D. Estimating the benefits of the Trade Facilitation Agreement · PDF fileWOLD TADE EOT 2015...

WORLD TRADE REPORT 2015

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D. Estimating the benefits of the Trade Facilitation Agreement

This section provides quantification of the various channels through which trade facilitation reform, and in particular implementation of the Trade Facilitation Agreement (TFA), can benefit the global economy. First of all, estimates of how much the implementation of the TFA could reduce trade costs are provided, and the group of countries and regions that may see the biggest reductions is identified. Further, estimates of the effects of the TFA on exports, export diversification and GDP, calculated using standard economic approaches, are presented. In order to provide a range of estimates, various implementation scenarios are considered. The differentiated impact of trade facilitation is analysed in order to provide insights on how the aggregate benefits of TFA implementation are distributed across country groups (developed, developing and least-developed countries), enterprises and product groups. Finally, the induced effects of trade facilitation on foreign direct investment, border revenue collection and reduction in trade-related and other forms of corruption are examined.

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TII. SPEEDING UP TRADE: BENEFITS AND CHALLENGES OF IMPLEMENTING

THE WTO TRADE FACILITATION AGREEMENT

Some key facts and findings

• Trade costs are high, particularly in developing countries. Full implementation of the Trade Facilitation Agreement (TFA) will reduce global trade costs by an average of 14.3 per cent. African countries and least-developed countries (LDCs) are expected to see the biggest average reduction in trade costs.

• Trade costs are among the fundamental factors shaping the evolution of trade. Any meaningful reduction in these costs will reduce the drag acting on global trade at present and has the potential to raise its future trajectory.

• Computable general equilibrium (CGE) simulations predict export gains from the TFA of between US$ 750 billion and well over US$ 1 trillion dollars per annum, depending on the implementation time-frame and coverage. Over the 2015-30 horizon, implementation of the TFA will add around 2.7 per cent per year to world export growth and more than half a per cent per year to world GDP growth.

• Gravity model estimates suggest that the trade gains from the TFA could be even larger, with increases in global exports of between US$ 1.1 trillion and US$ 3.6 trillion depending on the extent to which the provisions of the TFA are implemented.

• Developing countries have the most to gain from swift and full implementation of the TFA, as both exports and GDP growth will rise more than in developed countries.

• Implementing the TFA should create significant export diversification gains for developing countries, and particularly for LDCs. It should increase the opportunity for implementing developing countries to participate in global value chains. Furthermore, there is statistical evidence to show that, with trade facilitation reform, micro, small and medium-sized firms are more likely to export and to increase their export shares than large firms. Developing countries and LDCs implementing the TFA should also attract more foreign direct investment while improving their revenue collection and reducing the incidence of corruption.

Contents1 Reductionintradecosts 74

2 IncreasedtradeflowsandGDP 79

3 Differentiatedimpactoftradefacilitation 89

4 Inducedeffectsfromimplementingtradefacilitation 94

5 Conclusions 98

Appendixtables 101


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1. Reductionintradecosts

(a) Measuringtradecosts

As discussed in Section C, trade costs include allcostsincurredingettingagoodtothefinaluser,otherthan the cost of production itself (Anderson and vanWincoop, 2004). Trade costs include transportationcosts, tariffs and non-tariff measures, informationcosts,customsfeesandcharges,thecostoftime,etc.Some tradecostsareeasy tomeasure (e.g. feesandcharges forcustomsprocessing)butothersaremoredifficult(e.g.thecostofdelaysincustomsclearance).

Therearetwoprincipalwaysofmeasuringtradecosts:directlyandindirectly.Anexampleofmeasuringtradecosts directly is the collection of data on customsfees or transportation charges. In contrast, indirectmethods infer themagnitudeof tradecosts fromthevolume of trade flows or price differences acrossborders.Thedirectapproachtomeasuringtradecosts

and their components might seem preferable but isplaguedbydata limitations.Forexample, informationon transportation costs for all possible routes aredifficult to obtain from rail, shipping and airlinecompanies. Furthermore, the quality of this type ofdata can be poor (Hummels, 2001). The advantageof the indirect method is the greater availability ofthe data – for example trade flows – which are theraw material used to infer trade costs. This allowsestimates of trade costs to be made to cover morecountriesandyears.Theindirectmethodrequirestheuseofawell-groundedeconomicmodel,whichinthiscase is provided by the gravity model1 as extendedby Anderson and van Wincoop (2003), Novy (2011),andChenandNovy (2011). Thegravitymodel is themodern workhorse of empirical trade economics(HeadandMayer,2014)andalltheestimatesoftradecostsintherestofthissectionrelyonstudiesusingit.Themethodologyfordeducingthemagnitudeoftradecostsusing thegravitymodel isdescribed ingreaterdetailinBoxD.1.

Box D.1: Deriving trade costs from trade flows

Giventhedifficultiesinvolvedindirectlymeasuringtradecosts,researchershaveturnedtoindirectmethodstoinfertradecostsbycomparingthelevelsoftradeflows.Thebasicideabehindtheapproachisthatiftradebetweentwocountriesishigh,tradecostsbetweenthosetwocountriesmustberelativelylow,allthingsbeingthesame.

Novy (2011) builds on this idea and derives a ratio of “domestic” and international trade in a given sector.Domestictradereferstogoodstradedacrossdifferentregionsofthesamecountryandisusedasabenchmarkforborderlesstrade.Incontrast,exportsfromonecountrytoanotheraresubjecttoallthepossiblefrictionsthatcouldactoninternationaltrade.Thederivationofthisratiocapturesanythingthatmightrestricttradebetweentwopartners,overandabovetheeffectofintranationalbarriers.

Thefollowingequationsummarizestheapproachandyieldstradecostsinad valoremtariffequivalents,i.e.asapercentageoftheprice:

Trade costsij =

γ

–1Domestic tradeii Domestic tradejj

Exportsij Exportsjj

Thesubscript ij indicatesa flow fromcountry i to j, andγ isaparameteraccounting for theheterogeneityofproducts.Forexample, in theyear2000,Novy (2011)estimates that tradecostsbetween theUnitedStatesand Germany were equivalent to a 70 per cent tariff on average, whereas they amounted to a 25 per centtariffbetweentheUnitedStatesandCanada.Thesecostscomefromdistance,quotas,freightcosts,culturaldifferencesandanythingelsethatcoulddiscourageinternationaltrade.Infact,thismeasureevencapturestheeffectofhomebiasinconsumerpreferences.Thetariffequivalentisactuallytheaverageoftradecostsinbothdirections,meaningthatanychangeishardtoattributetoanactionbyeitheroneofthepartners.Thereisalsonodistinctionbetweenimportandexportcostsforeachcountry.

Theequationisabletoprovideestimatesofinternationaltradecosts,essentiallyallcostsincurredinmovingagoodfromtheborderofitotheborderofj.However,asnotedearlier,itdoesnotincludeintranationaltradecosts–thecostsinvolvedinmovingthegoodfromthesiteofproductionincountryitoitsborderorthecostofmovingthegoodfromtheborderofjtothefinalconsumptionsite.Thesecostsreflectavarietyofcauses,includinglackofcompetitionindistributionaswellaspoorinfrastructure.Theseintranationaltradecostsmaybequitehigh,even in developed countries. Agnosteva et al. (2014) estimate the intranational trade costs of manufacturedgoods inCanada tobeequivalent toapplyinganad valorem taxof109percent.AtkinandDavidson (2014)estimatethatthecostsofintranationaltradeareapproximatelyfourtofivetimeshigherinsomesub-SaharanAfricancountriesthanindevelopedcountries.

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Based on the available evidence, trade costs remainhigh.BasedontheArviset al. (2013)database, tradecostsindevelopingcountriesin2010wereequivalentto applying a 219 per cent ad valorem tariff oninternational trade.2 This implies that for each dollarit costs to manufacture a product, another US$ 2.19willbeaddedintheformoftradecosts.Eveninhigh-income countries, trade costs are high, as the sameproductwouldfaceanadditionalUS$1.34incost.3

Figure D.1 illustrates the magnitude of trade costsin developing countries and highlights their maincomponents.Thesizeofthetradecostrectangleisdrawnsothatitisproportionaltotheproductioncostofthegood.Alongwiththegeographicalfeaturesofthecountries(e.g.howdistant theyarefrommajormarkets),policy-relatedbarriersincludingtradefacilitation(logistics)accountformost of the variance in trade costs. The importance ofthese various components of trade cost is indicated bytheir font size: the bigger the font size the greater thecontributionofthatcomponenttotradecost.

(b) Sectoralpatternsoftradecosts

The aggregate estimates of trade costs discussedabove conceal large differences across sectors andregions. This sectoral and regional variation in tradecostsmeansthatimplementationoftheTFAislikelytohaveabiggertradeeffectonsomeproductsectorsandregionsthanonothers.

(i) Agriculture and manufacturing

In 2012, ad valorem trade costs in agriculture were68percenthigherthaninmanufacturing.4However,alackoftradefacilitationappearstobemoredamagingto trade in manufactured goods than to trade inagricultural goods. Part of this may be explained bythe fact that agricultural goods are traded in bulkand transported using slower moving carriers, sotraderscanadjusttodelaysincustomsclearance.Theone exception is fresh agricultural products, whichhave higher sensitivity to time and are increasinglytransported by air. By speeding up the clearance ofgoods across borders, trade facilitation could prove aboonfortradeinperishablegoods.

Tradecostsalsodifferamongmanufacturedgoods,asper Chen and Novy (2011), who calculate ad valoremtrade costs for different industries using EU memberdata.Goodswithahighweight-to-valueratio,suchasbricks (with an ad valorem trade cost of 30,000 percent)orplaster(800percent),faceextraordinarilyhightradecosts.Thosegoodsareexpensivetotransport–transit isoftenchargedbythekilogramme–buthavea low market value. Bread and pastry products areperishableandsofacehightradecosts(43percent).Finally, Chen and Novy find that high tech industriessuchasaircraftandspacecraftfacelowertradecosts(1.44percent).

(ii) Goods within value chains and the cost of time

Timeisacriticalfactorintheoperationofglobalvaluechains (GVCs). In 2013, the Fourth Global Reviewof Aid for Trade pointed to customs procedures,transportationcostsanddelaysasthebiggestfactorsblocking developing countries from integrating valuechains(WTO,2014).FigureD.2identifiesthedifferentdimensions of time that are critical to the success ofdisaggregated production structures, where just-in-time production is the order of the day. They includelead time, which refers to the time between when anorder ismadeandwhen thegoodsaredelivered,andvariabilityindeliverytime.

Zaki (2015) confirms that intermediate goods thatfeature prominently in GVCs are particularly time-sensitive,asthesegoodsaremoreadverselyaffectedby delays. He derives the ad valorem tariff equivalentoftimefordifferentproductsectors.Thisisanoverallmeasureof theeffectofdelaysand red tape ineachsector. Moreover, for each type of product, the costof time is described separately for export and importprocedures. Figure D.3 shows the 10 industries thatsufferthemostfromdelaysindeliverytime.Onaverage,thecostoftimeishigherontheimportsidethanontheexport side. Import procedures may take longer thanexportproceduresbecauseimportsareoftenarevenuesource, and because of the greater heterogeneity ofimports,giventhatcountriestypicallyimportabroaderrange of goods than they export. On both the import

Figure D.1: Composition of trade costs in developing countries

Production value of good

Distance and bordersTrade costs219% of

production value Currency

Other policy costs

Trade facilitation(logistics) andconnectivity

Tariffs Culture

Source: WTOSecretariatcalculationsbasedondatafromArviset al.(2013).


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and export sides, goods destined for use in valuechains (electricalmachineryandequipment, transportequipment, and apparel and textiles) are particularlytime-sensitive.

(c) Geographicalpatternsoftradecosts

This subsection presents the geographical pattern oftradecosts.Thesetariffequivalentscapturealltypesof

tradeimpedimentsandarebilateralaveragesofcostsinbothdirections,foreachpairofcountries.Thesead valorem equivalents include the costs of both exportand import procedures. The data come from Arvis et al.(2013)anddescribetradecostsfor178economiesfrom1995to2012.

Figure D.4 shows the world map of trade costs. The10 economies with the lowest trade costs are alllocated in Western Europe or North America. At theother end of the spectrum, the 10 economies withthehighesttradecostsareeitherfromAfricaorsmallislanddevelopingstates,suchasComoros,KiribatiandVanuatu.

AsshowninFigureD.5,tradecostsaredecreasinginincome levels.By region,Africahas thehighest tradecosts at over 260 ad valorem tariff equivalent. Theisolation of landlocked countries in the continent isevenstarker,as they incuranadditional tradecostof40percent,notapplicabletocoastalAfricancountries,although policy factors may also be a contributingfactor(Borchertet al.,2012).

(d) Estimatesoftradecostreductionsfromtradefacilitation

This subsection reviewsestimatesof the reduction intradecoststhatcouldbeachievedifallcountriesfullyimplement the provisions of the TFA. The first study,by Hillberry and Zhang (2015), looks at the impactof full implementation on the time required to importand export in each country, measured in days. Thesecond study, by Moïsé and Sorescu (2013), is morecomprehensive in scope and estimates reductionsin total trade costs from full implementation of theAgreement. The estimated reduction in trade costsderived by Moïsé and Sorescu (2013) will be used inthe latterpartofSectionD tosimulate the tradeandincomeeffectsofimplementingtheTFA.

Figure D.3: Ad valorem tariff equivalents of export and import times(per cent)

Other chemicals

Professional and scientific equipment

Beverages

Machinery, electric

Other manufactured products

Rubber products

Petroleum refineries

Machinery, except electrical

Textiles

Transport equipment

Exports

0 5 10 15 20 25 30 35 40

Non-ferrous metals

Rubber products

Furniture, except metal

Prof. and scientific equipment

Wearing apparel, except footwear

Other manufactured products

Machinery, electric

Textiles

Transport equipment

Beverages

Imports

0 10 20 30 40 50 60 70 80 90

Source: Zaki(2015)

Figure D.2: Dimensions of time in value chains

Just-in-timeProcess in which

inputs arriveat the factory at the

point where they enterthe production

chain

Lead timeTime between

order placementand receipt of

the goods

Time variabilityVariation in

delivery timesfrom a given

senderLead time is not

necessarily an issue if timevariability is low

(deliveries are predictable)

Source: Nordåset al.(2006)

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Both studies employ the OECD’s Trade FacilitationIndicators(TFIs),whichwerediscussedinSectionC,tosimulatefullimplementationoftheTFA.Thisassumesthat all economies reach best practice standards oftrade facilitation, as measured by twelve different

OECD TFIs. As detailed in Section C, each indicatorisscoredfromzerototwo,withtwobeingthehighestvalue.Inthefullimplementationscenario,itisassumedthateacheconomyachievesthemaximumscoreoftwoineachofthe12OECDTFIs.

Figure D.5: Ad valorem tariff equivalents of trade costs by region and level of development, 2008(per cent)

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Figure D.4: Ad valorem tariff equivalents of trade costs with the main world importers, 2010 or latest available year(per cent)

46–130 130–214 214–298 298–382 No data

Note: The“restoftheworld”,foreacheconomy, isconsideredtobethe10largest importersin2010.Theseare:theUnitedStates,China,Germany, France, Japan, the United Kingdom, Italy, Canada, Republic of Korea and Mexico. Trade costs are expressed as ad valoremequivalents. Data are unavailable at the time of writing for those territories coloured in green. Colours and boundaries do not imply anyjudgementonthepartoftheWTOastothelegalstatusofanyfrontierorterritory.



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(i) Reduction in time to import and export

One of the questions Hillberry and Zhang (2015)examine is the effect of trade facilitation on the timerequired to import and export. They find that fullimplementationoftheTFAhasthepotentialtoreducetimeto importbyoveradayandahalf(a47percentreduction)andtimetoexportbyalmosttwodays(a91percentreduction),forWTOmembers.Timetoexportis found to be more sensitive to trade facilitation.The authors note that export procedures are usuallyconcentratedinasubsetofproducts,andaresimpler,whereas import procedures are inherently morecomplicatedbecauseoftheheterogeneityofincominggoods. As noted earlier, countries typically export anarrowerrangeofgoodsthantheyimport,andimportsareoftenasourceofcustomsrevenues.

In terms of individual trade facilitation provisions,Hillberry and Zhang (2015) find that governanceand automation are the most time-saving reforms.Governance, for example, accounts for 37 per centof the reduction in the time to import. Automation isresponsible for about 30 per cent of the reductionin time to import, which is understandable, sinceautomation covers some of trade facilitation’s keyareas, suchas theelectronicexchangeofdocumentsandtheapplicationofriskmanagementprocedures.

(ii) Reduction in total trade costs

Turning now to the study of Moïsé and Sorescu,Figure D.6 shows the estimated trade cost reduction

across theglobe fromfull implementationof theTFA.The reduction in trade costs is in the range of9.6 to23.1per centwith theaverage reductionbeingequalto 14.5 per cent. Not surprisingly, economies withthe biggest pre-implementation deficiencies in tradefacilitation standards are set to reap the greatestreductions. Even the smallest estimate of trade costreduction implies that full implementation of the TFAwill have an even bigger impact on trade costs thanreducing all most-favoured nation tariffs (currentlyestimatedtoaveragearound9percent)tozero–recallthat theestimatedad valoremestimateof tradecostsindevelopingcountriesis219percent,andis134percent in high-income countries. Even if one takes thesmallestestimateofa9.6percent reduction in tradecosts, this is equivalent to reducing the ad valoremequivalent of trade costs in developing countries by21 percentage points (from 219 per cent to198 per cent) and by 13 percentage points in high-incomecountries(from134percentto121percent).

Overall, the average trade cost reduction for allmerchandisegoods is14.3percent,withtheaveragedecrease in trade costs for manufactured goods at18 per cent, against 10.4 per cent for agriculturalgoods.FigureD.7showsthatallregionsareexpectedto experience reductions in trade costs, with Africa(16.5 per cent) benefitting the most. Comparisonsof the anticipated impact of TFA implementation ondifferent incomegroupssuggest that least-developedcountries(LDCs)willseethebiggestreductionintradecosts(16.73percent).

Figure D.6: Estimated reductions in ad valorem tariff equivalent trade costs due to TFA implementation(percentage change)

9.6–12.2 12.2–13.9 13.9–15.8 15.8–23.1 No data

Note: Dataareunavailableatthetimeofwritingforthoseterritoriescolouredingreen.ColoursandboundariesdonotimplyanyjudgementonthepartoftheWTOastothelegalstatusofanyfrontierorterritory.

Source: WTOSecretariatcalculationsusingdisaggregatedestimatesfromMoiséandSorescu(2013)basedontheOECDTFIs.

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2. IncreasedtradeflowsandGDP

Thetwomostcommonlyusedeconomicapproachestoestimatingthetradeimpactoftradefacilitationreformaregravityandcomputablegeneralequilibrium(CGE)models.Thisreportemploysestimatesfromthesetwomethodologies to ensure that results are consistentand to provide complementary perspectives on thebenefitsof implementing theTFA.Beforeconsideringtheresultsofarangeofsuchstudies,thissubsectionprovidesashortsummaryofthesetwomethodologies(PiermartiniandTeh(2005)andWTOandUN(2012)).

CGEmodelsare“ex-ante”(i.e.,ananalysisofprospectiveresults) computer-based simulations of changes intrade policy, designed to answer “what if” types ofquestions.Theyallowpolicy-makerstoadjustthevalueofavariable,forexampletradeprocedures,andobtainnumericalvaluesoftheexpectedeffectsoneconomicvariables, either in a static or dynamicperspective. Incontrasttopartialequilibriummodels,CGEmodelstakeintoaccount the interdependenceofnations,marketsand economic actors, typically households and firms.They make assumptions about the market structure,productiontechnology,consumerpreferencesandthesubstitutabilitybetweenforeignanddomesticproductvarieties. The model is first calibrated to reproduceexactly theobserveddata for a reference year,whichisusedasthebaseline.Toproducethecounterfactualscenario, the policy change of interest is introducedto the model and the model is then solved by setting

prices in such a way that, in equilibrium, consumersmaximize their welfare, and firms their profits, underthe constraints imposed by the available resourcesandpolicies.Thedifference in tradeandGDP(oranyother economic variables of interest) between thecounterfactualandbaselinescenariosconstitutes thecausaleffectofthepolicychange.

Gravity models are econometric models of trade thatuse historical data to determine the effect of pastpolicyontradeflows.Whiletheyare“ex-post”models—basedonananalysisofpastoutcomes—theycanbeusedafterestimationtosimulatetheeffectofpolicies“ex-ante”,providedthatthesepoliciesareimplementedincomparablecircumstances.Theirnamecomesfromthe similarity with the Newtonian theory of gravity,since themain featureof themodel is that volumeoftradebetweenanytwocountriesispositivelyrelatedtothesizeoftheireconomies(usuallymeasuredbyGDP)andinverselyrelatedtothetradecostsbetweenthem.Inaddition,foranytwocountries,theleveloftradenotonlydependsontheirbilateraltradecosts,butalsoonthe barriers that they face as well as impose on therestoftheworld–theso-calledmultilateralresistanceterms(AndersonandvanWincoop,2003).

The high explanatory power of the gravity approachmakes it a common choice in the empirical tradeliterature, although this is not its only virtue. It hasbeen shown to be consistent with many models ofinternational trade including Ricardian comparative

Figure D.7: Estimated reductions in ad valorem tariff equivalent trade costs due to TFA implementation by region and level of development (per cent)

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Source: WTOSecretariatcalculationsusingdisaggregatedestimatesbyMoïséandSorescu(2013)basedontheOECDTFIs.


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advantageandKrugman’snewtradetheory(HeadandMayer,2014).Inmuchofthetradeliterature,simulationsundertaken with the gravity model are interpreted aspartialequilibriumanalysissincethechanges in tradefromthesimulationsdonotfeedbacktoGDPandthusonlythetradeeffectscanbedetermined.

A number of recent studies have estimated the tradeeffects of trade facilitation, using gravity, CGE or amix of the two models (see Table D.1 for a compactrepresentation of the results). Hufbauer and Schott(2013) perform a “thought experiment” in whichcountries improve their trade facilitation measureshalfwaytotheregion’stopperformerineachcategory.5Theyestimateanincreaseintotalmerchandiseexports

ofUS$1trillionperannum,withdevelopingcountries’traderisingbyUS$569billion(a9.9percentincrease)and developed countries’ total exports rising byUS$ 475 billion (a 4.5 per cent increase). Theseestimatesarelargerthaninanearlierstudy(Hufbaueret al.,2010),whichdrewontradefacilitationproxiesbyWilsonet al.(2005)andfoundincreasesinexportsofUS$ 47.3 billion and US$ 39.5 billion for developinganddevelopedcountries,respectively.

Hoekman and Nicita (2011) estimate that thepercentage increase in exports (imports) of low-income countries that would result from a combinedconvergence of the World Bank Group’s “DoingBusiness” cost-of-trading indicator and of the World

Table D.1: Selected studies on the effect of trade facilitation on trade flows

Study Model Assumption Variable Developed Developing World

DecreuxandFontagné(2009)

CGE50percentreductioninAVEcostoftimeattheborder,softandhardinfrastructure.

Export n.a. n.a. +bUS$ 383

IwanowandKirkpatrick(2009)

Gravity10percentimprovementintradefacilitationindex.

Export(manufacturing)

n.a. Africa:+6% +2.1%

Hufbaueret al.(2010)

OtherImprovemeasuresofcustomsandregulatoryenvironmenthalfwaytoglobalaverage.

Export +bUS$ 39.5 +bUS$ 47.3 +bUS$ 86.8

DecreuxandFontagné(2011)

CGE50percentreductioninAVEcostoftimeattheborder,softinfrastructure.

Export n.a. n.a.+bUS$ 359 (1.9%)

DennisandShepherd(2011)

Gravity10percentreductionincostsof(1)exporting(2)internationaltransport(3)marketentry.

Exportvariety n.a. n.a.(1)+3% (2)+4% (3)+1%

HoekmanandNicita(2011)

GravityImprovetradefacilitationtomiddle-incomecountriesaverage.

ExportImport

n.a.n.a.

+17% +13.5%

n.a.n.a.

Portugal-PerezandWilson(2012)

GravityImproveborderandtransportefficiencyhalfwaytotopperformerintheregion.

ExportPositiveeffectdecreasingwithincome.

Chad:+17% Mongolia:+3% Kazakhstan:+23% Venezuela:+4%

Positiveandsignificant

FerrantinoandTsigas(2013)

GravityandCGE

Countriesimprovetradefacilitationhalfwaytoglobalbestpractice.

Countriesimprovetradefacilitationhalfwaytoregionalbestpractice.

Export n.a. n.a.

bUS$ 1,584 (14.5%)

bUS$ 1,030 (9.4%)

HufbauerandSchott(2013)

GravityImprovetradefacilitationhalfwaytotheregion’stopperformerineachcategory.

Export+bUS$ 475 (4.5%)

+bUS$ 569 (+9.9%)

+bUS$ 1,043

Persson(2013) Gravity1percentreductioninnumberofdaysneededtoexport.

Exportvariety n.a. n.a.HG:+0.3% DG:+0.6%

FeenstraandMa(2014)

Gravity10percentimprovementinbilateralportefficiency.

Exportvariety n.a. n.a.+1.5% to +3.4%

Zaki(2014)

GravityandCGE(twosteps)

50percentreductioninAVEcostoftimetoimportandexport.

ExportEU:+10.6% US:+3.9 Japan:+2.1%

SSA:+22.3% Asia:+16.2% LAC:+16.2%

n.a.

Mevelet al.(forthcoming)

CGE

25percentreductioninAVEcostoftimetoimportandexport.Effectoftradefacilitationpost-CFTAimplementation.

Export

EU:+bUS$ 164.5 US:+bUS$ 121.8

NA:+bUS$ 11.5 MENA:+bUS$ 36.4 RoA:+bUS$ 38.4

+bUS$ 1,224

Notes: AVE = ad valorem equivalent; CFTA = Continental Free Trade Area in Africa; DG = differentiated good; HG = Homogeneous goods;LAC = Latin America and the Caribbean; NA = North Africa; RoA = Rest of Africa; MENA = Middle East and North African countries;SSA=Sub-SaharanAfrica.

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Bank’sLogisticsPerformanceIndex(LPI)scoretotheaverage of middle-income countries would be 17 percent(13.5percent).

DecreuxandFontagné(2011)andZaki(2014)providetworecentCGEestimatesofthetradeimpactoftradefacilitation. Decreux and Fontagné represent tradecosts as the ad valorem equivalent of the time at thefrontier(customsproceduresandtimeattheport),usinginformation from the “Doing Business” indicators andestimatesbyMinorandTsigas(2008).Tradefacilitationreform is represented by a 50 per cent reduction inthesecosts.UsingtheMIRAGE(ModellingInternationalRelationships in Applied General Equilibrium) CGEmodel, they calculate an expansion in global trade ofaround2percentorUS$359billion.Thisresultshouldbe considered more conservative than Decreux andFontagné(2009),who include infrastructurevariablesgoingbeyondthecoverageoftheTFA.Inthispreviousstudy,theyestimateanincreaseinexportinthesamerangeatUS$383billionandfindthatgainsfromtradefacilitation would almost only arise for developingcountries,inparticularinSub-SaharanAfrica.

Zakiadoptsatwo-stepapproach,usingagravitymodeltofirstcalculatethead valoremequivalentsofthetimeto export and import. In a second step he assumesthattradefacilitationreformwill leadtoa50percentreduction in these ad valorem trade costs, and alsouses the MIRAGE CGE model to simulate the tradeimpact.Hefindsthatdevelopingcountriestendtoseethelargestincreasesinbothexportsandimports.Sub-Saharan African, Asian, Latin American and MiddleEastern exports increase by 22.3 per cent, 16.2 percent, 16.2 per cent, and 13.8 per cent, respectively,followingtradefacilitationreform.Importsareincreasedbyalmostthesamemagnitude.

Mervel et al. (forthcoming) study the long-run yearlyimpact of the African Continental Free Trade Area(CFTA) and the TFA using a dynamic version of theMIRAGE CGE model covering 29 manufacturingsectorsinallNorthAfricancountriesandtherestoftheworld by sub-groups. They measure trade facilitationusing the same indicator as Decreux and Fontagné,but only consider a 25 per cent reduction in theestimatedad valoremcosttoexportby2017.TheextraincreaseinexportsbroughtbytheTFAismeasuredatUS$ 11.5 billion, US$ 36.4 billion, US$ 38.4 billion,US$ 164.5 billion and US$ 121.8 billion for NorthAfrica,theMiddleEast,therestofAfrica,theEuropeanUnion and the United States, respectively. Includingthe rest of the world, this amounts to an increase ofUS$1,224billioninglobaltrade.

Therestofthissubsectionwillpresentnewestimatesusing indicators of trade facilitation that more

closely reflect the TFA, developing more realisticimplementationscenariosandusingbotheconometricapproaches (subsections D.2(b) and (c)) and CGEsimulations (subsection D.2(d)). It begins with adescription of the data used and with details on theconstructionoftheimplementationscenarios.

(a) DataandTFAimplementationscenarios

In the following scenarios, the OECD TFIs (averageTFI(a)–TFI(l))areusedasaproxyfortradefacilitation.6As discussed in Section C, the OECD TFIs closelyreflect the WTO’s TFA. The OECD TFIs used in thisreportcover133economies.Thetradedatausedinthegravity estimation cover the years 2003 to 2011, aredisaggregatedbyimportingcountry,exportingcountryand HS67 sub-headings, and come from the CEPIIBACI dataset (i.e. the international trade database oftheCentre d’études et d’informations internationales).

The following three implementation scenarios of theTFAareusedinthesimulations:

1. Conservativescenario

This scenario takes into account notifications of TFACategoryA8commitments receivedby theWTOfrom52developingcountriesasofearlyJanuary2015.9

Forthegroupof52notifyingdevelopingcountries,thecommitments,byarticleoftheTFA,aretranslatedintoOECDTFIsusing thecorrespondencebetween theseindicatorsandtheTFA.Ifacountrycommitstoatleast95percentofthearticlesthatbelongtoeachindicator,thisindicatorissettoitsmaximumvalueof2.ThenewaverageTFIvalueiscalculatedaccordingly.

Forthegroupof35developedcountries,itisassumedthat theywill fully implement theTFAandhencetheirTFIscoresaresettothemaximumvalueof2.

Finally, for the group of non-notifying developingcountries, the new level of TFI is predicted “out-of-sample”.Theprocedureisasfollows:aregressionwiththeTFIasdependentvariable,usingthe levelofGDPpercapitaandWTOregionsasexplanatoryvariables,isestimatedonthesampleofthe52notifyingdevelopingcountries and35developedcountries. The estimatedcoefficients from the regression are then used to fitpredicted TFI values to the non-notifying developingcountries.

2. Liberalscenario

This scenario is constructed in a similar way to theconservativescenario–withtheonlydifferencebeingthat the threshold in commitments used to assign a


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value of 2 to the relevant TFI indicator is lower, andequalto75percent.

3. Fullimplementationscenario

Inthisscenario,theTFIissettoitsmaximumvalueof2forallcountries.

To assist the reader through the discussion of all thesimulationresults,TableD.2providesasummaryoftheestimatedimpactonexportsandGDPofimplementingthe TFA using the two methodological approachesusedinthisreport.

(b) Increaseinexportflows

This subsection estimates the impact of tradefacilitationontheintensivemarginsoftrade,i.e.ontotalexports, where, in order to smooth out fluctuations intheseries,dataonaverageexport flowsfor theyears2003-11areused.

Theeffectoftradefacilitationontotalexportsispositiveandsignificant,asshowninAppendixTableD.1.10Inthetable,Column(1)usesthe(naturallogarithmof)TFIoftheexportingcountryasameasureoftradefacilitation,controllingfor importerfixedeffects.Column(2)usesameasureof bilateral trade facilitation, TFIij, equal tothegeometricaverageoftheexporter’s(countryi)andimporter’s (country j) TFI, as in Moïsé and Sorescu(2013). These columns, too, include importer fixedeffects. Although coefficients cannot be compareddirectly across different regressions, bilateral tradefacilitationisassociatedwithabiggereffectontrade.

BasedontheestimationresultsofAppendixTableD.1,aseriesofcounterfactualanalyseswereconducted,toestimatethepercentage increase in thevalueof totalexportsaswellastheactualdollarincreasesunderthescenariosoutlinedabove.Theresults,averagedacrossincomegroups,arepresentedinTableD.3.Itshowsthat

the increase inexports isgenerallyhigher in theTFIijscenarios,which isnotsurprisingas thiscorrespondstoamultilateralincreaseinboththeexporter’sTFIiandtheimporter’sTFIj.Startingwiththefirsttwoscenarios,“conservative”and“liberal”, theestimatedincreasesinexportsrangefrom7percentto18percent.Perhapsnotsurprisingly,thebiggestincreaseoccursunderthe“full” implementationscenariowithexportgainsofupto36percent forLDCs.Thecorrespondingchangesin export values, measured in billions of US dollars,are also shown in Table D.3. Globally, the estimatedincreaseinexportsrangesfromUS$1,132.6billioninthe“conservative”scenario toUS$3,564.87billion inthe“full”implementationscenario.

A possible concern with these simulations is that theyare based on the average effect of trade facilitation,estimatedtobeequal forcountries that implement theTFAandcountries thatdonot in therelevantscenario.Theeffectscouldbenon-linearwithin thesample.Forinstance,theeffectoftradefacilitationcouldbehigherforlowvaluesoftradefacilitationasopposedtohighvaluesof trade facilitation. A number of different approacheswere explored to address these issues.11 The overallconclusion from exploring these different approachesisthattheresultspresentedinAppendixTableD.1andusedforthesimulationsarelargelyunaffected.

It is important to emphasize that the gravity-basedsimulationsconductedhereareofapartialequilibriumnature, since they only include the direct effects ofthe policy experiment (implementation of the TFA).Conditionalgeneralequilibriumanalysiswould includesecondary effects through the multilateral resistanceterms.Theliteratureonthetradeeffectsofpreferentialtrade arrangements (PTAs) has found that the partialequilibrium results overstate the conditional generalequilibriumoutcome.Inparticular,Andersonet al.(2014)haveshownthatinthecaseoftheNorthAmericanFreeTradeAgreement(NAFTA),thedifferenceisafactorofaroundtwo.

Table D.2: Estimated trade and GDP impacts of TFA implementation

Units Range of values

I. Gravity model

ExportsBillioncurrentUS$ 1,133 3,565

Percentagechange 9.1 28.7

II. Dynamic computable general equilibrium model

Exports

Billionconstant(2007)US$ 750 1,045

Additiontoaverageannualpercentagegrowth,2015-30

2.06 2.73

GDP

Billionconstant(2007)US$ 345 555

Additiontoaverageannualpercentagegrowth,2015-30

0.34 0.54

Source: WTOSecretariatandFontagnéet al.(2015).

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However, discriminatory trade liberalization, asembodiedbytheformationofaPTA, isdifferentfromtradefacilitation.InaPTA,bilateraltradecostsareonlyreducedforthepartners.Thismeansthatnon-membersbecomemore“distant”frommembers.Thismutesthepartialequilibriumtradeexpansioneffectsthroughthemultilateral resistance terms. However, in the case oftradefacilitation,bilateraltradecostsarereducedforallpossiblepairsofcountries.Therefore,theyallmaintainthesamerelative“distance”tooneanother.Thisimpliesthat there may not be a big difference between thepartial equilibrium and conditional general equilibriumresults. The results of CGE simulations, discussed insubsectionD.2(d),produce,infact,comparableresultsat the lower end of the estimates, yielding estimatesof trade expansion between US$ 750 billion andUS$1trillion.

(c) Exportdiversification:newmarketsandnewproducts

Trade facilitation is likely to impact both variable andfixed trade costs of exporting. The formalities andrequirements of a country’s customs have to be meteach timeashipmentcrossesaborder.Therearealso,however, one-time costs, such as those incurred by afirm to acquire information on border procedures. Thenumber and complexity of the documents required for

clearance can also be seen as a fixed cost. Tradershavetheone-timecostthat involves learninghowtofillintheforms.TheymayalsohavetopurchasespecialistITsystemsandsearchfordedicatedstaffwhowilldealwithcustomsmatters(Grainger,2008).AstheWTOTFAcontains provisions requiring countries to publish andmakeavailableinformationonborderprocedures,aswellastodecreaseandsimplifydocumentationrequirements,it should reduce fixed costs and create new tradingopportunities. Firms that did not export before may beable to do so now, since their revenues could coverthe lower fixedcostsofexporting (Melitz,2003).Tradefacilitationcan,therefore,leadtoexportdiversification.

The empirical evidence on the export diversificationeffects of trade facilitation is quite limited whencompared to the literature on its effects on existingtrade flows. Nordås et al. (2006) were among thefirst to show the negative effects of time to exporton the probability to export. Dennis and Shepherd(2011) estimate the impact of various World BankGroup’s “Doing Business” indicators on the numberof products that developing countries export to andimport from the European Union. They find that poortrade facilitationhasanegative impactondevelopingcountry export diversification. Another approach istakenbyFeenstraandMa(2014).Theyassociatetradefacilitationwithportefficiencyandestimateitsimpact

Table D.3: Estimated increases in exports by level of development under various TFA implementation scenarios from regression-based simulations(percentage change and billion current US$ increase)

TFIi TFIij

Percentage change bUS$ Percentage change bUS$

"Conservative" scenario

Developed 10 697.11 16 1,453.77

G-20developing 7 264.86 12 601.66

LDCs 13 11.15 10 16.67

Otherdeveloping 9 159.44 12 320.59

Total 1,132.6 2,392.7

“Liberal” scenario

Developed 10 697.11 18 1,514.70

G-20developing 9 387.86 15 778.05

LDCs 13 12.06 12 19.21


Total 1,304.7 2,716.9

“Full” scenario

Developed 10 697.11 26 1,664.71

G-20developing 12 629.20 27 1,168.48

LDCs 35 40.06 36 47.44


Total 1,788.32 3,564.87

Source: WTOSecretariat.


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onexportvariety,showing thepositiveandsignificanteffects of port efficiency on export variety. Finally,Persson (2013) distinguishes between the effectsof trade facilitation (measured using the number ofdays needed to export, from the World Bank Group’s“Doing Business” indicators) on homogeneous anddifferentiatedproducts.Shefindsthattradefacilitationhas a higher impact on differentiated products.Reducing export transaction costs increases thenumberofdifferentiatedproductsby0.7percentandby0.4percentforhomogeneousproducts.

This subsection presents evidence of the impactof the TFA on export diversification, based on themethodology outlined in Beverelli et al. (2015).Two indicators of export diversification areconsidered: the number of exported products bydestination and the number of export destinationsby product. The number of exported products,npdij, counts how many Harmonized System (HS)sub-headings (six-digit HS codes) a country i exportstodestination j. IntheHS2002classificationusedforthisexercise, thereare5,224sub-headings.Foreachcountry pair, npdij can therefore theoretically rangebetween 0 (no trade) and 5,224 (country i exportsall products to destination j).12 The number of exportdestinations,ndpik, countshowmanydestinationsareservedbycountryi ’sexportsofproductk.Thenumberof export destinations is bound by the number ofcountriesincludedintheCEPIIBACIdataset,whichisthesourceofthetradedata.

Descriptive statistics for npdij andndpik for groupsofcountriesatdifferentstagesofeconomicdevelopmentare presented in Table D.4. The table shows that thelevel of diversification in G-20 developing countries

is comparable to the diversification of developedcountries.Otherdevelopingcountries lagbehind.Thisis especially the case for LDCs, which, on average,exportonly23outofthepossible4,795productstoagivendestinationandserveonedestinationmarketoutofthepossible202foragivenproduct.

Econometric estimates of the impact of exporter’stradefacilitationonthenumberofexportedproductsbydestination,andon thenumberofexportdestinationsbyproduct,arepresentedinAppendixTableD.2.Tradefacilitationhasapositiveandsignificanteffectonthenumber of exported products by destination and thenumberofexportdestinationsbyproduct.

TheresultsshowninAppendixTableD.2havebeenusedtoconductcounterfactualanalysisaimedatprovidinginsightsintothepotentialexportdiversificationbenefitsof TFA implementation. The percentage increases inthe number of export destinations and in the numberof exported products have been estimated under thethree scenarios described in subsection D.2(a).13Table D.5 presents the results for the number ofproducts by destination, based on the estimationsin columns (1)-(2) of Appendix Table D.2. Table D.6presentstheresultsforthenumberofdestinationsbyproduct, based on the estimations in columns (3)-(4)of Appendix Table D.2. All results are aggregated bydevelopmentlevelinthesetables.14

The effect of trade facilitation reform on exportdiversification is estimated to be substantial fordeveloping countries, in particular for LDCs. ThesegainsareshowninTableD.5.Thefirstcolumnpresents“Baseline” estimations where the dependent variable(thenumberofHS6productsexported)isconstructed

Table D.4: Descriptive statistics on export diversification by level of development

Development status Average Median Standard deviation Maximum

Panel (a): Number of exported products by destination (npdij)

Developed 717 233 1,009.4 4,795

G-20developing 672 250 900.1 4,320

LDC 19 1 60.7 1,109

Otherdeveloping 101 6 297.0 4,144

Total 271 13 650.1 4,795

Panel (b): Number of export destinations by product (ndpik)

Developed 25 11 32.6 202

G-20developing 24 10 32.8 193

LDC 1 0 3.0 104

Otherdeveloping 4 0 9.9 177

Total 10 1 21.9 202

Notes: DescriptivestatisticsinPanel(a)obtainedfromthesampleofcolumn(1)ofAppendixTableD.2.DescriptivestatisticsinPanel(b)obtainedfromthesampleofcolumn(3)ofAppendixTableD.2.


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Table D.5: Estimated increases in the number of products by destination due to TFA implementation by level of development(percentage change)

Baseline New HS6


Developed 9.1 9.8

G-20developing 6.2 6.7

LDCs 11.8 12.8

Otherdeveloping 8.4 9.1


Developed 9.1 9.8


LDCs 12.1 13.1


“Full” scenario

Developed 9.1 9.8


LDCs 32.9 35.6


Notes: Thenumbersindicatepercentagechangeinnpdij(numberofexportedproductsbydestination)undertherelevantscenario.Thefirstcolumnpresents“Baseline”estimationswherethedependentvariable(thenumberofHS6productsexported)isconstructedusingtradedatafor2009.ThesecondcolumnusesonlythenumberofHS6productsthatwerenotexportedbefore2008(“NewHS6”)intheconstructionofthedependentvariable.Thisisintendedtoaddressreversecausalityconcerns,inotherwords,thepossibilitythatthenumberofproductsexportedbyacountrycauseschangestotradefacilitation.ByusingonlythenumberofnewHS6products,thispossibilityofreversecausationisreducedifnotentirelyeliminated.“Baseline”resultsarebasedoncolumn(1)ofAppendixTableD.2.“NewHS6”resultsarebasedoncolumn(2)ofAppendixTableD.2.


usingtradedatafor2009.Thesecondcolumnusesonlythe number of HS6 products that were not exportedbefore 2008 (“New HS6”) in the construction of thedependentvariable.Thisisintendedtoaddressreversecausality concerns, in other words, the possibilitythat the number of products exported by a countrycauseschangestotradefacilitation.ByusingonlythenumberofnewHS6products,thispossibilityofreversecausationisreducedifnotentirelyeliminated.

As shown in Table D.5, under the “conservative”scenario of partial implementation of the TFA,LDCs stand to increase the number of productsexported by destination by 11.8 to 12.8 per cent, onaverage. The gains become much larger under thefull implementation scenario, with gains of 32.9 to35.6 per cent. Other developing countries also standto experience big gains, with an estimated increasein the number of products exported by destinationranging from 8.4 to 9.1 per cent (“conservative”partial implementationscenario) tobetween18.4and20percent(fullimplementationscenario).

Asimilarpatternemergesforthenumberofdestinationsbyproduct(seeTableD.6).Otherdevelopingcountriesand (toa largerextent)LDCsstand togain themost.Thefirstcolumnpresents“Baseline”estimationswhere

the dependent variable (the number of destinationsexported to) is constructed using trade data for2009. The second column uses only the number ofdestinations thatwerenotservedbefore2008 (“Newdestinations”) in the construction of the dependentvariable. As explained above, this is intended toaddressreversecausalityconcernsthatthenumberofdestinationsthatacountryexportstocauseschangesto trade facilitation.Byusingonly thenumberofnewdestinations, this possibility of reverse causation isreducedifnotentirelyeliminated.

Consider again the “conservative” scenario of partialimplementation of the TFA. The percentage increasein thenumberofdestinationsbyproduct ranges from10 to 15.1 per cent for other developing countriesand from 14.1 to 21.3 per cent for LDCs. Under fullimplementation,thegainsarebetween22and33.2percentforotherdevelopingcountriesandbetween39.2and59.3percentforLDCs.

It is worth noting that the gains for G-20 developingcountries are smaller, and comparable in size to thegains for developed countries. This is because, asshowninsubsectionC.2,theyhave,onaverage,levelsof trade facilitationverysimilar to thoseofdevelopedcountries.


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(d) Computablegeneralequilibrium(CGE)simulations

Besides gravity-based estimations, CGE simulationshavebeenemployed inorder toassess theeconomicand trade impact of trade facilitation. While thestudiesreviewedintheintroductionareinlinewiththeestimationresultspresentedbelow,conductingitsownCGEsimulationsoffersthisreportanumberofdistinctadvantages. First, unlike previous studies using moregeneralmeasuresoftradecosts,oneisabletoisolatetheimpactoftradecostreductionsthatarespecificallydue to theTFAas reflected indisaggregatedcountryand sector level estimates by Moïsé and Sorescu(2013)using theOECDTFIs.15Second,onecan takeintoaccountvariousimplementationscenariosintermsofboththecoverageofprovisionsadoptedbyindividualcountriesandthetimeframewithinwhichcommitmentswill be implemented. In this way, it is possible toillustrate the sensitivity of outcomes to various levelsof “ambition”. One is also able to apportion the gainsto country groupings commonly used at the WTO.Third,onecanemployadynamicapproachcombininga macroeconomic baseline scenario (using the MaGE–MacroeconometricsoftheGlobalEconomy–model)with trade policy simulations in the context of a CGEframework (MIRAGE), following the set-up described

in Box D.2. This not only results in a fully traceable,internally consistent approach to long-term policysimulations,butalsoallowsonetotakeintoaccounttherelationshipbetweenachangingeconomicenvironmentandtheimpactoftheTFA.

TableD.7showstheprincipalresultsfromthecombinedmacroeconomic and trade simulations in terms ofprojected average annual growth rates of GDP andexportsduetotheTFA,whichallowsacomparisonofresults across scenarios despite their different timehorizons. Depending on the implementation scenario(full,liberal,conservative)andtimehorizon(immediately,infiveorin10years),theTFAaddsbetween0.34and0.54percentonaveragetoglobaleconomicgrowthperyear,withthehigherfigurecorrespondingtoimmediate,full implementation of the TFA and the lower boundresultingfromaconservativeimplementationtargettobeachievedoverthenext15years.

This growth impact from the TFA implies that globalGDP would be between 5.4 and 8.7 per cent higherin 2030, which translates into an additional US$ 5.5to 8.9 trillion (in constant 2007 dollars) for the worldas a whole.16 The predicted effect of the TFA onannualexportgrowthamountstoatleastanadditional2 per cent expansion under any scenario, rangingfrom2.06percentforthemostconservativeandslow

Table D.6: Estimated increases in the number of destinations by product due to TFA implementation by level of development(percentage change)

Baseline New destinations


Developed 10.7 16.2


LDCs 14.1 21.3



Developed 10.7 16.2


LDCs 14.5 21.9


“Full” scenario

Developed 12.5 19.0


LDCs 39.2 59.3


Notes: Thenumbersindicatepercentagechangeinndpik(numberofexportdestinationsbyproduct)undertherelevantscenario.Thefirstcolumnpresents“Baseline”estimationswherethedependentvariable(thenumberofdestinationsexportedto)isconstructedusingtradedatafor2009.Thesecondcolumnusesonlythenumberofdestinationsthatwerenotservedbefore2008(“Newdestinations”)intheconstructionofthedependentvariable.Thisisintendedtoaddressreversecausalityconcerns,inotherwords,thepossibilitythatthenumberofdestinationstowhichacountryexportscauseschangestotradefacilitation.Byusingonlythenumberofnewdestinations,thispossibilityofreversecausationisreducedifnotentirelyeliminated.“Baseline”resultsarebasedoncolumn(3)ofAppendixTableD.2.“Newdestinations”resultsarebasedoncolumn(4)ofAppendixTableD.2.


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Box D.2: Main elements of MIRAGE

ThelatestversionoftheMIRAGE(ModellingInternationalRelationshipsinAppliedGeneralEquilibrium)model,usedhere,isdocumentedinFontagnéet al.(2013),theoriginalmodelbeingfullydescribedinBchiret al.(2002)andDecreuxandValin(2007).

Onthesupplyside,eachsectorinMIRAGEismodelledasarepresentativefirm,whichcombinesvalue-addedandintermediateconsumptioninfixedshares.Value-addedisaCES(“constantelasticityofsubstitution”)bundleof imperfectly substitutableprimary factors (capital, skilledandunskilled labour, landandnatural resources).Firms’demand forproduction factors isorganizedasaCESaggregationof land,natural resources,unskilledlabour,andabundleoftheremainingfactors.ThisbundleisanestedCESaggregateofskilledlabourandcapital(thatareconsideredasrelativelymorecomplementary).

MIRAGEassumesfullemploymentofprimaryfactors.Population,participationinthelabourmarketandhumancapitalevolveineachcountry(orregionoftheworldeconomy)accordingtothedemographicsembeddedinthemacroprojections.Thisdetermines the labour forceaswellas itsskillcomposition (skilled/unskilled).Skilledandunskilledlabourisperfectlymobileacrosssectors,butimmobilebetweencountries.Naturalresourcesaresector-specific,whilelandismobilebetweenagriculturalsectors.Naturalresourcesfortheminingsectorandtotallandforagriculturalsectorsaresetattheir2007levels:pricesadjustdemandtothisfixedsupply.Naturalresourcesforprimaryfossilfuelproductionsectorsarecalibratedasbeingconstant.Installedcapitalisassumedtobeimmobile(sector-specific),whileinvestmentsareallocatedacrosssectorsaccordingtotheirratesofreturn.

Theoverallstockofcapitalevolvesbycombiningcapitalformationandaconstantdepreciationrateofcapitalof6percentthatisthesameasinthelong-termgrowthmodels.Grossinvestmentisdeterminedbythecombinationofsavings (thesavings rate from thegrowthmodel,applied to thenational income)and thecurrentaccount.Finally,whiletotalinvestmentissavings-driven,itsallocationisdeterminedbytherateofreturnoninvestmentinthevariousactivities.Forsimplicity,andbecausereliabledataonforeigndirectinvestment(FDI)arelackingatcountryoforigin,hostandsectorallevels,internationalcapitalflowsonlyappearthroughthecurrentaccountimbalances,andarenotexplicitlymodelled.

Onthedemandside,arepresentativeconsumerfromeachcountry/regionmaximizesinstantaneousutilityunderabudgetconstraintandsavesapartofitsincome,determinedbysavingratesprojectedinthefirst-stepexercise.Expenditure isallocatedtocommoditiesandservicesaccordingtoaLES-CES(LinearExpenditureSystem–ConstantElasticityofSubstitution)function.Thisimpliesthat,aboveaminimumlevelofconsumptionofgoodsproducedbyeachsector,consumptionchoicesofgoodsproducedbydifferentsectorsaremadeaccordingtoaCESfunction.Thisrepresentationofpreferencesisflexibleenoughtodealwithcountriesatdifferentlevelsofdevelopment.Withineachsector,goodsaredifferentiatedbytheirorigin.AnestedCESfunctionallowsforaparticularstatusfordomesticproductsaccordingtotheArmingtonhypothesis(Armington,1969):consumers’and firms’ choices are biased towards domestic production, and therefore domestic and foreign goods areimperfectlysubstitutable,usingaCESspecification.TheArmingtonelasticitiesprovidedbytheGTAP(GlobalTradeAnalysisProject)databaseandestimatedbyHertelet al.(2007)areused.Totaldemandisbuiltfromfinalconsumption,intermediateconsumptionandinvestmentincapitalgoods.

DynamicsinMIRAGEareoftwokinds:thetotalfactorproductivity(TFP)iscalibratedinabaselineexercise,whileproductionfactorsdynamicsaresetexogenously.Botharebuilt inMIRAGEusingmacroeconomicprojectionsfromtheMaGEmodeldocumentedinFouréet al.(2013).

TFPisbasedonthecombinationofthreemechanisms.First,agriculturalproductivityisprojectedseparately,asdetailedinFontagnéet al.(2013).Second,a2percentagepointgrowthdifferencebetweenTFPinmanufacturesandservicesisassumed(asinvandenMensbrugghe(2005)).Third,theaggregatecountry-levelTFPiscalibratedin the baseline exercise in order to match both production factors and GDP projections from the aggregategrowthmodel,given theexogenousagriculturalproductivityand theproductivitygapbetweenmanufacturingandservices.DynamicsinMIRAGEareimplementedinasequentiallyrecursiveway:thatis,theequilibriumcanbesolvedsuccessivelyforeachperiod,giventheexogenoustrajectoryforsector-specificTFP,ifcalibratedasdescribedabove,aswellastheaccumulationofproductionfactors–savings,currentaccounts,activepopulationandskilllevel–comingfromthegrowthmodel.Simulationsextendupto2030.Finally,MIRAGEiscalibratedontheGTAPdatasetversion8.1,with2007asabaseyear.


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implementationplantoalmost2.75percentinthemostambitiouscase.

Interesting patterns emerge when these figures areseparatedoutfordevelopedanddevelopingcountriesrespectively.IntermsoftheTFA’scontributiontoaverageannualGDPgrowth,developingcountries’gainsexceedthoseofdevelopedcountries,butonlyunderascenarioof full or fairly ambitious (“liberal”) implementation. Inthecaseoffullandimmediateimplementation,theTFAwouldaugmentaverageeconomicgrowthindevelopingcountriesbyalmost0.9percentannually,whileitwouldaddabout0.25percent toGDPgrowth indevelopedcountries.If,ontheotherhand,implementationislessambitious (“conservative”), the picture is reversed,withdevelopingcountries’growthreceivingaboostofbarely0.25percentanddevelopedcountries’growthincreasingbyalmost0.5cent.

For both country groups, quick implementation of theTFAismorebeneficialintermsofitseconomicimpactcomparedtoanimplementationprocessstretchingoverseveral years, with the difference amounting to up to0.1 per cent of annual GDP growth. For exports, thepicture is similar, albeit more extreme. DevelopingcountriesreapmuchlargerexportgainsfromtheTFAbut only in the case of an ambitious implementationschedule. In such a scenario, developing countrieswould see their exports rise by over 3.5 per cent perannum, while developed countries’ exports wouldincrease by about 1.8 per cent per year owing toimplementation of the TFA. For the less ambitiousscenariosconsideredhere,developedcountries’exportincreases exceed those of developing countries, withthe former achieving an additional boost to exportsof between 2.7 and over 3 per cent per annum andexportsinthelatterincreasingbyonlybetweenabout1and2percent.

Inpreviousstudiesthe impactoftradefacilitationhasalsobeenexpressed in termsof theabsoluteamountadded to world GDP and exports. Adopting a similarapproach,thereportfindsthattheTFAhasthepotentialtoaddbetweenUS$345billionandUS$555billion(inconstant2007dollars)toglobalGDPperyear,withfaster and fuller implementation of the TFA resultinginGDPgainsthatarelargerbyoverUS$200billion.17Similarly,exportswouldincreasebybetweenUS$750billionandoverUS$1trillion.

Again,whenlookedatseparatelyfordifferentcountrygroups, these numbers underscore the high stakesfor developing countries in implementing the TFA:Figure D.8 shows the projected increases inexports over the next 15 years under the baselinemacroeconomic scenario for both developed anddeveloping countries (solid lines). Exports of theformerarecurrentlylargerthanthoseofthelatter,butdevelopingcountries’exportsareexpected toexceedthoseofthedevelopedcountriesbytheyear2026.Anambitious implementation of the TFA could advancethis“cross-over”pointtotheyear2018(dashedlines),i.e. developing countries’ exports would account formorethanhalfofworldtradealreadythreeyearsdowntheroadowingtoimplementationoftheTFAalone.

AscanbeseenfromTableD.1above,theestimatesoftheimpactoftheTFAareattheupperboundofexistingstudies,confirmingtheoft-quoted“US$1trillion”figurebyHufbauerandSchott(2013),evenwhenusingmoreprecise data on TFA indicators and implementationscenarios and a more elaborate methodology. Theresultspresentedherearelargerthan,forinstance,theones generated in another recent study by the WorldEconomicForum(WEF)(2013),whichfindsanoverallpositiveimpactoftradefacilitationofplus4.7percent

Table D.7: Addition to annual export and GDP growth due to TFA implementation, by scenario(annual percentage change)

Exports GDP


Immediate 2.09 0.36

5years 2.08 0.35

10years 2.06 0.34


Immediate 2.33 0.43

5years 2.31 0.41

10years 2.29 0.40

“Full” scenario

Immediate 2.73 0.54

5years 2.71 0.52

10years 2.67 0.50

Source: Fontagnéet al.(2015).

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forGDPintheirmostambitiousscenario,thatis,almostonepercent less than the2030GDPexpansion thatis obtained in the most conservative scenario in thisreport.18

As different studies are often difficult to compare,another possible point of reference for the TFAresults isadifferentpolicy reformbaselinewithin thesameCGEmodel.Thisreporthasthereforesimulateda hypothetical situation in which tariffs would becompletelyeliminated.Upuntil2030,thiswouldresultinan11percenthigherlevelinexportsanda0.8percent higher level of GDP. While the effect of tradefacilitationonexportsislargerthantheonefromtariffelimination (in fact, in the “static” WEF exercise, theyareofthesameorderofmagnitude),thedifferenceisparticularlystarkforGDP,wheretheimpactoftheTFAexceedstheoneoftariffsbyafactorofmorethan10(about6.5inWEF,2013).Thisis,ofcourse,relatedtothefactthattradefacilitationreducesefficiencylosses,i.e.savesoneconomicresourcesthatwouldotherwisehave been wasted. In contrast, tariff reduction oreliminationproducessmallerefficiencygainsbecausepartofitsimplyredistributesrevenuesfromgovernmenttoconsumers.19

Finally,thesimulationsprovideanumberofinsightsatthe sectoral and regional level. Sectors where GVCsare prominent, such as electronics and textiles andclothing, would be among those enjoying the biggestimpact of the TFA, but only if the TFA were to beimplementedpromptlyandwithallitsprovisions.Insuchacase,exports in thesesectorswould increaseatanadditionalaveragerateofalmost4percentperannum.At the regional level, the importance for developing

countries of ambitious TFA implementation is borneoutevenmoreforcefully,withSub-SaharanAfricaandpartsofAsiarealizingsignificant increases inexportsonlyunderafar-reachingimplementationscenario.Bythesametoken,somedevelopedcountriesmayrealizeslightly higher growth in certain export sectors undera more conservative scenario, as they would be lessexposedtocompetitionfromdevelopingcountrieswhenTFA-relatedtradecostreductionsarelesssubstantial.

Overall, the simulations confirm that the trade gainsfrom speedy and comprehensive implementationof the TFA are likely to be in the trillion dollar range,contributinguptoalmostonepercenttoannualGDPgrowthinsomecountries.Atthesametime,moreisatstake for certain countries, notably in the developingworld,thanforothers,andtheimpactoftheTFAmaybelargestinsomeofthemostdynamicsectorsiftheTFAis implemented soon and in full. As compared to thesubstantialbenefitsthattheTFAcandeliveraccordingto these projections, existing estimates of the costsof implementation reviewed in subsection E.2 appearto be relatively small, but may vary across countriesand necessitate different forms of implementationassistanceandsupport,aswillbefurtherdiscussedinSectionE.20

3. Differentiatedimpactoftradefacilitation

While the previous analysis has largely concentratedon the overall trade impact of implementing the TFA,further insights into its effects could be gleaned bylooking at specific sectors or players in international

Figure D.8: Projected exports 2015-30, by country group(billion constant 2007 US$)

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Source: Fontagnéet al.(2015).


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trade.Tradefacilitationcanboostbilateraltrade,exportdiversification, and economic welfare. Although tradefacilitationcanbeexpectedtohavesignificantpositiveeffects in aggregate terms, there is a question as tohow those gains are distributed across and withinnations.Amongthequestionsthatwillberaisedinthissubsectionarethefollowing:isthebeneficialimpactoftradefacilitationgoingtobeuniformacrossallgoodsorare certain products (e.g. fresh produce, intermediateinputs used in GVCs) going to benefit more? Couldtrade facilitation expand the mix of firms engaged ininternational trade, allowing small and medium-sizedenterprises(SMEs)toenter?WillimplementationoftheTFAalsobenefitthepoorwithincountries?

(a) Sectoraleffects

A major dimension of the cost of complex borderprocedureistimetoexport.Alltransactionsleavingorenteringacountrymustbeprocessedbytheircustomsagencies and this processing takes time. Customsclearance delays can be substantial and significantlyreduce trade. Even when national averages are low,there can be substantial variability of export time atthe transaction level.Volpeet al. (2015)reportexportprocessingtimesrangingbetweenoneand31daysforUruguay.

Longexporttimesdonotneedtobeaproblemifdemandis stable and delivery time is predictable. However, ifthere is uncertainty about future demand, long leadtime (the time between initiation and execution) iscostly even when the customer knows exactly whenthemerchandisewillarrive.Iffuturedemandhasbeenunderestimated, running out of stock has costs interms of foregone sales and the possibility of losingcustomers. If future demand has been overestimated,excesssupplymustbesoldatadiscount.Similarly,themore variable the delivery time, the larger the bufferstocks needed. Thus, even if the average lead timeis low, a high rate of variability can render a supplieruncompetitiveandcanbemoredamagingthanhavinglong,butpredictableleadtimes.

Longexporttimesoruncertaindeliverytimecanaffecttradedifferentlydependingonthenatureofthetradedgood.Timecosts, forexample, representasignificantobstacle to trading intermediate goods. Timelinessmatters for trade in intermediate goods because it isessential to themanagementof theproductionchain.Delaysindeliveryincreasethecostsofholdingstocks,impederapidresponsestochangesincustomers’ordersand limit the ability to rapidly detect, fix and replacedefective components. In support of this argument,using information on firms’ transport modal choicebetweenexportinggoodsbyairorocean,HummelsandSchaur(2013)estimateahighervalueoftimefortrade

inpartsandcomponentsthantotaltrade.Thatis,firmsare more willing to pay the premium for air shippingonintermediategoodstrade.SaslavskyandShepherd(2014) show that goods traded within GVCs tend tobemoresensitivetoimprovementsintradefacilitationthanother typesofgoods.Usingagravitymodelwithtrade in machinery parts and components as a proxyfor goods traded within GVCs and using the WorldBank’sLogisticsPerformanceIndicators,theyfindthatintra-GVC trade is more sensitive to improvements inlogistics performance – another important aspect oftradefacilitation–thantrade inothertypesofgoods.Indeed, the linkbetween logisticsperformance (tradefacilitation)andtradeinGVCproductsisabout50percentstrongerthanforothergoods.TradefacilitationisthusparticularlyimportantinthecaseofGVCs.

Long export times or uncertain delivery time canrepresent a significant obstacle to trade in time-sensitive goods (perishable goods in agriculture andgoodswithahighpropensity tobeexportedbyplaneinmanufacturing).

Djankovet al. (2010)find thatdelayshavea relativelygreaterimpactonexportsoftime-sensitiveagriculturaland manufacturing goods. They find that a 10 percent increase inexport time reducesexportsof time-sensitive agricultural products by about 3.5 per centand of time-sensitive manufacturing goods by morethan4percent,allelsebeingequal.

Focusing on African agricultural exports, Freund andRocha (2010) show that trade costs affect exportsof time-sensitive goods and time-insensitive goodsdifferently; timeismorecriticalfortradeinperishableproducts than for trade in preserved goods such astinned food. Most importantly, they find inland transittime(thetimeittakesforthemerchandisetobemovedfrom the principal city to the port of exit) rather thandocument time (the time it takes for an exporter tocomplete all documentation activities), custom time(the time necessary to realize the technical controlsof the merchandise) and port time (terminal handlingtimes)tohavethestrongestimpactonthecompositionof trade, preventing countries from exporting time-sensitive agricultural goods. They explain this findingonthebasisthattransittimesaremoreuncertain.

Focusingoncustomsdelays(thatis,thetimerequiredfor the customs to carry out verifications, excludingtime required for document, inland transport andportor airport handling), a recent study by Volpe et al.(2015) on Uruguay transactions finds that a 10 percent increase in customs delay results in a 3.8 percent decline in exports. But time matters particularlyfor foodand textileandclothing–goods thatquicklylosevaluebecause theyareperishableoraresubjecttorapidfashioncycles.

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In a broader sense, trade facilitation also includesimprovements of transport and communicationinfrastructures. Some studies show that the provisionoftheseinfrastructuresalsoaffectsthevolumeandthecomposition of trade. Yeaple and Golub (2007) showthat the increasedprovisionof infrastructure tends toraisetotalfactorproductivity(TFP)inmostsectors,withroad networks having a particularly strong effect onTFP.Specifically,theyshowthatroadconnectionraisestheTFPofmostindustries(food,textiles,wood,paper,chemicals, metals, machinery, electronics, transport),whereas improved telephone lines raise the TFP oftransportandscientific instruments industries,andanimprovedelectricalgeneratingcapacityraisestheTFPof food and chemicals industries. Fink et al. (2005)also show that a good quality telecommunicationsinfrastructure boosts trade in differentiated goods.They find that the importers of telecommunicationsprices have a substantially larger impact on trade indifferentiatedproducts than trade in referencepricedproductsandhomogenousproducts.

(b) GreaterparticipationofSMEsintrade

EventhoughthedefinitionofSMEsisdifferentamongcountries and institutions, and it is therefore difficultto measure their incidence across countries, existingestimates suggest that the contribution of SMEs totheworldeconomyissignificant.Onestudyestimatesthat SMEs account for more than 95 per cent offirms in most economies and a significant amount ofemployment – between 50 and 85 per cent of totalemployment(Kuwayamaet al.,2005).

Yet, SMEs account for a relatively small share ofinternationaltrade.Thisisbecausetherearefixedcoststo enter a foreign market that impinge particularly onthe profits of small firms. Firms decide whether or nottoenteracertainexportmarketbeforetheydecidehowmuch to export. Due to cross-border trade costs, onlya few firms in each country actually export. Exportingfirms tend tobe largerandmoreproductive thannon-exportingfirms.Thisisbecauseonlythemostproductivefirmsareabletomakeprofitwithstandingtheadditionalcosts associated with exporting. Less productive onescannotdoso,andonlyproduceforthedomesticmarket.

Burdensome trade procedures, customs and traderegulation are often mentioned as major obstaclesto SMEs’ export participation. Large firms, especiallymultinationalfirms,canbebetterequippedtodealwithacomplexenvironmentandtherefore,perceivethisasless relevantobstacle to trade.Using theWorldBankEnterpriseSurveydatabase,TableD.8showsthat thehighestpercentageoffirmsindicatingthatcustomsandtraderegulationsaremajororverysevereobstaclestotradeareindeedSMEs.

Implementation of the TFA can boost SMEs’participation in trade. As trade costs fall, more andmore less productive firms will start to export. Tradefacilitationcan,therefore,potentiallypromotetheentryof SMEs into export markets. The simple correlationbetweentheminimumsizeofexportingfirmsbycountryand export time support this possibility. As shown inFigureD.9, the lowest times toexport areassociatedwithsmallerexportingfirms.

An issue discussed in the literature is, however, theriskthatsmallfirmsmayactuallynotreapthepotentialbenefits of trade facilitation. The concern relates tohowgainsoccurringthroughtradefacilitatingreformsaredistributedwithinGVCs.Oneconcernisthatthesegains are mainly appropriated by the “lead” firms –generally large multinational firms with market powerover their suppliers. The issue as to whether small orlargefirmsgainmoreisthereforeanempiricalquestion.

Existing econometric studies on the impact of tradefacilitation on exports at the firm level support theview that it is not just large firms that benefit from

Table D.8: Evaluation of customs and trade regulations as obstacles to trade, by size of exporter

Type of firm Percentage of replies

Largefirm(100+) 16.9

Medium-sizedfirm(20-99) 18.4

Smallfirm(5-20) 19.4

Note: Figures indicate the percentage of firms that replied thatcustoms and trade regulations are a major or very severe obstacletotrade.

Source: WorldBankEnterpriseSurvey.

Figure D.9: Relationship between minimum export sale (per country) and time to export

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tradefacilitation,butalsosmallfirms.Inaddition,someaspects of trade facilitation can benefit small firmsmore than large firms. One pioneer study on AsiancountriesfindsthatSMEs(definedinthestudyasfirmswith less than 100 employees) benefit mainly fromimprovements in the “soft” part of trade facilitation(in their study identified with a more transparent andpredictable policy), whereas large firms benefit morefrom improvements in transport and informationtechnology infrastructures (Li and Wilson, 2009). Amore recentstudybyHoekmanandShepherd (2013)distinguishes four types of firms: micro (less than10employees)small(between10and50employees),medium (between 50 and 250 employees) and largefirms (greater than 250 employees). This study findsthat firms of all sizes benefit from a reduction in theaverage time taken to export a good, as recordedby each firm, and that this effect is independent of afirm’ssize.

However, these studies present several drawbacks.First, data quality is clearly an issue. They use theWorld Bank’s Enterprise Surveys (2013 standardizedversion),whichincludedataforfirmsin119developingcountriesand11manufacturingsectorsovertheperiod2006-11. Although the database has broad countrycoverage,dataaresubject tostrong limitations.Sincethey are collected by private contractors with noenforcementpower in thecaseofmisstatement, theymaypresentqualityissues.Inaddition,datacoverageissubjecttofirms’willingnesstoreply.Thiscontrastswiththesituationwhenfirm-levelsurveysareconductedbynational authorities (such as customs data). Second,the database only covers firms in the formal sectorwithatleastfiveemployees.Inthedevelopingcountrycontext,itthereforeprobablyover-sampleslargefirms.Third, although the World Bank Enterprise Surveysdatabase collects information at the firm level on anumber of firms’ characteristics, such as their size,exports,and their reported time toexport,somefirm-specificcharacteristicsaremissingwhenthefirmdoesnot export. For example, a firm that does not exporttypicallydoesnotreportitsexporttime.Itfollowsthatan analysis of the impact of export time on trade willtypically exclude non-exporting firms. But long timedelaysmaybetheveryreasonwhyfirmsdonotexport.By dropping non-exporting firms from the sample,results on the impact of export time on trade will bebiased.

To address these limitations, this report hascomplemented existing firm-level analysis with threeadditional studies. Their general finding is that sometypes of trade facilitation improvements profit smallfirms more than large firms. One study looks at theimpact of time to export on trade margins. Using theWorldBankEnterpriseSurveysdatabaseandthesame

specification as Hoekman and Shepherd (2013), thestudyshowsthatwhenallfirmsinacountryaretakenintoaccount (at leastall those replying to thesurvey)ratherthanjustthesub-sampleofexportingfirms,theeffect of improved trade facilitation (measured as alowernumberofdaystoexport)ontradedoesdependonafirm’ssize.21Micro,smallandmedium-sizedfirmsprofitmorethanlargefirmsfromlowertimetoexport.Smallerfirmsaremorelikelytoexportandwillincreasetheirexportsharesmorethan largefirms(HyoungminandPiermartini,2015).

Using customs data for Colombian firms in theagricultural sector anddataon transport costs to theport at the regional level, another study shows thatlowerdomestictransportcoststotheportparticularlybenefit small firms. Figure D.10 shows the plot ofColombian firms’ export size in regions with high(above75thpercentile)andlow(below25thpercentile)transport costs, respectively. Low transport costs areassociatedwithashifttotheleftofthedistribution:thatis, exporting firms tend to be smaller when transportcosts to the port are low. Given the importance thatthe agricultural sector has for employment and forpoverty reduction, this finding stresses the potentialopportunitythatimprovementsintradefacilitationmayrepresentforpovertyreduction(Espitiaet al.,2015).

The third study explores how the differential effectof trade facilitation reforms on small and large firmschange across types of reforms. Using the firm-levelcustoms data of French exports, and looking at theeffectsonafirm’sexportofimprovingtradefacilitation

Figure D.10: Size distribution of exporting Colombian firms in agriculture, by level of transport costs to port

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in the importing country rather than in the exportingcountry, Fontagné et al. (2015) show that, while ingeneral all exporting firms gain from improved tradefacilitationintheimportingcountry,therelativeeffectsonsmallandlargefirmsvarybytypeoftradefacilitationmeasure. The study analyses the effect of improvingtrade facilitation on several aspects of trade: thenumberofproductsexported,thevolumeofexportsatthefirmlevel,aswellasthenumberofexportingfirms.Inparticular,followingthestructureoftheOECDTFIs,thestudyexploresthedifferentialeffectofeighttypesoftradefacilitationmeasures.Theseare:

1. informationavailability–anindicatoroftransparencyofgovernmentrulesandregulations;

2. advanceruling–anindicatorofcertaintyoftradingcondition;

3. appealprocedure–ameasureofqualityofjudicialinstitutions;

4. feesandcharges–anindexoftransparencyanditspecuniaryeffectsontrading;

5. formalities and documents – an index of thecomplexity of document requirements and time totrade;

6. formalitiesandautomation–anindexoftheuseofinformationtechnologybythepublicadministration;

7. formalitiesprocedures–anindexofefficiencyanduser-friendlinessofcontrolsattheborder;

8. border agency (internal and external) – an indexof coordination among different agencies withina country involved with trade and an index ofintegrationwithneighbouringcountries.

The study finds that small firms profit relativelymore when trade facilitation improvements relate toinformation availability, advance ruling and appealprocedures. Large firms profit relatively more whenthe importing countries facilitation reforms relate toformalities(documents,automationandprocedures).

(c) Thepooralsogainfromtradefacilitation

It has been shown so far that trade facilitationmeasures canaffect countriesdifferently.Developingcountrieshavepotentiallymoretogainfromimprovingtrade facilitation because they face higher tradefacilitation-relatedbarriers,becausetheytendtohaveacomparativeadvantageinagricultureandperishablegoods, which are often more time-sensitive than

manufacturing goods,22 and because their firms tendtobesmall.

Trade facilitation canalsohave redistributiveeffectswithin a country. Although research on the effectsof trade facilitation on the poor within a country islimited,existingstudiessuggestthattradefacilitationmay be particularly beneficial to the poor. Nguyen(2013)findsthatcountriesrequiringalargenumberofdocumentsforimportsandmoretimeforimportsandexportsaremorelikelytohaveahigherpovertyrate.At a poverty line of US$ 1.25 PPP (i.e. purchasingpower parity) per day, one additional document forimports is associated with a 0.77 percentage pointincreaseinthepovertyrate.Oneadditionaldayinthetimeneededforexportsorimportsisassociatedwithan increase of approximately 0.5 percentage pointsin the poverty rate.23 Using household data for theRepublic of Moldova in 2002, Porto (2005) showsthat the removal of informal barriers (including thecostofdoingbusiness)inthiscountrywouldincreasethe average real income of Moldovan families. In hissimulations, he models informal trade barriers asexporttaxes.TheRepublicofMoldovamainlyexportsprocessed agricultural products, and the majorityof the population works in the fields, providingagricultural inputs to manufacturing firms, or in agroand food-processing industries. Thus, a removal ofinformal barriers increases domestic food prices, totheadvantageof thoseworking in the food industry.Poverty declines, lifting between 100,000 and180,000Moldovancitizensoutofpoverty.

Ingeneral,onecanarguethatcumbersomecustomsprocedure–delaysanduncertaintyoftimelydelivery–maymattermost for the ruralpoorbecauseof theproducts they export, which tend to be perishable.Therefore, improvements in trade facilitation can bea powerful tool to raise the living standards of poorhouseholdsworkinginexport-oriented,time-sensitiveagricultural products in developing countries. Inaddition, trade facilitation also entails regulatorysimplification–e.g.consolidatingmultipledocumentsrequired for import/export clearance. Thesemeasures can lower the incidence of corruption andsignificantlyenhancetheefficiencyofcontrolsattheborder (e.g., through risk management techniquesand enhanced regional border coordination). This,in turn, has significant potential benefits for small/informal/women traders, who often do not have thenecessarycapacityorresourcestodealwithcomplexdocumentation requirements. Also, they do not havethe financial means to pay trade-related fees andchargesandmaybesubjecttoadditionalinspectionsattheborder(duetothelackofrichtrackrecordswithcustomsauthorities).24


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4. Inducedeffectsfromimplementingtradefacilitation

(a) Attractingmoreforeigndirectinvestment

The relationship between trade facilitation and FDIis, in principle, ambiguous. Trade facilitation could beseen by foreign investors as a proxy for a country’sinvestment climate,whichwould thusmeanmoreFDIfor the country if it improves trade facilitation (Dollaret al.,2006).AccordingtoEngman(2009), inefficienttrade procedures result in higher trade costs whichare then factored in thecost-benefitanalysisusedbycompaniestomakeforeigninvestmentdecisions.Somelimited empirical evidence (Olofsdotter and Persson,2013; Portugal-Perez and Wilson, 2015) suggeststhat countries with more inefficient trade proceduresreceivelessFDI.

The size of the FDI-receiving economy affects thenatureof theFDI it receives(horizontalorvertical)aswellas the relationshipbetween trade facilitationandFDI.HorizontalFDIispositivelyaffectedbymarketsizeand, as shown by Kinda (2014), by the pervasivenessof trade regulations. In this case, trade facilitation byreducingunnecessarytraderegulationswoulddecreasethe probability of a firm choosing FDI over exports(Persson, 2012; Olofsdotter and Persson, 2013).Vertical FDI and trade are complementary activities,arising(amongothers)fromcomparativeadvantage.Asmuchasitincreasestrade,tradefacilitationwouldthusincreasetheprobabilityofverticalFDI(Persson,2012).

Since the type of FDI flowing into poor countries ismostlyvertical,onewouldexpecttofindsomeevidenceofapositiverelationshipbetweentradefacilitationandFDI at lower levels of GDP.25 The relationship shouldbecome progressively weaker and may even turnnegative for large economies, where a relevant partofinwardFDIisofthehorizontaltype.Thereislimitedempiricalevidencesuggestingthatcountrieswithmoreinefficient tradeprocedures receive lessFDIwith theeffect being smaller in economically large countries(Olofsdotter and Persson, 2013). The explanation isthat larger economies attract more market-seekinginvestments, which in turn are expected to be lesssensitivetotradeprocedures.

To shed new light on the question of whether tradefacilitationleadstogreaterinwardFDI,andwhetherthiseffectdependsonthesizeoftheFDI-receivingeconomy,aformaloreconometrictestwasconducted.TheresultsshowninBoxD.3confirmthattherelationshipbetweentrade facilitation and FDI is conditional on the size oftheeconomy.Biggermarket size inducesmultinationalfirmstojumptheadditionaltradecostsduetopoortradefacilitation,andinvestdirectlyinacountrytogetmarketaccess.Inotherwords,biggermarketsmayattractmoreforeigninvestmentifthelackoftradefacilitationactsasabarriertotrade.However,insufficienttradefacilitationisexpectedtodiscourageFDIinsmallereconomies.Thisisbecausetheirdomesticmarketsarenotlargeenoughtomitigate theadditionalcostdue to insufficient tradefacilitation.

As FDI corresponds to higher domestic investment indeveloping countries and is resilient to financial crises

Box D.3: Trade facilitation, FDI and market size

ToexaminewhethertradefacilitationleadstogreaterinwardFDIandwhetherthiseffectdependsonthesizeoftheFDI-receivingeconomy,thefollowingeconometricspecificationwasestimatedbyordinaryleastsquares(OLS).

Ln(inwardFDIit)=ai +θt +β1TFit +β2 (TFit * Ln GDPit )+β3 Ln GDPit +εit (1)

Thedatausedintheestimationcovers141countriesoveratenyearperiod(2004-13).Thedependentvariableisthelogof inwardFDI incountry iattime t.Themainexplanatoryvariableof interest istheinteractiontermbetween trade facilitation and market size, proxied by GDP. Two different measures of trade facilitation areused:thenumberofdocumentstoimportandthetimetoimport,bothfromtheWorldBank’s“DoingBusiness”dataset.26TheresultsarereportedinAppendixTableD.5.

Foragivenleveloftradefacilitation,marketsizeispositivelycorrelatedwithinwardFDI.Conversely,foragivenlevelofmarketsize,tradefacilitationisnegativelycorrelatedwithinwardFDI.Theinteractionbetweenthetwovariables is positive and statistically significant. The negative effects of trade facilitation on inward FDI onlyoccurfor lowlevelsofGDP. Inparticular,fortheestimationwiththenumberofdocumentsto import(Column(1)),thethresholdofGDPafterwhichoneadditionaldocumenttoimportstartshavingapositiveeffectonGDPisestimatedatUS$1.1billion–which isslightlybelowthe25thpercentileofthesampledistributionofGDP.Fortheestimationofthenumberofdaystoimport,thisthresholdrisestoUS$8.9billion–whichisaroundthe70thpercentileof thesampledistributionofGDP.Formarketsizeabovethesethresholds, tradefacilitation ispositivelycorrelatedwithinwardFDI.

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(BosworthandCollins,1999;LounganiandRazin,2001),thereseemstobeaparticularcaseforimprovingtradefacilitation in smaller economies. Moreover, the resultspresented above should allay the fear that improvinginefficientcustomssystemsmayputadditionaldemandsonthelimitedresourcesofdevelopingcountries(OECD,2005). The resource-enhancing capacity of tradefacilitation, through increasedcapital inflow,couldhelpinmitigatingthecostofinvestingresourcesincustoms-relatedinfrastructure.

(b) Bettercollectionofgovernmentrevenues

Revenue collected by customs and other borderagencies remainsan important sourceofgovernmentincomefordevelopingcountriesandLDCs.AccordingtoaWorldCustomsOrganization(WCO)surveyon34LDCs(WCO,2014),thetotalofdutiesandothertaxescollected at the border still accounts for 45 per centof government tax revenue, of which 19 per cent arecustomsduties.

Giventhehighrelianceofsomedevelopingcountriesonborderrevenues,goodcustomsadministrationisakeyobjective.AccordingtotheOECD(MoïséandSorescu,2013),inefficientborderproceduresmaybethesourceof large foregone revenues in African countries ofup to 5 per cent of GDP. Trade facilitation-relatedreforms designed and implemented in conformitywith international principles are consistent with theobjective of maximizing customs revenues. Engman(2009) mentions cases in which the introduction ofmodern single-window automation systems (e.g. inGhana and Singapore) helped substantially increasecustomsrevenue.Actually, revenueenhancementmaybe one of the main motives for trade facilitation andcustomsreforms.Theprinciplesfor“effectivecustomsadministrationmodernization”27promotedbytheWCOaimtofostervoluntarycompliance,reducetransactioncostsand increaserevenue(Yasui,2010;Zaki,2014).In this framework, theWCO(2014)assesses that theTFAcould improvecustomsrevenue inthreedifferentways: by increasing trade flows, by improving traders’compliance,andbyhelping to recover revenue lossesfromcustomsfraud.

With respect to increasing trade flows, at any givenlevelof trade taxesandVAT rates, customs revenuesare likely to increase as cross-border merchandisetrade expands – the main variable being the actualexpansion of trade due to TFA reform. Greater tradeshould therefore increase the taxbase forconcernedgovernments(seesubsectionD.2).

With respect to improving traders’ compliance, forany given level of imports, trade facilitation reforms

wouldimprovetaxreturnsbyenablingamoreeffectivecollection of duties and taxes through increasedcompliance. Lesser and Moisé-Leeman (2009) showthatbysimplifyingcustomsprocedures,tradefacilitationencourages compliance, reduces informal trade andincreasesthelikelihoodofdutiesbeingpaid.TheWCOprovides examples of simplifying measures having apositive impact on administrative and tax compliance,suchasthesystemofauthorizedoperators,whichtrustsregisteredtradersandtheir representativestocomplyon a voluntary, declarative basis, but strengthenspenalties against false declaration. The system isdescribed to have fostered tax compliance (WCO,2014). The New Zealand Customs Service (2014)reported that97.3percentof imports transactions in2013weredeemedcompliantwithverylimitedphysicalordocumentaryinspectionssinceithasintroducedthissystem.

Withrespecttohelpingtorecoverrevenuelossesfromcustoms fraud, trade facilitation should improve tradetaxreceiptsthroughbetterdetectionofcustomsfraudand corruption. Customs fraud may take many forms,including mis-invoicing, non-filling of declarations,voluntary misclassification, transit and origin fraud.Regardless of its form, customs fraud can havesignificant economic consequences on developingeconomies when government revenues are reliant onborder taxes. For example, Global Financial Integrity(Kar and Spanjers, 2014) estimated the potentialcustomsannualtaxlossduetomis-invoicingatbetween7 and 13 per cent of the government revenue in fiveeconomies(Ghana,Kenya,Mozambique,TanzaniaandUganda). The Post-Clearance Audit process (PCA),in particular, can contribute to reducing duty and taxevasion. For instance, following the establishment ofPCA, Chinese Taipei customs were able to recovermore than US$ 26 million in revenue in the form ofevaded duties and fines in the fiscal year 2010-11,that is,10timesthecostofPCAimplementation.28 Inaddition,thelackoftransparencyorevenavailabilityoftraderulescreatesopportunitiesforthe inappropriateexercise of official discretion, for collusion betweencustomsofficialsandtraderswhereagentsextractrentfromtraders(ADBandUNESCAP,2013).

Djankov and Sequeira (2009) showed there was anegative correlation between the payment of bribesandthecollectionoftariffrevenue.Revenueleakagesthrough corruption in customs administrations canbe expected to decline as procedures and clearanceprocess become more transparent and simplified(Ferreira et al., 2007). In an attempt to penalizecorruptionandpoorpracticesobserved, the “integrityaction plan” introduced by Cameroon’s customs isworth mentioning. Building on previous reforms,Camerooncustoms implemented in2010asystemof


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performance contracts between customs leaders andfrontline officers. Since then revenue collection hasincreased – revenues per container increased by 12per cent between 2009 and 2010 — and clearancetimeshavebeenshortened(Cantens,2010).

Concernshavebeenexpressedregardinganypossiblenegative effects of trade facilitation measures ondeveloping countries’ revenue. According to WCO(2014), any negative impact should be negligible, oroutweighedby the increase in revenue resulting fromthe uniform implementation of the TFA. The potentialfor revenue lossesmaycomefromthe introductionofade minimissystem inwhichnodutiesandtaxeswillbe collected for shipments whose value falls below acertainthreshold.Still,therevenueimpactwoulddependon the threshold value and on the implementation ofthemeasure.Toalleviatethisconcern,theTFAactually

allows its signatories to determine their respectivethreshold amount. To further diminish the potentialfor revenue loss, the WCO (2014) recommends thatgovernments in developing countries first implementthe revenue-enhancing measures of the TFA, underits special and differential treatment provisions, andthus, only when the tax base is firmed up, implementmeasures that could pose a threat to establishedrevenue collection channels, or cost extra to beimplementedproperly. Inconclusion,customsreforms,trade facilitation and revenue collection should beregardedascomplementaryobjectives.This “possibletrinity” is further illustrated inBoxD.4,which focuseson the role of the Automated System for CustomsData (ASYCUDA) programme of the United NationsConference on Trade and Development (UNCTAD)system in trade facilitationand its impactoncustomsrevenuecollection.

Box D.4: ASYCUDA and the impact of customs performance measurement

Customs authorities are essential for facilitating trade flows, improving compliance and minimizing fraud.However,despitetheirkeyroleforgovernmenttaxcollection,manycustomsadministrationsfallshortofbeingefficientandeffective.

Information communication technology (ICT) and the automation of customs management has been, andremains, one of the most important tools to facilitate trade and achieve improvements in timeliness, cost,reliability, compliance, and revenue collection (OECD, 2005). The example of ASYCUDA is illustrative. Thelatestversion,ASYCUDAWorld,allowstraderstohandlemostdocumentsonline,and interactatallstages intheprocess,includingrequirementsrelatedtopre-shipment,clearanceprocessandchecking,upuntilrelease.Forgovernments, theautomatedrevenuecollectionprocessensuresthatcustomsdutiesandothertaxesareaccountedforinatimelymanner.Implementedin94countriesworldwide–including40LDCs–ithasbecomethereferenceforcustomscomputerizationindevelopingcountries.

Inadditiontotheevidentbenefitsofcomputerizedsystems,theunderlyingdatabasesrecordeachtransactionbycustomsagentsandallowfordetailedperformancemeasuresinordertoenhanceeffectiveness,complianceandrevenuecollection.OneofthefirstexploitingthispotentialwastheCamerooncustoms,whichdecidedtocollaborateanddiagnoseinefficiencieswiththehelpofASYCUDAdata,incooperationwiththeWorldBankandWCO.TheCamerooncustomsreformfocusedprimarilyondatamining(acomputationalprocessofextractinguseful knowledge from large data sets) and addressing performance issues by signing specific contractsbetweencustomsheadquartersandfrontlineofficials(Cantens,2010).

Severalquantifiableindicatorsshowedasignificantimpactonperformance:oneindicatorrelatedtoprocessingtimesshowedthatinspectorstendedtofirstassessadeclarationbutthentodecidetodelayfurtherclearanceon grounds of document controls (the so called “yellow channel”). After implementation of the performancemeasures,delayedentryofcustomsassessmentsfellonaverageby49percentintheobservedcustomsoffices(seeTableD.9,fromBilangnaandDjeuwo(2012)).

Other measures showed similar improvements after implementing the performance measures: the share ofdeclarations registered and assessed on the same day increased to above 90 per cent, and revenues fromdisputed claims – an area where corruption had been widespread – increased by 17 per cent in the largercustomsofficesandby322percentinthesmallercustomsoffices(Cantens,2010).Theexampleofperformancemeasurement at Cameroon’s customs shows how collection and benchmarking of indicators can reduce theasymmetryofinformationbetweencustomsheadofficesandfieldofficers,andhelptofightbadpracticesandcorruption.

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(c) Reductionintrade-relatedcorruption

This subsection will consider the impact of tradefacilitation on various forms of rent-seeking, inparticular trade-related corruption. Economic theorypurports two mechanisms through which corruptionaffects the economy at large. The “corruption asgrease” theoryargues that ifbribesaresetaccordingto the time preferences of private agents, corruptioncan be efficiency-enhancing, reducing delays forpublicservices (Leff,1964;Lui,1985).Analternativeview suggests that bribes are set according to thestrategicpreferenceofthebureaucrats,representinga“distortionarytransfertax”(Krueger,1974;ShleiferandVishny,1997;Rose-Ackerman,1978).

The literature on corruption and trade has arguedthatcorruption in tradingnetworks increasesthecostof trade (Yang,2008;ClarkeandXu,2004;AbeandWilson, 2008; Djankov and Sequeira, 2009). Theeffect of corruption, however, is likely to depend ontheinstitutionalsettingofacountry.Forexample,DuttandTraca (2010)show thatwhilecorruption impedestrade in a low-tariff environment, it could have trade-enhancingeffectswhentariffsarehigh.

Corruption and other illegal activities are intrinsicallydifficult to measure in a reliable way. An approachcommonly used in the trade literature (Fisman andWei,2004; Javorcik andNarciso,2008;RotunnoandVézina, 2012) is to look at differences between themerchandise declared by exporting countries (calledFOB or free-on-board) and the same merchandisedeclaredby the importingcountry (calledCIForcost-insurance-freight). Carrère and Grigoriou (2014)

investigate whether this “mirror data” method canindeed help to measure “informal” international trade.Inparticular, theirempiricalstrategyconsidersorphanimports, i.e. incoming flows recorded by importingcountries that have no corresponding export flows.UsingtheWorldBank’sCountryPolicyandInstitutionalAssessment “transparency, accountability, andcorruption in the public sector” rating to measurecorruption, and controlling for a number of countrycharacteristics, they find that corruption indeedincreasestheprobabilityofobservingorphanimports.Theyalsofindthatmorecorruptioniscorrelatedwithahigherratioofreportedimportsoverreportedexports(CIF/FOBratio),suggestingthatcorruptionmayindeedbe used by importers to fraudulently under-reportincomingflowsofmerchandise.

Trade-related corruption is positively affectedby thetime spent to clear customs procedures. Shepherd(2010) shows that a 10 per cent increase in tradetimeleadstoa14.5percentfallinbilateraltradeinalow-corruptioncountry,and toa15.3percent fall ina countrywithhigh levelsof corruption.By reducingthetimerequiredtomovegoodsacrossborders,tradefacilitation is therefore a useful instrument for anti-corruptioneffortsattheborder.Evidenceofapositivecorrelation between trade facilitation (measured bythe OECD TFIs) and two measures of transparency(customs transparency and time predictability ofimport procedures) is provided in Figure D.11.29 Thispositive correlation is significant after conditioningforGDPpercapita,asshowninAppendixTableD.6.Econometric evidence of a causal effect of tradefacilitationoncorruptionhas,however,remainedquiteelusive.

Box D.4: ASYCUDA and the impact of customs performance measurement (continued)

Table D.9: Delayed entry of customs assessments

Number of entries Decrease from 2009 to 2011

Customs office 2009 2010 2011 Number Per cent

DoualaInternationalairport 2,605 2,469 2,162 -443 -17

DoualaPortI 2,854 2,357 487 -2,367 -83

DoualaPortV 1,876 1,519 751 -1,125 -60

Doualaexternalwarehouse 875 781 787 -88 -10

Total 8,210 7,126 4,187 -4,023 -49

Source: BilangnaandDjeuwo(2012).

Basedonexperiences inCameroonand to furtherpromotecustoms integrityandperformance, theASYCUDASYstem for Performance Management (ASYPM) module was developed in 2013 by UNCTAD and the WCO.Themodulemeasuresandtrackstheperformanceof individualofficersandfacilitatesdataminingforcustomsmanagersbyprovidingup to29 indicatorsbyempiricalevidenceandobjectivemeasurement (UNCTAD,2014).ThesystemhasrecentlybeenimplementedbyLiberia’scustoms;althoughitistooearlytoshowsignificantresults,theperformanceindicatorsalreadymanagedtoidentifysomeinefficientpractices(Bolognesiet al.,2014).


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Some evidence that custom agencies that controlcorruption are better able to avoid import fraud isprovided by Jean and Mitaritonna (2010). Using thegap between the declarations of trading partners asa proxy for tariff evasion, they evaluate the effect ofthreespecifictradefacilitationmeasures:pre-shipmentinspections,the1979AgreementonImplementationofArticle VII of the GATT (also known as the CustomsValuation Agreement) and the ASYCUDA system. Allthesetransparency-enhancingmeasuresdecreasethediscretion of customs officials when reporting tradeflows.Theauthorsfindnostatisticallysignificanteffectofpre-shipmentinspectionsoncorruptionintheoverallsample. Pre-shipment inspections, however, tend tobe more effective for countries with relatively betterinstitutions.

Thisambiguousneteffectofpre-shipmentinspectionsonfraudisconsistentwiththefindingsofAnsonet al.(2006),whoshowgreatlydifferenteffectsdependingonthecountryconsidered.InthecaseoftheCustomsValuation Agreement, the harmonization of valuationpractices is found to have lowered the tariff evasionelasticity in the ratifying countries under analysis (12countries between 2001 and 2004), although theresult is not very robust. There is more encouragingnews in the case of ASYCUDA. The improvement inaccuracyandefficiencyofcustomclearancegenerateda substantial reduction in the tariff evasion elasticitywiththeestimationresultsappearingtobequiterobust.

World-wide import revenue losses due to custom-related corruption are estimated to amount to US$ 2billion (Michaelet al.,2012).A thoroughdiscussionof

how trade facilitation can lead to better collection ofgovernmentrevenuesispresentedinsubsectionD.4(b).

Summing up, the literature has shown that customagenciesthatcontrolcorruptionarebetterabletoavoidimport fraud. Moreover, the incentives to engage infraudulentpracticesattheborderarelarger,thelongerthetradingtimes.Tradefacilitationhasthepotentialtoreducetrade-relatedcorruptionbothdirectly(reducingthe scope for import fraud) and indirectly (shorteningtradingtimes).

5. Conclusions

ThissectionhasdocumentedhowdevelopingcountrieshavealottogainfromimplementationoftheTFA.

First, improving trade facilitation can give a morepowerful boost to developing countries exportsbecause they have high trade costs, a large part ofwhich are due to lack of trade facilitation. Delays atcustoms and cumbersome procedures are far morefrequently encountered in developing countries andLDCs. The gravity- and CGE-based simulations inthis section accordingly indicate large potential gainsfrom trade facilitation reform fordevelopingcountriesand LDCs in terms of increased export flows, exportdiversificationandhigherGDPgrowth.

The impact of trade facilitation may depend on thesectoral composition of traded goods. The trade-hindering effect of lengthy procedures for exportingand importing is particularly acute for time-sensitiveproducts.Anumberofstudiesshowthatfreshproduce

Figure D.11: Correlation between TFIs, customs transparency and time predictability of import procedures

Customs transparency index Fitted values Time predictability ofimport procedures

Fitted values

0

0.4

0.2

0.6

0.8

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0.20 0.4 0.6 0.8 1 1.2 1.4 1.6 1.8 2Average OECD TFI

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0.20 0.4 0.6 0.8 1 1.2 1.4 1.6 1.8 2Average OECD TFI

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Tim

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andperishablegoods tend tobemore time-sensitive.Thisimpliesthatdevelopingcountries(especiallysub-Saharancountries)thathaveacomparativeadvantagein food exports are likely to gain the most fromimplementing trade facilitation. Other studies showthat sectors characterized by rapid changes in taste(fashion), constant innovation (electronic products)and just-in-time production (intermediate goods insupplychains)arealsotime-sensitive.Inthiscase,too,developingcountriesstandtoreaplargebenefits.

Another dimension of importance for traders is thecertainty of delivery. Uncertainty in delivery times,particularly in value chains, increases trade costs.Since uncertainty in delivery time tends to be higherin lower-incomecountries,especiallytransitcountries,improvements in trade facilitation which result inincreased certainty of delivery time are likely to havethelargestimpactinlow-incomecountries.Importantly,through this channel, many low-income countries arelikelytoseegreaterparticipationinglobalvaluechains.

Anotherchannelthroughwhichtradefacilitationmayaffect countries differently is the size distributionof their enterprises. As discussed in this section,empiricalevidencesuggeststhatsmallfirms’exportstend to be more responsive to trade facilitation.Therefore, to the extent that some countries have alargerSMEsectortheymaygainrelativelymorefromtradefacilitation.

Two more channels, highlighted in this section, alsopoint to relatively largegainsfordevelopingcountriesfromimplementingtradefacilitationreform.First,tradefacilitation increases FDI in small economies – whichare relatively more dependent than large ones onthis channel for investment. Second, trade facilitationreformshelp to increasegovernment revenuesand toreducecustomsfraudandcorruption.Thisisimportantinthosedevelopingcountrieswherecustomsrevenuesrepresent a relatively large fraction of governmentrevenues and that are relatively more vulnerable torent-seekingattheborder.

Endnotes1 Althoughthegravitymodellongpredatedthepaperby

AndersonandvanWincoop(2003),theirseminalpapertransformeditintothemodernworkhorseofempiricaltradeeconomics.Startingfromatheoreticalmodelofintra-industrytrade,theywereabletoderivethegravitymodelforthebilateraltradebetweenanytwocountries,wherethetradebetweenthemdependsontheirgrossdomesticproducts(GDPs)andtheirrelativetradecosts.Inparticular,theyshowedthatforanytwocountriesAandB,A’simportsfromBdependnotonlyontheirbilateraltradecosts,butalsoontheoveralllevelofbarriersthatexportsofcountryBfaceintherestoftheworld,andtheoveralllevelofrestrictiontoimportsthatcountryAimposesontherestoftheworld(theso-calledmultilateralresistanceterms).

2 ThedatabaseontradecostspreparedbyArviset al.(2013)ismadeupofbilateraltradecostsforeachpairofcountriesinthesample:onereporterandonepartnercountry.Thefigures,computedaccordingtothemethodologyoutlinedinBoxD.1,arethemeancostsinbothdirections.Tocomputetheaveragetradecostsfordevelopingcountriesin2010,onlyasubsetofthedatasetwithdevelopingcountryreporterswasused.Thisway,theestimateaccountsforthecosteachdevelopingcountryfaces,withallcountriesinthesample.Theyear2010waschoseninsteadofamorerecentyearbecauseithadafarlargernumberofobservations.

3 Forthisfigure,tradecostsarecalculatedaccordingtothemethoddescribedinBoxD.1.Foreachcountry,therestoftheworldisconsideredtobeallothercountriesforwhichbilateralcostestimatesareavailable.DevelopingcountriesincludeG-20developing,otherdevelopingandleast-developedcountries.

4 TheArviset al.(2013)databaseontradecostssuppliesfiguresforoveralltrade,manufacturingandagriculture.However,therearemanymissingobservations.Tocomparecostsinagricultureandmanufacturing,onlythoseobservationswherethereweredataforbothsectorswere

included.Forthisanalysis,theyear2012waschosenbothbecauseitwasrecentandbecauseithadarelativelylargenumberofobservations.

5 ThecalculationsbyHufbauerandSchott(2013)usetheestimatesfromtheworkbyPortugal-PerezandWilson(2012).Usingagravitymodel,Portugal-PerezandWilsonconcludethattradefacilitationreformsimprovetheexportperformanceofdevelopingcountries.However,theydonotprovideestimatesoftheincreaseintradearisingfromthesereforms.Instead,theycalculatethead valoremtariffliberalizationthatwouldgeneratethesameincreaseintradeastradefacilitation.

6 ForadescriptionofOECDTFIsandthesub-components,seesubsectionC.4andTableC.4inparticular.

7 HS6isaHarmonizedSystemcode.TheWorldCustomsOrganization’sHarmonizedSystem(HS)usescodenumberstodefineproducts.Acodewithalownumberofdigitsdefinesbroadcategoriesofproducts;additionaldigitsindicatesub-divisionsintomoredetaileddefinitions.Six-digitcodesarethemostdetaileddefinitionsthatareusedasstandard.

8 PertheTFA,Articles14,“CategoryAcontainsprovisionsthatadevelopingcountryMemberoraleast-developedcountryMemberdesignatesforimplementationuponentryintoforceofthisAgreement,orinthecaseofaleast-developedcountryMemberwithinoneyearafterentryintoforce”.

9 Thelistof52developingeconomiesconsistsof:Albania;Botswana;Brazil;BruneiDarussalam;Chile;China;ChineseTaipei;Colombia;Congo;CostaRica;Côted’Ivoire;DominicanRepublic;Ecuador;Egypt;ElSalvador;Gabon;Guatemala;Honduras;HongKong,China;Indonesia;Israel;Jordan;RepublicofKorea;StateofKuwait;KyrgyzRepublic;Macao,China;Malaysia;Mauritius;Mexico;RepublicofMoldova;Mongolia;Montenegro;Morocco;Nicaragua;Nigeria;Oman;Panama;Paraguay;Peru;Philippines;Qatar;


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KingdomofSaudiArabia;Senegal;Singapore;SriLanka;Tajikistan;Thailand;Tunisia;Turkey;Ukraine;Uruguay;andVietNam.

10 AppendixTableD.1showstheresultsofpseudo-Poissonmaximumlikelihoodestimation.

11 First,regressionswithsplinesand,inanalternativespecification,withfractionalpolynomialswereestimated.Second,thecoefficientontradefacilitationwasestimatedseparatelyforthosecountriesabovetheregional/globalmedian.Thiscoefficientwasthenappliedtothe“reforming”countriesthatmovetotheregional/globalmedian.Inthefirstcase,nosignificantresultswereobtained.Inthesecondcase,theresultsweresimilartotheonespresentedinAppendixTableD.1,withslightlylargercoefficients.

12 IntheCEPIIBACI(theinternationaltradedatabaseoftheCentre d’études et d’informations internationales)datasetused,however,themaximumnumberofHS6sub-headingsislower,andequalto4,795.

13 Itisimportanttonotethatresultsofcounterfactualanalysishavetobetakencautiously,becausetheyareonlyasgoodastheunderlyingeconometricmodel.Althoughthereporthastakencaretoaddressomittedvariableandreversecausalitybiases,itcannotcontrolforeverypossiblecountry-specificvariablecorrelatedwithtradefacilitationandonecannotcompletelyexcludetheendogenousco-determinationoftradeoutcomesandtradefacilitationinfrastructure.

14 ResultsaggregatedbyregionareavailableinAppendixTablesD.3andD.4.

15 TradecostestimatesbytheOECDfollowthemethodologysetoutinChenandNovy(2009)andthetradecostreductionsduetotheTFAarethenbilateralizedasfurtherexplainedinFontagnéet al.(2015).

16 BesidesincreasesinGDP,whichmaybeconsideredareasonablytellingindicatorofeconomicgains,CGEmodelsalsoallowforthecalculationofwelfareimpacts.Inthepresentexercise,theseareinthesameballpark,rangingfrom4.6to6.6percenthigherlevelsofwelfarefortheworldasawholeby2030.Ofcourse,itmustbenotedthatthetypeofwelfaremeasurecommonlyusedinthesemodels,namelytheso-called“equivalentvariation”inrealincome–i.e.theincreaseinagents’incomethatwouldhavebeennecessarytoobtainthenewlevelofagents’utility,withpricesremainingunchanged–isinsufficientinitselfinthatitdoesnottakeintoaccountarangeofotherfactorsaffectingwelfare,suchasenvironmentalexternalitiesorincomedisparities.

17 Theabsolute,annualizedincreasesforGDPandexportvolumeswerecalculatedbysubtractingtheactual2014figurefromthesimulatedfigurefortheyear2030(simulationtimehorizon),distributingthedifferenceacross16equalinstalmentsperyearandfurtherreducingthisannualizednumberbytheaverageannualincreaseinGDP(respectively,exports)inthebaselinescenario,i.e.theincreasesthatareprojectedtooccurevenintheabsenceofaTFA.

18 Thereasonsforthesedisparitiesarerelatedtodifferentmodellingapproaches,scenariosanddataused.TheWEFstudyemploysthemuchbroadersub-indicesoftheEnablingTradeIndex(ETI)(seesubsectionC.4),includingtransportandcommunicationsinfrastructure,andfairlyroughtradefacilitationscenarios(halfwaytoglobal/regionalbestpractice).Butintermsofmethodology,onlythestaticGTAPmodelisused,whichforinstancedoesnottakeinto

accountthedynamicgainsthatresultfromanincreasedefficiencyoffactorallocationowingtotradefacilitation.Othermethodologicaldifferencesalsomakeacomparisondifficult.Notably,theWEFstudydoesnotshockactualtransactioncostscontainedinthemodel,butimposesexogenoustradeflowscomingfromagravityestimationontheCGEframework,whichconstitutesadrasticallydifferentmodellingchoicefromthatfollowedinthisreport.

19 SeesubsectionsC.2andC.3,whereitwasexplainedthatthegainsfromtradefacilitationareintheformof“rectangles”and“trapezoids”whilethegainsfromtariffreductionscorrespondtoHarberger“triangles”.

20 Afullerdiscussionofresults,alsoatamoredisaggregatedlevel,aswellasoffurthermethodologicalrefinements,notablyinrelationtocertaincostaspects,willbeprovidedintheforthcomingpaperbyFontagnéet al.(2015).

21 Inordertoconsiderthefullsampleoffirms,assumptionshadtobemadeastotheexpectedexporttimefacingthenon-exportingfirm.Thisstudyassumesthatdomesticfirmsthatdecidenottoexporttakethisdecision,usingasexpectedtimetoexporttheaverageexporttimeoffirmsproducinginthesamesectorandinthesamecountry.

22 FreundandRocha(2010);Djankovet al.(2010).

23 Byadmissionofthesameauthor,theseresultshavetobetakenwithcaution.Theyindicateaconditionalcorrelationratherthanacausaleffectoftradefacilitation.

24 ForanextensivediscussionoftheseeffectsseeWorldBankGroupandWTO(2015).

25 Alongsimilarlines,Ndonga(2013)arguesthatinefficientborderprocedureshaveanegativeimpactonverticalFDIflowsinAfrica.Theimplementationofsinglewindowsystemswouldthereforeconstituteaninvestmentfacilitationtool.

26 Inthissubsection,FDIdataisfromUNCTADandGDPdataisfromtheIMF’sWorldEconomicOutlook.TheOECDTFIindicatorsarenotusedinthiscontextbecausetheydonotvaryovertime.Therefore,theywouldnotallowtheestimationofpanelregressionsthatcontrolforcountryfixedeffects.AsdiscussedinsubsectionD.1,timetoimportandtimetoexportfromtheWorldBank“DoingBusiness”indicatorsarenegativelycorrelatedwiththeOECDTFIindicators.Thisjustifiestheiruseinthisanalysis.Resultsforcosttoimportarenotreportedbecausetheyarenotstatisticallysignificant.

27 TheRevisedKyotoConvention’sgoverningprinciplesareregardedastheinternationalblueprintforeffectiveandmoderncustomsclearanceprocedures,chiefamongtheseare:theapplicationofcustomsproceduresinapredictableandtransparentenvironment,theadoptionofmoderncustomstechniques(e.g.riskmanagement,audit-basedcontrolsandtheoptimaluseofinformationtechnology),aneffectivepartnershipwiththeprivatesectorandotherstakeholders,andareadilyaccessiblesystemofappeals(Preamble of the Text of the Revised Kyoto Convention,availableatwww.wcoomd.org/en/topics/facilitation/instrument-and-tools/conventions/pf_revised_kyoto_conv/kyoto_new.aspx).

28 “Post-ClearanceAudit”,apapersubmittedbytheSeparateCustomsTerritoryofTaiwan,Penghu,KinmenandMatsufortheJuly2012WTOSymposiumonTradeFacilitation.Availableathttps://www.wto.org/english/tratop_e/tradfa_e/case_studies_e/pca_tpkm_e.doc

29 BoththecustomstransparencyindexandthetimepredictabilityofimportproceduresaresourcedfromWEF(2014).Thedataarefortheyear2013.

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Appendix Table D.1: Intensive margin: regression results

(1)(2)

Total-tradeij

Log(TFIi)0.254*[0.138]

TFIij0.399*[0.211]

Log(GDPi)0.858***[0.023]

0.857***[0.023]

Log(marketaccessi)-0.310***

[0.102]-0.311***

[0.101]

NumberofPTAsi-0.006**[0.002]

-0.006**[0.002]

Log(areai)-0.069***

[0.016]-0.068***

[0.016]

Landlockedi-0.377***

[0.125]-0.379***

[0.125]

PTAij0.336***[0.083]

0.334***[0.084]

Log(distanceij)-0.715***[0.054]

-0.715***[0.055]

Commonborderij0.434***[0.130]

0.434***[0.130]

Commonlanguageij0.017

[0.083]0.016

[0.083]

Colonyij0.413**[0.184]

0.412**[0.184]

Observations 16,238 16,238

Logpseudolikelihood -2.760e+09 -2.760e+09

Partner(j)FE Yes Yes

Numberofid(jcountries) 129 129

Notes: Robust(clusteredonidvariable)standarderrorsinparentheses.***p<0.01,**p<0.05,*p<0.1,wherethep’sindicatelevelsofstatisticalsignificance:***pislessthan1%,**pislessthan5%and*pislessthan10%.Partnerjfixedeffectsandmultilateralresistancecontrolsincludedinbothregressions.


Appendix tables


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Appendix Table D.2: Extensive margin: regression results

(1) (2) (3) (4)

Number of exported products by destination (npdij)

Number of export destinations by product (ndpik)

Baseline New HS6 Baseline New destinations

TFI0.236***[0.026]

0.255***[0.025]

0.281***[0.006]

0.425***[0.006]

Log(GDPpercapita)0.171***[0.014]

0.038***[0.014]

0.372***[0.002]

0.248***[0.002]

Log(marketaccess)0.311***[0.008]

0.236***[0.008]

0.471***[0.003]

0.306***[0.002]

NumberofPTAs0.002***[0.000]

0.001***[0.000]

0.005***[0.000]

0.005***[0.000]

Log(area)0.016**[0.007]

0.013**[0.006]

0.310***[0.001]

0.211***[0.001]

Landlocked-0.032*[0.018]

-0.152***[0.014]

-0.371***[0.004]

-0.353***[0.004]

Weightedpartners’TFI-0.718***[0.183]

-0.160[0.151]

Log(bilateralGDP)0.393***[0.018]

0.376***[0.013]

PTAdummy0.069**[0.033]

0.035[0.030]

Log(distance)-0.497***[0.030]

-0.316***[0.030]

Contiguity-0.220***

[0.074]-0.511***[0.146]

Commonlanguage0.368***[0.040]

0.326***[0.036]

Colony0.527***[0.109]

0.333**[0.165]

Log(remoteness)-1.271***[0.007]

-0.712***[0.006]

Observations 22,910 22,910 667,776 667,904

Numberofid(partners) 180 180

Numberofid(HS6) 5,217 5,218

Notes: Bootstrapstandarderrors(100replications)inparentheses.Bootstrappingisastatisticalprocedurewhichinvolvesusingdatafromthedrawnsampleathandasa“surrogate”forthetruepopulation.Bytakingrepeatedsampleswithreplacementfromthissurrogatepopulation,onecanapproximatethesamplingdistributionofthestatisticofinterest,inthiscasethecoefficientestimates.SeeEfron(1979)andEfronandTibshirani(1993).

*** p<0.01,**p<0.05,*p<0.1,wherethep’sindicatelevelsofstatisticalsignificance:***pislessthan1%,**pislessthan5%and*pislessthan10%.

Partnerjfixedeffects,regiondummiesandmultilateralresistancecontrolsincludedincolumns(1)-(2).

Product(HS6)fixedeffects,regiondummiesandameasureforremotenessincludedincolumns(3)-(4).

Variable“Weightedpartners’TFI”usesinversebilateraldistanceasweights.

AppendixTableD.2usesnegativebinomialregressions,asdetailedinBeverelliet al.(2015).Columns(1)and(3)present“Baseline”estimations,withthedependentvariableconstructedusingtradedatafor2009.Columns(2)and(4)respectivelyuse“NewHS6”productsand“Newdestinations”intheconstructionofthedependentvariable,toaddressreversecausalityconcerns.Tocompute“NewHS6”products,theprocedureisasfollows:whencomputinghowmanyproductscountryiexportedtocountryjin2009,thereportonlyincludesthesubsetofproductsforwhich:(i)therewerenoexportsfromitoj(zeroormissing)recordedinanyoftheyearsbetween2003and2007;and(ii)therewerepositiveexportsfromito jrecordedinatleastoneyearbetween2008and2010.Inthiscase,npdijisthecountofnewHS6productsthatwerenottradedbefore2008.Theprocedurefor“Newdestinations”isverysimilar.Whencomputinghowmanydestinationcountrieswereservedbycountryiinexportingproductkin2009,thereportonlyincludesthesubsetofdestinationsforwhich:(i)therewerenoexportsofproductk(zeroormissing)recordedinanyoftheyearsbetween2003and2007;(ii)therewerepositiveexportsofproductkrecordedinatleastoneyearbetween2008and2010.Inthiscase,therefore,ndpikbecomesthecountofnewdestinationsthatwerenotservedbefore2008.Theuseof“newproducts”and“newdestinations”hastheadditionaladvantagethatonedoesnotnecessarilyexcludeproducts(respectively,destinations)wherecountryiceasedtoexporttocountryj(respectively,inproductk)duringthebigtradecollapseof2009.


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Appendix Table D.3: Estimated increases in the number of products by destination due to TFA implementation by geographic region(percentage change)

Baseline New HS6


Africa 8.9 9.6

Asia 5.6 6.0

CommonwealthofIndependentStates 11.2 12.1

Europe 8.6 9.3

MiddleEast 6.5 7.0

NorthAmerica 6.9 7.5

SouthandCentralAmericaandtheCaribbean 12.6 13.6


Africa 8.7 9.4

Asia 7.3 7.9


Europe 9.0 9.7

MiddleEast 10.0 10.9



“Full” scenario

Africa 30.3 32.8

Asia 12.8 13.9


Europe 9.5 10.3




Notes: Thenumbersindicatepercentagechangeinnpdij(numberofexportedproductsbydestination)undertherelevantscenario.“Baseline”resultsarebasedoncolumn(1)ofAppendixTableD.2.“NewHS6”resultsarebasedoncolumn(2)ofAppendixTableD.2.



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Appendix Table D.4: Estimated increases in the number of destinations by product due to TFA implementation by geographic region(percentage change)

Baseline New destinations


Africa 10.5 15.9

Asia 6.6 10.0


Europe 10.2 15.5

MiddleEast 7.7 11.7




Africa 10.3 15.6

Asia 8.7 13.1


Europe 10.7 16.1




“Full” scenario

Africa 34.9 52.7

Asia 15.3 23.1


Europe 11.3 17.1




Notes: Thenumbersindicatepercentagechangeinndpik(numberofexportdestinationsbyproduct)undertherelevantscenario.“Baseline”resultsarebasedoncolumn(3)ofAppendixTableD.2.“Newdestinations”resultsarebasedoncolumn(4)ofAppendixTableD.2.


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Appendix Table D.5: Foreign direct investment and trade facilitation regression results

(1) (2)

Documentstoimport-0.272***(0.084)

Documentstoimport#log(gdp)0.043***(0.012)

Timetoimport-0.085***

(0.031)

Timetoimport#log(gdp)0.012**(0.005)

log(gdp)1.545***(0.314)

1.455***(0.329)

Observations 1,048 1,048

R-squared 0.160 0.160

Numberofcountries 141 141

Notes: Dependentvariable:log(inwardFDI).Robuststandarderrorsinparentheses.***p<0.01,**p<0.05,*p<0.1,wherethep’sindicatelevelsofstatisticalsignificance:***pislessthan1%,**pislessthan5%and*pislessthan10%.Countryfixedeffectsandtimedummiesincluded.


Appendix Table D.6: TFI, customs transparency and time predictability of import procedures regression results

(1) (2) (3) (4)

Customs transparency Index Time predictability of import procedures

OLS GLM OLS Poisson

TFI0.163**(0.066)

0.938**(0.419)

0.524**(0.231)

0.139**(0.056)

Log(pcgdp)0.055***(0.013)

0.340***(0.082)

0.288***(0.047)

0.073***(0.011)

Observations 103 103 114 114

R-squared 0.284 0.419

Notes: Robuststandarderrorsinparentheses***p<0.01,**p<0.05,*p<0.1,wherethep’sindicatelevelsofstatisticalsignificance:***pislessthan1%,**pislessthan5%and*pislessthan10%.OLS=ordinaryleastsquares;GLM=generallinearmodel;Poisson=Poissonregressionmodel.


D. Estimating the benefits of the Trade Facilitation Agreement · PDF fileWOLD TADE EOT 2015...

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