AI对劳动力市场的影响研究

ANTHROP\C

LabormarketimpactsofAI:

Anewmeasure

andearlyevidence

PublishedAuthors

March5,2026MaximMassenkoffandPeterMcCrory

Acknowledgements

RuthAppel,TimBelonax,KeirBradwell,AndyBraden,DexterCallenderIII,MiriamChaum,MadisonClark,JakeEaton,

DeepGanguli,KunalHanda,RyanHeller,LaraKaradogan,JenniferMartinez,JaredMueller,SarahPollack,David

Saunders,CarlDeTorres,JackClark.

WeadditionallythankMarthaGimbel,AndersHumlum,EvanRose,andNathanWilmersforfeedbackonearlierversions

ofthisnote.

LabormarketimpactsofAI:

Keyfindings

•WeintroduceanewmeasureofAIdisplacementrisk,observedexposure,thatcombinestheoreticalLLMcapabilityandreal-worldusagedata,weighting

automated(ratherthanaugmentative)andwork-relatedusesmoreheavily

•AIisfarfromreachingitstheoreticalcapability:actualcoverageremainsafractionofwhat’sfeasible

•OccupationswithhigherobservedexposureareprojectedbytheBLStogrowlessthrough2034

•Workersinthemostexposedprofessionsaremorelikelytobeolder,female,moreeducated,andhigher-paid

•Wefindnosystematicincreaseinunemploymentforhighlyexposedworkerssincelate2022,thoughwefindsuggestiveevidencethathiringofyounger

workershasslowedinexposedoccupations

Anoverviewofourmethodandsomeofourmainresults

SeebelowforhowwemeasuretaskcoverageandtheimpactsofAIonunemployment.

LabormarketimpactsofAI,

TherapiddifusionofAIisgeneratingawaveofresearchmeasuringandforecastingitsimpactsonlabormarkets.Butthetrackrecordofpast

approachesgivesreasonforhumility.

Forexample,aprominentattempttomeasurejobofshorabilityidentified

roughlyaquarterofUSjobsasvulnerable,butadecadeon,mostofthosejobsmaintainedhealthyemploymentgrowth.Thegovernment’sownoccupationalgrowthforecasts,whiledirectionallycorrect,haveaddedlittlepredictivevaluebeyondlinearextrapolationofpasttrends.Eveninhindsight,theimpactof

majoreconomicdisruptionsonthelabormarketisoftenunclear.Studiesontheemploymentefectsofindustrialrobotsreachopposingconclusions,andthe

scaleofjoblossesattributedtotheChinatradeshockcontinuestobedebated.1

Inthispaper,wepresentanewframeworkforunderstandingAI’slabor

marketimpacts,andtestitagainstearlydata,findinglimitedevidencethatAIhasafectedemploymenttodate.OurgoalistoestablishanapproachformeasuringhowAIisafectingemployment,andtorevisittheseanalyses

periodically.Thisapproachwon’tcaptureeverychannelthroughwhichAIcouldreshapethelabormarket,butbylayingthisgroundworknow,beforemeaningfulefectshaveemerged,wehopefuturefindingswillmorereliablyidentifyeconomicdisruptionthanpost-hocanalyses.

ItispossiblethattheimpactsofAIwillbeunmistakable.Thisframeworkis

mostusefulwhentheefectsareambiguous—andcouldhelpidentifythemostvulnerablejobsbeforedisplacementisvisible.

Counterfactuals

Causalinferenceiseasierwhentheefectsarelargeandsudden.The

COVID-19pandemicandaccompanyingpolicymeasurescausedeconomic

disruptionsostarkthatsophisticatedstatisticalapproacheswereunnecessaryformanyquestions.Forexample,unemploymentjumpedsharplyintheearlyweeksofthepandemic,leavinglittleroomforalternativeexplanations.

TheimpactsofAI,however,mightbelesslikeCOVIDandmorelikethe

internetortradewithChina.Theefectsmaynotbeimmediatelyclearfrom

aggregateunemploymentdata;factorsliketradepolicyandthebusinesscyclecouldcloudinterpretationsoftrendlines.

LabormarketimpactsofAI.

OnecommonapproachistocompareoutcomesbetweenmoreorlessAI-

exposedworkers,firms,orindustries,inordertoisolatetheefectofAIfrom

confoundingforces.2Exposureistypicallydefinedatthetasklevel:AIcangradehomeworkbutnotmanageaclassroom,forexample,soteachersareconsideredlessexposedthanworkerswhoseentirejobcanbeperformedremotely.

Ourworkfollowsthistask-basedapproach,incorporatingmeasuresoftheoreticalAIcapabilityandreal-worldusage,beforeaggregatingtooccupations.³

Measuringexposure

Ourapproachcombinesdatafromthreesources.

•The

O*NET

database,whichenumeratestasksassociatedwitharound800uniqueoccupationsintheUS.

•Ourownusagedata(asmeasuredinthe

AnthropicEconomicIndex

).

•Task-levelexposureestimatesfromEloundouetal.(2023),whichmeasure

whetheritistheoreticallypossibleforanLLMtomakeataskatleasttwiceasfast.

Figure1:ShareofClaudeusagebyEloundouetal.taskexposurerating

ThisfigureshowsClaudeusagedistributedacrossO*NETtasksgroupedbytheirtheoreticalAIexposure.Tasksratedβ=1(fullyfeasibleforanLLMalone)accountfor68%ofobservedClaudeusage,whiletasksratedβ=0

(notfeasible)accountforjust3%.DataonClaudeusagecomesfromthepreviousfourEconomicIndexreports.

LabormarketimpactsofAI5

Eloundouetal.’smetric,β,scorestasksonasimplescale:1ifataskcanbe

doubledinspeedbyanLLMalone,0.5ifitrequiresadditionaltoolsorsoftwarebuiltontopoftheLLM,and0otherwise.⁴

Whymightactualusagefallshortoftheoreticalcapability?Sometasks

thataretheoreticallypossiblemaynotshowupinusagebecauseofmodel

limitations.Othersmaybeslowtodifuseduetolegalconstraints,specific

softwarerequirements,humanverificationsteps,orotherhurdles.For

example,Eloundouetal.mark“Authorizedrugrefillsandprovideprescriptioninformationtopharmacies”asfullyexposed(β=1).Wehavenotobserved

Claudeperformingthistask,althoughtheassessmentseemscorrectinthatitcouldtheoreticallybespedupbyanLLM.

Thatsaid,thesemeasuresoftheoreticalcapabilityandactualusagearehighlycorrelated.AsFigure1shows,97%ofthetasksobservedacrossthepreviousfourEconomicIndexreportsfallintocategoriesratedastheoreticallyfeasiblebyEloundouetal.(β=0.5orβ=1.0).

Anewmeasureofoccupationalexposure

Ournewmeasure,ObservedExposure,ismeanttoquantify:ofthosetasksthatLLMscouldtheoreticallyspeedup,whichareactuallyseeingautomatedusageinprofessionalsettings?Theoreticalcapabilityencompassesamuchbroaderrangeoftasks.Bytrackinghowthatgapnarrows,observedexposureprovidesinsightintoeconomicchangesastheyemerge.

OurmeasurequalitativelycapturesseveralaspectsofAIusagethatwethinkarepredictiveofjobimpacts.Ajob’sexposureishigherif:

•ItstasksaretheoreticallypossiblewithAI

•ItstasksseesignificantusageintheAnthropicEconomicIndex⁵

•Itstasksareperformedinwork-relatedcontexts

•IthasarelativelyhighershareofautomatedusepatternsorAPIimplementation

•ItsAI-impactedtasksmakeupalargershareoftheoverallrole⁶

LabormarketimpactsofAI6

WegivemathematicaldetailsintheAppendix.⁷Wecounttasksthatare

theoreticallycapablewithanLLMascoverediftheyhaveseensufficientwork-relatedusageinClaudetraffic.Wethenadjustforhowthetaskisbeingcarriedout:fullyautomatedimplementationsreceivefullweight,whileaugmentativeusereceiveshalfweight.Finally,thetask-levelcoveragemeasuresareaveragedtotheoccupationlevelweightedbythefractionoftimespentoneachtask.

Figure2:Theoreticalcapabilityandobservedexposurebyoccupationalcategory

ThisfigureshowstheshareofjobtasksthatLLMscouldtheoreticallyperform(bluearea)andourownjobcoveragemeasurederivedfromusagedata(redarea).

LabormarketimpactsofAI,

Figure2showsobservedexposure(inred)comparedtoβfromEloundouet

al.(inblue),illustratingthediferencebetweentheoreticalandactualuseonourplatform,groupedbybroadoccupationalcategories.Wecalculatethisbyfirstaveragingtotheoccupationlevelweightingbyourtimefractionmeasure,thenaveragingtotheoccupationcategoryweightingbytotalemployment.Forexample,theβmeasureshowsscopeforLLMpenetrationinthemajorityof

tasksinComputer&Math(94%)andOffice&Admin(90%)occupations.

Theredarea,depictingLLMusefromtheAnthropicEconomicIndex,showshowpeopleareusingClaudeinprofessionalsettings.ThecoverageshowsAIisfarfromreachingitstheoreticalcapabilities.Forinstance,Claudecurrentlycoversjust33%ofalltasksintheComputer&Mathcategory.

Ascapabilitiesadvance,adoptionspreads,anddeploymentdeepens,theredareawillgrowtocovertheblue.Thereisalargeuncoveredareatoo;manytasks,of

course,remainbeyondAI’sreach—fromphysicalagriculturalworklikepruning

treesandoperatingfarmmachinerytolegaltaskslikerepresentingclientsincourt.

Figure3showsthetenoccupationsmostexposedunderthismeasure.InlinewithotherdatashowingthatClaudeisextensivelyusedforcoding,Computer

Figure3:Mostexposedoccupations

Thisfigureshowsthetoptenmostexposedoccupationsusingourtaskcoveragemeasure.

LabormarketimpactsofAI.

Programmersareatthetop,with75%coverage,followedbyCustomerServiceRepresentatives,whosemaintasksweincreasinglyseeinfirst-partyAPItraffic.Finally,DataEntryKeyers,whoseprimarytaskofreadingsourcedocuments

andenteringdataseessignificantautomation,are67%covered.

Atthebottomend,30%ofworkershavezerocoverage,astheirtasksappearedtooinfrequentlyinourdatatomeettheminimumthreshold.Thisgroup

includes,forexample,Cooks,MotorcycleMechanics,Lifeguards,Bartenders,Dishwashers,andDressingRoomAttendants.

Howexposuretrackswithprojectedjobgrowthandworkercharacteristics

TheUSBureauofLaborStatistics(BLS)publishesregularemployment

projections,withthelatestset,publishedin2025,covering

predicted

changesinemploymentforeveryoccupationfrom2024to2034.InFigure4,we

compareourjob-levelcoveragemeasuretotheirpredictions.

Figure4:BLSprojectedemploymentgrowthfrom2024–2034vs.observedexposure

Thisisabinnedscatterplotwith25equally-sizedbins.Eachsoliddotshowstheaverageobservedexposureandprojectedemploymentchangeforoneofthebins.Thedashedlineshowsasimplelinearregressionfit,weightedbycurrentemploymentlevels.Thesmallsquaresmarkindividualexampleoccupationsforillustration.

LabormarketimpactsofAI,

Aregressionattheoccupationlevelweightedbycurrentemploymentfinds

thatgrowthprojectionsaresomewhatweakerforjobswithmoreobserved

exposure.Forevery10percentagepointincreaseincoverage,theBLS’sgrowthprojectiondropsby0.6percentagepoints.Thisprovidessomevalidation

inthatourmeasurestracktheindependentlyderivedestimatesfromlabormarketanalysts,althoughtherelationshipisslight.Interestingly,thereisnosuchcorrelationusingtheEloundouetal.measurealone.

Figure5showscharacteristicsofworkersinthetopquartileofexposure

andthe30%ofworkerswithzeroexposureinthethreemonthsbefore

ChatGPTwasreleased,AugusttoOctober2022,usingdatafromtheCurrentPopulationSurvey.Thegroupsareverydiferent.Themoreexposedgroup

is16percentagepointsmorelikelytobefemale,11percentagepointsmore

likelytobewhite,andalmosttwiceaslikelytobeAsian.Theyearn47%more,onaverage,andhavehigherlevelsofeducation.Forexample,peoplewith

graduatedegreesare4.5%oftheunexposedgroup,but17.4%ofthemostexposedgroup,analmostfourfolddiference.

Figure5:Differencesbetweenhighandlowexposureworkers,CurrentPopulationSurvey

Thistableshowsexposure,demographics,education,andlabormarketoutcomes.

LabormarketimpactsofAI10

Prioritizingoutcomes

Withtheseexposuremeasuresinhand,thequestioniswhattolookfor.

Researchershavetakendiferentapproaches.Forexample,Gimbeletal.

(2025)trackchangesintheoccupationalmixusingtheCurrentPopulationSurvey.TheirargumentisthatanyimportantrestructuringoftheeconomyfromAIwouldshowupaschangesindistributionofjobs.¹(Theyfindthat,sofar,changeshavebeenunremarkable.)Brynjolfssonetal.(2025)lookatemploymentlevelssplitbyagegroupusingdatafromthepayrollprocessingfirmADP,whileAcemogluetal.(2022)andHampoleetal.(2025)usejob

postingdatafromBurningGlass(nowLightcast)andRevelio,respectively.

Wefocusonunemploymentasourpriorityoutcomebecauseitmostdirectly

capturesthepotentialforeconomicharm—aworkerwhoisunemployedwantsajobandhasnotyetfoundone.Inthiscase,jobpostingsandemploymentdonotnecessarilysignaltheneedforpolicyresponses;adeclineinjobpostings

forahighlyexposedrolemaybecounteractedbyincreasedopeningsina

relatedone.MostharmfullabormarketdevelopmentsofAIshouldarguablyincludeaperiodofincreasedunemployment,asdisplacedworkerssearchforalternatives.TheCurrentPopulationSurveyiswellsuitedtotrackingthis,asunemployedrespondentsreporttheirpreviousjobandindustry.

Initialresults

Wenextstudytrendsinunemployment,matchingouroccupation-levelmeasurestorespondentsintheCurrentPopulationSurvey.8

Akeyquestionininterpretingourcoveragemeasureiswhichworkersshouldbeconsideredtreated?Shouldchangesinemploymentbeexpectedfromjust10%taskcoverage?GansandGoldfarb(2025)showthatifanO-ringmodelbestdescribesjobs,employmentefectsmightbeseenonlywhenalltasks

havesomedegreeofAIpenetration.Hampoleetal.(2025)arguethatmeanexposuredecreaseslabordemand,butconcentrationofexposureinonly

certaintaskscancounteractthis.AndAutorandThompson(2025)highlightthelevelofexpertiserequiredfortheremainingtasks.

Withaneyetowardsimplicity,andnotingthatwearemostconcernedwithlargeimpacts,wecenterouranalysisontheideathatimpactsshouldbefelt

LabormarketimpactsofAI11

Figure6:TrendsintheunemploymentrateforworkersinthetopquartileofobservedexposureandnoAIexposure,CurrentPopulationSurvey

Thetoppanelshowstheunemploymentrateforworkersinthetopquartileofexposure(redline)andthe30%ofworkerswithzeroexposure.Thebottompanelmeasuresthegapbetweenthesetwoseriesinadifference-in-differencesframework.

mostinthegroupswiththehighestmeanexposure.Wecompareworkersinthetopquartileoftime-weightedtaskcoveragetothoseinthebottom.IfAI

capabilitiesadvancequickly,taskcoveragemightbehighforlowerpercentilesofcoverage,whichmightmakeanabsolutethresholdmorehelpful.Butwe

maketheassumptionthatimpactsshouldafectthemostexposedworkersfirst,andpresentresultsvaryingthecutofweusetodefinetreatment.

TheupperpanelofFigure6showsrawtrendsintheunemploymentratesince2016forworkersinthetopquartileofexposureandtheunexposedgroup.

DuringCOVID,thelessAI-exposedworkers—whoaremorelikelytohave

in-personjobs—sawamuchlargerincreaseinunemployment.Sincethen,thetrendshavebeenlargelysimilarbetweenthetwogroups.Thelowerpanel

measuresthesizeofthegapbetweenthemostandleastexposedworkersinadiference-in-diferencesframework,mirroringthefindingsfromtheraw

data.TheaveragechangeinthegapsincethereleaseofChatGPTissmallandinsignificant,suggestingthattheunemploymentrateofthemoreexposed

grouphasincreasedslightlybuttheefectisindistinguishablefromzero.,

LabormarketimpactsofAI12

Whatkindofscenarioscanthisframeworkidentify?Basedontheconfidenceintervalofthepooledestimate,diferentialincreasesinunemploymenton

theorderof1percentagepointwouldbedetectable(thiswillchangeasnewdatacomesin,soitismerelyaballparkestimate).Ifallworkerswithinthetop10%ofcoveragewerelaidof,itwouldincreaseunemploymentwithinthetopquartilegroupfrom3%to43%,anditwouldincreaseaggregate

unemploymentfrom4%to13%.

Asmallerbutstillconcerningimpactwouldbeascenariosuchasa“Great

Recessionforwhite-collarworkers.”Duringthe2007-2009GreatRecession,unemploymentratesdoubledfrom5%to10%intheUS.Suchadoublingin

thetopquartileofexposurewouldincreaseitsunemploymentratefrom3%to6%.Thisshouldbevisibleinouranalysisaswell.Notethatourcoreestimateisbasedondiferentialchangesintheunemploymentrateintheexposed

groupcomparedtothelessexposedgroup.Ifunemploymentincreasedforallworkersinparallel,wewouldnotattributethistoAIadvancementsthatstillleavemanytasksunafected.

Onegroupofparticularconcernisyoungworkers.Brynjolfssonetal.reporta6–16%fallinemploymentinexposedoccupationsamongworkersaged22to25.Theyattributethisdecreaseprimarilytoaslowdowninhiringratherthananincreaseinseparations.10

Wefindthattheunemploymentrateforyoungworkersintheexposed

occupationsisflat(seeAppendix).Butslowedhiringmaynotnecessarily

manifestasincreasedunemployment,sincemanyyoungworkersarelabor

marketentrantswithoutalistedoccupationintheCPSdataandmayexitthelaborforceratherthanappearasunemployed.Toaddresshiringdirectly,weusethepaneldimensionoftheCPS,countingthepercentofyoung(22-25yearold)workerswhobeginanewjobinamorevs.lessexposedoccupationovertime.Figure7showsthemonthlyjobstartrate(i.e.,whenaworkerreportsa

jobthattheydidnothaveinthepreviousmonth)foryoungworkers,splitbywhethertheyareenteringahigh-vs.low-exposureoccupation.

Apartfromsomelargeswingsin2020-2021,theseseriesvisuallydiverge

in2024,withyoungworkersrelativelylesslikelytobehiredintoexposed

occupations.Jobfindingratesatthelessexposedoccupationsremainstableat2%permonth,whileentryintothemostexposedjobsdecreasesbyabout

LabormarketimpactsofAI13

Figure7:Newjobstartsamongworkersage22-25inoccupationswithhighobservedexposureandnoAIexposure,CurrentPopulationSurvey

Thetoppanelshowsthepercentofyoungworkersstartingnewjobsinhighvs.noexposureoccupations.

Thebottompanelmeasuresthegapbetweenthesetwoseriesinadifference-in-differencesframework.

halfapercentagepoint.Theaveragedestimateinthepost-ChatGPTeraisa14%dropinthejobfindingratecomparedtothatin2022intheexposedoccupations,althoughthisisjustbarelystatisticallysignificant.(Thereisnosuchdecreaseforworkersolderthan25.)

ThismayprovidesomesignaloftheearlyefectsofAIonemployment,andechoesthefindingsfromBrynjolfssonetal.Butthereareseveralalternativeinterpretations.Theyoungworkerswhoarenothiredmayberemaining

attheirexistingjobs,takingdiferentjobs,orreturningtoschool.Afurtherdata-relatedcaveatisthatjobtransitionsmaybemorevulnerableto

mismeasurementinsurveys.11

Discussion

ThisreportintroducesanewmeasureforunderstandingthelabormarketefectsofAIandstudiesimpactsonunemploymentandhiring.JobsaremoreexposedtoAItotheextentthattheirtasksaretheoreticallyfeasible

LabormarketimpactsofAI14

withLLMsandobservedonourplatformsinautomated,work-relateduse

cases.Wefindthatcomputerprogrammers,customerservicerepresentatives,andfinancialanalystsareamongthemostexposed.Usingsurveydatafrom

theUS,wefindnoimpactonunemploymentratesforworkersinthemost

exposedoccupations,althoughthere’stentativeevidencethathiringintothoseprofessionshasslowedslightlyforworkersaged22-25.

OurworkisafirststeptowardcatalogingtheimpactofAIonthelabor

market.Wehopethattheanalyticalstepstakeninthisreport,especially

aroundcoverageandcounterfactuals,willbeeasytoupdateasnewdataonemploymentandAIusageemerge.Anestablishedapproachmayhelpfutureobserversseparatesignalfromnoise.

Thereareseveralimprovementstobemadetothepresentwork.Ourusage

datawillbeincorporatedinfutureupdates,forminganevolvingpictureof

taskandjobcoverageintheeconomy.TheEloundouetal.metriccouldalsobeupdated,totheextentthatitislinkedtoLLMcapabilitiesasofearly2023.And,giventhesuggestiveresultsaroundyoungworkersandlabormarketentrants,akeynextstepmightbetolookathowrecentgraduateswitheducational

credentialsinexposedareasarenavigatingthelabormarket.

Dataavailability

Observedcoverageatthetaskandjoblevelisavailableat:

https://huggingface.

co/datasets/Anthropic/EconomicIndex

.

Bibtexcitation

@online{massenkoffmccrory2026labor,

author={MaximMassenkoffandPeterMcCrory},

title={LabormarketimpactsofAI:Anewmeasureandearlyevidence},

date={2026-03-05},

year={2026},

url={

https:Ⅱ/research/labor-market-impacts

},}

LabormarketimpactsofAI15

1Jobofshorability:Blinderetal.(2009)andOzimek(2019);Governmentgrowthforecasts:Massenkof(2025);Robots:GraetzandMichaels(2018)andAcemogluandRestrepo(2020);Chinashock:Autoretal.(2013)andBorusyaketal.(2022).

2Brynjolfssonetal.(2025)compareemploymenttrendsforworkersinmoreversuslessAI-exposedoccupations,usingthetaskexposuremeasuresfromEloundouetal.(2023)andpayrolldatafromADP.JohnstonandMakridis

(2025)doasimilartask-basedanalysisusingUSadministrativedata,but

theyaggregatetreatmenttotheindustrylevel.Huietal.(2024)studyhow

freelancejobsonUpworkrespondedtothereleaseofChatGPTandadvancedimagegenerationtools,comparingworkersindirectlyafectedcategories

tothoseinunafectedcategoriesbeforeandaftereachtool’sreleasedate.

Hampoleetal.(2025)instrumentforfirm-levelAIadoptionusinghistoricaluniversityhiringnetworks:firmsthathistoricallyrecruitedfromuniversitieswhosegraduateslaterenteredAI-relatedrolesfacedloweradoptioncosts.

3Ourtask-andoccupation-levelexposuremeasurescanreadilyincorporateotherusagedata,andbeextendedtodiferentcountries.Weintendtoapplythismethodologytonewsettingsovertime.

4Intheirframework,“Directlyexposed’”taskswerethosethatcouldbe

completedinhalfthetimewithanLLM(witha2,000-wordinputlimitand

noaccesstorecentfacts).Tasksthatwere“exposedwithtools”werethose

subjecttothesamespeedupwithanLLMthathadaccesstosoftwarefor,e.g.,informationretrievalandimageprocessing.Tasksthatwerenotexposed

couldnothavetheirdurationreducedby50%ormoreusinganLLM.

5WeusetheprevioustwoAnthropicEconomicIndexdatasets,coveringusagefromAugustandNovember2025.ForONETtasksthatarehighlysemanticallysimilar,wesplitthecountsacrossthem.

6Therearejudgmentcallsinvolvedateverystep.ShouldtheEloundouet

al.(2023)measureenteras{0,0.5,1}orsomethingelse?Whatdetermines“significant”use?Howdowehandletaskswhichseemverysimilartothosewithhighusage,butaretooraretohavebeenpickedupspecificallyinthe

LabormarketimpactsofAI16

samplingfortheEconomicIndex?Howmuchmoreshouldautomation

workflowscountcomparedtoaugmentation?AreassuringfindingwhichweexpandonintheAppendixisthattheSpearman(rank-rank)correlationofjobexposureacrossmanyresolutionstothesequestionsisexceedinglyhigh.

7Appendixavailable

here

.

8TomatchO*NET-SOCcodestoocc1990codesintheCPS,weusethecrosswalkprovidedby

EckhartandGoldschlag(2025)

.

9WeexplorethisfurtherinthreewaysintheAppendix.First,weaskwhetherthepercentilecutofthatweusetodefinetreatmentmatters,varyingitfromthemediantothe95thpercentile.Inallcases,theimpactisflatornegative(meaningthatun