Asian Regionalism and Its Effects on Trade in the 1980s and 1990s

Clarete, Ramon; Edmonds, Christopher M.; Wallack, Jessica Seddon Working Paper Asian Regionalism and Its Effects on Trade in the 1980s and 1990s ERD Working Paper Series, No. 30 Provided in Cooperation with: Asian Development Bank (ADB), Manila Suggested Citation: Clarete, Ramon; Edmonds, Christopher M.; Wallack, Jessica Seddon (2002) : Asian Regionalism and Its Effects on Trade in the 1980s and 1990s, ERD Working Paper Series, No. 30, Asian Development Bank (ADB), Manila, https://hdl.handle.net/11540/2067 This Version is available at: https://hdl.handle.net/10419/109251 Standard-Nutzungsbedingungen: Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden. Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen. 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If the documents have been made available under an Open Content Licence (especially Creative Commons Licences), you may exercise further usage rights as specified in the indicated licence. http://creativecommons.org/licenses/by/3.0/igo ECONOMICS AND RESEARCH DEPARTMENT ERD WORKING PAPER SERIES NO. 30 Ramon Clarete Christopher Edmonds Jessica Seddon Wallack November 2002 Asian Development Bank Asian Regionalism and Its Effects on Trade in the 1980s and 1990s 33 ERD Working Paper No. 30 ASIAN REGIONALISM AND ITS EFFECTS ON TRADE IN THE 1980S AND 1990S Ramon Clarete Christopher Edmonds Jessica Seddon Wallack November 2002 Ramon Clarete is a Professor of Economics at the University of the Philippines; Christopher Edmonds is an Economist in the Development Indicators and Policy Research Division of the Economics and Research Department, Asian Development Bank; and Jessica Seddon Wallack is a doctoral candidate at the Graduate School of Business, Stanford University. This paper has been accepted for publication in the Journal of Asian Economics (forthcoming). This paper was presented at the 24th International Conference on Asian Economic Studies held on 26-29 May 2002 in Beijing. The authors gratefully acknowledge useful consultations with Kym Anderson in the early phases of this research and the excellent research assistance of Catherine Lawas, and express thanks to the many participants of the Beijing Conference who offered useful comments on an earlier draft of the paper. Comments on an earlier paper related to this work from Malcolm Dowling, Jeffrey Liang, J.P. Verbiest, and Xianbin Yao are also gratefully acknowledged. This research was carried out with the financial support of the Asian Development Bank. The paper may not be quoted or cited without permission of the authors. The views expressed in this paper are those of the authors and do not necessarily represent the views of the institutions with which they are affiliated. ERD Working Paper No. 30 ASIAN REGIONALISM AND ITS EFFECTS ON TRADE IN THE 1980S AND 1990S 34 Asian Development Bank P.O. Box 789 0980 Manila Philippines 2002 by Asian Development Bank November 2002 ISSN 1655-5252 The views expressed in this paper are those of the author(s) and do not necessarily reflect the views or policies of the Asian Development Bank. 35 Foreword The ERD Working Paper Series is a forum for ongoing and recently completed research and policy studies undertaken in the Asian Development Bank or on its behalf. The Series is a quick-disseminating, informal publication meant to stimulate discussion and elicit feedback. Papers published under this Series could subsequently be revised for publication as articles in professional journals or chapters in books. ERD Working Paper No. 30 ASIAN REGIONALISM AND ITS EFFECTS ON TRADE IN THE 1980S AND 1990S 38 Contents Acronyms vii Abstract ix I. Introduction 1 II. PTAs: Trade-creating or Trade-diverting? 3 A. Overview of PTAs in Asia and the Rest of the World 3 III. Trends and Geographical Concentration of Trade in the Asian and Pacific Region 6 A. Trends in Trade 6 B. Geographical Patterns of Trade 7 C. Regional Trade Shares 8 D. Intrabloc Export Shares 8 E. Trade Intensity Indices 10 IV. Analyzing Trade Effects of PTAs Using a Gravity Model 13 A. Basic Determinants 13 B. Preferential Trade Agreements in the Gravity Model 15 C. Modeling the Effect of PTAs on Asian Trade 16 D. Data and Estimation Issues 17 V. Empirical Results 18 A. Basic Determinants of Trade Flows 18 B. PTAs Fostering Intrabloc Trade 19 C. PTAs Fostering Greater Intrabloc Trade and Greater Trade with the Rest of the World 23 D. PTAs that Reduced Gross Trade but did not Change Intrabloc Trade Significantly 25 E. Gross Intrabloc Effect 26 F. Effect of PTAs on Asian Trade 27 G. PTAs’ Contribution to World Trade 28 VI. Conclusions 29 References 30 ERD Working Paper No. 30 ASIAN REGIONALISM AND ITS EFFECTS ON TRADE IN THE 1980S AND 1990S 36 Acronyms ADB Asian Development Bank ADO Asian Development Outlook AFTA ASEAN Free Trade Area APEC Asia-Pacific Economic Cooperation forum ASEAN Association of Southeast Asian Nations CER Australia-New Zealand Closer Economic Relations Trade Agreement CIS Commonwealth of Independent States CU Customs union DMC Developing Member Country DOTS Direction of Trade Statistics ECO Economic Cooperation Organization EEC European Economic Community EFTA European Free Trade Association EU European Union FTA Free-trade agreement GATT General Agreement on Tariffs and Trade GDP Gross Domestic Product IMF International Monetary Fund Mercosur Southern Common Market MSG Malenesian Spearhead Group NAFTA North American Free Trade Agreement OLS Ordinary Least Squares PRC People’s Republic of China PTA Preferential trading arrangement SAPTA South Asian Preferential Trade Arrangement SPARTECA South Pacific Regional Trade and Economic Cooperation Agreement SREZ Subregional Economic Zone WTO World Trade Organization 37 Abstract This paper begins by outlining the major preferential trade agreements (PTAs) in Asia and other regions and reviewing trends in trade flows. The paper uses a gravity model augmented with several sets of dummy variables to estimate the effect of various PTAs on trade flows within and across membership groupings as well as the effect of PTAs on members’ trade with Asian countries. On the basis of these estimates, we are able to categorize 11 major PTAs into those that increase intrabloc trade at the expense of their respective imports from the rest of the world; those that expand their respective trade among their members without reducing their trade with nonmembers; and those that reduce trade with nonmembers without significant changes in intrabloc trade. The authors also show that PTAs have augmented trade in Asia. 1 I. INTRODUCTION The past few years have seen a sharp upturn in interest and activity in the formation of preferential trading arrangements (PTAs) in the Asian and Pacific region. Japan and Singapore recently signed an Economic Partnership Agreement in February 2002. Singapore also signed a bilateral trade agreement with New Zealand in 2001. Japanese policymakers have proposed a Japan-ASEAN Comprehensive Economic Partnership, and an ASEAN-People’s Republic of China Free Trade Area was proposed by the People’s Republic of China (PRC) and endorsed by ASEAN’s ten leaders in the organization’s ministerial meeting in Brunei in October 2001. In February 2002, government representatives of 14 Pacific Island nations met and agreed to form a PTA. These recent events follow more than a decade of increasing numbers of PTAs in the Asian and Pacific region and a similar upsurge in the number of PTAs in the world as a whole in the late 1980s and early 1990s. At present, about 97 percent of total global trade involves countries that are members of at least one PTA. This compares with a 72 percent share in 1990. The increased interest in preferential trade agreements raises the important question of whether these more limited, often regionally based, trading arrangements are beneficial to Asian economies. As PTAs become a more commonly considered policy option, it is increasingly important to evaluate how the economic effects of PTAs compare to the effects of broader multilateral trading arrangements as well as how the PTAs affect world trade flows in general. This paper focuses on the latter question. The following section describes the debate over PTAs’ effects on world trade flows and provides some background on the PTAs we include in the analysis. Sections III and IV present empirical and analytical explorations of trade flows within and across PTAs. We first present a set of descriptive measures of trade flows and Section V presents the result of an augmented gravity model that estimates the effect that PTAs have on trade flows after controlling for nonpolicy determinants of trade. Following Soloaga and Winters (2001), we use a combination of dummy variables in the gravity model that allows us to separately identify the effects of PTAs on intrabloc trade as well as trade between members and the rest of the world. Our estimating equation also includes a set of dummy variables to identify the impact that PTAs have had on trade with Asian countries in particular. Another contribution is to estimate the model using data covering the years 1980 to 2000, a panel that allows us to consider how the Asian financial crisis influenced trade flows and the effects of PTAs on trade flows. Our main finding is that the effect of PTAs on trade flows varies widely across PTAs. We estimated large positive “intra-bloc trade” effects for the Andean Pact, Economic Cooperation Organization (ECO), European Free Trade Association (EFTA), Mercosur, South Asian Preferential Trade Arrangement (SAPTA), and South Pacific Regional Trade and Economic Cooperation ERD Working Paper No. 30 ASIAN REGIONALISM AND ITS EFFECTS ON TRADE IN THE 1980S AND 1990S 8 Ir,r = xTr,r / xTr,W xTW,r / xTW,W If this index is one, bloc members are trading with each other in the same intensity as they would have traded with nonmembers. C. Regional Trade Shares The shares of total world trade originating from various regions and economies have changed markedly over the last half-century.2 North America, Western Europe, and Japan have consistently been the top three trading regions or countries. Together they account for 64.3 percent of world exports and 68.6 percent of imports. These figures are substantively higher than they were in 1948, at 59.2 and 61.2 percent, respectively. Recently, the share of the PRC in total world trade has been rising while that of Japan declined in 2000, having its peak in 1993. Like the PRC, the share of the group comprising Central and Eastern Europe, Baltic States, and CIS states has expanded in the 1990s. Asia’s share to total world trade of merchandise exports doubled over the past 50 years, while its share of world imports increased by only 60 percent. Eight countries account for 84 percent of Asia’s export share in 2000 and 82 percent of its import share. These include PRC, Japan, and six East Asian trading countries. About half a century ago, the corresponding figures representing the contribution of these countries to Asia’s share in world trade were respectively 32 and 36 percent. D. Intrabloc Export Shares A useful measure for comparison across time is the share of trade among members of a given group of trading countries or region to total trade of the region. Higher intrabloc trade shares may indicate a possible preference of members of a region or bloc to trade with each other. Figure 1 shows the intrabloc shares of exports for eleven trade blocs while Table 1 lays out the five-year averages of these shares.3 The blocs include AFTA, Andean, APEC, CER, ECO, EFTA, EU, Mercosur, NAFTA, SAPTA, and SPARTECA. The period covered in the table is from 1980 to 2000. Regional export shares exhibit a moderately rising trend toward the end of the 1990s. This pattern is most noticeable in the case of NAFTA, APEC, and ASEAN. Moderate growth of the respective intraregional export shares of the PTAs covered in this analysis may more likely be attributed to changes in the composition of these groupings, rather than to any intensification of preference of PTA members to trade among each other. In 1994, Canada and the US brought 2Trends in world merchandise trade between 1948 and 2000 are summarized on Table 3.4 on page 165 of the ADO 2002. 3The basic data comes from the International Trade Statistics 2001 (WTO 2001). 9 EU NAFTA AFTA EFTA SPARTECA ECO CER SAPTA Andean Mercosur EFTA CER SAPTA APEC NAFTA Year Andean Mercosur AFTA EU ECO SPARTECA 2000 1998 1994 1996 19921990 1988 1986198419821980 Sources: ( 2001); authors’ computation.Direction of Trade Statistics IMF Figure 1. Intrablock Export Shares of Selected PTAs, 1980-2000 Percent of Total PTA Export 80 0 10 20 30 40 60 50 70 APEC Mexico in to their FTA to form NAFTA. Chile, Mexico, and Papua New Guinea joined APEC in 1993, while Peru, Russia, and Viet Nam became members in 1998. As for ASEAN, Cambodia, Laos, Myanmar, and Viet Nam joined the organization between 1995 and 1998. There have been instances where intrabloc trade shares fell (e.g., ECO, Andean Pact, and Mercosur between 1998 and 2000) as a result of external shocks and institutional changes happening within these PTAs. Political instability and economic restructuring in Central Asia combined with the lack of integration of ECO countries in the world economy explain the fall in the ECO trade share. External shocks associated with the Asian financial crisis likely contributed to a decline in Asian PTAs in the late 1990s. Table 1 shows Asian PTAs (with the exception of APEC, which has many Asian countries as members but whose membership extends to North and South American countries as well) tend to have the larger share of their respective trade with nonmembers—particularly in comparison to EU and NAFTA. This observation may possibly be explained by the nature of the PTAs themselves, as promoting intrabloc trade among its members. That is, NAFTA or EU members comprise a natural bloc and the preferential policies have aggravated this natural attraction among members to trade with one another. This explanation can hardly be applied, however, to the case of APEC, to which we return shortly when we take up the apparent limitation of intrabloc trade shares for measuring the impact of PTAs. Section III Trends and Geographical Concentration of Trade in the Asian and Pacific Region ERD Working Paper No. 30 ASIAN REGIONALISM AND ITS EFFECTS ON TRADE IN THE 1980S AND 1990S 10 On the other side of the coin, one possible reason why intrabloc trade shares are low for Andean, Asia-based PTAs, and Mercosur is that these are developing country PTAs. Their smaller per capita GDPs—in turn the outcome of their particular development status, economic shocks, or political instability—are such that their trade will tend to flow toward more wealthy countries even if their respective members share common borders. The Latin American PTAs—the Andean Pact and Mercosur—trade predominantly with countries outside of the PTA, which reflects the importance of the EU or US as a trading partner in that region. It warrants note that the high intrabloc shares for APEC, EU, and NAFTA do not necessarily indicate that the respective members of these prefer trade with other bloc members over trade with nonmembers. The index tends to be higher PTAs that include more or larger trading economies. Frankel (1997) cites the case of EU (previously the European Economic Community [EEC]) when the PTA expanded from six members in the 1960s to 12 in the 1990s, resulting in an increase of EEC’s intraregional trade share from 49 percent in 1962 to 60 percent in 1990. The small intrabloc trade share of EFTA (i.e., 12 percent) may likewise be explained by the fact that this PTA has lost its members to EU. E. Trade Intensity Indices The weakness of intraregional trade shares as measures of trade orientation can be addressed by using simple concentration ratios or trade intensity indicators. The trade concentration ratio is obtained by dividing the intraregional trade share by the share of the region to total world trade. When the trade intensity indicator is equal to one, the PTA does not have any trade-diverting effect. That is, PTA members are trading among themselves at the same intensity as they would with nonmembers. If there is extra trade that goes on in the region beyond the normal pattern in the absence of the PTAs, then the trade intensity exceeds one. Table 1. Five-Year Average Intrabloc Export Shares of Selected PTAs, 1980 to 2000 PTAs 1980-84 1985-89 1990-94 1995-99 2000 AFTA 20.75 18.94 22.51 24.81 24.54 Andean Pact 5.01 4.82 9.13 13.23 10.77 APEC 66.30 72.18 73.08 74.31 75.24 CER 7.99 8.41 9.13 10.73 9.25 ECO 9.34 7.33 6.42 8.41 6.58 EFTA 16.53 16.39 13.73 12.60 11.82 EU 62.00 65.05 66.47 65.08 66.94 Mercosur 9.94 8.52 15.94 24.84 22.35 NAFTA 41.29 46.68 48.17 53.15 58.82 SAPTA 6.30 4.93 4.44 5.14 4.81 SPARTECA 11.88 11.44 12.78 14.18 12.31 Source: Authors’ computation based on Direction of Trade Statistics (IMF 2001). 11 The estimated trade intensity indices for the 11 PTAs from 1980 to 2000 are shown in Figure 2. In this figure and on Table 2, all the estimates are greater than one and display a similar pattern of results as in Frankel (1997).4 The bigger PTAs such as APEC, EU, and NAFTA tend to have indices close to one. The smaller ones tend to have bigger ratios, with size of PTAs defined as the PTA’s share of world trade. There are differences between our estimates and Frankel’s due to the difference in membership in the periods that the two studies focus on. Frankel’s period of analysis was from 1962 to 1994, while our analysis extends to 2000. 4See Table 2.3 of Frankel (1997). EU EFTA CER SAPTA APEC NAFTA Year Andean Mercosur AFTA EU ECO SPARTECA 2000 1998 1994 1996 19921990 1988 1986198419821980 Trade Intensity Index 18 2 4 6 8 10 14 12 16 0 NAFTA ECO SAPTA AFTA EFTA SPARTECA CER MERCOSUR Andean Figure 2. Trade Intensities of Selected PTAs, 1980 to 2000 Source: Authors’ computation based on .Direction of Trade Statistics (IMF 2001) It is interesting to note that the Andean and Mercosur trade blocs have the highest trade intensities, an observation reported as well by Frankel. The Asian PTAs have lower corresponding estimates, no more than ten. The ECO bloc countries, comprising mostly Central Asian economies, apparently traded relatively more among themselves in the first half of the 1990s. Based on the data for the second half of that decade, this appears no longer true. This observation may indicate that these countries have adopted a more outward trade orientation in that period. A similar observation may be said of AFTA, but unlike in ECO the intensity index for the Southeast Asian bloc consistently fell in the 1990s. SAPTA countries formed their PTA in the middle of the 1990s. As shown in the figure, the trade intensity index for SAPTA rose to 1997 but fell subsequently. Section III Trends and Geographical Concentration of Trade in the Asian and Pacific Region ERD Working Paper No. 30 ASIAN REGIONALISM AND ITS EFFECTS ON TRADE IN THE 1980S AND 1990S 12 We computed the five-year averages of the intensity indices since 1980 in order to describe more clearly the pattern of trade concentration disclosed by the ratios (see Table 2). APEC and EU have consistently the two lowest trade intensities among the 11 PTAs examined. NAFTA and EFTA switched in the bottom third or fourth places, with NAFTA increasing its index in the 1990s. The other PTAs in Asia exhibit through time an increasing outward orientation. It is interesting to note that CER and SPARTECA appear to focus their trade within their bloc compared with AFTA, ECO, or SAPTA in the 1990s. Table 2. Five-Year Average Trade Intensity Indices of Selected PTAs, 1980 to 2000 PTAs 1980-84 1985-89 1990-94 1995-99 2000 AFTA 4.22 4.78 3.78 3.72 3.97 Andean Pact 3.63 5.44 10.90 15.65 16.61 APEC 1.60 1.61 1.57 1.53 1.50 CER 4.15 4.62 5.81 7.08 6.76 ECO 5.48 5.24 4.20 5.67 4.67 EFTA 2.35 2.12 2.02 2.10 2.24 EU 1.52 1.54 1.60 1.66 1.70 Mercosur 5.58 7.48 11.70 13.16 14.31 NAFTA 1.83 1.82 2.04 2.18 2.15 SAPTA 4.10 3.46 3.90 4.22 4.14 SPARTECA 5.80 5.96 7.73 8.98 8.72 Source: Authors’ computation based on Direction of Trade Statistics (IMF 2001). Mercosur and Andean have the top two indices for the 1990s, with the latter exhibiting a sharp increase from being fifth in the first half of the 1980s to being at the top of the group in the second half of the 1990s. This indicates a surge of intrabloc trade activity among its members. Earlier and using intraregional trade share indices, we documented how Mercosur and Andean intrabloc exports had increased dramatically from 1995 to 1998 but had fallen from 1999 to 2000. What is interesting to note here is that by deflating the intraregional shares with the respective regional share of total world trade, we observe that Mercosur and Andean remained as having the highest intrabloc trade intensity. This has to indicate that the respective trade shares of these regions in world trade had obviously declined by a rate much greater than the decrease of intrabloc trade. Obviously, this highlights the effect of keeping track of general economic performance in assessing intraregional trade activity, and leads us to the analysis of trade flows using gravity models of trade. 13 5Those responsible in developing the theory of the gravity model include Deardorf (1984); Helpman and Krugman (1985); and Helpman (1987). Frankel (1997, 61) cites Helpman and Krugman as the originators of the standard gravity model. The name used for their analytical framework is taken after Newton’s theory of gravitation because of the analogy. Section IV Analyzing Trade Effects of PTAs Using a Gravity Model IV. ANALYZING TRADE EFFECTS OF PTAs USING A GRAVITY MODEL A. Basic Determinants In this section, we outline the gravity model of bilateral trade flows used in analyzing the effects of PTAs.5In the model, trade between two countries is viewed as being positively affected by the economic mass of trading partners and negatively affected by the distance between the trading partners. Additional variables, such as physical area, population, indicators of cultural affinity, and sharing contiguous borders are usually added to empirical gravity models to elaborate on the “economic mass” and distance variables. Under the model, the total merchandise exported by country i to country j (Xij) is defined as follows: Xij = AYiβiYjβjHiµiHjµjNiγiNjγjDijαDjδεij (1) where Yirepresents the gross domestic product of country i; Hirepresents the geographic size of country i; Nirepresents the population of country i; Dij represents the distance between country i and country j; Direpresents the average distance between country i and its export markets in other countries; Ais a constant; ε ij is an error term; and β,µ > 0; and γ, α, δ < 0. Taking the logarithm of (1), we get: log Xij = log A + βi log Yi + βj log Yj + µi log Hi + µj log Hj + γ i log Ni + γ j log Nj + α log Dij + δ log Di + log ε ij (2) The regression equation typically used: log Xij = log A + βi log Yi + βj log Yj + µi log Hi + µj log Hj + γ i log Ni + γ j log Nj + α log Dij + δ log Di + α ADJij + cIi + dIj + log ε ij (3) includes several dummy variables ADJij, Ii, and Ij to capture additional features of the country pair such as whether the trading partners have adjacent borders (ADJ) or either partner is an island economy (I). The error term is the standard Ordinary Least Squares (OLS) residual. ERD Working Paper No. 30 ASIAN REGIONALISM AND ITS EFFECTS ON TRADE IN THE 1980S AND 1990S 14 Per capita GDP is considered a key variable in the model, and larger economies are expected to engage in greater trade. However, a number of other factors act against the “gravity like” forces of economy size. Country geographic size and population are factors expected to reduce trade orientation by increasing the size of the domestic market and making economic activity more inwardly oriented. For example, the PRC and Japan both have large economies of roughly similar size, but trade little. This may be explained by the fact that the PRC has a lower per capita GDP, which weakens its capacity to attract trade from Japan. The PRC’s large population gives Chinese producers plenty of consumers domestically and tends to dampen rather than augment exports. Frankel (1997) explains that countries with large populations tend to be more inwardly oriented than smaller countries because they are better able to exploit scale economies in their large domestic markets. This may explain why bilateral trade flows generally have an inverse relationship to population size. Like population, physical area is expected to reduce trade flows to the extent that countries with relatively small or limited natural resource endowments tend to be smaller and thus depend more on trade to obtain natural resources not available in the country. Krugman (1991a) considers the distance between two countries to be an important determinant of geographical patterns of trade. Trade is attractive to the extent of the gains from trading less the transaction cost incurred in realizing such gains. Distance tends to increase the cost of transacting international exchange of goods and services. Beyond some distance, costs of consummating a cross-border exchange become prohibitive and accordingly no trade occurs. The farther apart two potential trading partners are, the more costly their bilateral trade, which erodes possible gains from trade. Linnemann (1966) categorizes the costs of international trade transactions into three types: (i) shipping cost, including freight and insurance; (ii) cost of time; and (iii) “psychic distance” or “cultural cost.” Distance is not the only determinant for shipping cost. In examining data on freight, insurance, and shipping charges, Frankel (1997) notes that shipping costs vary widely across countries in Central Africa, where two remote trading partners may have relatively low aggregate shipping cost because only commodities that have relatively low shipping cost are traded. Accordingly, commodity composition of trade is needed in order to understand the relationship between distance and shipping cost. Evidence suggests the effect of distance on trade flow has changed through time. Estimates from a gravity model carried out by Boisso and Ferrantino (1997) using data covering the years 1965-1985 suggest that distance had a deterrent effect on trade until the middle of the 1970s, but that this effect has declined since then. They claim that the average distance between trading partners increased in the postwar period, indicating that shipping costs have fallen steadily. Trading partners located far apart from each other will have to require more time in transporting goods between each other, which discourages trade. This cost includes the intrinsic value of the goods that is foregone if these are not delivered on time. The “psychic distance” or “cultural cost” refers to the lack of familiarity by the citizens of a country about their trading partners (Drysdale and Garnaut 1982). Cultural or linguistic affinity, shared borders, and whether the trading partner’s territories are islands are factors that would tend to reduce cultural distance. Countries sharing a common language or having citizens belonging to the same ethnic group are more likely to transact business with each other. 15 In the specification of the basic gravity model used in this paper, following Soloaga and Winters (2001) we include two variables in our basic gravity model to capture different aspects of the influence of distance on trade flows. First, we include a variable measuring the distance between the capital cities for each pair of trading countries (Dij). Second, we include a measure of the remoteness of a country captured by the average distance between the country and the country with which it trades (Di). In examining the effect of PTAs on the direction and volume of trade, it is important estimates controlled for the effect of distance and these other factors on trade flows. Next, we incorporate the variables representing PTAs, along with the other variables outlined as important in determining trade flows, into a gravity model. B. Preferential Trade Agreements in the Gravity Model In adopting the basic gravity model framework to study the effect of PTA membership on trade flows, Aitken (1973) and Braga, Safadi, and Yeats (1994) introduce a variable that takes the value of one if the two trading countries are both members of the PTA, and zero otherwise into the model. They interpreted the estimated coefficient of this dummy variable to be the sum of the trade-creation and trade-diversion effects of the PTAs. A positive coefficient for the variable indicates that the PTA tends to generate more trade to its members. One shortcoming of this initial approach is that a single variable cannot separate the effects of the PTA on trade creation and trade diversion, so the approach does not inform judgment regarding the relative magnitude of the creation and diversion effects. Bayoumi and Eichengreen (1995) and Frankel (1997) add a second variable to enable tradecreating and trade-diverting effects of PTAs to be separated in the estimates. The variable takes the value of one if the importing country is a member of the PTA and the exporting country is a nonmember; zero if otherwise. The coefficient of the “extra-bloc” variable represents the trade of nonmembers diverted to the members of the PTA. A positive value suggests PTA members reduce imports to the bloc from nonmembers. Soloaga and Winters (2001) introduce two additional PTA-related variables in order to capture the effects of PTAs on trade in general. One variable purportedly captures the impact of nondiscriminatory import liberalization enacted through the PTA, and takes a value of one if the importer is a member of a bloc and zero otherwise. This variable is different from the extrabloc PTA variable of Bayoumi and Eichengreen (1995) and Frankel (1997), because that variable captures only the extra imports of members from nonmembers. Soloaga and Winters’ specification considers the extra imports of members of the PTA from all trading partners regardless of their membership status. A final dummy variable introduced by Soloaga and Winters seeks to capture the extra exports of PTA members to all their trading partners, and takes a value of one if the exporter is a member and zero otherwise. Equation (4) represents the decomposition of the trade effects of PTAs that Soloaga and Winters introduce: Section IV Analyzing Trade Effects of PTAs Using a Gravity Model ERD Working Paper No. 30 ASIAN REGIONALISM AND ITS EFFECTS ON TRADE IN THE 1980S AND 1990S 16 log Xij = log A + βi log Yi + βj log Yj + µi log Hi + µj log Hj + γ i log Ni + γ j log Nj + α log Dij + δ log Di + a ADJij + cIi + dIj + bkPkiPkj + mkPkj + nkPki + log ε ij (4) where Pki is a dummy variable that takes the value of one if exporting country i belongs to PTA k and zero otherwise; and Pkj is a similarly defined dummy variable for importing country j belonging to PTA k. The coefficient bk on the interaction of Pkj and Pki represents the additional exports from i to j that occur when both countries are members of the PTA k. The coefficient on Pkj , mk, represents the additional exports from country i, not a member of PTA k, to a country j in PTA k. In other words, this dummy represents the additional imports that country j in PTA k receives from the world outside the PTA. The coefficient nk has a similar interpretation as country i’s exports to nonmembers of the PTA. Soloaga and Winters’ elaboration of the earlier models adapted to examine the trade effects of PTAs can be understood as seeking to measure the impact of PTAs on the trade of their respective members, and not just on intrabloc trade as in the traditional approach of Aitken (1973) and Braga, Safadi, and Yeats (1994). The trade liberalization effects of PTAs are highlighted. The trade of members of the OTA is measured through the sum of the coefficients of the intrabloc variable and the extra-import and extra-export variables. The total effect of the PTA on trade with bloc members is thus: bk + mk + nk, or the sum of trade diversion (bk) and general trade liberalization effects on exports (nk) and imports (mk). The separate dummy variables allow for us to assess the relative contribution of the PTA to narrow intrabloc trade as well as general trade with the world. In the most extreme trade-diverting case, the coefficient bk would be positive (indicating increased exports from when both countries are members of PTA k), and mk + nk is negative (indicating that being in PTA k depresses a country’s imports from the rest of the world more than it increases its exports to the rest of the world, or vice versa, so that the net effect on trade flows between PTA members and the world is negative). In a case where the PTA expanded intrabloc trade but trade with the rest of the world increased as well, we might also have a positive intrabloc effect as well as positive import and export effects. C. Modeling the Effect of PTAs on Asian Trade Because the focus of the present study pertains to the effect of PTAs on Asian trade, we introduce Asian variables into the gravity model in order to capture the effect of PTAs on Asia’s trade. Following Soloaga and Winters, we separate the extra imports and the extra exports that Asia gets because of a PTA. The “Asia extra import” effect of a PTA is denoted by the estimation coefficient in equation (5) of the interaction between the ASIA dummy variable j that takes the value of one if importer j is in Asia, and the dummy variable Pki that is one if the exporting country i is a member of PTA k. The estimation coefficient, mkA, measures the extra imports that Asian countries obtain from PTA k, regardless of whether they are members of PTA k or not. The “Asian extra export” effect is defined similarly. nkA measures the added exports Asian countries provide 17 to member countries of PTA k. It is the estimation coefficient of the interaction between the dummy variable denoting membership of importer j to PTA k and the Asian status variable of exporter i. The estimation equation is thus: log Xij = log A + βi log Yi + βj log Yj + µi log Hi + µj log Hj + γ i log Ni + γ j log Nj + α log Dij + δ log Di + a ADJij + cIi + dIj + bkPkiPkj + Σ kk=1 bkPkiPkj + mkPkj + nkPki + mkAPkiASIAj + nkAPkj ASIAi + log ε ij (5) As noted above, Soloaga and Winters separate the effects of a PTA into two: first, the effect on trade diversion/augmentation (excess trade within the bloc relative to that predicted by gravity model factors) and second, general liberalization effects (excess imports and exports that members have to all countries whether they are members or not), alongside the non-PTA trade determinants included in the gravity model. Thus for each trade bloc k, Soloaga and Winters identify the extent to which bloc k is tradediverting, bk, as against promoting its members’ overall trade in general, (mk+nk). The total effect of the PTA k on its members’ trade is (bk+mk+nk) or the sum of trade diversion and overall trade effects. This applies to PTAs that include Asian and non-Asian members. Under our specification, the effect of PTA k on members’ trade with Asian members (above and beyond its trade with members in general) is given by: mk+nk+mkA+nkA. This comprises: (i) the effect on Asian imports from bloc k, regardless of whether Asian importers belong to PTA k or not (mk+mkA); and (ii) the effect on Asia’s exports to bloc k, regardless of whether the Asian exporters are members of PTA k or not (nk+nkA). D. Data and Estimation Issues The data used in estimating the gravity model comes from the International Monetary Fund’s (2001) Direction of Trade Statistics (DOTS). Eighty-three countries are included in the analysis, and bilateral exports for every pair of these countries are extracted from the DOTS database for the years 1980 to 2000.5 The number of observations varies per year, and because the model was estimated in logarithms, instances of zero trade between two countries were dropped from the datasets used in estimations.6 Dropping these cases from our estimation implies that our results should be interpreted as capturing the effect of PTAs on trade flows among trading countries, conditional upon the decision to trade having been made. It seems reasonable to assume that the source of truncation—the decision to not export at all to a particular country—is at best only slightly correlated with memberships in PTAs and geographic variables so that bias in the coefficients is minimal. This is clearly a second-best solution that affects the efficiency of the OLS estimates, but the alternative of explicitly modeling the decision to trade would, we feel, involve 5These 83 countries accounted for roughly 73 to 85 percent of total global exports during the period 1980 to 2000. 6Across the 83 countries included in our dataset, instances of no trade between pairs of countries accounted for between 16 and 20 percent of the total country pairs. Section IV Analyzing Trade Effects of PTAs Using a Gravity Model ERD Working Paper No. 30 ASIAN REGIONALISM AND ITS EFFECTS ON TRADE IN THE 1980S AND 1990S 24 to being negative and statistically significant in the 1990s. The associated expansion of intrabloc trade over time appeared to occur at the expense of member economies’ imports from the rest of the world. The estimates of the coefficients measuring the effect of membership on total exports were all positive and statistically significant in our estimates. C. PTAs Fostering Greater Intrabloc Trade and Greater Trade with the Rest of the World Membership in APEC and EU was estimated to significantly expand trade between members of the PTA as well as between members and to the rest of the world. These results are summarized on Table 5. The signs of the coefficients of variables capturing the effect of APEC membership on intrabloc trade and on total imports and exports are all positive and statistically significant. This suggests that APEC is achieving its goals of open regionalism and augmenting total trade. The results obtained in our estimates are consistent with those of Frankel (1997). As with Frankel’s estimate, our estimated coefficient for the intra-APEC export dummy variable is large and positive and is statistically significant. The tendency for greater intrabloc trade identified in the analysis was accompanied by strong tendencies toward greater trade with the rest of the world as well. While some researchers have argued that the size of the coefficient of the intrabloc variable for APEC obtained in Frankel‘s estimate was too high (Polak 1996), Frankel attributed the strong effect to the large share of total world trade accounted for by APEC member economies. He also noted the large coefficient estimate was not due to the inclusion of entrepôt economies, as his estimates excluded Singapore or Hong Kong, China from APEC’s to control for the effect “extra open” economies might have on estimates. Frankel concludes that the “APEC effect is genuine” and quoting Garnaut (1994), he maintains that the trade-augmenting impact identified for APEC is consistent with the type of integration “where the initiative has remained primarily with enterprises acting separately from state decisions, and where official encouragement of regional integration does not include major elements of trade discrimination.” Across the years for which the gravity model was estimated, the estimated effect of EU (in the 1980s) was positive although not statistically significant. All the estimates of the effect of EU membership on total imports and total exports are positive and statistically significant. These results differ from those of Soloaga and Winters (2001), which found that EU has fostered neither overall trade nor intrabloc trade, as would ordinarily be expected. Soloaga and Winters offer the explanation that deeper economic integration between member economies has reduced EU’s imports from nonmembers. The differences in these estimation results might be explained by differences in the data used to estimate the gravity model across the two: our study and the earlier one by Soloaga and Winters. Soloaga and Winters used data on imports while our estimates are based on exports data.9 Bayoumi and Eichengreen (1997) observed that the strong intrabloc effect of EEC in the 1980s appeared to have dissipated by the early 1990s. 9It is unclear how use of exports versus imports affects results, although Havrylyshyn and Pritchett (1991) noted some of their gravity model estimates changed depending upon whether they used data on imports or exports to estimate the model. 25 Our gravity model estimates indicate that CER had no incremental trade effect within or outside the bloc, and most of the estimation coefficients for this PTA were not statistically different from zero. Coefficients associated with trade flows between member countries are no higher than we would expect them to be given the size of countries’ economies and their proximity. The signs of the coefficients of the intrabloc and Asian export variables are almost all negative, except for 2000. In the estimates carried out using data from 2000, many coefficients are statistically significant and suggest CER did not divert trade. The coefficients for the variables capturing the effect of the PTA on total imports and exports are positive and statistically significant. Frankel’s (1997) estimation results for the intrabloc trade effect for CER differ from ours. He found the intrabloc trade effects of the PTA were positive and statistically significant. Frankel used total trade data, i.e., sum of exports and imports while we use export data, which may account for the different results obtained in the two studies. Differences in the model specification (e.g., exclusion of language dummy variables in our estimates and the use of several additional dummy variables to gauge the effect of PTA membership on trade included in our model) may also account for the different results obtained. D. PTAs that Reduced Gross Trade but did not Change Intrabloc Trade Significantly In our estimates, AFTA and NAFTA were PTAs that showed no effect in altering intrabloc trade but appeared to have reduced exports and imports between members and the rest of the world. The estimates obtained in this study for the coefficients of the intrabloc, overall import, and overall export variables for ASEAN are all not statistically significant. This adds yet another study with results for AFTA that disagree with those obtained in earlier research. Frankel (1997), for example, found membership in AFTA was associated with significantly more intrabloc trade than would otherwise have been expected. Soloaga and Winters (2001) found AFTA had a negative and statistically significant effect on intrabloc trade. A possible explanation for why the results of this study differ from earlier research is that the data used in our estimates included new members of ASEAN, namely Cambodia, Lao PDR, Myanmar, and Viet Nam; while the earlier estimates did not. As a group of countries that are less developed and less integrated into the global economy than the previous five member countries of ASEAN, their inclusion in the gravity model may have diluted the effect of ASEAN on its trade within and outside the PTA.10 Estimation results related to the effect of NAFTA on intrabloc trade and on the trade of member economies with the rest of the world failed to reject the null hypothesis that the PTA has no effect. Earlier studies (Frankel 1997, Soloaga and Winters 2001) had earlier documented a similar result, so consensus is building that NAFTA has not affected the trade orientation of its constituent economies. In our panel estimates, NAFTA membership was associated with lower although not statistically significant intrabloc trade. 10 Sensitivity analysis suggests that estimate results are robust to changes in the specification of the PTA membership variables, but that inclusion of new ASEAN members in the dataset did significantly influence estimation results. Section V Empirical Results ERD Working Paper No. 30 ASIAN REGIONALISM AND ITS EFFECTS ON TRADE IN THE 1980S AND 1990S 26 Our results suggest NAFTA members’ total exports and total imports were lower than expected, and that the negative effect grew stronger over time. Soloaga and Winters had obtained a similar result, that the coefficient for overall imports of NAFTA members was negative and statistically significant after 1986. This same study found the coefficients capturing the effect of the PTA on total exports of members went from being positive in the early 1980s (specifically, 1980 to 1983) to being negative in the period after 1984. The results of these two studies suggest that NAFTA members may be reducing their overall trade with the rest of the world. Although our results are essentially the same as those obtained in earlier research, what is new about our results is that we have reached this conclusion using the latest trade data. E. Gross Intrabloc Effect Table 6 summarizes the effects of PTAs on the trade flows with their members and nonmembers. The measure used is the anti-logarithm of the sum of the coefficients of the intrabloc, overall import and the overall export variables of the PTA minus one. Soloaga and Winters refer to this sum of these logarithms as the “gross intra bloc” effect. This exercise involves adding up the coefficients reported in Tables 3 through 5. Since not all of these coefficients are statistically significant, we accept the hypothesis that the coefficients having estimates that are not significant at a 95 percent confidence level or higher are equal to zero. The estimates of the total trade effects vary markedly across the PTAs treated in our model estimates. APEC, ECO, and Mercosur appear to be the PTAs having the greatest impact on members’ trade flows. At the other extreme, estimation results suggest AFTA and NAFTA have reduced the trade of their member economies. The overall effect of the 11 PTAs is an expansion of gross intrabloc trade by a factor of 7.8 according to our estimates. Earlier studies of the effects Table 6. Summary of Effects of PTAs on Intrabloc Trade Flows, and Imports and Exports of the Bloc with the Rest of the World 1980 1985 1990 1995 2000 Average AFTA 0.00 -0.41 -0.01 0.76 -0.64 -0.06 Andean Pact 5.50 1.28 4.46 14.15 16.45 8.37 APEC 2.58 13.34 28.07 20.94 25.95 18.18 CER 0.00 0.00 0.00 0.00 5.74 1.15 ECO 2.10 0.53 2.87 42.44 35.35 16.66 EFTA 0.37 0.35 0.22 0.96 1.15 0.61 EU 0.41 1.80 1.75 1.60 4.10 1.93 Mercosur 14.01 29.19 21.37 18.28 21.15 20.80 NAFTA -0.70 -0.79 -0.83 -0.84 -0.83 -0.80 SAPTA 7.71 4.84 4.44 4.79 4.85 5.33 SPARTECA 18.60 27.13 14.93 7.37 0.26 13.66 Overall Average 7.79 Source: Authors’ computation based on statistically significant coefficients on Tables 4 and 5. 27 of PTAs on trade flows that have applied gravity model estimates have obtained similarly large effects of PTA membership (e.g., Frankel 1997, Soloaga and Winters 2001). F. Effect of PTAs on Asian Trade Our estimation model included two additional variables to capture the effect of PTAs on the trade of Asian region as a whole. The estimated coefficients for the two dummy variables representing Asian imports from and Asian exports to each PTA are also reported in Tables 4 and 5. Overall, our results suggest that PTAs fall into two groups with respect to their effects on Asian trade. In the first group, which tended to have insignificant intrabloc trade effects and neutral impact on member economies’ trade with the world (i.e., AFTA and NAFTA), members generally had higher than expected levels of trade with Asia. The other PTAs, which displayed significant intrabloc trade effects and in some cases positive and significant effects on total trade, showed either no significant effects or negative and significant effects on trade with Asia. Considering PTAs as a whole, empirical estimates suggest trade in Asia has been augmented by the existence of PTAs, including both PTAs within the region as well as PTAs based in other regions. As summarized in Table 7, results provide little support for the assertion that PTAs have diverted trade to member countries at the expense of trade outside the PTAs. The measure of this trade diversion/augmentation used in Table 7 is the anti-logarithm of the sum of the estimated coefficients for overall import, overall export, Asian import, and Asian export dummy variables in equation 4 minus one.11 According to our gravity model estimates, the general effect of PTAs on trade in the Asian and Pacific region is small compared to the effect PTAs have in other regions. While some individual 11 The formula used is: Y = AXβ 10βj(a1D1+a2D2). Table 7. Summary of Effects of PTAs on Asia’s Imports and Exports with the Rest of the World 1980 1985 1990 1995 2000 Average AFTA 1.38 1.72 0.05 -0.33 0.75 0.71 Andean Pact 0.00 -0.65 -0.39 -0.67 -0.57 -0.46 APEC 1.09 0.77 2.36 2.01 1.47 1.54 CER 0.00 -0.60 -0.61 -0.66 -0.64 -0.50 ECO -0.44 0.53 2.87 -0.75 -0.64 0.31 EFTA -0.71 -0.48 -0.56 -0.23 -0.24 -0.44 EU -0.37 -0.08 -0.17 0.45 1.86 0.34 Mercosur -0.18 0.37 0.59 0.45 0.05 0.25 NAFTA 0.42 -0.54 -0.67 -0.56 0.09 -0.25 SAPTA 0.78 0.05 0.72 -0.01 0.54 0.42 SPARTECA 0.00 3.42 3.56 3.85 4.85 3.14 Overall Average (weighted to trade shares) 0.67 Source: Authors’ computation based on statistically significant coefficients on Tables 4 and 5. Section V Empirical Results ERD Working Paper No. 30 ASIAN REGIONALISM AND ITS EFFECTS ON TRADE IN THE 1980S AND 1990S 28 PTAs (e.g., Andean, CER, EFTA, and NAFTA) are estimated to reduce trade flows between Asia and the member economies, the overall net effect of the 11 PTAs was positive. The 11 PTAs treated in our estimations are found to be associated with a net expansion of trade within Asia and between Asia and other regions by a factor of 0.67 according to the gravity model estimates presented in this paper. The figures reported on Table 7 reflect the sum of the PTA’s effects on overall imports and exports, and on imports and exports between member economies and Asian and Pacific economies. In some cases (e.g., NAFTA), the positive effect of the PTA on Asian trade is outweighed by the negative effects on overall trade. In the case of CER, negative effects of PTA membership on overall trade flows and on trade flows between Australia and New Zealand, and on trade flows with Asian and Pacific countries combine to generate a stronger negative effect. The net influence of PTAs based in Asia’s subregions, namely those involving countries of the South Pacific and Oceania (SPARTECA), South Asia (SAPTA), and Southeast Asia (AFTA), appears to have been to induce expanded trade in the greater Asian and Pacific region. The effect of the EU on Asian trade suggested by estimates indicates a more complicated picture. The EU was estimated to have a strong positive effect on trade flows between member economies and the rest of the world—including trade to Asia. However, the specific effect of EU on Asian trade was found to be negative and statistically significant. Overall, the total trade effect dominates the Asia-specific effect, making the net effect of the EU on Asian trade positive. It is also worth noting that cross sectional estimation results suggest the net effect of the EU on Asian trade has grown more positive over the past two decades. Although not covered in our estimates, the new least developed countries initiative for EU member countries, which grants nonreciprocal trade preferences toward small and least developed countries, could carry negative consequences for the EU’s level of trade with Asian countries excluded from the arrangement. Trade between countries in the Asian and Pacific region and Mercosur member economies was estimated to have occurred at a rate higher than would be expected in the absence of the PTA. Lastly, estimates show the effect of ECO on Asian trade varied greatly across years of the cross sectional estimates, which likely reflects the widespread structural changes in the constituent economies during the 1980s and 1990s, but on average had a small positive effect on trade flows to and from the Asian region as a whole and Central Asia. G. PTAs’ Contribution to World Trade In Table 8, the effects of PTAs on world trade in general are summarized. The indicator used for this purpose is the anti-logarithm of the sum of the estimated coefficients of the intrabloc, overall import, overall export, Asian import and Asian export variables less one. In general the indicators are positive. Only CER and NAFTA appear to have reduced trade. It was discussed earlier that the effect of NAFTA on its members’ trade with the world was significantly negative and this effect dominated the bloc’s positive effect on Asia’s trade with its members. For CER, the negative effect of this PTA on its Asia’s exports to its members explain why CER’s effect on world trade is also to reduce its members’ trade with the world. Both NAFTA and CER have 29 insignificant effects on intrabloc trade. On average, world trade is increased because of PTAs by a factor of 2.4. This result of the gravity model analysis provides evidence that these PTAs create trade. VI. CONCLUSIONS In this study, we estimated a gravity model of bilateral trade involving 11 trading blocs most of which are from the Asian and Pacific region. The trade data used in estimating the gravity model is that of 83 countries from 1980 to 2000. The estimated coefficients of the basic determinants of the gravity model such as GDP, distance between capitals of trading partners, population, and physical area explain well cross-country trade flows. Our estimates of the effect of different PTAs on the trade flows between members vary remarkably across PTAs. Preferential trading agreements are categorized into three groups based on whether they tend to foster intrabloc trade, foster greater trade with trading partners worldwide, or reduce trade in general without changing their respective intrabloc trade. Andean Pact, ECO, EFTA, Mercosur, SAPTA, and SPARTECA belong to the first group in varying intensity with respect to promoting intrabloc trade. These tend to expand their trade among their respective members at the expense of their members’ imports from the world and exports as well, although in a few instances these PTAs have a positive effect on their exports to the world. Interestingly, these PTAs have the propensity to expand Asia’s trade. APEC, CER, and EU belong to the second group of PTAs that have expanded or have not changed at all their intrabloc trade, but this was not at the expense of their trade with the world. APEC and CER in particular illustrate the type of PTAs that adhere to open regionalism. EU, being in this list, is a surprise as other authors are of the view that EU is diverting trade toward its members. Table 8. Summary of Effects of PTAs on Total World Trade 1980 1985 1990 1995 2000 Average AFTA 1.38 1.72 1.20 0.76 0.75 1.16 Andean Pact 5.50 0.11 4.46 6.30 16.45 6.57 APEC 1.09 2.71 6.83 5.94 5.36 4.39 CER 0.00 -0.60 -0.61 -0.66 -0.64 -0.50 ECO 2.10 0.53 2.87 11.24 17.60 6.87 EFTA -0.30 0.35 0.22 0.96 1.15 0.48 EU -0.64 -0.49 -0.17 0.45 1.86 0.20 Mercosur 4.09 6.67 5.15 6.73 7.80 6.09 NAFTA 0.42 -0.54 -0.67 -0.56 0.09 -0.25 SAPTA 7.71 2.05 3.24 2.17 4.85 4.00 SPARTECA 18.60 57.56 41.01 68.47 63.51 49.83 Overall Average (weighted to trade shares) 2.42 Source: Authors’ computation based on statistically significant coefficients on Tables 4 and 5. Section VI Conclusions ERD Working Paper No. 30 ASIAN REGIONALISM AND ITS EFFECTS ON TRADE IN THE 1980S AND 1990S 30 AFTA and NAFTA are the PTAs that have not changed their intrabloc trade but reduced their overall trade with the world. While other authors have regarded AFTA as trade-creating, the result may be explained by the fact that in this analysis the bloc includes its new members. Earlier independent estimates had only included the original AFTA contracting parties. The new AFTA members are less integrated with the world economy as the founding members of this PTA. In this study, we introduced two new dummy variables that allow the analyst to measure the impact of PTAs on the trades of countries in the Asian and Pacific region, while retaining the innovation made by Soloaga and Winters (2001) to the empirical gravity model analysis. One variable is designed to capture the effects of PTAs on Asia’s imports from it. The other variable measures the impact of the PTA on Asia’s exports to the trade bloc. The resulting added feature of the gravity model makes possible the impact of PTAs on Asia’s overall trade. In summary, the PTAs in this analysis have contributed significantly to trade expansion both at the global and regional (Asian and Pacific) levels. The results obtained in this study provide evidence that PTAs can create rather than divert trade. These results suggest that PTAs offer a next-best path toward expanding world trade if negotiations for multilateral trade liberalization take a longer time to get completed. It will be important to follow macro-level cross-country research such as this paper with more focused studies on the dynamics of PTA members’ policies toward trade with the rest of the world and participation in multilateral trading agreements such as the WTO. One claim that could be tested, for example, is whether negotiating PTAs help developing countries gain experience with trade liberalization on a limited scale that later smoothes the way toward more general trade opening (Michalopoulos 1999). 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A Reassessment of Mankiw-Romer-Weil’s Test of the Neoclassical Growth Model —Jesus Felipe and John McCombie August 2002 No. 20 Modernization and Son Preference in People’s Republic of China —Robin Burgess and Juzhong Zhuang September 2002 No. 21 The Doha Agenda and Development: A View from the Uruguay Round —J. Michael Finger September 2002 No. 22 Conceptual Issues in the Role of Education Decentralization in Promoting Effective Schooling in Asian Developing Countries —Jere R. Behrman, Anil B. Deolalikar, and Lee- Ying Son September 2002 No. 23 Promoting Effective Schooling through Education Decentralization in Bangladesh, Indonesia, and Philippines —Jere R. Behrman, Anil B. Deolalikar, and Lee- Ying Son September 2002 No. 24 Financial Opening under the WTO Agreement in Selected Asian Countries: Progress and Issues —Yun-Hwan Kim September 2002 No. 25 Revisiting Growth and Poverty Reduction in Indonesia: What Do Subnational Data Show? —Arsenio M. Balisacan, Ernesto M. Pernia, and Abuzar Asra October 2002 No. 26 Causes of the 1997 Asian Financial Crisis: What Can an Early Warning System Model Tell Us? —Juzhong Zhuang and J. Malcolm Dowling October 2002 No. 27 Digital Divide: Determinants and Policies with Special Reference to Asia —M. G. Quibria, Shamsun N. Ahmed, Ted Tschang, and Mari-Len Reyes-Macasaquit October 2002 No. 28 Regional Cooperation in Asia: Long-term Progress, Recent Retrogression, and the Way Forward —Ramgopal Agarwala and Brahm Prakash October 2002 No. 29 How can Cambodia, Lao PDR, Myanmar, and Viet Nam Cope with Revenue Lost Due to AFTA Tariff Reductions? —Kanokpan Lao-Araya November 2002 No. 30 Asian Regionalism and Its Effects on Trade in the 1980s and 1990s —Ramon Clarete, Christopher Edmonds, and Jessica Seddon Wallack November 2002 40 SERIALS (Co-published with Oxford University Press; Available commercially through Oxford University Press Offices, Associated Companies, and Agents) 1. 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