世界银行-产品市场垄断与劳动力市场垄断

PublicPublicDisclosureAuthorizedPublicDisclosureAuthorizedPublicDisclosureAuthorizedPublicDisclosureAuthorizedPolicyResearchWorkingPaper10388alPracticeMarch2023PolicyResearchWorkingPaper10388ecttoinvestmentrestrictions.Theresultisrationalizedusingasimpleoligopsonymodelinwhichhigherentrycostsgemploymentoptionsforworkersandhence,theirlaborerentryisthemaindriverofempiricallythathigherbarrierstoentryinproductmar-powerthemarginalproductoflaborandthewage.Thelitera-tshareofnationaloutput.UsingvariationininvestmentrtbytheheychoolUniversityofOxfordKeywords:productmarketregulation;labormarketpower;markdown;firmentry;minimumwageJELclassification:J31;J38;J42;L13;L4*TheauthorsthankAufaDoarest,BobRijkersandRomànDavidZàrateforhelpfulcomments.PresidentethanksCitiforgenerousfinancialsupport.Theviewsexpressedinthispaperareoftheauthorsanddonotnecessarilyreflectthoseoftheaffiliatinginstitutions.tCorrespondingauthor:giorgio.presidente@oxfordmartin.ox.ac.uk21IntroductionLabormarketpowerisanincreasinglyimportantsourceofmarketdistortionsinmoderneconomies(Yehetal.,2022;Benmelechetal.,2022;Mertens,2022),asittypicallyallowsfirmstopayawagebelowthemarginalproductoflabor.1Thewedgebetweenwagesandthemarginalproductoflaborhasimportanteconomicimplications.Bydepartingfromallocativeefficiency,labormarketpowerreducestheeconomy’soveralloutputandemployment.2Bydepressingemploymentandwages,marketpowercanalsoreducethelaborshareofnationaloutput(Naiduetal.,2018;Brooksetal.,2021;Mertens,2022),akeymeasureofinequalitythathasbeendeclininginmostoftheworld(e.g.Autoretal.,2020;Brooksetal.,2021;GutiérrezandPhilippon,2017;KarabarbounisandNeiman,2014;DeLoeckerandEeckhout,2018).Understandingthedeterminantsoflabormarketpoweristhuscrucialtoaddressitspotentiallydistortionaryeffects.Theliteraturehaspositedapositiverelationbetweenlabormarketconcentrationandemployers’marketpower,whichisconsistentwithwagesbeinglowerinmoreconcentratedlabormarkets(Amodioetal.,2022;Benmelechetal.,2022).Onthebasisofthisintuitiverelationship,someauthorshaveproposedtoextendantitrustapproachesusedtoregulateproductmarketstoregulatelabormarkets(Naiduetal.,2018;Marinescuetal.,2021).Howeversystematicevidenceofacausalrelationbetweenmarketconcentrationandlabormarketpowerremainselusive.Thispaperstartstofillthisgapbystudyinghowchangesinregulatorybarrierstoentryaffectfirms’labormarketpower.Toguidetheempiricalanalysis,webuildasimplemodelinwhichafinitenumberofemployerscompetestrategicallytoattractworkers.Inthemodel,de-regulatingproductmarketslowersentrycostsandincreasestheequilibriumnumberoffirms.Thisinturnraisesthenumberofalternativeemploymentopportunitiesforworkers.Theresultinglossofemployers’labormarketpowerreducestheirabilitytopaywagesbelowthemarginalproductoflabor,i.e.toimposeapositivewagemarkdown.1Whileinprinciplealsoworkerscouldenjoylabormarketpower,inpracticetheevidenceofwagesabovemarginalproductoflaborislimited.2Naiduetal.(2016)estimatethatlabormarketpowerbyU.S.firmsreducesoveralloutputandemploymentby13percent.3WetestourtheoryempiricallyfocusingonthecaseofIndonesianmanufacturing,whereourestimatessuggestthatthevastmajorityofplantsexertsomedegreeoflabormarketpower.Specifically,wetakeadvantageofquasi-exogenousvariationininvestmentrestrictionsacross346narrowly-definedmanufacturingproductmarketsinIndonesia.SuchrestrictionsareimplementedbythegovernmentthroughthepublicationoftheNegativeInvestmentList(NIL),aPresidentialregulationwhichdetailstheconditionsthatnewinvestorshavetofulfilltoregisteracompanyinanyIndonesiansector.AfteraddressingconcernsofpotentialendogeneityofchangestotheNILandproductmarkettrends,weexploitchangesinrestrictionsacrossproductmarketsin2011toestimatethecausalimpactofproductmarketregulationonwagemarkdowns.Toestimatemarkdowns,weusegranularinformationonpricesandquantitiesof9-digitproductsandintermediateinputsfromahighlyrepresentativesampleofIndonesianmanufacturingplants.3Thisconstitutesanadvantageoverpreviousstudies,whichoftenrelyonindustry-levelpriceindicestodeflatenominalquantities,incurringinseveralsourcesofbias(Bondetal.,2021;DeLoeckeretal.,2016;Fosteretal.,2008).Importantly,wealsodisentanglewagemarkdownsfrompricemarkups,whichareembeddedinthe“naive”comparisonofmarginalproductoflaborandthewagepaidtoemployees.Usingthisapproach,weprovidereduced-formestimatesoftheelasticityofwagemarkdownstoinvestmentrestrictions,whichisaround0.25.ThisimpliesthatNIL-relatedentrybarriersintheproductmarkethaveincreasedmarkdownsbyaround4.3%inoursample.TheresultsarerobusttoabatteryoftestsandarealsoconsistentwithaneventstudyregressionbasedonachangeoftheNILasthe“event”.Theabsenceofpre-trendsintheeventstudyfurtherrelievesendogeneityconcernsfortheinstrument.Inaddition,weprobetherobustnessofourresultsusinganalternativeidentificationstrategybasedonaBartikinstrumentexploitingthedifferentialexposuretoregulatedproductmarketsacross274commutingzones.SuchdesignminimizesthepotentialendogeneityofchangestotheNILandlabormarketpowerinagivenproductmarket,thusprovidingfurtherreassuranceagainstpossibleendogeneitybiasingourresults.3Indonesianmanufacturingdatahavebeenextensivelyusedinpreviouswork(e.g.AmitiandKonings,2007;Javorcik,2004;ArnoldandJavorcik,2009;Hallward-DriemeierandRijkers,2013).4Wethentestempiricallytowhatextentfirmentrycanexplainthiseffect,aspostu-latedbythemodel.Tothatend,wefirstshowthatinvestmentrestrictionsareindeedpowerfulpredictorsofsubsequententrybymanufacturingfirmsattheproductmarket-level.WethenbuildonthisfindingandinstrumenttheentryinaproductmarketwithinvestmentrestrictionsusingtheNIL.TheresultingTwo-StageLeast-Squares(2SLS)es-timatesimplyanelasticityofmarkdownwithrespecttoproductmarketregulationthatisalmostidenticaltothereducedformelasticity.Thissupportsthechannelidentifiedinthemodelasdrivingtherelationbetweenproductmarketregulationandlabormarketpower.Thesimple,yetunderstudiedrelationshipbetweenproductmarketregulationandlabormarketpowerishighlypolicy-relevant.Ifproductmarketregulationaffectslabormarketpower,asourevidencesuggests,itcanalsobeusedasapolicytooltomitigatelaborexploitationandrisinginequality(MarinescuandHovenkamp,2019;Naiduetal.,2018).Thisseemsparticularlyrelevantinlightofthegrowingevidenceofoligopsonypowerinlabormarketsaroundtheworld(e.g.Yehetal.,2022;Dubeetal.,2020;Brooksetal.,2021;Naiduetal.,2016;Mertens,2022).Thepaperisrelatedtoseveralstreamsofliterature.First,wecontributetotheliteraturelookingatconcentrationinthelabormarket(Azaretal.,2020;Dubeetal.,2020;Benmelechetal.,2022;Yehetal.,2022;Marinescuetal.,2021;Arnold,2019;Schubertetal.,2021).SincethesepapersarebasedontheUnitedStates,ourfocusonIndonesiaisoneofthefeaturesthatsetsourstudyapartfromtheliterature.Infact,labormarketconcentrationisespeciallylikelytoharmworkers’welfareinadevelopingcountry,wherethegeographicmobilityoflaborismorelimitedandthelevelsofskillsandcompliancewithlaborregulationarelower.4Indeed,ourestimatessuggestthatbetween95and97percentoftheplantsinoursamplehavesomelabormarketpower,ascapturedbyamarkdownlargerthanone.Moreover,noneoftheabove-mentionedstudiesexaminethelinkbetweenproductmarketregulationandlabormarketpower,aswedointhispaper.4TwoexceptionsareNaiduetal.(2016)andBrooksetal.(2021),whichbasetheiranalysisontheUnitedArabEmirates,ChinaandIndia.5Morespecifically,ourpaperisrelatedtotheliteratureonmonopsonyandoligopsonypowerinthelabormarket(Bergeretal.,2022;BurdettandMortensen,1998;Cardetal.,2018;Manning,2013,2003).5Ourcontributiontothisliteratureislinkingproductmarketregulationtolabormarketoligopsonypower.Inthiscontext,arelatedpaperisBlanchardandGiavazzi(2003),whichexaminesthelinkbetweenproductmarketregulationandthelabormarket.Howeveritdoesnotexplicitlymodelstrategicinteractionamongemployers,nordoesittestempiricallytherelationshipbetweenregulationandlabormarketpower.Second,wejoinagrowingliteratureonmarketpower.Amongthesepapers,Autoretal.(2020)andDeLoeckeretal.(2020)areagnosticaboutthesourcesofincreasingproductmarketconcentration.DeLoeckeretal.(2021)examinestheroleofmarketstructureforlabormarketoutcomesusingageneralequilibriummodel.However,theyabstractfromoligopsonypowerinthelabormarket.GutiérrezandPhilippon(2017)andGutiérrezetal.(2018)pointtotheregulationasthemaindriverofincreasingconcen-tration.Weaddtothesepapersbyprovidingevidenceofacausalrelationshipbetweenproductmarketandlabormarketpowerusinghighlygranularinformationonproductmarketreformsandplant-levelmarkdowns.Finally,wecontributetotheliteraturemeasuringfirm-levelmarketpowerusingtheproductionapproach(Halletal.,1986;Hall,1988;DeLoeckerandWarzynski,2012;DeLoeckeretal.,2016).LikeinYehetal.(2022),DobbelaereandMairesse(2013),Morlacco(2019)andMertens(2022),weapplysuchmethodologytoestimatewagemark-downs.However,unlikemostoftheliterature,weobservequantityandvaluesof9-digit-levelproductsandinputsusedbyplants.Thisallowsustocomputeplant-specificoutputandinputspricedeflatorsthathelpmitigatingthebiasarisingfromusingrevenue-basedmeasuresforthecomputationofmarkdowns(e.g.Bondetal.,2021).Therestofthepaperisorganizedasfollows:Section2presentsasimplemodellinkingwagemarkdownsandproductmarketregulation;Section3describesthedatausedtotestempiricallythepredictionsofthethemodel;Section4describesourproceduretoestimatemarkdowns;Section5illustratestheeconometricapproachandaddressesthe5SeeBhaskaretal.(2002)forasurvey.6potentialselectionofproductmarketsintoreformingactivity;Section6presentstheresultsrelatingproductmarketregulationtowagemarkdowns,andSection7concludes.2TheLinkbetweenProductMarketRegulationandLaborMarketPowerWepresentasimplemodeltoelucidatehowchangesinproductmarketregulationthataffectfirms’entrycouldaffectfirms’labormarketpower.Consideracommutingzonempopulatedbyafinitenumberoffirms,indexedbyf.Firmsproducehorizontallydifferentiatedproducts,indexedbyi.Weassumethatitisinfinitelycostlyforworkerstocommuteacrossdifferentcom-mutingzones—anassumptionconsistentwithourdata,asdiscussedfurtherbelow,aswellaswithevidencefromadvancedeconomies(KennanandWalker,2011).6Asabenchmarkcase,weassumethatlaborsupplyiscommutingzoneandproduct-specific,forinstanceduetotheskillrequirementsforproducingacertaingood.7Thisassumptionsimplifiestheanalysisbecauseitallowsustoconsiderfirmsinaproductmarket-commutingzonepair{m,i}independentlyofotherfirmsinm.WerelaxthisassumptioninamodelextensioninOnlineAppendixE,andinSection6wepresenttheempiricalresultsofmodifyingourestimatoraccordingly.WagesaredeterminedbytheinverselaborsupplyfunctionWm(.),whichweassumetobeanincreasing,continuousanddifferentiablefunctionofaggregateproductmarket-commutingzone-specificlabordemand,Lmi.Weindexthefunctionbymtocapturetheideathatthelaborsupplyelasticityislikelylocation-specific,forinstanceduetothequalityoftransportationinfrastructurethataffectsthedisutilityoflabor.Weassumethatthenumberoffirmsinalocallabormarket,aproductmarket-commutingzonepair,isfiniteandgivenbyNmi.Hence,thelabormarketisnotperfectlycompetitive,whichimpliesthatemployershavelabormarketpower:Wm(.)isupward-6Onewouldexpectcommutingcoststobeonaveragehigherindevelopingcountries,wherethetransportationinfrastructureisusuallylessefficientthaninadvancedeconomies.7Bergeretal.(2022)useasimilardefinitionoflabormarketintheUnitedStates,acommutingzoneandthree-digitindustry.7 F\(L)Lslopingbutlessthan F\(L)LTosimplifythenotation,weomitthefindexfromallfirm-levelvariables.LetLdenotingfirm-levelemployment.Firms’outputisgivenbyQ=F(L),whereF(.)isanincreasingandconcavefunction.Weusetheoutputpriceasthenumeraire.Theprofitfunctionisgivenby:Π(L,Lmi)三F(L)-Wm(Lmi)L(1)Firms’optimallabordemandisobtainedfromprofitmaximization,whichimpliesdifferentiating(1)withrespecttolabor:F\(L)=W(Lmi).L+Wm(Lmi)(2)whereF\(L)denotesthepartialderivativeofFwithrespecttoL.Ourfocusistostudyfirms’labormarketpower,whichasintheliteraturewecapturethroughthewagemarkdown,i.e.thewedgebetweenthemarginalproductoflaborandthewagepaidtotheworkers.WedivideEquation(2)byWm(Lmi)toderivethewagemarkdownν:三W(Lmi)Lmiwhereε三W(Lmi)LmiWm(Lmi)Lmiν三=1+εmWm(Lmi)Lmidenotestheinverselaborsupplyelasticity.Thelasttermisthefirmemploymentsharewithinthelabormarket.Equation(3)showsthatthemarkdownisdecreasinginthelaborsupplyelasticityandincreasingintheemploymentshare.TheintuitionbehindEquation(3)isthatworkershavefewalternativeemploymentopportunitieswhenthelabormarketisconcentrated,i.e.afewfirmsemploymostworkers,whichallowsemployerstoextractrents.Thisimpliesthatanyfactorincreasingfirms’employmentshareswithinalabormarkettendstoincreasewagemarkdowns.8Sincelabormarketpowerarisesbecauseemployersare“scarce”,ourmodelcanbeconsideredasoneofclassicaloligopsony,asopposedtoalternativetheoriesbasedonsearchfrictionsorheterogeneousworkers’preferencesoverjobs(Manning,2003;Bhaskaretal.,2002).8WefocusonthesymmetricCournotequilibrium,forwhichexistenceandunique-nessarediscussedinAmirandLambson(2000)fortheoligopolycase.WeadaptthesesufficientconditionsfortheoligopsonycaseinOnlineAppendixB.1.Inasymmetricequilibrium,Lmi=LxNmi.Thenumberofactivefirmsisdeterminedendogenouslybythefree-entrycondition:Π(Nmi)=χi(4)whereχirepresentsafixedentrycostthatentrantfirmsneedtopaytoproduceandselltheirproductintherespectiveproductmarket.OnlineAppendixB.2showsthatasufficient(butnotnecessary)conditionfortheprofitfunctiontobemonotonicallydecreasinginNmiisW(Lmi)>0.Assumingthatconditiontoholdanddenotingby(.)theinverseprofitfunction,Equation(3)canbewrittenas:ν=1+(5)IfWm(.)isaconstantelasticityofsubstitutionfunction(CES),thenemisconstantandtheimpactofproductmarketregulationonmarkdownsisunambiguouslypositive.93DataWetestempiricallytheinsightsofthemodelonIndonesianmanufacturingplants.Tothatendweexploittwomainsourcesofdata:anextensivepanelofmanufacturingplantsanddataonproductmarketregulationovertime,whichwemanuallycode.3.1ManufacturingDataPlant-leveldataaretakenfromtheIndonesiansurveyofmanufacturingplantswithatleast20employees(StatistikIndustri,SI)administeredbytheIndonesianStatisticalOffice9Theimpactofproductmarketregulationonmarkdownisambiguousinthemodelextensionwithhomogeneouslaborwithinacommutingzone,asshowninOnlineAppendixE.9(BPS).Thecoverageofthesurveyisextensive;infactitbecomesanactualcensusin1996and2006anditisveryclosetoacensusintheremainingyears,henceensuringhighrepresentativesevenfornarrowly-definedindustriesandgeographicareas.Plantsaregroupedinto5-digitsindustriesfollowingthedefinitionKlasifikasiBakuLapanganUsahaIndonesia(KBLI),aclassificationmostlycompatiblewithISICcoding.OnechallengeoftheStatistikIndustridataisthelackofcompleteseriesofcapitalstock.Toaddresstheissue,wedevelopanalgorithmdescribedinOnlineAppendixF.1.Onceweobtaincleancapitalseries,wedeflatethemusingpriceindexesfromBPS,distinguishingbetweenmachineryandequipment,vehicles,buildings,andland.Todeflatenominalquantities,weconstructplant-specificoutputandmaterialspriceindexes,asinEslavaetal.(2004).Todoso,weexploitthefactthatourdataincludeinformationonquantitiesandvaluesoftheproductsproducedandmaterialsusedinproduction.Thesearebothdefinedatahighlygranularlevel,namely9-digitsKlasifikasiKomoditiIndonesia(KKI),amoredetailedclassificationbasedonKBLI.Inoursample,eachplantproducesonaverage2products,25%oftheplantsproducemorethanoneproduct,andeachplantusesfourdifferentvarietiesofrawinputs.OnlineAppendixF.2describesindetailthemethodologyweusetocleanproduct-andinput-leveldata.Aftercomputingunitpricesbydividingvaluewithquantities,weusethemtoconstructplant-leveloutputandinputpricedeflators(seeOnlineAppendixF.3).AsdiscussedinSection4below,weuseenergyconsumptiontoproxyforunobservedproductivitytoestimateplant-levelproductionfunctions.Todoso,wetakeadvantageoftheunusualfeatureofourdata,whichprovideinformationonthequantityofenergyused,byenergytype.10Inourempiricalexamination,weuseIndonesianregenciestoidentifycommutingzones.Regenciesarethesecondlevelofsub-nationaladministrativedivisions(thefirstbeingtheprovince).Anumberoffeaturesmakeitareasonableproxyforacommut-ingzoneinIndonesia.First,themobilityoflaborislimitedacrossregencies.In201010Specifically,weconsiderelectricity,gasoline,diesel,lubricants.Theseconstituteroughly90percentofenergyconsumptioninoursampleandarereportedseparatelyinallyearsofthesample.ToconvertlitersoffossilfuelsintoKWhequivalents,weusedthefollowingstandardconversionfactors:1literofdieselcorrespondsto10kWh;gasoline:9.1kWh;lubricants:11kWh.forexample,only5percentoftheworkforceworkedinadifferentregencythantheirresidence.11Second,regenciesholdsignificantadministrativepowersfollowingthe1999decentralizationreforminIndonesia.Thoseincludealsotheminimumwagesetting.Weusethepre-decentralizationreformdivisionin292regenciestoensuretheconsistencyoftheanalysisovertime.Inoursample,34%ofplantschangeproductmarketoverthesampleand5%ofplantschangecommutingzone.Toensureconsistencyovertheyears,wedropallsuchplants.However,ourresultsarerobusttojustdroppingobservationsafterplantschangeproductorlocation,ortonotdroppingthematall.Aftercleaningthedataandkeepingobservationswithnon-missingvaluesforallthedependentvariablesconsidered,weendupwithanunbalancedpanelof14,142plantsbetween2009and2014—including346productmarkets(5-digitindustries)and274com-mutingzones(regencies).Wetakethecensusyear2006asourbaseyeartomaximizerepresentativeness.OnlineAppendixTableA1presentssummarystatisticsofallvariablesusedintheempiricalanalysis.3.2MeasuringProductMarketRegulationBringingtheinsightsofthemodelinSection2tothedatarequiresidentifyingasuitablemeasureofentrycostsandanexogenoussourceofvariation.Tothatend,wecollectgranulardataoninvestmentrestrictionsacrossIndonesianproduct-marketsandexploittwoconsecutiveIndonesianPresidentialDecrees—DaftarNegatifInvestasi,orNegativeInvestmentList(NIL).TheconceptofaNILwasintroducedinIndonesiain2000throughthePresidentialDecree96/2000,whichaimedtocreateasinglerepositoryofthemanyexistingsectoralrestrictionsoninvestmentsatthecentralgovernment-level.Infact,itwasnotuntil2008thattheNILapproachwasproperlyenforced,astheInvestmentLawNo.25/2007replacedtheoldInvestmentLaw(No.1/1967),whichusedapositivelistapproachtorestrictions,i.e.whatevermarketisnotincludedintheregulationsistobeconsideredclosedto11Indonesia’sislandgeographyandoftenunderdevelopedtransportationinfrastructuresmakethehy-pothesisoflimitedmobilitylikelytohold.investments.ThiswasfollowedbythePresidentialDecree77/2007,whichprovidedthefirstofficialNILinIndonesia.12InadditiontohavingamorecoherentlegalbasisforenforcingtheNIL,thisDecreewasthefirsttoexplicitlylisttheconditionsoninvestmentsacrossproductmarkets.13Inaddition,forthefirsttimetheDecreeprovidedaconsistentdefinition