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PolicyResearchWorkingPaper10792

BridgingtheGapinTradeReportingInsightsfromtheDiscrepancyIndex

SonjaMitikj

SiddheshVishwanathKaushik

WORLDBANKGROUP

DevelopmentEconomicsDevelopmentDataGroupJune2024

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PolicyResearchWorkingPaper10792

Abstract

Accuratetradedataremaincentralforempiricalinvesti-gationsofinternationaltradeandinformedformulationoftradepolicies.However,discrepanciesintradereport-ing,stemmingfromreasonssuchaslogisticstodeliberatemisclassification,posechallengestoobtaininganaccuraterepresentationoftradeactivities.ThispaperprovidesasystematicexaminationofthesediscrepanciesbyusingtheDiscrepancyIndex,ameasureofbilateralasymmetryintradereporting.First,thepaperproposesarichsetofcountry-andproduct-levelindicatorsthatcaptureboththefrequencyofmisreportinganditsimpactontheoverallrecordedtradevalue.Second,itdemonstrateshowtheDis-crepancyIndexdatabasecanaidanalysisandresolvedatareliabilityissuesininternationaltrade.Thiscomprehensive

datasetisusedtoanalyzethegeneraltrendsintradedatareportinganditsreliability,providingempiricalinsightsintothenatureandextentofreportingdiscrepancies.Finally,thepaperdemonstratesthepracticalapplicationofthedevel-opeddiscrepancydatabaseandaggregateindicatorsthroughcasestudiesofSenegalandthetraderelationshipbetweenMadagascarandFrance,sheddinglightonreporter-spe-cificinstances.Thepaperseekstoequiptradeanalystsandresearcherswithtoolsandresourcestomakeinformeddeci-sionsontheuseofreportedtradedataandtheirmirror.Indoingso,thestudycontributestothebroaderendeavorofenhancingthereliabilityofinternationaltradedata,therebycontributingtoamoreaccurateempiricalinvestigationofglobaltradepatternsandtheirpolicyramifications.

ThispaperisaproductoftheDevelopmentDataGroup,DevelopmentEconomics.ItispartofalargereffortbytheWorldBanktoprovideopenaccesstoitsresearchandmakeacontributiontodevelopmentpolicydiscussionsaroundtheworld.PolicyResearchWorkingPapersarealsopostedontheWebat

/prwp

.Theauthorsmaybecontactedatskaushik@andsmitikj@.Averifiedreproducibilitypackageforthispaperisavailableat

,click

here

fordirectaccess.

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ThePolicyResearchWorkingPaperSeriesdisseminatesthefindingsofworkinprogresstoencouragetheexchangeofideasaboutdevelopmentissues.Anobjectiveoftheseriesistogetthefindingsoutquickly,evenifthepresentationsarelessthanfullypolished.Thepaperscarrythenamesoftheauthorsandshouldbecitedaccordingly.Thefindings,interpretations,andconclusionsexpressedinthispaperareentirelythoseoftheauthors.TheydonotnecessarilyrepresenttheviewsoftheInternationalBankforReconstructionandDevelopment/WorldBankanditsaffiliatedorganizations,orthoseoftheExecutiveDirectorsoftheWorldBankorthegovernmentstheyrepresent.

ProducedbytheResearchSupportTeam

BridgingtheGapinTradeReporting:InsightsfromtheDiscrepancyIndex

SonjaMitikj

SiddheshVishwanathKaushik

JELclassification:F14,C55,C82

Keywords:InternationalTradedata,DiscrepancyIndex,DataQuality,MirrorStatistics.

Acknowledgment:WearegratefultoAnaMargaridaFernandes,BobRijkers,HiauLooKi,

MarkieMuryawan,andMichaelFerrantinofortheirinsightfulcommentsandfeedbackthat

significantlyimprovedthiswork.WealsoextendourappreciationtoUmarSerajuddinandDariaTaglionifortheirleadershipandsupportthroughouttheproject.

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Contents

1.Introduction 3

2.Sourcesofdiscrepanciesininternationaltradereporting 5

3.Methodsformeasuringdiscrepanciesintradereporting 7

3.1TheDiscrepancyIndex 9

3.2Aggregateindicatorsbasedonthediscrepancyindex 14

4.Datadescription 20

5.Resultsanddiscussion 21

5.1Stylizedfactsaboutinternationalmerchandisetradereporting 21

5.2Estimatingthereliabilityofreporters 29

5.3.ThecaseofSenegal 38

6.Conclusion 40

Appendix 42

A1)ListofadditionalvariablesderivedfromtheDiscrepancyIndex 42

A2)ImportreportinginallHSnomenclatures(1988-2019) 43

A3)ExportreportinginallHSnomenclatures(1988-2019) 46

A4)Detailedlookatorphanimportsandlostexports 49

A5)Trackingre-exportsandtheirimpactondiscrepancies 53

A6)Resolvingdiscrepancies 54

A7)Supportingmaterialsforthefindings 61

A8)Databasetabledetails 68

A9)CountryCodesandNames 71

References 75

DISCLAIMER

ThematerialsinthereproducibilitypackagesaredistributedastheywerepreparedbythestaffoftheInternational

BankforReconstructionandDevelopment/theWorldBank.Thefindings,interpretations,andconclusionsexpressedinthisstudydonotnecessarilyreflecttheviewsoftheWorldBank,theExecutiveDirectorsoftheWorldBank,orthegovernmentstheyrepresent.TheWorldBankdoesnotguaranteetheaccuracyofthematerialsincludedinthe

reproducibilitypackage.

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1.Introduction

Cross-bordertradeplaysapivotalroleinacademicresearchoninternationaldevelopmentandthecomplexitiesofpolicydesign.Thisimportancestemsfromitsabilitytoprovideinsightintoeconomicinteractions,dependencies,andthedynamicsofglobalmarkets.Theestimationofsuchcross-borderactivitiesprimarilyhingesontradedata,whichprovidesaquantitative

assessmentofgoodsexchangedbetweencountries.Accuratedatainformsimporttariffsetting,guidesnegotiationsfortradeagreements,andsteersmonetarydecisionsthatimpactinterest

ratesandcurrencyvaluation.Furthermore,itinfluencesindustrialsubsidies,infrastructure

investments,environmentalregulations,andevennationalsecurityconsiderations.Givenits

importance,theincreasingnumberofstudieshighlightingdiscrepanciesinreportedtradeflowsisconcerning(Gaulie&Zignago,2010;Carrère&Grigoriou,2015;Fortanier,2016;Shaar,

2019;Chenetal.,2022).Reportingdiscrepanciesareoftenoverlookedinthedesignof

empiricalstudiesofinternationaltrade,compromisingthevalidityorrobustnessoftheobtainedresults(Linsi&Mügge,2019;Linsi,Burgoon,&Mügge,2023).Thisisespeciallyimportant

becausestatisticalresultsguidingpolicyinterventionshavebeenshowntobesensitiveto

changesintheunderlyingdata(Bahmani-Oskooee,Hegerty&Harvey,2013;Farhadetal.,

2023).Consequently,anyinaccuracyorinconsistencyintradedatacandistortorcompromisethevalidityofresearchoutcomesandtheformulationofpolicyrecommendations.

Evaluatingthereliabilityandaccuracyoftradedatatypicallyreliesontheprincipleofdualrecordingofbilateraltransactions.Ideally,tradetransactionsbetweencountriesshouldberecordedbyboththereportingcountryanditstradingpartner,resultingindualrecords.

However,empiricaltradedataoftenlacksthisdualrecording,withmanytransactionshavingnocorrespondingmirror(Carrère&Grigoriou,2015;Shaar,2019;Chenetal.,2022).Furthermore,

mirrorrecordsoftenreportconflictinginformationregardingthevalueorquantityofthe

transaction,resultinginareportingdiscrepancy.Theabsenceofmirrorrecordsandthe

prevalenceofreportingdiscrepanciescomplicatestheevaluationofdatareliability.Thishas

propellednumerousstudiestoexplorethepotentialdriversofdiscrepancies(Ferrantino&Wang

2008;Carrère&Grigoriou,2015;Demir&Javorcik,2020;Kee&Nicita,2022),construct

measuresforreportingreliability(Shaar,2019,Farhadetal.,2023),anddevelopreconciliationproceduresforestimatingtradeflows(Gehlhar,1996;Gaulie&Zignago,2010,Fortanier,2016).Yet,resolvingthesetradedataqualitychallengesremainsdifficultduetothemultitudeoffactorscontributingtotheobserveddiscrepancies.

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Inthisstudy,webridgethegapbyproposingacomprehensivecountry-andproduct-level

DiscrepancyIndexdatabasethatcapturesboththefrequencyofmisreportinganditsimpactonoverallrecordedtradevalue.ThedatabasewascreatedbyleveragingtheUNComtrade

database,capturingallavailableHarmonizedSystem(HS)datafrom1988to2022.Centralto

thisapproachisuseofabilateralDiscrepancyIndex(DI),whichcalculatesthelevelof

divergencebetweenreporteddataanditscorrespondingmirror(datareportedbytradingpartner).

ThisstudymakesseveralcontributionstowardsmeasuringdiscrepanciesandassessingreporterreliabilityintheUNSDComtradedatabase.First,weprovideacomprehensive

coverageofdiscrepancymeasurementsacrossallperiodsofobservation,reportingcountries,products,andproductdetailfortheHSnomenclature.Hence,resourcesprovidedherecan

assistresearchersaimingtotracediscrepanciestospecificcauses,whetherlogisticor

otherwise.Second,weshowthatthefunctionalformofDIpresentedhereavoidssomeofthe

pitfallsofcommonlyusedtradeasymmetrymeasuresandisthereforemoresuitedfor

penalizingdiscrepanciesthatareleastlikelytobeexplainedbysomelogisticfactor.Third,wedemonstratehowtheinternationalmerchandisetradereportingdiscrepancydatabasecanaiddiscrepancyanalysisandresolvedatareliabilityissuesintheUNComtradedatabase.By

measuringdiscrepancyinreportedvaluesacrosstime,reportingnomenclatures,trading

partnersandproducts,weidentifyanencouragingtrendofanincreasingqualityofreportedtradeovertime.Weidentifypersistentseriousqualityproblemslinkedtosomereportersandnotepotentialeffectsofreportingdiscrepanciesonimportanttradeindicatorssuchastradebalances.Thus,thisstudyalsocontributestoongoingdiscourseregardingqualityofdataininternationalmerchandisetradebyprovidingmeasuresandtoolsforitsassessmentand

outliningimportantconsiderationsinpracticalapplicationsoftradedata.Moreimportantly,ourresultscanequiptradeanalystswiththenecessarytoolstomakeinformeddecisionsregardingtheuseofacountry’sreporteddataoritsmirror.

Therestofthispaperisorganizedintofivesections.Section2discussesthenumerousfactorscontributingtodiscrepanciesininternationalmerchandisetradereporting.Section3discussesmethodsformeasuringreportingdiscrepanciesininternationalmerchandisetradeandprovidesdetailsonmainandaggregateindicators.Section4describesthedatausedinthisanalysisandprovidesdetailsonaccessingthediscrepancyanalysistoolsdevelopedinthisstudy.Section5outlinesthestudy’skeyfindingsandresultsalongwithexamplesandcountrycasestudies.

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Finally,section6offersconcludingremarks,suggestsdirectionsforfutureresearch,andacknowledgesthelimitationsofourapproach.

2.Sourcesofdiscrepanciesininternationaltradereporting

Agrowingbodyofliteraturehasstudiedtherelativecontributionsofseveralfactorstothe

observeddiscrepanciesininternationalmerchandisetradereporting(Ferrantino&ZhiWang2008;Carrère&Grigoriou,2015;Demir&Javorcik,2020;Kee&Nicita,2022).Thesestudieshaveidentifiedbothstructuralandnon-logisticreasonsforthelackofdualrecordingand

observedinconsistenciesinsuccessfullymirroredrecords.Inthissection,weoutlinethecausesofdiscrepanciesandexploretheireffectonthequalityoftheobtaineddata.

Discrepanciesininternationaltradereportingarestructural,i.e.,theyaredrivenbylogistic

reasonsrelatedtothevaluationmethodsandreportingguidelinesforinternationalmerchandisetrade.TheseguidelinesaredetailedintheInternationalMerchandiseTradeStatistics:ConceptsandDefinitions2010(IMTS2010),publishedbytheUnitedNationsStatisticalDivision(UNSD).TheUNComtradedatabases,theprimarysourceofofficialmerchandisetradedatacollected

anddisseminatedbyUNSD

/,

strivetoalignwiththeIMTS2010guidelinesintheempiricaldatathattheyprovide.Asaresult,dataobtainedthroughUN

Comtrade(oranysourcethatadherestotheserecommendations)inherentlypossessseveralstructuraldiscrepancies.Anexampleofthisstructuraldiscrepancyoccursinvaluationmethodsthattypicallyconsiderfreightandinsurancecostsforimportsbutnotforexports.Therefore,

structuraldiscrepanciesarisebecausethereportedimportvalueexceedsthatofthe

correspondingmirror.Manyhavenotedthatextreme(andevennegative)empiricalmeasurementsofdifferencebetweenreportedimportsandmirrorrecordssuggest

discrepanciesthatcannotentirelybeexplainedbydifferencesinvaluationmethods(Carrère&Grigoriou,2015).

Moreover,IMTS2010recommendslistingthecountryoforiginforimports,butthelastknown

destinationforexports(UnitedNations,InternationalMerchandiseTradeStatistics).Thiswill

structurallycreatetransactionswithoutacorrespondingmirrorincaseswhereexportspass

throughintermediatecountriesbeforereachingtheirfinaldestination.Insuchcases,reported

exportsfromtheintermediatecountrieswillnothaveamirrorasthepartnerthattheylistintheirexporttransactionliststheoriginalsourcecountry(andnottheintermediatecountry)intheir

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correspondingimportrecord.Conversely,thereportedimportsofboththeintermediate

countries(excludingthefirstone)andthedestinationwillalsolackacorrespondingmirror.

CarrèreandGrigoriou(2015)estimatedthatasmuchas23%ofrecordedtradeflowsonthe

aggregateleveldonothaveacorrespondingmirror.However,therelativeeffectofre-export

reportingonpartnermisattributioninmirrordataremainsdifficulttoassess.Althoughtherisingroleofre-exportinginmerchandisetradeanditseffectonreporteddiscrepancieshasbeen

documentedforthelargestre-exportinghubs-HongKongSAR,China;Singapore;andthe

Netherlands(Ferrantino&ZhiWang,2008;Fortanier,2016;Jonesetal.,2020),thereisno

comprehensivemethodologythatconsidersre-exportingonaglobalscale.Thechallengeof

trackingre-exportsandgoodsundergoingprocessingisfurthercomplicatedbythenon-uniformapplicationofre-exportreportingguidelinesacrosscountries,with118reportershavingneverreportedre-exportstotheUNComtradesystem(Jonesetal.,2020).

Therefore,structuralconstraints,suchasdifferencesinvaluationmethods,resultinmany

inconsistenciesinreportedtrade.However,itsimultaneouslysuggeststhatthemagnitudesofmanyobserveddiscrepanciescannotbeattributedtologisticconstraintsalone.Therefore,agrowingnumberofstudieshaveturnedtocountryandbilateralcharacteristicstoexplaintherecordedgapinreporting.

Besideslogisticreasons,discrepanciesininternationaltradereportingcanalsobenon-logistic,i.e.,theyareoftenadeliberatemisevaluationormisclassificationforevadingimporttariffs

(Cantens,2015andDemirandJavorcik,2020)andexporttaxes(Chalendardetal.,2020),

minimizingcorporateprofitand/orturnovertax,andothernon-tariffmeasures(KeeandNicita,

2022).Themisclassificationandmisinvoicingofproductshavebeenshowntobesubstantial

(Carrère&Grigoriou,2015),with77%ofallbilateraltradeflowsreportedbybothpartnersattheaggregatelevelandonly47%ofbilateraltradeflowsreportedbybothpartnersatthesix-digit

level.Largerdiscrepanciesindisaggregatedproductshavelongbeenobserved(Rozanski&

Yeats,1994)andareoftenattributedtohumanerror(misclassification)ordeliberatemisreporting.

Animportantquestionthenishowtoinferwhethertheobserveddiscrepancyis“expected,”i.e.,impliedbystructuralreasons,asopposedtodeliberate,i.e.,causedbyfactorsthatarenot

purelylogisticinnature.Ifsomediscrepanciesarestructurallyexpected,adependablereporterisnotonewithoutanydiscrepancies,butonethatexhibitsdiscrepanciesthataremostlikelyto

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beexplainedbylogisticconstraints.Thisnecessitatesthedevelopmentofmeasuresofdatareliabilitythatprioritizeidentifyingdiscrepanciesthatgobeyondstructuralfactors.

Numerousstudieshaveattemptedtomeasureandreconcilethediscrepanciesobservedin

UNSD’sComtradedatabase.Often,theyrelyonmeasuresofbilateralasymmetrytocapture

discrepancybetweenrecordedvalueanditsmirror(Ferrantino&Wang2008;Chenetal.,2022;Farhadetal.,2023).However,somesuggestedmeasuresareoftenlineartotheobserved

discrepancy(Carrère&Grigoriou,2015),i.e.,theychangelinearlyinrelationtotheunaccountedtradevalueirrespectiveofwhethertheunaccountedtradevalueisduetotheadditionof

insuranceandfreightcostsforimportsoranunderreportingofimportsintheequivalentamount.

Thisisinconvenientbecausethefirsttypeofdiscrepancyisexpectedandstructurally

guaranteedbyIMTS2010guidelines,whilethelatterindicatesmissingimports,whichisnot

easilyexplainedbylogisticfactorsalone.Inaddition,somemeasuresareconstructedusing

absolutedifferencesinrecordedvalues(Chenetal.,2022),resultinginindicatorsthatcannotexplicitlyaccountforthedirectionofmisreporting,i.e.,whetheranimportwasover-orunder-reported.Thisissimilarlyinconvenientbecauseimportoverreportingismeasuredasequally

severeasimportunderreporting.Whileindicesofbilateralasymmetrythatarenon-linearto

unaccountedtradevalueandcanaccountforthedirectionofdiscrepancyhavebeenproposed

(Ferrantino&Wang2008),theirapplicationintheliteratureisusuallylimitedtospecificcountries.

3.Methodsformeasuringdiscrepanciesintradereporting

Thequalityofreportedtradeisusuallyinvestigatedinrelationtoitsmirror,i.e.,thedatareported

bythetradingpartner.Acomparisonbetweentherecordedvalueanditsmirrorisusually

achievedthroughameasureofbilateralasymmetrythatquantifiesthemagnitude(anddirection)oftheobserveddiscrepancy.ManysuchmeasureshavebeenproposedtoassessthequalityoftheUNComtradedatabase(Carrère&Grigoriou,2015,Chenetal.,2022;Farhadetal.,2023).

Thesemeasureshaveprovenespeciallyusefulinunderstandinggeneralpatternsintrade

reporting,pinpointinguncertainandproblematicdata,andrelatingcountry-specificandbilateralcharacteristicstomisreporting.However,specialattentionmustbepaidtobothstructuralandnon-structuralcausesofdiscrepanciesinthemeasure’sconstructionandinterpretation.

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Thefirstmajorpointofconsiderationinthebilateralasymmetrymeasureisthatitinvolvesa

comparisonbetweentradevaluesrecordedunderdifferentvaluationmethods.Thatis,bilateralasymmetrymeasurescomparetheFreeonBoard(FOB)valuationofexportsandtheCost

InsuranceandFreight(CIF)valuationoftheequivalentimportvalue.Whileitispreferableto

simplytaketheFOBvaluationforimport,theyarerarelyavailable.Thisimpliesthatbilateral

asymmetrymeasureswillindicateimportoverreportingincaseswhereimportrecordssimply

includeCIFadjustments.Severalapproachestoaccountfordifferencesinthevaluationof

recordedvalueshavebeenproposed.IntheBACIdatabase(Gaulie&Zignago,2010),theCIFrateisestimated(andremoved)viaagravity-typemodelbeforediscrepanciesarefurther

resolved.

Alternatively,theinfluenceoftheCIFratecanbefactoredinbyaccountingforproduct

composition(Farhadetal.,2023),whichwillinevitablycontainthemagnitudeofthisratio.

Finally,theinclusionoftheCIFrateintheinterpretationofbilateralasymmetrymeasureshasbeenimplementedusingsimplethresholding,withmanyflaggingtransactionswhoseCIFrateexceedsthe10%threshold.

However,thevariabilityoftheCIFrateacrosspartnersandproductssuggeststhatthis

thresholdisauseful,yetroughestimate.Thisfacilitatestheneedforbilateralasymmetry

measuresthataremorepenalizingtowarddiscrepanciesthatareleastlikelytobeexplainedbylogisticfactors,suchasdifferencesinvaluation.Inaddition,manyproposedbilateralasymmetrymeasurescanindicatethemagnitudeofthediscrepancy,butnotitsdirection.Inotherwords,

withoutadditionalinformation,thesemeasuresalonecannotindicatewhetherthediscrepancywasduetoanoverorunderreportedimportvalue.Consideringthedifferencesinvaluation

outlinedearlier,thedirectionofthediscrepancycanhelpisolatediscrepanciesthatgobeyondCIFadjustments.

Measuresofbilateralasymmetry,however,canonlyquantifythelevelofdivergenceofreportedtradevaluesonasinglebilateraltransaction.Tocapturereporters’reliability,thereisaclear

needtosummarizethedistributionofbilateralasymmetriesacrosspartnersandcommodities.

Therefore,measuresofbilateralasymmetryareusuallyaccompaniedbyanaggregation

functionthatcapturesimportantdistributionalpropertiesoftheobserveddiscrepanciesacrosstradeactivitiesandpartners.

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Aggregateindicatorshavebeendrivennotonlybytheneedtoassessdataqualitybutalsobytheirsignificantroleinreconciliationproceduresoftradedata.Reconciliationprocedures

(Gehlhar,1996;Gaulie&Zignago,2010,Fortanier,2016)attempttoprovideareconciledvalueforabilateraltransaction,usuallyasaweightedmeanofdifferingaccounts.Here,theweightsreflectameasureofreliabilityfromareporterineachtransaction.Inconstructingaggregate-

levelindicators,weightedindicatorsareusuallypreferredbecausemajordiscrepanciesoftenarisefromtradeswithsmallervalues.Adjustingmeasuresofreliabilityforpartnerandproductcompositionisalsopreferred,asoftenfaringpoorlyonmeasuresofbilateralasymmetrycouldbeattributedtotradingwithpoorreporters.

3.1TheDiscrepancyIndex

Here,weintroducetheDiscrepancyIndex(DI)andinvestigatethemaindifferencesbetweentheDIandothercommonlyusedmeasures,demonstratingthattheDIisbothnonlineartoobserved

discrepancyandabletocapturethedirectionofmisreporting.Lastly,weintroducethe

aggregate-levelindicatorsthatareusedtosummarizethedistributionoftheDItoobtainimportantinsightsintotradereportingpractices.

Definitionandempiricaldistribution

Foranygivenyear,givenapairofcountriesAandBandaproductC,theDiscrepancyIndexforthereportedimportofcountryAfromcountryBinproductCcanbedefinedasfollows:

(1.0)

whereMABCisvalueinUSdollars(USD)ofA’sreportedimportfromBinproductCandXBACisvalueinUSDofB’sreportedexporttoAinproductC.Here,werelyonthedefinitionof

Ferrantino&Wang,2008.Forsimplicity,timedimensionisomittedfromthenotation.Forany

orderedpairofcountries(A,B)andproductC,DIrangesfrom-1to1.Avalueof-1indicatesanorphanimport.DIABc=−1,whenAreportsanimportfromBbutBneverreportedthe

correspondingexporttoA(inproductC).Avalueof1indicateslostexport.DIABc=1,whenBreportsanexporttoAbutAneverreportedthecorrespondingimportfromB(inproductC).

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Avalueof0indicatesnodiscrepancybetweenthereportedexportandthecorrespondingreportedimport(ofproductC).TheinterpretationofthevaluesoftheDiscrepancyIndexisshowninFigure1.

Figure1:Interpretationofthevaluesofthediscrepancyindex

Note:Avalueof-1indicatesanorphanimport,i.e.,thereportedimporthasnocorrespondingmirror.Avalueof1indicatesalostexport,thatis,thereportedexporthasnocorrespondingmirror.Avalueof0indicatesno

discrepancy.Valuesbelow0areinterpretedasoverreportedimports,whereasvaluesabove0areinterpretedasunderreportedimports.

Ourconsiderationofbothstructuralandnon-structuralreasonsfortradediscrepanciessetsoutseveralexpectationsregardingthedistributionofthisbilateralasymmetrymeasure.First,we

anticipatethatreportedimportswillexceedreportedexportsbecausefreightandinsurance

costsareincludedinimportvaluation.Therefore,weexpecttheDiscrepancyIndextobemostlybelow0,indicatingoverreportedimports.

Second,weexpectthenumberoforphanimportsandlostexportstobeapproximatelyequal,assumingadherencetoreportingguidelines.Thisisbecausewhenanexportpassesthroughmultiplecountriesbeforereachingitsfinaldestination,everyintermediatecountrywillreportalostexport,asthedestinationthattheylistintheirexporttransactionliststheoriginalsourceofexports(andnottheintermediatecountry)inthecorrespondingimportrecord.Similarly,everyintermediatecountry(excludingthefirstone)andthedestinationwillalsoproduceanorphan

import.Therefore,assumingadherencetoreportingguidelines,itcanbeproventhatexports

passingthroughnintermediatecountrieswillproduceexactlynorphanimportandnlostexport

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records.Inaddition,thesizeandtradevalueoforphanimportsandlostexportswillreflecttheprevalenceofre-exportingininternationaltrade.

Finally,whenthevalueoftheDiscrepancyIndexisabove0,itshould(ideally)beexactlyoneandcorrespondtothelostre-exportscenario.ThisisbecauseanyvalueoftheDiscrepancy

Indexthatisabove0,butnotexactlyone,isleastlikelytobeexplainedbylogisticreasons.

Figure2evaluatesourassumptionsaboutthedistributionoftheDiscrepancyIndex.ThefigurepresentstheempiricaldistributionoftheDiscrepancyIndexatthe6-digitlevelforcountrypairsandproductsin2017.Thedistributionisderivedfrom10,307,996observationsinvolving208countries.

Figure2:DistributionoftheDiscrepancyIndex(DI)(2017)atthe6-digitlevel

Figure2showsthatat6-digitlevel,distributionofdiscrepancyindexacrossallcountry

partnershipsandcommoditygroupsshowsalargepresenceoforphanimportsandlostexports.Specifically,32%oftransactionscanbeclassifiedasorphanimports,whereas22%are

categorizedaslostexports.Infact,orp