheadvantageofusingIndeed,asopposedtotheJobOpeningsandLaborTurnoverSur-vey(JOLTS)fromtheBLS,isitsmoregranularindustryclassifications,whichenableustocaptureshocksatthe3-digitNAICSlevel.AlimitationoftheIndeeddatasetisthatitmaynotcapturealljobvacancies,assomearenotpostedonline.Toaddressthis,werescalethevacanciesfromIndeedintonationallyrepresentativeunits,andwedescribethisadjustmentprocedureinAppendixA.3.Additionally,Indeedallowsustocomputethevacancy-to-unemploymentratioattheMSA-monthlevel—ameasurenotavailablefromJOLTS.Weusethismeasuretoclassifylocallabormarketswithlaborshortageswheninvestigatingthenon-linearityofprice-wagepass-throughbasedonlocallabormarketconditions.

TheidentifyingassumptionunderlyingourBartikshock,asBorusyaketal.(2022)show,isthattheindustrydemandshocks,ln(Vk,t)andln(Uk,t),arequasi-randomlyassigned.Thismeansthattheshocksareuncorrelatedwithrelevantunobservablesinexpectationandthatashock-levellawoflargenumbersapplies,thatis,theinstrumentincorporatesmanysufficient