__ PSE1 POLICY RESEARCH WORKING PAPER 2689 Global Trade How food safety is addressed in the world trade system is and Food Safety critical for developing countries that continue to rely Winners and Losers on agricultural exports. An analysis shows that adopting in a Fragmented System a worldwide standard for a toxin affecting nuts and Jobn S. Wilson grains could increase trade in Tsunebiro Otsuki these commodities by S38 billion compared with levels under today's widely divergent national standards. The World Bank Development Research Group Trade H October 2001 POLICY RESEARCH WORKING PAPER 2689 Summary findings Food safety standards and the tradeoff between these importing countries (including 4 devel )ping countries) standards and agricultural export growth are at the on exports from 31 countries (21 of them developing). forefront of the trade policy debate. How food safety is Aflatoxin is a natural substance that ca-i contaminate addressed in the world trade system is critical for certain nuts and grains when storage arid drving facilities developing countries that continue to rely on agricultural are inadequate. exports. In a fragmented system of conflicting national The analysis shows that adopting a worldwide food safety standards and no globally accepted standards, standard for aflatoxin BI (potentially tie most toxic of export prospects for the least developed countries can be aflatoxins) based on current international guidelines severely limited. would increase nut and cereal trade among the countries Wilson and Otsuki examine the impact that adopting studied by $6.1 billion compared with 1998 levels. This international food safety standards and harmonizing harmonization of standards would incr ase world standards would have on global food trade patterns. exports by $38.8 billion. They estimate the effect of aflatoxin standards in 15 This paper-a product of Trade, Development Research Group-is part of a larger effort in the group to expand empirical and policy understanding of the [ink between trade, development, and standards. Copies of the paper are available free from the World Bank, 1818 H Street NW, Washington, DC 20433. Please contact Lili Tabada, room MC3-333, telephone 202-473-6896, fax 202-522-1159, email address ltabadafilworldbank.org. Policy Research Working Papers are also posted on the Web at http://econ.worldbank.org. The authors may be contacted at jswilsonOv orldbank.org or totsuki(cworldbank.org. October 2001. (34 pages) 7Te Policy Research WVorking Paper Series dissemninates the fintdinigs of work in progress to encourage the exchange ( f ideas aboult dev,elopment issues. An objective of the series is to get the findings out quickly, even if the presentations are less tha7 fTll-, polished. The papers carry the names of the authors and should be cited accordingly. The findinsgs, interpretations, and conclusions expressed in this paper are entirely those of the authors. 'They do not necessarily represent the view of the World Bank, its Executive Di,ectors. or the countries they represent. Produced by the Policy Research Dissemination Center Global Trade and Food Safety: Winners and Losers in a Fragmented System John S. Wilsona Tsunehiro Otsuki *,b abDevelopment Research Group (DECRG), The World Bank 1818 H Street NW, Washington DC 20433, USA JEL Classification: F14, Q17 ,b Corresponding author. E-mail address: totsuki(a)worldbank.ora (Tsunehiro Otsuki). Copyright 2001 by John S. Wilson and Tsunehiro Otsuki. All rights reserved. Readers may make verbatim copies of this document for non-commercial purposes by any means, provided that this copyright notice appears on all such copies. The authors are grateful for the useful comments from attendants at the World Bank trade seminar on July 10, 2001. The authors are also grateful for assistance provided by Baishali Majumdar and Robert Simms. I. Introduction The need to understand more precisely how food safety regulations affect trade is being driven, to a great extent, as a function of challenges in meeting the Agreement on the Application of Sanitary and Phytosanitary Standards (the "SPS Agreement") of the World Trade Organization (WTO). The SPS Agreement sets general guidelines under which trade in agricultural products is conducted to ensure standards are based on sound science, and does not arbitrarily discriminate or restrict trade. The WTO rules do allow members to set domestic standards at any level they deem appropriate, however, governments are encouraged to use international standards-where they exist. The WTO disciplines suggest, therefore, that harmonization and equivalence are the preferred methods of ensuring non-discrimination. A fragmented system of unilateral action on food safety standards is counter to both general WTO principles, and economically inefficient due to high transaction costs for exporters and global consumers. Although there is only limited empirical data in this field, it is assumed that developing countries are most directly affected by a fragmented system in which firms must meet differing standards for multiple export markets. In the food trade, the Codex Alimentarius Commission (Codex) plays a central role in setting internationally acceptable standards. While governments through Codex have made progress in crafting harmonized standards in some areas, through the Commission consensus on key international food safety standards is lacking while national standards proliferate. Since regulatory requirements and product standards are substantially different across countries, typically between developed and developing 2 countries (World Bank, 2001), trade disputes in a non-harmonized system are inevitable.I The rising number of notifications to the WTO from developed and developing countries about national sanitary and phytosanitary standards (a 26 percent increase from 1995 to 1998) reflects this fact. Understanding the trade impact of these differing standards, therefore, is of significant importance and an area of key public policy concern as options to expand trade in agricultural products are examined. This paper analyzes how global trade patterns in selected food products will change when differing levels of aflatoxin B1 standard are assumed. Aflatoxins are a group of toxic substances that can contaminate certain foods. There is evidence that aflatoxin B 1 contamination is linked to liver cancer. The analysis here extends Otsuki et al. (2001b) by broadening the country coverage from Africa to a global scope, and by explicitly examining how imports and exports differ under various regulatory scenarios. The paper examines trade among 15 importing (4 developing) countries and 31 (21 developing) exporting countries in the world. All of these countries are WTO members except for Russia, Kazakhstan, and Vietnam. These three countries are, however, observers. The paper is organized as follows. Section II reviews the concepts and debates over food safety regulations in general in the world food trade. Section III reviews issues related to aflatoxin regulations and world food trade. Section IV develops the empirical methodology to estimate the effect of aflatoxin regulations on bilateral trade flows. ' One example of the widely different approach to standards and food safety among trading partners is the new European Union (EU) maximum allowable level of aflatoxins in cereals, dried and preserved fruits and nut imports. This regulation, set for implementation in April 2002, has generated concern among exporting countries, many of them developing countries. Among the countries expressing concerns over the new EU standards were Argentina, Australia, Brazil, Canada, Colombia, India, Indonesia, Malaysia, Mexico, the Philippines, Senegal, South Africa, Thailand, Turkey, Uruguay and the US (1998, CRC Press LLC). 3 Section V then reports the results, and Section VI concludes and discusses the policy implications. II. World Food Safety Regulations and Trade Food safety regulations are mandatory controls over the quality attributes of a final product, based on the potential effects on human health from food handling, preparation, or consumption (Hooker 1999). The growing prominence of food safety controls in the public policy debate is based on both scientific and economic grounds (Henson and Caswell 1999). The role of science in forming food safety regulations includes the assessment of risk of food related hazards, the management of risk at a socially acceptable level, and the release of information about risk to the public. The economic basis for food safety regulation emerges out of the concept of a "socially optimum" level of risk at which the marginal costs of food safety regulations equal their marginal benefits to the society. What about trade rules and food safety? The WTO Sanitary and Phytosanitary (SPS) Agreement disciplines play an important role in promoting harmonization of food safety standards. The Agreement was entered into force as part of the Uruguay Round Agreements in January, 1995. The overall goal of the Agreement is to ensure transparency and non-discrimination in how governments can apply food safety, animal, and plant health regulations. SPS measures also address issues relating to market failures involved with imperfect information on food safety that can arise when consumers cannot pay for desired levels of safety and/or producers fail to supply improved food safety (IATRC 2001). 4 Disputes related to SPS measures are often based on questions of (1) whether a food safety standard is based on sound scientific principles, (2) whether there is discrimination between treatment of domestic and foreign producers, and (3) whether the regulation in place is appropriate to mitigate against risk to public health and least trade distorting. The International Agricultural Trade Research Consortium (IATRC)( 2001) outlines three disputes that have challenged the use of science as a ground for food safety measures. The first case is where the U.S. and Canada challenged the scientific basis for the European Union(EU) ban on growth hormones in beef production. The second dispute challenged by the U.S. was regarding Japanese testing requirements regarding treatment effectiveness for new varieties of selected horticultural products. In the third case, Canada challenged Australia's ban on salmon imports to prevent the spread of fish diseases. Food safety measures may have different implications in terms of the welfare effects in different countries depending on the differences in risk perceptions, available market information, the incidence of risk in production, and traditional methods of food processing and preparation as noted by IATRC (2001). The benefits of food safety regulation are reductions in risks of morbidity and mortality associated with the consumption of contamninated food (Antle, 1999). The costs of food safety regulation include the cost of production, the compliance cost, the administrative cost borne by the taxpayers, and the deadweight loss associated with taxation (Antle). Petrey and Johnson (1993), Ndayisenga and Kinsey (1994), and Thilmany and Barrett (1997) illustrate the case where food safety regulations impede trade. DeRemer (1997) and Thornsbury et al.(1997) estimated the total impact of technical barriers on 5 U.S. exports of agricultural products, and it was $4,907 million in 1996, or 90 percent of which was due to sanitary and phytosanitary measures. The impact of food safety measures was estimated to be around $2,288 million. According to Henson and Caswell (1999), several international standards organizations, such as Codex, the International Plant Protection Convention (IPPC), and the International Office of Epizotics (OIE) have attempted to harmonize food safety regulations. Codex has designed a food code, particularly to serve as a global food treaty that can promote and protect SPS standards. The WTO is a proponent of using this food code to resolve scientific disputes. According to Henson and Caswell (1999), there are two approaches through which national food safety regulations can be justified. First, is the adoption of international standards that are assumed to comply with the provision of SPS agreement. Second, is the assessment of the risks to human health, plants and animal life, as per food safety regulations. -II. The Regulation of Aflatoxins The regulation of aflatoxins in food products has gained considerable attention in recent years. Aflatoxins are a group of structurally related toxic compounds that contaminate certain foods and have been associated with acute liver carcinogens in humans. The different types of poisonous aflatoxins found in food are B1, B2, GI and G2 (UNDP-FAO, 2000). Aflatoxin Bl is the most toxic and common aflatoxin. It is generally present in corn and corn products, groundnuts and groundnut products, cottonseed milk, and tree nuts, e.g. Brazil nuts, pecans, pistachio nuts, and walnuts (FAO- WHO,1997). In 1997, a Joint FAO/WHO Expert Committee on Food Additives 6 (JECFA) estimated that reducing the aflatoxin standard from 20 ppb (part per billion) to 10 ppb will decrease 2 cancer deaths a year per billion people. In 1997, the European Commission (EC) proposed a harmonization of maximum acceptable level of aflatoxins in certain foodstuffs. The standard ranged from 4ppb in cereals, edible nuts, and dried fruit, to lOppb for nuts that are subject to further processing. Henson et al. (2000) noted that the EC proposal had led to concern among food exporters about the new and more restrictive standards' effect on trade patterns. Several exporting countries feared losses in their exports as a result of the more restrictive standard. Countries such as Bolivia, Brazil, Peru, India, Argentina, Canada, Mexico, Uruguay, Australia, and Pakistan requested detailed risk assessments from the European Union used in designing the new standard. As a consequence of consultations with their trading partners about these concerns, the European Commission relaxed the proposed aflatoxin standard in cereals, dried fruits, and nuts. The revised aflatoxin standard in groundnuts subject to further processing was set at 15 ppb (8 ppb for Bi) and 10 ppb (5 ppb for Bi) for other nuts and dried fruits subject to further processing. For cereals, dried fruits, and nuts intended for direct human consumption, the standard was much more stringent and was set at 4 ppb (2 ppb for B 1).2 The aflatoxin standards suggested by Codex is significantly more relaxed than the EU standards. While Codex does set a standard specifically for B1 group of aflatoxin, it assumes that 50-70 percent or around 7.5-10.5 ppb of the total aflatoxin level of 15 ppb is caused by aflatoxin B 1. The overall Codex standard, therefore, is approximately 9ppb. 2Otsuki, Wilson and Sewadeh (2001 a) provide a more detailed discussion of aflatoxin standards. 7 Otsuki et al. (2001b) find that the implementation of the new aflatoxin standard by the European Commission will have an adverse effect on African exports of cereals, dried fruits, and edible nuts to Europe. The results for 9 African and 15 European countries show that as the maximum allowable level of aflatoxin B1 is lowered by 1 percent, exports of cereals from Africa to Europe decreases by 1. 1 percent and the drop is 0.43 percent for fruits, nuts and vegetables. Groundnuts are most significantly affected by aflatoxin standards with a 1.3 percent decrease in exports. Results suggest that the aflatoxin standards proposed by the European Commission are far more stringent than the guidelines set by Codex when considering reduced exports. The total loss of export revenue for the 9 African countries in the study is estimated to be US $400 under EU standards, compared to a gain of US $670 million if standards were adopted according to Codex guidelines. IV. An Econometric Model to Examine Trade and Food Safety Standards When a measure of stringency of standards is available, an econometric approach has an advantage in measuring the statistical relationship between standards and trade flow, without prior imposition of the sign of the effect. It is also useful for examining policy implications once the relationship is estimated. Swann et al. (1996), Blind and Jungmittag (1999), Moenius (2000), Otsuki et al. (2001a), and Otsuki et al. (2001b), employed an econometric model where trade flows were regressed on a proxy for standards along with other factors that promote or divert trade. Swann et al. and Blind and Jungmittag regressed import and export on the stock of standards. Using a gravity model, Moenius regressed bilateral trade flow on the stock of standards along with Gross 8 National Product (GNP) and population, and geographical distance between variables countries. A gravity model is used to explain bilateral trade flows using key economic variables that represent the size of a country's economy, such as Gross National Product (GNP) and population, and geographical distance between variable countries. WAhen combined with data on food safety standards in importing countries, bilateral trade flow data allows analysis of how differing standards promote or limit trade between pairs of importing and exporting countries. Our specification of gravity model is as follows: In V, = bo + b1 In GNPPCj + b2 ln GNPPCj + b3 ln DIST,, + b4 In STj + b5Dcol + b6DEII + b7DASEAN + b8 DNAA + b9D,ERCOSUR + 6u VY, denotes the value of trade from country j to country i. It is obtained from the trade data of the United Nations Statistical Office. Products that are included in this analysis include wheat (SITC041), rice (SITC042), maize (SITC044), dried and preserved fruits (SITC052), and nuts (SITC05171 and 05172). We use data for the time period between 1995 and 1998. Parameter b's are coefficients, and c k is the error term that is assumed to be normally distributed with mean zero. GNPPCi and GNPPJQ are real per-capita GNP of importing country i and exporting country j in 1995 U.S. dollars, respectively. DIST is the geographical distance between country i andj. STi is the maximum level of Aflatoxin BI imposed on imports by the importing country, i. It is expressed as Aflatoxin B1 contamination in parts per billion, and is obtained from FAO survey of mycotoxin standards on food and feedstuffs in 1995 (FAO, 9 1995). Table I depicts the Aflatoxin B1 standards for the importing countries in our sample. A greater value of this variable implies a more lax regulation of Aflatoxin B1 contamination, and vice versa. If this standard is applied at the border, products with Aflatoxin B 1 contamination equal to or below ST would successfully enter the importing country. Products with Aflatoxin Bl contamination above ST are retained in the exporting country, or rejected at the importing country's border. In this respect, a country that exports food products to more than one country faces different aflatoxin standards. Positive trade flows in COMTRADE data recorded from country to country with different standards imply that countries export food products with differing levels of aflatoxin contamination. Under the fragmented system of standard setting, aflatoxin standards for food safety tend to be heterogeneous within a given exporting country (e.g. there are production and distribution channels that satisfy different aflatoxin standards). The standards of exporting countries, therefore, do not necessarily measure minimum level of aflatoxin contamination in their exports. The coefficient for this variable in our gravity model generally implies changes in exports associated with an incremental change (relaxation or tightening) in ST. If this standard does limit trade, then this coefficient is expected to be positive. A dummy variable for colonial ties is included in order to control the omitted variable effect of colonial ties on trade flow as used in Otsuki et al. (2001a, 2001b). It takes the value of one if a colonial tie exists between a given set of importing and exporting countries, and zero, otherwise. Dummy variables for the free trade area (FTA) are included for a similar reason, as preferential treatment of exporting countries in a 10 FTA member is likely to have a trade-promoting effect (Soloaga and Winters, 1999). The terms DEU, DASSA4, DNAFTA and DM,ERCoSUR denote the dummies for European Union, ASEAN, NAFTA and MERCOSUR, respectively. Dummy variables for the year also are included in the model, in order to control for systematic differences across time. V. Results Separate regressions are run for three product groups, cereals, nut products and dried and preserved fruits using an fixed-effects model. Following the models developed by Otsuki et al. (2001a, 2001b), a panel is formed, with respect to exporting countries whose unobserved characteristics that are country-specific, may cause systematic variation. Results are reported in Table 2.3 The results generally supports the conclusion that the gravity model is well suited to examine all product groups in the analysis. The coefficients for distance are negative and are significant for all of the product groups. The coefficients for per-capita GNP in importing countries are positive and significant for all of the product groups. The results for per-capita GNP are not predictable in prior due to two counteractive effects, domestic absorption and the scale effect on production. We find that aflatoxin B 1 standards in importing countries have a negative effect on trade flows in the cereals and nuts regression. The impact of the standard is insignificant in the dried and preserved fruits regression. The first two results are consistent with the findings in Otsuki et al. (2001b). When global trade is examined in 3The results were examined for robustness of variances using WLS. The fixed-effects model result is found to be robust against heteroscedasticity of the standard error. 11 cereals and nuts, we find that a more stringent standard tends to limit trade. The results for dried and preserved fruits indicates, however, that the negative effect of the aflatoxin standard cannot be generalized globally. The EU dummy is found to be positive and significant for all of the product groups. The Mercosur dummy is found to be positive and significant for cereals and dried and preserved fruits, but is insignificant for cereals. The results for the other FTA dummies do not show a strong support for the trade-promoting effect of a FTA. Simulation Exercises Under Various Scenarios In this section, we predict how trade patterns change, as aflatoxin B1 standards are harmonized at varying levels. We make the following assumptions prior to conducting the simulation analysis. The first relates to the effect of an exporting country's standard on its exports. We do not have data on exporting country standards in all of the cases. Importing and exporting countries are treated independently, therefore, such that an assumed level of aflatoxin B 1 standard of a country as an importer does not imply the level of maximum aflatoxin B1 contamination of its exports of the same product. The fixed-effects model coefficient estimates on the standard variable are used to predict changes in trade flows associated with different levels of aflatoxin B I standards.4 Figure 1 presents the simulated relationship between aflatoxin standards and total trade flows between the 31 exporting countries and 15 importing countries. 4 See Otsuki et al (200 la) for a detailed description of the methodology. 12 One important observation is the total trade flow under different levels of harrnonization. Table 3 highlights the gains and losses for the trade flow of cereals and nuts at, (1) the Codex Standard, (2) EU harmonizing at 2 ppb and (3), the harmonized level of 2 ppb for all nations compared to the break even point where the sums of losses and gains from a harmonized standard are equal. This break-even point provides a zero- sum condition on the changes in the value of exports across the exporting countries. The Codex standard at 9 ppb being more lax than the standard at break even point (5.1 ppb for cereals and 4.1 ppb for nuts), increases the total trade flow of cereals and nuts by $6140 million. On the other hand, the stringency of EU standard at 2 ppb reduces the trade flow by $6050 million. The loss in trade flow is significantly less ($995 million) when only EU harmonizes at 2ppb while the rest of the countries maintain their status quo level i.e. standards remain unchanged from the 1998 level. The other interesting issue would be to do a country level analysis that compares trade flow for all the exporters under a different level of standard. This paper presents five different scenarios to highlight this issue. Scenario One: The first scenario compares (1) the value of exports when Europe adopts it new standard of 2 ppb in 2002 with all other countries' standards unchanged from their 1998 levels, and (2) all importing countries standards remain unchanged from their 1998 levels. This comparison shows how trade will change after Europe implements its new standard in 2002 for 31 exporting countries. The results are reported in Table 4. They suggest that the value of exports under case (1) is US $ 995 million (8.3 percent) less compared to the case (2). Hungary, Israel and Brazil are found to be gainers from the EU harmonized standard. Their largest 13 trading partner of cereals and nuts is Austria, which had a I ppb standard prior to the harmonization. The other importing countries in the exercise are all expected to decrease exports . Scenario Two: In this case, the comparison is between (1) all importing countries adopting a standard of 2ppb and (2) Europe implements its 2ppb standard and all other countries stay at 1998 levels of regulatory stringency. As shown in Table 5 the value of exports under case (1) is US$ 5.1 billion (46 percent) lower when compared to case (2). This implies that trade becomes much more restricted when all importers adopt the EU harmonized standard. While there is not an obvious pattern of distribution of gainers and losers in scenario 1, scenario 2 shows a clear contrast in the difference between developed and developing countries. The global harmonization at 2 ppb generates more loss for non- OECD countries than OECD countries. This is because the change in standards in non- OECD importing countries is more drastic than that in OECD countries given standards are less stringent in non-OECD today. Non-OECD countries that export primarily to other non-OECD countries tend to lose from a world wide harmonization of standards at 2ppb. Scenario Three: The third scenario compares (1) a harmonization under a break- even condition where the sums of loss and gains from a harmonized standard are equal and (2) all importing countries standards remain unchanged from their 1998 levels. As Table 6 indicates, the majority of non-OECD exporting countries are losers whereas OECD countries are primarily gainers in this scenario. The OECD member countries are estimated to gain by US$ 536 million or 7.7 percent of the total exports from the OECD 14 member countries in the sample. In contrast, the non-OECD countries are estimated to lose by US$ 502 million or 10 percent of the total exports from the non OECD countries in the sample. Scenario Four: In this case, we examine trade flow when (1) all countries adopt an international standard of 9ppb in contrast to (2) all importing countries remaining at 1998 standards. Harmonization at the Codex level is estimated to increase the value of cereal and nut exports by US$ 6.1 billion or 51 percent of the status-quo level of 1998. The results reported in Table 7 indicates that the value of exports under the case (1) generates US$ 6 billion more than the case (2). In this scenario the EU countries e.g. France, Denmark and the Netherlands gain as a result of Codex standard. This is because these countries trade with other EU countries such as Germany and U.K which have relatively stringent standard currently. When the standards are relaxed to the Codex standard at 9 ppb, these countries experience an increase in trade flows. In contrast, developing countries such as Pakistan, Vietnam and Thailand exhibit a trade loss as a consequence of adopting the Codex standard. Scenario Five: In this exercise we compare the case where (1) all the importing countries adopting a standard of 2ppb and (2) harmonization of standards by all countries at 9ppb. The results in Table 7 suggest that harmonization at the-2-ppb level across all the importing countries will result in US$ 12.2 billion or 67 percent decrease in cereal and nut exports. Some of the losing exporters under case (1) i.e. at 2ppb are Thailand, Uruguay and Paraguay.. As we expect when the standards reach the stringency level of 2 ppb from the Codex standard, all the countries experience a loss in trade flows. Results are depicted in table 8. 15 Combined with the result in Table 5, the case (2) will result in $US 7.1 billion (64 percent) more exports than the case where only EU harmonizes standard at 2 ppb leaving other importing countries unchanged their standards. In sum, the country-level analysis indicates that the value of exports from EU countries are relatively unaffected by the EU harmonized standard whereas developing countries are mostly losers from the harmonization. In the final simulation, changes in value of trade flow are computed for each importing and exporting country. The trading partner within the sample countries which account for the largest gain and loss of trade flow is then identified. Table 9 and 10 contain all the results. Table 9 presents the result for importing countries. The highest gain is experienced by U.K. with an estimated increase of 718.7 thousand, accounting for 45 percent of the total positive change in trade flow. Countries that increase imports from the harmonization at the break-even point level are UK, Germany, Austria, Brazil, France, Australia, Spain, Italy and Israel. However, among them three EU countries UK, Germany and Austria constitute for more than 90 percent of the gains. This reinstates the fact that EU countries have had the most stringent standard in the world and thus they are better off when standards are relaxed to 5.1 for cereals and 4.7 forniiuts at the break even point. France is the major exporting partner to most of the EU importing countries. The harmonization thus will tend to increase intra-regional trade in EU or industrialized countries in general. India suffers the biggest loss in imports, with Thailand as its trading partner whose trade flow will decrease the most. This result confirms that India has the most lax standards (30 ppb) of all the importing countries in the sample. 16 Table 10 shows the result of the same exercise for the exporting countries. The result indicates that France increases exports accounting for 71.6 percent of the total positive gain. The six EU countries (France, Italy, Netherlands, Germany, Spain and Hungary) account for more than 95 percent of gains in exports. Their trading partners gaining from the harmonization are also EU countries, Germany, UK and Austria. This also confirms that the harmonization at the break-even point will greatly increase intra- EU trade. It should be noted that the trading partners(i.e. the importers) of the gainers are the countries with very stringent aflatoxin standard. Hence it is obvious that harmonization at the break even point benefits the six EU countries, the gains coming from countries moving to relatively lax standard from very stringent standard. On the other hand, most developing countries lose exports as a result of harmonization. Countries like Canada, Mexico, Australia and Pakistan who feared losses due to the stringent standards set by EU (2 ppb), suffer a loss in exports even from harmonization at the break-even point. With stringent standard level at EU harmonization, some countries in table 10 (e.g. Israel, Egypt) with very small gains are likely to lose . It is interesting to note that developing countries like India and Nigeria gain as exporters as a result of harmonization even though as importers they lose. This is due to the separation assumption on the base model for simulation. The change in the value of exports and imports of these countries are computed as though they were different countries. Hence, it is possible that India and Nigeria have the EU countries as their trading partners and hence, gain as exporters as a result of relaxation of standard in the EU due to harmonization. USA and Canada will also decrease their exports due to the contraction of mutual trade since their standards are more lax than the break-even level. 17 Simulation results in table 10 shows that U.S. and Canada lose in exports as a consequence of harmonization at the break-even point. Authors' calculation based on the UN COMTRADE data records report that U.S. and Canada experienced a 5.6% decline in exports in the global market between 1995-1998 .5 Hence, it is reasonable to assume that harnonization of aflatoxin standard in general (may be different from the break even point level) will adversely affect U.S. and Canada as exporters. However, the effect of harmonization on European Union countries is imprecise. These countries experience a positive change in exports at the break-even point whereas UN COMTRADE data records show that there is a downward trend of 3.2% in exports for these countries between 1995-1998. Hence, the net effect of harmonization is hard to predict. On the other hand, the Asian, African and Latin American countries are found to have a positive trend in exports for the period 1995-1998. This positive growth is as high as 27% for the Asian countries. Consider Vietnam, Thailand, Sri Lanka and Pakistan as representative of the Asian sector. These countries who are actually suffering a loss in exports at the break even point might turn out to be gainers due to harmonization if this loss is offset by the positive trend in exports. The African and Latin American countries in our sample exhibit both positive and negative change in trade flow at the break even point. Hence, the net effect of harmonized aflatoxin standards on these countries is unclear at this point. VI. Conclusions This study examines the impact of adopting international food safety standards and harmonization of standards on global food trade patterns. The paper develops 5 Factors other than aflatoxin standard also affect this change in exports 18 econometric models and a simulation method to estimate the effect of aflatoxin standards in 15 importing (4 developing) countries on exports from 31 (21 developing) countries. The analysis extends Otsuki et al. (2001b) by broadening the country coverage from Africa to a global scope and by explicitly examining how imports and exports differ under various regulatory scenarios. Our analysis uses the first stage estimates of the elasticity of bilateral trade flows in certain foods with respect to the Aflatoxin B1 standard. The findings support those in Otsuki et al. (2001b) which show that the value of trade in cereals and nuts is negatively affected by aflatoxin B1 standard and that this negative relationship is not apparent in the case of dried and preserved fruits trade. The results in this analysis are combined to predict how the direction of trade is altered by food safety regulations under alternative scenarios. We find that adopting an international standard for aflatoxin BI based on current Codex guidelines will increase cereal and nut trade among countries in the exercise by $US 6.1 billion, or 51 percent from the 1998 levels. It is $US 12.2 billion or 67 percent more than the value of exports under the case where all 15 importing countries harmonize their standards at the 2 ppb level. Moreover, we estimate that world exports would rise by $38.8 billion if an international standard (Codex) were adopted, compared to the currieit divergent national standards in place. Exports are estimated to decrease by $3.1 billion if the world adopted the EU standard (i.e. 2 ppb) compared to current national standards. Harmonization of this food safety standard at a level more stringent than one suggested by intemational standards indicates that food safety standards can severely limit developing country exports. This analysis reveals, moreover, the trade impact of a 19 fragmented food safety system in which national regulations differ across trading partners. An initiative to encourage international standards, along with mechanisms to directly assist developing countries in raising standards to international levels merits serious consideration. In this specific case of aflatoxin standards, one might consider programs to provide vaccination against hepatitis B to lower risk of liver cancer (along with other serious health risks), encouraging the development of an international standard to be adopted worldwide, and aid to the least developed producers of agricultural commodities most affected by aflatoxin contaminations.6 6 For details on conclusions by JECFA regarding aflatoxin standards and risk see; John L. Herrman, World Health Organization, World Trade Organization, Presentation at the Risk Assessment Workshop, June 19- 20, 2000, http://www.wto.org/english/tratop_e/sps e/riskOO_e/riskOO e.htm#programme. 20 References Antle, John M. (1999). Benefits and Costs of Food Safety Regulation. Food Policy 24. 605-623. Blind, K. and A. Jungmittag (1999). The impacts of innovations and standards and German trade in general and on trade with the UK in particular. Internal Paper of Fraunhofer 2: 205-221. Committee on Sanitary and Phytosanitary Measures, World Trade Organization (1998). Submission by the Gambia. G/SPS/GEN/50, February 10, 1998. World Trade Organization, Geneva. European Commission (1997). Commission Regulation (EC) No. 194/97 of 31 of January 1997, The European Commission. European Commission (1998). Commission Regulation (EC) No. 1525/98 of 16 July 1998, European The Commission. FAO/WHO (Food and Agriculture Organisation and World Health Organisation) (1997). Acceptable Daily Intakes, Other Txicological Information, and Information on Specifications. Joint FAO/WHO Expert Committee on Food Additives, Rome, 17- 26 June 1997. Finger, Michael. J. and Phillip Schuler. (2000). Implementation of Uruguay Round Commitments: the Development Challenge. World Economy v23, n4: 511-25. Food and Agriculture Organization (1995). Worldwide Regulations for Micotoxins 1995: A Compendium. FAO, Rome. Hooker, Neal H. (1999). Food Safety Regulation and Trade in Food Products. Food Policy 24, 653-668. Hooker, Neal H. and Caswell, Julie A. (1995). Regulatory Targets and Regimes for Food Safety: A Comparison of North American and European Approaches. Food Marketing Policy Center, Department of Agricultural and Regource Economics, University of Connecticut. Henson, Spencer and Caswell, Julie A. (1999). Food Safety Regulation: An Overview of Contemporary Issues. Food Policy 24, 589-603. Moenius, J. (2000). Three Essays on Trade Barriers and Trade Volumes. Ph.D. Dissertation. University of California, San Diego Maskus, Keith. E. and John S. Wilson (2001). Technical Barriers to Trade: A Review of Past Attempts and the New Policy Context. In Maskus, K.E. and Wilson, J.S. 21 (Eds.) Quantifying Trade Effect of Technical Barriers: Can it be done? University of Michigan Press, Ann Arbor, MI. Maskus, Keith. E. and John S. Wilson, and Tsunehiro Otsuki (2001). An Empirical Framework for Analyzing Technical Regulations and Trade. In Maskus, K.E. and Wilson, J.S. (Eds.) Quantifying Trade Effect of Technical Barriers: Can it be done? University of Michigan Press, Ann Arbor, MI. Ndayisenga, F., Kinsey, J., (1994). The Structure of Non-Tariff Trade Measures on Agricultural Products in High Income Countries. Agribusiness 10 (4), 275-292. Orden, David and Donna Roberts (Eds.), 1997. Understanding Technical Barriers to Agriculture Trade, Proceedings of a Conference of the International Agricultural Trade Research Consortium, University of Minnesota, Departrnent of Applied Economics, St. Paul, MN. Otsuki, Tsunehiro, John S. Wilson, and Mirvat Sewadeh (200 la). What Price Precaution? European Harmonisation of Aflatoxin Regulations and African Groundnuts Exports. European Review of Agricultural Economics. Otsuki, Tsunehiro, John S. Wilson, and Mirvat Sewadeh (2001b). Saving Two in a Billion: Quantifying the Trade Effect of European Food Safety Standards on African exports. Food Policy. Petrey, L.A. and Johnson, R.W.M. (1993). Agriculture in the Uruguay Round: Sanitary and Phytosanitary Measures. Review of Marketing and Agricultural Economics 61,433-442. Roberts, D. and DeRemer, K. (1997). Technical Barriers to US Agricultural Exports. Economic Research Service, USDA, Washington, DC. Soloaga, I. and L. A. Winters (1999). How Has Regionalism in the 1990s Affected Trade. World Bank Policy Research Working Paper #2156. The World Bank. Washington, D.C. Swann, P., P. Temple, and M. Shurmer (1996). Standards and trade performance: The UK experience. Economic Joumal 106: 1297-1313. The International Agricultural Trade Research Consortium (2001). The Role of Product Attributes in The Agricultural Negotiations, Commissioned Paper # 17, May 2001. Thilmany, D.D., Barrett, C.B. (1997). Regulatory Barriers in an Integrating World Food Market. Review of Agricultural Economics 19 (1), 91-107. Thornsbury, S., Roberts, D., DeRemer, K., and Orden, D. (1997). A First Step in Understanding Technical Barriers to Agricultural Trade. Paper presented at the 22 Conference of the International Association of Agricultural Economists, Sacramento, August 1997. UNDP/FAO (1998). Regional Network Inter-Country Cooperation on Preharvest Technology and Quality Control of Food grains (REGNET) and the ASEAN Grain Postharvest Programme,Bangkok, Thailand. http://www.fao.org/inpholvlibrary/xO036e/xO036e00.htm. U.S. Food and Drug Administration (2000). Foodborne Pathogenic Microorganisms and Natural Toxins Handbook. http://vm.cfsan.fda.gov/-mow/chap4l.html Wilson, John S. (2000). The Development Challenge in Trade: Sanitary and Phytosanitary Standards. Paper submitted to WTO Meeting on Sanitary and Phytosanitary Standards June 19, World Trade Organization, Geneva. World Bank (2000). Global Economic Prospects 2001, Washington, DC 23 Figure 1. Estimated Relationship between Aflatoxin BI Standards and Trade Flow 20 - 18- 16- als 14 .2 12 10-/, D 8- 6- 4 - . . .Nt I on fo *- / 1inI Afaon I +,A(pb B erenak- Br1 eveak 01 20 25 30 L_ nuts fiorAflatoxinBl standardpb 24 Table 1. Aflatoxin B1 Standards followed by the Importing Countries Importer Standards for cereals and Standards for nuts (ppb) dried fruits (ppb) Australia 2.5 7.5 Austria I I Brazil 5 5 Canada 7.5 7.5 France 5 1 Germany 2 2 India 30 30 Israel 5 5 Italy 5 5 Japan 10 10 Malaysia 17.5 17.5 Nigeria 20 20 Spain 5 5 UK 2 2 USA 10 10 Source: FAO (1995) 25 Table 2. Fixed-Effects Model Regression Results (Dependent Variable = Value of Trade Flow) Cereals Nuts Dried/preserved Fruits Log of importer's 0.25*** 0.27*** 0.77*** GNP per capita (0.09) (0.09) (0. 1) Log of exporter's GNP 0.99** 0.55 2.90*** per capita (0.48) (0.5) (0.48) Log of distance -1.66*** -1.08*** -I 10*** (0.15) (0.14) (0.12) Log of standard 1.12*** 0.34*** 0.09 (0.13) (0.11) (0.11) Colonial tie dummy 2.44*** 1.84*** 1.8*** (0.92) (0.61) (0.51) Dummy for European 2.75*** 2.12*** 1.04*** Union Member (0.4) (0.38) (0.33) Dummy for Mercosur 3.76*** -0.96 3.9*** Member (0.85) (1.09) (0.97) Dummy for Asean -1.93 -0.35 2.23** Member (1.34) (1.17) (1.06) Dummy for NAFTA -2.60*** 0.70 1.03* Member (0.78) (0.7) (0.61) Time dummy for year 0.01 0.02 0.25 96 (0.23) (0.21) (0.19) Time dummy for year 0.09 0.20 -0.25 97 (0.23) (0.2) (0.19) Time dummy for year 0.19 0.03 -0.38* 98 (0.23) (0.21) (0.19) Adjusted R-squared 0.555 0.517 0.546 Number of 970 912 844 observations _ . 1. *, ** and *** imply significance at the 10 percent, 5 percent and 1 percent levels under a two-tailed test respectively. 2. Inside parentheses are standard errors. 26 Table 3. Predicted Value of Trade Flow under Alternative Regulatory Scenarios (US$ million) Cereals Nuts Total Flow Change /A % Flow Change IC % Flow Change F/E % (B) L (D) (F) Benchmark (A) 9117 0 0.0 (C) 284 0.0 (E) 1195 0 0. (No change) _ I Break-even 9117 0. 2840 0. 11957 0 0. Point Codex 9 ppb 14783 +5666 +62.1 3313 +473 +16.7 18096 +614 +51.3 EU harmoniz- 8108 -100 -11.1 2854 +1 +0.5 10962 -995 -8.3 ation 2 ppb _ _ __ _ _ All 2 ppb 3382 -5735 -62.9 2524 -31 11.1 5906 -605( -50. 27 Table 4: Scenario 1 Exporter EU 2ppb with the rest of Status Quo Change from % difference the importers status-quo Status Quo with status quo (US $1,000) (US$1,000) (US $1,000) Hungary 51825 46737 5088 10.89 Israel 7260 7176 84 1.17 Brazil 26270 26228 42 0.16 Paraguay 37269 37366 -97 -0.26 Uruguay 46849 47068 -219 -0.47 Sri Lanka 20067 20162 -95 -0.47 Argentina 3840299 3858778 -18479 -0.48 Tanzania 5837 5871 -34 -0.58 Vietnam 35028 35420 -392 -1.11 Pakistan 94809 96083 -1274 -1.33 India 184913 188000 -3087 -1.64 Egypt 2593 2645 -52 -1.97 Australia 138015 142713 -4698 -3.29 Thailand 623751 646472 -22721 -3.51 South Africa 22410 23250 -840 -3.61 Mexico 4635 4888 -253 -5.18 USA 3673428 3901735 -228307 -5.85 Zimbabwe 2598 2805 -207 -7.38 Nigeria 1531 1724 -193 -11.19 Canada 362278 415762 -53484 -12.86 Kazakhstan 13464 15722 -2258 -14.36 Russia 2449 2958 -509 -17.21 France 1020665 1261822 -241157 -19.11 Romania 6642 8216 -1574 -19.16 Spain 99084 128920 -29836 -23.14 Netherlands 121900 165978 -44078 -26.56 Italy 290317 439438 -149121 -33.93 Senegal 4739 7258 -2519 -34.71 Denmark 13133 21342 -8209 -38.46 Germany 192118 363257 -171139 -47.11 Austria 15869 30843 -14974 -48.55 Total 21924092 23913276 -1989184 -8.32 28 Table 5: Scenario 2 Exporter All importers 2ppb EU 2ppb with Change from EU % difference the rest of the 2 ppb with the rest with EU 2 ppb importers of the importers and the rest of status-quo status quo the importers status-quo (US $1,000) (US$1,000) (US $1,000) Netherlands 121376 121900 -524 -0.43 France 1012015 1020665 -8650 -0.85 Germany 190229 192118 -1889 -0.98 Spain 97327 99084 -1757 -177 Denmark 12853 13133 -280 -2.13 Austria 15522 15869 -347 -2.19 Italy 282161 290317 -8156 -2.81 Israel 6897 7260 -363 -5.00 Hungary 46576 51825 -5249 -10.13 Brazil 23535 26270 -2735 -10.41 Tanzania 4971 5837 -866 -14.84 India 142176 184913 -42737 -23.11 Nigeria 1114 1531 -417 -27.24 Egypt 1841 2593 -752 -29.00 Romania 4543 6642 -2099 -31.60 Mexico 3094 4635 -1541 -33.25 Sri Lanka 13246 20067 -6821 -33.99 South Africa 14762 22410 -7648 -34.13 USA 2394095 3673428 -1279333 -34.83 Kazakhstan 7920 13464 -5544 -41.1 8 Senegal 2703 4739 -2036 -42.96 Russia 1254 2449 -1195 -48.80 Zimbabwe 1060 2598 -1538 -59.20 Vietnam 12544 35028 -22484 -64.19 Paraguay 12177 37269 -25092 -67.33 Argentina 1253267 3840299 -2587032 -67.37 Uruguay 15287 46849 -31562 -67.37 Australia 41214 138015 -96801 -70.14 Canada 97333 362278 -264945 -73.13 Thailand 63760 623751 -559991 -89.78 Pakistan 9573 94809 -85236 -89.90 Total 5906424 10962047 -5055623 -46.12 29 Table 6: Scenario 3 Exporter Break -Even point Status Quo Change from % difference Status Quo with status quo (US $1,000) (US$1,000) (US $1,000) France 2124519 1261822 862697 68.37 Netherlands 250961 165978 84983 51.20 Hungary 66231 46737 19494 41.71 Denmark 29763 21342 8421 39.46 Italy 566311 439438 126873 28.87 Spain 164350 128920 35430 27.48 Austria 38430 30843 7587 24.60 Germany 434150 363257 70893 19.52 Israel 8551 7176 1375 19.16 Nigeria 1977 1724 253 14.68 Romania 8828 8216 612 7.45 Brazil 28169 26228 1941 7.40 Egypt 2833 2645 188 7.11 Tanzania 6234 5871 363 6.18 India 193889 188000 5889 3.13 Paraguay 37742 37366 376 1.01 Uruguay 47169 47068 101 0.21 Argentina 3864668 3858778 5890 0.15 Kazakhstan 15162 15722 -560 -3.56 South Africa 22029 23250 -1221 -5.25 Russia 2726 2958 -232 -7.84 Senegal 6405 7258 -853 -11.75 USA 3419356 3901735 -482379 -12.36 Mexico 4259 4888 -629 -12.87 SriLanka 16509 20162 -3653 -18.12 Zimbabwe 2255 2805 -550 -19.61 Canada 281076 415762 -134686 -32.39 Australia 79534 142713 -63179 -44.27 Vietnam 19278 35420 -16142 -45.57 Thailand 226445 646472 -420027 -64.97 Pakistan 21361 96083 -74722 -77.77 Total 11991170 11956637 34533 0.29 30 Table 7: Scenario 4 Exporter Codex Standard Status Quo Change from % difference Status Quo with status quo (US $1,000) (US$1,000) (US $1,000) France 2458854 1261822 1197032 94.87 Denmark 40883 21342 19541 91.56 Netherlands 317510 165978 151532 91.30 Austria 58441 30843 27598 89.48 Paraguay 70092 37366 32726 87.58 Germany 678527 363257 315270 86.79 Uruguay 87431 47068 40363 85.75 Argentina 7161983 . 3858778 3303205 85.60 Italy 806800 439438 367362 83.60 Hungary 85001 46737 38264 81.87 Spain 226340 128920 97420 75.57 Romania 13284 8216 5068 61.68 Nigeria 2608 1724 884 51.28 Egypt 3942 2645 1297 49.04 Senegal 10795 7258 3537 48.73 Kazakhstan 22322 15722 6600 41.98 Russia 4185 2958 1227 41.48 Israel 10122 7176 2946 41.05 India 241664 188000 53664 28.54 Tanzania 7534 5871 1663 28.33 Brazil 33164 26228 6936 26.45 South Africa 28413 23250 5163 22.21 USA 4602486 3901735 700751 17.96 Canada 481298 415762 65536 15.76 Zimbabwe 3199 2805 394 14.05 Mexico 5560 4888 672 13.75 Sri Lanka 20275 20162 113 0.56 Australia 125813 142713 -16900 -11.84 Vietnam 27389 35420 -8031 -22.67 Thailand 420877 646472 -225595 -34.90 Pakistan 39472 96083 -56611 -58.92 Total 18096264 11956637 6139627 51.35 31 Table 8: Scenario 5 Exporter All importers 2ppb Codex Change from % difference with Standard Codex Standard Codex Standard (US $1,000) (US$1,000) (US $1,000) Brazil 23535 33164 -9629 -29.03 Israel 6897 10122 -3225 -31.86 Tanzania 4971 7534 -2563 -34.02 Sri Lanka 13246 20275 -7029 -34.67 India 142176 241664 -99488 41.17 Mexico 3094 5560 -2466 -44.35 Hungary 46576 85001 -38425 -45.21 South Africa 14762 28413 -13651 -48.04 USA 2394095 4602486 -2208391 -47.98 Egypt 1841 3942 -2101 -53.30 Vietnam 12544 27389 -14845 -54.20 Nigeria 1114 2608 -1494 -57.29 Spain 97327 226340 -129013 -57.00 France 1012015 2458854 -1446839 -58.84 Netherlands 121376 317510 -196134 -61.77 Italy 282161 806800 -524639 -65.03 Kazakhstan 7920 22322 -14402 -64.52 Romania 4543 13284 -8741 -65.80 Australia 41214 125813 -84599 -67.24 Zimbabwe 1060 3199 -2139 -66.86 Denmark 12853 40883 -28030 -68.56 Russia 1254 4185 -2931 -70.04 Germany 190229 678527 -488298 -71.96 Austria 15522 58441 -42919 -73.44 Senegal 2703 10795 -8092 -74.96 Pakistan 9573 39472 -29899 -75.75 Canada 97333 481298 -383965 -79.78 Argentina 1253267 7161983 -5908716 -82.50 Paraguay 12177 70092 -57915 -82.63 Uruguay 15287 87431 -72144 -82.52 Thailand 63760 420877 -357117 -84.85 Total 5906425 18096264 -12189839 -67.36 32 Table 9. Predicted Change in Imports at the Break-Even Point Importer Change Share in Change (%) Partner Change Partner Change (US$ total in country's whose trade (US$ whose (TJS$ 1,000) positive export flow will 1,000) trade flow 1,000) (negative) increase will change in most decrease percent most UK +718725 +45 +91 France 462788 Germany +642428 +40.2 +93 France 394212 Austria +93678 +5.9 +100 USA 40773 Brazil +74081 +4.6 +2 Argentina 71104 India 38 France +33577 +2.1 +4 USA 9111 Australia +18859 +1.2 +33 Thailand 8608 India 1851 Spain +7943 +0.5 +1 France 3489 India 99 Italy +6874 +0.4 +1 France 3403 India 125 Israel +1554 +0.1 +1 USA 770 India 159 USA -132257 -8.3 -52 Canada 91800 Nigeria -170477 -10.7 -78 USA 98833 Japan -190853 -11.9 -49 USA 80737 Malaysia -283674 -17.8 -73 Thailand 125267 Canada -325236 -20.4 -22 USA 307920 India -495190 -31 -91 Thailand 231528 33 Table 10. Predicted Change in Exports at the Break-even Point Exporter Change Share in Change (%/) Partner Change Partner Change (US$ total in country's whose trade (US$ whose (US$ 1,000) 1,000) positive export flow will 1,000) trade flow (negative) increase will change in most decrease percent most France +861288 +71.6 +69 UK 463235 India 1562 Italy +120195 +10.0 +28 Gernany 71352 India 1482 The Netherlands +84559 +7.0 +52 Germany 57252 India 98 Germany +56169 +4.7 +17 UK 49075 India 343 Spain +27681 +2.3 +24 UK 13166 Nigeria 326 Hungary +19984 +1.7 +42 Austria 17829 India 1155 India +8828 +0.7 +4 UK 30390 Malaysia 16447 Denmark +8332 +0.7 +40 Gernany 5492 India 61 Austria +7490 +0.6 +25 Germany 5279 India 74 Argentina +5542 +0.5 0 Brazil 82251 Nigeria 20996 Tanzania +2118 +0.2 +10 UK 3010 India 419 Romania +543 +0.05 +7 Austria 746 India 455 Paraguay +367 +0.03 +1 Brazil 818 USA 137 Nigeria +314 +0.03 +16 UK 458 India 97 Uruguay +95 +0.01 0 Brazil 1005 Nigeria 255 Egypt +51 +0.01 +4 UK 102 India 40 Israel +34 +0.01 +8 Austria 42 India 17 Brazil -189 -0.02 -I Austria 1185 USA 735 Russia -239 -0.02 -8 Germany 204 India 368 Zimbabwe -478 -0.04 -14 UK 533 Nigeria 404 Senegal -643 -0.05 -6 France 397 Nigeria 867 Mexico -729 -0.06 -16 Germany 101 USA 259 Kazakhstan -837 -0.07 -6 Germany 1023 India 1694 South Africa -2188 -0.2 -17 UK 2045 Nigeria 1764 Sri Lanka -5163 -0.4 -25 Austria 625 India 2706 Vietnam -17471 -1.5 -49 Austria 468 Malaysia 10742 Australia -64675 -5.4 -55 Germany 1309 Malaysia 28509 Pakistan -75124 -6.2 -83 Germany 385 India 71428 Canada -134549 -11.2 -33 UK 12308 USA 91532 Thailand -419924 -34.9 -65 Australia 8614 India 231402 USA -481349 -40 -17 UK 67538 Canada 291574 34 Policy Research Working Paper Series Contact Title Author Date for paper WPS2667 Trade Reform and Household Welfare: Elena lanchovichina August 2001 L. Tabada The Case of Mexico Alessandro Nicita 36896 Isidro Soloaga WPS2668 Comparative Life Expectancy in Africa F. Desmond McCarthy August 2001 H. Sladovich Holger Wolf 37698 WPS2669 The Impact of NAFTA and Options for Jorge Martinez-Vazquez September 2001 S. Everhart Tax Reform in Mexico Duanjie Chen 30128 WPS2670 Stock Markets, Banks, and Growth: Thorsten Beck September 2001 A. Yaptenco Correlation or Causality? Ross Levine 31823 WPS2671 Who Participates? The Supply of Norbert R. Schady September 2001 T. Gomez Volunteer Labor and the Distribution 32127 of Government Programs in Rural Peru WPS2672 Do Workfare Participants Recover Martin Ravallion September 2001 C. Cunanan Quickly from Retrenchment? Emanuela Galasso 32301 Teodoro Lazo Ernesto Philipp WPS2673 Pollution Havens and Foreign Direct Beata K. Smarzynska September 2001 L. Tabada Investment: Dirty Secret or Popular Shang-Jin Wei 36896 Myth? WPS2674 Measuring Economic Downside Yan Wang September 2001 A. Rivas Risk and Severity: Growth at Risk Yudong Yao 36270 WPS2675 Road Infrastructure Concession Franck Bousquet September 2001 G. Chenet-Smith Practice in Europe Alain Fayard 36370 WPS2676 An Alternative Unifying Measure of Philippe Auffret September 2001 K. Tomlinson Welfare Gains from Risk-Sharing 39763 WPS2677Can Local Institutions Reduce Poverty? Paula Donnelly-Roark September 2001 E. Hornsby Rural Decentralization in Burkina Faso Karim Ouedraogo 33375 Xiao Ye WPS2678 Emerging Markets Instability: Do Graciela Kaminsky September 2001 E. Khine Sovereign Ratings Affect Country Sergio Schmukler 37471 Risk and Stock Returns? WPS2679 "Deposit Insurance Around the Globe: Asl1 Demirgu,-Kunt September 2001 K. Labrie Where Does It Work? Edward J. Kane 31001 WPS2680 International Cartel Enforcement: Simon J. Evenett September 2001 L. Tabada Lessons from the 1990s Margaret C. Levenstein 36896 Valerie Y. Suslow Policy Research Working Paper Series Contact Title Author Date for paper WPS2681 On the Duration of Civil War Paul Collier September 2001 P. Collier Anke Hoeffler 88208 Mans Soderbom WPS2682 Deposit Insurance and Financial Robert Cull September 2001 K. Labrie Development Lemma W. Senbet 31001 Marco Sorge WPS2683 Financial Policies and the Prevention Frederic S. Mishkin October 2001 R. Vo of Financial Crises in Emerging 33722 Market Economies WPS2684 From Monetary Targeting to Inflation Frederic S. Mishkin October 2001 R. Vo Targeting: Lessons from Industrialized 33722 Countries WPS2685 Monetary Policy Strategies for Frederic S. Mishkin October 2001 R. Vo Latin America Miguel A. Savastano 33722 WPS2686 Education, Earnings, and Inequality Andreas Blom October 2001 S. Benbouzid in Brazil, 1982-98: Implications for Lauritz Holm-Nielsen 88469 Education Policy Dorte Verner WPS2687 Geographic Patterns of Land Use Kenneth M. Chomitz October 2001 S. Hendrckson and Land Intensity in the Brazilian Timothy S. Thomas 37118 Amazon WPS2688 Aid, Shocks, and Growth Paul Collier October 2001 A. Kitson-Walters Jan Dehn 33712