Trends in international trade

world trade report 2013

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A comprehensive and fruitful analysis of the shaping factors of international trade and their implications for trade policy cannot be performed without having a clear idea of the evolution of trade patterns over time. This part of the Report analyses past, present and future trends in international trade and economic activity. It begins with a historical analysis of trade developments from pre-industrial times to the present, focusing on the key role that technology and institutions have played in the past. It then identifies and explains important trends in international trade that have emerged over the last 30 years. In doing so, the section describes who the main players are in international trade (in terms of countries or companies), what countries trade and with whom, and how the nature of trade has changed over time. Finally, it provides some illustrative simulations of possible future trade scenarios.

B. Trends in international trade

II – Factors shapIng the Future oF world trade

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Contents 1 Theevolutionofinternationaltrade:insightsfromeconomichistory 46

2 Howhastradechangedinthelast20-30years? 55

3 Futureeconomicandtradescenarios 89

4 Conclusions 103

Appendixtables 109

Some key facts and findings

• Dramatic decreases in transport and communication costs have been the driving forces behind today’s global trading system. Geopolitics has also played a decisive role in advancing and reinforcing these structural trends.

• In the last 30 years, world merchandise and commercial services trade have increased by about 7 per cent per year on average, reaching a peak of US$ 18 trillion and US$ 4 trillion respectively in 2011. When trade is measured in value-added terms, services play a larger role.

• Between 1980 and 2011, developing economies raised their share in world exports from 34 per cent to 47 per cent and their share in world imports from 29 per cent to 42 per cent. Asia is playing an increasing role in world trade.

• For a number of decades, world trade has grown on average nearly twice as fast as world production. This reflects the increasing prominence of international supply chains and hence the importance of measuring trade in value-added terms.

• Simulations show that in a dynamic economic and open trade environment, developing countries are likely to outpace developed countries in terms of both export and GDP growth by a factor of two to three in future decades. By contrast, their GDP would grow by less than half this rate in a pessimistic economic and protectionist scenario, and export growth would be lower than in developed countries.


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1. Theevolutionofinternationaltrade:insightsfromeconomichistory

Understanding the future shaping factors of worldtrade begins with an understanding of the historicalforcesthatcreatedtheglobaltradingsystemwehavetoday.Theriseofaworldtradingsystem,likesomanyother features of the modern world economy, beganlargely with the industrial revolution. The immensetechnological advances in transportation andcommunications that itunleashed– fromsteamships,railroads and telegraphs to automobiles, aeroplanesandtheinternet–steadilyreducedthecostofmovinggoods, capital, technology, and people around theglobe. This “death of distance”, to use the modernmetaphor,hasbeenoneofthemost importantforcesshapingglobaleconomicdevelopmentsincetheearly1800s(Cairncross,1997).

Theriseofaworldeconomy, thespreadof investmentand technology, the growth of internationalspecialization,theascentofneweconomicpowers,thedramaticsurgeingrowthandpopulation–noneofthisin turn would have been possible without a massiveexpansion of global trade over the past 200 years. Atthesametime, thespreadof industrialization–first toEurope,next to theAmericas,and then toAsia,Africaand elsewhere – fuelled a further expansion ofinternationaltradeandeconomicintegration.Sincethemid-1800s, the world’s population has grown roughlysix-fold, world output has grown 60-fold, and worldtradehasgrownover140-fold (Maddison,2008).Thisvirtuouscircleofdeepening integrationandexpandinggrowthiswhatwenowrefertoasglobalization.

While underlying technological and structural forcesare the main drivers behind globalization, politicalforces play an equally central role – sometimesfacilitating and cushioning the rise of a globallyintegratedmarket,othertimesresistingorreversingit.Karl Polanyi’s insight that a global free market is notonlyimpossible,butdoomedtoself-destructionintheabsence of effective international cooperation looksas valid today as it did when he first advanced it in1944(Polanyi,1944).

Itisdifficulttoimaginetheriseofglobalizationduringthe19thcenturywithoutthegoldstandard,thedensewebofbilateraltradeagreements,andGreatBritain’seconomic dominance, just as it is difficult to imaginethepost-1945resumptionofglobalizationwithouttheadvent of the new multilateral economic institutions,more activist economic and social policies at thedomesticlevel,andAmerica’sassumptionofthegloballeadershipmantle.Indeed,theevolutionofglobalizationover the past 200 years has generally beenaccompanied not by a contraction of government butby its steady expansion at both the national andinternationallevel(seeSectionC.6).

Yetatothertimes,politicshasintervened–sometimesconsciously,sometimesaccidentally–toslowdownoreven roll back the integrationist pressures oftechnologyandmarkets.Itisthiscomplexinterplayofstructural and political forces that explains thesuccessive waves of economic integration anddisintegrationoverthepast200years;andinparticularhow theseemingly inexorable riseof the “firstageofglobalization” in the 19th century was abruptly cutshort between 1914 and 1945 – by the relatedcatastrophes of the First World War, the GreatDepression and the Second World War – only to befollowedbytheriseofa“secondageofglobalization”during the latter half of the 20th century. While thelong-termtrendhasbeeninthedirectionofexpandingtrade and deeper integration, unpredicted (andperhaps unpredictable) geopolitical shocks haveperiodically interrupted or reversed this trend,suggestingtheneedforcaution inextrapolatingfromtheeconomicpastintotheeconomicfuture.

(a) Thefirstageofglobalization

Theearly19thcenturymarkedamajorturningpointforworld trade.Although theoutlinesofaworldeconomywerealreadyevidentinthe17thand18thcenturies–asadvancesinshipdesignandnavigationledtoEurope’sdiscoveryoftheAmericas,theopeningupofnewroutestoAsiaaroundAfrica,andMagellan’scircumnavigationoftheglobe(Maddison,2008)–itwasthearrivaloftheindustrialrevolutionintheearly1800swhichtriggeredthemassiveexpansionoftrade,capitalandtechnologyflows, the explosion of migration and communications,and the “shrinking” of the world economy, that is nowreferredtoas“thefirstageofglobalization”(Ikenberry,2000). In particular, breakthroughs in transporttechnologies opened up national economies to tradeandinvestmentinwaysthatdifferedradicallyfromwhathad gone before, relentlessly eroding what economichistorian Geoffrey Blainey has termed “the tyranny ofdistance”(Blainey,1968).

Steampowerwasthefirstrevolutionarytechnologytotransform transportation, starting with steamships.Although early vessels were initially limited to inlandriversandcanals,by the late1830ssteamshipswereregularly crossing the Atlantic and by the 1850s aservice toSouthandWestAfricahadbegun.Atfirst,steamshipscarriedonlyhigh-valuecommodities,suchas mail, but a series of incremental technologicalimprovements over subsequent decades – screwpropellers,thecompoundandturbineengine,improvedhull design, more efficient ports – resulted in faster,bigger, and more fuel-efficient steamships, furtherdriving down transport costs, and opening up trans-oceanicsteamship tradetobulkcommodities,aswellasluxurygoods(Landes,1969).

The opening of the Suez Canal in 1869 marked afurther breakthrough in trans-oceanic steam shipping.Until then, steamships could not carry enough coal to


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circumnavigateAfricaleavingsailingshipsstilldominantonFarEasterntraderoutes.Bycreatingamajorshort-cuttoAsiafromEurope,theSuezCanalsuddenlymadesteamships viable, and most cost efficient on theseroutes as well, completing their conquest of trans-oceanicshippingbytheendofthe1800s.

Railwaysweretheothermajorsteam-relatedtransportinnovation of the industrial revolution. Inlandtransportationcostshadalreadystarted to fall in thelate 18th century as a result of road and especiallycanalconstruction.ThelengthofnavigablewaterwaysinBritainquadrupledbetween1750and1820;canalconstructioninFrancealsosoaredwhileintheUnitedStates the massive Erie Canal, constructed between1817 and 1825, reduced the transportation costsbetweenBuffaloandNewYorkby85percentandcutthe journeytimefrom21toeightdays(O’RourkeandWilliamson,1999).

Theimportanceofinlandwaterwayswassooneclipsedby the railway boom. The world’s first rail line, theStocktonandDarlingtonRailway,openedin1825,andwas soon copied, not just throughout Britain, but inBelgium, France, Germany and the rest of WesternEurope. The explosion of railways was particularlynotableintheUnitedStatesduringthesecondhalfofthe 19th century, where new trans-continentalnetworks would play a major role, not just in thesettlement of the West and in forging a nationaleconomybutinlinkingthevastAmericanhinterlandtoglobal markets (O’Rourke and Findlay, 2007). Atranscontinental line linkedtheEastandWestcoastsof the United States by 1869; the Canadian-Pacificrailroadwascompletedby1885andthetrans-Siberianrailway by 1903. The decade prior to the First WorldWar also saw an explosion of railway building inArgentina, India, Australia, China and elsewhere,largely financed by British capital. From virtuallynothingin1826,almostamillionkilometresofrailhadbeenbuiltby1913(Maddison,2008).

Ifsteampower revolutionized trade in thefirsthalfofthe19thcentury,awaveofevennewertechnologies–such as refrigerated ships and submarine telegraphcables–contributedtoafurtherloweringoftradeandcommunications costs and a deepening of globalintegration in the second half of the 19th century.Refrigerationhadmajortrade implications.Developedin the 1830s and refined over the following twodecades, mechanical refrigeration meant that chilledbeef could be exported from the United States toEurope as early as 1870; by the 1880s, SouthAmerican meat, Australian meat and New Zealandbutter were all being exported in large quantities toEurope(Mokyr,1990).

Thearrivaloftheelectronictelegraphinthe1840swasanother transformative event, ushering in the moderneraofnear instantaneousglobalcommunications.Thefirst successful transatlantic telegraph message was

sentinAugust1858,reducingthecommunicationtimebetweenEuropeandNorthAmericafromtendays–thetimeittooktodeliveramessagebyship–toamatterofminutes. By the end of the 19th century, British-,French-,German-andUS-ownedcableslinkedEuropeandNorthAmericainasophisticatedweboftelegraphiccommunications.

International trade increased rapidly after 1820,underpinned by falling transport and communicationscosts. Inland transport costs fell by over 90 per centbetween1800and1910;transatlantictransportcostsfellroughly60percentinjustthreedecadesbetween1870 and 1900 (Lundgren, 1996). Meanwhile, worldexports expanded by an average of 3.4 per centannually, substantially above the 2.1 per cent annualincrease inworldGDP (Maddison,2001).Asa result,theshareoftradeinoutput(oropenness)rosesteadily,reaching a high point in 1913 (see Table B.1), justbefore theFirstWorldWar,whichwasnot surpasseduntilthe1960s(Maddison,2001).

(b) Agrowingdivisionoflabourandawideningwealthgap

The vast expansion of international trade in the19th century enabled countries to specialize in theproducts at which they were most efficient, thusreinforcing and accelerating the international divisionof labour. Although trade also helped to diffuse newtechnologies and products – and to reduce thehandicapthatcountrieswithlimitednaturalresourceshadhithertofaced–industrializationanddevelopmentspread unevenly, with Britain taking an early lead,followedbyWesternEurope,NorthAmerica,andmuchlaterJapan.Thus,evenasglobaleconomicintegrationdeepenedinthe19thcentury,theincomegapbetweena fast-industrializing North and a raw-materialsupplying South widened – a process economichistorian Kenneth Pomeranz has called “the greatdivergence”(Pomeranz,2000).

Dramatically falling transportcosts resultednot just inincreasing volumes of trade but also in tradediversification.Beforetheindustrialrevolution,thevastmajorityofgoodsandrawmaterialsweretoodifficultorexpensive to transport over great distances, with theresult thatonlygoodswith thehighestprice-to-weightratio–spices,preciousmetals, teaandcoffee–weretraded. However, as steamships replaced wooden

TableB.1:Share of world exports in world GDP, 1870-1998 (percentage)

1870 4.6

1913 7.9

1950 5.5

1973 10.5

1998 17.2

Source:OECD(2001).


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sailingvessels,andasrailwaysreplacedtransportationby horses, a greater variety of commodities weresuddenly accessible to the world’s industrial centres,andamuchwider rangeofmanufacturedgoodswereavailabletotherestoftheworld.

Over the course of the 19th century, trans-oceanictrade in grains, metals, textiles and other bulkcommodities became increasingly common.1 Afterthe mid-19th century, European farmers increasinglyfound themselves indirectcompetitionwith thevastand highly productive farms of the Americas andRussia.2 Despite a fast-growing population andlimited arable land, food prices in Britain stoppedrising in the 1840s and started falling thereafter(O’Rourke and Findlay, 2007; O’Rourke andWilliamson,1999).

Decliningfoodpricesbenefitedindustrialworkersandurban consumers – helping to fuel furtherindustrializationandurbanization–butdisadvantagedlandowners and farm labourers. According toPomeranz, one of the key factors that facilitatedEurope’s rapid industrialization throughout the 1800swasthevastamountoffertile,uncultivatedlandintheAmericas which could be used to grow the largequantities of agricultural products needed to feed afast-expandingEuropeanpopulation, therebyallowingEurope’s labour and land to be freed up for furtherindustrialization(Pomeranz,2000).

Atthesametime,theAmericas,AsiaandAfricaservedas an expanding market for European manufacturedgoods.Justasfarmersinindustrializedcountriesfacedpowerful new competition from highly competitiveagricultural producers in the New World, developing-country artisanal and craft producers also foundthemselves out-competed and overwhelmed by morecapital-andtechnology-intensiveproducersinthefast-industrializingNorth(BairochandKozul-Wright,1996).

Massive inflows of European manufactured goods,particularly of textiles and clothing, throughout the19thcenturyresultedinwhateconomichistorianPaulBairochdescribesas the“de-industrialization”of thedevelopingworld,bothinabsoluteandrelativeterms.The destruction of India’s textile industry was astriking example, but a similar de-industrializationprocesswastakingplaceinChina,LatinAmericaandthe Middle East (Bairoch and Kozul-Wright, 1996).The developing world saw its share of globalmanufacturing fall from over a third to less than atenthbetween1860and1913(Bairoch,1982).Onlyafter the turn-of-the-centurydid thedownturn in thedeveloping world’s industrial capacity begin toreverse.

Improved transport and communications allowedpeople and capital as well as goods to move morefreelyacross theglobe, further fuelling thegrowthofoverseas markets, providing new investments in

transport and communications infrastructure, anddrivingupthepaceofglobalintegration.From1820to1913, 26 million people migrated from Europe to theUnited States, Canada, Australia, New Zealand,Argentina and Brazil. Five million Indians migratedwithin the British Empire to destinations such asBurma,Malaysia,SriLankaandAfrica.Anevenlargernumber of Chinese migrated to countries around thePacificRimandbeyond(Ravenhill,2011).

The opening up of the Americas, Australasia andNorthern Asia to new settlement required massivecapital investments, especially in railways. After 1870,there was a massive outflow of European capital foroverseas investments. By 1913, Britain, Franceand Germany had investments abroad totalling overUS$ 33 billion; after 1870, Britain invested morethan half its savings abroad, and the income from itsforeign investments in 1913 was equivalent to almost10 per cent of all the goods and services produceddomestically (Maddison, 2001). Moreover, this capitalflowed increasingly towards the developing world.Between1870and1914,theshareofBritishinvestmentgoing to Europe and the United States halved, from52percentto26percentofthetotal,whiletheshareof investment absorbed by Latin America and Britishcolonies and dominions rose from 23 per cent to55percent(KenwoodandLoughheed,1994).

A new global economic landscape – defined by anadvanced industrial “core” and a raw-material-supplying “periphery”–gradually tookshapeover thecourse of the 19th century, reflecting the increasinginternationaldivisionof labour (O’RourkeandFindlay,2007). For Britain in particular, trade with its Empireand dominions was more important than trade withother industrialized countries. For example, in 1913,Britain imported more from Australia, Canada andIndia (and some others) combined than the UnitedStates–despite the latter’s importanceasasupplierofcottonforBritain’stextileindustry–anditexportedfivetimesasmuchtothesecountriesastotheUnitedStates.Similarly,FranceexportedmoretoAlgeriathantotheUnitedStatesin1913(Ravenhill,2011).

Evenamongindustrializedcountries,tradewaslargelydominated by primary products until after the FirstWorld War. According to Kenwood and Lougheed(1994), at its peak in 1890, agriculture and otherprimary products accounted for 68 per cent of worldtrade, declining slightly to 62.5 per cent by 1913(Kenwood and Lougheed, 1994). At the outbreak oftheFirstWorldWar,primaryproductsstillconstitutedtwo-thirdsoftotalBritishimports(Ravenhill,2011).

If incomes within the industrialized core generallyconverged during the 19th century, incomes betweenthe core and the periphery of the world economydramatically diverged. Many economists, beginningmost notably with Raul Prebisch in the 1950s, havearguedthatthisdivergencewasaresultofthegrowing


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internationaldivisionoflabour,especiallythewaytheirgrowing dependence on raw material exportsprevented poorer countries from industrializing.3Although commodity specialization brought someperiphery countries significant economic benefits –Argentina,forexample,hadamongtheworld’shighestper capita income in 19134 – for many others,economicprogresswasmodestornon-existent.

Meanwhile, the industrialized countries’ access tocheaper raw materials and vast markets for theirmanufactured goods allowed them to advance at amuch greater pace, both economically andtechnologically,thantherestoftheworld.In1860,thethreeleadingindustrialcountriesproducedoverathirdof totalglobaloutput;by1913theirsharewasa littleundertwo-thirds(ofamuchlargertotal). In1820,therichest countries of the world had a GDP per capitaabout three times the poorest (see Figure B.1);by1910,theratiowasninetooneandby1925,fifteentoone(Maddison,2001).

Theindustrializedcorealsograduallyexpandedduringthis period. Britain was the undisputed economicpower in themid-1800s,butby1913both theUnitedStatesandGermanywerecontributinga largershareof world output, as is shown in Table B.2. While in1870, no country had achieved a level of per capitaindustrializationhalfthatofBritain’s,by1913Germany,Belgium, Switzerland and Sweden had caught up.5

However, as Bairoch notes, even by the end of the19th century, “the core of world industry comprised avery small group of countries” (Bairoch and Kozul-Wright,1996).

(c) Globaleconomiccooperationandintegration

The spectacular growth in international economicintegration in the 19th century rested on relativelysimple – but in many ways fragile – internationalpoliticalfoundations.

The central pillar of the 19th-century global economywastheinternationalgoldstandard.FollowingBritain’sexamplesince theearly1820s,6Germanyguaranteedgoldparityforitsexchangeratein1872aspartofitsefforts toconsolidate itsnewlyunifiedempirearounda single currency and a common monetary policy.Denmark, Norway and Sweden followed Germany in1873, the Netherlands in 1875, Belgium, France andSwitzerlandin1876andtheUnitedStatesin1879.Bythe end of the 1880s, virtually the whole world hadjoinedBritainonthegoldstandard,effectivelycreatingasingleworldfinancialsystem(Frieden,2006).Sinceeverycountryfixedthevalueofitsnationalcurrencyintermsofgold,eachcurrencyhadafixedexchangerateagainsteveryother– thusvirtuallyeliminating foreignexchange risk andbarriers to international payments.The period between the 1870s and 1914 was one ofremarkable stability and predictability in internationaltradeandcapitalflows.

European countries also negotiated a dense networkofbilateral tradeagreementswithoneanotherduringthisperiod,triggeredbytheconclusionoftheCobden-ChevalierTreatybetweenBritainandFrancein1860.The treaty not only reduced tariff barriers betweenEurope’s two largest economies,7 but included an

FigureB.1:GDP per capita of selected economies, 1820-1938 (1990Internationaldollars)

United States UK, France, Germany (average) Japan India China

0

1,000

18

20

18

25

18

30

18

35

18

40

18

45

18

50

18

55

18

60

18

65

18

70

18

75

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85

18

90

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19

05

19

10

19

15

19

20

19

25

19

30

19

40

2,000

3,000

4,000

5,000

6,000

7,000

8,000

19

35

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unconditionalmost-favoured-nation(MFN)clausewhichguaranteed equal, non-discriminatory access if eitherFrance or Britain lowered tariffs with third countries.This MFN clause provided the “cornerstone” of the19th-centurycommercialtreatynetwork(Bairoch,1982).

While Britain made its tariff reductions under thetreaty applicable to all countries, France adopted atwo-tieredtariffsystem,withlowerMFNtariffratesforBritain and higher rates for others – creating apowerful incentive for other European states tonegotiateMFNagreementswith Franceaswell, thussecuringequaltreatmentfortheirownexports.Franceconcluded a treaty with Belgium in 1861, followed inquick succession by agreements with the GermanZollvereinin1862,Italy in1863,Switzerlandin1864,Sweden, Norway and the Netherlands in 1865, andAustria in1866.8AseconomichistorianDouglasIrwinputsit,“throughavarietyoffortuitouscircumstances,asinglebilateral agreement to reduce tariffs blossomedinto dozens of bilateral accords, resulting in aneffectively multilateral arrangement under whichinternational trade entered an unprecedentedly liberalera”(Irwin,1995).

Europe’s vast overseas empires and spheres ofinfluence, already deeply integrated by trade,investment,andmigrationflows,alsoplayedakeyrolein shaping global economic integration. Much of thedevelopingworldhadbeen–orwasintheprocessofbeing–openeduptotradeandinvestmentasaresultof colonial rule and the expectation that imperialpowersshouldenjoyfreeaccesstotheresourcesandmarkets of their colonial possessions.9 Theseextensive imperial and colonial ties meant that largepartsof theworldeconomywereautomaticallydrawnintotheliberaltradingorderbeingconstructedamongEuropeancountriesafter1860.

French,German,BelgianandDutchcoloniesessentiallyadoptedthesametariffcodesastheirhomecountries,while most of Britain’s dependencies, such as India,applied the same low, non-discriminatory tariff onforeign as well as British imports. If trade relationsamong industrialized countries, according to Bairoch,still resembled “islands of liberalism surrounded by asea of protectionism” in the 19th century, in thedeveloping world they resembled “an ocean ofliberalism with islands of protectionism” (Bairoch andKozul-Wright,1996).

There were also various attempts at the internationallevel to meet the policy coordination and cooperationchallenges thrown up by new transport andcommunications technologies. For example, theInternational Telegraph Union (ITU), the world’s oldestinternational body, was formed in 1873 to harmonizetelegraph regulations and tariffs.10 An InternationalConference for Promoting Technical Uniformity inRailwayswasheldin1883tohelplinkupnationalrailwaynetworks; the United International Bureau for theProtection of Intellectual Property was established in1893 to administer the newly negotiated BerneConvention for the protection of literary and artisticworks and the Paris Convention for the protection ofindustrial property. Many of these 19th-centuryinternationalinnovationsprovidedbuildingblocksfortheLeagueofNations(1919)andtheUnitedNations(1945).

All of these developments can only be understood inrelationtoBritain’scentralroleintheglobaleconomy.Astheworld’sdominant industrial,financialandnavalpower throughout much of the century, Britaingenerallyused its influenceandexampletoshapeaninternationaleconomythatmaximizedliberaltradeandinvestment flows. The mid-century push for freerglobaltradewasalmostentirelyaBritishpreoccupationandinitiative, ledbyBritain’s1846repealoftheCornLaws (highagricultural tariffs), its1849repealof theNavigation Acts (laws restricting foreign tradebetween Britain and its colonies), and finally itsinvitation to France to negotiate the 1860 Cobden-ChevalierTreaty.

Similarly, theuseofsterlingas themain internationalcurrency and the pivotal role of British banks in theinternational financial system signified Britain’seconomicstrengthandtheextenttowhichitbenefitedfrom global economic openness. Just as important,Britain’s naval supremacy ensured that the world sealanes,thearteriesofthe19th-centuryglobaleconomy,remainedopen–andnotjusttoBritishtradebuttothecommerceoftheworld.

One of the striking features of the 19th-centuryeconomicsystem–ifitcanbetermeda“system”–isthat it evolved piecemeal and autonomously, not byinternational design and agreement. Trade relationswere underpinned by a patchwork quilt of separatebilateral undertakings, while the international goldstandard entailed only countries’ individualcommitments to fix the price of their domestic

TableB.2:Percentage distribution of the world’s manufacturing production

YearUnited States

Britain Germany France RussiaOther

developed countries

Other

1830 2.4 9.5 3.5 5.2 5.6 13.3 60.5

1860 7.2 19.9 4.9 7.9 7.8 15.7 36.6

1913 32.0 13.6 14.8 6.1 8.2 17.8 7.5

Source:Bairoch(1982).


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currenciesintermsofaspecificamountofgold.Inthislackofoverarchingstructuresand institutions lay thesystem’s fundamental and inherent weakness. In theabsenceofformalinternationalconstraintsorscrutiny,mostEuropeancountriesgradually raised the leveloftheir tariffs in the last three decades of the19thcenturytoprotectdomesticproducersagainsttheincreasing global competition that had flowed fromfallingtransportcosts.

TheunificationofGermanyandItalyintheearly1870salso placed pressure on Europe’s non-discriminatorysystemoftraderelations,asbothcountriessoughttoconsolidate internal unity by raising external tariffbarriers.Theworldwidedepressionfrom1873to1877–whose impactapproachedtheseverityof theGreatDepression60yearslater–addedfurtherpressureformoredomesticprotectionandweakenedthedriveforaccess to foreign markets. The fact that the UnitedStates, already a major agricultural exporter and afast-rising manufacturing power, refused to lower itsowntariffsortograntunconditionalMFNtreatmentinits tradeagreements,alsoplacedagrowingstrainonthesystem.

By the turn of the century, the average tariff levelin Germany and Japan was 12 per cent, in France16 per cent, and in the United States 32.5 per cent.The rush by European powers to consolidate andexpandtheircolonialempiresinAfricaandAsiawasaclearsignthatBritain’s“imperialismoffreetrade”wasalreadywaning(GallagherandRobinson,1953).Evenin Britain, the free trade orthodoxy was beingchallenged by growing political calls for Britain tostrengthen and protect its Empire through exclusivetradepreferences.

(d) De-globalization

Thefirstageofglobalizationwasalreadyunderstrainwhen the First World War delivered a fatal blow –destroyingnot just the liberaleconomicorderbut theassumption,remarkablywidespreadinthe1800s,thattechnology-driven integration, interdependence andprosperity alone were sufficient to underpininternationalcooperationandpeace(Ravenhill,2011).Trade was massively disrupted, the gold standardcollapsed, economic controls and restrictions werewidespread, and Europe, the former core of the worldeconomy,wasleftdevastatedorexhausted.

The economic instability and disorder of the inter-waryears was rooted in the failed attempt to rebuild theglobalizedeconomyofthe19thcentury.Partlythisfailurearose from an inability to recognize that the post-warworldwasfundamentallyaltered,andthattherecouldbeno quick or easy return to the pre-war “golden age” ofopen trade and financial stability. Countriesunderestimated the immensechallengeof restructuringwartime industries, finding work for millions ofunemployed soldiers, or coping with raw material and

foodshortages.Oneofthewar’smostsignificantimpactswas on the changing perceptions of a government’seconomicrole.Mobilizingcountriesbehindtotalwarhaddemanded unprecedented state involvement ineconomies. After the war, there were strong politicaldemands for national governments to continue tomanageeconomiesinordertopromotefullemployment,reconstruction and greater social justice – but thesepressures for economic nationalism often clashed withpressuresforinternationaleconomiccooperation.

Economic challenges were compounded by financialchallenges.Inthefaceofwidespreadfinancialvolatilityand competitive devaluations, countries kept or re-imposed trade and exchange restrictions to slowimports and strengthen their balance of payments.When leading countries finally agreed to reinstate amodified version of the gold standard in 1925, theywereuncertainastowhatthepost-warparitiesshouldbe: the resultwascurrencymisalignments, leaving thepoundsterlingandtheFrenchfrancwildlyover-valued.

The lack of global economic leadership andcooperationwasperhapsthebiggestobstacletointer-war recovery. Pressure for war reparations and loanrepayments not only undermined Europe’s recoveryefforts but poisoned relations, further handicappinginternational cooperation. The United States failed toloweritstradebarrierstoEuropeanexports–socriticaltoEurope’seconomicrecovery–evenasitaccumulatedever-greatersurpluses.UnitedStates’ loans toEuropeafter 1924 served to mask underlying economicfragilities and accumulating global imbalances. WhentheWallStreetstockmarketcrashedinOctober1929,these weaknesses were exposed and the worldeconomyplungedintotheGreatDepression.

Totheproblemsofcollapsingdemand,bankingcrisesand growing unemployment were added risingprotectionism and economic nationalism. In responseto pressure to protect domestic farmers from fallingprices and foreign competition, the US CongresspassedtheinfamousSmoot-HawleyTariffActin1930,raising US tariffs to historically high levels andpromptingothercountriestoretreatbehindnewtariffwalls and trade blocs. Trade wars pushed the worldaveragetariffrateupto25percentatits1930speak(ClemensandWilliamson,2001).Asa resultof thesenew trade barriers and collapsing demand,international trade collapsed, its value declining bytwo-thirdsbetween1929and1934(seeFigureB.2).

AsCharlesKindleberger famously argued, “the1929depressionwassowide,sodeep,andsolongbecausethe international economic system was renderedunstable by British inability and United Statesunwillingness to assume responsibility for stabilizingit”(Kindleberger,1973).Inter-wareconomic“mistakes”,most notably the Smoot-Hawley Tariff Act, featureprominently in narratives of this era but the rootproblemwastheabsenceofastatepowerfulenough


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FigureB.2:Plummeting world trade during the Great Depression, 1929-33 (monthlyvaluesinmillionsofoldUSgolddollars)

0

500

1929 1930 1931 1932 1933

2,998

2,739

1,206992

1,000

1,500

2,000

2,500

3,000

3,500

1,839

Source:Totalimportsofseventy-fivecountries,LeagueofNations,Monthly Bulletin of Statistics ,February1934,p.51.

to provide leadership to the system, to underwrite aviable recovery plan and to restore internationalstabilityandconfidence.

Largelyasa resultof theirwartimeexperience–andits toxic and turbulent aftermath – countries werealready wary of working together to find cooperativesolutions. Faced with an unprecedented globaleconomic crisis and no sign of an early solution,countriestookaseriesoffatefulstepstoprotecttheirownnationalinterestsattheexpenseoftheircollectiveinterests–withtheresultthattheirindividualinterestswerealsoultimatelyundermined.Althoughthe1920ssaw some modest progress in efforts to restore thepre-1914 economic order, the Great Depressiondelivered a devastating blow from which the 1930snever recovered. Economic insecurity fed politicalinsecurity, resulting in the rise of political extremism,thebreakdownofcollectivesecurity,aracetore-arm,andultimatelytheoutbreakoftheSecondWorldWar.

(e) Re-globalization

In many ways, the world economy has undergone aprocess of “re-globalization” since the Second WorldWar – to use the term coined by Ronald Findlay andKevin O’Rourke – resuming and dramaticallyacceleratingthe integrationpath thatwasabruptlyde-railed by the First World War and the economic andpolitical chaos that followed (O’Rourke and Findlay,2007). Indeed, the world economy grew far fasterbetween1950and1973thanithaddonebefore1914,anditsgeographicalscopewasfarwider–usheringina“goldenage”ofunprecedentedprosperity(Maddison,2001).WorldpercapitaGDProsebynearly3percentayear, and world trade by nearly 8 per cent a year.However,thereisoneimportantdifferencebetweenthefirstand thesecondageofglobalization.Whereas the

19th-century version was accompanied by onlyrudimentary efforts at international economiccooperation,the20th-centuryversion,byexplicitdesign,wasbuiltonafoundationofnewmultilateraleconomicinstitutions known collectively as the Bretton Woodssystem: the International Monetary Fund (IMF), theWorldBankandtheGeneralAgreementonTariffsandTrade(GATT).

The key lesson drawn from the inter-war experiencewas that international political cooperation – and anenduring peace – depended fundamentally oninternational economic cooperation. No countryabsorbed this lesson more than the United States.Conscious of how its failure to assume leadershipafter1918–anddrifttowardseconomicprotectionismand nationalism after 1930 – had contributed to theinter-war economic disasters, it resolved to use itspost-warglobaldominance toconstructanew liberaleconomicorderbasedonopentrade,financialstabilityandeconomicintegration.

Thisnewsystemwasbothsimilar to the19th-centuryorderandverydifferent.TheaimoftheIMFwastore-establish the exchange-rate stability of the goldstandard era while at the same time preservingcountries’ freedom to promote full employment andeconomic growth. Under the new Bretton Woodssystem,exchangerateswerefixed,butadjustable,andinternationalstabilizationfundsweremadeavailabletocountries facing balance-of-payments difficulties.Meanwhile,theWorldBankwasestablishedtoprovidesoft loans for both economic reconstruction andindustrialdevelopment.

There were also intensive negotiations for a newInternationalTradeOrganization(ITO),intendedasthethird pillar of the new multilateral economic system.However, when the US Congress failed to ratify theITOcharterinthelate1940s,countrieswereforcedtorely on the GATT, designed as a temporary tariffcutting agreement until the ITO was formallyestablished, but embodying most of the ITO’s keycommercialpolicyrules.AlthoughtheGATTwasneverintended as an international organization, it graduallycame to play that role – both lowering tariffs andstrengthening trade rules through eight successive“rounds”ofnegotiations–until itsreplacementbytheWorldTradeOrganizationon1January1995.

This new post-war commitment to internationaleconomiccooperation–andthemultilateralinstitutionsneededtosustainit–alsofoundexpressioninaseriesof bold steps to integrate European economies. The1948 Marshall Plan, for example, stipulated thatEuropean countries should decide among themselvesnotonlyhowtodistributetheUS$12billioninMarshallAid provided by the United States but how to begindismantling internal barriers to intra-European tradeand investment.11 In the1950s, theUnitedStatesalsosupportedEuropeanplans topool production in areas


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of heavy industry, to establish international authoritieswiththepowertooverseethiscommonproductionandtoestablishhugefreetradeareas–whichlatercametofruition in the formation of the European EconomicCommunity (EEC) and ultimately the present-dayEuropeanUnion(EU).

Although the overall trend since 1945 has beentowards growing international economic cooperationanddeepening integration,progresshasbeenbumpyanduneven,withmajorobstaclesalongtheways.Theemerging Cold War in the late 1940s put wartimevisions of a new global economic order on hold foralmost fifty years (but also reinforced the sharedinterestsoffree-marketeconomies)untilthefalloftheBerlinWall in1989.TherapidunravellingofEurope’scolonial empires after the Second World War –together with the collapse of the Soviet Union after1991 – led to the creation of dozens of newlyindependent states, with their own economic, tradeand monetary systems, further complicating the taskof international coordination. Even the extraordinarysuccessof thepost-war internationaleconomicorderin underpinning global growth and development hascreated its own political challenges. On-goingeconomicintegrationisrenderingshallowermodelsofcooperation obsolete – first signalled by the abruptend of the Bretton Woods system of fixed exchangerates in 1971 – without necessarily creating supportfor alternative, deeper models. Similarly, the rise ofneweconomicpowershasentailedtherelativedeclineoftheUnitedStates,forcingtheworldtolookbeyondtheoldhegemonforwiderglobaleconomicleadership.

(f) Thecontinuingtransportandcommunicationsrevolution

Evenasworldpoliticswent throughaprocessofde-globalization between the wars followed by re-globalization after 1945, underlying technologicaladvances in transport andcommunicationscontinuedand,insomeinstances,evenaccelerated.

War actually served to fuel innovations in trans-oceanic shipping, including the introduction of betterboilers to convert steam, the development ofturboelectric transmission mechanisms and thereplacement of coal-fired plants with oil and dieselengines. In 1914, almost the entire world merchantfleet,96.9percent,werecoalburningsteamships;thisdeclined to about 70 per cent in the 1920s and lessthan50percentfromthelatterhalfofthe1930s.By1961,only4percentof theworldfleet,measured intonnage,werecoal-burningships(Lundgren,1996).

Themid-1950switnessedanothermajorbreakthroughinshippingtechnology,promptedlargelybytheclosureof the Suez Canal in 1956-57 (and again in 1965).Suddenly faced with the expense of transporting oil,coal, iron ore and other bulk commodities over muchgreater distances, the shipping industry decided

to invest in huge, specialized bulk carriers as wellas in the harbour facilities needed to handlethese new vessels. Whereas oil tankers averaged16,000 deadweight tonnes (dwts) in the early 1950s(theirdesignpartlyconstrainedbytheneedtonavigatetheSuezCanal),theyaveragedover100,000dwtsbythe 1990s – with modern “super-tankers” exceeding500,000dwts and capable of carryingover3millionbarrels of oil. The same technological advancestransformedbulkfreightersaswell,withshipsgrowingfromanaverageoflessthan20,000dwtsin1960toabout45,000dwtsintheearly1990s.Worldmaritimetrade has grown from 500 million tonnes in 1950 to4,200milliontonnesin1992(Lundgren,1996).

Railway networks also expanded rapidly between thetwoworldwars,especially indevelopingcountries.By1937,5.7percentof theworld’s railwaymileagewaslocated inAfrica,10.2per cent inLatinAmericaand10.9 per cent in Asia (O’Rourke and Findlay, 2007).By the late 1920s, diesel and electric locomotiveswere increasingly replacingsteamengines.The inter-war period also witnessed the mass adoption of themotor vehicle. Initially limited to transportingpassengers in urban areas, large motorized truckswere soon serving on feeder routes to the mainrailways lines, and eventually they were competingwiththoselines.AdoptionwasparticularlyrapidintheUnited States: in 1921 there was one commercialmotor vehicle for every 85 Americans, whereas in1938therewasoneforevery29.In1913,thefleetofpassengercarswasabout1.5million;by2002,itwas530million(Maddison,2008).Thegrowingimportanceofmotorvehicleswas in turnoneof themain factorsunderlying the rise of petroleum as an increasinglyvitalenergysourcefortheworldeconomy.

The rapid expansion of airfreight represented yetanother major transportation breakthrough. Aircraftwereputtousecarryingcargointheformof“airmail”asearlyas1911.DuringtheFirstWorldWar,airbornemilitary cargodramatically increasedandby themid-1920s aircraft manufacturers were designing andbuilding dedicated cargo aircraft. After the arrival ofFederalExpressinthelate1970s,promisingnext-daydelivery of freight through a dedicated fleet of cargocarriers,theindustrygrewexponentially.By1980,therealcostsofairfreighthadfallentoaboutaquarterofits level at the beginning of the Second World War(Dollar, 2001). This, in turn, has massively expandedthe volumes traded, the distances covered, and theproducts involved. Used in conjunction with otherforms of shipping, such as sea, rail and groundtransport, airfreight has become a key component ofinternational trade. Overall, air passenger miles rosefrom 28 billion in 1950 to 2.6 trillion in 1998(Maddison,2008).

Astheremainderof thisReportmakesclear, theworldeconomy isbeing reshapedbyanevennewerwaveofintegrationist technologies, driven by innovations in


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telecommunications, computing and the globalinformation networks they have spawned. Thanks tofibre optic cables, satellites and digital technology, thecost of overseas telecommunications is approachingzero. As the power of computer chips has multiplied –following Moore’s Law (that the power of integratedcircuitsroughlydoubleseverytwoyears)–thepriceofcomputingpowerhasalsofallendramatically.Meanwhile,the internet has emerged, almost by accident, as theembodiment of the “global information superhighway”firstpredicted in theearly1990s,servingnot justasanewmeansofglobalcommunicationsbutalsoasavastsourceofglobalinformation.

Onestrikingchangeistheglobalizationofproduction.Just as rapidly falling transport costs in the 19thcentury led to globalization’s “first unbundling” –separating factories from consumers – the newestwave of integrationist technologies, according toRichard Baldwin, is leading to globalization’s “secondunbundling” – the end of the need to perform mostmanufacturing stages near one another (Baldwin,2011a). Manufacturing is increasingly managedthrough complex global supply chains – effectivelyworld factories – which locate various stages of theproduction process in the world’s most cost-efficientlocations.

Whereas in the inter-war years, the composition oftradedifferedlittlefromthatofthepreviouscentury–that is, it was largely dominated by the exchange ofraw materials and agricultural products formanufactured goods – since 1945, the maincomponent of trade has been the internationalexchangeofmanufacturedgoodsor the componentsof manufactured goods (from 40 per cent of worldtrade in 1900 to 75 per cent in 2000), whileagriculture’s relativeshareofworld tradehassteadilydeclined(seeFigureB.3).

As a result of radical reductions in communicationscosts, services trade is also expanding dramatically.Whole sectors that were once non-traded (and thusimpervioustoforeigncompetition)–suchasbanking,retail,medicineoreducation–arerapidlytransformingthrough e-banking, e-commerce, e-medicine ore-learning into some of the most globally tradablesectors. Meanwhile, world trade has been growingeven more rapidly than world production – by7.2percentperannumbetween1950and1980(withmanufacture goods growing even more rapidly thanprimary commodities), whereas world gross domesticproduct (GDP) grew by 4.7 per cent over the sameperiod (WTO International Trade Statistics, 2012) –underscoring the powerful forces continuing to driveglobaleconomicintegration.

Acentralfeatureofthissecondageofglobalizationistheriseofmultinationalcorporationsandtheexplosionof foreigndirect investment (FDI).Withsomenotableexceptions,suchasthemajoroilcompanies,firmsthatengaged in FDI – that is, the ownership andmanagement of assets in more than one country forthe purposes of production of goods and services –were relative rarities before 1945. In the post-1945period,however,FDIhassurged,growingmorerapidlythan either production or international trade – eventhough this growth has been volatile, with dramaticfallsaswellasrisesoverthisperiod.12By2009,itwasestimated that there were 82,000 multinationals inoperation,controllingmore than810,000subsidiariesworldwide. Upwards of two-thirds of world trade nowtakes place within multinational companies or theirsuppliers – underlining the growing importance ofglobalsupplychains(UNCTAD,2010).

A far more significant change is the rise of neweconomicpowers–bothreflectinganddrivingtheon-going expansion of world trade. If the first age of

FigureB.3:Product shares in world merchandise exports since 1900 (percentage)

0

20.0

1900

57

3

1925

6

54

1938

11

44

1955

19

35

1963

16

29

1970

16

20

1980

28

15

1990

14

12

2000

14

9

2011

22

9

40 40 45 45 52 61 55 70 75 65

40.0

60.0

80.0

100.0

nes Manufactures Fuels and mining products Agricultural products

3 3 3 4

Sources:UNStatisticalYearbook(1969),GATTSpecialStudiesNo.5andNo.7,andWTOSecretariatestimates.


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globalization involved de-industrialization in theperipheryandindustrializationinthecore,thesecondagehas, insome respects, reversed thispattern.The1980s and especially the 1990s saw the rapidindustrializationofmanydevelopingcountries–andahuge increase in theirshareofmanufacturedexportsand foreign investment – while advanced countrieshave become increasingly concerned about de-industrialization as a result of the “off-shoring” and“outsourcing”ofmanufacturingcapacityandjobs.

Likewise,ifthe19thcenturywasmarkedbythe“greatdivergence”, we are now experiencing the “greatconvergence” – as billions in the developing worldrapidly“catchup”withtheadvancedWest.China,withits1.3billionpeople,hasgrownatanaverageof9percent a year for the past three decades – largelywithoutinterruption–overtakingJapanastheworld’ssecondbiggesteconomyandGermanyastheworld’sbiggestexporter. India istravellingasimilareconomicpath,asismuchoftherestofAsia,SouthAmericaandAfrica.

(g) Summary

Theindustrialrevolutionmarkedamajorturningpointfor the world economy – from the pre-globalizationagetotheageofglobalization.Indeed,thecurrentriseof the developing world is in many ways merely areflection of the on-going spread of the industrialrevolution– twocenturiesafter it first swept throughBritain – but on a scale and at a pace that easilydwarfsthe“greattransformation”ofEuropeandNorthAmerica.13 It is also a process that, in many ways, isstill unfolding. Real per capita income in the Westincreased 20-fold between 1820 and 2003, but onlyseven-foldintherestoftheworld–economiccatchuphasalongwaytogo(Maddison,2008).Centraltothisdevelopment–and itscontinuation– is theunfolding“death of distance” and the on-going transport andcommunicationsrevolutionthatliesbehindit.

China could not have become the new “workshop ofthe world” without the transpacific “conveyer belt”provided by breakthroughs in containerization afterthe 1970s. India could not be a new global serviceshub without the invention of fibre optics andbroadband.Itisbecauseofthesetechnologicalforcesthat the nature of the global economy is profoundlychanging, and with it the political, social andinstitutional structures needed to sustain andlegitimize it. The unprecedented integration andexpansionof theworldeconomy in thedecadesafter1945isatestamentnotjusttotheenduringpowerofunderlyingtechnologicalandmarketforcesbuttothesuccessof thepost-warpolitical order thathasbeensocriticaltoharnessingandmanagingtheseforces.

Two broad questions emerge from this discussion.First,willthesameshapingfactorsthathavegivenriseto today’s global trade system likely continue in the

immediate and longer-term future? In particular, willtransport and communication costs continue theirdramatic, linear decline as a result of continuedincremental technological improvement or even theintroduction of entirely new technologies? Or willmarginalimprovementsbegintodiminishinthefuture,makingdecliningtransportandcommunicationscostsa less salient shaping factor for world trade – evenleadingtoaslowingoftradegrowth?

Secondly,towhatextentcanweexpectfuturepoliticalshocks to the tradingsystem?Andcan theseshocksbe anticipated and hopefully avoided? One of thelessonsfromthelasttwocenturiesisthatgeopoliticshasadecisiveimpact–forgoodorill–onunderlyingtechnological and structural trends. The currentglobalizationphasebeganin1945withtheriseofUShegemony and the advent of the Bretton Woodssystem, and then accelerated with China opening upto the world in 1979 and with the end of the ColdWar in 1989. What kind of international politicalaccommodationorsystemisneededforthefuture?

2. Howhastradechangedinthelast20-30years?

International trade flows have increased dramaticallyover the last threedecades.According toWTO tradestatistics,thevalueofworldmerchandiseexportsrosefromUS$2.03trillionin1980toUS$18.26trillionin2011, which is equivalent to 7.3 per cent growth peryear on average in current dollar terms. Commercialservices trade recorded even faster growth over thesameperiod,advancingfromUS$367billionin1980toUS$4.17 trillion in2011, or8.2per centper year.Whenconsidered in volume terms (i.e. accounting forchanges in prices and exchange rates), worldmerchandise trade recorded a more than four-foldincreasebetween1980and2011.

Manyfactorsmayhavecontributedtothisremarkableexpansionoftradebutthefactthatitcoincidedwithasignificant reduction in trade barriers is inescapable.Tradebarriersincludeallcostsofgettingagoodtothefinal consumer other than the cost of producing thegood itself: transportation costs (both freight costsand time costs), policy barriers (tariffs and non-tariffbarriers) and internal trade and transaction costs(including domestic information costs, contractenforcement costs, legal and regulatory costs, localdistribution, customs clearance procedures,administrativeredtape,etc.).

Policybarrierscanbebroadlydivided into tariffs (ad-valoremandspecific)andnon-tariffmeasures(NTMs).Although tariffs are still the most widely used policyinstrument to restrict trade, their relative importancehasbeendeclining.Tradeopening,whetherunilateral,the result of agreements negotiated under theauspices of the World Trade Organization, or the


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consequenceofpreferentialtradeagreements(PTAs),hasgreatlyreducedtheaveragelevelofappliedtariffs(WTR,2011).Asanexample,considerthefactthattheaverage tariff imposed by developed economies in2010-11onallimportswasaround5.0percent,whiletheaveragerateonnon-agriculturalproductswasjust2.5percent,basedondatafromtheWTO’sIntegratedDatabase.

Conversely, the use of NTMs has increased both interms of the number of products covered and thenumber of countries utilizing them (WTR, 2012). Non-tariffmeasures,suchastechnicalbarrierstotrade(TBT)and sanitary and phytosanitary (SPS) measures, taxesandsubsidies,areoftenusedbygovernmentstoachievelegitimatepublicpolicyobjectivessuchastheprotectionof domestic consumers from injury or disease. On theother hand, NTMs may also be used by countries tomanipulate the terms of trade or to protect domesticproducers from foreign competition. The fact remainsthatNTMs used to pursuepublic policy objectives canalsobemisusedforprotectionistpurposes.

The theoretical and empirical literature documentingthe positive impact of traditional forms of tradeliberalizationisextensive.Nevertheless,othertypesoftradecosts,suchasdomestictradecosts,stillpresentsignificant barriers to trade. Anderson and VanWincoop(2004),forinstance,showthatfordevelopedcountries, the overall impact of trade costs can bedecomposed as follows: 21 per cent transportationcosts (including both directly measured freight costsand a 9 per cent tax equivalent of the time value ofgoods in transit), 44 per cent border-related tradebarriers and 55 per cent retail and wholesaledistribution costs.14 Hoekman and Nicita (2011) findthat while traditional trade policies continue to beimportant indevelopingcountriesaswellasforsome

sectors in high-income countries (agriculture inparticular), non-tariff measures and domestic tradecostsarealsoofgreat importance.Finally,RubinandTal (2008) suggest transportation costs represent agreaterbarriertotradethanpolicy-inducedobstacles,suchastariffs.AtapriceofUS$100perbarrelofoil,theyestimatetransportationcoststobeequivalenttoan average tariff of 9 per cent, nearly double theWTO’sestimateoftheaverageappliedtariff.

Perhaps the most significant fact about world tradesince1980isthatithasgrownmuchfasterthanworldoutput for most of this period. This is illustrated byFigure B.4, which shows five-year average annualgrowth rates for the volume of world merchandisetrade (i.e. the average of exports and imports) andworld real GDP growth, together with impliedelasticitiesoftradewithrespecttoglobalGDP.15

Trade and GDP growth are represented by verticalbars inFigureB.4andaremeasuredagainst the leftaxis.Elasticityisshownasasolidlineandismeasuredagainst the right axis. During the early 1980s, globaloutputandtradegrewatnearlythesamerate,around3 per cent per year. Output as measured by GDPincreased at a slightly faster pace of 3.2 per centbetween 1980 and 1985, while the growth ofmerchandise exports in volume terms averaged2.9percentperyear,implyinganelasticityofcloseto1 (0.92 to be precise). However, since 1985 worldtradehasgrownnearly twiceasfastasoutput.Tradegrowthaveraged5.6percentperyearbetween1985and2011.Comparedto the3.1percentaveragerateforglobalGDPforthesameperiod,weseethatworldtradegrewabout1.8timesasfastasoutput.

Many factors may have contributed to the fastergrowth of trade relative to GDP over the past three

FigureB.4:World merchandise trade volume and real GDP, 1980-2011 (annualpercentagechange)

0

1.0

1980-1985 1985-1990 1990-1995 1995-2000 2000-2005 2005-2011

2.0

3.0

4.0

5.0

6.0

8.0

7.0

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1.0

1.5

2.5

2.0

GDP growth (left scale) Merchandise trade volume growth (left scale) Elasticity (right scale)

Source:WTOSecretariat.Note:Merchandisetradereferstotheaverageofexportsandimports.


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decades.Theendof theColdWarprovideda “peacedividend”indevelopedeconomies,whichallowedthemto reducemilitaryexpendituresandboost investmentin other areas. The development of the internet andthe digital economy also appears to have boostedtrade,possiblytounsustainablelevelsaswitnessedbythe subsequentburstingof assetbubblesaround theworld. Finally, large developing economies such asChina and India embraced economic reform andinitiatedaprocessof catch-upgrowth inwhich tradehasplayedanimportantrole.

ThefactthattradegrewfasterthanGDPmayalsobepartlyexplainedbythespreadofsupplychains,whichare characterized by the unbundling of productionprocesses across countries,16 and partly bymeasurement issues.Goodsare increasinglymade intwoormoresequentialstages,withfirmsrelyingmoreand more on imported material inputs and offshoredadministrative tasks. However, since world trade ismeasured in gross terms, the value of intermediategoods may be counted more than once when goodscross borders at different stages of production,whereasintermediategoodsareonlycountedonceinGDPstatistics.

Asaresult,thegrowthofworldtradeinrecentdecadesmay be somewhat inflated compared to output. Forexample, a television produced entirely in Japan andexported to the United States in 1980 might havecontributed US$ 500 to both world GDP and worldtrade, whereas today components from Japan worthUS$400aremorelikelytobecombinedwithUS$100of value added in assembly in China, which would (allotherthingsbeingequal)raiseworldGDPbythesameUS$500whileincreasingworldtradebyUS$900(i.e.US$400ofcomponentsexportedfromJapantoChina,plusUS$500forthefinishedtelevisionexportedfromChinatotheUnitedStates).

The measure of trade elasticity shown in Figure B.4rose to1.50 in the late1980sandpeakedat2.32 inthefirsthalfofthe1990s,butithasdeclinedineveryhalfdecadesincethen.Itfellto1.96inthelate1990s,to1.71intheearly2000sandfinallyto1.66between2005 and 2011 (which is admittedly slightly longerthanahalf-decade).17AveragetradeandGDPgrowthrates in the latest six-year period have undoubtedlybeeninfluencedbythefinancialcrisisanditsaftermathbut it is difficult to gauge the extent to which theseevents altered the elasticity of trade. World exportvolumes contracted much more than world GDP in2009 (-12.5 per cent for trade and -2.4 per cent forGDP, which implies an elasticity of 5.2).18 Trade alsoreboundedmuchmore thanGDPduring the recoveryof2010(13.8percentfortrade,3.8percentforGDP,whichimpliesa3.7multipleoftradeoveroutput).

It is possible that the ratio of trade growth to GDPgrowthcouldmovecloserto2againasthe impactofthe financial crisis recedes. However, this seems

unlikely since many of the factors that drove tradegrowthoverrecentdecades(theendoftheColdWar,the rise of China, the World Wide Web, etc.) havealreadybeenexploited.

Sections B.2(a) through B.2(f) present numerouschartsandtablesshowingtheevolutionofglobaltradepatterns. The time periods covered by these chartsandtablesaredictatedbydataavailability,soalthougheveryefforthasbeenmade topresentdevelopmentsover a 20 to 30 year period, it has sometimes beennecessary to use a shorter interval. It is important tonotethatsomeofthetendenciesidentifiedbelowmayhave reached their high-water marks before thefinancial crisis and trade collapse of 2008-09. As aresult, direct extrapolations of current trends areunlikely to be very informative. Although the focus oftheReportisonlong-rundevelopments,themagnitudeof the trade collapse was so great that it casts ashadow over many of the statistics, especially periodaveragesand levels in the latestperiods.Asa result,the influence of this pivotal event should always bekeptinmindwhenconsultingthesetablesandcharts.

(a) Whoarethemainplayersininternationaltrade?

NexttothefasterrateoftradegrowthrelativetoGDPgrowth, perhaps the most important change in tradepatternsinrecentyearshasbeentheincreasedshareof developing economies in world trade and thecorresponding decline in the share of developedeconomies.SectionB.2(a)examinesthisissueinsomedetail, identifying countries that have advanced andrecededinworldtraderankingsoverthelast30yearsorso.Italsoexaminestheevolutionoftradewithinandbetween developed and developing economies (seedefinitions in Box B.1) over time, and considerswhether a small number of large countries areresponsibleforadisproportionateamountoftrade.

(i) Leading exporters and importers by level of development

FigureB.5illustratestheincreasedshareofdevelopingeconomies in world merchandise exports between1980and2011,aswellasthecorrespondingreductionin the share of developed countries. Developingeconomies,whoseexportsrepresentedjust34percentof world trade in 1980, saw their share rise to47percent,ornearlyhalfof thetotal,by2011.At thesametime,theshareofdevelopedeconomiesdroppedsharply from 66 per cent to 53 per cent. A strikingdifferencebetweenthetwoperiodsisthepredominanceofoilexportersamongdevelopingeconomies in1980,incontrast to themore important roleplayedbyAsiandevelopingeconomiesin2011.

China’s 1 per cent share in world exports in 1980made it only the tenth-largest exporter among


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developingeconomies,butby2011itssharehadrisento 11 per cent, making it the largest developingexporter,and indeedthe largestexporter intheworldwhen individual EU member states are countedseparately (see Table B.3). The Republic of Korea,India and Thailand were not even represented in thetop ten developing exporters in 1980, but by 2011theirshareshadrisento3percent,2percentand1percent,respectively.

The European Union, the United States and Japan allrecorded declines in their shares in world exportsbetween 1980 and 2011. The European Union saw itsshare fall from 37 per cent to 30 per cent, while theshareoftheUnitedStatesslippedfrom11percentto8percentandJapan’ssharedroppedfrom6percentto5per cent. It should be noted that the European Unionhere refers to the 15-country membership prior to the2004 enlargement, including intra-EU15 trade. It is

BoxB.1: Definitions of developed and developing economies

The terms “developed” and “developingandemerging” countries are looselybasedon theUnitedNationsMillenniumDevelopmentGoals(MDG)classification.Ourdevelopedcountriesgroupincludesthefollowing:all27membersoftheEuropeanUnion(includingnewlyaccededmembersthatareregardedas“transitioneconomies” under the MDG classification), other non-EU western European countries and territories(includingSwitzerland,Norway,Iceland,etc.),theUnitedStates,Canada,Japan,AustraliaandNewZealand.All other countries are termed “developing and emerging economies” although the word emerging issometimes dropped in the interest of brevity. The developing group basically corresponds to the MDGdevelopingeconomiesgroupplustheCommonwealthofIndependentStates(CIS).

Ourchoiceof countrygroupshascertainadvantagesanddisadvantages.Sinceboth the “developed”and“developingandemerging”countrygroupsarefixed,theycanbeusedtoanalysetrendsintradeandoutputovertime.Thissortofinvestigationwouldbeproblematicifpercapitaincomewereusedasthemaincriterionfordetermininglevelofdevelopment,sincegroupmembershipwouldbeconstantlychanging.Ontheotherhand,underourdefinitionssomecountriesarepresumedtobedeveloped(Greece,Malta,Poland)despitethefactthattheymaybeconsiderablypoorerthansomehigh-incomedevelopingeconomies(Singapore,theUnitedArabEmirates).Anincome-basedgroupingmaybepreferableforcertainanalyses(e.g.forexaminingacross-sectionofcountriesatapointintime)butforthemomentwewillcontinuetouseourclassificationwhilebearinginminditsinherentlimitations.

Groupingcountriesaccordingtolevelofdevelopmentposesspecificchallengesfortradepolicy-makers.Forinstance, WTO agreements allow preferential treatment for developing and least-developed economies incertain contexts. The definitions of “developed” and “developing” used in this publication should not beinterpreted as implying anything about any country’s rights and obligations under WTO agreements, andshouldonlybeseenasindicativeofacountry’sstatus.Forfurtherdiscussion,seeSectionE.

FigureB.5:Shares of selected economies in world merchandise exports by level of development, 1980-2011 (percentage)

Other developingand emergingeconomies, 15%

1980 2011

Mexico, 1%

China, 1%

Other developedeconomies, 11%

Saudi Arabia,Kingdom of, 5%

FormerSoviet Union, 4%

Iraq, 1%

Nigeria, 1%

South Africa, 1%

European Union (15),a 37%

United States, 11%Japan, 6%

Other developingand emergingeconomies, 16%

Indonesia, 1%

Brazil, 1%

Chinese Taipei, 1%

Singapore, 1% Malaysia, 1%

Other developedeconomies, 11%China, 11%


United States, 8%

Japan, 5%Korea, Republic of, 3%

Russian Federation, 3%

Singapore, 2%

Developingand

emergingeconomies,

34%

Developed economies, 66%

Mexico, 2%

Chinese Taipei, 2%

India, 2%

Brazil, 1%

Thailand, 1%

Saudi Arabia, Kingdom of, 2%

Developing and

emerging economies,

47%Developed economies, 53%

aIncludesintra-EUtrade.Source:WTOSecretariat.


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FigureB.6:Shares of selected economies in world merchandise imports by level of development, 1980-2011 (percentage)

1980 2011

Other developing and emerging economies, 15%

China, 1%

Taipei, Chinese, 1%

Other developed economies, 11%

FormerSoviet Union, 3%

Saudi Arabia,Kingdom of, 1%

Singapore, 1%

South Africa, 1%

Brazil, 1%



Nigeria, 1%

Iraq, 1%

Mexico, 1%

Korea, Republic of, 1%

Developingand

emergingeconomies,

29%

Developed economies, 71%

Other developing and emerging economies, 14%

United Arab Emirates, 1%

Thailand, 1%

Other developedeconomies, 10%

China, 10%

Commonwealth ofIndependent States (CIS), 3%

Korea, Republic of, 3%

India, 3%

Singapore, 2%



Mexico, 2%

Taipei, Chinese, 2%

Turkey, 1%

Brazil, 1%

Developingand

emergingeconomies,

42%Developed economies, 58%

aIncludesintra-EUtrade.Source:WTOSecretariat.

impossible to calculate the share of the current 27countrymembership in1980sincesomemembersdidnotexistat thattime(CzechRepublic,SlovakRepublic,Slovenia and the Baltic states) but the enlarged tradebloc’ssharein2011was34percent,whichisstill lessthanthe1980shareofthe15countrymembership.

Similar trends can be observed on the import side,whichisillustratedbyFigureB.6.Theriseintheshareof developing and emerging economies in worldimports was nearly as dramatic as the rise on theexportside(from29percentin1980to42percentin2011) although the final share was smaller. China’sshareinworldimportswasslightly lessthanitssharein world exports in 2011 (10 per cent rather than11 per cent) but India’s share in imports was larger(3percentcomparedwith2percent).

The United States’ contribution to world importsactuallyincreasedslightly,from12percentin1980to13percentin2011despiteanoverallreductionintheshare of developed economies from 71 per cent to58 per cent. Japan saw some slippage in its importsharefrom7percentto5percent,whiletheEuropeanUnion’ssharedroppedfrom41percentto30percentduring thesameperiod.Aswithexports, theshare in2011onlyreferstothe15pre-enlargementcountries.

Increased exports contributed to higher GDP growthin developing economies between 1980 and 2011,while rising incomessupportedexpanded imports.Toillustratetheparalleldevelopmentoftradeandoutputin developing countries, shares of developed anddeveloping economies in world GDP are shown inFigureB.7,bothatpurchasingpowerparity(PPP)andatcurrentprices.Theshareofdevelopingeconomies

in GDP at PPP rose from 31 per cent in 1980 to52 per cent in 2011. Equivalent shares at currentexchangeratesweresmaller,24percentin1980and39 per cent in 2011. The fact that the share ofdeveloping economies in world imports in 2011remained well below the 50 per cent share of theseeconomiesinworldGDPatPPPmaybeexplainedbythefactthattheabilitytopurchasegoodsandservicesfromothercountriesdependsmoreonthedollarvalue

FigureB.7:Shares of developed and developing economies in world GDP, 1980-2011 (percentage)

0

30%

1980

25

9

31

4

29

2011 1980 2011

Purchasing power parity Current prices

50%

70%

90%

100%

20%

40%

60%

80%

10%

United States Japan European UnionOther developed economies ChinaOther developing and emerging economies

19

6

20

3

14

37

26

10

34

5

22

22

8

25

6

10

28

Source:IMFWorldEconomicOutlookdatabase,October2012.


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TableB.3:Leading merchandise exporters, 1980-2011 (US$billionandpercentage)

2011 1980

Value RankShare

in worldRank

Share in world

World 18,255.2 - 100.00 - 100.00

China 1,898.4 1 10.40 30 0.89

UnitedStates 1,480.4 2 8.11 1 11.09

Germanya 1,472.3 3 8.06 2 9.48

Japan 822.6 4 4.51 3 6.41

Netherlands 661.0 5 3.62 9 3.64

France 596.1 6 3.27 4 5.70

Korea,Republicof 555.2 7 3.04 32 0.86

Italy 523.2 8 2.87 7 3.84

RussianFederation 522.0 9 2.86 - -

Belgiumb 476.7 10 2.61 11 3.17

UnitedKingdom 473.2 11 2.59 5 5.41

HongKong,China 455.6 12 2.50 22 1.00

Domesticexports 16.8 - 0.09 - 0.67

Re-exports 438.8 - 2.40 - 0.33

Canada 452.4 13 2.48 10 3.33

Singapore 409.5 14 2.24 26 0.95

Domesticexports 223.9 - 1.23 -

Re-exports 185.6 - 1.02 - 0.33

SaudiArabia,Kingdomof 364.7 15 2.00 6 5.36

Mexico 349.6 16 1.91 31 0.89

Spain 308.7 17 1.69 21 1.02

Taipei,Chinese 308.3 18 1.69 24 0.98

India 304.6 19 1.67 45 0.42

UnitedArabEmirates 285.0 20 1.56 17 1.08

Australia 270.4 21 1.48 18 1.08

Brazil 256.0 22 1.40 23 0.99

Switzerland 234.4 23 1.28 13 1.46

Thailand 228.8 24 1.25 48 0.32

Malaysia 227.0 25 1.24 39 0.64

Indonesia 200.6 26 1.10 20 1.08

Poland 187.4 27 1.03 34 0.84

Sweden 187.2 28 1.03 12 1.52

Austria 178.0 29 0.97 33 0.86

CzechRepublic 162.3 30 0.89 - -

Norway 159.3 31 0.87 29 0.91

Turkey 134.9 32 0.74 67 0.14

Iran 131.5 33 0.72 40 0.61

Ireland 126.9 34 0.70 46 0.41

Nigeria 116.0 35 0.64 15 1.28

Qatar 114.3 36 0.63 50 0.28

Denmark 113.3 37 0.62 35 0.82

Hungary 112.2 38 0.61 44 0.42

Kuwait,theStateof 103.5 39 0.57 25 0.97

VietNam 96.9 40 0.53 124 0.02

Memo

EuropeanUnionc 6,038.60 - 33.08 - 37.06

intra-trade 3,905.71 - 21.40 - 22.55

extra-trade 2,132.89 - 11.68 - 14.51

Source:WTOSecretariat.

aGermanyreferstoWestGermanyin1980.bBelgiumreferstoBelgium-Luxembourgin1980.cEuropeanUnionreferstoEU27in2011andEU15in1980.


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TableB.4:Leading merchandise importers, 1980-2011 (US$billionandpercentage)

2011 1980

Value RankShare

in worldRank

Share in world

World 18,437.7 - 100.00 - 100.00

UnitedStates 2,265.9 1 12.29 1 12.38

China 1,743.5 2 9.46 22 0.96

Germanya 1,253.9 3 6.80 2 9.06

Japan 855.0 4 4.64 3 6.81

France 713.9 5 3.87 4 6.50

UnitedKingdom 637.8 6 3.46 5 5.57

Netherlands 598.7 7 3.25 7 3.76

Italy 557.5 8 3.02 6 4.85


HongKong,China 510.9 10 2.77 18 1.11

Retainedimports 130.2 - 0.71 - 0.79

Canada 462.6 11 2.51 10 3.01

India 462.6 12 2.51 33 0.72

Belgiumb 461.4 13 2.50 8 3.46

Spain 374.2 14 2.03 12 1.64

Singapore 365.8 15 1.98 17 1.16

Retainedimports 180.2 - 0.98 - 0.83

Mexico 361.1 16 1.96 21 1.07


Taipei,Chinese 281.4 18 1.53 23 0.95

Australia 243.7 19 1.32 19 1.08

Turkey 240.8 20 1.31 51 0.38

Brazil 236.9 21 1.28 15 1.20

Thailand 228.5 22 1.24 47 0.44

Switzerland 208.3 23 1.13 11 1.75

Poland 207.7 24 1.13 26 0.92

UnitedArabEmirates 205.0 25 1.11 49 0.42

Austria 191.0 26 1.04 16 1.18

Malaysia 187.7 27 1.02 40 0.52

Indonesia 176.9 28 0.96 39 0.52

Sweden 176.0 29 0.95 13 1.61

CzechRepublic 151.6 30 0.82 - -


SouthAfrica 121.6 32 0.66 24 0.94

VietNam 106.7 33 0.58 89 0.06

Hungary 102.6 34 0.56 48 0.44

Denmark 97.8 35 0.53 25 0.93

Norway 90.9 36 0.49 28 0.82

Finland 84.1 37 0.46 30 0.75

Ukraine 82.6 38 0.45 - -

Portugal 80.3 39 0.44 46 0.45

SlovakRepublic 77.3 40 0.42 - -

Memo

EuropeanUnionc 6,255.6 - 33.93 - 40.82

intra-trade 3,905.7 - 21.18 - 21.99

extra-trade 2,349.9 - 12.74 - 18.82


aGermanyreferstoWestGermanyin1980.bBelgiumreferstoBelgium-Luxembourgin1980.cEuropeanUnionreferstoEU27in2011andEU15in1980.


62

ofnational income thanon relativestandardof living.China’sshareinworldimportsisalsomorecomparableto itsshare inworldoutputatmarketexchangeratesthantoitsshareatPPP.

The greater prominence of Asian developingeconomies, such as China, India and the Republic ofKorea, in world trade has already been noted in thediscussionofFiguresB.5andB.6.Equallynoteworthyare thestrongdeclines insharesand ranks recordedby other economies, particularly certain Europeancountriesandnatural resourceexporters,onboththeexportandimportsides.

Tables B.3 and B.4 show ranks and shares in worldmerchandise exports and imports for selectedeconomies between 1980 and 2011, includingindividual EU member states. Starting on the exportside,wesee thatFrancewent frombeing the fourth-largestexporterofgoodsin1980witha5.7percentshareinworldtradetothesixthlargestexporterwitha3.3 per cent share in 2011. The United Kingdomexperienced an even steeper decline, dropping fromfifthplace inworldexportswith5.4percentofworldtradeto11thplaceandjust2.6percentofworldtradebetween 1980 and 2011. Switzerland’s 1.5 per centshare of world exports in 1980 was big enough tosecure it13thplace in theglobalexport rankings,butby 2011 the country’s share had dropped to 1.3 percentanditsrankto23.MostdramaticofallhasbeenSouth Africa’s slide in world trade. The country’sexports constituted 1.3 per cent of world trade in1980,whichwasgoodenoughtoearnit16thplaceinworld export rankings. However, by 2011 SouthAfrica’ssharehadplunged to just0.5percent,whileitsrankinworldexportsplummetedto41.

Turningtoimports,weseethatFranceandtheUnitedKingdom have mostly managed to maintain theirpositions inworldmerchandise tradesince1980,butSwitzerland, Austria, Sweden, the Kingdom of SaudiArabia and Nigeria have all fallen in world rankings.The diminished importance of natural resourceexporters in world imports may seem strange at firstglance, considering the high prices for fuels andmining products that have prevailed in recent years,but itmakesmoresensewhenoneconsiders thatoilprices adjusted for inflation were actually higher in1980 than they were in 2011. As for the Europeancountries thathaveslid inworld rankings, theysimplyappear to have been overtaken by developingeconomies with rising incomes, including Singapore,ChineseTaipei,ThailandandBrazil.

Finally,nodiscussionofnewandoldplayers inworldtrade can neglect the rise of new suppliers andconsumersofcommercialservices inrecentdecades.WTO data on total commercial services exports forselected economies in 1980 and 2012 are shown inTablesB.5andB.6,alongwiththeirranksandsharesinworldtrade.Itshouldbenotedthatthesestatistics,

which are derived from balance of payments data,cover only three out of the four modes of supplydefinedintheGeneralAgreementonTradeinServices(GATS). These data include information on cross-border supply of services (mode 1), consumption ofservices abroad (mode 2), and presence of naturalpersons(mode4)but theyexcludeservicesdeliveredthroughforeignaffiliates(mode3).Informationonthislast category is partially captured by statistics onforeigndirectinvestment(FDI),whicharediscussedinSectionB.2(e).

InTableB.5,weseeonceagain thatAsianexportershaverisentoprominenceasChina,IndiaandChineseTaipei have climbed in world export rankings. TheRepublic of Korea is also a leading exporter ofcommercial services but it already counted itselfamongthetop20in1980.Irelandwasthe12thlargestexporterof services in2011,up from38thposition in1980.Italy,AustriaandNorwaymovedintheoppositedirection, fallingsharply inworld rankings.Otherwise,the relative positions of countries in global servicesexportshavechangedlittlesince1980.

TableB.6tellsasimilarstoryontheimportside.Asianeconomies such as China, India, Singapore, theRepublic of Korea and Thailand have risen sharply inworld rankings, as have Ireland and the United ArabEmirates. Meanwhile, the strongest declines wererecordedbySwedenandtheKingdomofSaudiArabia.

(ii) Trade within and between developed and developing economies

Another aspect of the changing country compositionoftradeistheamountoftradethatgoesonwithinandbetween groups of countries. In this context, thedeveloped economies are customarily referred to asNorthanddeveloping/emergingeconomiesasSouth,with trade between the developed and developing/emerging groups, for example, denoted by the termNorth-Southtrade.

FigureB.8showssharesofNorth-North,South-Southand North-South trade in exports of manufacturedgoodssince1990.Natural resourcesareexcluded toavoidhavingfluctuationsincommoditypricesskewtheshares.Asthechartmakesclear, theshareofNorth-North tradehasdroppedsteadily from56percent in1990 to 36 per cent in 2011. This decline coincidedwith rising South-South trade, which increased from8percentto24percentoverthisinterval.Theshareof North-South trade remained remarkably steadysince2000ataround37percent.

TherisingshareofSouth-Southtradeinworldexportscanbeexplainedbyanumberoffactors,oneofwhichisthenumberofPTAsnegotiatedbetweendevelopingeconomies.Suchagreementsactuallyaccountforthemajority of new PTAs concluded since 1990 (WTR,2011). Even if some of these PTAs are not fully


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implemented, greater openness and reduced barriersto trade between developing economies is stillexpectedtoleadtomoreSouth-Southtrade.

Alessstraightforwardbutmorecompellingexplanationfor thepatternobserved inFigureB.8has todowiththe nature of countries’ preferences: if developingeconomies have non-homothetic preferences (i.e.consumers desire a greater variety of goods as theybecome wealthier), they may start to produce andconsumemoreandmoresimilarbundlesofgoodsastheir incomes rise. If this is indeed the case, thenrapidly growing developing economies would beexpectedtotrademorenotonlywithoneanotherbutalso with the developed economies that theyincreasingly resemble. This would explain both therisingshareofSouth-SouthtradeandthefallingshareofNorth-Northtradeinglobalexportsofmanufacturedgoods. This result may depend strongly on how the“developed” and “developing” country groups aredefined, since reclassifying newly industrializedeconomies in Asia as developed might instantly halttheslideinthe“North-North”shareinworldtrade.

(iii) Is world trade dominated by a few large countries?

Another question related to new and old players inworld trade is whether trade is dominated by a largenumberofsmallcountriesorasmallnumberof largecountries. The answer to this question has importantimplications for beliefs about the fairness of theinternationaltradingsystem,sincesmallcountriesmayfeel that they cannot benefit from trade if they areoverwhelmedbyafewlargetradersandviceversa.

The Gini coefficient is an indicator most oftenemployedtomeasureincomeinequality,butitcanalsobe used to measure disparities in international tradeflows. The Gini coefficient is based on the Lorenzcurve, which can depict the concentration of anypopulation,forexamplecountrysharesinworldtrade.Insuchacurve,exportersarerankedfromsmallesttolargest and their cumulative rank in world exports(expressed as a percentage) is plotted against theircumulativeshare inworldexports.Theblueandlight-blue curves in Figure B.9 are examples of Lorenz

TableB.5:Leading exporters of commercial services, 1980-2011 (US$billionandpercentage)

2011 1980

Value Rank Share Rank Share

World 4,168.8 - 100.00 - 100.00

UnitedStates 580.9 1 13.93 2 10.38

UnitedKingdom 273.7 2 6.57 3 9.34

Germanya 253.4 3 6.08 4 7.57

China 182.4 4 4.38 31 0.55

France 166.6 5 4.00 1 11.48

Japan 142.5 6 3.42 6 5.11

Spain 140.3 7 3.37 9 3.12

India 136.6 8 3.28 25 0.78

Netherlands 133.5 9 3.20 7 4.55

Singapore 128.9 10 3.09 17 1.30

HongKong,China 121.4 11 2.91 15 1.60

Ireland 109.4 12 2.62 38 0.36

Italy 105.2 13 2.52 5 5.13

Switzerland 94.3 14 2.26 14 1.88


Belgiumb 87.3 16 2.10 8 3.13

Sweden 76.0 17 1.82 12 2.01

Canada 74.5 18 1.79 13 1.94

Luxembourg 72.5 19 1.74 - -

Denmark 64.8 20 1.55 19 1.28

Austria 61.2 21 1.47 10 2.35


Australia 50.9 23 1.22 23 1.00

Taipei,Chinese 46.0 24 1.10 33 0.53

Norway 41.9 25 1.00 11 2.32


Note:Ranksinworldtradein2011arenotcomparabletoranksin1980duetonumerouschangesinnationalboundaries.Asaresult,strongconclusionsshouldnotbedrawnfromsmallchangesinranks.

aGermanyreferstoWestGermanyin1980.bBelgiumreferstoBelgium-Luxembourgin1980.


64

curves for 1980 and 2011. The fact that both curves(nearly) pass through thepoint78,10means that the78 per cent of countries with the smallest exportvalueswereonly responsible for10percentofworldexports in both periods. Looked at from anotherperspective, it also means that the 22 per cent ofcountries with the largest export values wereresponsibleforaround90percentofworldexportsinbothyears.

The diagonal line represents an equal distribution ofexportsacrosscountries,suchthat,iftheLorenzcurvewere on this line, 40 per cent of exporting countrieswould be responsible for 40 per cent of exports,75percentofexporterswouldaccountfor75percentoftheexports,andsoon.Forthistobethecase,eachcountrywouldhavetoexportexactlythesameamount,which is clearly unrealistic. The other extreme, whichwouldrequireasinglecountrytoexportalloftheworld’sgoods, isequally implausible.However,aLorenzcurvethat is closer to the diagonal would represent a moreequaldistributionofexportsacrosscountries.TheGinicoefficient is defined as the area between the Lorenz

curveand thediagonaldividedby the totalareaunderthediagonal,sothataGiniscoreof0wouldindicateanequaldistributionofexports(i.e.allcountriesexportingthesameamount)whileaGiniscoreof1wouldsuggestperfectinequality(i.e.asingleexporter).

The Gini coefficients of 0.83 for 1980 and 0.82 for2011 derived from Figure B.9 suggest that trade isveryunequallydistributedand that this inequalityhashardlychangedatallinmorethan30years.However,a different picture emerges if we plot countries’cumulative percentages in world population (rankedfrom smallest to largest) against their share in worldtrade. In this case, the concentration curves actuallyreach beyond the diagonal. In principle, such a curvecould even cross the diagonal, which makesinterpretation difficult. What it suggests is thatcountrieswithsmallpopulationsareresponsibleforadisproportionateshareofworldexports,whereaslargecountries’ contributions to world trade are less thantheir contributions to the world’s population. The factthatthepopulationexportscurvemovedclosertothediagonalbetween1980and2011 is indicativeof the

TableB.6:Leading importers of commercial services, 1980-2011 (US$billionandpercentage)

2011 1980

Value Rank Share Rank Share

World 3,953.0 - 100.00 - 100.00

UnitedStates 395.3 1 10.00 4 7.16

Germanya 289.1 2 7.31 1 10.73

China 236.5 3 5.98 41 0.51

UnitedKingdom 170.4 4 4.31 5 6.25

Japan 165.8 5 4.19 2 7.95

France 143.5 6 3.63 3 7.69

India 123.7 7 3.13 30 0.72

Netherlands 118.2 8 2.99 6 4.40

Ireland 114.3 9 2.89 47 0.39

Italy 114.0 10 2.88 7 3.89

Singapore 113.8 11 2.88 31 0.72

Canada 99.8 12 2.53 10 2.50


Spain 93.2 14 2.36 17 1.34


Belgiumb 84.6 16 2.14 9 3.07

Brazil 73.1 17 1.85 23 1.10

Australia 59.5 18 1.51 14 1.57

Denmark 56.1 19 1.42 28 0.86

HongKong,China 55.7 20 1.41 25 1.00

Sweden 55.6 21 1.41 11 1.72


Thailand 50.9 23 1.29 46 0.40

UnitedArabEmirates 48.8 24 1.23 - -

Switzerland 46.9 25 1.19 21 1.21


Note:Ranksinworldtradein2011arenotcomparabletoranksin1980duetonumerouschangesinnationalboundaries.Asaresult,strongconclusionsshouldnotbedrawnfromsmallchangesinranks.

aGermanyreferstoWestGermanyin1980.bBelgiumreferstoBelgium-Luxembourgin1980.


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FigureB.8:Shares of “North-North”, “North-South” and “South-South” trade in world merchandise exports, 1990-2011 (percentageshare)

0%

20%

1990 1995 2000 2005 2008 2009 2010 2011

40%

60%

80%

100%

10%

30%

50%

70%

90%56

33

8

North-North North-South South-South Unspecified destinations

51

35

12

50

36

12

46

37

16

41

37

20

40

37

21

37

38

23

36

38

24


Note:SouthincludesCentralandEasternEuropebefore2000,equalto1.6percentofworldtradein1995.

FigureB.9:Concentration of world merchandise exports, 1980-2011 (cumulativepercentageshares)

Per cent of world exports plotted against per cent of countries, 1980

Per cent of world exports plotted against per cent of countries, 2011

Per cent of world exports plotted against per cent of world population, 1980

Per cent of world exports plotted against per cent of world population, 2011

0

0 10 20 30 40 50 60 70 80 90 100

10

Per

cen

t of w

orld

mer

chan

dise

exp

orts

Per cent of countries, per cent of world population

20

40

60

70

80

90

100

30

50

Source:WTOSecretariatestimates.

fact that large countries like India and China did notexportmuchtotherestoftheworldin1980buttheywereexportingmuchmorein2011.

Making comparisons between these curves and Ginicoefficients in 1980 and 2011 is complicated by thefact that the number of traders has increased overtimeduetothebreak-upofseveralcountriesandtheamalgamationofothersfollowingtheendof theColdWar.AsKrugmanobserves,“itisusefultothinkaboutworldtradebyimaginingthatitwerepossibletotakeagiven geography of world production andtransportation and then draw arbitrary lines on themap called national borders without affecting theunderlying economic geography” (Krugman, 1995).Indeed, Cuaresma and Roser (2012) find that about1 per cent of measured trade today is simply due tochanges in national borders since the Second WorldWar; inotherwords, thisamountof trade, considered“international”today,wouldhavebeen“domestic”tradeonamapof1946.Inthesamevein,Llano-Verdurasetal.(2011)showthatthefactthatcountriestrademuchmore with themselves than with other partners (theborder effect) decreases substantially once theartificial nature of geographical aggregations isproperlytakenintoaccount.

The problem of changing national boundaries isaccountedforinFigureB.9byusingamatchedgroupof countries in both periods. Countries that broke upbetween1980and2011(e.g.theformerSovietUnion)are reconstructed in the secondperiodby taking thesum of trade flows from the successor countries andsubtracting intra-trade between them. On the otherhand,countriesthatamalgamated(e.g.EastandWestGermany)are rebuilt byaggregating their tradeflowsandsubtractingtradebetweentheminthefirstperiod.

Inthisway,wecanbefairlycertainthatanychangesinthefiguresarenotsimplyduetore-classifyingcertaintrade flows as international rather than domestic (orviceversa).


66

(b) Hasthecompositionoftradechanged?

Just as the relative importance of countries ininternational trade has shifted over time, so has themix of traded goods and services. This sub-sectionexamines theevolvingcompositionof trade, includingtheproductbreakdownofmerchandise tradeand therelative importance of commercial services tradecomparedwithgoodsinrecentdecades.

(i) Evolution of trade by major product categories

For many years, the share of manufactured goods inworld merchandise trade increased relentlessly. Aswas already noted in the discussion of Figure B.3,manufacturesaccountedfor just40percentoftradein1900, but this rose to70per cent in1990and to75percentin2000beforefallingbackto65percentin 2011. In contrast to manufactures, agriculturalproducts saw their share in world trade fall steadily

over time, from 57 per cent at the turn of thelast century to 12 per cent in 1990, and finally to9 per cent in 2011. The advance of manufacturedgoods was only slowed by rising primary commodityprices, which in recent years have tended to inflatesharesforfuelsandminingproductsattheexpenseofmanufactures. Unlike both agricultural products andmanufactured goods, the share of fuels and miningproductsinworldtradehasexhibitednocleartrendinthepost-SecondWorldWarperiod,asitrisesandfallsinstepwithoilprices(seeBoxB.2).

Among sub-categories of manufactured goods, onlychemicalsandofficeandtelecomequipmentrecordedhighersharesinworldtradein2011thanin1990(seeFigure B.10). Most other goods, including automotiveproducts, textiles and clothing, saw their sharesdecline,butironandsteel’ssharewasunchanged.

Product shares in world trade may paint a misleadingpictureof thecontributionofdifferentclassesofgoods

BoxB.2: Trends in world commodity prices

Fluctuationsinprimarycommoditypricesovertimecanhaveimportantimplicationsfortheexportearningsofdevelopingcountriesaswellas for their foodsecurityandaccess to industrial inputs.According to theInternational Monetary Fund’s Primary Commodity Statistics database (www.imf.org/external/np/res/commod/index.aspx,10January2013),globalfoodpricesmorethandoubledbetweenJanuary2000andDecember2012,rising214percent.Bycomparison,thepricesofagriculturalrawmaterialsonlyrose40percent during this period. Food prices were characterized by occasional spikes and boom-bust cycles. Forexample,betweenJuneandDecember2008foodprices fell32percent,whereas theyadvanced37percentbetweenFebruary2010andFebruary2011.Evenmoreextremefluctuationscanbeobservedinpricesof mining products, which climbed 293 per cent between January 2000 and December 2012, and fuels,which jumped396per centover this period.Meanwhile, pricesofmanufacturedgoodsonly increasedbyaround20percentduringthesameperiod.

Although primary product prices have tended to increase since around 2000, they recorded a long-termdeclineduringthe1980sand1990s.BetweenJanuary1980andJanuary1999,pricesofmetalsandfuelsdeclinedby41percentand71percent,respectively.

Forfurtherdiscussionoftheimplicationsofcommoditypricesforfoodsecurityindevelopingcountries,seeSectionE.2.

FigureB.10:Shares in world merchandise exports by product, 1990-2011 (percentage)

1990

Others, 29%

Automotive products,10%

Textiles, 3%

Clothing, 3%

Agricultural products, 12%

Fuels and miningproducts, 14%

Office and telecom equipment, 9%

Iron and steel, 3%

Chemicals, 9%

Other semi-manufactures,8%

2011

Others, 15%

Automotiveproducts, 7%

Industrialmachinery,

12%

Clothing, 2%

Agricultural products, 9%

Fuels and mining products, 23%

Office and telecomequipment, 10%

Iron and steel, 3%

Chemicals, 11%

Other semi-manufactures,6%

Textiles, 2%



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toworldtradegrowth,sincetheyarestronglyinfluencedbyfluctuationsincommoditypricesandexchangerates.As a result, it makes sense to look at the data fromanotherperspective that takes theeffect of prices intoaccount. This is provided by Figure B.11, which showsworldmerchandisetradevolumeindicesbymajorproductcategory since 1980. These indices are derived fromexportandimportvolumeindicesforindividualcountries,whichareinturncalculatedbydividinggrowthinnominaltradevaluesbychangesinexportandimportprices(seeWTO World Trade Report 2012 for detailed notes onmethodology). This gives a reliable global estimate of“real”physicalquantitiesofgoodstradedovertime.

By this measure, the volume of world exports morethanquadrupledbetween1980and2011,withmostofthe growth attributable to increased shipments ofmanufactured goods. Indeed, manufactures recordedanearsix-fold increasesince1980,whileagriculturalproducts only increased 2.6 times and fuels only2.1 times. The main disadvantage of these volumeindices is that no detailed breakdown by product ispossible beyond the three broad categories ofagricultural products, fuels and mining products, andmanufacturedgoods.

(ii) Creation and destruction of old and new products

Merchandisetradestatisticsdonotalwaysaccuratelyreflect the current product composition of tradebecause new products are constantly being createdand older ones are constantly slipping intoobsolescence.Statisticiansfromgovernmentagenciesand international organizations try to keep up with

these developments by regularly updating statisticalclassificationsoninternationaltrade,usuallyeveryfiveyears. The World Customs Organization is chargedwith maintaining the most widely used classification,the Harmonized System (HS). During a revision,HScodesmaybeaddedtoaccountfortradeinneworchangedproducts,orelse theymaybedeletedwhentradeinaparticulargoodfallstoaverylowlevelforanumber of years. When codes are removed from theclassification,remainingtradeinthatgoodisallocatedtooneormoreothersub-headings,whichcanresultinchangesinscopeforexistingHScodes.

TableB.7showschangesintheHStradeclassificationbetween its 1992 and 2007 revisions. New sub-headingswereaddedduringthisperiodtoaccountfortrade inendangeredspeciesandalso to trackgoodsthat are subject to international agreements (e.g.persistent environmental toxins controlled under theStockholmConvention).Forexample,thesub-heading021090which represented “Meatandedibleoffal” intheHS1992classificationwasreplacedby thecodes021091(“Meatandedibleoffalofprimates”),021092(“Meatandedibleoffalofwhales/dolphins/porpoises/etc.”), 021093 (“Meat and edible offal of snakes/turtles/etc.”),and021099(“Meatandedibleoffalnotelsewherespecified”) inHS2007.New,moredetailedcodes were also added for various species of fish,e.g. salmon, tuna, swordfish,etc., aswell as formanyvarietiesofplants.Significantchangeshavealsobeenintroduced in technology-related headings forcomputers,printing,etc.

In some cases, a product’s share in world trade mayhave fallen substantially without its code being

FigureB.11:Volume of world merchandise exports by major product category, 1980-2011 (index,1980=100)

Manufactures Total merchandisea Agricultural products Fuels and mining products

0

100

19

80

19

81

19

83

19

85

19

87

19

89

19

91

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93

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500

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82

19

84

19

86

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88

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90

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92

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94

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aIncludesunspecifiedproducts.Source:WTOSecretariat.


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removed.Thisoccurredbetween1996and2011foranumber of controlled substances, such as carbontetrachloride,demandforwhichhasfallensharplydueto the fact that it is a precursor chemical for ozone-depletingchlorofluorocarbons(CFCs).

Magnetic tape-based video recorders have seen theirshareinworldtradefallfrom0.251percentin1996to0.002percentin2011,adeclineof99percent.Despitethis collapsing share, these devices have retained theirown six-digit HS sub-heading, at least till the 2007versionoftheclassification.However,obsoleteproductssuch as this will eventually be deleted, possibly in theforthcomingHS2012classification.

Photographic film cameras, including instant filmcamerasand35mmcameras(900640and900651-59), also saw their share in world trade dropprecipitously from 0.105 per cent in 1996 to0.002percentin2011.Similardeclinesalsooccurredforotherfilmphotographyrelatedproducts,includingslide projectors (900810), photographic enlargers(900840)andautomatic filmdevelopmentmachines(901010).

At theproduct level, tradegrowthcanbeattributed tochangesintheintensivemargin(i.e.moreorlesstradeinexistingcategoriesofgoods)ortheextensivemargin(i.e. more or less trade in new products, or thedisappearanceofoldproducts).Contributionsof these

marginstoworldtradeinmanufacturedgoodsbetween1991and2011areshowninFigureB.12.Theextensiveand intensive margins can be defined in a number ofdifferentwaysbut for thepurposesof this sectionweconsider the intensive margin to be trade in productsthatexisted inboth revisions3and4of theStandardInternational Trade Classification (SITC) and whoseshareinworldtradeneitherrosesharply(+100percentor more) nor fell dramatically (-75 per cent or more)between 1991 and 2011. All other changes areattributed to the extensive margin. Note that onlymanufactured goods are considered in Figure B.12 inordertoavoidtheproblemofsharesfallingduetorisingcommodityprices.

It is clear from the chart that most of the growth ofworld trade in manufactures in recent decades wasduetotheintensivemarginoftrade(76percent)butthe fact that nearly a quarter (24 per cent) of theincreaseduringthisperiodwasrelatedtotheextensivemargin is still significant. Unfortunately, it is notpossibletosayexactlywhichnewproductscontributedhow much to this growth, since many have yet to beincluded in statistical classifications. This situationmay be improved in 2013 when many countries willbeginreportingdatainaccordancewiththenew2012versionoftheHarmonizedSystem.Theextensiveandintensivemarginscanalsobedefinedintermsoffirmsentering new markets and producing new products.SeeSectionB.2(f)foradiscussionofthisliterature.

TableB.7:New and old products in international trade

Products deleted due to low volume of trade between HS1992 and HS2007

Horse hair (050300), natural sponges (050900), asbestos (252400), lead carbonate (283670), rolls of instant print film (370220),photographic film in rolls (370292), equinehides/skins (410140), articlesof catgut (420610),wholebeaver furskins (430140),wholesealfurskins(430170),carbonpaper(480910and481610),punchcardsformachinereading(482330),bowties(611720),headgearoffurskin (650692), articles containing asbestos (numerous subheadings under headings 6811 and 6812), lead pipes (780500), phototypesetting machines (844210), several products related to printing under heading 8443, shuttles for weaving machines (844841),typewriters and word-processing machines (several subheadings under heading 8469), vinyl record players (several products underhading8519),casettetaperecorders/players(severallinesunderheading8520),magnetictapes(852311-13),cigarorcigaretteholders(961490)

Products retained despite reduced shares in world trade between HS1992 and HS2007

Sardines(0302610),dogfishandothersharks(030265),eels(030266),snails(030760),opium(130211),cottonseedoil(151221),naturalbariumcarbonate (251120),wasteoilscontainingpolychlorinatedbiphenylsorPCBs (271091), leadmonoxide (282410),heavywaterordeuteriumoxide(284510),carbontetrachloride(290314),hexachlorobenzeneandDDT(290362),numerousphotographicfilmandpaperproductsundertheheading3702-3705,anti-knockenginepreparationsbasedonleadcompounds(381111),rawfurskinsoffox(430160),dictionariesandencyclopedias (490191),silver tableware (821591),magnetic tapevideo recorders (852110),photographicfilmcameras(900640and900651-59).

Additions to the HS classification to represent new/rising/regulated products in world trade

Liveprimates(010611),livewhales/dolphins(010612),livereptiles(010620),livebirdsofprey(010631),detailedbreakdownsformanyfishproductsundertheheadings0303and0304,detailedbreakdownsforcutflowersunderheading0603,cocaleaf(121130),semi-conductormedia including “smart cards” (852351-59), dental floss (330620), pulp from recyled paper/cardboard (470620), car air conditioners(841520),variouscodesrelatedtoprintersundertheheading8443,portablecomputers(847130),industrialrobots(847950),machinesformanufacturing semiconductors and integrated circuits (848620), machines and apparatus for the manufacture of flat panel displays(848630), wind-powered electric generating sets (850231), line telephones with cordless handsets (851711), telephones for cellularnetworks(851712),safetyairbags(870895).

Other products whose shares in world trade have risen significantly between HS1992 and HS2007

Connectorsforopticalfibres(853670),colordata/graphicdisplays(854040),otherliquidcrystaldisplaydevices(901380),anthracitecoal(270111)aswell asothergradesof coal, liquifiednaturalgas (271111), rareearthmetals (280530), ethyleneglycol (290531), umbrellaframes(660310),household/laundry-typewashingmachines(845020).

Source:UNComtradedatabase.


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(iii) Intra-industry trade

Theneoclassicaltradetheory,presentedinSectionB.2(c),is useful for explaining many aspects of internationaltrade but it fails to capture a number of importantphenomena, particularly trade within industries (intra-industry trade).Forexample, thefact thatGermanyandJapan both export cars to one another is difficult toaccountforinatheoreticalframeworkwherecomparativeadvantage leads tohigh levelsofspecialization.Modelsthat address monopolistic competition, particularlyKrugman’s influential (1979)model,arenoteworthydueto the fact that they naturally give rise to intra-industrytrade,i.e.countrypairsmayexportandimportthesametypesofgoods.

Krugman’s key assumptionsare increasing returns toscale technology and “love-of-variety” preferences.19Increasing returns to scale20 are modelled byintroducing a fixed cost of production: when a firmexpands its total output, even holding the unit costconstant,thefixedcostwillbedistributedoveralargernumberofunits,andthusaveragecostdeclines.Inthisset-up, concentration of production is efficient. Thiscontrastswiththeexistenceofmanyproducerswithinanindustry.Toreconcilethesetwodivergentfeatures,Krugman assumes monopolistic competition acrossfirms. Inotherwords,producerssellproductsthatareslightly differentiated – different brands or quality –butnotperfectsubstitutes.Therefore,whileeachfirmisassumedtobeamonopolistforitsownvariety,itisstillsubjecttocompetitionfromotherfirms–itcansellless of its variety, the larger the number of othervarieties sold. Krugman’s model allows countries togain from trade by accessing a greater variety ofgoods and by capturing economies of scale inproduction. This approach has firms specializing invarieties of goods but it may also be applicable to21st-centurytradewherefirmsmay insteadchoosetospecializeincertaintasks.

A common measure of the amount of intra-industrytrade that takes place between countries is theGrubel-Lloyd(GL)indexwhichisdefinedasfollowsforagivenproducti:

GLi=1-(|exporti–importi|/(exporti+importi))

Ifacountryonlyexportsorimportsgoodi,thentheGLindexforthatsectorisequalto0.Ontheotherhand,ifa country imports exactly as much of good i as itexports,thenitsGLscoreforsectoriwouldbe1.

In Table B.8, Grubel-Lloyd indices were calculated forall four-digit codes in theStandard InternationalTradeClassification(SITC)forallavailablereportersintheUNComtrade database against the world developed anddevelopingeconomiesin1996and2011.ThearithmeticmeanwasusedtocalculateasimpleaverageGLscoreforeachcountryandpartner,whichshouldbesufficientto provide an indication of which countries engage inrelatively more or less intra-industry trade. Countrieswere then sorted in descending order according tooverallGLscoresin2011.

The main messages from this table are thatindustrialized developed economies (e.g. the UnitedStates,theEuropeanUnion,CanadaandSwitzerland)and rapidly industrializing developing economies (e.g.HongKong,China;Singapore;MalaysiaandThailand)tend to engage in more intra-industry trade, whereasresource-rich developing economies (e.g. Algeria,Nigeria, Bolivarian Republic of Venezuela) and LDCs(Central African Republic, Niger and Madagascar)tend to have relatively little intra-industry trade. FewsignificantchangesinaverageGLscoresareobservedbetween 1996 and 2011, the main exceptions beingPanamaandEgypt.DevelopedeconomiessuchastheUnitedStatesandtheEuropeanUnionengageinmoreintra-industry trade with other developed economies,whereasdevelopingeconomiessuchasMalaysiaandThailand have more intra-industry trade with otherdevelopingcountries.

Despite the fact that China and the Republic of Koreaare designated as developing economies, they areactually more similar in structure to developedeconomies,sincetheyhavesucceededinindustrializing,while many poorer and resource-rich developingeconomies have not. Japan is also something of anoutlierinthesetablesinthatitsaverageGLscoreisquitelow compared with other developed economies, and ithasmoreintra-industrytradewithdevelopingeconomies.Its low overall GL score could be due to the fact thatJapanhasfewnaturalresourcesandhastoimportmostrawmaterials.Thecountry’srelativelyhighlevelofintra-industry trade with developing economies might beexplained by geographic proximity to developing Asianeconomiesandtothefactthatmanyoftheseostensiblydevelopingeconomiesareinfactindustrialized.

As already noted in Section B.2(a), the nature ofcountries’preferencesoffersoneexplanation forwhy

FigureB.12:Contributions of intensive and extensive margins to growth in world trade in manufactures, 1991-2011 (percentage)

0%

20%

24

Intensive margin Extensive margin

40%

60%

80% 76

100%

Source:WTOSecretariatestimatesbasedonavailablereportersintheUNComtradedatabase.


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TableB.8:Average Grubel-Lloyd indices across sectors for selected economies, 1996-2011 (Index,0-1)

1996 2011

World Developed Developing World Developed Developing

HongKong,China 0.70 0.29 0.65 0.66 0.30 0.61

Singapore 0.65 0.31 0.60 0.65 0.38 0.59

UnitedStates 0.61 0.65 0.47 0.62 0.68 0.51

EuropeanUnion(27) - - - 0.60 0.63 0.51

Malaysia 0.43 0.28 0.51 0.55 0.37 0.58

Canada 0.57 0.59 0.36 0.53 0.58 0.34

Switzerland 0.51 0.52 0.31 0.49 0.49 0.37

Thailand 0.36 0.26 0.44 0.49 0.38 0.53

Mexico 0.50 0.47 0.42 0.49 0.46 0.38

Korea,Republicof 0.42 0.35 0.35 0.48 0.43 0.42

Taipei,Chinese 0.44 0.34 0.38 0.48 0.40 0.48

India 0.34 0.30 0.34 0.44 0.39 0.43

Ukraine 0.43 0.30 0.44 0.43 0.27 0.44

SouthAfricaa 0.41 0.31 0.44 0.41 0.30 0.44

Brazil 0.43 0.32 0.43 0.41 0.33 0.43

China 0.39 0.33 0.40 0.40 0.38 0.36

Panama 0.12 0.08 0.13 0.39 0.12 0.47

Turkey 0.32 0.27 0.36 0.39 0.36 0.41

Japan 0.35 0.34 0.32 0.39 0.36 0.39

Indonesia 0.29 0.23 0.33 0.38 0.30 0.40

NewZealand 0.35 0.34 0.32 0.37 0.40 0.31

Norway 0.38 0.37 0.28 0.33 0.33 0.29

Argentina 0.36 0.21 0.43 0.32 0.19 0.39

Tunisia 0.26 0.18 0.36 0.32 0.26 0.32

CostaRica 0.26 0.14 0.31 0.32 0.18 0.34

Guatemala 0.29 0.12 0.38 0.31 0.11 0.39

Philippines 0.27 0.23 0.29 0.31 0.28 0.29

Colombia 0.29 0.16 0.39 0.31 0.18 0.36

Australia 0.39 0.38 0.39 0.30 0.34 0.31

Egypt 0.17 0.12 0.19 0.28 0.20 0.33

Chile 0.24 0.14 0.31 0.27 0.14 0.32

RussianFederation 0.38 0.26 0.47 0.26 0.20 0.33

Peru 0.18 0.13 0.21 0.26 0.16 0.29

Uganda 0.12 0.04 0.13 0.24 0.09 0.26

Pakistan 0.14 0.09 0.16 0.24 0.16 0.27

Senegal 0.11 0.06 0.20 0.21 0.10 0.26

KyrgyzRep. 0.34 0.07 0.36 0.20 0.06 0.23

Côted'Ivoire 0.22 0.09 0.32 0.19 0.08 0.22

Bahrain,Kingdomof 0.17 0.05 0.28 0.19 0.05 0.24

Ghana 0.11 0.06 0.19 0.19 0.11 0.18

Ecuador 0.19 0.11 0.24 0.18 0.10 0.21

Zambia 0.18 0.08 0.18 0.17 0.04 0.18

Albania 0.15 0.14 0.11 0.17 0.16 0.14

Madagascar 0.12 0.11 0.11 0.17 0.15 0.16

Kazakhstan 0.32 0.09 0.37 0.15 0.06 0.17

Nigeria 0.09 0.09 0.08 0.14 0.11 0.13

Azerbaijan 0.20 0.05 0.19 0.14 0.04 0.15

Iceland 0.08 0.07 0.09 0.13 0.13 0.14

Nicaragua 0.14 0.07 0.15 0.12 0.09 0.16

Paraguay 0.12 0.05 0.13 0.12 0.06 0.13

Bolivia,PlurinationalStateof 0.13 0.07 0.17 0.12 0.09 0.11

Niger 0.16 0.02 0.18 0.08 0.06 0.10

Venezuela,BolivarianRep.of 0.26 0.16 0.36 0.08 0.05 0.09

Algeria 0.08 0.06 0.12 0.05 0.04 0.04

CentralAfricanRep. 0.08 0.04 0.06 0.02 0.03 0.04

Source:WTOSecretariatestimatesbasedondataforavailablereportersintheUNComtradedatabase.

Note:AveragesaretakenacrossSITCRev.3productsatthe3-digitlevel.aSouthAfricareferstoSouthAfricanCustomsUnionin1996.


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similareconomiesoften trademorewithoneanother,andthisextendstointra-industrytradeaswell.Simpletrade models usually assume that countries havehomothetic preferences, which implies that budgetshareswillremainconstantregardlessoftheirlevelofincome. If this assumption is relaxed, countries withsimilar incomes will tend to consume and producesimilar types of goods. Linder (1961), for example,shows that firms producing in a rich country that isclose to a large consumer market for high-quality (orluxury) goods have a comparative advantage inproducing these goods. In addition, exporting firmsfind more extensive markets for their high-qualitygoodsinotherrichcountries.

Fieler (2011) also shows why poor countries, even ifsimilar in termsof income, trademuch lesswitheachothercomparedwithrichcountries.Hermodelshowsthat trade volumes between similar countries dependon how differentiated products are. Countries whereoverallproductivityislowhavelowwagesandproduceless differentiated goods. Technologically advancedcountrieshavehighwagesandproducegoodswhosetechnologies are more variable across countries. Inthis set-up, rich countries trade a lot with each otherbecause high-income-elastic goods are moredifferentiated,whilepoorcountriesdonottrademuchwitheachotherbecauselow-income-elasticgoodsarelessdifferentiated.

(iv) Trade in commercial services

As Section B.1 has shown, improved informationtechnologyandreducedtransportcostshavemade itpossible for firms to split manufacturing processesinto a series of tasks that can be carried out indifferent locations based on comparative advantage.These tasks extend to commercial services, many ofwhich (transportation, financial services) are closelylinkedtotradeingoods.Asaresult,itshouldnotcomeas a surprise that trade in commercial services hasgrowninlinewithtradeingoodsforthelast20years.

FigureB.13showsworldtradeincommercialservicesexports since 1980, both as dollar values and as ashare of world goods and services exports. Althoughservices trade grew faster than goods trade in the1980s and 1990s, the rate of increase in servicesslowed in the 2000s to the point where its averagerate fell below that of goods. Furthermore, servicestradehasbeenmuchlessvolatilethantradeingoodssince the global financial crisis of 2008-09.Consequently, the share of services in the total hasremainedmoreorlessconstantsince1990.Itisoftenassumed that trade in commercial services is stillgrowing faster than goods trade, but this may notnecessarilybethecase.

Wheninternationaltradeflowsaremeasuredinvalue-addedratherthangrossterms,servicesappeartoplaya larger role in world trade (see Section B.2(e) formore informationon trade invalue-added terms).Thecoverage of data on commercial services is notparticularly good (see Section B.2(a)) and there maybe significant overlap between this trade and foreigndirect investment (FDI) as well as with offshoring ofbusinessactivities.

(c) Havecountriesbecomemoreorlessspecialized?

A major reason why countries trade is that they havedifferent comparative advantages21 in production and,therefore, they can gain from specialization.Comparative advantage, which can be defined as theability of one country to produce a particular good orserviceatarelativelylowercostoveranother(Deardoff,1998), is derived from two sources: differences intechnologyanddifferencesinfactorendowments.

TheRicardianmodelfocusesontechnologytoexplaintrade patterns. In a model where labour is the onlyfactor of production, differences in technology arerepresentedbydifferences in labourproductivity. Ina

FigureB.13:Composition of world goods and commercial services exports, 1980-2011 (US$trillionandpercentage)

0

52.31 2.26

4.226.28

7.89

12.88

22.27

4.17

18.1010.37

6.395.103.431.881.94 2.511.491.18

1980 1985 1990 1995

Value (US$ trillion) Share of commercial services in goods and services

2000 2005 2011

10

15

20

25

0

5

15.917.0

18.7 18.8 18.9 19.5 18.7

1980 1985 1990 1995 2000 2005 2011

10

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Goods (BOP) Commercial services Commercial services



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simplified world of two countries and two goods,Ricardoshowsthatevenwhenoneofthetwocountrieshas an absolute advantage in the production of bothgoods,i.e.itcanproducemoreoutputwithoneunitoflabour in both goods, there is scope for mutuallybeneficial trade if both countries specialize in thegoods where the opportunity cost is lower (and thecomparative advantage greater) relative to othercountries.22

The Heckscher-Ohlin (HO) theory focuses on cross-country differences in the endowments of factors ofproduction such as labour and capital. Given thedifferentfactorintensitiesacrosssectors,thepriceofthe factor used intensively in a specific sector in acountry that is abundant in that factor will be lowerrelative to other countries; thus this country shouldhave a lower opportunity cost in that sector, and willspecializeaccordinglyinanopeneconomy.23

In this neoclassical framework, regardless of themotive for trade, countries will specialize in theproduction and export of certain goods based oncomparative advantage. However, improvements intelecommunications and information technology,together with increased economic integration andgreatertradeopenness,haveenabledhigherlevelsoftechnologicaldiffusionandincreasedthemobilityandaccumulation of productive factors over time. Thisraisesthequestionofwhethercountriesmaybecomeless specialized in the export of particular productsas a result, and therefore more similar in terms oftheir export composition. In this sub-section, theevolution of two different measures of internationalspecialization, export concentration and RevealedComparative Advantage (RCA), will be considered toinvestigate whether countries have become more orlesssimilarintermsoftheirexports.

(i) Export concentration

Tocaptureexportspecialization,wefirstcomputethelevelofconcentrationofmerchandiseexportsforasetof countries in 1990 and 2010. Specifically, wecompute the Herfindahl-Hirschmann (H) index,24whichisdefinedasfollows,foracertaineconomyi:

𝐻𝐻 =(𝑥𝑥!/ 𝑥𝑥!! )! ! − 1/𝑛𝑛

1− 1/𝑛𝑛,

where 𝑥𝑥!/ 𝑥𝑥!! istheshareofexportlinek,andn

isthenumberoftotalexportlines.Theindexhasbeennormalizedtoobtainvaluesthatrangebetween0and1,with1beingfullconcentrationofexports.

Wethencomparetheindicesbytakingthedifferencebetweenthetwoyearstoreflectthepatternsofexportspecialization across countries over this 20-yearperiod(seeTableB.9).

Today,theexportsofasignificantnumberofcountriesare diversified (the H index of almost 80 per cent ofthe countries in our sample was below 0.4 in 2010).Highly diversified countries are mainly located inEurope, North America and Asia (see Table B.9). Incontrast, those with highly concentrated exports aremostlydevelopingcountriesandinmanycasesnaturalresource-rich countries (for instance,Congo,ChileorMozambique).

With respect to the evolution of specialization overtime, we observe that, between 1990 and 2010, theHerfindahl-Hirschmann indices of the majority ofcountries either decrease, so countries have becomemore diversified, or experience no significant change(thechangesinHindicesarewithin[-0.025,+0.025]).Therefore, we can conclude that countries arebecomingmoresimilarovertime.

(ii) Revealed comparative advantage

To further explain patterns of internationalspecialization,wecalculatedtheRevealedComparativeAdvantage(RCA) indexforselectedeconomiesacrossthreebroadproductcategories (agriculturalproducts,fuels and mining products, manufactures) and sevenmanufacturing sub-sectors between 1990 and 2010.The RCA index is based on Balassa’s (1965) relativeexportperformanceofacertain industry (orproduct)andcountryandiscomputedasfollows:

𝑅𝑅𝑅𝑅𝑅𝑅!" = (𝑋𝑋!" 𝑋𝑋!") (𝑋𝑋! 𝑋𝑋!)

where Xijareexportsofcountry iinindustry j, XWjareworldexportsofindustry j; XirepresentstotalexportsofcountryiandXWrepresenttotalworldexports.

The data shown in Table B.10 paint an interestingpicture of the evolution of RCA across countries andsectors. Some developed economies have seen theircomparative advantage deteriorate in manufacturinggenerally (the United Kingdom, Canada) while othershave experienced declines in specific manufacturingsectors(ironandsteelinAustralia,chemicalsinNorway,automotive products in Sweden, office and telecomequipment inJapan,etc.)A few improvements inRCAhave been recorded by developed economies(agricultural products in New Zealand, steel in Japan,textiles in the United States) but losers generallyoutnumbergainersinadvancedmanufacturingsectors.

Among developing economies, there is a divergencebetween those thatare resource richandothers thatare industrializing. Countries such as China, Mexicoand Turkey that used to have a strong comparativeadvantage in primary products25 have recently losttheir advantages in these sectors and gained inmanufacturedgoods.On theotherhand, theRussianFederation, Brazil and India have either lostcomparativeadvantage inmanufacturingorgained inprimaryproducts, or both.Despite the fact that large


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TableB.9:Changes in manufacturing export concentration for selected economies, 1990-2010 (index,-1to+1)Country 1990 2010 Diff Country 1990 2010 Diff

Italy 0.05 0.06 0.00 Paraguay 0.41 0.23 0.18

UnitedStates 0.11 0.07 0.04 Honduras 0.32 0.24 0.08

Indonesia 0.38 0.08 0.30 Albania 0.50 0.24 0.26

Austria 0.06 0.08 -0.02 CentralAfricanRep. 0.85 0.24 0.61

Brazil 0.09 0.08 0.01 Malaysia 0.29 0.24 0.05

Netherlands 0.06 0.09 -0.03 Macao,China 0.21 0.25 -0.04

Turkey 0.14 0.09 0.05 Burundi 0.45 0.25 0.20

Poland 0.08 0.09 -0.01 HongKong,China 0.10 0.26 -0.16

Portugal 0.08 0.09 -0.01 CostaRica 0.13 0.27 -0.15

Denmark 0.07 0.10 -0.03 SriLanka 0.46 0.27 0.18

Lithuania 0.12 0.10 0.01 TheGambia 0.36 0.28 0.08

Thailand 0.15 0.11 0.05 Venezuela,BolivarianRep.of 0.32 0.28 0.04

Kenya 0.09 0.11 -0.02 Grenada 0.25 0.28 -0.03

Germany 0.09 0.11 -0.02 Jordan 0.23 0.28 -0.05

Latvia 0.13 0.11 0.02 Mali 0.61 0.29 0.33

NewZealand 0.18 0.11 0.07 Ghana 0.46 0.29 0.17

Sweden 0.12 0.11 0.01 Djibouti 0.25 0.29 -0.04

FYRMacedonia 0.21 0.11 0.09 UnitedArabEmirates 0.15 0.29 -0.14

Guatemala 0.21 0.12 0.09 Kazakhstan 0.26 0.30 -0.04

Romania 0.12 0.12 0.00 Morocco 0.33 0.30 0.03

Estonia 0.10 0.12 -0.02 Cameroon 0.43 0.31 0.12

Nicaragua 0.21 0.12 0.09 Israel 0.35 0.31 0.05

CzechRep. 0.06 0.12 -0.06 SaudiArabia,Kingdomof 0.27 0.32 -0.05

France 0.07 0.13 -0.05 Jamaica 0.16 0.32 -0.16

Egypt 0.37 0.13 0.24 Switzerland 0.09 0.32 -0.23

Japan 0.14 0.13 0.01 Ethiopia 0.94 0.32 0.61

Greece 0.14 0.13 0.01 Guinea 0.71 0.33 0.39

Spain 0.16 0.13 0.02 Singapore 0.20 0.33 -0.14

UnitedKingdom 0.06 0.13 -0.07 Senegal 0.44 0.33 0.10

China 0.11 0.13 -0.02 Azerbaijan 0.20 0.34 -0.14

Colombia 0.17 0.14 0.03 Niger 0.47 0.34 0.12

Australia 0.15 0.14 0.01 Pakistan 0.38 0.35 0.03

Slovenia 0.10 0.14 -0.04 Cyprus 0.13 0.35 -0.23

KyrgyzRep. 0.16 0.14 0.02 Benin 0.54 0.37 0.17

Norway 0.16 0.14 0.02 Togo 0.37 0.37 -0.01

Malawi 0.30 0.15 0.15 Bahamas 0.27 0.37 -0.10

Ecuador 0.22 0.15 0.08 Georgia 0.25 0.39 -0.15

Finland 0.27 0.15 0.12 Sudan 0.80 0.40 0.41

India 0.25 0.15 0.10 Ireland 0.21 0.40 -0.19

Rwanda 0.72 0.16 0.56 Philippines 0.22 0.41 -0.19

Mexico 0.21 0.16 0.05 Barbados 0.20 0.41 -0.21

Bulgaria 0.11 0.16 -0.05 Bolivia,PlurinationalStateof 0.55 0.41 0.13

RussianFederation 0.16 0.16 0.00 Zimbabwe 0.31 0.43 -0.12

Korea,Rep.of 0.12 0.16 -0.03 Algeria 0.14 0.43 -0.29

Canada 0.19 0.16 0.02 Panama 0.18 0.43 -0.25

Tunisia 0.21 0.17 0.05 Bhutan 0.56 0.43 0.13

Uruguay 0.23 0.17 0.06 Peru 0.51 0.46 0.06

Hungary 0.08 0.17 -0.10 Côted'Ivoire 0.17 0.46 -0.29

Argentina 0.13 0.17 -0.04 Kuwait,theStateof 0.15 0.50 -0.35

Yemen 0.20 0.18 0.02 Gabon 0.41 0.52 -0.11

Croatia 0.17 0.18 -0.01 Nigeria 0.31 0.53 -0.22

Madagascar 0.30 0.18 0.12 Bahrain,Kingdomof 0.61 0.53 0.08

BurkinaFaso 0.32 0.18 0.14 Belize 0.22 0.65 -0.43

SyrianArabRep. 0.50 0.19 0.31 Mauritania 0.22 0.66 -0.44

ElSalvador 0.19 0.19 0.00 Montserrat 0.86 0.69 0.17

SlovakRep. 0.11 0.19 -0.08 Dominica 0.70 0.69 0.01

Mauritius 0.27 0.20 0.07 Chile 0.80 0.75 0.05

Uganda 0.20 0.20 0.00 Iceland 0.59 0.75 -0.17


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TableB.9:Changes in manufacturing export concentration for selected economies, 1990-2010 (continued)(index,-1to+1)Country 1990 2010 Diff Country 1990 2010 Diff

DominicanRep. 0.34 0.20 0.14 Zambia 0.91 0.89 0.02

Ukraine 0.15 0.21 -0.06 Congo 0.57 0.91 -0.34

SouthAfrica 0.10 0.21 -0.12 Mozambique 0.19 0.95 -0.76

Nepal 0.85 0.22 0.63 Myanmar 0.54 0.96 -0.42

Oman 0.31 0.23 0.08 Samoa 0.57 0.98 -0.41

Moldova,Rep.of 0.16 0.23 -0.07 CapeVerde 0.44 0.99 -0.56

Source:AuthorscalculationsonUNComtradeSITIC3-digitRev.2database.

Note: Export concentration is calculatedwith theHerfindahl-Hirschmann index (H).Changes inmarket concentrationare calculatedas thedifferenceinHerfindahl-Hirschmannindicesbetween1990-2010.TheHindicesrangefrom0to1(maximumconcentration).Therefore,thedifferenceinthelevelsofconcentrationrangesfrom-1to1.

TableB.10:RCA evolution for selected economies and sectors, 1990-2010Commodity Countries that gain RCA Countries that lose RCA

AgriculturalproductsBrazil;Germany;Greece;Indonesia;Italy;Japan;NewZealand;Spain;Switzerland

Australia;China;CzechRepublic;HongKong,China;Hungary;Ireland;Mexico;Singapore;Turkey

Fuelsandminingproducts

Australia;Brazil;Canada;Denmark;Finland;Iceland;India;Thailand;UnitedStates

China;CzechRepublic;Indonesia;Ireland;Hungary;Malaysia;Mexico;Poland;Singapore;SlovakRepublic

ManufacturesChile;China;France;Hungary;Malaysia;Mexico;Poland;Singapore;Thailand;Turkey

Australia;Brazil;Canada;Finland;India;Norway;RussianFederation;SouthAfrica;Sweden;UnitedKingdom

IronandsteelCanada;Estonia;Finland;India;Italy;Japan;Malaysia;Portugal;Thailand;UnitedStates

Australia;Brazil;CzechRepublic;Hungary;Ireland;Mexico;Norway;Poland;RussianFederation;SlovakRepublic

ChemicalsGreece;Iceland;Indonesia;Ireland;Italy;Japan;RepublicofKorea;Malaysia;Singapore;Thailand

China;CzechRepublic;Estonia;HongKong,China;Hungary;Mexico;Norway;RussianFederation;SlovakRepublic;SouthAfrica

Officeandtelecomequipment

Chile;China;CzechRepublic;Greece;Hungary;HongKong,China;Indonesia;Mexico;Poland;SlovakRepublic

Australia;Austria;Brazil;Canada;Ireland;Italy;Japan;RussianFederation;Switzerland;UnitedKingdom

AutomotiveproductsChile;CzechRepublic;India;Indonesia;RepublicofKorea;Poland;SlovakRepublic;SouthAfrica;Thailand;Turkey

Australia;Canada;China;Estonia;Netherlands;Norway;RussianFederation;Sweden

OthermachineryChile;China;Estonia;Greece;Iceland;Indonesia;RepublicofKorea;Mexico;Thailand;Turkey

Australia;Germany;Ireland;Israel;Poland;RussianFederation;Spain;Sweden;Switzerland;UnitedKingdom

TextilesCanada;Chile;Israel;Italy;Malaysia;NewZealand;Slovenia;Spain;Turkey;UnitedStates;

Australia;Brazil;Estonia;Ireland;RepublicofKorea;RussianFederation;Singapore;SlovakRepublic;SouthAfrica;Switzerland

ClothingCanada;Chile;Denmark;France;Mexico;Netherlands;NewZealand;Spain;Sweden;UnitedKingdom

Brazil;Hungary;Iceland;Israel;RepublicofKorea;RussianFederation;Singapore;Slovenia;SouthAfrica;Thailand

Source:Author’scalculationbasedonUNComtradedatabase.

Note:RCAindicesarecalculatedformajorselectedeconomies.

developing economies (including Brazil, China, theRussian Federation, India and Turkey) share a recenthistory of rapid economic growth, this has beenachieved in different ways depending on the country.Insomecases,labourandcapitalhavebeenharnessedtofuelexport-orientedmanufacturinggrowth,whileinotherstheirgrowthhasdependedmoreonhighglobalcommodity prices, which are beyond their influence.Underthesecircumstances,economicgrowthmaybemore durable in the first group and subject to boom-bustcyclesinthesecondgroup.

The findings outlined above are in line with moresophisticated empirical studies confirming that

countries have become less specialized over time.Proudman and Redding (2000), for example, usemodels of income convergence based on distributiondynamics (Dornbusch et al. 1977) to assess thespecialization patterns – captured with RevealedComparativeAdvantage–oftheUnitedStates,Japan,France, Germany and Italy between 1960 and 2010.They find substantial changes in the distribution ofRCAacrossindustriesovertime.

LevchenkoandZhang(2011)investigatetheevolutionof comparative advantage for a set of 75 developedand developing countries over the last five decades.The authors use total factor productivity26 (TFP) by


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industry to capture countries’ relative technologies.Themainresultoftheirstudyisthatinbothdevelopedand developing countries, productivity has grownfaster in those industries experiencing lower relativelevelsofproductivity.

Carrereet al. (2009) indirectly support the fact thatcomparativeadvantagehasshiftedacross industriesovertime:forasetof156developedanddevelopingcountries, the authors find that during the period1988-2006, exports diversify and then re-concentratewithincome,27whileatlow-incomelevelscountriesdiversifyinbothexistingandnewproducts,and rich countries re-concentrated their exports. Ascountriesbecomericher,theyaccumulatecapitalandimprovetheirproductiontechnologies;therefore,theystop exporting low-value differentiated goods,intensiveinfactorssuchaslowskilllabourwhicharenot any more in line with their new set of factorendowments.

This lastresult is in linewithmodelssuchasRomalis(2004), which predicts that countries accumulating afactor faster than the rest of the world will see theirproduction and export structure move towardscommoditiesthatmoreintensivelyusethatfactor.Theauthorconfirms this in thedataandfinds that rapidlygrowing countries have seen their export structurechange towards more skill- and capital-intensiveindustries.Heller(1976)alsoshowsthatthechangeinJapan’s factor endowment between 1956 and 1969strongly altered its comparative advantage in trade.The composition of its export bundle shifted towardsthecapital-intensivesectors.Thisshiftwasreinforcedbyarelativelyfasterdeepeninginthecapitalintensityofthesesectors(seeBoxC.4forfurtherdiscussion).

Asstandardeconomictheorysuggests,specializationin the production and export of certain goods basedoncomparativeadvantagehasanimpactoncountries’welfare: an implication of the Stolper-Samuelsontheorem is thatunder trade liberalization, thepriceoftherelativelymoreabundantfactorrisesandthepriceof the relativelyscarce factor falls. Insuchacontext,the shifting of comparative advantage across time,highlightedinthissection,willhavesomeimplicationsintermsofwithincountryinequalityanddevelopment.Some of these implications will be discussed inSectionD.1oftheReport.

(d) Hastheworldbecomemoreglobalizedormoreregionalized?

Preferential tradeagreementsbetweencountriesandgroups of countries have increased in number andambition in the last two decades. According to the2011 World Trade Report, the number of suchagreements more than tripled between 1990 and2010,fromaround70atthebeginningoftheperiodtonearly300attheend(WTO,2011a).Researchersandpolicy-makershaveusedtheterms“preferential trade

agreements” (PTAs) and “regional trade agreements”(RTAs)moreorlessinterchangeablyinthepastduetothe fact that PTAs traditionally had a strong regionalorientation. This raises the question of whether theproliferationofPTAshascausedinternationaltradetobecomemoreorlessregionalizedovertime.

The answer to this question is far from obvious.Recently negotiated PTAs have increasingly beencross-regional in that they involve parties in differentregions.Althoughnearlythree-quartersofPTAswerewithin the same region (intra-regional) in the mid-1990s, this fraction had dropped to around half by2010 (WTR, 2011). All else being equal, more cross-regional agreements should make trade lessregionalized.However,otherfactorsmaybeworkingintheoppositedirection, including the spreadof supplychains inAsia (seeSectionB.2(e) foradiscussionoftheinfluenceofsupplychainsontrade).

Toillustratetheevolutionoftradewithinandbetweenregions, we mostly make use of the Network ofMerchandise Trade dataset from the WTO’s annualInternational Trade Statistics publication (2012).28These data cover exports of geographic regions byproduct and region of destination (including regionsdefined by level of development) in current US dollarterms.NetworkdataaccordingtocurrentWTOproductcategories and country groups are available back to2000,andbackto1990accordingtotheWTO’solderdata classifications.29 In other cases (e.g. trade inpartsandcomponents),wehavecalculatedestimatesbasedonavailabledataintheUNComtradedatabase.

(i) Intra-regional trade

Figure B.14 shows total merchandise exports bygeographic region from 1990 to 2011, together withsharesofintra-regionalandextra-regionaltrade.NorthAmerica, Europe and Asia are shown to one scale,whileotherregionsshareadifferentscale.FiguresforEurope exclude intra-EU trade. Export values andintra-regionaltradesharesforEuropearemuchlargerif thesedataare included,but thesearediscussed inthe text.Moredetailedbreakdownsbypartner regionand major product group are also provided in anappendixattheendofthischapter.

As Figure B.14 makes clear, intra-regional traderepresentsalargeandrisingpercentageoftotalexportsfrom Asian countries. This share has grown from42per cent in1990 to52per cent in2011, so that itnowrepresentsamajorityofAsiantrade.Althoughtheintra-regional trade share of Asia is the largest of anyregion in this chart, it is actually smaller than Europe’swhenintra-EUtradeisincludedinthecalculation.

TheriseofAsia’sintra-regionaltradesharecamemostlyat theexpenseofNorthAmerica,whoseshare intotalAsian merchandise exports fell from 26 per cent to16percentbetween2000and2011andwhoseshare


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inAsianexportsofmanufacturedgoodsdroppedfrom29 per cent to 19 per cent during the same period.Meanwhile, the share of Europe in Asia’s totalmerchandiseexportsandmanufacturedgoodsexportswas unchanged (17 per cent and 19 per cent,respectively,seeAppendixTableB.2).

Europe’sintra-regionaltradeshareinexportsfellfrom35 per cent to 29 per cent between 1990 and 2011with intra-EU trade excluded. However, the pattern isquitedifferentwhenintra-EUtradeisaddedbackintothe total. In this case, Europe’s total exports are thelargest of any region (US$ 1.7 trillion in 1990,US$6.6trillionin2011),witharelativelysteadyintra-regional trade share in exports of around72percent.Thissharewasslightly larger in2000at73percentbutitslippedto71percentin2011.

Theshareof intra-regional trade in thetotalexportsofNorth America (which includes Mexico) rose from41 per cent in 1990 to 56 per cent in 2000 beforereceding to 48 per cent in 2011. The decrease in theregion’sintra-regionaltradeshareismostlyexplainedbyrisingexportstoSouthandCentralAmerica(9percentofexportsin2011,upfrom6percentin2000)andAsia(21per cent in2011,19per cent in2000),withotherdeveloping region destinations recording more modestincreases,andEuropeunchangedat17percent.

Other regions shown in thechart, all ofwhichexportsignificant quantities of natural resources, saw theirintra-regionaltradesharesriseinthelast20yearsbutthey are still extremely small in absolute terms. Forexample, Africa’s intra-regional trade share doubledfrom 6 per cent to 12 per cent between 1990 and2011butthisremainsremarkablysmallcomparedwithmoreindustrializedregions.

The rise of PTAs may explain some of the abovechanges in intra-regional trade shares. For example,the reduced importance of intra-regional trade inNorth American exports could be partly due to theUnitedStatesconcludingtradeagreementswithSouthand Central American countries (e.g. Chile, ColombiaandPanama)butwedonot observea similarly largeshift in the intra-regional trade share of Europe overthe same interval (at least when intra-EU trade isincluded) despite the fact that the EU has alsonegotiated a number of trade agreements withcountriesinotherregionssince2000.

(ii) Trade flows between regions

FiguresB.15.AandB.15.Bshowhowtotalmerchandisetrade between selected pairs of geographic regions(e.g.exportsofEuropetoAsiaplusexportsofAsiatoEurope) changed between 1990 and 2011 when

FigureB.14:Intra-regional and extra-regional merchandise exports of WTO regions, 1990-2011 (US$billionandpercentage)

1990 2000

North America

2011

548

1,225

2,282

1990 2000

South and Central America

2011

1990 2000 2011

1990 2000 2011

1990 2000 2011

1990 2000 2011

1990 2000

Europe (excl. EU-intra)

Africa

Asia

CIS

Middle East2011

41%59%

56%

44%48%

52%

706966

2,707

35%

65%

27%

73%29%

71%

138268

1,251

94%

10694%

12086%

198

74%

75074%

26%14991%

594

88%

12%

91%15%

85%

739

1,658

5,538

58%

42%

51%

49%

48%

52%

58146

789

80%

81%

19%

Extra Intra

Sources:WTOInternational Trade Statistics 2012,supplementedwithSecretariatestimatespriorto2000.

Note:Graphsforregionsarenotshowntoscale.ColoursandboundariesdonotimplyanyjudgementonthepartoftheWTOastothelegalstatusofanyfrontierorterritory.


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expressedasapercentageofworldtrade.Weightsofarrows between regions indicate the overallimportance of bilateral trade relationships betweenpairsofregionsin1990and2011.TheunderlyingdataarederivedfromAppendixTableB.2.

What is immediately apparent from the map of tradeflows is the centrality of Asia in inter-regional trade.The three most important bilateral relationships inworld tradeasof2011were thosebetweenAsiaand

Europe(8.8percentofworldtradein2011),AsiaandNorthAmerica(7.8percentofglobaltrade)andAsiaandtheMiddleEast(5.1percentofworldtrade).

Asia’s bilateral trade with all regions increased as ashareofworldtradebetween1990and2011,withtheexception of trade with North America. In this case,theshareoftradeslippedfrom10.2percentin1990to7.8percentin2011.TheshareofAfrica-Asiatradeinworld tradenearly tripledduring thisperiod, driven

FigureB.15.A:Share of total trade between geographic regions in world trade, 1990 (percentage)

To Asia

South and CentralAmerica-Asia, 0.8%

North America-South

and CentralAmerica,

2.6%

South andCentral

America-Europe,1.6%

North America-MiddleEast, 0.9%

Europe-Africa,3.4%

Europe-MiddleEast, 2.5% Europe-Asia,

8.1%

CIS-Asia,0.7%

Europe-CIS, 3.6%

North America-Asia,10.2%

To South andCentral AmericaMiddle East-Asia,

3.2%

Africa-Asia, 0.6%North America-Africa, 0.7%

North America-Europe, 7.8%

NorthAmerica

South andCentral America

Europe

Africa

MiddleEast Asia

CIS


Note:Worldtradeincludesintra-EUtrade.Arrowweightsbasedonsharesin1990.Tradewithinregionsandwithunspecifieddestinationsrepresented53%ofworldtradein1990.

FigureB.15.B:Share of total trade between geographic regions in world trade, 2011 (percentage)

To Asia

South and CentralAmerica-Asia, 2.0%

North America-South

and CentralAmerica,

2.1%

South andCentral

America-Europe,1.4%

North America-MiddleEast, 1.0%

Europe-Africa,2.3%

Europe-MiddleEast, 2.0% Europe-Asia,

8.8%

CIS-Asia,1.3%

Europe-CIS, 3.6%

North America-Asia,7.8%

To South andCentral AmericaMiddle East-Asia,

5.1%

Africa-Asia, 1.7%North America-Africa, 0.8%

North America-Europe, 4.8%

NorthAmerica

South andCentral America

Europe

Africa

MiddleEast Asia

CIS


Note:Worldtradeincludesintra-EUtrade.Arrowweightsbasedonsharesin2011.Tradewithinregionsandwithunspecifieddestinationsrepresented54%ofworldtradein2011.


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by shipments of oil and other natural resources toChina and by exports of manufactured goods fromChinatoresourceexporters.Despitethisrapidgrowth,theshareofAfrica-Asiatradeinworldtraderemainedrelativelysmallin2011.

In contrast to the rising importance of Asia, NorthAmerica’s bilateral trade flows with other regionseither maintained their shares in world trade (e.g.NorthAmerica-MiddleEast)orfellsharply(e.g.NorthAmerica-Europe, which dropped from 7.8 per cent to4.8percentofworldtrade).

(iii) Supply chains and intermediate goods

Tradeinpartsandcomponents,servingasaproxyforintermediate goods more generally, may provide anindication of the development of supply chains byregion. These data are provided in Table B.11, whichshows the shareof parts andcomponents inexportsof manufactured goods by region since 1990, withadditional breakdowns by intra-regional and extra-regionaltrade.

Thetableshowsthatgrowthintheshareofpartsandcomponents in manufactured goods trade wasstronger for intra-Asia trade than for trade betweenAsia and other regions. The share of intra-regionaltrade in parts and components is also larger in Asiathan in any other region. This suggests that Asiansupply chains may be becoming more intra-regionalrather than trans-regional (to the extent that trade inpartsandcomponentsisindeedareliableindicatorofsupplychainsactivity).

(e) Havesupplychainschangedpatternsofinternationaltrade?

Over recent decades, one of the most importantchanges in thenatureof international tradehasbeenthe growing interconnectedness of productionprocesses across many countries, with each countryspecializinginparticularstagesofagood’sproduction.In the trade literature, thisphenomenon is referred toas “global supply chains”, “global value chains”,“international production networks”, “verticalspecialization”, “offshoreoutsourcing”and“productionfragmentation”. In the Report, we will use the term“global supply chains” with the recognition thatinternationalisedsupplychainsmayoftenberegional,ratherthanglobal,innature.

International fragmentation of production throughglobalsupplychainshasbeenabusinessrealitysincethe generalization of the so-called “Toyota” model30and the spread of international outsourcing in the1980s. The Business Guide to the World Trading System, published by the International Trade Centre(ITC)andtheCommonwealthSecretariatin1999,says“virtually all manufactured products available inmarketstodayareproducedinmorethanonecountry”.

Infact,afirstattempttoformalizethisphenomenonisattributed to Leontief in the 1960s (Leontief andStrout,1963).

Yet, it is only recently that trade economists havelooked into the theoretical implications of “trade intasks”. The seminal work of Grossman and Rossi-Hansberg(2006)referredtoitas“thenewparadigm”.It isbasedontheideathatinordertoproduceafinalgood, several tasks have to be performed, some ofwhichcanbeoffshored.Considertwocountries,calledNorth and South, where firms in North have superiortechnology, and thus wages in North are higher. ANorth firm is interested in combining its bettertechnologywiththecheaper labour inSouth,facingatask-specificcostofoffshoring.Thefirmwillthereforeoffshore the task as long as the wage gap is largerthan the offshoring cost. This creates tradeopportunitiesthatwouldnothaveexistedinaclassicaltrade in final goods. Moreover, productivity in Northwill increasesinceworkers inNorthwill focuson thetasks where they have a “trade-cost-adjusted”comparative advantage. A major difference betweenthisapproachandthetraditionaltradeliteratureisthatthe technology of production is firm-specific, notcountry-specific.

On the empirical side, the estimation of global valuechainshasbeenachallengeforeconomists:statisticson international trade flows are collected in grossterms and therefore lead to a multiple-counting oftradeinintermediategoods.Thisdistortstherealityofinternational trade and influences public opinion andpolicy. Consider, for instance, the perceivedcomparative advantage of a country which may bedifferentiftradeismeasuredbythedomesticcontentinexports rather thangross tradeflows (Koopmanetal., 2012). Similarly, bilateral global imbalances areinfluenced by the fact that countries engagedprincipallyincompletingtasksdownstreamhavemostof the value of the goods and services attributed tothem.Protectionistpoliciesdesignedtopreservejobsmayalsoberenderedcounter-productive.Forexample,asizeableproportionofUSimportsfromChinaaretheresultofgoodsandservicespurchasedfromUSfirms,with thefinalproductassembled inChina. IncreasingtariffswouldhaveanadverseimpactonjobsfortheseUS firms. Finally, a better understanding of value-added trade flows would enable policy-makers toidentify the transmission of macroeconomic shocks,such as the recent financial crisis, and adopt theappropriatepolicyresponses.

Given that the existence of global supply chainschangesourperceptionofinternationaltradeandhasprofoundimplicationsfortheanalysisoftradepatterns,an accurate measure of trade flows in value-addedterms is necessary to correctly assess future tradescenarios. This section will first highlight the currenteffortsmadebyeconomistsandtheWTOtoaccuratelymeasure trade in value-added terms. Secondly, it will


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usesomerecentestimatesoftradeinvalue-addedtoreviewthetrendsdescribedearlier.31

(i) Conventional measures of trade in value-added

Besides measuring gross flows, international tradestatistics should also be able to reflect value-addedflowsbetweencountries.Owingtothelackofrelevantdata, there is little systematic evidence quantifyingthis.MostofthedatathathavebeenproducedtodatecomefromcasestudiesonAppleandNokiaproductsor Mattel’s Barbie doll, which break down the partsandaccessoriesusedtocreatethesegoods.Thecasestudies illustrate thehugediscrepancybetweenwhatwasrecordedundertraditionalrulesoforiginandwhatwouldberecordedonthebasisoftheactualvalueofcomponentsandmanufacturingservices.

National statistical authorities have traditionallyconductedsurveysfocusedonselectedfirms(usuallylarge multinationals). Another approach has been tolinkbusinessandtraderegisters,as isbeingdonebytheEuropeanUnion’sEUROSTATandMexico’sINEGI.Thisleadstothecreationofmicro-databasesthatareboth representative and detailed. Unfortunately, theimplementation of such an approach is intensive inresources and access to micro-databases is oftenlimitedduetoconfidentialityrestrictions.32

An alternative way to measure trade in value-addedterms is touse theClassificationbyBroadEconomicCategories (BEC)or theStandard InternationalTradeClassification (SITC) to categorize goods as beingintermediateorfinal.Thistypeofanalysiswasinitiatedby Yeats (1998) and subsequently utilized by others,

including Athukorala and Yamashita (2006). Trade inintermediategoodsisamongthefewreadilyavailablestatistics to provide information on the intensity ofinternationalsupplychainactivity.

As was shown in Section B.2(d), trade in parts andcomponents canbeusedasaproxy for intermediategoodstomeasurethedevelopmentofsupplychainsbyregion. Using the SITC definition of parts andcomponents from this earlier section, Figure B.16shows that while the value of world trade in theseproducts increased steadily over the last threedecades, their share in world trade in manufacturedgoodspeakedmore thanadecadeago.Theshareofparts and components in world exports ofmanufactured goods increased from 22 per cent in1980to29percentin2000.However,between2000and2008 itdeclinedbyroughly4percentagepoints,onlytorecoversomewhatthereafter.In2011,thesharestoodat26percent,roughlyequaltoitslevelin1995.Thestagnatingshareofpartsandcomponentsmaybeexplained inpartby theeconomiccrisisof2001andthe more recent financial crisis. Another possibility isthat trade may have experienced a one-time jump inthe share of intermediate goods as a result of theinternationalization of production, which is unlikely tobe repeated since there are no more large countrieson the scale of China or India waiting to join globalproductionnetworks.

Aclassificationofgoodsinto“intermediate”and“final”is based on expert judgement, which is by naturesubjective, and therefore may be somewhat arbitrary.Many goods might be both final and intermediatedependingonthecontext.Hence,tradeinvalue-addedis increasingly being estimated by using international

TableB.11:Shares of parts and components in exports of manufactures by region, 1990-2011 (percentage)

Total exports of manufactures

Intra-regional exports of manufactures

Extra-regional exports of manufactures

NorthAmerica

1990 33.5 35.5 32.1

2000 35.2 32.7 38.2

2011 26.1 28.1 24.1

SouthandCentralAmerica

1990 20.0 15.9 21.0

2000 19.0 16.9 20.5

2011 17.1 17.1 17.0

Europe

1990 22.6 22.4 23.0

2000 24.2 23.1 26.9

2011 21.8 21.2 23.0

Asia

1990 27.6 33.3 24.5

2000 35.4 43.1 28.4

2011 31.1 38.3 22.9

Sources:WTOSecretariatestimatesbasedontheUNComtradedatabase.

Note:PartsandcomponentsaredefinedastheSITCequivalentofBECpartsandcomponentsplusunfinishedtextilesinSITCsectiondivision65.


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or global Input-Output (I-O) tables, which combinenational I-Omatriceswith tradeflowsof intermediateandfinalgoodsandservices.

AglobalI-Otabledepictsaninternationalproductionstructure enabling the user to trace a “value chain”foreach finalgoodorservicesold in theeconomiescovered.Buildingonthe I-Oframework,Hummelsetal. (2001) developed the concept of verticalspecialization, defined as the value of importedintermediategoodsembodied inacountry’sexports.Theyshowedthatthegrowthinverticalspecializationaccountedforaboutone-thirdofthegrowthinoverallexports for 13 OECD members and Chinese Taipeibetween 1970 and 1990. In a more recent study,Miroudot et al. (2009) used such an approachto show that the share of intermediate goods inOECD merchandise trade increased from just over50percent in1999 toalmost60percent in2007.This suggests that while the share of trade inintermediate goods in total merchandise tradeincreased somewhat, trade in final goods alsoincreased at a brisk pace. The authors also showthat in 2007, over 70 per cent of services tradeinvolved intermediategoods, i.e. itcontributedto theproductionofproducts.

(ii) Developing a comprehensive dataset on value-added trade

In recent years, there have been numerous initiativesaimedatusingtheinput-outputframeworktodescribetheinterdependenciesofindustriesbetweencountries.

Oneofthefirstexamplesofinternationalinput-outputtables was the Asian Input-Output (AIO) tabledeveloped by Japan’s Institute of DevelopingEconomies (IDE-JETRO) in the 1980s as an attempttomodel the relationshipsbetween industries inEastAsia that emerged when Japanese firms outsourcedsomeoftheirindustrialactivity(WTOandIDE-JETRO,2011). The AIO covers nine Asian economies as wellastheUnitedStatesandupto76sectors.

A few academic initiatives were also undertaken in thearea of global I-O tables, such as the Global TradeAnalysisProject(GTAP)database,aworld-wideI-Otablepartiallybasedonofficialdata,ortheMulti-RegionInput-Output(MRIO)database,developedbytheUniversityofSydney,whichismostlydedicatedtoenvironmentaldataandreliantonmathematicalmodelling.

However, it isonly in2012thatglobal I-Otablesbuilton official statistical sources were produced. TheWorldInput-OutputDatabase(WIOD)projectresultedin theWorld Input-OutputTable (WIOT) inMay2012,whichcovers40economiesanda“Restoftheworld”aggregate for 35 sectors over the period 1995-2009.33 The OECD also developed an Inter-CountryInput-Output (ICIO) table covering 58 economiessupplemented by a “Rest of the world” aggregate for37sectorsandasetofbenchmarkyears(1995,2000,2005,2008and2009).BuildingontheseOECDICIOtables, the WTO and OECD developed a seriesof indicators of bilateral trade in value-added (seeBoxB.3).34

FigureB.16:World exports of parts and components, 1980-2011 (US$billionandpercentage)

22.1

29.0

26.2

Other manufactures Parts and components

0

19

80

19

82

19

84

19

86

19

88

19

90

19

92

19

94

19

96

19

98

20

02

20

06

20

08

20

04

20

00

20

10

2,000

4,000

6,000

8,000

10,000

12,000Value (US$ billion)

15.0

19

80

19

82

19

84

19

86

19

88

19

90

19

92

19

94

19

96

19

98

20

02

20

06

20

08

20

04

20

00

20

10

20.0

25.0

30.0

35.0Share of parts and components in manufactures (per cent)



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BoxB.3: Trade in value-added terms: one concept, different measures

The first papers to explicitly refer to a comprehensive measurement of the value-added content of worldtrade based on an international input-output framework are Daudin et al. (2006, 2009), Johnson andNoguera(2011),Koopmanetal.(2011)andStehrer(2012).

Daudinetal.(2006,2009)furtherdevelopedtheconceptofverticalspecializationasdefinedbyHummelsetal.(2001).UsingGTAPtables,theymeasuredverticaltradeasthesumofimportedintermediategoodsdirectlyusedas inputs for theproductionofexports, domesticallyproduced inputswhichenter into theproductionofanothercountry’sexports,andexportsthatarereimportedinthecountryoforiginforfinaluse. Value-added trade, thus, is defined as standard trade minus vertical trade. Johnson and Noguera(2011)definevalue-addedexportsasthevalueaddedproducedbythehomecountryandabsorbedbyitstradepartners,i.e.discardinganyvalueaddedreflectedbacktothehomecountry.Theyproposetheratioofvalueaddedtogrossexports(orVAXratio)asameasureoftheintensityofcross-countryproductionsharing.

Yet, intermediate exports which are returned to the home country are extremely relevant for describingsome important cases of bilateral supply chains, such as between Mexico and the United States. Toovercomethisshortcoming,Koopmanetal.(2011)provideafulldecompositionofvalue-addedexportsinasingleconceptualframeworkthatencompassesallthepreviousmeasures.Exportsarefirstdecomposedintodomesticvalueadded,returneddomesticvalueaddedandforeignvalueadded.Domesticvalueaddedis split between exports absorbed by direct importers and indirect exports sent to third countries. Bytaking into account the returned domestic value added and the indirect exports to third countries, thedecomposition iscomplete (thusmatchingstandard tradedata ingross termswhenall thedecomposedvaluesareaggregated).

While the previous approach estimates the domestic and foreign value-added components of exports,Stehrer (2012) suggested yet another methodology, which focuses on the importer’s perspective andestimatestheforeignvalueaddedcontainedinthefinaldemandofacountry. Itcanbeshownthatwhilethetwoapproachesgeneratedifferentbilateralflowsofvalueadded,theresultsatthegloballevelarethesame.

Inalltheapproachesabove,thecalculationsarebasedontheassumptionthattheproductsthatareexporteddonotdiffersubstantiallyfromthoseintendedfordomesticconsumption.35

Thenotionofvalue-addedexports in thissectionrefers to thedomesticcontentofexports,asdefinedbyJohnsonandNoguera(2011).Itincludes:

• the domestic value added directly absorbed by the importer, i.e. either consumed or invested in thedomesticeconomy

• thedomesticvalueaddedimportedbythetradepartnerbutre-exportedtothirdcountries.

Thiscomponentisalmostentirelytradeinintermediategoodsandistypicalofactivitiestakingplacewithininternationalproductionchains.

FigureB.17illustratesthecomparisonbetweengrosstradeandvalue-addedtrade.

Theconventionalmeasureoftradeinthisfigureindicatesexportsbetweenthreecountriestotalling210,whereasonly110ofvalue-addedhasbeenactuallygenerated.ConventionalmeasuresalsoshowthatChasatradedeficitof110withB,andnotradeatallwithA.If,instead,weincludevalue-addedcontent,C’stradedeficitwithBreducesto10anditnowrunsadeficitof100withA.

FigureB.17:Comparison of gross and value-added trade

Country B

Direct VA exports (10)

Final goods (110)

Indirect VA exports (100)

Gross trade(reported in official statistics)

Value-added trade(imputed)

Intermediategoods (100)

Country A

Country C



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(iii) Patterns of trade in value-added terms

Composition of trade

Measuring trade in value-added terms resizes worldtrade figures by taking out double counting andmeasuring only the actual economic content.FigureB.18showstheevolutionof theratioofvalue-addedovergrossexports(VAXratio,seeBoxB.3)atworld level during the years 1995-2007. The ratiodecreasedbyaround10percentagepointsduringthistime span, reaching 71 per cent in 2007. In otherwords,almost30percentoftotaltradeconsistsofre-exports of intermediate inputs; this suggests anincreasedinterdependenceofeconomies.

Sectors are not affected in a similar way, and asexpected, it is trade in manufactured goods whichshows the deepest vertical specialization. Themanufacturing sector, which had already the lowestVAXratioin1995,decreasedto43percentin2007,whilethedomesticcontentofexportsisalmoststablefor agriculture, and falls only slightly for fuels andmining.Regarding theservicessector, twopointsareworth mentioning: (i) the VAX ratio has declined forservices as well, indicating that services, much likegoods, are being disaggregated and tradedinternationallyasseparate“tasks”;(ii)theVAXratioiswell above 100 per cent, suggesting that in thedomestic cost of production of manufactured goods,there is significant value-added purchased fromsuppliersintheservicessectorwhichisthenembodiedintradeingoods.

FigureB.18:VAX ratio, by sector, world level (percentage)

0

40

Agr

icul

ture

Fuel

s an

dm

inin

g

Man

ufac

turin

g

Ser

vice

s

Tota

l

80

120

160

20

60

100

140

180

67 68

101

78

43

174

1995 2007

87

50

147

71

Sources:WTOSecretariatestimatesbasedonWIODdata.

Note:TheVAXratiocanbehigherthan100percentwhenasector“indirectly”exportsvalue-addedthroughothersectors.Thisisespeciallytrueforservices,whichareextensivelyembeddedintradedgoods.

Indeed, the role of services is crucial when analysingtradeinglobalvaluechains;theyguarantee,forexample,just-in-time delivery and sound financing of globalproduction networks. Traditional trade statisticsunderestimatethecontributionofservicestointernationaltrade: as shown in Figure B.19, services account forabout20percentofworldexportsifconsideredingrossterms, while the value-added measure reveals that thecontribution of services is twice as high. Symmetrically,the weight of manufacturing is reduced, while othersectorsarealmostunaffected.

Adequatelydetermining thecontributionof theservicessector to the international trade of an economy isimportant for the analysis of trade and development. Inadvancedeconomies,mostlabourisconcentratedintheservicessector,whichappearslooselyinterconnectedtotheworldeconomyifwebasetheanalysisontraditionaltrade statistics. However, when looking at the value-addeddirectlyand indirectly traded, theservicessectorbecomes the most important contributor to trade, wellaheadofmanufacturedgoods.Thishasalsoanimportantcontribution to our understanding of trade and firmheterogeneity (ordifferencesbetweenfirms).While theliteratureonfirmheterogeneity(theso-called“newnew”tradetheory)focusesontheleadingroleoflargefirmsininternationaltrade(seeBoxB.4),value-addeddatashowthat small and medium-sized firms are probably asimportant as large firms in generating value and arethereforesignificantwhenitcomestodeterminingglobalcompetitiveness. 36

Who are the main players?

Not all countries are similarly engaged in global valuechains, and significant differences can be observedbetweencountries.FigureB.20showstheratioofvalue-added to gross exports for selected economies. It isimportanttomentionthattheWIODinput-outputtablesonly partially take into account the specific productiontechnology of export processing zones; for economieswith sizeable processing trade, notably China andMexico,thismeansthattheactualvalue-addedtogross

FigureB.19:Sectoral contribution to total trade, gross and value-added measures, 2008 (percentage)

Structure of world exports in gross terms, 2008

12%

65%

23%

Structure of world exports in value-added terms, 2008

18%

37%

45%

Primary products Manufacturing Services

Source:WTOSecretariatestimatesbasedonOECD-WTO2008data.


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FigureB.20:VAX ratio, all sectors, selected economies (percentage)

0

20

Hun

gary

Cze

ch R

ep.

Chi

nese

Tai

pei

Net

herla

nds

Kor

ea, R

ep. o

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Pol

and

Sw

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Spa

in

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ico

Ger

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Turk

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Fran

ce

Chi

na

Italy

Can

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Indi

a

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Kin

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Japa

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Bra

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60

80

100

10

30

50

70

90

VAX 1995 VAX 1997


export ratio has been certainly overestimated or,conversely, that the extent of trade within global valuechainsisstillsignificantlyunderestimated.37

There issubstantialvarietyboth inthe leveland inthevariationof the ratioover time.Nevertheless, theVAXratio has been decreasing for almost all economies inthe sample, suggesting a general tendency towardsmore fragmented production processes. The sharpestdeclinesoccurredforEasternEuropeancountriessuchas Hungary, Poland and the Czech Republic, togetherwithTurkey,theRepublicofKoreaandChineseTaipei.

Thedecreaseintheshareofdomesticcontentofexportsisasymptomofhigherinterdependencyofeconomiesinglobal supply chains. Economies are relying more andmore frequently on their production partners to importintermediate inputs for the production of goods andservices that they will either consume domestically orexport. Because many of the industrialized economiesengaging in production networks have the technicalcapacitytoproducethoseinputsbutchosenottodosomeans that access to competitive imports affect acountry’sexportcompetitiveness.

Figure B.21 plots the change of the verticalspecialization index (VS) from 1995 to 2007 againstthe export performance of the economy in themanufacturing sector in the same time span. Thereseems to be a positive correlation between verticalspecializationandincreasesingrossexports:ahigherintegrationofaneconomyintheglobalsupplychainisassociated with an increased export performance. Inotherwords,moreintermediateinputsareimportedfortheproductionofexports.Moreover, importsnotonlyguarantee international competitiveness of aneconomy’s exports but at the same time ensuredomestic output at affordable prices for consumers,

thusdoublycontributing toeconomicwelfare,firstbyenhancing integration in the global economy, andsecondlybyimprovinghouseholds’purchasingpower.

Are countries more or less specialized?

Trade in value-added alters the construction andinterpretationofmostindicatorsthatarebuiltonmarketshares. The Revealed Comparative Advantage (RCA)indicatorisoneofthem.Thisstatisticalindicatorisoftenused as a synthetic measure of internationalcompetitiveness, alone or in addition to “shift-share”analysis (Piezas-Zerbi and Nee, 2009). Traditionally,comparativeadvantagehasbeenconsideredintermsoffinal goods. With the increased fragmentation ofproduction,itismoreappropriatetoevaluatecomparativeadvantageonthebasisof“tradeintasks”.38

AsshowninSectionB.2(c),RCAisdefinedastheshareofasectorinacountry’stotalexportsascomparedwiththeworldaverageofthesamesectorinworldexports.Ifthe indicator is larger than 1, the economy is said tohave a revealed comparative advantage in the sectorconsidered. Theissueofdoublecountingofintermediateinputs in traditional trade statistics implies that thecomputation of the index in gross terms may bemisleading.Inparticular,countriessituateddownstreamin the supply chainmay spuriously incorporate in theirapparentcompetitiveadvantagesthere-exportedvalueaddedofupstreamsuppliers.

Figure B.22 is a 45-degree plot which compares the“traditional” RCA index against the same indicatorcalculated in value-added terms for machinery andtransport equipment (Panel A) and electrical andoptical equipment (Panel B), both industries having asignificantdegreeofverticalspecialization.


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FigureB.21:Relative variations of foreign content of exports versus gross exports, manufacturing sector, 1995-2007

Linear trend

0

5

2520151050-5

10Australia

Bulgaria

Brazil

Canada

China

Czech Rep.

GermanySpain

Estonia

France

United Kingdom

Greece

Hungary

Indonesia

India

Ireland

Italy

Japan

Korea, Rep. of

Latvia

Mexico

Netherlands

Poland

Portugal

Romania

Russian Federation

Turkey

Chinese Taipei

United States

15

Man

ufac

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xpor

ts in

crea

se

19

95

-20

07

% g

row

th in

gro

ss e

xpor

ts

VS 2007 – VS 1995

20

25

Foreign content of exports (VS) increases

Source:WTOSecretariatestimatesbasedonWIODdata.

Economies below the 45-degree line see their RCAreducedifmeasuredinvalue-addedterms.EconomiesabovethelinehaveahigherRCAinvalue-addedtermsthaningrossterms;inotherwords,thosecountriesareexportersofpartsandcomponentswithhighdomesticcontentwhichare furtherprocessedor assembled indownstream countries. In the case of Panel A, India,ChinaandMexico,forexample,seetheirRCAreducedwhen based only on domestic content; the reverse istrue forJapan, theRepublicofKoreaand theUnitedStates. For electrical and optical equipment, Chinaand Mexico, for example, show a reduction of theirRCA. Both countries are heavily engaged in exportprocessingzones.

(iv) Global rebalancing and trade in value-added

Accounting for intermediate goods may dramaticallychange bilateral trade balances between countries.Indeed,itwasoneofthemostsalientresultsofearlierresearchsuchasDaudinetal.(2006b).Tradestatisticsingrossterms,byreportingimportsbyfinalcountryoforigin,masktheoriginsoftheintermediateinputsandthus skew bilateral trade balances. This has beenparticularly relevant in the post 2008-09 globaleconomic environment, when mounting externaldisequilibria during the 2000s and their underlyingcauseswerepartlyblamedfortriggeringthecrisis.

Figure B.23 shows six economies’ bilateral tradebalances,measuredingrossandinvalue-addedterms.Both goods and services are included, and the

balances are shown with respect to five selectedpartners.While thecalculationbasedonvalue-addeddoesnotchangethetotaltradebalancewiththeworld,itre-distributesitaccordingtotheactualoriginofthevalue-added of imports and exports. For instance,China’stradesurpluswiththeUnitedStatesisreducedby almost 30 per cent if measured in value-addedterms.Theoppositechangecanalsobeobserved:thesurplus of Germany with the United States, forexample,increasesifconsideredinvalue-addedterms.

(f) Istradeconcentratedinthehandsofafewglobalcompanies?

Inrecentyears, theavailabilityof largenewdatasetsandtheincreasedcomputationalcapabilitytoprocesslargeamountsof informationhasallowedeconomiststousefirm-leveldatatoinvestigatetradepatterns.Thefindingssuggestthatcurrenttradeismainlydrivenbya few big trading firms across countries. Assessingwhether export (import) concentration among a fewplayersisarecentphenomenonornot,andwhetheritwill persist, is still a challenge given the limitedavailabilityofhistoricaldataatfirmlevel.However,therich literature on the current micro-level dynamics ofexporting firms, presented in this sub-section, is agoodstartingpointtounderstandthedeterminantsofaggregatetradeflowsandtobetterevaluatethefuturetrendsofinternationaltrade.

Firm participation in exporting activities is very rare(see Table B.12). For the United States, on average,18 per cent of manufacturing firms export (Bernard


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and Jensen, 1995; Bernard et al., 2007). A similarpattern is found in other developed economies, suchasFranceandJapan,aswellasdevelopingeconomies,such as Chile, Colombia and Indonesia. In addition,exporting firms ship a small share of their totalshipmentsabroad (intensivemarginof trade). For theUnited States, among exporters, exports representlessthan15percentoftheirtotalshipment(Bernardet al., 2007). European firms also export a relativelysmall share of their output: in countries such asFrance, the United Kingdom and Spain, the intensivemargin of trade represents on average less than30percent(EFIGE,2011).39

From Table B.13, we can also see that exports arelargely concentrated among a handful of exporters:1 per cent of larger exporters contribute more than80 per cent of total exports in the United States. Inaddition, the top 10 per cent of exporters account formore than 96 per cent of US exports (Bernard et al.,2009).FortheEuropeancountriesshown inthetable,the average shares of the top 1 per cent and top10 per cent of exporters are 50 per cent and85percent,respectively(MayerandOttaviano,2007).Developingcountriesshowasimilarpattern:onaverage,81percentofexportsareconcentratedamongthetopfivelargestexportingfirms(Cebecietal.,2012).

FigureB.22:Revealed Comparative Advantage (RCA) in gross and value-added terms, selected sectors, 2007

0.2

0.2 0.4 0.6 0.8 1.0 1.2 1.4 1.6 1.8

0.4

0.6

0.8

1.0

1.4

1.8

2.0

1.2

RC

A, v

alue

-add

ed

RCA, gross

Machinery and transport equipment, 2007

1.6

Korea, Rep. ofChinese Taipei

Japan

MexicoUnited States

ChinaPoland

Germany

Sweden France

United Kingdom

India

Romania

Canada

Italy

Turkey

Brazil

Denmark

Indonesia

Netherlands

Panel A

0.5

0.5 1.0 1.5 2.0 2.5 3.0

1.0

1.5

2.0

3.0

3.5

RC

A, v

alue

-add

ed

RCA, gross

Electrical and optical equipment, 2007

2.5Korea, Rep. of Hungary

Mexico

Japan

Finland

ChinaIreland

United States

Germany

Poland

FranceSweden

IndiaUnited Kingdom

Netherlands

Slovak Rep.

Czech Rep.

Spain

Panel B

Chinese Taipei

Italy


Note:Countriesabove/belowthe45°line(inbeige)haveavalue-addedRCAhigher/lowerthantheGross.


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FigureB.23:Bilateral trade balances measured in gross and value-added terms, 2008

United States

-10 -5 0 5US$ billions

10 15 20

Mexico

China

France

Germany

Brazil

United States


150 200 250

UnitedKingdom

Germany

Japan

Korea, Rep. of

100

China

United States


30 50 70

Canada

Spain

France

Germany

20 40 60

Mexico

Spain

-250 -200 -150 -100US$ billions

0 50

Korea, Rep. of

Japan

Mexico

China

-50

United States

Trade balance in value-added termsTrade balance in gross terms

United States

-6 -4 -2 0US$ billions

4 8

Netherlands

China

Hong Kong,China

Singapore

2 6

India

UnitedKingdom

-8 -6 -4 -2US$ billions

2 4

Japan

Germany

United States

China

0

South Africa

Italy

0 5 10 15US$ billions

20 25 30

Spain

France

United States

UnitedKingdom

Germany

China

-30 -20 -10 0US$ billions

40 50 60

Taipei, Chinese

United States

Germany

Japan

20 3010

Republic of Korea

Sources:WTOSecretariatestimatesbasedonOECDICIOdata.


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The fact that exporters are rare and concentratedamong a small number of firms implies that exportingfirmsareessentiallydifferentfromfirmsthatonlysellindomesticmarkets.Bernardetal. (2007)showthatUSexporters compared with non-exporters are larger (by97 per cent for employment, and 108 per cent forshipments), are more productive (by 11 per cent forvalue-added,and3percentfortotalfactorproductivity),payhigherwages(by6percent)andownmorecapital.AlsoamongEUmemberstates,exportershavehigherlabourproductivitythannon-exportingfirms(MayerandOttaviano,2007).Bernardetal. (2011)alsoshow thatfor the United States, similar conclusions can bereachedforimportingfirms:importersarebigger,moreproductive, pay higher wages and are more skill- andcapital-intensive than non-importers. In addition, theyshow that firms which both import and export (41 percentofUSexportersalso import,while79percentofimportersalsoexport) exhibit the largest performancedifferencescomparedwithdomesticfirms.

The exceptional performance of exporters acrosscountries raises the question whether exporters arealready “better” even before they start exporting, orwhetherexportingcausesproductivitygrowththroughsome form of “learning by exporting”. Many studiesconfirm that high productivity precedes entry intoexport markets. Das et al. (2007), for instance, showthat it is the potentially large sunk cost of enteringforeign markets that induces the self-selectionprocess among firms within industries so that onlythemostproductivefirmsexport. Incontrast, there islittle evidence supporting “learning-by-exporting”.40However, there isevidence thatfirmsenteringexportmarkets grow faster in terms of employment andoutputthannon-exporters.41

Theempiricalfindingssummarizedabovesuggestthatfirmsareheterogeneousordifferentfromoneanother.Thiswasignoredbytraditionalandnewtradetheories,where assumptions such as the existence of a

TableB.12:Share of exporting firms in total number of manufacturing firms (percentage)

YearShare of exporters in total number of

manufacturing firms

UnitedStates 1987and2002 18

Norway 2003 39.2

France 1986 17.4

Japan 2000 20

Chile 1999 20.9

Colombia 1990 18.2

Indonesia 1991-2000 19

Sources:WTO(2008)andAmitiandCameron(2012)forIndonesia.

TableB.13:Share of exports accounted for by the largest exporters (percentage)Country Year Top 1% Top 5% Top 10%

UnitedStates 1993 78.2 91.8 95.6

2002 80.9 93 96.3

EuropeanCountries

Belgium 2003 48 73 84

France 2003 44 73 84

Germany 2003 59 81 90

Hungary 2003 77 91 96

Italy 2003 32 59 72

Norway 2003 53 81 91

UnitedKingdom 2003 42 69 80

DevelopingCountriesa

Brazil 2009 56 82 98

Mexico 2009 67 90 99

Bangladesh 2009 22 52 90

Turkey 2009 56 78 96

SouthAfrica 2009 75 90 99

Egypt 2009 49 76 96

Iran 2009 51 72 94

Sources:BernardandJensen(1995),Bernardetal.(2007),MayerandOttaviano(2007),Cebecietal.(2012).

aFordevelopingcountriesreportedintheWBEDD,wereporttheexportssharebythetop25%firmsinsteadoftop10%firmsduetodataavailability.


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representativeandconsumerloveofvarietyimplythatallfirmsare identicalandallfirmsexport. Inspiredbythis, several theoretical works pioneered by Melitz(2003), combining the theoretical literature on firmheterogeneity43 with the Krugman model, have beensuccessful in explaining the observed facts aboutfirmsininternationaltrade(foramoredetailedanalysisoftheMelitzmodel,seeBoxB.4).

Finally,agrowingbodyofliteraturehasfocusedontherole of global firms: multi-product firms exporting tomultipledestinations.Bernardetal. (2007)showthatamong US exporters, 40 per cent exported a singleproducttoasingledestinationmarketandrepresentedaverysmallportion(0.2percent)oftotalUSexportsin2000.Conversely,asmallnumberoffirms(15.5percent of total exporters) exported more than fourproducts to more than four destination countries andrepresentedover90percentoftotalexports(PanelAof Table B.14). Cebeci et al. (2012) find a similarfeatureamongexportersfrom34developingcountries(Panels B and C illustrate the cases of Mexico andColombia): on average, 35 per cent of exporters aresingle-product,single-destinationfirmsandcontributelessthan3percentoftotalexports.Incontrast,multi-product,multi-destinationexporters,representingonly13 per cent of all exporters, contribute more than60percentoftotalexports.

Thedominantperformanceofglobalfirmsemphasizesthe importance of these “superstar” exporters in

shaping trade patterns. Studies such as Freund andPierola (2012), by focusing on the top 1 per cent ofexporters, show that these superstars are the maindriving forceof theRevealedComparativeAdvantageand theycontributeover three-quartersof theexportgrowth across countries. The analysis of globalexporters is also useful to highlight the mechanismsbehind the positive impact of trade liberalization onaggregate productivity. Baldwin and Gu (2009) andBernard et al. (2011) find that in Canada and theUnitedStatesrespectively,multi-productfirms,afterareduction in trade barriers (or a reduction incompetition in foreign markets), stop producing theleast successful products, which in turn increasesfirm-levelproductivity.

Theempiricalevidencesummarizedabovefocusesonmanufacturing firms. A handful of studies, mainly ondevelopedcountries,havealsoinvestigatedtheroleofservices firms in trade; their main findings are in linewith the previous literature. Breinlich and Crusciolo(2011)andGourlayetal.(2005)highlightthat,forUKservices firms, trade participation varies significantlybysectorandbyfirmsize. Inaddition, largerfirmsaremore likely tobeexportersandexportmore typesofservices to more destinations. Similar patterns arefoundbyGonzálezSanzandRodríguezCaloca(2010)for Spanish services firms. Evidence for German andDutchservicesfirmsalsoconfirms thatexportersarelarger, more productive and pay higher wages thannon-exporters.44 This result is also confirmed by the

BoxB.4: The Melitz model of heterogeneous firms

Melitz (2003)analyses intra-industry tradebetween two identical countries.On theproductionside,eachfirmproducesonesinglevarietyusingasinglefactorofproduction,labour,andatechnologywithincreasingreturnstoscale.Firmsdrawtheirproductivitylevelfroma“lottery”afterpayingaone-timefixedsunkcostofentry. In addition, firms have to pay an additional fixed cost to enter the domestic and foreign marketrespectively.Onlyfirmswithsufficientlyhighproductivity,orlowmarginalcosts,willbeabletosellenoughtocoverfixedcosts.Thethresholdmarginalcostforenteringthelocalmarketdependsonthefixedentrycostofenteringthedomesticmarketaswellasonpricesanddemandconditions.Similarly,thecut-offmarginalcost forenteringtheexportmarket isafunctionof thefixedcostofenteringtheexportmarket, thetradecosts,thepriceanddemandconditions.

Inthisset-up,wecanrankfirmsaccordingtotheirproductivity levelandclassifytheminthreegroupsandtwocut-offconditions–that is, twothreshold levelsofmarginalcost:firmswiththe lowestmarginalcostswill find it profitable to pay the entry cost for both the domestic and export market, while firms withintermediateproductivity levelswillfind itprofitable topayonly theentrycost for thedomesticmarket. Inotherwords,onlythemostproductivefirmsbecomeexporters.

Inaworldwhereexportersaremoreproductiveandgrowfasterthannon-exporters,tradeliberalizationwillforcetheleastproductivefirmstoexitthemarketandreallocatemarketsharesfromlesstomoreproductivefirms. Thus, the least productive non-exporting firms will be forced out of the market due to increasedexposure to competition, but a set of new firms with higher productivities will start exporting because ofincreased sales from foreign markets. This process induces the reallocation of resources towards moreproductivefirms,andthuswillincreaseaverageindustrialproductivity.

Thepredictionsof theMelitzmodelareconfirmedbyaseriesofempirical studieson the impactof tradeliberalizationonbothfirmandaggregateindustryproductivity.42Inaddition,themainempiricalfactsonfirmsandtradecanalsobefoundinmodelswherethedifferences inproductivityacrossfirmsare includedinaRicardianframework(EatonandKortum,2002).


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USTradeCommissioninastudyofsmallandmedium-sizedenterprises.45

The firm-level evidence presented in this section hassignificant implications for future trade. First, theevolutionofaggregatetradeflowscanbeevaluatedbyidentifyingandanalysingthebehaviourofahandfulofbigexportingfirms.Also,giventhatbiggerfirmsexportmore products to more destinations, understandingtheperformanceofsuchfirmswillshedsomelightonthecontributionoftheextensivemarginoftradetotheobserved increase in international trade in the lastdecades.46Fromapolicyperspective,theexistenceoffirm heterogeneity suggests that fixed costs ofexportingandnotonlytariffsareimportantinaworldwhere firms have different levels of productivity andface economies of scale in production. Finally, theprominenceoftheso-called“superstar”exportersinaworld characterized by an increased role ofinternational fragmentation of production highlights

thenecessitytofurtheranalysethedecisionsofsuchfirms in termsofproduction locationand involvementinsupplychainactivities.

The facts about current developments in tradepresentedinthissectionwillbeusedasguidelinestounderstandandevaluatefuturetradescenarios,whichisthefocusofthenextsection.

3. Futureeconomicandtradescenarios

Thissectionwillprovideanoverviewofexisting long-termprojectionsoftrade,explainingbrieflyhowtheseareusuallymade (seeBoxB.5).Wewill thenprovideourownprojectionsonthebasisofseveralscenarios,both optimistic and pessimistic, illustrating keyfeatures of the changing landscape of trade.47 Theprincipal purpose of these simulations is not

TableB.14:Distribution of exporters and export value (percentage)

Panel A. United States 2000

ShareofexportingfirmsShareofexport

value

Numberofdestinations Numberofdestinations

Numberofproducts

1 2 3 4+ AllNumberofproducts

1 2 3 4+ All

1 40.4 1.2 0.3 0.3 42.2 1 0.20 0.06 0.02 0.09 0.4

2 10.4 4.7 0.8 0.7 16.6 2 0.19 0.12 0.04 0.18 0.5

3 4.7 2.3 1.3 0.9 9.2 3 0.19 0.07 1.05 0.22 0.6

4+ 8.5 4.3 3.7 15.5 32.0 4+ 2.75 1.31 1.10 93.40 98.6

Total 64.0 12.5 6.1 17.4 100 Total 3.3 1.6 1.2 93.9 100

Panel B. Colombia 2009


value


Numberofproducts


1 2 3 4+ All

1 34.5 4.4 1.6 3.0 43.5 1 3.7 3.2 0.9 5.0 12.8

2 9.0 3.9 1.3 2.6 16.8 2 4.7 2.9 0.4 5.0 13.0

3 4.3 2.1 1.2 2.0 9.6 3 1.6 1.5 1.4 5.7 10.2

4+ 9.9 4.5 3.4 12.2 30.0 4+ 4.5 3.1 1.2 55.2 64.0

Total 57.7 14.9 7.5 19.8 100 Total 14.5 10.7 3.9 70.9 100

Panel C. Mexico 2009


value


Numberofproducts


1 2 3 4+ All

1 39.3 2.0 0.5 0.8 42.6 1 3.0 0.2 0.2 0.3 3.7

2 10.1 2.6 0.7 0.7 14.1 2 1.4 0.2 0.1 0.3 2.0

3 5.2 1.5 0.7 0.8 8.2 3 1.4 0.2 0.3 0.6 2.5

4+ 17.4 5.0 2.8 9.9 35.1 4+ 19.6 7.2 2.8 62.1 91.7

Total 72.0 11.1 4.7 12.2 100 Total 25.4 7.8 3.4 63.3 100

Source:ThedataforColombiaandMexicoarefromtheWorldBank’sExporterDynamicDatabase.

Note:PanelAdataarefromthe2000Linked/LongitudinalFirmTradeTransactionDatabase.ThetabledisplaysthejointdistributionofUSmanufacturingfirmsthatexport(leftpanel)andtheirexportvalue(rightpanel)accordingtothenumberofproductsthatfirmsexport(rows)andtheirnumberofexportdestinations(columns).Productsaredefinedasten-digitHarmonizedSystemcategories.SimilarinformationisprovidedforPanelsBandC.


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necessarily to provide better projections thanelsewhereintheliterature,buttoportrayresultsinthewayinwhichdiscussionsareusuallyframedwithintheWTO context (country groups, main sectors) and todemonstrate the sensitivity of outcomes to keyassumptions as far as both economic fundamentalsand policy scenarios are concerned. The latterdiscussionwillalsofeedintothein-depthexaminationof those factors that will fundamentally shape worldtrade in the long term, notably demographics,investment, technological progress, energy/naturalresources, transport, institutions as well as tradepoliciesandrelatedpolicymeasures,intheremainderoftheReport.

(a) Overviewoflong-termprojections

Simple extrapolations of current trends are a first,straightforward way of making predictions about thefuture development of key economic parameters.Although these techniques are capable of producingadequate forecasts for world trade and output, theirpredictive power diminishes over time and dependscruciallyonthenatureoftheirunderlyingassumptions.Ease of computation adds to their appeal despite alackofanalyticalrigour.Atbest,theyprovideplausibleinitial estimates of important economic aggregates,which can then serve as benchmarks for evaluatingtheoutputofmoresophisticatedapproaches.

BoxB.5: How are long-term trade projections made?

Long-term projections of trade usually proceed in two steps: first, as the volume of trade depends oncountries’GDPs(asamplydemonstratedinthe“gravity”literature),trajectoriesofeconomicgrowthmustbedeveloped.Thisisdoneusingamacroeconomicmodel.Severalapproachesexist,allowingformoreorlesscountry detail. Based on the extensive literature on economic growth, models usually take into account“conditionalconvergence”,i.e.thefactthatcountrieswitharelativelylowGDPpercapitagrowfaster,subjecttocountry-specificstructuralfactorsandpolicies.FontagnéandFouré(2013),onwhichthesimulations inthisreportarebased,employthreefactorsofproduction(labour,capitalandenergy)besidestechnologicalprogress.48

Different studies may make varying assumptions about these fundamental economic factors, how theydevelopandhowtheyare interrelated.FontagnéandFouré(2013), for instance,determinethefuturesizeandcompositionof the labour forceasa functionofpopulationgrowth,ageing, labour forceparticipation,educationandmigration.Similarly, theyallow fordifferentdegreesof internationalcapitalmobility,energyefficiency and total factor productivity improvements. By projecting each variable forward based onestimationsofpastbehaviour,areferencescenarioisdevelopedforallofthecountries/regionsinthemodel,taking into account interlinkages with other relevant variables. For instance, a projection of educationalconvergenceinthefuturedependsonboththisvariable’spastbehaviouranditsinterdependencewithfuturedemographicdevelopments.

By imposing overall “closure” rules, such as global savings being required to equal global investment, thetheoretical macroeconomic framework ensures that country-level baseline projections are consistent withone another and result in a coherent set of growth projections for the world economy. A simulation thenconsistsofintroducinga“shock”,i.e.adefineddeviationofanindividualvariablefromitsbaselineprojection,inordertoseewhatdifferenceitmakesintermsofeconomicoutcomescomparedwiththebaseline.Notalleconomic“shocks”affectdevelopedanddevelopingcountriesalikeandmostmodels,includinginthisreport,allowfordifferentiated,morerealisticscenariosdependingonlevelsofdevelopment.

Secondly,futuretradepatternsneedtobemodelled.Countriesdifferinfactorendowments,technologyandthe relative economic importance of individual sectors, and different sectors employ factors at differentintensities. In addition, the product composition of demand changes at varying levels of income. As aconsequence, countries will experience structural change in terms of consumption, production and trade.Factorre-allocationsanddemandpatternsareinfluencedbypricesindifferentmarkets,whichultimatelyallneed to be in equilibrium. This is why, for this second step, a traditional Computable General Equilibrium(CGE)modeloftheworldeconomycanusefullybeemployed.49

Dependingontheextenttowhichthebasketofgoodsandservicesconsumeddiffersfromwhatisproducedlocally, trade flows emerge, conditional on the evolution of trade costs. Ultimately, countries specialize invariousgoodsandservicessectors,takingadvantageoftheirfactorendowments,technologyandproximitytodemand. In thesimulationspresented in this report,different typesof tradecostsareconsidered,bothgeography- and policy-related. The former depend on the transportation sector and the evolution of fuelprices.Asfarasthe latterareconcerned,bothtrade“taxes”andothernon-tariffmeasures,suchascostsrelatedtocustomsclearanceandinspectionofgoods,aswellasservicesbarriersareconsidered.


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FigureB.24showssimpleprojectionsofreal(inflation-adjusted) GDP and real merchandise exports fordeveloped and developing economies up to 2030 at2005 prices and exchange rates. World GDP growthwasestimatedastheweightedaverageofactualandprojected GDP growth rates for available countriesusing2005GDPvaluesasweights.GDPforecastsforindividualcountriesup to2017wereobtained fromavarietyofsources, includingtheIMF,OECDandotherpublic and private forecasters. Next, growth rates for2018-30 were estimated either by an ordinary leastsquaresregressionorbytakingaveragegrowthratesover the last few years of the series. Finally, growthrates for the world, individual countries and countrygroups were applied to the 2005 base year GDPvalues to calculate values and shares up to 2030 in2005USdollars.

This approach results in some questionably largeestimates for GDP growth in certain developingcountries, particularly fast-growing Asian economiessuchasChinaandIndia.Thishastheeffectofinflatingprojected GDP values for these countries to the pointwherethesumofindividualcountryvaluesin2030wasabout 10 per cent larger than a simple projection ofaggregateworldGDPwouldindicate.Thissuggeststhatoutputgrowthintheseeconomiesislikelytoproceedata slower pace in the future than in recent years.50 Toaccount for this expected slowdown, estimates forChina,Indiaandotherswerescaleddownonanadhocbasiswhilestillremainingwellabovetheworldaverage.

After theseadjustments,FigureB.23has theshareofdevelopedcountriesinworldGDPfallingto61percentin 2030 from 71 per cent in 2010, and the share ofdevelopingeconomiesrisingto39percentfrom29percent over the same period. If this forecast is realized,the reduced share of developed economies will comemostly at the expense of the European Union andJapan,whoserespectivesharesinworldoutputwillfallto22percentand6percentin2030,from28percentand 9 per cent in 2010. Meanwhile, the share of theUnitedStatesshouldremainrelativelystablethroughoutthe forecastperiodataround25percent,despite thefalling share for developed countries overall. On theotherhand,China’sshare inworldGDPisprojectedtoincreasefrom8percentto15percentbetween2010and 2030, while its share in developing economiesoutputrisesfrom26percentto37percent.

World trade growth was estimated up to 2030 byapplyinganassumedincomeelasticityof1.5toworldGDP growth in line with the elasticity estimate inFigure B.4. Exports of developed countries wereassumed to grow at a continuous rate estimated byleastsquaresregression,withremainingtradegrowthattributed to developing countries. China’s rate offuture export growth was simply equated to theaveragerateover the last fewyears.Onceagain, thisproducesanunrealistically largeestimateofChinesegrowthinthefutureduetorecenthighgrowthrates.Ifthisrate isextrapolatedto2030, thevalueofChina’sexports at the end of the period is larger than a

FigureB.24:Simple extrapolations of world real GDP and real exports, 2000-30 (billion2005US$)

EU (27)Japan

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United StatesOther developed economiesNICs (6)India

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similarly extrapolated value for all developedeconomiestakentogether.

InlinewiththeapproachforGDP,weassumedthattherate of increase in Chinese exports will moderate inthe future while remaining well above the worldaverage.Withthisadjustmentinplace,weexpectthatdeveloping economies will see their share in worldexportsrisefrom41percentin2010to57percentin2030, while the share of developed economies dropfrom 59 per cent to 43 per cent. China’s exportsshouldincreaseasapercentageofbothworldexports(9percentto15percent)anddevelopingeconomies’exports (23 per cent to 27 per cent) over this timeperiod.51

Figure B.24 paints a reasonably realistic picture offuturetrendsintradeandoutputbuttheuseofadhocassumptionsbasedoninformedjudgementmakestheresultslessgeneralizable.Formorereliableestimates,theoreticallygroundedmodelsareneeded.AsnotedinBox B.5, for the task at hand it is useful to combinemacroeconomic growth models with multi-sector,multi-regionalmodelsoftrade.

(i) Macroeconomic projections

Anumberofinstitutionsinrecentyearshaveemployedmacroeconomic models to make projections of long-term economic growth. Prominent examples includestudies by the World Bank, the Asian DevelopmentBank,OECDandCEPII(Centred’EtudesProspectiveset d’Informations Internationales).52 Not all of thesestudies are subsequently used to develop baselinemacroeconomic projections for trade analysis in aComputable General Equilibrium (CGE) modellingframework. It is common to such macroeconomicmodels that assumptions need to be made on keygrowth determinants,53 notably developments in thelabour force and human capital, physical capital,natural resources (energy, land) as well astechnological progress (here measured as “multi-factor productivity” or “total factor productivity”).Model outcomes may be sensitive to the preciseassumptionsmadeforeachofthesevariables.

For example, OECD (2012c) assumes that countrieswill succeed in continuously improving access toeducation,whichwillhaveanoverallpositiveinfluenceon the size and composition of the labour force.Fontagnéetal.(2012)andFouréetal.(2010)ofCEPIImake a similar overall assumption but allow fordiffering speeds of convergence of educationalattainment.Suchvariationoftendoesnotmakeiteasytocomparetheresultsofdifferentstudiesandidentifywhatdrivesaparticularresult. Inparticular,whenoneis interested in results at the country level, suchdifferencescanplayanimportantrole.However,asfarastheoveralleconomictrendsandtheirdrivingforcesare concerned, the main long-term macroeconomicprojectionsbroadlyconcurintheirresults.

In terms of economic outcomes, all of the studiesreviewed find that differences in GDP per capita willnarrow.For2030,WorldBank(2007)predictsgrowthin developed countries to remain at the long-termaverageofabout2percent,whilegrowthindevelopingcountrieswouldaccelerate fromanaverageof2.4 to3.1 per cent. OECD (2012c) projects similar growthrates up until 2060 but it highlights that despite the“catching-up” process, today’s rich countries wouldcontinue to lead in terms of GDP per capita.54However,therelativesizeofeconomieswouldchangedramatically.

OECD (2012c) forecasts that OECD countries’ shareinglobalGDPwoulddeclinefromcurrentlytwo-thirdsto about one-half in 2030 and to only about 44 percentin2060.Amongthenon-OECDcountries,China’sand India’s share would increase substantially, withhardly any changes in the share of other non-OECDcountries.ChinawouldexpanditsglobalshareinGDPfrom 17 per cent in 2011 to 28 per cent in 2030(where it would remain in 2060), while India wouldexperienceitsmajorexpansionafter2030,risingfromcurrently 7 per cent to 11 per cent in 2030 and to18percentin2060.

As far as the drivers of economic growth areconcerned, technological progress has by far thelargest impact in these models. OECD (2012c), forinstance, shows that productivity improvementsaccount for more than two-thirds of average annualGDPgrowthforalmostallofthecountriesconsideredand can explain much of the differences in growthrates among countries in the next 50 years. Asemphasized by both OECD (2012c) and the AsianDevelopmentBank(2011), thenotableexceptionmaybe certain middle-income countries, which need tomakethetransitionfromagrowthstrategybasedonalargepoolof labour,capitalaccumulationor resourceextractiontowardsTFP-drivengrowthinanattempttoward off competition from low-income economies ontheonehandandtotakeonadvancedeconomiesontheother.Oilproducersareanotherexception,astheirGDPlargelydependsonthepriceofenergy.

Demographics also play an important role in therelative growth performance of economies, withcountries such as India and South Africa benefitingfrom the so-called “demographic dividend” (seeSection C.1 for an extensive discussion), while mostadvancedeconomies,aswellasChina,arelikelytobeweighed down by increased dependency ratios.Whethertheformercountrieswillbeabletotranslatefavourable demographics into labour force-drivengrowthperformancewilldependonarangeoffactors,mostimportantlythebuild-upofhumancapitalandtheparticipation of women in the workforce. For others,theagestructureofsocietyaswellasmigratoryflowswill be important considerations (Fouré et al., 2010;AsianDevelopmentBank,2011;OECD,2012c).


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Capitalaccumulationstill remainsan important factorfor economic growth in many countries. With savingsratesprojected todeclinealmosteverywhere (OECD,2012c), capital mobility can play an important role ineconomic performance, particularly for certaindeveloping regions (Fouré et al., 2010). In addition,capital formation drives the capital per worker ratioand hence the comparative advantage of countries –animportantdeterminantoftradepatternsinthelongrun.

Atfirstsight(andsomewhatsurprisingly),energypriceincreases play a relatively minor role for economicgrowth prospects when ensuing improvements inenergy productivity are considered on the basis ofhistorical experience (Fouré et al., 2010). Suchadvances include enhanced substitution possibilities,technological progress in regard to new uses andbehaviouraladjustmenttopricedevelopments.Similarprogress will have to be made for other naturalresources, for which prices are likely to increase,particularly in Asia, where consumption of primarygoods will grow in line with further industrialization(AsianDevelopmentBank,2011).

Finally,someofthesestudieshighlighttheimportanceof macroeconomic policies, such as fiscalconsolidation, for future growth prospects (OECD,2012c; Asian Development Bank, 2011). OECD(2012c) also mentions improvements in productmarket regulation. When the focus is on tradeoutcomes, some of these policy assumptions andbroader institutional issues are better introduced inthe more detailed multi-sector, multi-region CGEframework,aswillbefurtherdiscussedbelow.

(ii) Global trade simulations

Inordertomovefrommacroeconomicprojectionstoamore detailed analysis of future world trade flows,most studies use one of the leading global generalequilibrium models that exist (Global Trade AnalysisProject,Mirage,Linkage)butmanyconfinethemselvesto an analysis of certain sectors or a focus on aparticularregion.55

WorldBank(2007)wasanearlystudyfeaturinglong-term predictions of trade for the time horizonconsidered in this report. The simulationsweremadein the context of the World Bank’s Global EconomicProspects(GEP)Report(2007),whichwasdevotedtothe“nextwaveofglobalization”,andprovidedforecastsuptotheyear2030.Theauthorsofthestudydidnotemploy an explicit, independent macroeconomicgrowth model in a first step but directly imposedassumptions over TFP growth on the World Bank’sstandard multi-sectoral, multi-regional CGE model(Linkage). They also assumed an autonomous 1 percent per year increase in energy efficiency for allregions and a 1 per cent yearly decrease ininternationaltradecosts.

Thestudyfinds that tradewouldcontinue tobemoredynamicthanGDP,withthelevelofexportsmorethantriplingand theworldeconomy increasingbya factoroftwowithinthetimeframeconsidered.Thiswouldbeparticularlytruefordevelopingcountries,whichwouldsee their exports increase by a factor of four. Thesetrade predictions assume no changes in policy. Ifuniversal reductions in applied protection onmerchandise trade by three-quarters are added,exports by developing countries would increase byaboutanotherone-fifth.

Since then, interest in long-term trade analyses haspicked up significantly, perhaps as a result of theeconomic crisis and perceptions of increaseduncertainty. Petri and Zhai (2012) use themacroeconomicprojectionsbytheAsianDevelopmentBank (2011) as a baseline in their own CGE modeland,onthisbasis,analysepotentialstructuralchangeand policy challenges faced by the Association ofSoutheast Asian Nations (ASEAN), China and Indiaunder different scenarios. As in World Bank (2007),the authors choose the year 2030 as their forecasthorizon and, in the benchmark scenario, obtainsimilarlyoptimisticresultsforthecountriesexamined.They find that incomes would quadruple and povertywould almost be eradicated. The region would alsoconstituteonehalfofanewglobalmiddleclassbytheend of the forecast horizon. As far as trade isconcerned, the strongest increase would take placeamongdevelopingcountries, reaching36percentofglobal trade in 2030, with developed-developingcountrytradeincreasingslowlyto43percentofworldtrade and trade between developed countries fallingsharplytoonly21percent.

The authors then subject their CGE baselineprojections to a number of potential “shocks” in keyfactors that could derail the economic outlook. Theyfind adverse productivity shocks to be the mostimportant factor affecting long-term economicprospects.Even if adeceleration inproductivitywereonly to take hold in developed countries (not entirelyunrealistic given the current subdued economicenvironment), the Asian economies examined wouldsuffer. Another important assumption concernsadvances in energy efficiency and conservation: if,unlike in the past, projected energy price increaseswere not matched by technological improvements,baseline economic growth prospects would besubstantially reduced. On the positive side, anambitious global trade agreement could more thancompensateformostoftheadverseshockssimulated,with the exception of technological slowdown in thedevelopingcountries.56

Anderson and Strutt (2012) also consider the year2030,usingthesamemacroeconomicforecast(AsianDevelopment Bank, 2011) supplemented withprojections from CEPII (Fouré et al., 2010) forcountries not represented in the Asian Development


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Bank sample. They also adjust developments in anumber of key factors, such as labour forcecomposition and growth, energy and land resources,using data from specialized publications. From this,theybuildamacroeconomicbaselineprojectionfortheGlobal Trade Analysis Project (GTAP) CGE model,perhaps the most widely used model for world- andeconomy-wide trade analysis. The bright outlook fordeveloping countries (especially in Asia) in terms ofgrowth in economic weight and convergence in percapitaincomesissimilartoPetriandZhai(2012).

AndersonandStrutt (2012) thenproceed toprovideamoredetailedanalysisofpredictedtradepatternsatthecountryandsectorallevels.Accordingtothisstudy,thedeveloping world would continue to see itsmanufacturing share in world exports increase fromabout 22 per cent in the base year (2004) to38 per cent in 2030. As a function of their continuedrapid industrialization, developing countries wouldimport an increasing share of agriculture products,other primary products (more than quadrupling theirinitialshareovertheforecasthorizon)andmanufacturedgoods.Thesedevelopmentswillleadtoimportantshiftsin bilateral trade patterns. In line with Petri and Zhai(2012), the share of South-South trade in total tradevolumesispredictedtoriseto30percent,whiletradeamong industrialized nations would fall drastically tojustaboveone-quarterofglobaltrade.Theauthorsalsoprovide additional directional details of future tradeflows by constructing regional trade indices. Theprojectionsindicateageographicaldispersionoftrade,with the current high intensity of intra-regional trade,particularly in Asia (see Section B.2(d)), declining andthe propensity to trade with other regions becomingrelativelymoreimportant.

AndersonandStrutt (2012)also implementanumberof alternative scenarios in their CGE analysis.Considering the possibility of persistent subduedgrowth, currently an acute concern in developedeconomies, they show that the structuraltransformationofmajordevelopingcountries towardsnon-primary sectors would be delayed. The authorsalso simulate various trade policy scenarios. Mostnotably,liberalizationwouldfurtherimprovetheSouth-South share in global trade. They note that othershaping factors of world trade, notably transport andcommunicationcosts,areheldconstant.Ifthesewereto continue their long-term decline, trade benefitsshouldfurtherincrease.Atthesametime,theauthorsalso acknowledge protectionist risks. They note, forexample, that the projected increase in farm productimports, particularly by China and India, could beparticularlysensitivetotradepolicyintervention.57

Finally, Fontagné et al. (2012) combine CEPII’smacroeconomicmodel (MaGE)with itsmulti-sectoraldynamic CGE model of the world economy (Mirage).Their study, which considers a 2100 time horizon, istargeted mainly at evaluating policies related to

environmental issues, notably CO2 emissions thatcould feed into larger climate studies, rather thantrade analysis. Because of the long time horizon,forecasts for certain exogenous variables requirefairly keen assumptions. GDP developments aresimilar to other macroeconomic studies discussedabove: developed countries’ growth hovers around2percentover thewhole timehorizon,whilevariousemergingeconomiesovertakeeachother intermsofgrowthdynamics.While initially,China’sgrowth ratestopallothers,itiseventuallyovertakenbyIndiawhichbegins togrowfasterafter2035.By2100, themostdynamic region is Sub-Saharan Africa, maintaining4percentannualgrowthonaverage,closelyfollowedby Brazil which does not experience the samedecelerationofgrowthdynamicsassomeoftheotheremergingeconomies.

ThestudypresentstraderesultsfortheUnitedStates,Japan,theEuropeanUnionandChina.Themaininsightis that with certain exceptions, export specializationdoesnotchangethatmuch.Chinawouldbecomeanetmachinery exporter and remain an important exporterofelectronicdeviceswhilecontinuingtoimportprimarycommodities, increasingly also food and agriculturalproduce.Machineryexportsharesdeclineforalloftheindustrialized countries examined but for Japan othermanufactured goods become more important exports,while the United States and the European Unionincreasetheirservicesexports.TheUnitedStatesalsodevelopsintoagasexporter.

Despitesomecommontrendsandbroadinsightsthatcanbederivedfromthesestudies,nocomprehensivepicture emerges regarding economic activity andglobal trade patterns in the decades ahead, which isthefocusofthisreport.Wehavethereforeincludedaset of “tailor-made” simulations in the Report todevelop consistent scenarios for the macroeconomicgrowthandCGEtrademodelsatthegloballeveluntil2035.Therearefurtheradvantagestoconductingourownsimulations,althoughthesecanhardlybesaidtobe better or worse than existing approaches in thetradeliterature.Inparticular,assumptionscanbespeltoutindetailandthesensitivityofoutcomestovariousscenarioscanbedocumentedclearly.

Furthermore, the multitude of results can beaggregated and summarized by region and sector inthewayinwhichdiscussionsusuallytakeplaceinthecontext of the WTO. The simulations presented hererelyonthemodellingapproachintroducedinFouréetal. (2010)andFontagnéetal. (2012)butareadaptedto the specific interest at hand.58 To our knowledge,it is the only exercise conducted so far at this scaleand time horizon, for which the macroeconomicbaseline scenarios are fully traceable throughoutthesubsequentCGEsimulationsof trade,makingtheentireframeworkinternallyconsistent.


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(b) Asimulationoftheworldeconomyoverthenexttwodecades

Inordertoenvisagetherangeofpossibleglobal tradepatternsinthedecadesahead,itisimperativetoincludeall the principal drivers of economic activity andinternational trade in the modelling framework. At thesametime,thehighdegreeofunpredictabilityofcertainvariablesneedstobeacknowledged.Energyprices,forinstance,arenotonlya functionof theeconomic lawsof supply and demand but are strongly affected bygeopolitical developments that are hard to predict atany level of confidence. The same is true for otherfactors, such as migratory flows, international capitalmobility as well as technology transfer and innovationthat are highly uncertain by nature and subject todevelopments beyond the scope of any economicmodel. Though less uncertain, projections regardingeducational convergence must also be handled withcaution.Therefore,whilethesimulationsareundertakeninatheoreticallyrigorousandcomprehensivemodellingframework,weallowforuncertaintybydevelopingtwo“extreme”trajectoriesforallkeyvariables.

By combining simultaneously the “high” and “low”scenarios (depending on the expected GDP impact)respectively foreachvariable,weareable todevelopan upper and lower boundary for our overallprojections. Combining “shocks” on the down- andupsides also takes account of the fact that bothadverse and positive developments tend to cluster.Most notably, it has been shown time and again thatperiods of economic crisis tend to go hand in handwith protectionist tendencies and vice versa. Hence,whilenoneoftheseextremetrajectoriesmayrepresentthe most plausible scenario for the future, which is

likely to fall somewhere in between, these bandshighlightrisksandopportunities,settingoutarangeofpossibletrackstheworldeconomyandtradecantakein thefuture.BoxB.6providesanoverviewandshortdescriptionofthescenarioschosenforeachkeydriverofeconomicgrowthandinternationaltrade.59

(i) Economic growth trajectories

TableB.15showstheprojectedaverageannualgrowthrates for major countries and regions in themacroeconomic model along with the GDP levels inconstant dollars to be attained by 2035, which areimpliedby theseGDPgrowth rates. Italsoshows therespectivesharesinglobalGDP.Thecombinedeffectsof the “high” and “low” scenarios for all main driverscan be read from the table as a deviation from thereferencescenario.FigureB.25visuallyportraysthesegrowthtrajectories.

ItcanbeseenthatChinaisprojectedtoovertaketheUnited States and the European Union in terms ofeconomic size at the latest by 2030 in the “high”scenario. The economic development of India isprojectedtoonlytakeoffunderthe“high”scenario,inwhichcaseitwouldreachChina’s“low”scenariolevel.Similarly, for Sub-Saharan Africa, attaining the “high”scenario makes a substantial difference: rather thanvirtuallystagnating,itcouldovertakeBrazilintermsofeconomicimportanceevenbefore2030.

Overall, the level of uncertainty, as implied by thevariation between high and low trajectories, is quitesubstantial. Whether the growth path ultimatelyrealizedisclosertooneortheother“boundary”couldmake a big difference, particularly for developing

FigureB.25:Simulation of GDP under two different scenarios (high, low), 2000-35 (billion2005US$)

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countries,whoseaverageannualgrowthrateovertheforecast period may vary by as much as 2 per cent,resultinginaboutone-thirdloweror50percenthigherper capita incomes by 2035. For certain countries,such as China or India, the divergence of differentgrowthpaths iseven largerandmuchwilldependonhowsomeofthemaindrivingfactorsdevelopandmaybeshapedbypolicy.

Giventhebreadthofpossibleoutcomes,itisusefultovary one “shaping factor” at a time to isolate itsindividualimportancefordeviationsfromtheprojectedgrowth path. As in previous studies, technologicalprogresshasbyfarthelargest impact.Fordevelopedcountries,ourscenariosimplybarelyonehalfofapercent more or less growth per year, amounting to

around 9 per cent higher/lower GDP levels in 2035.Conversely, for developing countries, continuedimprovements in technological progress make a bigdifference, ranging fromaboutplus/minus1percentgrowthimpactperannumforBraziltoover2percentfor China. As a result, projected GDP levels in 2035would be about 20 per cent larger/smaller in Brazilandvarybymorethan55percentinChina.

For developing countries overall, adding/shaving offabout 1.5 per cent GDP growth per annum throughcontinued/slowed down technological progress leadsto a variation of about 30 to 40 per cent in GDP by2035. Given the heightened importance oftechnological progress for developing countries, inorder to catch up with the developed world, the

BoxB.6: Overview of simulation scenarios

Thetablebelowshowsthe“boundary”scenariosthathavebeenimplementedinoursimulationexercisetoaccountfortheuncertaintysurroundingourbaselineprojectionandtoillustratethesensitivityofeconomicandtradeoutcomestotheassumptionsoverpotentialdevelopmentsinkeyshapingfactors.Thetableshowsthetwoscenariosthathavebeenimplementedforeachmain“driver”:60

Low High

Labour

Demography Referencecaseinhigh-incomecountries,lowfertilityinother(UNDP)

Referencecaseinhigh-incomecountries,highfertilityinother(UNDP)

Educationconvergence 1.5half-lifetime 0.5half-lifetime

Femaleparticipation Noimprovements Referencecase

Migration Referencecase AdditionalmigrationfromSSAandMENAtoEUandfromSAMtoUS

Capital

Capitalmobility ConvergencetoI=Sin2050LowFeldstein-Horiokacorrelationcoefficient(asinnon-OECD)forallcountries

Natural resources

Energyprice Highpricescenario(EIA) Lowpricescenario(EIA)

Energyproductivity +50%highincomein2050,referencecaseinother

+50%lowandmidincomein2050,referencecaseinother

Technology

TotalFactorProductivity

-50%TFPgrowthrateforlow-andmid-incomecountries,-25%forhigh-income

+50%TFPgrowthrateforlow-andmid-incomecountries,+25%forhigh-income

Trade costs

Tariffs "Tradewar":Returntopre-UruguayRoundappliedtariffs "Tradeopening":-50%inappliedtariffs

Othertransactioncostsongoods +50%dgcs,+20%ddcs -50%dgcs,-20%ddcs

Servicesbarriers Nochange "Tradeopening":-50%inservicesbarriers

Notes:Tradecostsonlyvaryinthetradescenarios.

“Referencecase”meansthatavariableisprojectedforwardonthebasisofitsestimatedbehaviourinthepast,takingintoaccountalsointerlinkages with other relevant variables. This is done for all countries in the model individually and may imply an improvement ordeteriorationdependingontheestimatedbehaviourforthecountryinquestion.Atthegloballevel,inthereferencecase,Mirageissettoreproduceaconservativeelasticityofworldtradetoincomeobservedinthelongrun(withtheexceptionofthe1990s,characterizedbytheexpansionofglobalvaluechainsandthesurgeofnewbigtraders).

Regardingeducationalconvergence,half-life time is the timeacountrywill take to reduce itsdifferencewith the initialpositionof theleaderbyhalf.Here,theleaderisavirtualcountrycomposedoftheleadersforeachagegroup,levelofeducationandtimeperiod.

TheFeldstein-Horiokacorrelationcoefficientisnamedaftertwoeconomistsobservingahighcorrelationbetweendomesticsavingsandinvestmentrates,whichcontradictsapresumptionofperfectcapitalmobility,withinvestmenttakingplacewherethehighestreturncanbe achieved. A lower Feldstein-Horioka correlation coefficient in OECD countries here means that the correlation between domesticsavingsanddomesticinvestmentisassumedtobelower,asinnon-OECDcountries.Thisimpactstheallocationofinvestmentbetweencountries,whichisreducedintheformerandincreasedinthelatter.


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“deceleration” scenario would imply about 6 per centhigher shares in global GDP (albeit at lower overalllevels) for developed countries and vice versa.61SectionC.3discussesinmoredetailwhatdeterminestherateoftechnologicalinnovationandcatch-up.

Another important factor shaping future economicoutcomes is demography. Population growth/declinehasa significant impacton the labourpool in certaindeveloping countries, most notably in India, Sub-Saharan Africa and China.62 Under any of ourscenarios, Sub-Saharan Africa’s active population ispredicted to overtake China’s by 2045 at the latest,and possibly several years earlier. Without furtherimprovementsineducation,thedemographiceffectonGDP is comparatively small under our scenarios,increasing or decreasing GDP in 2035 by about1percentinthecountriesmentionedabove.

Ifthegapineducationalattainmentbetweenrichandpoorcountriescanbenarrowedfaster thanwhathashitherto been the case, developing countries in theMiddleEastandNorthAfrica,Sub-SaharanAfricaandLatinAmericaaswellasIndiacanincreasetheirGDPby about 3 per cent in 2035. Increased femaleparticipationineducationiscrucial inmanycountries,particularlyIndiaandtheMiddleEastandNorthAfrica,where a lack of action in this regard would beassociatedwitha4percentlowerlevelofGDP.

In many developed countries, the extent of migrationhas by far the largest economic impact amongdemographic factors, as it changes not only the sizeand composition of the labour force but, in light ofageing societies, also plays a major role forconsumption/savings behaviour. If the number ofmigrants into the North from regions such as the

MiddleEastandNorthAfrica,aswellasSub-SaharanAfrica for the European Union and South Americafor the United States, were to increase by around1 million per year and region, GDP in destinationcountrieswouldrisemorethanoverallpopulationsize,increasing GDP per capita by about 2 per cent in2035. The complex inter-relationship betweendifferent demographic developments and economicoutcomesisfurtherexploredinSectionC.1.

Besides demography and human capital, physicalcapital accumulation continues to be an importantfactor for future growth. While demography anddomesticsavingsplayanimportantrole,theextenttowhich the most productive investment opportunitiescanbefinancedstronglydependsalsooninternationalcapital mobility. A scenario of increased capitalmobility that would set free flows from developedcountries currently invested at home (given theobserveddomesticbiasofinvestmentbehaviourratherthan exclusive focus on return on capital) wouldbenefit strongly the vast majority of developingcountries, adding up to one-third of a per cent toannual growth. This would add 8 per cent to GDP inthe Russian Federation in 2035, over 6 per cent inIndia and China and more than 4 per cent in Brazil,Sub-SaharanAfricaandthedevelopingworldoverall.

Conversely, under a low capital mobility scenario, onlysurplus developing countries (principally the RussianFederation, India and China) could avert a negativeimpact on growth rates, with Brazil losing almost4 per cent in GDP by 2035 and Sub-Saharan Africabeing1percentworseoff.Thepresentmodeldoesnotallow for a more profound analysis of the relationshipbetween savings, investment opportunities, sources offinancing, capital accumulation and their respective

TableB.15:Projected annual average GDP growth rates and GDP levels by 2035, by country and region (annualpercentagechange,2005US$billionandpercentage)

GDP growth GDP in 2035 Share of world GDP

Ref Low High Ref Low High Ref Low High

UnitedStates 1.74 -0.12 0.44 20562 -2.75 10.49 20.3 2.99 -3.40

Japan 1.53 -0.12 0.20 6749 -2.63 4.53 6.7 0.99 -1.42

EuropeanUnion 1.43 -0.02 0.80 20458 -0.37 19.81 20.2 3.55 -1.97

Brazil 2.97 -1.01 1.31 2299 -20.31 33.78 2.3 -0.14 0.02

RussianFederation 4.13 -1.51 2.34 2481 -28.55 66.66 2.5 -0.38 0.63

India 5.96 -2.33 2.48 5450 -40.10 70.23 5.4 -1.58 1.52

China 6.07 -2.70 2.76 17217 -44.79 80.48 17.0 -5.93 6.12

LatinAmerica 3.34 -0.79 0.76 4674 -16.22 18.38 4.6 -0.05 -0.50

MENA 3.47 -0.57 0.79 5440 -11.86 19.05 5.4 0.21 -0.55

SSA 5.09 -1.43 1.68 2727 -27.04 43.99 2.7 -0.37 0.23

RestofAsia 3.98 -0.91 1.37 7154 -18.24 35.05 7.1 -0.25 0.12

RestoftheWorld 2.69 -0.07 0.63 6039 -1.61 14.99 6.0 0.96 -0.80

TotalWorld 2.84 -0.74 1.27 101251 -15.24 32.73 100.0 - -

TotalDeveloped 1.64 -0.04 0.52 52842 -0.95 12.57 52.2 8.80 -7.93

TotalDeveloping 4.72 -1.67 2.01 48409 -30.84 54.73 47.8 -8.80 7.93



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determinants, includinginstitutionalparameters.ThisisundertakenmoreextensivelyinSectionC.2.

Finally, natural resources are an important input intoproduction, and their availability and pricing mayinfluencegrowthopportunitiesdifferentlyfordifferentcountries.Inthesimulations,thefocusisonenergyasapervasive inputtoalmostalleconomicactivitiesbutother natural resources, such as land, are alsoaccounted for and can be simulated, for instance viachangesinagriculturalproductivity.

If the high/low energy price scenarios, as developedbytheUSEnergyInformationAdministration(EIA)for2035,arelookedatinisolation,theirGDPimpactcanbe quite substantial, particularly in developingcountries,affectingaverageannualGDPgrowthbyuptoafifthofapercent,forinstanceinChinaandIndia.High-energy prices can thus cost up to almost4 per cent of GDP in 2035 in these countries. Theopposite is true for main exporters, such as theRussianFederation,partsofLatinAmerica(BolivarianRepublic of Venezuela, Colombia and Mexico) and inparticular the Middle East and North Africa, wherelowerpricescouldreduceannualgrowthbyoverone-thirdofapercent, leading toamore than7percentlowerGDPin2035.

However, historically improvements in energyproductivity in both production and consumption havepracticallynullifiedtheseeffects.Iffurtherreductionsinenergy intensity (via improved productivity andsubstitution)areconsidered,developedcountriesremainbasicallyunaffectedevenbyahighpricescenario,whileaffecteddevelopingcountriescanpreventamajordragon economic growth, with India and China offsettingabout 40 per cent of the price impact on economicgrowth.Whetherornottechnologicalprogressinregardtoenergy (andothernatural resources)productionandconsumption is likely tocontinue in the future,avertingdurable negative economic consequences of higherprices, as has happened in the past, along with theprincipal factors determining such advances will befurtherdiscussedinSectionC.4.

(ii) Combined macroeconomic and trade scenarios

Wenow turn toprospective tradedevelopmentsusingthe two macroeconomic projections as a basis forconstructingahigh/lowgrowtheconomicenvironmentinwhichoptimisticandpessimistictradecostscenarioswill be simulated. This will allow us to see under whatconditionssomeofthemaintrendsintradeidentifiedinSectionB.2arelikelytocontinueorchange.63

AsnotedintheoverviewinBoxB.6,weconsidertradepolicies, suchas tariffs andservicesbarriers, aswellas broader transaction costs affecting goods (e.g.related to institutions, shipping charges andformalities). Again, rather stark trade cost scenarioshave been chosen in order to create a reasonably

broad range of trade outcomes so as to illustrateopportunities and threats for policy-makers. At thesametime,thesetradecostscenariosarenecessarilysimplisticanddonotallowforanysubstantiveanalysisof the types of trade costs related to transportation,theinstitutionalframeworkandspecificpolicies.

The issueof transportationcostsand itsdeterminantsis therefore taken up in detail in Section C.5, whileSection C.6 deals with the relationship between tradeandtradepolicyandthewiderinstitutionalframework.64Itwouldbefutile,ofcourse,toseektopredictspecifictrade policies in the absence of any analysis of thepossible reasons that may motivate policy-makers toenact such measures. As policies affecting trade maybe taken in response to political economy and othersocietal concerns, Section D will address a range ofprominent issues in the wider socio-economic contextthat are high on the political agenda and, therefore,likely to determine whether there will be more or lesstradeopeninginthefuture.65

FigureB.26summarizesourcombinedmacroeconomicand trade simulations in terms of projected averageannualgrowthratesofGDPandexportsupto2035.ItshowsthatexportsarelikelytobemuchmorevolatilethanGDP,growingmore thanGDP in the “optimistic”scenario and shrinking further than GDP in the“pessimistic” scenario, as witnessed already in therecentfinancialcrisis.Thevariationismuchgreaterfordevelopingthanfordevelopedcountries,whichhavealot more to gain from a strong economic and opentradeenvironment in the futureandmore to lose inapessimisticprotectionistscenario.

In fact, while developing countries largely outpacedevelopedcountriesintermsofbothGDPandexportsin the optimistic scenario, their export growth fallsbehind developed countries’ growth rate in a gloomyeconomic and trade environment. Also, developed

FigureB.26:Predicted annual growth rates of exports and GDP, average 2012-2035, by country group (percent)

0 2 4 6 8 10

Exp

orts

(vol

., ex

cl. i

ntra

-tra

de)

GD

P (v

ol.)

High

Low

High

Low

Developing Developed



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countries’ growth rates of both GDP and exports areaffected to a comparatively minor level by potentialchanges in tradecosts,while theseplayamuchmoreimportanteconomicrolefordevelopingcountries,whichcangain/losealmosthalfapercentagepointofaverageannualgrowthinanopen/restrictivetradeenvironment.

Will the rise of new players in global trade continue?

FiguresB.27andB.28showtowhatextentregional/countrysharesinglobalGDPandexportsmaychangecomparedwiththecurrentsituation.Thepiechartsareproportional to the respective total value (taking the“high” scenario for 2035 as a point of reference).Clearly, the trend of new players emerging in globaltrade, identified inSectionB.2(a), is likelytocontinueiftheworldcansustainhighgrowthandamoreopentradeenvironment.

Under the “high” scenario, China could increase itsexport share to almost one-quarter of global trade,while India could more than double its share, to5 per cent. Although the shares of major developedcountries would decline, the absolute values of boththeir exports and GDP would continue to increase.

Conversely,despitetheirsubstantiallylargersharesina low-growth, high trade cost scenario in 2035,developed countries would be worse off in absoluteterms in regards to both their GDP and exportscompared with the “high” scenario, given the overallmuchlarger“sizeofthepie”inthelatter.Chinawouldbe particularly affected in a world of deceleratinggrowthandconfrontationaltradepolicy,losingnotonlyin terms of export market share but also absoluteexportvaluecomparedwiththepresentday.

Will services trade become more and more important, and will developing countries continue to expand their share of trade in manufactures and services?

FigureB.29confirmstheprobablecontinuationofanothertrend identified above, namely the changing sectoralcomposition of trade (see Section B.2(b)). In fact, thetrendtowardsanincreasedimportanceofservicestradeisapparent inboththe“high”and“low”scenarios.Whilethelattermaybestronglyinfluencedbypossiblenegativetradepolicydevelopmentsintheareaofgoods,theformerscenario assumes symmetric improvements in reducingbarriersforbothgoodsandservicestrade(plusafurther

FigureB.27:Country/regional shares in global GDP, constant 2004 prices (percentage)

RoW, 14%

Korea,Rep. of,12%

AUNZ, 11%

SouthAfr, 4%

RoAfr, 6%Canada,

14%

RoEurope, 3%

RoLAC,17%

Mexico, 10%

EFTA, 9%

India, 12%China, 7% Brazil, 2%

RussianFederation,2%

ASEAN, 2%

MENA, 4%Japan,10%

EU (27), 28%

United States,27%

2012Total: US$ 49,992 billion

Low 2035Total: US$ 77,758 billion

RoW, 13%

Korea,Rep. of, 13%

AUNZ,12%

SouthAfr, 3%

RoAfr, 9%Canada,

14%

RoEurope,2%

RoLAC, 16%

Mexico, 10%

EFTA, 8%

MENA, 5%

India, 3%

China, 9%

Brazil, 2%


Japan, 9%

ASEAN, 3%

EU (27), 25%

United States, 24%

India, 6%

RoW, 19%

Korea, Rep. of, 11%

AUNZ, 8%

SouthAfr, 3%

RoAfr, 15%

Canada, 9%

RoEurope,7%

RoLAC,15%

Mexico, 9%

EFTA, 4%

China, 20%ASEAN, 4%

MENA, 7%

Japan, 6%

Brazil, 2%Russian Federation, 3%

EU (27), 18%

United States, 17%

High 2035Total: US$ 129,617 billion

RoW RoW

Rest of World

Rest of World

Rest of World

RoW


Note:RoW:RestoftheWorld;RoLAC:RestofLatinAmericaandtheCaribbean;RoAfr:RestofAfrica;ASEAN:AssociationofSoutheastAsianNations;AUNZ:AustraliaNewZealand;EFTA:EuropeanFreeTradeAssociation;MENA:MiddleEastandNorthAfrica.


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FigureB.28:Country/regional shares in global exports (excluding intra-trade), constant 2004 prices (percentage)

RoW, 22%

Korea,Rep. of,15% AUNZ, 6%

SouthAfr,3%

RoAfr, 6%Canada,

15%

RoEurope, 4%RoLAC, 10%

Mexico, 9%

EFTA, 10%

India, 2%

China, 15%

Brazil, 1%


ASEAN, 7%

MENA, 6%

EU (27), 19%

United States, 16%

Japan, 7%



RoW, 21%

Korea,Rep. of, 17%

AUNZ,7%

SouthAfr,3%

RoAfr,6%Canada,

18%

RoEurope, 4%

RoLAC, 8%

Mexico, 8%

EFTA, 8%

MENA, 6%

India, 3%China, 11%


Japan, 7%

ASEAN, 6%

EU (27), 19%

United States,18%

RoW, 28%

Korea, Rep. of, 15%

AUNZ, 4%SouthAfr, 3%

RoAfr, 14%

Canada, 8%

RoEurope, 9%

RoLAC, 8%

Mexico, 7%

EFTA, 4%

China, 24%

ASEAN, 8%

MENA, 9%

Japan, 4%


India, 5%

EU (27), 12% United States, 10%

Brazil, 1%


RoW RoW

Rest of World

Rest of World

Rest of World

RoW


Note:RoW:RestoftheWorld;RoLAC:RestofLatinAmericaandtheCaribbean;RoAfr:RestofAfrica;ASEAN:AssociationofSoutheastAsianNations;AUNZ:AustraliaNewZealand;EFTA:EuropeanFreeTradeAssociation;MENA:MiddleEastandNorthAfrica.

lowering of transaction costs affecting goods). Despitethis, the changing economic environment will lead torelatively more services trade, increasing its absolutevaluebymorethanfivetimesin2035.

Despiteaslightlylowershareunderthe“high”scenario,manufacturing will continue to dominate internationaltrade, accounting for over two-thirds of global exportsand increasing by a factor of almost 4.5 in volume by2035. Trade in agriculture continues to account for aminorshareofglobaltradeunderanyscenario.

Figures B.30 and B.31 show the predicted regional/country shares in the export of manufactures andservices respectively under the different scenarios.Overall,developingcountriescanimprovetheirmarketsharesforservicesexports, inparticularChina,underthe high scenario. The same is true for exports ofmanufactured goods but only if the economic andtrade policy outlook is bright, in which case Chinawouldapproachthe30percentmark.

Iftheeconomicclimateworsensandcountriesdonotmaintain their trade commitments, exports ofmanufacturedgoodswouldbarelygrowinthenexttwo

decades, with China and other developing countrieslosingmarketshare.DespitetheEuropeanUnionandtheUnitedStatesachievingahighermarketshareofexports of manufactured goods in such a gloomyenvironment, theywould lose inabsolute terms,giventhe dramatic shrinkage of the “overall export pie” tojust over one-quarter compared with a scenario offurtherdynamicgrowthandintegration.

Will developing countries continue to trade more with each other?

Asfarasthedirectionoftradeisconcerned,FigureB.32shows an almost unchanged share in “North-South”trade, i.e. trade between developed and developingcountries,overthenextfewdecadesunderallscenarios.Infact, thestructureoftradeamongandwithincountrygroups would barely change under the “low” scenario,withNorth-Northremainingthevastlydominantdirectionof trade at over 40 per cent and South-South traderetreatingslightlytojust18percent.

By contrast, under the “optimistic” scenario, thesepositions are inversed. Trade among developingcountries would represent the largest part in global


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trade at 43 per cent while trade among developedcountrieswouldconstitute just17percent.However,this is still 25 per cent larger than under the “low”scenarioinvalueterms.Theseresultswouldbeinlinewith the trend of greater trade between developingcountriesidentifiedinSectionB.2(a).Theywouldalsobroadly confirm the increased relevance of intra-industry trade and the similarity of countries’ exportbasketsnotedinSectionsB.2(b)andB.2(c).

Will trade become more regionalized or globalized?

Section B.2(d) identified a trend towards furtherregionalization, particularly in Asia. The modelsimulations up to 2035 do not, however, necessarilyreflect this. In fact, under an “optimistic” outlook quitethe contrary seems to be the case. Trade within themajorregionalblocsispredictedtodeclinesubstantiallycompared with multilateral trade relationships

FigureB.29:Sectoral shares in global exports (excluding intra-trade), constant 2004 prices (percentage)

Services, 17%

Manufactures, 71%

Agriculture, 2%

Energy, 10%Services, 24%

Manufactures, 65%

Agriculture, 3%Energy, 8%




Services, 19%

Manufactures, 68%

Agriculture, 3%

Energy, 10%


FigureB.30:Country/regional shares in global exports of manufactures (excluding intra-trade), constant 2004 prices (percentage)

RoW, 24%

United States, 16%

Japan, 8%

Brazil, 1%


EU (27), 19%

India, 2%

China, 19%

ASEAN, 7%

MENA, 3%




RoW, 25%

United States, 19%

Japan, 9%

Brazil, 1%


EU (27), 20%

India, 2%

China, 15%

ASEAN, 6%

MENA, 2%

RoW, 22%

United States, 8%

Japan, 5%

Brazil, 1%

India, 7%


EU (27), 11%

China, 29%

ASEAN, 8%

MENA, 6%


Note:MENA:MiddleEastandNorthAfrica;RoW:RestoftheWorld.


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FigureB.31:Country/regional shares in global exports of services (excluding intra-trade), constant 2004 prices (percentage)

RoW, 26%

United States, 20%


EU (27), 27%

Japan, 4%India, 3%

China, 6%

ASEAN, 5%

MENA, 7%




RoW, 30%

United States, 15%

Japan, 4%

Brazil, 0.5%


EU (27), 23%

India, 4%

China, 7%

MENA, 10%

ASEAN, 6%

RoW, 25%

United States, 14%

Japan, 3%

Brazil, 0.5%


EU (27), 21%

China, 18%India, 3%

ASEAN, 5%

MENA, 8%


Note:MENA:MiddleEastandNorthAfrica;RoW:RestoftheWorld.

FigureB.32:Bilateral trade shares (including intra-trade), constant 2004 prices, by country group (percentage)

Dvd-Dvg, 19%

Dvd-Dvd, 40%

Dvg-Dvg, 19%

Dvg-Dvd, 22%

Dvd-Dvg, 21%

Dvd-Dvd, 41%

Dvg-Dvg, 18%

Dvg-Dvd, 20%

Dvd-Dvd, 17%

Dvg-Dvg, 43%

Dvd-Dvg, 18%

Dvg-Dvd, 22%





Note:Dvd:developed;Dvg:developing.

(see Figure B.33). Trade within the European Unionwouldexperiencethelargestdecline,from21percentofglobaltradevolumestojust8percent,andtheNorthAmericanFreeTradeAgreement(NAFTA)wouldseeitsshare more than halved. Conversely, trade with otherregions would increase from 70 per cent to over85percentofworldtrade,indicatingtheimportanceoffurthermultilateralintegration.

In anutshell, thediscussion in this sectionhas shownthatnotallofthetrendsintradepresentlyobservedwillnecessarilycontinue.Thescenarioschosenherechartpossible boundaries for a vast range of future tradedevelopments.Moreisatstakeforsomecountriesthanforothers.Forinstance,ChinaandIndia’sshareofworldexportswouldincreasesignificantlyinafuturescenarioof high sustained growth dynamics and a more open


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trade environment. In a world of decelerating growthdynamics and confrontational trade policy, however,India’s share would increase only very modestly andChina’s share would decline. Similarly, for worldmanufactures exports, China and other developingeconomies would lose market share if the economicclimateworsensandcountries fall backon their tradecommitments. Furthermore, the share of South-Southtrade would decline slightly in the “pessimistic” futurescenario, but would more than double – constitutingalmosthalfofworld trade– in the“optimistic”outlook.Outcomes will not only depend on trade policy andwidertradetransactioncostsbutwillbeinfluencedbyarangeofotherfactorsshapingthefutureofworldtrade.Itwillbecriticaltounderstandwhatdrivesthesefactorsas this may give rise to policy action at both thedomestic and international level in a number of areas,includingattheWTO.

4. Conclusions

Theindustrialrevolutionwasthemaindrivingforceforthedevelopmentof themodernworld tradingsystem:significant technological advances in transportationand communication together with population andinvestmentgrowthwereresponsibleforthesustainedincrease of international trade during the 19th and20thcenturies.Tradeliberalizationhadalimitedroleinthe expansion of international trade during the firstwaveofglobalization.AftertheGreatDepressionandtheSecondWorldWar,however,politicalandeconomiccooperationacrosscountriesaimedat reducingtradebarriersplayedakeyroleinmaintainingthecontinuousgrowth of trade during the second wave ofglobalization.

Thissectionhaspresentedaseriesoffactsrelatedtothecurrentstateofinternationaltradeandhighlightedthemaintheoriesthathavebeendevelopedtoexplain

such patterns. First, WTO data show a dramaticincrease in both the volumes and values of tradebetween 1980 and 2011, with most of this growthattributable to increased shipments of manufacturedgoods. However, when trade is measured in value-added terms, services play a larger role. In the lastthreedecadesworldtradegrewmuchfasterthanGDP.Thiscanbeexplainedtosomeextentbytheincreasingprominenceofinternationalsupplychainsintheglobaleconomy.Attheproductlevel,tradegrowthduringthisperiod was mostly due to changes in the intensivemargin of trade (i.e. more or less trade in existingcategoriesofgoods)althoughtheextensivemarginoftrade (i.e. trade in new products) also made animportantcontribution.

Secondly, in recent years new protagonists haveemergedintheglobalmarket.Thesharesoftrade,bothin terms of manufactured goods and services, ofdevelopingcountriessuchasChina,India,theRepublicofKoreaandThailandhavesignificantlyrisenovertime.China,inparticular,hasbecomethelargestexporterintheworld.Incontrast,developedcountriessuchastheUnited States and Japan recorded declines in theirshares in world exports between 1980 and 2011.Natural resource-exporting countries and regions sawtheir shares in world trade rise and fall in in line withprimarycommodityprices,whicharecurrentlyhighbutwere weak in the late 1990s and early 2000s. As aresult,despiterecentgains,theshareofAfricainworldexportswasroughlythesamein2011asitwasin1990.Brazil falls into twocategories,beingamajorexporterof both primary products and manufactured goods.Although the country has raised its shares in worldexports and imports since 1980, its ranking for bothexportsandimportsisrelativelyunchanged.

Thirdly,bothdevelopinganddevelopedcountrieshavebecome less specialized in exporting particular

FigureB.33:Intra- and extra-regional shares in global trade (including intra-trade), constant 2004 prices, by agreement (percentage)

Other, 70%

ASEAN, 1%

MERCOSUR, 1%

NAFTA, 7%

EU, 21%

Other, 86%

ASEAN, 2%

MERCOSUR, 1%

NAFTA, 3%

EU, 8%

Other, 68%

ASEAN, 2%

MERCOSUR, 1%

NAFTA, 8%

EU, 21%






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products. In other words, their exports have becomemore diversified. Countries that have experienced ahigher concentration of exports are in many casesnaturalresource-richeconomies.

Fourthly,tradehasbecomemoreregionalizedinmostparts of the developing world but this trend is mostpronounced inAsia. Incontrast, industrializedregionshave seen their intra-regional trade shares eitherstagnate(Europe)ordecline(NorthAmerica)inrecentyears.Bothof thesedevelopmentsmaybe related totheriseofChinainworldtrade,sinceitsevergrowingshareofworldtradewouldtendtoboostintra-regionaltrade in Asia and trade with other regions. Trade ismainly driven by a few big trading firms acrosscountries, and the dominant performance of globalfirmsemphasizesthe importanceofthese“superstar”exportersinshapingtradepatterns.

Finally, the increasing fragmentation of productionwithin and across countries brings into question thetraditionalmeasuresoftradeflowsandcallsforanewsystemofmeasurementtoidentifywherevalue-addedisaccumulated.Measuringtradeinvalue-addedtermsprovides a more accurate picture of the relationshipbetweentradeandeconomicactivity.

For future trade patterns, simulations of the worldeconomyandtradeoverthecomingdecadesproduceanumberofinsights.Theriseofdevelopingcountries– some more than others – is bound to continue.Increasingly,thesecountrieswilltradewitheachother.Developing countries have a lot more to gain from adynamic economic and open trade environment thandevelopedcountriesandtheyhavemoretolosefromagloomy, confrontational scenario. Services will play amore important role in world trade for practicallyeveryone.Despitetheregionalizationoftradebeingacurrent trend, multilateral trade relationships areunlikelytolosetheirimportanceandhavethepotentialtoincreasesignificantly.

Thepredictionsforfuturetradehighlighthowsensitivethe results are to the underlying assumptions andjustify further analysis of the main determinants oftradeandeconomicgrowth:demographics,investment,technological progress, energy/natural resources,transportandinstitutions.TheremainderoftheReportis therefore devoted to an in-depth analysis of thesefundamentaleconomicfactorswithinabroadersocio-economiccontextandtheimplicationsthatthesemayentailfortradepolicy.


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1 Althoughtheluxuryimportsofthepreviouscenturies–sugar,tea,coffeeandtobacco–hadbecomestaplesinthedietsofthenewurbanworkingandmiddleclasses,theirimportanceinEuropeanimportshadshrunkrelativetoothercommodities,notablywheatandflour,butterandvegetableoils,andmeatbytheendofthe19thcentury,whichaccountedforthebulkofthedevelopingworld’ssurgingexports.

2 Notonlydidrailwaysandsteamshipsmeanthatgrainmarketsbecameincreasinglyglobal,butrefrigerationalsoreducedthenaturalprotectionthatdistanceformerlyprovidedtoEuropeanmeatanddairyproducers,withtheresultthattheytoofacedgrowingcompetitionfromfar-awayproducersinArgentina,AustraliaandNewZealand(O’RourkeandWilliamson,1999).

3 SeeWTO(2010).

4 O’RourkeandWilliamsonarguethatfactorpriceconvergenceinthelate19thcentury,asaresultofincreasingtrade,investmentandmigration,servedtodiminishtherelativerealwageandstandardoflivingadvantagesofeventherichestmembersoftheNewWorld.“Convergencewasubiquitousinthelatenineteenthcentury,butitwasmostlyastoryaboutlabour-abundantEuropewithlowerworkers’livingstandardscatchingupwiththelabour-scarceNewWorldwithhigherworkers’livingstandards”.RelativetoBritain,realwagesintheUnitedStateswere106percenthigherin1855,72percenthigherin1870and44percenthigherin1880(O’RourkeandWilliamson,1999).

5 In1913,thesefiveeconomieshadapercapitallevelofindustrializationmorethanhalfthatoftheUnitedStates,bythentheworld’sleadingindustrialpower,illustratinghowmuchoftheUSeconomywasstilldevotedtoagriculturalandrawmaterialproduction.

6 Theoriginsofthe19th-centurygoldstandardlayinactionbytheBankofEnglandin1821tomakeallitsnotesconvertibletogold(althoughBritainhadoperatedadefactogoldstandardfromasearlyas1717).

7 Bilateraltariffcuttingafter1860wasparticularlysignificantsincetariffsconstitutedthemainbarriertoglobaltrade,partlytoproviderevenueforgovernments,andpartlytoshieldeconomiesfromtheintegrationistpressuresofnewtechnologies,mademorenecessarybytherigidconstraintsofthegoldstandard(whichprecludedcurrencydevaluationasanadjustmentmechanism).Beyondtariffs,however,government’simpactontradewassmallerthanitistoday.Domesticregulationwasminimal,aswerefiscalandsocialpolicies:adjustmenttoglobalizationwasaccomplishedthroughthebluntoperationofthepricemechanism,ofteninvolvingdramaticwagedeclinesandhighunemployment,notthroughactivistfiscalorsocialpolicies.

8 By1908,Francehad20MFNagreements,Britain46,andGermany30(Hornbeck,1910).

9 EveninthenominallyindependentstatesofLatinAmericaandEastAsia,Europeanpressurehadimposedonmostofthemtreatiesinthefirsthalfofthe19thcenturywhichentailedtheeliminationofcustomsandduties,thusopeningupmarketstoBritishandEuropeanmanufacturedexports.

10 Theoriginal20membersoftheITUwereEuropean,buttheITUsoonwelcomednationsfromthenon-industrializedworld,includingIndia(1869),Egypt(1876),Brazil(1877),Thailand(1883),andArgentina(1889).

11 FearfulofSovietglobalexpansionandEurope’srapideconomicdeteriorationinthewinterof1946-47,theUSCongresspassedtheEconomicCooperationAct–knownastheMarshallPlan–inMarch1948,approvingfundingthatwouldeventuallyrisetooverUS$12billionforrebuildingWesternEurope.

12 Forexample,worldFDIflowsdeclined28percentbetween1981and1983;26percentbetween1990and1991;58percentbetween2000and2003;and39percentbetween2007and2009.Incontrast,tradesufferedjustthreemajordeclinesinthepost-warperiod:7percentin1975;2percentin1982;and12percentin2009.Themultinationalcompanyhasemergedasthekeyactorintheglobalizedeconomy.

13 Foranumberofeconomichistorians,thecurrentworldtradingsystem,farfrombeingunprecedented,isessentiallyareturntothedevelopmentaltrajectoryoftheworldeconomyinauguratedbythebirthoftheindustrialage.Someevenarguethattheworldeconomystillhasawaytogoinordertoachievethecomprehensivelevelsofglobal,trade,capitalandlabourmarketintegrationofthepre-1914era(O’RourkeandWilliamson,1999).

14 Fromthistheauthorscalculatethata“roughestimateofthetaxequivalentof‘representative’tradecostsforindustrializedcountriesis170percent.(2.7=1.21*1.44*1.55)”(AndersonandVanWincoop,2004).

15 Theincomeelasticityoftradeisdefinedasthepercentagechangeintradevolume(T)correspondingtoa1percentchangeinrealGDP(Y).ItcanbeestimatedbysimplytakingtheratiooftradegrowthtoGDPgrowthforaparticularperiod,i.e.(T/T)/(Y/Y)whereindicatesadiscretechangeinavariable.Thepointelasticityoftrade,whichiswrittenasdT/dY×(Y/T)incalculusnotation,issimplythelimitofthisexpressionasthechangeinGDPgoestozero.Thelattermustbeestimatedbyordinaryleastsquaresregression,buttheresultsarenearlyidenticaltothesimplerdiscreteapproach.InTableB.2wehaveusedasimplediscreteelasticitymeasure,butitishelpfultounderstandbothapproaches.

16 SeepaperssuchasFeenstraandHanson(1996),Feenstra(1998),CampaandGoldberg(1997),Hummelsetal.(2001),Yeats(2001)andBorgaandZeile(2004).

17 Anumberofpapersestimatingincomeelasticitiesfortradeflowsgenerallyfindthemtoliebetween1and3½.See,forexample,Hooperetal.(2000)andKwacketal.(2007),Freund(2009)andIrwin(2002).

18 EmpiricalstudiessuchasFreund(2009),Levchenkoetal.(2009)andBernsetal.(2011)identifiedinternationalfragmentationofproductionasoneofthemainreasonsexplainingwhytradedroppedmuchmorethanGDPduringtherecession.Foramorecomprehensiveanalysisofthecausesofthegreattradecollapse,seeBaldwin(2009).

19 NoticethattheKrugmanmodelcanactuallybecombinedwithmodelsofcomparativeadvantagetocaptureboth

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inter-industryaswellasintra-industrytrade,seeHelpmanandKrugman(1985).

20 InKrugman(1979)increasingreturnstoscaleareinternaltothefirm.However,increasingreturnstoscalecanalsobeexternaltothefirm:firm’saveragecostsdecreasewithindustryoutput.Alargeandconcentratedindustrydecreasethecostsofproductionthroughchannelssuchaslabourpooling,specializedequipmentortechnologyspilloversandthereforemaygivefirmstheincentivetoclustergeographically.

21 Thenotionofcomparativeadvantageisveryusefultoexplainthecurrentpatternsoftradetakingplacemainlybetweendevelopedanddevelopingcountries(seeFigureB.8).

22 ForanumericalpresentationoftheRicardianmodel,pleaserefertoBox1oftheWorld Trade Report 2008.

23 BoththeRicardianandHOtheorieshavebeengeneralizedtoincludemultipleproductionfactors,goodsandcountriesandhavesuccessfullyconfirmedthattradeconformstocomparativeadvantageinanaveragesenseacrossindustriesandcountries(seeDeardorff,2011;LevchenkoandZhang,2011;EatonandKortum,2002;Ethier,1984;andBrecher,1974).

24 ThedefinitionoftheHerfindahl-HirschmannindexhasbeentakenfromUNCTADstatisticsonexportsconcentration.Theindexhasbeencomputedusingtradedatadisaggregatedatthree-digitgrouplevel.

25 Primaryproductsincludeagriculturalproductsandfuelsandminingproducts.

26 Totalfactorproductivityrepresentstheshareofoutputthatisnotexplainedbyproductioninputs.

27 TheseresultsareinlinewiththefindingsofImbsandWacziarg(2003),whichdocumentaU-shapedrelationshipbetweenthelevelofdevelopmentandasetofmeasuresofindustrysize,suchassharesofsectorialemploymentandvalueadded,forasetofcountriesbetweenearly1960sandmid1990s.

28 AlldatafromtheInternational Trade StatisticspublicationcanbedownloadedfromtheWTOstatisticsgatewayatwww.wto.org/statistics.

29 Networkdatafor1990-99havebeenharmonizedwithcurrentclassificationtothegreatestextentpossibleinalltablesandchartsinwhichtheyareused.

30 FormoredetailsontheToyotamodel,seeOhno(1988).

31 Theestimationsofthevalue-addedexportspresentedinthissectionandrequiringhistoricalcomparisonmakeuseoftheWorldInput-OutputDatabase(WIOD).Thedatasetconsistsof40economies(plusrestoftheworld),35ISICrev3sectors,15years(1995-2007).AllthefiguresarebasedonthesectoralclassificationpresentedinAppendixTableB.1.OtherindicatorsrefertotheOECD-WTOdatabaseontradeinvalue-added,availableonlyformostrecentyearsatthedateofpreparingthisdocument.Seehttp://www.wto.org/miwi.

32 International Sourcing Statistics – Statistics Explained,availableathttp://epp.eurostat.ec.europa.eu/statistics_explained/index.php/International_sourcing_statistics,lastaccessedon17December2012,and(Sturgeon,2012),GlobalValueChainsandEconomicGlobalization.

33 ForWIOD,seehttp://www.wiod.org/.

34 Seehttp://www.wto.org/english/res_e/statis_e/miwi_e/miwi_e.htm.

35 Thehomogeneityoffirmsisanimportantunderlyingassumptionofalltheseapproaches.Itimpliesthattheproductionstructureisthesameacrossallfirmsinagivencountry.Thishasobviouslimitations,especiallywhenfirmsactivelyengagedintradediffersignificantlyfromthoseproducingonlyforthedomesticmarket.On-goingresearchislookingintowaysofsplittingthenationalinput-outputmatricesintosub-categories,inordertolimitthebias.Forexample,theChineseNationalAcademyofSciencehasproducedameasureofvalue-addedtradebasedonthreesub-categories:domesticfirms,export-orientedfirmsusingdomesticinputsandexport-processingfirms.Indeed,muchoftheresultspresentedinthissectionshouldbetreatedasfirstestimates,whichunder-estimatetheverticalspecializationofexport-orientedfirms(oftenbyalargemargin,suchasinChinaorMexico).

36 USITC,Small and Medium-Sized Enterprises: US and EU Export Activities, and Barriers and Opportunities Experienced by US Firms ,USITCpublication4169,July2010.

37 Exportsprocessingzones(EPZs)areindustrialzoneswithspecialincentivestoencourageexport-orientedactivities.AsproductsexportedfromEPZs(referredtoasprocessingtrade)employfarmoreforeigninputsthanordinary(ornon-processing)exports,nottakingintoaccountthespecificityofprocessingtradewouldoverestimatethedomesticvalueadded.SeeKoopmanetal.(2011).Consideringprocessingtrade,JohnsonandNoguera(2011)estimate59percentofdomesticcontentforChinaand52percentforMexico.

38 SeealsoWTOandIDE-Jetro(2011).

39 ItisimportanttonotethatsincethedataofEFIGEcomefromasurveytheyconductedonaselectedsampleoffirms,whicharefarfromcomprehensive,theirresultsarenotcomparablewiththoseofBernardetal.,andespeciallytheextensivemarginsinEFIGEareveryhighacrosscountries.Infact,thekeyinformationoftheEFIGEfigureisthatthereareobviousvariationsonbothintensiveandextensivemarginsofexportsacrosstheseEUmemberstates.

40 SeeBernardandJensen(1999)fortheUnitedStates,Clerides,LachandTybout(2012)forColombia,MexicoandMoroccoandAlvarezandLopez(2005)forChile.

41 SeeBernardandJensen(1999),Bernardetal.(2007)andBustos(2011).

42 SeeTyboutandWestbrook(1995),Pavcnik(2002),Trefler(2004),Bernardet.al(2006)andBustos(2011).

43 SeeJovanovic(1982)andHopenhayn(1990).

44 SeeMinondo(2011)forSpanishservicesfirms,Vogel(2011)fortheGermanbusinesssectorandMasurel(2001)forDutcharchitecturalfirms.

45 SeeUnitedStatesInternationalTradeCommission(2010).

46 PaperssuchasHummelsandKlenow(2005),forinstance,findthat60percentofthedifferenceinaggregatetradeflowsbetweenrichandpoorcountriescomesfromdifferencesinthenumberofgoodstraded.

47 Foramoreextensivedescriptionofscenariosanddiscussionofresults,seeFontagnéatal.(2013).


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48 Technologicalprogressismeasuredherebytotalfactorproductivity(TFP)andenergyefficiency.Italsocapturesthegainsfromhumancapitalaccumulation(theoutputofeducation).InMaGE,themacroeconomicmodelusedforthegrowthprojections,TFPisdeterminedendogenouslythroughaprocessofcatching-up.Inthe“high”and“low”scenarios(seeBoxB.6),anexogenousgainorlossofTFPisaddedtothisprocess.ATFPgaincanresultfromadditionaltechnologytransferthroughFDI,exportsorcollaborativeresearch.IntheCGEmodel(Mirage)usedforthetradesimulations,whichallowsforsectoraldetail,agriculturalTFPisexogenousandsettovaluespredictedbyaseparateddetailedanalysisofthesector.TFPinmanufacturedgoodsandservicesareendogenous,withtheformerbeingslightlyhigherthanthelatter,asmodelledelsewhereintheliterature(e.g.VanderMensbrugghe,2005).Also,productionfactorsarefurtherrefinedbydifferentiatingskilledfromunskilledlabourandaddinglandandothernaturalresourcesbesidesenergy.Formoretechnicaldetails,seeFontagnéandFouré(2013).

49 AlesscommonmethodologymixesthetwostagesinsuchanexercisebydirectlyimposingassumptionsontechnologicalprogressatthesectorallevelintheCGEmodel.SeethediscussionofWorldBank(2007).

50 Eichengreenetal.(2012)findthatfast-growingdevelopingeconomiestendtoseegrowthratesslowwhenpercapitaincomesreacharoundUS$16,000atpurchasingpowerparity.

51 Fortheemergenceofnewplayersininternationaltradetodate,seeSectionB.2(a).

52 SeeWorldBank(2007),AsianDevelopmentBank(2011),OECD(2012c)andDuvalanddelaMaisonneuve(2010)fortheOECD,aswellasFontagnéetal.(2012)andFouréetal.(2010)fromCEPII.

53 Theseassumptionsarenotadhoc.Theyarebasedonadescriptionofthebehaviourofeconomicagents(e.g.intermsofeducation,labourforceparticipationorsavings),whichisusedasaframeworktoeconometricallyestimateandprojecttrajectoriesforaggregatevariablesinthemediumtolongrun.Aseconomicgrowthdependsonthespecificpathoffactoraccumulationandtechnologicalprogress,differentstudiesusuallytakeintoaccountthesamesetofgrowthdeterminantsandmerelydiffersomewhatinthelevelofdetailwithwhichcertainfactorsaremodelled.SeeFouréetal.(2012)foranoverviewandFouréetal.(2010)foramoredetailedpresentation.

54 Fouréetal.(2010)obtainverysimilarresultsfortheyear2050.Theynotethatby2050,China’sGDPwouldincrease13-foldandIndia’seconomybyafactorof10,whileGDPinmostindustrializedcountrieswoulddoubleortripleatbest.TheUnitedStateswouldcontinuetoleadintermsofGDPpercapita,butJapanwouldloseitssecondspottoChina,withIndiaadvancingtheranksrapidly,closinginonBrazil.

55 Variousinstitutions,suchastheEconomistIntelligenceUnit(EIU),EuropeanCommissionandUSNationalIntelligenceCouncil,haverecentlyreleasedstudiesonwidersocietalchallengesthatmayariseby2030or2050,respectively.Manyofthediscussions,e.g.ondemographyandeducation,technology,etc.,arealsocoveredindetailinthisreportwithaspecificfocusontheirrelationshipwithtrade.Incontrast,thesestudiestouchupontradeonlycursorily.Inparticular,inasmuchasquantitativepredictionsareconcerned,thestudiesappeartoprincipallyrelyonoutsidematerialfrom

theinstitutionscoveredintheoverviewhere,notablyCEPIIandtheWorldBank,andotherwisedonotprovidemuchdetailonmethodology.SeeEconomistIntelligenceUnit(2012),EuropeanCommission(2011)andNationalIntelligenceCouncil(2012).

56 AswillbefurtherdiscussedinSectionC.3,tradeopennessandtechnologicalprogressarehighlyinterdependent.ThisisnottakenintoaccountbyPetriandZhai(2012).OthershortcomingsinmeasuringthewelfarebenefitsoftradeopeninginaCGE-typesettingalwaysneedtobeborneinmindaswell,suchasthehighlevelofaggregation(and,hence,underestimationofintra-industrytradegrowth),demanddevelopmentsrelatedtotheloveofvarietybyconsumers,varyingscaleeconomiesinproductionetc.

57 Otherconcerns,suchasmacroeconomicimbalances,mayalsoleadtopolicyresponsesseekingtoconstrainbilateraltradesurpluses/deficitsandarenotfurtherconsideredinthepaper.Withtheproliferationofglobalsupplychains,suchpolicyactioncouldhaveknock-oneffectsonexportersofintermediateinputsbeyondthecountriesconcerned.

58 AmoreextensivedocumentationofthemethodologyusedandofresultswillbepublishedinFontagnéandFouré(2013)andFontagnéetal.(2013).

59 Foreaseofreference,thesearegroupedbyendowmentfactors,technologyandtradecosts,althoughmanifoldinterlinkagesexist,includingviathedemandsidechannel.Forinstance,differentdemographicscenariosleadtodifferentamountsofoverallsavings,thedistributionofwhichintoproductiveactivitiesaroundtheglobeagaindependsoncapitalmobility.

60 Again,theseextremescenarioshavetobetreatedwithcautionandcertainlynotallofthemareequallylikely.Somehavesimplybeenchosenforsymmetryreasons,e.g.thelowerboundscenarioontechnologycomparedtothehigherboundscenario,inordernottodistortthefinaloutcomesbychoosingvastlyunevenoppositescenarios.

61 Basedonhistoricalexperience,wehaveoptedhereforamorerealistic“asymmetric”shockinTFPfordevelopedversusdevelopingcountries.ResultsdonotchangemuchifTFPfordevelopedcountriesisshockedinexactlythesamewayasfordevelopingcountries.Thiswouldresult,forinstance,inplus/minus5percentdeviationsinglobalGDPsharesby2035ratherthan6percent.

62 AswillbefurtherdiscussedinSectionC.1,demographynotonlyplaysafundamentaleconomicroleinregardtolabourforcedevelopments,butalsoviatheconsumption/savingschannelrelatedtochangesintheagestructureofsociety.Interestingly,lowerfertilityinthedevelopingworldleadstoarelativelylargermiddleagegroupandhigherglobalsavings.Ifcapitalmobilityishigh,thisalsohasbeneficialgrowtheffectsinthedevelopedworld.

63 GiventhecomplexityofglobalCGEmodelsandtheirmassivedatarequirements,certaintrendsdiscussedinSectionB.2cannotbeaccountedforinthesimulationsinviewofthelackofconsistentdataonthesephenomenaatthatlevel,inparticularglobalsupplychainsandtheroleoffirmsininternationaltrade.Also,someofthefuturedrivingforcesdiscussedinSectionsCandD,suchasfurtherdigitization,robotics,shalegasdiscoveriesandthelikehavenotbeen(andmostlycannotbe)addressedatanylevelofdetailinthesesimulationmodels.However,someotherissuesnotfurtherexaminedhere,suchasclimatechange,aretakenintoaccountinmorespecializedstudies,suchasFontagnéetal.(2012).


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64 Countries’institutionsalsoaffect(andareaffectedby)economicgrowthandtrade(bothviaimpactsoncomparativeadvantageandtransactioncosts).Itisdifficulttoincludethesefactorsintheglobalmodelsdiscussedhereinastraightforwardmanner.However,anindirectrepresentationstilloccurs,notablyviachangesinproductivityandscenariosonbroadertransactioncosts.Tradecostsrelatedtotransportationaretakenintoaccountinvariousotherwaysaswell,includingthroughenergypricedevelopmentsandspecificproductivitydevelopmentsinthetransportationsector.

65 SectionDalsodiscussesthedeterminantsofpublicperceptionsoftradeandpolicychoices,whichmayincludeanyofthefactorscoveredinSectionC.ThechangesinunderlyingconditionsfortradedescribedinSectionCcouldalsothemselveshaveanimpactontradepolicy.Forexample,immigrationhasimplicationsfortradeviachangesincomparativeadvantageandthelevelandcompositionofdemandasdiscussedinSectionC.1,butimmigrantsmayalsoshapeinterestsintradepolicy-makinginaparticularmanner.See,forinstance,Peters(2012).AsmentionedinSectionA,thelinksbetweenissuesimpactingtradearemanifoldandoftenbi-directionalthusexceedingwhatcanreasonablybediscussedinanyonestudy.


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AppendixTableB.1:Sectoral classification of value-added trade statistics

Sector ISICRev.3definition

Total ISICAtoP

Agriculture ISICA,B,15and16

Fuels and mining ISICC,23,E

Manufacturing ISIC17to37excl.23

of which:

Ironandsteel ISIC27,28

Textilesandclothing ISIC17,18

Chemicals ISIC24,25

Machineryandtransportequipment ISIC29to35

Services ISICFtoPexcl.L


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AppendixTableB.2:Network of world merchandise trade by product and region, 1990-2011 (US$billion)Destination Worlda North America South and Central America Europe CIS Africa Middle East Asia Destination

1990 2000 2011 1990 2000 2011 1990 2000 2011 1990 2000 2011 1990 2000 2011 1990 2000 2011 1990 2000 2011 1990 2000 2011

Origin Origin

World World

Agriculturalproducts 414.72 551.18 1,659.52 51.35 89.50 196.41 11.01 20.39 67.64 214.99 256.69 689.44 16.74 12.56 66.66 15.58 19.42 89.91 15.26 19.76 86.61 89.79 128.80 451.53 Agriculturalproducts

Fuelsandminingproducts 488.32 852.63 4,007.83 92.82 188.41 611.91 16.03 31.33 155.95 217.73 319.88 1,364.06 14.42 11.66 64.95 8.83 13.17 98.40 7.16 8.91 77.81 131.33 254.74 1,525.88 Fuelsandmining

products

Manufactures 2,391.15 4,692.27 11,510.95 489.51 1,232.48 2,054.77 75.23 146.88 503.51 1,213.89 2,016.28 4,630.77 64.67 51.43 392.62 62.69 85.69 332.13 68.82 111.99 484.33 416.34 1,018.25 3,028.67 Manufactures

Total merchandiseb 3,395.36 6,277.19 17,816.37 650.28 1,549.12 2,922.57 104.60 203.60 748.88 1,676.61 2,659.83 6,881.27 127.96 76.64 529.70 88.51 122.36 538.08 94.60 145.56 671.92 652.82 1,433.18 5,132.73 Total merchandiseb

North America North America

Agriculturalproducts 85.21 115.31 251.36 24.14 49.14 94.80 3.34 6.26 17.40 17.37 15.78 23.87 3.38 1.04 2.66 2.59 3.20 9.38 2.68 3.10 7.08 31.70 36.41 95.90 Agriculturalproducts

Fuelsandminingproducts 58.79 94.34 408.87 29.51 71.17 237.84 2.57 4.05 41.09 12.01 9.22 60.41 0.06 0.03 1.26 0.42 0.51 4.62 0.59 0.42 2.92 13.63 8.93 59.96 Fuelsandmining

products

Manufactures 375.20 963.22 1,499.02 152.33 534.99 731.11 30.89 54.66 135.67 92.71 167.33 249.79 1.12 2.23 11.19 5.56 7.64 21.64 8.34 15.56 49.31 84.25 180.61 299.49 Manufactures

Total merchandiseb 547.66 1,224.98 2,282.46 217.46 682.79 1102.89 37.66 67.87 201.23 130.07 205.16 382.20 6.17 3.52 15.37 9.05 12.10 37.47 12.54 20.38 62.78 134.70 232.56 476.31 Total merchandiseb

South and Central America South and Central America



products

Manufactures 44.30 72.96 198.09 24.97 33.53 55.07 7.47 24.72 94.65 6.52 9.89 25.55 0.23 0.03 0.50 0.72 0.82 4.26 0.64 0.32 1.49 3.76 3.55 16.13 Manufactures

Total merchandiseb 120.33 197.77 749.98 49.27 78.17 181.39 17.29 50.56 200.41 28.43 38.84 137.51 9.02 1.29 8.46 2.07 2.80 21.35 2.08 2.85 17.83 12.18 19.10 168.79 Total merchandiseb

Europe Europe



products

Manufactures 1,328.66 2,125.51 4,977.05 113.09 237.40 393.66 21.64 39.98 103.92 954.93 1,532.78 3,414.84 49.59 26.98 200.02 43.78 49.90 141.39 36.99 50.80 158.35 108.63 174.13 540.61 Manufactures

Total merchandiseb 1,685.82 2,633.98 6,612.32 135.52 275.77 480.07 24.38 45.05 118.75 1,223.39 1,928.08 4,667.31 78.43 33.29 234.00 54.19 61.91 199.39 46.01 59.79 194.40 123.89 199.95 638.57 Total merchandiseb

Commonwealth of Independent States (CIS) Commonwealth of Independent States (CIS)

Agriculturalproducts 6.05 13.10 58.93 0.03 0.42 0.53 0.26 0.04 0.21 4.15 3.97 13.87 - 3.94 21.01 0.31 0.22 4.25 0.13 0.29 4.27 1.16 3.88 11.99 Agriculturalproducts

Fuelsandminingproducts 32.86 84.81 521.30 0.74 6.11 34.76 0.65 4.72 3.29 27.91 55.90 334.17 - 10.03 53.60 0.26 0.15 2.97 0.35 0.97 7.14 2.95 6.75 79.40 Fuelsandmining

products

Manufactures 17.14 43.66 180.48 0.20 3.57 7.41 1.45 1.04 6.05 9.49 12.21 50.45 - 14.91 76.99 1.32 1.31 3.67 1.55 1.84 9.97 3.13 8.58 23.10 Manufactures

Total merchandiseb 58.13 145.72 788.76 0.99 10.16 43.22 2.59 5.79 10.75 42.77 74.70 408.77 - 29.13 154.15 1.91 1.78 12.49 2.52 3.12 23.77 7.35 20.01 116.95 Total merchandiseb

Africa Africa



products



Middle East Middle East



products



Asia Asia



products

Manufactures 584.56 1,396.35 4,284.79 194.28 405.94 831.34 13.30 25.39 156.66 130.26 260.71 798.33 11.08 6.12 99.32 8.36 17.73 117.77 16.99 34.74 198.54 210.30 635.51 2,043.69 Manufactures

Total merchandiseb 739.01 1,658.16 5,537.99 211.26 435.73 906.14 15.99 28.37 188.55 150.74 289.84 922.17 17.84 7.66 109.92 10.83 22.09 152.48 21.30 42.51 241.64 311.06 814.73 2,926.03 Total merchandiseb


Note:FiguresforEuropein1990donotincludetheBalticStatesofEstonia,LatviaandLithuania,whilefiguresforCISin1990doincludetheBalticStates.

aIncludesunspecifieddestinations.bIncludesunspecifiedproducts


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AppendixTableB.2:Network of world merchandise trade by product and region, 1990-2011 (US$billion)Destination Worlda North America South and Central America Europe CIS Africa Middle East Asia Destination

1990 2000 2011 1990 2000 2011 1990 2000 2011 1990 2000 2011 1990 2000 2011 1990 2000 2011 1990 2000 2011 1990 2000 2011

Origin Origin

World World

Agriculturalproducts 414.72 551.18 1,659.52 51.35 89.50 196.41 11.01 20.39 67.64 214.99 256.69 689.44 16.74 12.56 66.66 15.58 19.42 89.91 15.26 19.76 86.61 89.79 128.80 451.53 Agriculturalproducts

Fuelsandminingproducts 488.32 852.63 4,007.83 92.82 188.41 611.91 16.03 31.33 155.95 217.73 319.88 1,364.06 14.42 11.66 64.95 8.83 13.17 98.40 7.16 8.91 77.81 131.33 254.74 1,525.88 Fuelsandmining

products

Manufactures 2,391.15 4,692.27 11,510.95 489.51 1,232.48 2,054.77 75.23 146.88 503.51 1,213.89 2,016.28 4,630.77 64.67 51.43 392.62 62.69 85.69 332.13 68.82 111.99 484.33 416.34 1,018.25 3,028.67 Manufactures

Total merchandiseb 3,395.36 6,277.19 17,816.37 650.28 1,549.12 2,922.57 104.60 203.60 748.88 1,676.61 2,659.83 6,881.27 127.96 76.64 529.70 88.51 122.36 538.08 94.60 145.56 671.92 652.82 1,433.18 5,132.73 Total merchandiseb

North America North America



products

Manufactures 375.20 963.22 1,499.02 152.33 534.99 731.11 30.89 54.66 135.67 92.71 167.33 249.79 1.12 2.23 11.19 5.56 7.64 21.64 8.34 15.56 49.31 84.25 180.61 299.49 Manufactures

Total merchandiseb 547.66 1,224.98 2,282.46 217.46 682.79 1102.89 37.66 67.87 201.23 130.07 205.16 382.20 6.17 3.52 15.37 9.05 12.10 37.47 12.54 20.38 62.78 134.70 232.56 476.31 Total merchandiseb

South and Central America South and Central America



products



Europe Europe



products

Manufactures 1,328.66 2,125.51 4,977.05 113.09 237.40 393.66 21.64 39.98 103.92 954.93 1,532.78 3,414.84 49.59 26.98 200.02 43.78 49.90 141.39 36.99 50.80 158.35 108.63 174.13 540.61 Manufactures

Total merchandiseb 1,685.82 2,633.98 6,612.32 135.52 275.77 480.07 24.38 45.05 118.75 1,223.39 1,928.08 4,667.31 78.43 33.29 234.00 54.19 61.91 199.39 46.01 59.79 194.40 123.89 199.95 638.57 Total merchandiseb

Commonwealth of Independent States (CIS) Commonwealth of Independent States (CIS)

Agriculturalproducts 6.05 13.10 58.93 0.03 0.42 0.53 0.26 0.04 0.21 4.15 3.97 13.87 - 3.94 21.01 0.31 0.22 4.25 0.13 0.29 4.27 1.16 3.88 11.99 Agriculturalproducts

Fuelsandminingproducts 32.86 84.81 521.30 0.74 6.11 34.76 0.65 4.72 3.29 27.91 55.90 334.17 - 10.03 53.60 0.26 0.15 2.97 0.35 0.97 7.14 2.95 6.75 79.40 Fuelsandmining

products

Manufactures 17.14 43.66 180.48 0.20 3.57 7.41 1.45 1.04 6.05 9.49 12.21 50.45 - 14.91 76.99 1.32 1.31 3.67 1.55 1.84 9.97 3.13 8.58 23.10 Manufactures

Total merchandiseb 58.13 145.72 788.76 0.99 10.16 43.22 2.59 5.79 10.75 42.77 74.70 408.77 - 29.13 154.15 1.91 1.78 12.49 2.52 3.12 23.77 7.35 20.01 116.95 Total merchandiseb

Africa Africa



products



Middle East Middle East



products



Asia Asia



products

Manufactures 584.56 1,396.35 4,284.79 194.28 405.94 831.34 13.30 25.39 156.66 130.26 260.71 798.33 11.08 6.12 99.32 8.36 17.73 117.77 16.99 34.74 198.54 210.30 635.51 2,043.69 Manufactures

Total merchandiseb 739.01 1,658.16 5,537.99 211.26 435.73 906.14 15.99 28.37 188.55 150.74 289.84 922.17 17.84 7.66 109.92 10.83 22.09 152.48 21.30 42.51 241.64 311.06 814.73 2,926.03 Total merchandiseb


Note:FiguresforEuropein1990donotincludetheBalticStatesofEstonia,LatviaandLithuania,whilefiguresforCISin1990doincludetheBalticStates.

aIncludesunspecifieddestinations.bIncludesunspecifiedproducts

Trends in international trade

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