TheHeterogeneousImpactsofFirm

UpgradingonEnergyIntensity

PovilasLastauskas,ZiranDingandMustaphaDouch

WP/24/248

IMFWorkingPapersdescriberesearchin

progressbytheauthor(s)andarepublishedtoelicitcommentsandtoencouragedebate.

TheviewsexpressedinIMFWorkingPapersarethoseoftheauthor(s)anddonotnecessarily

representtheviewsoftheIMF,itsExecutiveBoard,orIMFmanagement.

2024

DEC

NATn

*PovilasLastauskas:InternationalMonetaryFund;ZiranDing:CEFER,BankofLithuania;MustaphaDouch:Universityof

Edinburgh.Theauthorsthankthemembersoftheirrespectivedepartmentsforcommentsonanearlierdraftofthepaper.For

helpfulcommentsanddiscussions,wealsothankJanisBerzins,Jūrat?Jarait?-Ka?ukausk?,AndriusKa?ukauskas,seminarandconferenceparticipantsattheBankofLithuania,VilniusUniversity,6thBalticEconomicConference,CEFER/KTU/VU

Workshop,andETSGconference.WearegratefultoGreysonCulbertforhisexcellentresearchassistance.ThepaperusesconfidentialdataprovidedexclusivelybyStatisticsLithuaniaandaccessedinasecureenvironmentattheBankofLithuania.TheviewsexpressedinthispaperarethoseoftheauthorsanddonotnecessarilyreflectthepositionoftheBankofLithuania,theEurosystem,ortheIMF,itsExecutiveBoard,oritsmanagement.Allerrorsareours.

?2024InternationalMonetaryFundWP/24/248

IMFWorkingPaper

Strategy,PolicyandReview(SPR)

TheHeterogeneousImpactsofFirmUpgradingonEnergyIntensityPreparedbyPovilasLastauskas,ZiranDingandMustaphaDouch*

AuthorizedfordistributionbyPrithaMitraDecember2024

IMFWorkingPapersdescriberesearchinprogressbytheauthor(s)andarepublishedtoelicit

commentsandtoencouragedebate.TheviewsexpressedinIMFWorkingPapersarethoseofthe

author(s)anddonotnecessarilyrepresenttheviewsoftheIMF,itsExecutiveBoard,orIMFmanagement.

ABSTRACT:Thispaperexamineshowexportactivityimpactsafirm'senergyintensity,emphasizingthe

upgradingprocess.Weintroduceafirm-levelcomplexityindexincorporatingtwodimensions:thecomplexityofthetradedgoodsandmarketdestinations.Weshowthatgrowthinexternaldemandincentivizesfirmsto

undertakeupgradingactivities,resultinginlowerenergyintensity.However,financialconstraintsdiminishtheenergyefficiencygainsfromupgrading,especiallyforsmallfirms.Additionally,upgradedfirmscanleveragehighermarkups,butthisiseffectiveonlyforlargerfirms.Thefindingssuggesttargetedsupportforsmallfirmsandunderscorethenecessityofopentradeinafragmentedgloballandscape.

JELClassificationNumbers:

F14,D22,O33,Q56

Keywords:

FirmUpgrading;InternationalTrade;EnergyIntensity;Complexity;StructuralTransformation;EconomicDevelopment

Authors’E-MailAddresses:

plastauskas2@,zding@lb.lt,Mustapha.Douch@ed.ac.uk

IMFWORKINGPAPERSTheHeterogeneousImpactsofFirmUpgradingonEnergyIntensity

1Introduction

Firms’energyintensityiscentraltothegreentransition,aslowerenergyintensityhelpsre-ducegreenhousegas(GHG)emissions(Marraetal.,2024).Thisrelationshipisinterconnectedwithinternationaltrade,wherebothenergye?iciencyandtradecompetitivenessmayinfluenceoneanother.Thereversalofpastglobalizationtrendsandongoingregulatoryadaptationscallforevidenceabouttheirimpactonthegreengoalsandstructuraltransformationmoregener-ally.Althoughpolicymakersarealreadyimplementingvariousindustrialpoliciestonavigateturbulenteconomicenvironment(Juhászetal.,2023;Ilyinaetal.,2024),theimplicationsforinternationaltradeandenergyusageremaincomplex,ascountriesandfirmsrecalibratesupplychainsandtradepoliciesinresponsetodisruptionslikeCOVID-19andgeopoliticalconflicts(Antràs,2020).Suchchangescouldfundamentallyreshapeenergye?iciencypatterns,e.g.,duetochallengesofbalancingglobalizationwithdomesticeconomicpriorities(Rodrik,2017),asfirmsadapttonewdemandenvironmentandtradebarriers,makingthepolicycontextforexport-relatedenergye?iciencyallthemorecritical.

Infact,theinternationaltradeliteraturehasfoundambiguouseffectsofexportsonfirm-levelenergyintensity.Tradecaninduceexporterstoupgradetheirtechnologyandtherebyreducetheirenergyintensity(Forslidetal.,2018).However,tradecanalsoinduceexporterstoadjusttheirproductmix,makingthemmoreenergyintensive(BarrowsandOllivier,2018).Noristhecausalityeasytosortout.Articlesthatconsidertheeffectsofexportonfirm-levelenergye?iciencyoftenconflatecausaleffectswithselectioneffects(BatrakovaandDavies,2012;Holladay,2016;Forslidetal.,2018;BarrowsandOllivier,2018).

Inthispaper,weprovidecausalevidenceoftrade-inducedupgradinganditsassociatedimpactonfirm-levelenergyintensity.Todoso,weemployauniquedatasetthatcoverstheuniverseoffirmsinLithuaniafrom2000–2015.Wethenaugmentitwiththematchedcustomsdatathatcontainstheimportandexportvolumeoffirms’productbasketandtheirrelevanttradingpartners.ThisperiodincludesLithuania’smajoreconomictransitions,includingEUaccessionin2004,whichacceleratedshiftsinfirmbehaviorregardingtradeandenergyintensitythroughtighterregulatorystandardsandexpandedmarketaccess.

Thisgranularinformationenablesustofurtherleverageexternaldatasetsthatarecrucialformeasuringfirms’upgradingprocessesandtheexternaldemandshockstheyarefacing.Webeginbyconstructingafirm-levelcomplexityindexthatcapturestheessenceoffirms’upgrading

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IMFWORKINGPAPERSTheHeterogeneousImpactsofFirmUpgradingonEnergyIntensity

processaccordingtoVerhoogen(2023).Thisindexcapturesnotonlythecomplexityofthegoodstraded,butalsothecomplexityofthedestinationmarketsserved.Hence,afirmcanupgradebytradingmorecomplexgoods,tradingwithmorecomplexcountries,orboth.Inoursample,bothofthesedimensionscontributetothesteadyupgradingoffirmsinLithuania.

Wethenexaminehowexogenousshockstotradeaffectfirm-levelcomplexity.Toseparatethecausaleffectsofexternaldemandgrowthfromunobservablesthataffecttheenergye?i-ciencyofindividualLithuanianexporters,weconstructfirm-specificexternaldemandshocksbycombiningaggregate(Lithuania-wide)product-specificforeigndemandgrowthwithfirm-specificproductsalesshares,similartoHummelsetal.(2014);Mayeretal.(2021);BarrowsandOllivier(2021).Followingtherecentworkonshift-shareinstruments,ouridentificationisbasedontheexogeneityoftheexternaldemandgrowthshocks,thatis,the”shocksview”asinBorusyaketal.(2022).1WhiletheseshocksareexogenoustoLithuanianfirms,theirimpactvariesmarkedlyacrossfirmspreciselybecausefirmshavedifferentexportbaskets,hencetheheterogeneousexposurestotheexogenousshocks.Inaddition,thegranularityofourproductclassification,aswellastheobservedvariationinexternaldemand,ensurestheconsistencyofshift-shareinstrumentalvariable(SSIV)estimationsinourcontext.

Wefindanincreasedexternaldemandleadstoariseinthegrowthoffirm-levelcomplexity.Thisfindingisrobustacrossdifferentspecificationsandidentificationmethods.Buildingonthisresult,wethenexplorehowtheinstrumentedfirm-levelcomplexitygrowthaffectsfirm’senergyintensity.Theresultspresentaquiteheterogeneouspicture:smallfirmsexperienceasubstantialdecreaseinenergyintensitywithincreasingcomplexity,whereaslargefirms’energye?iciencyimprovementisnotsignificant.TheseresultsalsosuggestthatLithuania’sEUac-cessionmayhavepromptedimprovementsinenergye?iciencybyloweringbarrierstoadoptingcleanertechnologies,enforcingmorestringentenvironmentalstandards,andpromotingcompet-itiveupgradingamongfirms.Thisfindingalignswithpriorstudiesshowinghowtradeexposurecandriveproductivitygains,especiallyforfirmsintegratingintosupplychainsofadvancedinputs,whichcanalsoaffectenergye?iciency(Halpernetal.,2015).

Afterestablishingthesefindingsonupgradingandenergyintensity,weturntoamorepolicy-relevantanalysis.Specifically,weexplorewhethermarketforcesaresu?icienttoincentivize

firmstoimprovetheircomplexityandthusenhanceenergye?iciency.Forlargefirms,wefind

1Asarobustnesscheck,wealsoreportresultsbasedonthetraditionalpanelinstrumentalvariableapproach.Bothapproachesdeliversimilarresults.

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IMFWORKINGPAPERSTheHeterogeneousImpactsofFirmUpgradingonEnergyIntensity

thatfinancialconstraintsgenerallyincreaseenergyintensity,thoughthisnegativeimpactcanbemitigatedbyincreasingcomplexity.Forsmallfirms,financialconstraintsdonotdirectlyimpactenergyintensitybutdohinderimprovementsinenergye?iciencyduringtheupgradingprocess.Employingfirm-levelmarkups,wethenexploreiffirmscanfinancetheirupgradingbychargingahighermarkup.Wefindsmallfirmstemporarilychargealowermarkupafterupgrading,suggestingatoughercompetitionenvironment,whereaslargefirmscancapitalizeontheirresourcesandthriveafterupgrading.

RelatedLiteratureOurpapercontributestoseveralstrandsoftheliterature.ThereisalargeliteratureontheapplicationsofeconomiccomplexityindicesfollowingthepioneeringworkofHidalgoetal.(2009),rangingovervariousfieldsandtopics(Hidalgo,2021).Forinstance,Stojkoskietal.(2023)integratedeconomiccomplexitymetrics,traditionallyderivedfromtradegeography,withdataonpatentapplicationsandresearchpublicationstoimprovepredictionsofinclusivegreengrowth.Theauthorsdocumentrobustimprovementsinexplaininginternationalvariationsininclusivegreengrowth,showcasingthecombinedinfluenceoftrade,technology,andresearchoneconomicgrowth,incomeinequality,andemissionintensities.Wecontributetothisliteraturebyconstructingafirm-levelcomplexityindexthatutilizesboththeproduct-levelcomplexityandthecountry-levelcomplexity,whicharethetwomostimportantaspectsoffirm’supgradingprocess(Verhoogen,2023).

Alargebodyofresearchhasinvestigatedtheclimateimplicationsoftradeonfirm-leveloutcomes.Theevidenceinthisliteratureisquitemixed.Ontheonehand,somepapersfindtradecanreducefirm-levelemissionsthroughtrade-inducedtechnicalchange(Shapiroand

Walker,2018;Forslidetal.,2018;Akermanetal.,2021;MoenchandSoofiSiavash,2023),exceptLevinson(2009),whichfindsthattechnologicaldevelopmentisthemaindriverofemissionreduction,withtradeonlyplayingaminimalrole.Ontheotherhand,therearealsopapersthatsuggestthattradecanincreasefirm-levelemissionsduetofirms’adjustmentoftheirproductbundle(BarrowsandOllivier,2021;Iqbaletal.,2021).Wecontributetothisliteraturebycausallyidentifyingachannelwheretradeinducesfirmstoupgradeandreducesfirm-levelenergyintensity.

Asaconsequence,ourstudyalsoshedslightontheliteraturethatexploreshowtradepoli-ciesandregulationsimpactclimate.Forexample,Lietal.(2023)usesthe2018US-ChinatradewarasanaturalexperimentandfindsthatgreaterexposuretoTrumptariffsleadstolowerregulationtargetsinChina,inducinganincreaseinairpollutionandcarbonemissions.Brunel

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IMFWORKINGPAPERSTheHeterogeneousImpactsofFirmUpgradingonEnergyIntensity

andLevinson(2021)investigatewhethertherelativelylaxemissionregulationsintheUShaveturnedthecountryintoapollutionhaven.Theyfoundincreasedemissionsembodiedintradeonlythroughthescaleeffect,butnopollutionhavenwascreated.ShapiroandWalker(2018)foundthatmorestringentenvironmentalregulationsencouragedtheadoptionofenvironmen-taltechnology,whichwasresponsibleforthemajorityofreducedemissionsthroughloweredemissionintensity.Wecontributebyfocusingonthefirm-levelclimateimplicationsregardingLithuania’sEUaccession.

Ourpaperisalsorelatedtostudiesthatexploretheimplicationsofstructuraltransforma-tionforparticipationinglobalvaluechains(GVC).QuiteafewearlierstudiesfocusonthetechnologicalupgradingeffectsviaGVCparticipationandtheirimplicationsforenergye?i-ciencyandintensityhavebeenquitemixed(Wangetal.,2022;DeMeloandSolleder,2023).Morerecently,Atkinetal.(2024)findthattheemergenceofChinaintheGVCerahasheldbackcapabilitygrowthforanumberofAfricancountrieswhoarepushedawayfromtheirmostcomplexsectors,whichChinaexports,andintotheirleastcomplexsectors,whichChinaim-ports.Ourpaperoffersajointtreatmentoffirm-levelupgradingthroughparticipationinGVCanditsimplicationsforclimate.Whilemostofthesestudiesfocusondevelopingcountriesandcross-countrycomparisonswithasectoralview,ourpaperprovidesamoregranularanalysisofaCentralandEasternEuropean(CEE)countrythatunderwentmassivetransformationsinceitsEUaccession.

Therestofthepaperisorganizedasfollows.Section2providesadetaileddescriptionofourdataandhowweutilizethemtocreateourpreferredmeasures.Italsodocumentsasummaryofourrawdataandourconstructedmeasures.Section3discussesourempiricalstrategyforour

causalanalysis.Section4presentsourbenchmarkempiricalresults,whileSection5providesextensionsandadditionalchannelsinreferencetoourbenchmarkanalysis.Section6offersadiscussionandpolicyimplicationsinlightofourfindings.Section7concludes.

2DataandMeasurements

2.1DataSources

Therearethreeprimarydatasetsforourexercise:(i)theannualfirm-levelsurveycarriedoutbyValstyb?sDuomen?Agentūra,whichistheo?icialstatisticsdepartmentofLithuania,(ii)product-leveldatafromLithuaniancustomsLietuvosRespublikosMuitin?,and(iii)theglobal

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IMFWORKINGPAPERSTheHeterogeneousImpactsofFirmUpgradingonEnergyIntensity

product-leveltradedatafromCEPII’sBACIdatabase.

AnnualSurveyofEnterprises

OurmaindatasourcecomesfromtheannualsurveyofalltheLithuanianfirmscarriedoutbyStatisticsLithuaniafrom1995-2019.Duringthistime,theLithuanianeconomyexhibitedanaverageGDPgrowthrateofover4.5%,whichismuchhigherthantheEuroareaaverageandtheUSeconomy.TheEUmembershipnotonlyenabledaccesstonewtradingpartnersbutalsoinducedthecountrytogothroughasubstantialstructuraltransformation,witharapiddeclineintheagriculturesectorandasharpincreaseintheservice,wholesale,andretailsectors(Garcia-LouzaoandTarasonis,2023).

Thesurveyismandatoryforalltypesoffirms2inLithuania,exceptforsoleproprietorsorassociationsandpublicadministrativeentities.Thedatasetcontainsdetailedfirm-levelinforma-tioncombiningbothbalancesheetsandincomestatements,includinginformationaboutfirms’birthandliquidationdates,employment,sectorialactivity,ownershipstructure,assets,liabili-ties,equities,value-added,revenuesandprofits,etc.Unfortunately,therearetwoshortcomingsofthisdata:(i)from1995-1999,thereportingcriteriawerenotcompatiblewithinternationalaccountingstandards,(ii)from2016-2019,asignificantportionoftheabovevariablesaremiss-ing.3Therefore,weprovidesummarystatisticsandourmainanalysisbasedontheperiodfrom2000to2015.

Weimposethefollowingrestrictionsontheoriginaldatasettoobtainoursampleofanalysis.Firstly,weexcludeenterpriseswithnocontinuousentries.Secondly,firmsinfinancialandinsuranceactivitiesareexcluded,aswellasthosefromagriculture,healthcare,andeducationsincethesefirmsareeitherpoorlyrepresentedinthedataormostlysoleproprietorfirmsandpublicentities.Thirdly,wewinsorizefirmsthathaverevenuebeloworabovethe2ndand98thpercentileinoursampleperiod.Thiswinsorizationproduceafinalsampleof96,299firmsobservedover569,540firm-yearobservationsfrom2000-2015.

LithuaniaCustomsData

Wethenmergethesamplewithcustomsdata,whichincludesfirmidentifier,productcode(HS8

digits,except2010,whichisHS6digits),importsource,exportdestination,andtheirrespec-

2Foramoredetaileddescriptionofthedata,seeConstantinescuandPro?kut?(2019).

3Inaddition,areformimplementedin2019alteredthestructureoflaborcostsbyshiftingtheresponsibilityofsocialsecuritycontributionsfromcompaniestoemployees,theeffectsofwhicharenotrepresentedinourdata.

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tivevolume4.Thevaluesareinlitasbefore2012,soweconvertittoeuroswiththeconversionratio3.4528litasto1euro.Tokeeptheproductcodeconsistentthroughtheperiodofanaly-sis,weaggregatetheHS8digittoHS6digit,whilemaintainingthesamefirm-product(HS6)-source/destinationpairs.Thisallowustomaintainaconsistentdatabasewithfirm-year-HS6-destination/origininformationthroughtheentireperiodofanalysis.

BACIdata

TocomputeexternaldemandforLithuanianfirms,wetakeinternationaltradeflowdatafromCEPII’sBACIdatabase,whichcontainsvaluesofbilateraltradeflowsintheHS6-digitproductclassification.Tomaketheproductcodescomparableacrosstime,weconvertalltheHS6codestothe1992version.

2.2AFirm-levelComplexityIndex

Duringtheperiodofouranalysis,Lithuaniaismostlyintransitiontoamarket-basedeconomy.5FollowingtheinsightfromVerhoogen(2023),firms’upgradingprocessnotonlybenefitsfromtheirinteractionswithbuyersorsuppliersbutalsodependsonthecountrytheyaretradingwith.6Factorssuchasdemandpatterns,availability(andprices)ofinputs,andknow-howoftheentrepreneursthemselvesveryoftendifferbycountry.Therefore,toaccountfortheroles

ofthesetwodimensions,weutilizeboththeproduct-levelandcountry-leveldataofcomplexityfromtheAtlasofEconomicComplexitydevelopedbytheHarvardGrowthLab.7

AccordingtotheAtlaswebpage,theproductcomplexityindexcapturestheamountandsophisticationofknow-howrequiredtoproduceaproduct,8whileacountry’scomplexityindex

isbasedonhowdiversifiedandcomplexthecountry’sexportbasketis.Inthecontextofour

4Thecustomsdataisavailablefrom1995-2019,buttokeepitconsistentwithourmainanalysis,wefocusontheperiod2000-2015.

5AccordingtotheIMF,Lithuaniabecameanadvancedeconomyin2015butcompleteditstransitiontoamarket-basedeconomyin2019.

6Formoreevidenceonspilloversbetweenfirms,seeBloometal.(2013)andLuckingetal.(2019).Formoreevidenceonspilloversbetweencountries,seePeri(2005)andEugsteretal.(2022).

7Foramoredetaileddescriptionofthesetwoindices,pleaserefertoAppendixB.

8AccordingtotheAtlaswebsite,”Themostcomplexproducts(thatonlyafew,highlycomplexcountriescanproduce)includesophisticatedmachinery,electronicsandchemicals,ascomparedtotheleastcomplexproducts(thatnearlyallcountriesincludingtheleastcomplexcanproduce)includingrawmaterialsandsimpleagricultural

products.”

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analysis,westartwiththefirmcomplexityindexforeachimportandexportmarketasfollows:

wheres,t(IM)standsfortheexport(import)shareofproductjwithinfirmi’stotalexport

(import)to(from)countrycinagivenyeart.Therefore,eachindexcapturestheaveragecomplexityscoreforallexportedandimportedvarietiesj,differentiatedbydestinationandsourcecountries,respectively.Thehigherthescore,themorecomplexityisassociatedwiththeexportandimportbaskets.However,thisindexignorescross-countryheterogeneityincomplexity.Thatis,certainproductiveknow-how,includingsophisticated,uniqueknow-how,isquitecountry-specific,hencethesamevarietycanbeproducedquitedifferentlyindifferentcountries.

Therefore,toaccountforthoseparticularspecializedknow-howsfromimportandexportpartners,weaugmentthepreviousindexinthefollowingway:

UFCI(3)

wherewc,t=denotestherelativecomplexityofthecountryccomparedtothe

averagecountry-levelcomplexityattimet.Clearly,acountrythatsourcesorexportstoanaveragecountryjustgetsanexactsameupdatedindexastheoriginalone,whereasthecountrywhosetradepartnersaremorecomplexthantheaverage”improves”thescore(i.e.,itlowersit)andotherwiseiftradehappenswithlesscomplextradepartners.

Finally,itisclearthatthetwoindicescouldhavebeencombinedintoasingleindexsincethecountry-levelcomplexityindexweightonlyvariesbycountryandtime:

UFCItComplexityj,t=Complexityj,t,

UFCIComplexityj,t=Complexityj,t.

Wetaketheabsolutevalueoftheminimumofthecomplexityindex,minComplexityj,t,and

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addituptothewholeseriesofthecomplexityindex.Thenewminimummeasureiszero.

2.3AFirstLookattheData

ThesummarystatisticsinTable1offersvaluableinsightsintothecharacteristicsandperfor-mancemetricsoffirmsobservedbetween2000and2015.Thesestatisticsprovidethefirstglimpseofthedynamicswithinthebusinesslandscape,andshedlightonvariousaspectsoffirmbehaviour,economicperformance,andmarketconditions.Forinstance,themeanrevenueof€1,170,496reflectstheaveragesalesoffirmsduringtheobservedperiod.However,thewidestandarddeviationindicatessignificantvariabilityinrevenueacrossfirms,suggestingdiversebusinessmodelsandmarketpositionsaswellasfirmsize.Similarly,whiletheaverageemploy-mentofaround19employeesperfirmprovidesanindicationofworkforcesize,theconsiderablestandarddeviationof132.42highlightstheheterogeneityinlabourdemandandfirmsizewithinthedataset.

Furthermore,amongexporters,themeanexportvalueis€1.3million.Thestandarddevia-tionof8.5millionhighlightsthesubstantialvariationinexportperformance,reflectingdiffer-encesinmarketaccess,productcompetitiveness,andglobaleconomicconditions.Additionally,theaverageexportofapproximately10productsperfirmsuggestsadegreeofdiversificationinexportportfolios,withfirmsengaginginmultipleproductcategoriestoaccessinternationalmarkets.

Theaverageexpenditureonenergy(€47thousand)andcostofsales(€930thousand)pro-videinsightsintofirms’operatingexpensesandcoststructures.Thewidestandarddeviationsindicateconsiderabledispersioninexpenditurepatternsandcostdrivers,whichmayreflectdifferencesinproductionprocesses,energye?iciencymeasures,andinputpricesbetweenfirms.Similarly,themeantotaldebtof€477,290indicatestheaverageleveloffinancialleverageamongfirms.Variabilityindebtlevels,asindicatedbythestandarddeviation,suggestsdifferencesinfinancingstrategies,riskprofiles,andcapitalstructuredecisionsbetweenfirms.

Ontheotherhand,intermsoftotalfactorproductivity(TFP)andmarkupprovideinsightsintofirms’e?iciencylevelsandpricingbehaviour.ThemeanTFPof2.55suggestsanaveragelevelofproductivitybetweenfirms,whiletheaveragemarkupof1.11indicatesfirms’pricingpowerandmarketcompetitiveness.Thedistributionalpropertiesofthesevariables,includingskewnessandvariability,offerfurtherinsightintotheunderlyingdriversoffirmperformanceandmarketdynamics.

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Finally,intermsoffirmcomplexity,theindicesmeasuredbyUFCIand△UFCI(inlevelsandgrowth)highlightfirms’exportcomplexityascrucialdeterminantsofinternationaltradedeci-sionsandmarketoutcomes.Themeanvaluesofthesevariablesprovideindicationsofthelevelsandvariabilityofexport-relatedcomplexitywithinthedataset,highlightingtheimportanceofstrategicdecision-makinginglobaltradeoperations.

Table1.Summarystatistics

Mean

Median

Std.Dev.

Small(mean)

Large(mean)

Revenue

1170496.03

103921.50

11243539.42

470017.12

11115233.09

Employment

19.1125

5

132.42

8.08962

175.606

Export

1302561.63

66948

8568029.59

474027.42

5002895.98

Exporterproducts

10.28

3

25.53

1

24

ExpenditureonEnergy

47177.41

1660

1205280.38

14943.58

504778.47

CostofSales

929668.44

55812

9563562

367302.19

8913612.00

TotalDebt

477288.7

39881.5

4528501

223423

4081241

log(TFP)

2.55

2.58

0.71

2.60

2.20

Markup

1.11

1.07

0.18

1.11

1.12

UFCIEX

57.79

16.71

113.30

43.65

116.89

△UFCIEX

0.03

0.01

0.71

0.02

0.05

Note:Descriptivestatisticsarecomputedoverthe569,540firm-yearobservationscorrespondingto96,299firmsob-servedbetween2000and2015.Revenuecorrespondstototalsalesrevenue.Employmentistheaveragenumberofemployeeswithinayear.Totaldebtisthesumofcurrentliabilitiesandlong-termdebt.Exportreferstothetotalexportvalueatthefirmlevel.Expenditureenergyisthesumofexpenditureonfuel,electricit