IMPACTS OF TRADE LIBERALIZATION ON THE WORLD SUGAR MARKET
This document was prepared by the Economic Research Service (ERS) of USDA for the Sugar and Beverages Group, Commodities and Trade Division. Tables have been left out due to space limitation.
Sugar is an important commodity in the world agricultural market with a annual average production of 120.1 million tons, consumption of 118.1 million tons, and a world trade equal to 28 percent of production for the period from 1994 through 1996 (USDA, 1997). Sugar is produced under a broad range of climatic conditions in some 120 countries and is one of the most heavily traded agricultural commodities. Like the international trade of other major agricultural commodities, sugar trade has several distinguished characteristics that include heavy government intervention, large price fluctuation, widespread production in many parts of the world, and a growing market for sugar substitutes. These features make the world sugar market a vital target for policy analysis, although they also pose considerable modelling difficulties.
Sugar is produced from sugarcane and sugarbeet. Sugarcane is mostly grown in tropical and sub-tropical regions and sugarbeet predominantly grown in temperate regions. So that sugar is produced in many parts of the world. However, sugarcane accounts for approximately 60 percent of total production of centrifugal sugar which contributes basically all of international trade. In general, many sugar producing countries, except the United States and Australia, are developing countries and cost of sugar production appears to be relatively lower in the low-income than in the high-income countries (Devadoss and Kropf, 1996). More importantly, those developing countries export and compete directly in the world sugar market. As a result, the developed countries such as the United States, Japan, Canada, and European Union (EU) heavily subsidized sugar crop producers, often at the expense of domestic consumers. The total costs to consumers, according to previous studies (Borrell and Duncan 1993, Roberts and Whish-Wilson 1991, and Sturgiss, Tobler, and Connell, 1988), surpassed 2 billions of dollars annually in those countries.
Sugar policies, for instance government intervention by developed countries, induced significant loss on low-income sugar exporting countries as they exporters experienced lower world prices and likely lower production and reduction in employment opportunities (Devadoss and Kropf, 1996). Several previous research studies also concluded that developed countries' sugar policies have made sugar markets among the most distorted of all agricultural commodity markets and have caused significant global economic welfare losses (Marks and Maskus, 1993). However, the trade liberalization called by the Uruguay Round (UR) of the General Agreement on Tariffs and Trade (GATT)/the World Trade Organization (WTO) should lead to an improved world resource allocation by shifting sugar production to more efficient areas. Other regional trade liberalization agreements currently under discussions among APEC and ASEAN member countries of which many are important sugar traders also will provide significant impacts on world sugar production, consumption and trade. As UR policy provisions are implemented and APEC and ASEAN trade liberalization policies are carried out, it is important to sugar exporting and importing countries to assess the effects of these trade reforms on their sugar markets.
The objective of this study is to use a Computable General Equilibrium (CGE) framework that includes a majority of the sugar producing and trading countries to quantify the effects of the trade liberalization agreements negotiated under the UR on sugar production, consumption, trade, and prices of the major sugar exporting and importing countries. This study further assumes that if only APEC or ASEAN member countries liberalize their sugar related policies, or even a complete world trade liberalization, how each of the changes would affect the world sugar production, consumption, and trade. This study is different from other studies, because the CGE framework employed in this analysis allows us to evaluate the impacts not only among different countries, but also intra-sectoral effects among different sectors, including non-agricultural, or industrial and service sectors. The results of these trade liberalization analyses will be useful to sugar producers, consumers, trading companies, and government policymakers.
The CGE model used in this analysis is constructed around a 13-region, 13-sector Social Accounting Matrix (SAM) estimated for 1992 based on the Global Trade Analysis Project (GTAP) database (Hertel, 1997). Details of this type of multi-region SAM and its construction from the GTAP Database are described in Wang (1994). The 13 regions are: (1) the United States and Canada (USA/CAN), (2) European Union (EU) (15 member countries), (3) Australia and New Zealand (AUS/NZL), (4) Japan, (5) China (including China, Hong Kong Special Administrative Region), (6) India, (7) Indonesia, (8) the Philippines, (9) Thailand, (10) Malaysia and Singapore (MYS/SGP), (11) Brazil, (12) Former USSR and Central Europe Associates (Bulgaria, Czech Republic, Hungary, Poland, Romania, Slovakia, and Slovenia) (ESU), and (13) Rest of the World (ROW). The 13 sectors include 4 agricultural sectors: (1) grain, (2) sugarcane and sugarbeet, (3) other non-grain crops, and (4) rest of agriculture; 3 food processing sectors: (5) sugar processing, (6) beverage and tobacco, and (7) other processed food; 1 natural resource sector: (8) minerals and energy; 4 manufacturing sectors: (9) textiles and wearing apparel, (10) other light manufactures, (11) manufactured intermediates, and (12) machinery and transportation equipment; and, finally, (13) transportation, construction, and services, a portion of which is allocated to international shipping. There are no sugar crops sector and sugar processing sector in the version 3 of the GTAP database. The two sectors are aggregated in the "non-grain crops" and "other food processing" in the GTAP database. So, detailed data on sugar crops and sugar processing sectors have been collected to split the two GTAP sectors. The separation work and the correspondence between the model and GTAP sectors are given in appendix and appendix tables.
Factor Endowments and Comparative Advantage Across Regions
i) Production Resources Unevenly Distributed Across the World -- The four high income regions (USA/CAN, Japan, EU, and AUS/NZL) account for only 16 percent of the global labor force, but possess more than 75 percent of the world capital stock. In contrast, around half of the global labor force with less than 4 percent of the world's capital resides in the five low-income Asian developing regions (China, India, Indonesia, the Philippines, and Thailand). The four high-income regions are also relatively abundant in skilled-labor and arable land, while the skilled-labor share of the total labor force and arable land as a percent of total land mass are much smaller in China, ASEAN, and India.
ii) Wide Differences in Factor Intensities and Costs Among Regions -- Because of the uneven distribution of factor endowments, low-income developing countries have the lowest capital intensity (capital stock per worker), the largest shares of unskilled labor in their total labor force, and the highest rental-wage ratios. The reverse is true for the four high-income regions. In terms of natural resources, Japan and China are poorly endowed with arable land relative to labor. Therefore, they have the lowest land/labor intensities (arable land per worker) and relatively higher land returns (relative to labor and capital) compared with other regions. This condition is just the opposite in North America and AUS/NZL, where land as an abundant factor earns a relatively lower return there. These endowment differences are quite important for understanding net trade flows across regions based on conventional trade theory.
iii) Different Net Trade Patterns -- Sectoral net trade by region in the 1992 base year show that among the industrial countries, labor-intensive manufactured goods and mineral products are the major net imports, while capital and skill-intensive manufactured are the major net export sectors (except for machinery and equipment in the U.S. and Canada because of its deficit with Japan).
iv) Domestic Tax Policy and Import Protection -- Most general equilibrium analysis of regional economic liberalization focuses on the removal of ad valorem tariff equivalents on imports. The pattern and level of protection are very important in determining the impacts of trade liberalization. The larger the initial distortion, the greater the induced impact from an assumed policy change. For this analysis, the impact of APEC and ASEAN trade liberalization depends on the structure of the trade barriers in the estimated multi-regional SAM. The initial sectoral import protection rates as percentage of f.o.b. value, along with sectoral tax rates include the tariff equivalents of non-tariff barriers for agricultural and food products, quota rent of the Multi Fiber Arrangement (MFA) on textiles and apparel in most developing regions, and anti-dumping duties for the United States, Canada, and the EU (Hertel, 1997).
The domestic protection and export tax equivalent rates indicate that most regions in the model subsidize agriculture. Only MYS/SGP, the Philippines, China, and ESU still tax agricultural production.
Global Sugar Market - Production, Trade, and Government Intervention
Production --Climate and geographic conditions are determining factors for production of sugarcane and sugarbeet. ROW, EU, India, and Brazil are important producers of sugarcane and sugarbeet. The four countries and regions produces 68 percent of sugarcane and sugarbeet of the world. Their regional output shares of sugar crops sector and sugar processing sector are quite similar. ROW, EU, India, Brazil, and ESU are also important producers of sugar processing goods.
Trade -- It is apparent that MYS/SGP is the typical outward, while India is the typical inward economy in sugar processing sector. Thailand and AUS/NZL are more export oriented, and Japan, ESU, North America and EU are highly dependent on the supply of the world sugar market.
In the world sugar market (referring to sugar processing sector only), Thailand, EU, Brazil, and AUS/NZL are main net exporters, while ESU, North America, Japan, MYS/SGP, Indonesia, and China are net importers. The Philippines, India, and ROW are also net exporters but their size of net exports is very small. ROW and ESU are two largest importers in the world sugar market, their shares of imports in the world market are 34 percent and 21 percent, respectively. EU and North America are also significant importers. On the other hand, ROW is the largest exporter, providing 38 percent of world exports of sugar processing goods. Although Thailand accounts for only 2.4 percent of world sugar processing goods, its share in world sugar exports is 9.2 percent. In addition, Brazil and EU also play important roles in world sugar export market.
EU, ESU, and North America are the main destinations for sugar exports from ROW. ROW and ESU import most of their sugar from EU, Brazil, China, and India. APEC area is a major market of the sugar exports of AUS/NZL and the Philippines. As to the sugar imports, 95 percent of imports in EU, 60 percent in North America are from ROW. EU and ROW are main exporters of sugar to ESU market and APEC area is the supplier for Indonesia and MYS/SGP.
Government Intervention -- There is substantial government intervention in world sugar markets. Almost all the developed and developing countries protect their domestic sugar production. Typically, the import protection rate (tariff equivalent) in Japan is 372 percent. The import protection rates are around 100 percent in developing countries. There are also government subsidies on production and exports of sugar in some regions. All these policies heavily distorts the global sugar market.
All the structural information discussed above will have important implications for understanding the impact of regional trade arrangements on the world sugar market and Asian economies. However, this information cannot be considered in isolation, since changes in trade policies and protection levels in any of the regions and sectors will have impacts on other regions and sectors. It is on this point that application of a CGE model which includes all major regions in the world can make a significant contribution to understanding the possible impacts of regional trade arrangements on the world sugar market and Asian economies. The purposes of the above SAM-based analysis is to provide insights to facilitate understanding of simulation results reported later in this paper.
Structure of the Model
The model used in this paper is developed by Wang (1997) and is an extension of de Melo and David Tarr's basic general equilibrium trade model (1992) to a multi-country setting. In the extension, Wang followed John Whalley's tradition (1985) to endogenize all regions including the rest of the world, and incorporated the macro economic specifications from Devarrajan, Lewis, and Robinson (1990), as well as the international shipping sector similar to the GTAP model (Hertel, 1997). Moreover, the up-level Leontief technology in de Melo and Tarr's model was replaced by CES function, which allows substitution between value-added and aggregate inputs in the upper-level of the production tree, and their ELS demand system has been extended to ELES system, thus household saving decisions become endogenous in the model. Because duality approaches are used throughout the specification, the model is relatively simple and transparent in structure. A detailed algebraic description and a complete equation list of the model can be found in Wang and Schuh (forthcoming article entitled "The Impact of Economic Integration Among Taiwan Province of China, China, Hong Kong Special Administrative Region, and China: A CGE Analysis). The model is implemented by General Algebraic Modelling System (GAMS, Brooke, et.al. 1988).
In this study, 13 region and 13 production sectors in each region are specified in the model to represent the world economy. Each region is assumed to have basically the same structure. Four primary factors of production are modelled: agricultural land, capital, unskilled labor, and skilled labor. The division between skilled and unskilled labor is a distinction between professional workers and production workers. Primary factors are assumed to be mobile across sectors, but immobile across regions.
Economic Agents and Factor Endowments -- Three demand-side agents are assumed for each region: a private household, a public household (government), and an investor. Factor endowments are assumed to be owned by households and are set exogenously. Private households are assumed to sell the two categories of labor and to rent capital to firms, and to allocate their income from factor returns to savings and expenditures, which buy final consumption goods from the firms. The investor simply collects savings from households, government, and firms, accounting for foreign capital inflows or outflows. Total regional savings is available to the investor as his budget to buy capital goods, which are assumed to consist of fixed proportion of the 13 composite goods for gross investment.
Production -- There is a competitive firm in each sector for every region. The production is characterized by two-level nesting of constant elasticity of substitution (CES) functions. At the first level, firms are assumed to use two types of inputs: a composite primary factor and an aggregate intermediate input according to a CES cost function. At the second level, the split of intermediate demand is assumed to follow Leontief specification, therefore, there is no substitution among intermediate inputs. The four primary factors also substitute smoothly through a CES cost function. The degree of substitutability between the composite primary factor and the aggregate intermediate as well as among the four primary factors depends on their base year share in production and on the elasticity of substitution that is assumed to be constant. Technology in all sectors exhibit constant return to scale implying constant average and marginal cost. Firm's output is sold on the domestic market or exported to other regions through a constant elasticity of transformation (CET) function. The structure of production are illustrated in Figure 1. The CET function can be partially or entirely turned off in the model, in such case, exports and domestic sales become perfect substitutes.
Demands -- Agents in each region value products from different regions as imperfect substitutes (the Armington assumption). The private household in each region maximizes a Stone-Geary utility function over the 13 composite goods, subject to their budget constraint, which leads to the Extended Linear Expenditure System (ELES) of household demand functions. Household savings are treated as demand for future consumption goods with zero subsistence quantity (Howe, 1975). An economy-wide consumer price index is specified as the price of savings. It represents the opportunity cost of giving up current consumption in exchange for future consumption (Wang and Kinsey, 1994). Government spending and investment decisions in each region are based on Cobb-Douglas utility functions, which generate constant expenditure shares for each composite commodity. In each region, firm intermediate inputs, household consumption, government spending and investment demand constitute total demand for the same Armington composite of domestic products and imported goods from different sources, A two-level nested CES aggregation function is specified for each composite commodity in each region. The total demand is first divided according to geographical origin under the assumption of cost minimization. Sectoral import demand functions for each region are derived from the corresponding cost function according to Shephard's lemma. Complete trade flow matrices for all trade partners are part of the model solution.
There is an international shipping industry in the model to transport products from one region to another. Each region is assumed to allocate a fraction of the output of its transportation and service sector to satisfy the demand for shipping which is generated by interregional trade. The global shipping industry is assumed to have a unitary elasticity of substitution among supplier sources. This means the margins associated with this activity are commodity/route specific. In equilibrium, the total value of international transportation services at the world price equals the sum of the export proportions of the service sector's output from each region.
Trade-Distorting Policy -- The government in each region is assumed to impose import tariffs, export subsidies, and indirect taxes, all in ad valorem terms, Tariff and tax (subsidy) rates vary by sector and by destination.
Price System -- There are 10 types of prices for the good with same sector classification in each region. They are value-added prices, aggregate intermediate prices, average output prices, composite good prices, consumer prices, producer prices, export prices, import prices, f.o.b. prices, and c.i.f. prices. The value-added price equals the unit cost of primary factor inputs. The aggregate intermediate price is a fixed proportion (IO coefficients) weighted average of composite good prices. A CES aggregation of the two equals the average output prices. Adding to it the production taxes yields the producer prices which are tax inclusive CET aggregation of domestic and export prices. Sellers receive this price. The composite good price is a tax inclusive CES aggregation of domestic and import price, which in turn is an aggregation of tariff inclusive import prices from different sources. The consumer price is the composite good price plus sales tax. Buyers pay this price. The f.o.b. price of each Armington good is the firm's export price plus the export taxes or minus export subsidies. Adding to it the international transportation margins yield the c.i.f. price. An exchange rate, as a conversion factor, translates world market prices into domestic prices. An adjustable exchange rate in the model implies a change in domestic price index is sufficient to sustain a constant current-account balance measured at world prices.
Equilibrium -- Equilibrium is defined as a set of prices and quantities for good and factors in all regions such that (i) demand equals supply for all goods and factors; (ii) each industry earn zero profit; and (iii) gross investment equals aggregate savings in each region.
Choice of Numeraire -- In common with other CGE models, only relative price matters. The absolute price level must be set exogenously. The aggregate consumer price index in each region is used as numeraire. The advantage of this normalization choice is that factor returns and household income in model solution are in real terms. Moreover, the equilibrium exchange rates defined in the model are also in real terms, and can be seen as equilibrium price-level-deflated (PLD) exchange rates, using the country's consumer price indices as deflators (Lewis, Robinson, and Wang, 1995).
Macro Closure -- Macro closure of a CGE model has two aspects: macro accounting balances and assumption about macro adjustment behavior. There are three major macro balances in each region: (i) the government deficit (surplus); (ii) aggregate saving and investment; and (iii) the balance of trade. Although each agent has a balanced budget in equilibrium, there is no presumption that bilateral trade flows between any two regions are balanced. They are determined endogenously. The government deficit or surplus is the difference between revenues and expenditures, one of which has to be fixed exogenously.
In the benchmark equilibrium, all three macro balances hold. The behavioral specification of macro closure in a CGE model involves choice of a mechanism by which macro balances are brought back to equilibrium when exogenous shocks disrupt the benchmark equilibrium during an experiment. Thus, a macro scenario is imposed on the CGE model, which then traces out the sectoral implications of the assumed macro behavior (Devarajan, Lewis, and Robinson, 1990). Because the macro behavior is not based on optimizing behavior by rational agents in the model, different assumptions about the macro adjustment process may lead to different results.
Since the major purpose of this study is to estimate the impact of differential trade liberalization, the savings-investment gap is held constant in each region for all the simulations conducted by the model. This is achieved by keeping fixed balance of trade, total real government expenditures, and aggregate real investment in each region. Thus, the government deficit (saving) is endogenous and the model is investment driven. If government revenue changes because of a reduction in tariffs, the macro economic effect will be either a change in the exchange rate or a change in household savings, or both, since the induced government deficit is financed by foreign capital inflows or domestic borrowing.
By a macroeconomic identity, the fixed balance of trade implies that a constant sum of domestic savings and taxes in real terms is needed to finance fixed investment plus real government expenditures. Thus, any changes in real GDP in the model will go exclusively to changes in real consumption, making it easy to compare the results from different simulations.
The model is neoclassical in spirit. Prices in each region's product markets are assumed to be flexible to clear the markets. Each region is assumed to have a fixed amount of arable land specific to agriculture.
Static and Medium Term Accumulation Effects- There are usually two types of gains from trade liberalization: the gains from more efficient utilization of resources, which lead to a one-time permanent increase in GDP and social welfare, and the gains from a "medium-run growth bonus", which compound the initial efficiency gain and lead to higher savings and investment. The static efficiency gains induce higher income and lower prices for capital goods, accelerate capital accumulation, and lead to more capital stock available in the economy. This, in turn, yields more output, leading to further savings and investment. As Francois et al. (1995) have pointed out, this type of mid-term accumulation effect is different from any long-run, permanent growth effect induced by human capital and technology improvements, since it will ultimately decline to zero over time.
To quantify these two types of gains, two alternative capital market closures can be chosen in the model: one static, and one steady-state. Under the static capital market closure, the aggregate productive capital stock is fixed in each region, and the region-specific average rental rate adjusts to ensure that regional capital is fully utilized. It is the empirical analogue of the comparative-static analysis that is common in theoretical work. Under the steady-state capital market closure, the return of capital is held constant while the capital stock in each region is endogenously determined. This closure assumes that since each region's aggregate capital stock is at its steady-state level in the benchmark equilibrium, liberalized trade will increase capital returns due to more efficient allocation of resources. In a dynamic sense, this will lead to a higher savings and investment rate. More capital stock in the economy will drive down the marginal productivity of capital, thus decreasing the return of capital until its initial level. Although this simulation cannot provide information about the transition path of how the capital price in each region returns to its steady-state equilibrium after an external shock, it can shed some light on the approximate size of the accumulation effect from trade liberalization-induced investment growth in a classical Solow-type growth model at almost no additional implementation cost. The theoretical underpinnings of this approach are based on the concept of invariant capital stock equilibrium proposed by Hansen and Koopmans (1972), and it was introduced into CGE analysis to estimate the accumulation effects of trade liberalization by Harrision, et al. (1995).
There are 4 sets of counterfactual experiments carried out by this study:
Scenario I -- The impact of Uruguay Round trade liberalization,
Scenario II -- The impact of AEFA trade liberalization,
Scenario III -- The impact of APEC trade liberalization, and
Scenario IV -- The impact of global trade liberalization.
For the last 3 scenarios, experiments are repeated for each scenario with two simulations: one with trade liberalization only taking place in the two sugar sectors (EXP 1) and the second trade liberalization taking place in all sectors (EXP 2). Therefore, all together 7 simulations were conducted. In each simulation, the steady state capital market closures were adopted.
For scenario I, the percentage reduction in import protection rates by sector and by region agreed to in the Uruguay Round is presented in table 6. The data for non-sugar are aggregated from version 3 GTAP database, which is based on World Bank estimates, covering 31 GTAP sectors (except 6 service sectors) and 28 regions (except China and Taiwan Province of China). The average reduction in domestic agricultural support is 20 percent for developed countries, 13.3 percent for developing countries (but except the sugar crops sector). The reduction of agricultural export subsidies is 36 percent for developed countries and 24 percent for developing countries, based on estimates by Francois et. al.(1995). To simulate the termination of Multi Fiber Arrangement (MFA) quota system, the quota rent equivalent export taxes are eliminated for all developing countries.
For the other 3 scenarios, APEC trade liberalization means reducing all bilateral protection to zero among North America, Japan, AUS/NZL, China, Indonesia, the Philippines, Thailand, MYS/SGP. AEFA trade liberalization means reducing all bilateral protection to zero among Indonesia, the Philippines, Thailand, and MYS/SGP. Global trade liberalization means reducing bilateral protection rates to zero for all regions. In the experiments of trade liberalization in all sectors for all 3 scenarios, the termination of MFA quota system is also incorporated. We assume that the quota rent equivalent export taxes are eliminated among the trade liberalization regions.
For each of those experiments, the CGE model generates results regarding the effects on social welfare, terms of trade, the volume of trade, output, the wages paid for each factor, and changes in prices and resource allocation. The difference between the assumed scenarios and the base case is our estimates of the impact of regional trade liberalization. However, our estimates should be regarded as results from controlled experiments rather than as forecast. In reality, actual and output patterns are affected by many more factors than just trade liberalization, such as domestic macroeconomic and income policy changes.
Tables have been omitted due to space limitation.
Macro results -- The social welfare measured by the Hicksian equivalent variation would increase in all regions except China, because China is excluded from the Uruguay Round trade liberalization. ESU (East Europe and Former Soviet Union) gains little because FSU is also excluded in the Uruguay Round trade liberalization. The developing countries' gains are large because of the small size of their economies, relatively high trade orientation, and low capital return rate.
The termination of MFA quota system and trade liberalization in agriculture and food are two important outcomes of the Uruguay Round, they would result in higher prices for agricultural products and lower price for textile. Consequently, the terms of trade of developing countries, which export textiles to developed countries, improves. The terms of trade of EU, AUS/NZL, and USA/CAN would also improve because they are important exporters of agricultural products. But Japan is an important importer of agricultural products, this explains why its terms of trade would decline
The trade liberalization of Uruguay Round expands global trade. India and ASEAN countries exports would increase rapidly because of the elimination of MFA quota system and their comparative advantage in labor-intensive textiles products. There would be little changes in the trade of China and ESU, even the exports of China would decline slightly.
Sugar -- The sugar production of importers would decline and sugar production of exporters would increase, except for EU and MYS/SGP. The production of sugar in EU would decline because of its high protection in sugar sector and the reduction of export tax. Since the production of sugar in MYS/SGP were almost all exported, the increase of sugar prices in world market after UR trade liberalization would result in increase of export and production of sugar of MYS/SGP. Japan has one of the most heavily protected sugar sectors in the world sugar sector before UR, so its production of sugar would suffer the largest decline.
The gains in UR trade liberalization would promote the increase of demand for sugar. The demand for sugar in Thailand would increase 6 percent, because it gains most relative to the size of its economy.
The increase of net exports is mainly provided by Thailand, Brazil and ROW. Although AUS/NZL is an important exporter of sugar, UR trade liberalization would not result in its rapid increase of export, because much of its resources is reallocated in the grain sector.
Macro results -- AEFA trade liberation of the sugar sectors would increase the social welfare of all the ASEAN countries, although the improvement is very limited. Thailand s terms of trade would improve, while the other three ASEAN countries decrease, because of the increase in Indonesia, MYS/SGP, and Philippine s demand for Thai sugar.
AEFA trade liberation in all sectors would improve the ASEAN s social welfare, and the trade diversion would slightly decrease the social welfare of Japan, AUS/NZL and India. But the distribution of gains is uneven in ASEAN regions. MYS/SGP gains much more than the other three countries, because there is a strong trade connection between MYS/SGP and the other three countries, but the trade among the three countries is relatively small.
Sugar -- In ASEAN countries, Thailand is a net exporter of sugar and its imports of sugar are almost zero. The Philippines is also a net exporter, but most of its sugar exports are shipped to the United States, and the Philippines has a heavy import protection on domestic sugar market. Indonesia is a net importer of sugar, it also has heavy protection for its own sugar sector. When all the import protection in sugar sector among ASEAN region are eliminated, sugar production and sugar exports of Thailand would increase, and, on the contrary, imports of Indonesia, MYS/SGP, and Philippine would increase. In the experiment of trade liberalization in all sectors, the pattern of change in sugar trade is largely the same as the experiment of sugar-sector-only liberalization.
Macro Results -- All the APEC members would gain in the APEC trade liberalization, while non-APEC members would lose. In the experiment of trade liberalization for sugar sector, the terms of trade of the main exporters of sugar, Thailand and AUS/NZL, increase. In the experiment of trade liberalization in all sectors, the increase in demand for agricultural products among USA/CAN, AUS/NZL, China, and Indonesia would improve their terms of trade.
Because of the trade diversion, the trade of non-APEC members would decrease, while the trade of APEC countries would increase. The trade of ASEAN and China would increase the most because of the elimination of MFA quota in textile exports to USA/CAN.
Sugar -- AUS/NZL and Thailand are the main exporters of sugar in the APEC area. Their production would increase significantly in the APEC trade liberation. USA/CAN, Japan, China, and Indonesia would decrease their production because their high import protection to APEC regions is eliminated. The production in ROW and Brazil would also decrease because of the trade diversion.
The pattern of changing in the experiment of trade liberation in all sectors is similar to the sugar sector trade liberalization experiment. But the trade liberalization in other sectors would affect the resource allocation, and thus affect the sugar sector. The production and exports of sugar of AUS/NZL in EXP 2 (all sectors) is smaller than EXP 1 only sugar sector), while production and export of Thailand in EXP 1 is larger than EXP-2. This is because the trade liberalization in agriculture results in the booming demand for agricultural products of AUS/NZL, promotes the growth of production and exports of AUS/NZL s grain sector, and results in the contraction of sugar crops sector and sugar processing sector. While Thailand has more comparative advantage in the sugar crops sector than other agricultural sector, therefore, it would import more other grain products and produce more sugar products. For similar reasons sugar exports of USA/CAN would decrease.
Global Trade Liberalization
Macro Results -- Global trade liberalization promotes the social welfare increases in all the regions. Similar to the previous scenarios, developing countries gain more relative to the size of their economies. The pattern of change in terms of trade is also similar to the previous scenarios.
Sugar -- In the global trade liberation scenario, AUS/NZL, Thailand, Brazil and ROW would increase their production of sugar, while EU would decrease much of its production (table 8-C). The increase of production and exports of AUS/NZL and Thailand would be less than that in the APEC trade liberalization scenario, because some trade opportunities would transfer to Brazil and ROW.
Sugar is an important commodity in world agricultural commodity market, which is characterized by heavy government intervention, large price fluctuation, growing market for sugar substitutes, and widespread production in many parts of the world. As Uruguay Round policy provisions are implemented and APEC and ASEAN trade liberalization policies are carried out, it is critical for sugar exporting and importing countries to assess the effects of these trade reforms on their sugar markets.
The objective of this study is to use a CGE framework that includes majority of the sugar producing and trading countries to quantify the effect of the trade liberalization agreements negotiated under the UR on sugar production, consumption, trade, and prices of the major sugar exporting and importing countries. A 13-region and 13-production-sector model is constructed for this study and we found the following results.
In general, the conclusions can be summarize as follows:
1. The trade liberalization of the Uruguay Round will expand global trade and social welfare would increase in all regions or countries, except China (China is excluded from the UR trade liberalization). The developing countries gains are large relative to their smaller size of economies and high trade orientation. The gains in UR trade liberalization promote the increase of demand for sugar. Sugar production of importers would decline and sugar production of exporters would increase, except EU and MYS/SGP.
2. AEFA trade liberalization in all sectors would improve the ASEAN's social welfare, but the distribution of gains is uneven in ASEAN regions. AEFA trade liberalization in sugar sector would increase the social welfare of all ASEAN countries, although the improvement is rather limited. The terms of trade improve for Thailand, while the other three ASEAN countries, Indonesia, MYS/SGP, and the Philippines, decrease because of their demand for Thailand's sugar. When all the import protection in sugar sector among ASEAN regions are eliminated, sugar exports of Thailand would increase and imports of Indonesia, MYS/SGP, and Philippine would increase.
3. All APEC members would gain in the APEC trade liberalization, however non-APEC members would lose. In the experiment of trade liberalization in sugar sector, the terms of trade of the main exporters of sugar, Thailand and AUS/NZL, increase. In the case of trade liberalization in all sectors, the increase in demand for agricultural products among USA/CAN, AUS/NZL, China and Indonesia would improve their terms of trade. In the APEC sugar trade liberalization, sugar production in AUS/NZL and Thailand would increase the most. USA/CAN, Japan, China, and Indonesia would decrease their sugar production, because of high import protection to APEC regions is eliminated. The production of ROW and Brazil would also decrease because of trade diversion. The pattern of changes in the experiment of trade liberalization in all sectors is similar to the sugar trade liberalization experiment.
4. Finally, global trade liberalization would promote welfare increases in all regions. Similar to the UR scenario, developing countries' gains are large relative to the size of their economies. The pattern of change in terms of trade is also the same as previous scenarios. In the global trade liberalization scenario, AUS/NZL, Thailand, Brazil and ROW would increase their production of sugar, while EU would decrease much of its production. The increase of production and exports of AUS/NZL and Thailand would be less than APEC trade liberalization scenario, because some trade opportunities would transfer to Brazil and ROW.