The BIMSTEC FTA and Its Relevance

Discussion Paper #36 The BIMSTEC FTA and Its Relevance Nilanjan Banik Centre for Studies in International Relations and Development (CSIRD) Kolkata The BIMSTEC FTA and Its Relevance Nilanjan Banik CSIRD Discussion Paper #36 October 2007 Centre for Studies in International Relations and Development P 534 Raja Basanta Roy Road, Kolkata 700029, India Phone: +91-33-2463 7322 Fax: + 91-33-2463 7322 Email: [email protected]; [email protected] Websites: http://www.csird.org.in; http://www.bntt.org CSIRD Discussion Papers are published to disseminate research findings and to attract comments. The feedback and comments may be directed to the author(s) directly. Views expressed by the author(s) are his / her personal, and in no way reflect the views of CSIRD. CSIRD Discussion Papers are available at www.csird.org.in Contents 1. Introduction .............................................................................. 1 2. Why more trade? ...................................................................... 2 2.1 Criteria for a successful RTA ....................................... 3 3. How well BIMSTEC members’ fit into these criteria? ............ 6 4. Model ................................................................................ 10 5. Results and Analysis .............................................................. 14 6. Concluding remarks ............................................................... 15 Appendix ................................................................................ 16 References .............................................................................. 17 The BIMSTEC FTA and Its Relevance Nilanjan Banik* Abstract: In this article we attempted to determine to what extent BIMSTEC economies are ready to form an FTA. The present analysis suggests that the BIMSTEC region has the requisite characteristics that would be desirable to form an FTA. We based our analysis on the basis of few criteria, such as, price, income, geographical characteristics, and trade, as an indication for forming an FTA. In general we found there are favorable indications for the BIMSTEC economies to flourish into a successful RTA. Forming an FTA would be expected to create relative advantage for the member countries. JEL Classification: C33 and F13 Key Words: Growth, Trade, RTA, BIMSTEC 1. Introduction A newly formed economic cooperation bloc between Bangladesh, India, Myanmar, Sri Lanka, Thailand, Bhutan and Nepal is gathering attention. Better known as BIMSTEC, the initiative for this economic cooperation, was undertaken in 1997. BIMSTEC was formed with the idea of imparting greater economic cooperation among the member nations in the area of technology, transport and communications, energy, tourism, agriculture, fisheries and human resources development. In addition to the sectoral cooperation, BIMSTEC also wanted to strengthen cooperation in the areas of trade and investment. * Associate Professor, Center for Advanced Financial Studies (CAFS), Institute of Financial Management Research, Chennai. An earlier version of the paper was presented by the author at the 2nd International Conference on BIMSTEC-Japan Cooperation, organized by CSIRD and TDRI, supported by Sasakawa Peace Foundation (SPF), Tokyo, held at Bangkok, during 7-8 December 2006. For any further queries please correspond through [email protected] Author is grateful to the discussants and participants of the aforesaid conference for their comments. The views expressed are entirely personal. Usual disclaimers apply. 2 All the seven BIMSTEC members have agreed to set up a Free Trade Area (FTA) by July 2007. Negotiations on FTA regarding services and investment have begun in January, 2007. During the last two decades, regional trading agreements (RTAs) have gained increased prominence. Repeated failures of multilateral negotiations, especially at various ministerial meetings of WTO, has lead to an increase in the number of RTAs. Also, increased internationalization of markets (i.e. globalization) and the fear of losing out to other inefficient producers have put pressure on individual country to become part of an RTA. Around 220 RTAs were notified at the World Trade Organization (WTO) till 2006. Most of the developing countries are now a member of one or more RTAs. Compared to South Asian Free Trade Area (SAFTA), BIMSTEC FTA seems to be more promising. A deeper economic integration process with in the South Asian Association of Regional Cooperation (SAARC) sometime suffers because of political tension among some of its members. Such things are less likely to happen in case of BIMSTEC. It is believed that negotiation under BIMSTEC umbrella will be easier than under SAFTA because all the BIMSTEC members are purely guided by economic interests rather than by political interests. In view of above, the purpose of this paper is to analyze whether BIMSTEC is likely to emerge as a success story in terms of greater flow of goods and services in the South East Asia. We base our analysis on the basis of the following factors: prices, income, trade barriers (tariffs and non-tariffs barriers), economic structure, and geographical characteristics of the BIMSTEC member countries. These factors are essential in shaping up formation of a successful RTA. 2. Why more trade? Success of an RTA is measured in terms of increased flow of goods and services. The more the economies trade among themselves the greater will be the tendencies for further economic integration.1 Since 3 trade affects growth, a greater flow of goods and services are likely to see less opposition in the way of economic integration. Trade affects growth in three primary ways. First, trade encourages flow of resources from low productive sectors to the high productive sectors, leading to an overall increase in output. Export growth may affect total productivity growth through dynamic spillover effects on the rest of the economy (Feder, 1983). The possible sources of this positive dynamic spillover include more efficient management styles, better forms of organization, labor training, and knowledge about technology and international markets (Chuang, 1998). Second, with unemployed resources, an increase in export sales lead to an overall expansion in production and a fall in unemployment rate. As production increases, firms because of increase in scale of operation (economies of scale) become more efficient (Helpman and Krugman, 1985). Third, international trade also allows for the purchase of capital goods from foreign countries and exposes an economy to technological advances of the developed countries. Recent theoretical work suggests that capital goods import from technologically advanced countries may increase productivity and thereby growth, since knowledge and technology is embodied in equipment and machinery and therefore transferred through international trade (Chuang, 1998). 2.1 Criteria for a successful RTA Despite these positive aspects, free trade is opposed mainly because workers and producers associated with the inefficient industries stand to lose out. There are considerable amount of lobbying pressure by the inefficient producers demanding more protection. As raising tariff barriers is not allowed under the WTO framework, individual governments try to protect their respective economies by imposing non-tariff barriers (NTBs), like, antidumping measures, import license, sanitary standards, among others. The answer to a successful RTA therefore lies in controlling the factors that act against RTA, and nurturing the factors which helps forming and sustaining a RTA. Some of the factors that affect formation of an RTA are considered below. 4 Intra-industry trade: RTA is more likely to happen when trade happens in similar commodities, that is, intra-industry trade. The likelihood that industry association will demand more protection is less in case of intra-industry trade. In presence of intra-industry trade (for example, India exporting TATA Indica cars to the US and at the same time importing FORD cars from the US), adjustment cost associated with removing trade barriers are lower. In this case jobs lost due to customers shifting to more efficient foreign suppliers may to a large extent be offset by the job enhancing expansion in foreign demand for similar, differentiated good produced domestically. The political opposition to liberalizing and expanding intra-industry trade tends to be far less when compared to trade involving in dissimilar items, that is, inter-industry trade. Country characteristics: Economies that are similar in terms of size are better candidates for forming an RTA. Similarities are measured in terms of economic development and geographical proximities. The more similar are the economies, the more is the likelihood of intra-industry trade. This is because geographically near economies with similar level of economic development have access to similar kind of technology. Consequently they tend to produce more or less similar items and tend to trade in similar commodities (closely differentiated products as in the monopolistic competition type market structure). As the literature on gravity model on trade demonstrates, similarities in economic structure and geographical distance between respective economies are powerful determinant of trade (Linneman, 1966; Frankel et al., 1995; and Frankel, 1997). Trade increases with economic size and proximity of the trading partners. Prices: Low technology intensive items, like, leather footwear, garments, gems and jewellery, textile products, etc., which are typical of any developing country’s exports profile are very much sensitive to movement in prices, i.e. are price elastic. When it comes to form an RTA, countries analyze whether such an arrangement will enable them to realize a greater demand for their exports. From the demand-side perspective, it can be argued that sustained demand growth cannot be maintained in a small domestic market, since any economic impulse 5 based on expansion of domestic demand is bound to be exhausted. However, export markets do not exhaust quickly. An RTA not only provides a platform for a greater market share but also enable countries to produce efficiently. As the literatures on monopolistic competition suggest, a way to produce exports competitively is to take advantage of economies of scale in production which can be realized from a greater market share resulting from an RTA (Helpman and Krugman, 1985; Leamer, 1984). Government policies: A more liberal government policies is likely to be beneficial for an RTA. There is a general consensus in the literature that trade volume, both exports and imports, increase following external sector liberalization (Agosin, 1991; Bertola et al., 1991; Kohli, 1991; Clarke et al., 1992; Joshi et al., 1996). 2 Both the imports and exports of a country tend to increase with external sector liberalization. Under small country assumption, a fall in tariff barriers reduces the price of imports and cause imports to rise. Exports also increase and this is true whether the economy has a fixed, or, flexible exchange rate regimes. Under flexible exchange rate regimes when the economy opens up, first its imports rise. An increase in imports causes a relative increase in the supply of domestic currencies vis-à-vis the foreign currencies. This happens because foreign currencies are used to finance imports. With flexible exchange rates the value of domestic currency is market determined; an excess supply causes it values to depreciate. This means the price of exports for this economy falls; causing exports to rise. Under fixed exchange rate regimes, increase in exports happen in a different way. First, because of liberalization imports increase. However, market price of domestic currency does not fall as it is fixed now. An increase in imports release resources from the import competing sectors. A considerable portion of these resources find their use in the export sectors. As a result production of exports increases. Exports price falls, partly because of increase production and partly because inputs prices are cheaper with more coming from the import competing sectors. Exports increase. Higher trade volume, resulting from external sector liberalization, is expected to increase the likelihood of an RTA formation. 6 Geographical characteristics: This factor acts a catalyst; and can have an accelerating effect on any country’s trade. Like trade affect growth, geographical characteristics of a region can also affect growth. Although a country’s geographical characteristics is not influenced by government policies but it can have an important effect on a country’s income by its influence on trade. Thus, countries’ geographical characteristics can be used as another variable to measure the impact of trade on income. For instance, one can argue one of the reasons for Nepal to trade less and hence poor (per capita wise) relative to Thailand is because the former is mountain-locked and have no coastline in comparison to the latter. Thus, countries with more favorable geographical characteristics are more likely candidates for an RTA. 3. How well BIMSTEC members’ fit into these criteria? Given the discussion about the aforementioned criteria necessary to form an RTA in general, it is of interest to examine future prospect of the BIMSTEC area against these criteria. Economic characteristics: When compared in terms of their economic structure, namely, value addition of services, industry, and agriculture sector, to Gross Domestic Product (GDP), BIMSTEC nations have many similarities. Except in case of Thailand, the industrial sector constitutes roughly a fourth of GDP in all countries. All these economies are predominantly associated with service related activities. Although majority of the population still lives in the rural areas, all of these nations are becoming increasingly urbanized. Geographical proximity along with similar economic profile indicates similarity in consumption, production, and trading pattern. Going by the argument of monopolistic competition (intra-industry trade and economies of scale) all these economies stand to gain the more they trade among themselves. Trade: Presently trade in the BIMSTEC region is low. One of the reasons for lower trade has to do with the closed nature of the BIMSTEC economies. Most of the BIMSTEC member countries have lower trade-GDP ratio and have initiated external sector liberalization 7 (that is, bringing down tariff barriers) only starting early nineties.3 Presently, there also exists a large number of NTBs in the region. The NTBs include procedural requirements, sanitary standards, certification and technical standards (Kelegama, 2001; Mukherji, 1997). The encouraging point is that most of these economies have started to open-up and have also registered healthy growth. During 2003-2004, all BIMSTEC countries, except Nepal, witnessed strong economic growth in the range of 5-13 percent as well as 4-5 percent per capita GDP growth. As McCombie and Thirlwall (1997), Paulino (2002), and Paulino and Thirlwall (2004) have pointed out, a robust economic growth encourages a more liberalized trade regime. With similar exports profile, trading partners are better-off by placing less restriction. Because countries in BIMSTEC share a similar exports profile they also face same types of NTBs; and hence share a similar negotiating stance for removing these barriers. Recent trend in trade data reflect this. India’s trade with other developing countries like, Brazil, Sri Lanka and Thailand are on the rise. Exports in the BIMSTEC region have increased from US$ 105 billion in 1999-2000 to US$ 198 billion in 2005-2006; whereas imports grew firmly from US$ 103 billion in 1999-2000 to US$ 215 billion in 2005-2006. Since early nineties, Indian industries have started enjoying economies of scale (Barua and Chakraborty, 2004). Therefore, there are indications that the present low intra-BIMSTEC trade is likely to flourish in the future. Prices, Income, External Sector Liberalization, and Geographical Characteristics: To ascertain the importance of these factors in fostering an RTA, we did an econometric analysis in the context of BIMSTEC. In general, we found statistically significant coefficients associated with price, income and geographical characteristics. A statistically significant price coefficient implies that trade in the region will flourish provided the products are price competitive and there is no market access problems related to NTBs. A statistically significant income coefficient ascertains that higher GDP growth will encourage a more liberalized trade regime in the region. A statistically significant external sector trade liberalization dummy implies that liberal government trade policy has an important role in increasing trade. Lastly, statistically significant geographical 8 Table 1: Intra-BIMSTEC trade during 2003! Exports To: Bangladesh Bangladesh Bhutan India Japan Myanmar Nepal Sri Lanka Thailand Bhutan India Japan Myanmar 2.38 55.34 51.49 2.44 2.98 1976.00 2396.00 247.01 126.89 328.76 6.52 245.05 160.98 641.00 11435.00 73.00 125.00 217.00 13.00 0.24 439.00 1.66 28.00 1358.00 428.00 30.21 4.42 11.17 273.00 4.00 10.00 Bangladesh Bhutan India 3.84 1494.22 Nepal Sri Lanka Thailand World 9.45 6229.40 957.00 799.00 375.00 16043.00 1.36 831.65 0.22 1.24 11.54 161.00 60641.00 473911.00 2641.70 649.40 5133.30 80521.00 5.80 Imports From: Bangladesh Bhutan India Japan Myanmar Nepal Sri Lanka Thailand ! 61.00 131.00 2.68 3.28 5.64 30.00 Figures are in millions U.S. dollars Source: CSIRD, India. 29.00 Japan Myanmar Nepal Sri Lanka 566.70 33.23 4.86 2636.00 2174.00 76.49 136.96 228.29 14.43 1076.16 448.13 879.00 18266.00 259.00 140.00 345.00 7.00 2.29 915.00 0.19 1.00 Thailand World 176.56 9672.30 227.00 706.00 193.00 11890.00 0.37 483.39 1.18 30.57 145.89 8.00 85294.00 383025.00 3204.90 996.60 6671.90 75809.00 9.24 Table 2: Economic Structure of the BIMSTEC Countries Country GDP Avg. annual % growth Sectoral Composition of Output (GDP) Agriculture Value Added Industry Value Added Services Value Added 2000-04 1995 2004 1995 2004 1995 2004 Bangladesh 5.1 31 21 18 27 52 53 India 6.2 29 22 29 26 41 52 Nepal 2.6 42 40 22 23 36 37 Sri Lanka 3.8 23 17 25 25 52 58 Thailand 5.3 11 10 40 44 49 46 Source: World Bank (2005), World Development Report, New York, Oxford University Press. 9 10 characteristics coefficients’ imply to facilitate trade there is a need to develop infrastructure in the BIMSTEC region. A country with miles of coastline without any port facilities will not be much different when compared with countries without any coastlines. Here, infrastructure is seen as a factor complementing trade flow in the region. There is a need for the BIMSTEC countries to invest resources for development of infrastructure. Since some of the countries are resource poor – during 2005, annual per capita GDP (measured in constant 2000 US $) for Bangladesh and Nepal were US$ 410 and US$ 256, respectively – there is a need for foreign capital. In order to attract increased intraregional Foreign Direct Investment (FDI) and portfolio investment flows, member countries should further strengthen macroeconomic conditions and liberalize and harmonize investment regime. 4. Model In the following we estimate exports functions of the BIMSTEC member countries. The literature generally agrees about the empirical specifications of the demand and supply functions for imports and exports (Leamer and Stern, 1970; Magee, 1975). The demand for imports (M) is a function of domestic real income (GNP), the price of imports in domestic currency (PM) relative to the domestic prices (P), and the ratio of reserves (R) to imports lagged one period. There is considerable evidence available that many developing countries’ capacity to import is constrained by the stock of real international reserves and hence the idea behind including reserves as an explanatory variable (Khan and Knight; 1988). It is expected to have a positive coefficient, as higher international reserves increases the ability of the country to import more. The relative price variable is expected to have a negative sign; a higher price implies a lower amount of imports demanded. The variable domestic real income is expected to have a positive coefficient; demand for imports are expected to increase with an increase in domestic real income. Under the assumption that the world supply of imports is infinitely elastic, we need not have to specify the supply function of imports (Khan and Knight; 1988). The foreign demand for exports is determined by the world real income (GNPW) and the ratio of exports 11 price (PX) to the price of foreign substitute (PW). The coefficient on world real income is expected to have a positive sign; demand for exports is expected to increase with a stronger world real income. Similarly, the coefficient on the price variable is expected to have a negative sign; foreign demand for exports will fall when the price of exports increase. The supply of exports will depend on price of foreign substitute (PW) relative to domestic price (P), stock of fixed capital (K) and a term representing the role of imports in exports supply (M.PM / PX). Exporters are willing to supply more when exports price increase. Accordingly, the price variable in the export supply equation is expected to have a positive coefficient. Similarly, more capital stock, and more importable inputs used for exports, means a higher supply of exports. Hence, the coefficients of these two variables are expected to have positive coefficients. We assume that the adjustment of import demand, export demand and export supply to changes in prices and income are not instantaneous, so we included lagged endogenous variables for the dynamic specification of the system. The other modification of this basic model is the introduction of our measures of geographical characteristics in the import demand and the export supply equations. Two basic measures of geographical characteristics are considered in this study. The first measure is the miles of coastline. The second measure is the area of land as a percentage of total surface area that a country shares border with other countries. Our assumption is that the geographical characteristics variables, namely, miles of coastline (C) and proportion of border lands (L), will facilitate trade and hence expected to have positive signs. We do not introduce these variables in the export demand equation, as the foreign demands for any country’s exports depends upon relative price competitiveness and not on the country’s geographical characteristics. We include dit as the external sector liberalization dummy variable to capture the effect of liberalization on any country’s export. Accordingly, the dummy take values 1 for the years following trade 12 liberalization and values 0 otherwise. As, data on import tariff does not change much in the short run (because tariff commitments is a long run phenomenon), we took the difference between consumer price index (CPI) in the exporting country and that in the US economy as a proxy to capture the effect of trade liberalization on exports. This way of estimation (i.e. taking CPI difference as a proxy of liberalization) is indicated in some studies published from Institute for International Economics. It also makes sense to incorporate CPI difference as a proxy for trade liberalization. Going by the “law of one price” theory, as any individual countries bring down its tariff barriers, world price and domestic price of tradable tends to equate with one another. The model is log linear, with price and income coefficient reflecting the respective elasticities. Thus, the equations can be written as: where, i denotes countries; t denotes time periods;; denotes the general equation specific errors. If is observed for all countries, then the entire model can be treated as an ordinary linear model and fit by least squares. For the purpose of estimation, we consider the classic pool model and the within 13 Table 3: Import and Export Growth Incorporating Geographical Characteristics! 2SLS 3SLS Within 2SLS Within 3SLS -0.131 (-1.10) -0.095 (-0.91) _ _ PM Log — P 0.005 (0.27) 0.006 (0.32) -0.025 (-1.36) -0.055** (-1.76) LogGNPit 0.017** (1.80) 0.045** (1.86) 0.789* (4.93) 0. 770* (5.34) LogMit-1 0.969* (46.38) 0.864* (47.69) 0.720* (10.60) 0.527* (11.45) R Log — M 0.051* (3.73) 0.049* (3.72) 0.029* (2.09) 0.039* (2.87) Log(C) 0.008** (1.76) 0.006 (1.37) _ _ Log(L) 2.846** (1.84) 3.481** (1.72) _ _ d 3.225* (2.85) 4.552* (2.98) _ _ AdjR2) 0.978 Import Demand (M) Intercept [ ] [ ] 0.834 Export Demand (X) Intercept -4.271 (-1.23) -2.225 (-1.42) _ _ PW Log — P Log(GNPW) -1.726* (-1.99) -2.615* (-2.16) -2.755* (-2.05) -2.782* (-4.27) 1.930 (1.52) 1.762** (1.74) 0.277 (1.64) 0.295* (4.17) LogX-1) 0.999* (122.64) 0.998* (123.00) 0.940* (15.76) 0.907* (20.02) AdjR2) 0.989 0.088 (0.50) 0.086 (0.88) _ _ -0.023** (-1.93) -0.004 (-0.51) -0.033 (-1.31) -0.0006 (-0.06) LogK 0.017* (2.70) 0.005* (2.07) 0.084 (1.04) 0.043 (1.08) LogX-1 0.846* (28.68) 0.937* (48.34) 0.766* (12.11) 0.904* (20.30) Log(M.PM/ PX) 0.158* (5.29) 0.062* (3.35) 0.208* (3.72) 0.085* (2.64) Log(C) 0.015* (3.37) 0.004* (1.81) _ _ Log(L) 4.535* (2.11) 2.39* (1.98) _ _ AdjR2) 0.992 [ ] Export Supply (X) Intercept [ ] PW Log — P ! 0.799 Figures in parentheses ( ) are t-ratios. ** Indicates that a coefficient is significant at the 10 % level and *significant at 5 % level. 14 transformation model. If contains only a constant term, then the ordinary least squares estimation provides consistent and efficient estimates of the common intercept terms and the slope vectors. This is a classic pool model (also known in the literature as least square dummy variable model). Another variant of the fixed effects model is within transformation model. Here the pooled regression is reformulated in terms of deviation from the series means leading to disappearance of the intercept terms and the dummies. This model is more efficient than models with dummy variables as it gives n degrees of freedom (corresponding to relevant dummies and the intercept term) back with same parameter estimates. For estimation, we have data for seven countries in the BIMSTEC region covering the period between 1990 and 2005. However, for the entire time period (1990-2005) not all the variables could be found for all the sample countries, leading to unbalanced panel data set. In total we have 85 data points. To avoid possible heteroscedasticity in errors all the quantitative variables are expressed in per-capita terms. Precise definitions of variables along with the source are listed in the Appendix. There are three endogenous variables in the system, which are Log(X), Log(M) and Log(PX) . Table 3 summarizes estimates of all of the parameters, using classic pooled 2SLS, classic pooled 3SLS, within transformed 2SLS and within transformed 3SLS. 5. Results and Analysis All the estimates have theoretically estimated correct signs, except in PW one case where the coefficient of Log — P has come out with negative sign. Importantly, the geographical characteristics variables have statistically significant coefficient in three out of four cases, suggesting that they have important role in facilitating trade. Based on the within estimates, we find the income elasticity for the demand for exports are 1.93 (2SLS) and 1.76 (3SLS) respectively. Similarly, long run price elasticity demand for exports are -1.72 (Classic Pooled 2SLS) and -2.61 (Classic Pooled 3SLS). Hence, both income and price competitiveness of exports are important factors in determining exports [ ] 15 performance of BIMSTEC countries. A statistically significant external sector trade liberalization dummies indicates that intra-BIMSTEC trade is going flourish more with the removal of tariff and NTBs. 6. Concluding remarks As evident from the above discussion, BIMSTEC region has many characteristics that would be desirable to form an FTA. We based our analysis on the basis of few criteria, such as, price, income, economic and geographical characteristics, and trade, as an indication for forming an FTA. In general we found there are favorable indications for the BIMSTEC economies to flourish into a successful RTA. Forming an FTA would be expected to create relative advantage for the member countries. Greater economic cooperation among BIMSTEC member nations has important implications in the form of larger market, economies of scale in production, and improved resource allocation. 16 Appendix Data Definitions and Sources The sources of data are: (a) IMF, International Financial Statistics and (b) World Bank, World Development Indicators. X : Per capita nominal exports in (constant 1995 US$); source (b). M : Per capita nominal imports in (constant 1995 US$); source (b). R ) : Official foreign reserves (constant 1995 US$) divided by (– M nominal imports per capita; source (b). GNP : Per capita Gross Domestic Product (constant 1995 US$); source (b). K : Per capita Gross Fixed Capital (constant 1995 US$); source (b). GNPW : Per capita real GNP for the World; source (b). PX : Unit value of exports (US$), 1995 = 100; source (a). PM : Unit value of imports (US$), 1995 = 100; source (a). PW : Unit value of exports of the continent of the originating country (US$), 1995 = 100; source (a). P : Domestic Consumer Price Index, 1995 = 100; source (a). POP : Population; source (b). 17 Endnotes 1 2 3 There are four different forms of regional trading agreements, namely, FTA, custom unions (CU), common markets (CM) and economic unions (EU). In forming FTA, members remove trade barriers among themselves but keep their separate national barriers against trade with outside nations. In a CU, members not only remove trade barriers among themselves but also adopt a common set of external barriers. In a CM, members allow full freedom of factor flows (migration of labor and capital) among themselves in additionto having a CU. In an EU, members unify all their economic policies, including monetary, fiscal and welfare policies, while retaining features of a CM. A deepening of economic integration means member countries graduating from FTA to CU; thereafter from CU to CM; and finally from CM to EU. In the trade literature, external sector liberalization is also known as trade liberalization. It means reduction in tariff barriers, phasing out of NTBs, like quotas, import license, etc., export promotion and a move towards a market determined exchange rates. The only exception being Thailand undertaking external sector liberalization during early seventies and Sri Lanka initiating liberalization starting 1977. References Agosin, M. (1991), ‘Trade policy reform and economic performance: a review of the issues and some preliminary evidence’, UNCTAD Discussion Papers, No. 41, Geneva, Switzerland. Barua, A. and Chakraborty, D. (2004), ‘Liberalization, trade and industrial performance in India: an empirical study’, paper presented in the Seminar entitled ‘WTO negotiations: India’s post-Cancun concerns’ jointly organized by Planning Commission and International Trade and Development Division, JNU. Bertola, G. and Faini, R. (1991), ‘Import demand and non-tariff barriers: the impact of trade liberalization’, Journal of Development Economics, Vol. 34, 269-86. Chuang, C. (1998), ‘Learning by doing, the technology gap, and growth’, International Economic Review, Vol. 39, 697-721. Clarke, R. and Kirkpatrick, C. (1992), ‘Trade policy reform and economic performance in developing countries: assessing the empirical evidence’, in (R. Adhikari, C. Kirkpatrick and J. Weiss, eds.), Industrial and trade policy reform in developing countries, Manchester: Manchester University Press. Feder, G. (1983), ‘On exports and economic growth’, Journal of Development Economics, Vol. 12, 59-73. Frankel, Jeffrey A., Stein, E., and Wei, S. (1995), ‘Trading blocs and the Americas: The natural, the unnatural, and the supernatural’ Journal of Development Economics, Vol. 47, 61-95. Frankel, Jeffrey A. (1997), ‘Regional trading blocs in the world trading system’, Washington, DC: Institute of International Economics. 18 Goldstein, Morris and Khan, Mohsin S. (1978), ‘The supply and demand for exports: A simultaneous approach’, Review of Economics and Statistics, Vol. 60, 275-86. Helpman, E. and Krugman, P. (1985), ‘Increasing returns, imperfect competition, and international trade’, Cambridge, MIT Press. Joshi, V. and Little, I.M. D. (1996), ‘India’s Economic Reforms 1991-2001’, Oxford: Oxford University Press. Kelegama, S. (2001), ‘Bangkok agreement and BIMSTEC: crawling regional economic groupings in Asia’, Journal of Asian Economics, Vol 12, 105121. Khan, Mohsin S. (1974), ‘Import and export demand in developing countries’, IMF Staff Papers, 678-693. Khan, Mohsin S. and Knight, D. M. (1988), ‘Import compression and export performance in developing countries’, The Review of Economics and Statistics, Vol. 20. 315-321. Kohli, U. (1991), ‘Technology duality and foreign trade’, Ann Arbor: University of Michigan Press. Leamer, E. (1984), ‘Sources of comparative advantage: theory and evidence’, Cambridge, MIT Press. Leamer, Edward E. and Stern, Robert M. (1970), ‘Quantitative International Economics’, (Boston, MA: Allyn and Bacon). Linneman, H. (1966), ‘An econometric study of international trade flows’, Amsterdam: North Holland, 1966. Magee, S. P. (1975), ‘Prices, income and foreign trade: A survey of recent economic studies’, in Peter B. Kenen (edited) International Trade and Finance: Frontiers for Research (Cambridge, England: Cambridge University Press). McCombie, J. and Thirwall, A.P. (1997), ‘The dynamic foreign trade multiplier and the demand oriented approach to economic growth: an evaluation’, International Review of Applied Economics, Vol 11, 5-26. Mukherji, N, I. (1997), ‘Strengthening the Bangkok Agreement as a regional mechanism for promoting cooperation in trade: country report – Thailand and Myanmar’, ESCAP. Paulino, A. (2002), ‘The effects of trade liberalization on imports in selected developing countries’, World Development, Vol. 30, No. 6. 959-974. Paulino, A. and Thirlwall, A. P. (2004), ‘The impact of trade liberalization on exports, imports and the balance of payments of developing countries’, The Economic Journal, Vol. 114, 50-72. 19 Centre for Studies in International Relations and Development The Centre for Studies in International Relations and Development (CSIRD) is a non-profit research organization which seeks to carry out policy-related work in the field of international relations and development cooperation. It aims to grow into a leading think tank to promote policy issues related to globalisation, trade and development. CSIRD emerged out of a recognised need for an institution that would give a distinct shape to the realisation of a shared future for the World. It is an organisation involved in addressing issues of multilateral, regional, bilateral and national concern to our society. The work of CSIRD is published in the form of research papers, books, working papers, monographs and journals. Centre for Studies in International Relations and Development P 534 Raja Basanta Roy Road Kolkata 700029, India Phone: +91-33-2463 7322 Fax: + 91-33-2463 7322 Email: [email protected]; [email protected] Websites: http://www.csird.org.in; http://www.bntt.org