有本事来追上我：欧洲行业的生产率差异与趋同

European

commission

EconomicandFinancialAffairs

CatchMeIfYouCan:ProductivityDispersionandConvergence

inEuropeanIndustries

WouterSimons

EUROPEANECONOMY

DISCUSSIONPAPER253|JULY2026

EuropeanCommission

Directorate-GeneralforEconomicandFinancialAffairs

CatchMeIfYouCan:

ProductivityDispersionandConvergenceinEuropeanIndustries

WouterSimons

Abstract

Thispaperinvestigateswithin-industrydispersioninlabourproductivityin19Europeancountriesover2005-2022,leveragingtheCompNetdatabase.ItdocumentstheexistenceofsubstantialgapsinproductivitywithinEUindustries,withleadingfirmsexhibitinglabourproductivitytwotofivetimeshigherthanlaggards.ThesegapsareevidentacrossallcountriesandindustriesbutparticularlypronouncedinCentralandEasternEuropean(CEE)countries,andsomewhathigherinservicesthaninmanufacturingindustries.Wefindtheselabourproductivitygapsbetweenleadersandlaggardstoberelativelypersistentovertime.Yet,inCEEcountriesweobserveagradualnarrowingoftheproductivitygapoverthelastdecade,withtheexceptionofthepandemicyear2020.

Thepaperfurtherexploresfactorsthatmayaffectproductivitygrowthamonglaggards.Wefindthatwhenlaggingfirmsarefurtherbehindthefrontier,theirlabourproductivitygrowthtendstobestronger,pointingtothepresenceofalabourproductivitycatch-upeffect.Wefindthiscatch-upeffecttobeunaffectedbythedigitalorintangibleintensityoftheindustry.Finally,inindustrieswherelaggingfirmsarerelativelycapitalintensive,theirproductivitygrowthperformanceisstronger.

Ourfindingshelptoshedlightonwithin-industryproductivitydynamics.Theyunderscoretheneedforpoliciestostrikeabalancebetweenfosteringtheinnovativeactivityoffrontierfirmsandimprovingthediffusionoftheseinnovationsthroughoutthefirmpopulation.

JELClassification:D24,E22,L11,L25,O33,O47,O52.

Keywords:Labourproductivity,productivitydispersion,productivitygrowth,convergence,CompNetdata.

Acknowledgements:TheauthorisgratefultoLizaArchanskaia,WilliamConnell,BjörnDöhring,MirkoLicchetta,AlessandroTurriniandLukasVogelforvaluablecommentsandsuggestions.

Contact:WouterSimons,wouter.simons@ec.europa.eu,EuropeanCommission,Directorate-GeneralforInternalMarket,Industry,EntrepreneurshipandSMEs.

EUROPEANECONOMYDiscussionPaper253

CONTENTS

1.Introduction 3

2.Data 4

3.Within-industryproductivitydispersion 6

3.1.Astaticview 7

3.2.Adynamicview 9

4.ProductivitygrowthofLaggingfirms 13

5.Conclusion 16

REFERENCES 17

ANNEXI 18

TABLES

Table4.1.Regressionresults:driversoflaggards’productivitygrowth 14

GRAPHS

Graph3.1.Industry-levellabourproductivityvs.labourproductivitygapbetween10%mostand

10%leastproductivefirms–allindustries(2010-2021)

6

Graph3.2.Labourproductivitydifference(realvalueaddedperemployee,inlogs)between10%

mostproductiveand10%leastproductivefirms–subsetofmanufacturingindustries 7

Graph3.3.Labourproductivitydifference(realvalueaddedperemployee,inlogs)between10%

mostproductiveand10%leastproductivefirms–services 8

Graph3.4.Boxplotofwithin-industrygapsinlabourproductivity(realvalueaddedperemployee,

inlogs)between10%mostproductiveand10%leastproductivefirms,across

industries 8

Graph3.5.Densityplotofthegapinlabourproductivity(realvalueaddedperemployee,inlogs)

between10%mostproductiveand10%leastproductivefirms(2010-2022) 9

Graph3.6.Within-industrygapinlabourproductivity(realvalueaddedperemployee,inlogs),

averageover2010-2012vs.over2017-2019 10

Graph3.7.Within-industrygapinlabourproductivityover2010-2022–WesternEuropeanvs.CEE

countries 11

Graph3.8.Labourproductivityofleadersandlaggardsover2010-2022–WesternEuropeanvs.

CEEcountries 12

GraphA.1.Within-industrygapinlabourproductivityover2010-2022–WesternEuropeanvs.CEE

countries,manufacturingvs.services 18

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1.INTRODUCTION

GrowthintheEUhasbeencomparativelyslowoverthepastdecades,drivenbyweakeningproductivitygrowth.ProductivitygrowthhasbeensubduedinEuropesincethemid-90s,substantiallylaggingbehindthatoftheUS.

1

RaisingcompetitivenessandreignitingproductivityarecrucialtoreviveeconomicgrowthinEurope,asemphasisedforcefullyintheDraghireport(2024).TherelativelyweakinnovationperformanceoftheEU(i.e.the“innovationgap”),theslowingdiffusionoftechnologyfromfrontiertolaggingfirms,thelackofbusinessdynamismandthemanybarriersfacedbycompaniestoscaleupareamongthekeychallengesputforwardintheDraghireport.Thesefactorsmaycontributetoanincreasingproductivitydispersionbetweenfirms,whichultimatelyputsadragonaggregategrowth.

2

TheaimofthispaperistoshedlightonproductivitydispersionandconvergenceinEuropeanindustries.Fordataavailabilityreasons,thepaperfocusesonlabourproductivity.

Alargebodyofresearchhasemphasisedtheimportanceoffirmheterogeneityforunderstandingaggregateproductivitydynamics.BuildingontheseminalcontributionsofHopenhayn(1992)andMelitz(2003),agrowingliteraturehasshownthatproductivitydifferencesacrossfirmswithinnarrowlydefinedindustriesaresubstantialandpersistent(Corradoetal.,2021;Andrewsetal.,2016;HsiehandKlenow,2009;Syverson,2004).Thesefindingshaveshiftedattentionawayfromrepresentative-firmapproachestowardsanalysesthataccountfortheallocationofresourcesacrossheterogeneousfirmsandthemechanismsthroughwhichtechnologyandmanagerialpracticesdiffusewithinindustries.Indeed,thesestudieshavehighlightedtheroleofweakeningdiffusion,businessdynamism,resourcemisallocationandintangibleassetsinshapingproductivitygrowthanddispersion(e.g.Corradoetal.,2021;Andrewsetal.,2016;HsiehandKlenow,2009).Againstthisbackdrop,understandingtheevolutionofproductivitydispersionwithinEuropeanindustriesisparticularlyrelevant,givenconcernsaboutEurope’sinnovationperformance,scale-upcapacityandtechnologyadoption.However,despiteextensiveevidenceonfirmheterogeneityandproductivitygaps,lessisknownabouthowthesepatternshaverecentlyevolvedacrossEuropeanindustriesandcountries.Thispaperaimstoaddressthisgap.

Analysingproductivitydispersionprovidesadditionalinsightsbeyondthoseobtainedfromaggregateproductivitymeasures.Theexistenceofsignificantintra-industrygapsinproductivitysuggeststhatitmaynotsufficetoanalyseproductivityattheaggregateindustry-level:industrieswithsimilaraggregateproductivitydynamicsmaybecharacterisedbydifferentunderlyingdistributions,withdifferentimplicationsforpolicy.Indeed,sluggishproductivitygrowthcouldbeduetoalackofinnovativeperformersatthetop,ortoomanylaggingfirmsatthebottom,pointingtoweakbusinessdynamism(firmexit).Themaincontributionofthispaperisthereforetoprovideasystematicanalysisofthelevelandevolutionofwithin-industryproductivitydispersioninEuropeusingmicro-aggregateddata,whichallowtouncovertrendsandpatternsthatareoftenobscuredinmoreaggregateddatasets.

ToinvestigateproductivitydispersioninEuropeanindustries,thispaperleveragestheCompNetdatabase,whichprovidesharmonisedindicatorsderivedfromfirm-leveldataforaround20Europeancountriesandabroadrangeofindustriesuntil2022.WhiletheinformationintheCompNetdatabaseisgroundedinfirm-leveldata,itprovidesnoinformationaboutindividualfirms.Instead,firm-levelinformationisaggregatedtodifferentlevels(industries,countries,…)andpublishedasmicro-aggregatedindicators.Nevertheless,thedatabaseallowsustodocumentproductivitydispersionwithinindustries–inparticularthegapbetweenleadingandlaggingfirms–forarangeofEuropeancountries,byanalysingthedifferentmomentsofthewithin-industrylabourproductivitydistribution.Wemaximisecountrycoveragebyexploitingdatafromthe9thand10thVintageoftheCompNetdatabase,resultinginanunbalancedsampleof19countries,35industriesandtheyears2005-2022.

1SeeforinstanceNikolov,P.,Simons,W.,Turrini,A.andVoigt,P.(2026).“Mid-TechEurope?SectoralPatternsofTotalFactorProductivityGrowthintheEUvs.theUS”,Intereconomics,61(1),40-49.

2SeeforinstanceBerlingieri,G.,Calligaris,S.,Criscuolo,C.,andVerlhac,R.(2025).“Lastbutnotleast:Laggardfirms,technologydiffusion,anditsstructuralandpolicydeterminants”,InternationalEconomicReview,66(2),595–627.

/10.1111/iere.12748

andAndrews,D.,Criscuolo,C.andGal,P.(2016),"TheBestversustheRest:TheGlobalProductivitySlowdown,DivergenceacrossFirmsandtheRoleofPublicPolicy",OECDProductivityWorkingPapers,No.5,OECDPublishing,Paris,

/10.1787/63629cc9-en.

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Thispapercomplementsandextendspreviousworkonthisdatabasebyprovidinganelaborateanalysisoflabourproductivitydispersionandconvergence.Tothebestofourknowledge,theanalysisinthispapergoesbeyondpreviousworkonthesedata,includingtheCompNet(2025)flagshipfirmproductivityreport.Ourpaperanalysesproductivitydispersionfrombothastaticanddynamicpointofview,documentingdifferencesacrosscountriesintheextentandtheevolutionofwithin-industrygapsinlabourproductivity.Italsotestsforthepresenceofacatch-upeffectinlabourproductivitygrowthandexploresifthiscatch-upisaffectedbyfactorslikethedigitalorintangibleintensityoftheindustry.Italsoanalysestheroleoflaggards’capitalintensityasadriveroftheirproductivitygrowth.

Theremainderofthispaperisstructuredasfollows.Thenextsectiondescribesthedata.Section3documentswithin-industryproductivitydispersionanditstrendsovertime.Section4investigatesfactorsaffectingproductivitygrowthamonglaggingfirms.Thefinalsectionconcludes.

2.DATA

ThispaperreliesontheCompNetdatabase,arichdatasetgroundedinfirm-leveldatathatspansaround20Europeancountriesandawiderangeofindustriesovertheperiod2000-2022.

3

The10thVintageoftheCompNetdatabasewasreleasedinthespringof2025andcontainsanunbalancedpaneldatasetcovering17Europeancountries.FourMemberStates(Belgium,Finland,ItalyandSweden)werecoveredinthe9thVintagebutarenotincluded,atthetimeofwriting,inthe10thVintage.Tomaximisecountrycoverage,dataforthesefourcountriesfromthe9thVintage(until2019)aremergedwiththe10thVintage.TheCompNetdatabaseprovidesinformationforthefullsamplethatincludesallfirmsinthetargetpopulation,andforasubsamplethatonlyincludesfirmswith20ormoreemployees.The+20emplsampleensurescomparabilityacrosscountries,sincefirmsinsomecountriesarenotobligedtoreporttheirbalancesheetdatabelowacertainsizethreshold(e.g.GermanyandPoland).Forthisreason,wefocusonthesampleoffirmswithatleast20employeesinthispaper.

WhiletheCompNetdatabasedoesnotcontaininformationonindividualfirms,itprovidesdetailedinformationontheunderlyingdistributionoffirm-leveloutcomesatdifferentlevelsofaggregation.Thedatabasecoversvariousaspectsofeconomicperformance:Competition,Productivity,Labour,Trade,andFinance.Firm-levelinformationontheseindicatorsisnotpublishedassuchbutaggregatedtodifferentlevels(industries,countries,regions,…)andpublishedasmicro-aggregatedindicators.Thedatabasethusprovidesthemomentsofthedistribution(within-industry,within-country,…)foreachoftheseindicators.Toillustrate,considerlabourproductivityamongfoodproducersinGermany.Ratherthanreportingproductivityofeachindividualfirminthisindustry,thedatabaseprovidesdistributionalstatistics:e.g.the10thpercentilethatcapturestheproductivitylevelbelowwhich10%ofGermanfoodproducersarelocated.Suchinformationmakesitpossibletoanalyseproductivitydispersionwithinindustrieswhilepreservingfirmconfidentiality.

The2-digitindustry-levelclassificationformsthebasisofanalysisinthispaper.Theprimaryfocusofthispaperisonproductivitydispersionatthemostdisaggregate,industry2-digit(NACERev.2)levelofaggregation.Webelievethe2-digitindustryclassificationtobethemostappropriatelevelofaggregationtoanalyseproductivitydispersion.

4

Itensuresthatcomparisonsaremadebetweenfirmsthatoperatewithbroadlysimilartechnologiesandproductionprocesses,whichiscrucialforameaningfulanalysisofproductivitydifferences.Indeed,productivitydifferenceswithinanaggregate1-digitsectorlikemanufacturingmaynotnecessarilyreflectdifferencesbetweentopandbottomperformingfirms,butratherbetweenfirmswithverydifferentactivities.

5

3Formoreinformation,seetheCompNetwebsite:

https://www.iwh-halle.de/en/compnet.

Researcherscanfreelyapplyforaccesstothedatabase.

4Limiteddataavailabilitypreventstheuseofanevenfinersectoralclassification(e.g.at4-digitlevel),whichwouldbethefirstbestforthistypeofanalysis.

5ThemedianlabourproductivityfoodproducerinGermany,forinstance,wouldrankamongthe10%leastproductiveGermanmachinerymanufacturers.

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Thefocusofthispaperisondispersioninlabourproductivity.Productivityistypicallymeasuredbylabourproductivityortotalfactorproductivity(TFP).TheTFPmeasurecapturestheefficiencywithwhichfirmstransforminputsintooutputandthusisolatestheroleoftechnologyandorganisationalcapital.LabourproductivityreflectsnotonlytheefficiencycapturedbyTFPbutalsodifferencesininputintensity,especiallycapitaldeepening.Fordataavailabilityreasons,thispaperfocusessolelyondispersionandgrowthinlabourproductivity.

6

WhileananalysisofTFPwouldhelpsharpenthedistinctionbetweentechnologicalandinput-relatedsourcesofproductivityheterogeneity,focusingonlabourproductivityalonecanalreadyprovidevaluableinsightsintothemechanismsofproductivitydivergenceanddiffusion.Differencesinlabourproductivityreflectbothefficiencygapsanddisparitiesininputintensityandcanthereforesignalfrictionsinthediffusionofinnovation,weakresourcereallocation,orunevencapitalandskillaccumulation.Moreover,becauselabourproductivitydirectlylinkstowages,employment,andcompetitiveness,analysingitsdispersioncanshedlightonhowunevenperformanceacrossfirmsmaytranslateintobroadereconomicoutcomes.

Productivitydispersionwithinanindustrycanbeunderpinnedwitharangeofindicators,eachhighlightingdifferentaspectsofdispersion.Inthispaper,wewillmeasuredispersioninlabourproductivitybycomparingproductivitylevelsoftwoextrememomentsofthewithin-industryproductivitydistribution,notablythe10thand90thpercentile.Incaseofdataunavailability,thebottomandtopquintile(20%)ofthedistributionarecomparedinstead.Thechoiceofourcoremeasureofdispersion,thelogratioofproductivityofthetopdecileandthebottomdecileoffirms(orbottomandtopquintiles),isnotonlymotivatedbyitseaseofinterpretation,butalsoitsabilitytocapturethesignificantdifferencesbetweentheextremesoftheproductivitydistribution,whichcarryhighrelevanceforpolicy.Indeed,thep90/p10measureunderscoresthegapbetweenthemostproductive“leading”firms,oftenatthetechnologicalfrontier,andthosethatlagbehind,providinganindicationofpolarisationwithinanindustry.

7

Byfocusingonthetailsofthedistribution,thelogdecileratioallowsustoassesswhetherleadingfirmsarepullingawayfromtherest,orwhetheranarrowinggapsuggestscatch-updynamicsbylaggingfirms.Thismakesitaneffectivetoolforunderstandingboththeextentofdispersionanditsimplicationsforindustry-wideperformance.

Theanalysisinthispaperisrestrictedtoareliablesubsetofcountries,industriesandyears.Fordataqualityreasons,werestrictthesampleinthispapertoasetof19countries(Belgium,Czechia,Germany,Denmark,Spain,Finland,France,Croatia,Hungary,Italy,Lithuania,Netherlands,Poland,Portugal,Romania,Sweden,Slovenia,SlovakiaandSwitzerland),35industries(16manufacturing,19services)andtheyears2005-2022.Thesecountries,industriesandyearsconstitutethesubsetofthedatabasethatmeetscertainthresholdsofreliabilityandcoverage.Inparticular,weexcludecountry-industrieswithaninsufficientsamplesize(i.e.lessthan30firms)tomitigateconcernsaboutthereliabilityandinterpretationofthemomentsofthefirmdistribution.

8

Moreover,country-industryobservationswithimplausiblejumpsinsomeindicators(e.g.samplesizeincreasingtenfoldfromoneyeartothenext)arealsoexcluded.Severalanalysesinthispaperrelyonasamplethatisrestrictedevenfurther(alongthecountry,industryandtimedimensions)incaseabalancedpanelisrequired,dataqualityrequirementsaremorestringentorcomplementarydatasetsareused.Throughoutthepaper,detailsonthespecificsampleusedareprovidedbelowthegraphsandtables.ForadetailedassessmentofCompNetdataquality,reliabilityandcross-countrycomparability,wereferthereadertoCompNet(2018).

9

6Anadditionalmotivationforfocusingonlabourproductivity,adirectlyobservedmeasure,stemsfromthepracticalchallengesinmeasuringfirm-levelTFP.See,forinstance,Syverson,C.(2011)."WhatDeterminesProductivity?",JournalofEconomicLiterature,49(2),326–365.

7Thistypeofmeasureofproductivitydispersioniswidelyusedintheliterature.See,forinstance,Syverson,C.(2004).“ProductSubstitutabilityandProductivityDispersion.”TheReviewofEconomicsandStatistics,86(2),534–550.;Bormans,Y.,Theodorakopoulos,A.

(2023),“Productivitydispersion,wagedispersionandsuperstarfirms”,Economica,90(360),1145-1172.;andBerlingierietal.(2025).

8Dataqualityissueswithmicro-aggregatedindicatorsmayarisefromsmallsamplesizes,atthecountry-industry-yearlevel,usedtoconstructthem.Withsmallsamplesizes,variouschallengesmayarise.Theycanhinderrobustnessoffindings,leadtogapsinthedata,triggerconfidentialityconcerns(tothepointwherethedataproviderrestrictspublicationofthedata)orpreventexaminingvariousmomentsofthewithin-industrydistribution.Insomecases,theCompNetdatabasemayprovideinformationonthemomentsofthedistribution(includingextremepercentilessuchasp5andp95),evenifthesampleoffirmsinthecountry-industryissmall(e.g.lessthan20firms).

9CompNet(2018),“AssessingthereliabilityoftheCompNetmicro-aggregateddatasetforpolicyanalysisandresearch:Coverage,representativenessandcross-EUcomparability”.

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3.WITHIN-INDUSTRYPRODUCTIVITYDISPERSION

Thissectionpresentsbothastaticandadynamicviewofproductivitydispersion.Investigatingproductivitydispersionmayprovideusefulinsightstopolicy,asithelpsuncovertheunderlyingmechanismsthatdriveaggregateproductivity.Aggregate(industry-level)productivityreflectsboththeproductivityofindividualfirmsoperatinginanindustryandhowresourcesormarketsharesareallocatedacrossthem.Inthissense,dispersionisinformativeaboutthedegreeofheterogeneitywithinindustriesandtheextenttowhichproductivityadvantagesatthefrontieraretransmittedtotherestoftheeconomy.Widegapsinproductivitybetweenleadingandlaggingfirmsmayreflectstructuralissues,suchasbarrierstodiffusion,differencesinaccesstocapital,orvaryinglevelsoftechnologicaladoption.Ifinnovationandtechnologicaladvancementsfailtoreachfirmsatthebottom,aggregateproductivitymayremainbelowitspotential.

1011

Indeed,aggregateproductivitytendstobeweakerinindustrieswithhigherproductivitydispersion.Graph3.1showsanegativerelationshipbetweenproductivitydispersionandaggregateproductivityattheindustry-level:industrieswithalargergapbetweenleadersandlaggardsarecharacterisedbyloweraggregateproductivity.

12

Thisnegativerelationshipisstatisticallysignificantandholdsformanufacturingandservices.

13

Ourestimatessuggestthataca.10%higherlabourproductivitygapbetweenleadersandlaggardsisassociatedwitha3%loweraverageindustry-levellabourproductivity.Understandingthesegapscanprovideusefulinsights,motivatingacloseranalysisofproductivitydispersionwithinindustries.Thisisthesubjectofthissection.

Graph3.1.Industry-levellabourproductivityvs.labourproductivitygapbetween10%mostand10%leastproductivefirms–allindustries(2010-2021)

Note:Aggregateindustry-levellabourproductivityisobtainedasthemeanrealvalueaddedperemployee(inlogs)inthecountry-industry,whilelabourproductivitydispersionwithintheindustryiscomputedasthe

10Moreover,persistingdisparitiescouldalsohavesocialimplications:typically,thereisastrongandpositiverelationbetweenafirm’sproductivityandthewagesitpays,i.e.wagesarehigherinhigher-productivityfirms.Therefore,higherproductivitydispersionbetweenfirmswithinanindustrymayimplyhigherwageinequality.SeeforinstanceBerlingieri,G.,Calligaris,S.andCriscuolo,C.(2018),"Theproductivity-wagepremium:Doessizestillmatterinaserviceeconomy?",OECDScience,TechnologyandIndustryWorkingPapers,No.2018/13,OECDPublishing,Paris,

/10.1787/04e36c29-en.

11Nevertheless,productivitygapsneednotbeasignofamalfunctioningeconomy;infact,theymayreflectthepresenceofhighlyproductive,innovativefirmsatthetop,whichdrivetechnologicaladvancements.Also,winner-take-alldynamics,whereallocativeefficiencyimprovesastopfirmsgainmarketshare,mayresultinhigherproductivityattheaggregate.

12Wetaketheunweightedaverageacrossthecountriesinoursampleforbothindustry-levellabourproductivityandtheleader-laggardlabourproductivitygapandpurgethemofyearandindustryfixedeffects.SeeAndrewsetal.(2016),op.cit.

13SimilarresultsarefoundinAndrewsetal.(2016)forTFPforasampleofOECDcountriesandasimilarsetofindustriesfortheperiod1998-2007.

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differenceinrealvalueaddedperemployee(inlogs)betweentopandbottom10%offirms.Forbothvariables,wecomputetheunweightedaverageof19countries(Belgium,Czechia,Germany,Denmark,Spain,Finland,France,Croatia,Hungary,Italy,Lithuania,Netherlands,Poland,Portugal,Romania,Sweden,Slovenia,SlovakiaandSwitzerland),foreachyearfrom2005to2021andfor35industries(16manufacturing,19services).Inthenextstep,wepurgetheindustry-yearobservationsofindustryandtimeeffectsbyregressingbothaggregateproductivityandproductivitydispersiononindustryfixedeffectsandyearfixedeffects.Theresidualsoftheregressionsareplottedinthegraph.Ourfindingsaresimilarwhen,insteadofindustry-levelobservations(averagingacrosscountries),weplotcountry-industryobservations(purgedofcountry-industryandyeareffects).

Source:Ownelaborationsbasedonthe10thVintageand9thVintage(forBE,FI,ITandSE)ofCompNet(20Esample);

/.

3.1.ASTATICVIEW

Allcountriesandindustriesinoursamplearecharacterisedbyapronouncedgapinlabourproductivitybetweenleadingandlaggingfirms.Thereisanotabledifferenceinlabourproductivitybetweentopandbottomperformers.Graphs3.2and3.3showthat,acrossmostcountriesandindustriesin2021,labourproductivityofthe10%mostefficientfirmsinanindustryis2to5timesashighasthatofthe10%firmsatthebottomoftheproductivitydistribution(logdifferencerangingfrom0.5to1.5).Thesemagnitudesofdispersionareinlinewithotherstudies(e.g.Syverson,2004,fortheUS).

Therearesignificantdifferencesacrosscountriesinthemagnitudeoftheproductivitygap.Whilethereisanotabledifferenceinlabourproductivitybetweentopandbottomperformersinallcountries,somecountriesarecharacterisedbyrelativelylargerwithin-industryproductivitygaps.Graph3.4showsthatlabourproductivitygapsaremorepronouncedine.g.HungaryandSlovakia,withmedianindustryvaluesofmorethan1.5(logdifference)indicatingthatinmanyindustriesinthesecountries,topfirmsareatleastfivetimesasproductiveasbottomfirms.Finland,ontheotherhand,ischaracterisedbyrelativelysmallproductivitygapsinitsindustries.

Graph3.2.Labourproductivitydifference(realvalueaddedperemployee,inlogs)between10%mostproductiveand10%leastproductivefirms–subsetofman