tariffs tend to be mosthurtful to the poor, as T&C industries primarily employ low-skilledworkers, often migrants from rural areas. Also, low-income households in industrial countries bear the brunt of the cost of MFA andhigh tariff restrictions as the poor spend a larger share of their income on necessities such as T&C.The delay in the integration plan according to the ATC leads toadjustment needs. The above mentioned back loading of effectiveliberalization turns what was planned as a gradual adjustment process into a shock at the end of the transition period (in 2005) – forboth importing and exporting countries. According to the IMF andWorld Bank study, this raises concern that political pressures mightspark greater recourse to other forms of protection once quotas arephase out, with trade remedy action and perhaps non-transparent‘voluntary’ export restraints (prohibited in principle under theWTO) becoming a ‘new line of defence’.145 A sudden withdrawalof quota protection at the end of the transition period might alsoincrease resistance to further reductions in tariffs. Accelerating theremoval of quotas on textiles and clothing imports is an urgent priority. Additionally, the Doha round negotiations should lead tosubstantially lower tariffs on T&C trade, in both industrial and developing countries.143 Ibidem, 42 et seq.144 Ibidem, 3.145 Ibidem, 44.
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Preferences for LDCs are not a long-term solution to problemsof competitiveness, but schemes that provide LCDs with duty- andquota-free market access may ease problems of transition. Benefitsof preferential market access can be substantially reduced and evennegated by restrictive rules of origin, either because of the need toswitch to higher-cost sourcing of intermediate goods, or becausevalue added thresholds for preferential access are hard to meet.Mattoo et al. estimate that benefits under the AGOA could be reduced by as much as 75-80 percent because of onerous rules ofregion (there are similar problems with EU preferentialschemes).146 In addition to the rules of origin, there is often a finebalance to strike on social and environmental conditions. As demonstrated in the case of minimum labour standards in connectionwith Cambodia’s exports of T&C, minimum wages and other conditions for preferential access may have limited the benefits thecountry has drawn from these preferential schemes.147IV. Gains from Trade Liberalizationunder a Successful Doha Round
A. Formula Approaches to Market Access Negotiations1. The General Procedure of NegotiationsConcerning market access for products, there are 146 membersnegotiating on thousands of products. Under such circumstances,any means for simplifying negotiations are welcome. One instrument is the ‘formula approach’.A variety of approaches has been used in the past to negotiatethe reduction of bound tariffs starting with the request and offerapproach. This technique, grounded in the selected product byproduct approach proved cumbersome and yielded results that werenot particularly ambitious. Two significant departures from thisapproach occurred during the Kennedy Round. Industrialised countries adopted a linear tariff reduction technique and developingcountries were granted ‘less than full reciprocity’.148In the Tokyo Round an explicit reference was made to ‘appropriate formulae’. A number of proposals were submitted in re146 Mattoo et al. (2002).147 See IMF / The World Bank (2002), 46 for a case study on Cambodia.148 Hoda (2001).
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sponse to the mandate, including some that had the effect of higherreductions for higher tariff rates in contrast to a linear reduction.The proposal from Switzerland was ultimately adopted by somecountries.In the so-called ‘Swiss formula’149 the target tariff rate,t1 depends non-linearly on the initial tariff rate t 0 and a coefficient a :at 0,(3)t1a  t0where a is a coefficient corresponding to the upper limit of desiredtariff rates after the cut. In applying this formula some countriesused a coefficient a equal to 14, others adopted 16. The formulawas not universally applied by all countries and those that applied itdid so with exceptions. Francois and Martin survey a range of formula options and examine both targeted and flexible applications ofthe Swiss formula that target tariff escalation and peaks, and wouldallow policymakers to directly target how far they will move towards free trade, while providing some flexibility for trading offreductions in peak tariffs against reductions in lower-tariff sectors.150The mandate for the Uruguay Round negotiations and theDDA did not specifically mention the use of formulae as the coremodality. However, during both negotiations proposals for modalities based on formulae have figured prominently. In the currentDoha agriculture negotiations some Members proposed the Swissformula with a coefficient a equal 25. In the non-agricultural market access negotiations the Swiss formula was proposed by theUnited States with a coefficient of 8 for certain phases of their proposed tariff reduction plan. In addition, variants of the Swiss formula that take into account the diversity of Members’ profiles wereproposed.151
149 See WTO (2003), 150; Fontagné (2003), 6; Francois / Martin(2003).150 Francois / Martin (2003), see also Panagariya (2002) for more details on the general properties of formulas that have been used for reciprocal negotiations.151 See WTO (2003), 150 et seq. with references to the documents forthe full variety of proposals.
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The Chair’s draft proposal for the Doha negotiations on agriculture followed the approach used during the Uruguay Roundwhich was a target rate of reduction based on a simple average ofout-quota tariff rates with a minimum cut per line. The reductionswould apply across three different bands of tariffs with a higheraverage reduction for tariffs in the high range. Developing countrieswere proposed a similar approach, but with higher thresholds fortariffs to be reduced and lower percentage reductions.In the Doha non-agricultural market access negotiations theChair proposed a number of elements for the reduction of tariffs.The core element is the following formula to be applied on a lineby-line basis:Bt a t 0t1(4)Bt a  t 0where, t1 is the final rate, to be bound in ad valorem terms; t0 is thebase rate for negotiations, ta is the average of the base rates and B isa coefficient with a unique value to be determined by the participants.Less than reciprocity in this context is incorporated into theformula through the ta coefficient. A higher coefficient implies alower reduction and developing countries in general have higheraverage applied and bound tariffs (see Table 1). The Chair furtherproposed that WTO members could consider the elimination oftariffs in certain sectors of export interest to developing countries.As with agriculture, the Chair’s proposal in non-agricultural marketaccess takes into account the issue of special and differential treatment (SDT) for developing countries.The impact of a 50 percent Swiss-formula based reduction ofaverage tariff bindings for industrial and developing countries hasbeen demonstrated152 (see Table 11a and Table 11b).With the implementation of the Uruguay Round commitments,average ad valorem tariffs in the industrial countries, generally arearound 3 percent (see Table 11a, first column). However, there areimportant exceptions. One of these is textiles and clothing, wherethe average rate is roughly three times this overall average. This isreflected in the standard deviation and maximum tariff columns.With full implementation of current commitments, the estimatedsimple average industrial tariff in the United States is 3.2 percent,152 Francois / Martin (2003); Francois / van Meijl / van Tongeren (2003).
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with a standard deviation of 4.3, and a maximum tariff of 37.5 percent. The European Union has a higher average (3.7 percent), butless dispersion (3.6 percent) and a maximum tariff rate of 17 percent. For the developing countries, average industrial tariffs rangefrom a low of 3 to 4 percent to a high of more than 20 percent. InTable 11a the data for three developing countries are presented:Brazil, India, and Thailand. Brazil’s tariffs are all bound, though theaverage rate for industrial products is 14.9 percentage points abovethe currently applied rate (binding overhang). India and Thailand’stariffs are partially covered by bindings, again with significantbinding overhang.Table 11a: The Post-Uruguay Round and ITAi) Applied Tariffs inSelected Industrial and Developing CountriesPost-UR and ITA tariffs (in %)StandardMaximumBindingdeviationtariffoverhangii)AgricultureEU5.97.574.90.3Japan6.28.143.31.2USA3.57.490.00.5Brazil12.95.127.022.6India31.020.8150.090.7Thailand26.514.465.07.1Non-agricultureEU3.73.617.00.4Japan2.33.430.90.1USA3.24.337.50.2Brazil15.96.035.014.9India19.216.540.03.9Thailand10.510.880.07.8i)ITA = Information Technology Agreement.ii)Binding overhang is the gap between the bound rate and the currentapplied tariff rate.Source: Francois / van Meijl / van Tongeren (2003), Table 2.2.Simpleaverage
Because of the small binding overhang in industrial countries a50 percentage point tariff reduction according to the Swiss formulaleads also to a comparable strong reduction in applied tariffs (seelast column in Table 11b). In general, for developing countries, thebinding overhang is large enough that reductions in the range of 50percent are necessary to force any reductions in average appliedrates for countries like Brazil. For many countries, even this will
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have little or no effect, as tariffs are largely unbound. This limitsseverely the negotiating leverage of developing countries in theWTO. This is also why the debate over using bound, applied, or‘historic’ rates in the WTO as a starting point for negotiations isimportant.153Table 11b: Effects of Basic Swiss Formula Reductions: AppliedTariffs after a 50 % Cut in Average Tariff BindingsStandard Maximum Bindingø%deviationtariffoverhang reductionAgriculture:EU3.02.910.90.1-48.6Japan3.53.713.90.2-43.0USA1.92.411.50.1-46.6Brazil12.44.622.35.3-3.7India29.514.970.831.3-4.8Thailand15.16.330.11.7-43.0Non-agricultureEU1.91.45.00.1-47.7Japan1.21.45.60.0-48.5USA1.71.66.10.0-48.3Brazil13.54.216.71.9-15.4India11.39.230.50.3-41.3Thailand7.26.120.72.0-31.6Source: Francois / van Meijl / van Tongeren (2003), Table 2.2.Simpleaverage
2. The Danger of Preference Erosion for the Developing CountriesA formula approach fits well the objectives of the DDA and hasadvantages and caveats:1541. Advantages: By strongly reducing tariff peaks, it offers betteraccess to LDC exports in labour intensive and agriculturalgoods. It opens other developing countries’ markets that remain currently highly protected and thus stimulates SouthSouth trade. It allows a different a coefficient for developedand developing economies and, hence, respects the spirit of theSDT; last but not least it allows also a different coefficient fortrade in manufactures and food products in order to match political economy constraints.
153 See Francois / van Meijl / van Tongeren (2003), 3.154 See Fontagné (2003), 6 et seqq.
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Shortcomings: This means, however, ‘killing too many birdswith one stone’.155 The advantage of differentiating the acoefficient contradicts the objective of making agriculturalmarkets more open, or of enhancing South-South trade. Tariffpeaks potentially affect exports of LDCs which are nevertheless conceded preferential market access (ACP countries, theGSP scheme, AGOA, EBA, etc.). Hence, any (non-linear)formula approach will have two effects: a) to eradicate the remaining peaks faced by LCDs exporters, and b) to erode themargin of preferences they had been conceded. The net effectmay be negative.Fontagné by discussing a number of other subtle problemsconnected with the impact of formula based trade liberalization fordeveloping countries simulates the different formula approacheswith a multi-country CGE model (see Table 12).156
2.
Table 12: Formula Approaches – which Differences for WelfareChanges? (Simulations with a CGE world model)LinearLinearSwissSwiss formulaLong-run welfareformulaformulaformula+ SDTchange in %excl. peaksEU-250.380.140.550.47USA0.180.090.240.12Japan0.860.291.451.29Cairns0.300.140.350.39Developing Asia0.800.281.070.91ACP countries0.430.260.410.29Other countries0.550.200.790.70World0.420.160.610.51Assumptions for coefficient a = 35 % for the linear formula t1 = at0 and aSwiss formula, and a coefficient a equal to 28 (manufactures) or 58 (food).Source: Fontagné (2003), 8.
Fontagné focuses on market access with a menu of scenariosin which developing countries are conceded SDT. Bilateral tariffs atthe product level (HS-6 level), derived from MAcMaps, are cut
155 Ibidem, 6.156 Ibidem, 7 et seq.
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according to a linear formula (where tariff peaks157 can be includedor excluded from the liberalization), versus a truncated Swiss formula158 (applied to all tariffs). Coefficients of reduction are thosesuggested by previous rounds, and the SDT offered to developingcountries is a lower coefficient of linear reduction and a larger acoefficient in the Swiss formula.159The results of Table 12 highlight that benefits of increasedmarket access at the world level are much higher with a Swissformula and, in contrast, rather limited if one adopts a linear formula excluding peaks. Considering the Swiss formula combinedwith the SDT, the largest benefits accrue to Japan, where agriculture is highly protected. This is also why EU gains are much largerthan US ones. Lastly, ACP countries record very limited gains, inparticular in comparison to developing Asia which has in the pastbeen conceded less preferences by industrialised importers.In summing up, Fontagné asserts that a formula approachleads to a sizeable erosion of preferences conceded to the poorestdeveloping countries so far, with the aim of favouring exports ofsmall and insufficiently diversified economies. The more specialised the exporters, the larger the benefits extracted in the past frompreferential access schemes and the stronger the adverse effects ofmarket opening they will have to cope with.160B. How to Estimate Gains from Multilateral Trade Liberalization?The estimation in quantitative terms of the potential gains fromtrade liberalization is now done primarily with CGE models. Thesystematic use of CGE models to simulate the effects of trade negotiations started during the Tokyo Round.161 Since then rapid progress has been made as regards both modelling and data collectionand assembly. Results from CGE simulations found a wide echobefore the conclusion of the Uruguay Round, showing that nearly157 Tariff peaks are defined as those superior to 15 percent inmanufacturing, energy and raw materials, and those above 85 percentin agriculture and agrofood.158 In a truncated Swiss formula, the reduction is linear up to the threshold defined as a tariff peak, and non-linear thereafter.159 Fontagné (2003), 8.160 Ibidem.161 See Deardorff / Stern (1981); Deardorff / Stern (1986); Whalley(1985).
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all countries would have lost opportunities from a failure to reachagreement.162In recent years, several CGE analyses of the effects of tradepolicy reforms in a future WTO Round have been produced.163Some of them only consider agricultural liberalization (with welfaregains ranging from US$ 27 billion to US$ 384 billion, dependingon the liberalization assumptions and the model type), others include manufacturing tariff reform (the welfare gains range fromUS$ 284 billion to US$ 1,210 billion). Only a few analyses consider the impact of service trade liberalization, mainly because ofpoor data on trade flows in the services sector and poor measurement of service trade barriers. The few studies considering liberalization in trade in services produce very large welfare gains.164These large gains are due to two reasons: 1) Services account for alarge share in consumption in most middle and high-income countries, much larger than that of agriculture. 2) Services are majorinputs in the production of manufactures. Estimations of the WorldBank of the effects of a 100 percent cut in merchandise protectionand a 100 percent cut in service protection lead to a welfare gain inthe static case of US$ 255 billion and in the dynamic version ofUS$ 830 billion.165 Brown et al. with the same liberalization experiment reach welfare gains of US$ 1,857 billion.166There are several reasons for the large discrepancies in the estimations of welfare gains: a) assumption about the deepness of theliberalization; b) results are sensitive to model specifications: liberalization gains are higher in models allowing for increasing returnsto scale and imperfect competition in the manufacturing sector. Thegains are further enhanced in specifications allowing for dynamic(growth) effects of trade liberalization (trade-related changes insavings and investment or with development in productivity); c)also the chosen baseline influences the outcome; in most recentstudies the GATP database (of 1997) is used to replicate the worldeconomy. These most updated versions yield lower estimates of the162 See the surveys of Harrison et al. (1997), and Francois et al. (1994)and (1996).163 For a survey, see UNCTAD (2003), 39, and also Francois (2000).164 See Brown et al. (2001); World Bank (2001).165 World Bank (2001).166 Brown et al. (2001).
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world-wide liberalization effects since the status-quo level of tradebarriers is lower (after the tariff cuts of the Uruguay Round); d) alsothe dimensionality of the models (the number of sectors and regionsconsidered) influences the outcome.Notwithstanding the notable differences in results from thevarious CGE analyses, there are a number of common findings:1671) Global welfare results of agricultural liberalization are quitesimilar across models and studies. This is due to the consensus ofmodelling agriculture as a constant returns to scale sector wheretrade-related dynamic gains are quite limited. 2) A common featureof static, constant returns to scale CGE models is that the globalgains associated with (full) agricultural liberalization are not verydifferent from those originating from trade liberalization in manufactures. 3) Concerning the source of gains, almost all studies showthat the major source of the gains accruing to each country is itsown liberalization, rather than that of partner countries. 4) As forthe distribution of the global gains between developed and developing countries, in the majority of the studies it was found that thegains are shared quite equally between the two groups. Amongdeveloping countries, Asian countries will reap the largest gains,while the gains for Latin American and African countries will bemore limited. Even possible losses are found for Sub-Saharancountries associated with agricultural liberalization, markedly withterms-of-trade developments as a consequence of export subsidiesremoval.In the following two recent CGE model exercises are presented. One is a simulation of a world-wide cut of all merchandisetariffs (agricultural and manufactures) with a static model.168 Theother one by Francois et al. is more ambitious as it considers acomplete liberalization package (agriculture, manufactures, services) and uses a model with imperfect competition and dynamicelements.1691. UNCTAD SimulationsUNCTAD uses a static CGE model based on GTAP5 data base witha benchmark year 1997, disaggregated to six sectors (natural resources, manufactures, primary and processed agricultural products,167 See UNCTAD (2003), 40.168 Ibidem, 48 et seq.169 Francois / van Meijl / van Tongeren (2003)
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textiles and apparel, services) and twelve world regions of whichfour are developing country regions.170 A worldwide 50 percentreduction of all merchandise tariffs (agricultural and manufactures)– a so-called comprehensive liberalization scenario – leads to thefollowing results (see Table 13): The global welfare gain of aroundUS$ 40 billion is almost twice as much than that arising from liberalization in agriculture only (see Table 10). The big gainers fromadding manufacturing liberalization to agriculture liberalization arethe Asian regions (+0.6 percentage points increase in welfare), followed by North Africa and Middle East (+0.4 percentage points),China and Oceania. Some countries, however, will not have anadvantage from extending liberalization beyond agriculture. Theseare in particular North America (Canada, United States), transitioneconomies (Hungary, Poland, the Rest of Central European countries, Former Soviet Union) and Sub-Saharan Africa, which wouldsuffer from terms-of-trade losses by adding manufacturing liberalization. All these countries would see their market shares in textilesand clothing and other manufactures eroded by surging importsfrom Asia.
170 UNCTAD (2003), 48 et seq.
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Table 13: A Comprehensive Doha Round Liberalization Scenario:Results of Model Simulations of a 50 % Worldwide Cut in Tariffson all Merchandise TradeRegions
Welfare effectsAggregate trade dataPercentageTotal valueExports Terms of tradechange(‘97 US$ mill.) Percentage change0.6746,636.53.8990.1680.4245,017.17.4580.0120.2821,383.312.043-1.7470.0755,489.61.1050.0780.0231,778.02.591-0.0080.079603.13.860-0.483
Asian NICsChinaSouth AsiaWestern EuropeNorth AmericaTransitioneconomiesSub-Saharan0.004AfricaOceania0.386North Africa and0.476Middle EastLatin America0.079Japan0.307Rest of the world0.281TotalSource: UNCTAD (2003), 48.
13.3
4.590
-0.927
1,584.13,735.8
4.2655.004
1.435-0.806
1,414.011,207.4706.339.568.5
5.7195.5128.789
-0.7340.7520.091
The removal of all tariff protection boosts exports in all areas(see Table 13). The increase is in general much stronger than thatassociated with the elimination of agricultural tariffs only. The bigger increases in exports occur in low- to middle-income Asiancountries (China, South Asia), followed by other developing countries and by Japan and Oceania. Western Europe and North America do not achieve major expansion of their exports.These results – not taking into account dynamic effects and imperfect competition in the manufacturing sectors – underline whatwas found in previous studies,171 namely that the inclusion ofmanufacturing liberalization in a ‘comprehensive round’ of negotiations would be especially interesting for the developing countries. This conclusion holds for developing economies taken as asingle broad aggregate. There are, however, regions, in particularSub-Saharan Africa, that might actually lose from extending liberalization from agriculture alone to all merchandise trade.171 See Hertel / Martin (2000).
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2. CGE Model Simulations with Imperfect CompetitionFrancois, van Meijl and van Tongeren with a CGE model with imperfect (monopolistic) competition and investment (dynamic) effects simulated the potential gains from a comprehensive DohaRound trade liberalization.172 They take the short-run (static) andthe long-run (dynamic model) view. They include in their scenariosof trade liberalization tariff reductions (in agricultural, manufactures and in services trade), elimination of border controls, exportsubsidies, agricultural support and trade facilitation.The data on tariffs are taken from the WTO’s integrated database, with supplemental information from the World Bank’s recentassessment of detailed pre- and post-Uruguay Round tariff schedules and from the UNCTAD/World Bank WITS dataset. All of thistariff information has been concorded to GTAP model sectors. Services trade barriers are based on the gravity model estimates. Alsothe schedule of China accession commitments is implemented.While the basic GTAP dataset is benchmarked to 1997, and reflectsapplied tariffs actually in place in 1997, the authors want to workwith a representation of a post-Uruguay Round world. This includesthe accession of China, the enlargement of the EU; and Agenda2000 reforms a part of the baseline. In the baseline scenario therefore the following inclusions have been made:173x Implementation of the rest of the Uruguay Round tariff commitments,x implementation of the ATC phasing-out quotas,x implementation China’s accession to the WTO,x implementation of Agenda 2000,x implementation of the EU enlargement by 12 countries (EU27).The CGE model has been aggregated to 17 sectors and 16 regions. Perfect competition is assumed in the agricultural sectors.The manufacturing and services sectors involve imperfect (monopolistic) competition. There is a dynamic link, whereby the staticor direct income effects of trade liberalization induce shifts in theregional pattern of savings and investment. These effects relate toclassical models of capital accumulation and growth, rather than toendogenous growth mechanism. How much these ‘accumulation172 Francois / van Meijl / van Tongeren (2003).173 Ibidem, 8.
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effects’ will supplement static effects depends on the marginalproduct of capital and underlying savings behaviour. This specification allows to differentiate between short-run versus long-runeffects. In the short-run capital stocks are fixed and in the long-runcapital stocks adjust. The model includes the basic features of ‘economic geography’ models, including intermediate linkages, monopolistic competition, and returns from specialization.174In the model estimations three scenarios are carried out:175 Thefirst two are partial liberalization scenarios. In the ‘Linear 50%’scenario all trade instruments are reduced by 50 percent. This involves a 50 percent reduction in agricultural and industrial tariffsand export subsidies, a 50 percent reduction in OECD domesticsupport for agricultures, a 50 percent reduction in the tariff-equivalent of services barriers, and a partial reduction in trading costs,related to trade facilitation measures (1.5 percent of the value oftrade). The second partial liberalization experiment is called the‘Swiss formula’ experiment. In this experiment the reduction inimport tariffs in agriculture and manufactures is based on a straightSwiss formula with a coefficient of 25, meaning the maximum tariffis reduced to 25 percent. The third scenario simply involves fullelimination of all trade barriers, implying in the case of trade facilitation a reduction of trade costs of 3 percent of the value oftrade.
174 Ibidem, 7.175 Ibidem , see also Table 14.
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Table 14: Three Liberalization ScenariosScenario definitionInstrumentsLinear 50%Swiss formula Full liberalizationImport tariffs in50% reduction Swiss formula100%agriculture andReduction (with areductionmanufacturingmax 25% tariff)Estimated border50% reduction 50% reduction100%measures in servicesreduction50% reduction 50% reduction100%Export subsidiesreductionDomestic agricul50% reduction 50% reduction100%tural support inreductionOECD countriesTrade facilitation1.5% of value 1.5% of value of 1.5% of valueof tradetradeof tradeSource: Francois / van Meilj / van Tongeren (2003), Table 2.5
The results are reported in Table 15.176 They refer to staticwelfare gains from a linear 50 percent liberalization (scenario I).The overall effects of agricultural liberalization are not clear-cut.Liberalization of domestic support in the OECD is generally positive for the OECD (in particular positive for EU countries andNorth America), however, negative for the food-importing SubSaharan Africa. But also other developing countries would lose.Even Australia and New Zealand, both net agricultural exportersgain only marginally from liberalizing domestic support. Agricultural liberalization of border measures sees all countries as winnersif assuming constant returns to scale. If, however, increasing returnsto scale are considered a number of countries are losers: Mediterranean, China, India, Australia and New Zealand, South Africa andSub-Saharan Africa.
176 Ibidem, 11-15.
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Table 15: Static Welfare Effects (Equivalent Variations) from aLinear 50% Liberalization (Scenario I of Table 14), US$ mill.OECDAgriculture(bordermeasures)Agriculture(domesticsupport)Manufactures(border measures)ServicesliberalizationTradefacilitationTotal
24.482(16.818)
Developingcountries32.446(11.083)
Othercountries4.630
Total(World)61.558[96.743]
8.744
-
711
9.455[12.368]
12.057(5.622)
22.230(12.012)
2.789
37.076[54.247]
17.2256.9071.96326.0