Global Implications of Unraveling Textiles and Apparel Quotas Patrick Conway Department of Economics Gardner Hall, CB 3305 University of North Carolina Chapel Hill, NC 27599-3305 [email protected] Revised: 30 May 2006 Abstract With the end of the Agreement on Textiles and Clothing on 1 January 2005, the system of bilateral quota restraints on textiles and clothing negotiated by the US and European Union was dismantled. In this paper I examine the high-risk strategy that some countries adopted to exploit this protective system, and I analyze the impacts on the trade patterns of these countries from the removal of the quotas. There is evidence of a re-establishment of comparative advantage as the determinant of trade patterns and volumes. There have been more successes in maintaining and expanding market share among those countries pursuing the high-risk strategy of concentrated textiles/apparel exports to the US and EU than had been forecast. Unfortunately, there have also been many failures, with attendant steep reductions in manufactured exports. Thanks to Marco Fugazza and the economists of the Trade Analysis Branch at UNCTAD for stimulating my interest in this question. All conclusions are of course mine alone, as are any mistakes. Removal of Quotas on Textiles and Apparel - 2 The system of bilateral quantitative restraints (or quotas) on textile and apparel imports was an enduring feature of the US and European Union (EU) commercial policy system. From its inception in the early 1960s with the Long-Term Arrangement in Cotton Textiles (LTA), through its codification in the Multi-Fiber Arrangement (MFA) from 1974 to 1995, and to its 1995-2005 form in the Agreement on Textiles and Clothing (ATC), the system provided protection to US and EU producers of textiles and apparel. In the negotiations that led to the adoption of the ATC in 1995, the US and EU agreed to dismantle the system of quantitative restraints sequentially. A large number of restraints was removed at the beginning of 1995, 1998 and 2002, but those remaining governed trade in the categories of textiles and apparel most produced in the US and EU. These remaining restraints were removed on 1 January 2005. The ATC by its end had evolved into a complicated interlocking set of bilateral agreements on quantities exported. They acted as voluntary export restraints, but they were binding in any given year on only a small subset of the countries under restraint. Specific limits and group limits interacted in non-transparent ways to limit a given country’s exports. Removal of the ATC restraints led to a drastic re-sourcing of US and EU textiles and apparel imports. In this paper I illustrate the initial resourcing of imports, both in aggregate and in three specific quota categories. The increased concentration of sourcing in China and India, predicted prior to the removal of restraints, is certainly evident. Also evident is the success of firms in a number of other countries in expanding their exports. The tragedy of this trade liberalization has been felt in a number of smaller developing countries whose exports have been cut back drastically. I. Characteristics of the restraints on textiles imports to the US and EU. The basic unit of the quota system was the restraint category, or quota category. These categories were defined as aggregated subgroups of textile and apparel products with some shared characteristic or raw material. The system of import restraints defined by the US identified 11 aggregated categories of yarns, 34 aggregated categories of textiles, 86 categories of apparel and 16 categories of miscellaneous textiles (e.g., towels). Together these categories spanned the entire set of US textile and apparel imports. The EU identified 41 categories of yarns, 28 categories of textiles, 42 categories of apparel and 32 categories of miscellaneous textiles for a total of 143 categories – although some of these categories were further subdivided by raw material.1 Each category included multiple products. For example, US category 225 (blue denim) was aggregated from 16 distinct HS product lines. Products included in each category were similar, but could have significant differences: for example, the “blue denim” category included denim made from both cotton and man-made fibers. There is no corresponding category for the EU: its blue-denim imports would have been classified 1 The categories for the US, and the correspondence between those categories and the HS classification of imports, are published by the Office of Textiles and Apparel (OTEXA), Department of Commerce, at http://otexa.ita.doc.gov/corr.htm. The categories for the EU, and concordance with CN category, are published in EEC Council Regulation 3030/93 of 12 October 1993. Removal of Quotas on Textiles and Apparel - 3 EU category 2 (woven cotton fabric, with 105 CN product lines) or EU category 3 (synthetic woven fabric, with 80 CN product lines). Limits under the system of restraints were divided into specific limits and group limits. Specific limits governed the import of goods within the specific quota category. Group limits placed aggregate limits on a subset of the quota categories. If a country’s exports were subject to group limits but not specific limits, then the suppliers of that country (or more likely, a government agency supervising these exports) could choose any mix of goods shipped to the US so long as in aggregate the totals did not exceed the group limit. Some group limits covered only two quota categories: e.g., US group 300/301, covering US quota categories 300 (carded cotton yarn) and 301 (combed cotton yarn). Others spanned a large number of categories: for example, Subgroup 1 in Hong Kong included US quota categories 200, 226, 313, 314, 315, 369 and 604. In many cases, a country had its exports bound by both specific limits and group limits. Under the MFA and ATC, exporting countries were given flexibility in meeting these restraints. In each category, the agreement specified a percentage by which the country could either exceed or fall short of its restraint. In those cases, a maximum percent of possible “carryforward” or “carryover” is specified in the agreement. With carryforward, the country transfers part of this year’s quota to the following year. With carryover, the country exceeds its quota in this period by counting the excess against quota in the following year.2 Not all textiles exporters were subject to quantitative limits. Under the MFA and ATC, restraints were negotiated whenever a country’s exports caused (or threatened to cause) market disruption in the US or EU. Of the 152 countries exporting cotton knit shirts to the US (US categories 338 and 339), only 32 were subject to quantitative limits in 2004 and of these only 11 exported as much as 90 percent of the quota limit to the US. Similarly, of the 156 countries exporting knit shirts (cotton and other fabrics) to the EU only 25 were subject to quantitative limits in 2004, and of those four exported more than 90 percent of the quota limit to the EU. II. Previous research on these restraints. The ATC and its predecessor MFA have prompted academic research in the past that can be reported in two broad categories. The larger category has included calculations of the quantitative impact of these restraints on welfare in the US. Cline (1987), de Melo and Tarr (1990), and more recently US ITC (2002), illustrate these efforts and document the large costs to consumers associated with the restraints. The smaller category includes papers that examine the quantitative effects of these restraints on the exporting nations. Dean (1990) examines aggregate imports of textiles and clothing products from eight Asian countries during the period 1975-1984, and concludes that the MFA restraints were successful in restraining exports from the targeted countries: in her words, “a controlled 2 Information on flexibility is drawn from “Summary of Agreements”, OTEXA, January 2003 and from Annex 8, EEC Council Regulation 3030/93, as updated in EC Commission Regulation 930/2005. Removal of Quotas on Textiles and Apparel - 4 country’s import share grew, on average, 56 percent more slowly than the share of an uncontrolled country.” (Dean, 1990, p. 69) A number of authors have used computable general-equilibrium models to estimate the impact of the MFA system (and its removal) on developing countries. Trela and Whalley (1990) found that the aggregated system imposed welfare losses upon the developing- country exporters, and calculated a new general-equilibrium outcome for the post-system world economy. Yang et al. (1997) examined the relative growth of textiles exports to the US across developing-country exporters as the system of restraints is discontinued. All regions were forecast to increase textile exports, although Hong Kong, Taiwan and Korea were expected to face reduced demand for apparel as other developing countries expanded market share. Dean (1995) examined the incidence of restraint agreements under the MFA in order to determine the determinants of negotiated restraints.. The MFA, and after that the ATC, called for restraints to be negotiated on categories of textiles and apparel imported into the US if a country’s exports caused or threatened to cause market disruption in the US. Dean concluded that in the early years of the MFA (1974-1977) this was in fact the case – exporters individually responsible for large shares of US imports were targeted with these restrictions. In the later years of the MFA (1978-1985), the restraints were introduced upon countries representing much smaller shares of total US imports. These, according to Dean, may have been designed to target the threat of disruption rather than an actual disruption.3 Evans and Harrigan (2003) investigated the sourcing of apparel imports into the US under the constraints of the MFA. They used a simple model of import sourcing with three determinants: a country-specific effect, a “trade frictions” variable dependent upon tariffs and transport costs, and an interactive term of distance and a replenishment coefficient. Their central hypothesis relates to the hypothesis of “lean retailing” from Abernathy et al. (1999) – that retailers will source rapid-replenishment goods in closer locations to ensure quick availability – and they estimated this in a model that admits the impact of quota restrictions. They separated apparel imports into categories, and identify each category either as “rapid replenishment” or not. They concluded that import growth in rapid-replenishment goods was significantly larger in local suppliers, thus supporting the lean retailing hypothesis. Panagariya et al. (2001) estimated a demand system for apparel exports from Asia to the US. They used the fact that restraints were binding to simplify the typical demand system: quantities were treated as exogenous, and prices as endogenous. The MFA system was not itself the subject of the analysis, but the maintained hypothesis. The authors conclude that within this system the price elasticities of demand for textiles and apparel in the US are quite high: for example, they estimated a price elasticity of 26 for Bangladesh’s textiles and apparel exports to the US. 3 It’s also the case that restraints, once introduced, have not been removed. Thus, the “second wave” of restraints would have to be on smaller exporters, even if the policy goal is to restrain the largest exporters remaining unrestrained. Removal of Quotas on Textiles and Apparel - 5 III. Warning signs for countries of removal of quotas. Removing the quota system certainly created winners and losers. In a well-diversified economy, these gains and losses will be moderated. However, there will be some economies in which the potential for gain and loss will be magnified by the country’s reliance upon one product, and one export market, for a disproportionate part of its sales. In this section I identify those countries susceptible to large swings, either up or down, in response to the removal of quotas. This organization is built around the concept of export-led growth. If textile and apparel products are a disproportionately large share of total exports, if the US and EU are a disproportionately large share of the export market, and if the export/GDP ratio is large, then I will conclude that the country is disproportionately at risk from quota removal. The critical ratio for most countries will be the existing (i.e., observed in 2004) ratio of textile and apparel exports to the US and EU over the GDP of the exporting country.4 Denote the value of textile and apparel exports to the US and EU as X , and GDP as Y. TU Then this ratio can be expanded as follows: X /Y = (X /X )*(X /X)*(X/Y) TU TU U U The ratio breaks into three components. • The first component (X /X ) is the ratio of textiles and clothing exports to the TU U US and EU to total exports to the two regions. It indicates the importance of textiles and apparel exports for the export performance of the regions by the country. • The second component (X /X) is the ratio of exports to these two regions to total U exports by the country. Larger values of this ratio represent more concentrated and specialized export profiles for the country. • The third component (X/Y) measures the ratio of total exports to total GDP for the country. It indicates the degree to which exports are relied upon as a source of demand for domestic production. An elevated value of any of these can be interpreted as a source of risk to the country when quotas are eliminated. Risk is not necessarily a bad thing in this instance: heightened risk indicates simply that there is a greater potential for large swings in exports, and thus economic growth, in the exporting country. That swing could be positive, leading to more rapid growth, or negative. The best analogy may be to diversification of a portfolio. When a country has low values of each of these components of risk, it is well-diversified with regard to the shock from removal of quotas. Larger values for each component indicate concentration: either in goods produced, in trading partner, or in reliance on exports for growth. Such 4 The EU is defined in this paper as the EU-15. It does not include the accession countries. Removal of Quotas on Textiles and Apparel - 6 concentration will magnify gains and/or losses incurred with the removal of the quota system. Concentration in exports of textiles and apparel. The first source of risk comes from heavy reliance upon textiles and apparel sales among total exports to the quota-imposing countries. As an indicator of this reliance, I examine the ratio of the value of textiles and apparel exports to total exports to the US and EU in 2004. Those countries for whom textiles and apparel exports represent at least 30 percent of total exports to these two regions are listed in Table 1 with their values of (X /X ). These 34 TU U countries are typically small economies, and their residents had identified export niches within textiles and apparel that were apparently not available in other sectors.5 The countries are ranked by the weighted average of concentration ratios. Some (like Cambodia or Bangladesh) are strongly specialized in their trade with both the US and the EU, while others specialize with regard to one but not the other. Laos, for example, specializes in textiles and apparel for the EU market, but less so for the US; the Maldives Islands specializes in the US market, but not for the EU. Concentration in exports to the US and EU. The second source of risk arises with reliance upon the US and EU markets as a destination for exports. In Table 2 I report the ratio (X /X) for countries with values greater than 40 percent. The table U includes countries from all geographical regions, and underscores the importance of the US and the EU as markets for the world’s goods. Those with highest values include disproportionately the countries of North and Central America that trade predominantly with the US, although the EU has its own specialized trading partners in Libya and Mauritania. Concentration on exports as a stimulus to GDP. The export-led growth strategy is acknowledged as quite successful in attaining rapid economic growth. It also, however, increases the dependence of domestic producers upon stable demand in the importing countries. If this demand is disturbed, the reliance on exports will translate into volatility in GDP growth rates. Table 3 lists those exporters with export/GDP ratios greater than 50 percent. For the EU members on the list the exports measured include exports to other EU members. “At risk” countries. The “at risk” countries can be summarized as in Table 4. The countries are ranked by multiplying the three risk components to obtain a risk score. Those most “at risk” are not the large exporters, as is evident by China’s position near the bottom of the first row. Rather, those most at risk are small countries with a disproportionately large share of the economy tied up in textiles and apparel exports to the US and EU. The Central American countries are prominent among the high scores. So also are other countries that have specialized in textiles and apparel exports within the structure of the quota system: Cambodia, Lesotho, Mauritius, Mongolia, Madagascar, the Maldives Islands and Jordan. 5 I have calculated the ratio for all 228 countries exporting to the US and EU, and will use all these values in later analysis. I present only the top 34 to illustrate the nature of the countries with high concentrations in textiles and apparel. Removal of Quotas on Textiles and Apparel - 7 Table 1: Countries with Textile and Apparel exports in excess of 30 percent of total exports to the US and EU-15 in 2004 Share in EU Share in US Country Exports Exports Combined Share Cambodia 86.75 95.64 92.69 Free St Micronesia 1.40 92.38 92.13 Lesotho 3.52 97.60 91.94 Laos 88.73 62.18 88.20 Bangladesh 87.56 89.09 88.02 Nepal 77.87 91.47 85.23 Mongolia 27.15 95.75 84.31 Haiti 14.19 85.18 82.10 Macao 56.37 96.29 80.87 El Salvador 4.34 83.24 76.61 Jordan 4.05 87.27 69.25 Mali 72.68 1.67 68.95 Maldives Islands 0.79 98.03 68.22 Sri Lanka 54.33 80.69 67.74 Kyrgyz Republic 68.03 61.23 65.91 Honduras 7.78 72.23 65.79 Pakistan 42.76 85.92 60.55 Guatemala 1.97 62.05 56.48 Nicaragua 1.96 60.06 54.35 Tajikistan 52.30 83.89 54.10 Mauritius 45.64 83.76 51.81 Brunei 1.98 64.82 51.56 Swaziland 3.40 89.88 49.85 Madagascar 29.97 68.61 45.70 Niue 3.75 70.04 42.16 Dominican Republic 1.98 45.35 40.63 Cape Verde Islands 31.12 81.53 40.22 Tunisia 39.95 21.70 39.51 Macedonia 35.94 55.80 37.45 Morocco 37.79 13.80 36.28 Bahrain 12.43 50.45 31.00 Burkina Faso 31.15 8.63 30.90 Vietnam 12.22 52.42 30.22 Turkey 29.46 35.48 30.18 Source: US International Trade Commission and Eurostat. The “Combined” column provides the average share of textiles and apparel in total trade with these two regions weighted for relative values of total trade. Removal of Quotas on Textiles and Apparel - 8 Table 2: Countries with more than 40 percent of exports to the US or EU-15. Share of exports to Share of exports to Exports to EU US combined Honduras 8.43 118.62 127.05 Liberia 45.53 49.18 94.73 Trinidad & Tobago 5.39 82.05 87.44 Lesotho 3.28 79.97 83.25 Guatemala 5.03 76.79 81.82 St Vincent & Grenadines 79.62 1.97 81.59 Mexico 2.62 76.44 79.06 Madagascar 37.59 40.32 77.91 Nicaragua 5.00 71.71 76.70 Haiti 2.10 72.48 74.58 Libya 72.09 2.02 74.11 Canada 3.34 67.45 70.79 Cambodia 16.78 52.88 69.66 Congo (ROC) 13.50 54.82 68.33 Costa Rica 28.41 39.76 68.18 Gabon 10.08 54.83 64.91 Venezuela 4.11 60.39 64.50 Mauritania 60.80 1.63 62.43 Bangladesh 36.70 24.94 61.64 Aruba 6.00 53.30 59.29 Ecuador 10.39 47.69 58.08 Algeria 35.57 20.23 55.80 Namibia 41.70 13.68 55.38 Nigeria 11.09 43.25 54.34 Dominican Republic 3.82 48.86 52.67 Colombia 12.12 38.45 50.57 El Salvador 2.80 47.73 50.54 Suriname 23.92 25.62 49.54 Guinea 38.70 8.53 47.23 Central African Republic 40.43 5.84 46.28 Sierra Leone 41.06 4.91 45.97 China 14.81 30.71 45.52 Norway 39.47 5.91 45.38 Romania 41.64 3.45 45.10 Tunisia 43.20 1.69 44.89 Cameroon 35.55 8.92 44.47 Iceland 36.30 7.29 43.59 Sri Lanka 16.61 26.87 43.49 Mozambique 42.04 0.63 42.67 Bahamas 16.04 26.31 42.35 Burundi 33.82 8.27 42.09 Israel 12.92 28.81 41.74 Botswana 39.77 1.91 41.68 St Kitts-Nevis 6.35 34.48 40.83 Chad 8.38 32.07 40.45 Source: US International Trade Commission (Exports to US), Eurostat (Exports to EU-15) and World Development Indicators (Total exports from the Balance of Payments). The data should be interpreted carefully, especially that for Honduras and Liberia. (Exports from Liberia to EU-15 divided by 10). Removal of Quotas on Textiles and Apparel - 9 Table 3: The ratio of exports to GDP: countries above 50 percent Trading partner X/GDP Singapore 157.8 Malaysia 121.3 Mali 114.3 Maldives Islands 98.0 Malta 85.2 Slovak Republic 83.8 Thailand 83.5 Swaziland 83.1 Congo (ROC) 82.5 Belgium 82.2 Bahrain 79.8 Hong Kong 78.5 Spain 78.0 Belarus 77.4 Estonia 76.2 Seychelles 73.0 Angola 71.3 Saudi Arabia 70.0 Gabon 69.0 Cambodia 67.7 Turkmenistan 65.7 Mongolia 65.1 Hungary 64.9 Tajikistan 64.9 Panama 64.0 Czech Republic 62.8 Djibouti 62.8 Kuwait 60.9 Trinidad & Tobago 60.2 Taiwan 60.0 Bulgaria 57.7 Oman 55.9 St Lucia Is 55.7 Sweden 55.7 Lithuania 55.0 Mauritius 54.4 Belize 53.5 Chad 53.2 Ukraine 53.2 Vanuatu 53.0 Philippines 52.0 Dominican Republic 51.9 Austria 51.8 Source: World Development Indicators. When 2004 data were unavailable, 2003 data were used. Removal of Quotas on Textiles and Apparel - 10 Table 4: Risk from Removal of the Quota System Risk Risk Risk Country Index Country Index Country Index Cambodia 496299 Hong Kong 15901 Ethiopia 1136 Honduras 307363 Egypt 15136 Togo 1129 Lesotho 305254 Uzbekistan 14220 Ecuador 1071 Mauritius 138855 Malawi 13935 Liberia 1010 Haiti 136902 India 13182 Paraguay 992 Mongolia 135192 Hungary 12545 Australia 991 Madagascar 128407 Bosnia 12155 Gambia 881 Sri Lanka 126577 Belarus 11645 Guinea-Bissau 827 Tunisia 119756 Mexico 11623 Azerbaijan 820 Maldives Is 118619 Peru 10812 Argentina 804 Dominican Rep 111375 Malaysia 10251 Burundi 769 El Salvador 102245 Slovenia 9932 Russia 746 Bangladesh 101472 Kyrgyz Republic 9459 Mauritania 716 Nicaragua 96851 Armenia 8797 Kazakhstan 689 Jordan 89263 Ukraine 8654 Dominica Is 687 Guatemala 81412 Cape Verde 8495 Iceland 655 Swaziland 79911 Serbia 7455 Comoros 649 Laos 73190 Chad 7245 Senegal 643 Romania 71398 Colombia 6698 Kuwait 618 Macedonia 68268 Oman 6473 New Zealand 557 Bulgaria 66916 Bolivia 5691 Lebanon 544 Morocco 64531 St Lucia Is 5370 Nigeria 528 Moldova 63816 Switzerland 5033 Japan 466 Pakistan 50572 Israel 4807 Chile 444 Mali 43982 Poland 4685 Guinea 305 Tajikistan 39505 Cen African Re 3942 Saudi Arabia 283 Vietnam 37365 Samoa 3760 Sao Tome & Pri 243 Turkey 36974 Botswana 3511 Norway 239 Malta 34593 Korea 3385 Niger 207 Lithuania 32991 Burkina Faso 3343 Panama 180 Nepal 30781 Cyprus 3317 Angola 140 Costa Rica 28858 Mozambique 3036 Barbados 139 Philippines 28317 Canada 2691 Grenada Is 114 Bahrain 27212 Singapore 2474 Yemen 95 Estonia 25236 Sierra Leone 2438 Trinidad & Tobago 88 Thailand 25176 Zambia 2164 Suriname 61 Kenya 20456 Cameroon 2151 Seychelles 51 Albania 19631 Iran 2012 St Vinc & Gren 49 Slovak Rep 19117 Tanzania 1898 Gabon 43 Jamaica 18872 Uruguay 1828 Venezuela 33 Belize 18539 Guyana 1729 Eritrea 31 China 18232 South Africa 1626 Papua New Guin 20 Latvia 17951 Benin 1442 St Kitts-Nevis 20 Namibia 17896 Cote d'Ivoire 1338 Rwanda 16 Indonesia 17532 Georgia 1331 Algeria 13 Turkmenistan 17223 Brazil 1321 Congo (ROC) 8 Croatia 16394 Sudan 1262 West Bank/Gaza 0 Syria 16179 Uganda 1259 Vanuatu 0 Czech Republic 15908 Ghana 1153 Source: Author’s calculations. Maximum possible value: 1 million.