英文【IMF】企業(yè)升級(jí)對(duì)能源強(qiáng)度的異質(zhì)性影響（英）2024

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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IMFWORKINGPAPERSTheHeterogeneousImpactsofFirmUpgradingonEnergyIntensity

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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IMFWORKINGPAPERSTheHeterogeneousImpactsofFirmUpgradingonEnergyIntensity

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