Assessing Welfare and Growth Effects of Grain-based Fuel Ethanol Development in China: A General Equilibrium Framework

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1 Journal of Convergence Information Technology Volume 5, Number 0. December 200 Assessing Welfare and Growth Effects of Grain-based Fuel Ethanol Development in China: A General Equilibrium Framework Lab of Resources and Environmental Management China University of Geosciences (Beijing) Beijing, China kakenpei@yahoo.co.jp, leiyalin@cugb.edu.cn doi:0.456/jcit.vol5. issue0. Abstract In this study, we use the computable general equilibrium (CGE) model to examine welfare and growth effects of expanding grain-based fuel ethanol production in China. The results show that reasonable development of grain-based fuel ethanol will accelerate China s economy, improve rural household income, and narrow the gap between the rich and the poor. However, expanding the production of grain-based fuel ethanol will also stimulate consumer price index (CPI). Keywords: Welfare, Growth, Grain-based, Fuel Ethanol, China, Computable General Equilibrium. Introduction Over the period 2002 to 2008, China s fuel ethanol production has been expanding rapidly and has become the third largest producer in the world. In 2008, the fuel ethanol production reached.58 MMT, with the growth of 3% over the previous year (Table ). Chinese government plans for renewable energy generation to meet 5% of the country s growing demand for energy by According to China s medium- to long-term renewable energy development plan (2020) (Table 2), the fuel ethanol production will achieve an output of 0 million tons. Significantly, growth of fuel ethanol production has affected food supply and prices, thereby exert pressure on many developing countries and poor households (de Gorter and Just) [4]. However, although it is a dilemma of food crisis and price increase, some surveys show positively that corn-based fuel ethanol production brought increased demand for 4.2 million tons of grain, increased farmers income by 5 billion RMB, and, from 2002 to 2006, saved annual costs of 332 million RMB and 2.3 billion RMB respectively in government warehousing and construction, according to China Chemical News [5]. Table. A Historical Look at China s Fuel Ethanol Production Year Production Quantity % Increase from Previous Year 2002 and before Official fuel ethanol production began in There is little recorded fuel ethanol production before < 20,000 tons/year ,000 tons/year 400% ,000 tons/year 206% 2006,300,000 tons/year 4% 2007,370,000 tons/year 5% 2008,580,000 tons/year 3% Source: USDA Foreign Agricultural Service NA - -

2 Assessing Welfare and Growth Effects of Grain-based Fuel Ethanol Development in China: A General Equilibrium Framework Table 2. China s Medium to Long-term Renewable Energy Development Plan (2020) Energy Sources Unit Total Primary Energy Supply (TPES) Million tce Renewable Energy Share of TPES % 0 6 Total Renewable Energy Consumption Million tce Hydro Thousand MW Wind Thousand MW 5 30 Photovoltaic Thousand MW Biomass Generation (Agriculture and Forestry) Thousand MW Solar Water Heater Million m Biogas Billion m Solid Biomass Fuel Million tons 0 50 Bio-ethanol Million tons 2 0 Bio-diesel Million tons Source: Xinhua News Agency , Zhong Guo Dian Li Bao (China Electric Power News) There are an increasing number of studies on the welfare effects of fuel ethanol expansion. Babcock [] evaluated the welfare impacts of ethanol policies. He found out that the U.S. ethanol policy brought a large welfare transfer from taxpayers and non-ethanol corn users to corn producers, fuel blenders, and ethanol producers, as well as large associated net welfare loss. Gallagher et al. [8] analyzed the implications of a renewable fuel mandate of 5 billion gallons of ethanol as a fuel additive with a conjunction of national MTBE ban on social welfare. They found out that social welfare decreased by 6% without taking environmental benefits into account. Gardner [9] concluded in his study that ethanol subsidies have a greater net welfare effect than government commodity program outlays. Lasco and Khanna [4] developed a stylized model of fuel markets to analyze the impact of ethanol policy on social welfare. Their analysis shows that the combined subsidy and tariff policy decreases welfare by about $3.6 billion relative to a non intervention policy. Martinez-Gonzalez et al. [6] used a partial equilibrium trade model and a back-of-envelope formula to assess welfare effects of distortions in the ethanol market. This study shows that trade liberalization results in decline in the surplus of corn farmers, ethanol producers, and ethanol consumers. In addition, fuel ethanol is widely recognized as an economic stimulus. Hausmann [0] viewed fuel ethanol as being net positive for growth and development, particularly in developing countries. Dixon et al. [6] used a dynamic CGE model called USAGE to investigate the economy wide implications of an ethanol policy. It is concluded that fuel ethanol development benefits to the United States economy including the increase in employment and export prices. The objective of this study is to conduct an economic analysis to assess welfare and economic impacts of grain-based fuel ethanol development in China. In this study, we perform simulations based on China s fuel ethanol policy using the static computable general equilibrium (CGE) model. 2. Methodology Fuel ethanol development affects not only industries but also farmers, the well-being of consumers, balance of trade, and the government budget. Understanding the impacts of fuel ethanol on the overall economy requires a modeling framework which accounts for all the feedback mechanisms between fuel ethanol and other markets. A computable general equilibrium (CGE) analysis would be one of the best techniques to assess the above effects (Sadoulet and de Janvry) [20]. The CGE model, based on the general equilibrium theory of Walras [23], uses a series of equations to describe interactions among different elements and agents in the regional or national macro-economy. The first study in which the CGE model was adopted for energy was by Hudson and Jorgenson [], it projected economic activity and energy utilization for the period 975 to Since then, some studies have been focused on energy/environment: analysis of marginal costs and - 2 -

3 Journal of Convergence Information Technology Volume 5, Number 0. December 200 co-benefits of energy efficiency investment by Jakob [2]; the results from energy prices changing by Klepper et al [3]; and the effects of investment growth in the energy sectors in western areas of China on the local economy and emission of carbon dioxide by Lu et al [5]. During this period, there have been some studies on the Interactions among energy, automobile and environment development, such as an analysis of the market damage caused by the automobile-related carbon tax by Muto et al [7] and an evaluation of the automobile and environmental policy by Tokunaga et al [22]. With the emergence of bio-fuel, the CGE model has been used to assess bio-fuel policy, especially in Brazil, America, and European countries. Perry [9] used the CGE model to assess the impact of biomass production on food and land markets. Channing et al [3] evaluated the implications of largescale investment in bio-fuels for growth and income distribution. Doumax [7] adopted the CGE model to assess the economic impact of bio-fuels on global economy. This study adopts the CGE model to assess welfare and economic impact of grain-based fuel ethanol in China at the national economy level. The rest of the paper is organized as follows. The Model section introduces the general framework of the model. The Model Results section describes the impacts of grain-based fuel ethanol on social welfare and economic growth under the Chinese government s policy. Finally, a policy on fuel ethanol is recommended in the Conclusions section. 3. The Model The model attempts to simulate fuel ethanol policies. The prototype of the model refers to the CGE model of Okiyama and Tokunaga [8], which we extend with following points. First, in our model, since China is a large trading country, we adopt the large country assumption with endogenous international prices. Second, for the consumption phase, the model includes two types of households, rural and urban. Third, keeping in mind our study s objective, the CPI was added to our model in order to measure the food price crisis. 3.. Model Structure The SAM (Social Accounting Matrix) related to grain-based fuel ethanol was created based on the 2002 input-output table of China for the CGE model. Our model includes 6 blocks: production, trade, households, government, savings and investment, and market equilibrium.at the production stage, a two-stage nest is used to describe production behavior. The Leontief production function and the CES production technique are used to establish the demand function of intermediate inputs and agricultural labor, nonagricultural labor, and capital inputs. For the trade block, we use the CET technique to describe the distribution of output between domestic and foreign markets, and the Armington function to explain the imperfect substitution between domestic products and imports. Since this model adopts the large country assumption, the international prices containing international import and export prices are endogenous. For the household block, third-stage nested CES functions are used to characterize households behaviors for maximizing total household utility subject to budget constraints. On the first level, disposable income is allocated to consumption and savings. On the second level, total consumption is distributed to composite commodities, automobiles, and fuels. On the third level, total fuel consumption is assigned to fossil fuel and grain-based fuel ethanol. In the model, government saving is given at a fixed rate; investment is endogenous and equal to total savings; thus, the model has neoclassical closure. The numeraire of the model is given to fix the domestic price of insurance and financials Parameter Calibration The parameters in the model include exogenous and endogenous parameters. We estimated three exogenous parameters using the CES functions, as shown in Table 3. The elasticity of substitution between fossil fuel and fuel ethanol refers to the research by Birur [2]. The value given for China in the study by Birur et al is 2. However, by sensitivity analysis, we obtained the most stable value for - 3 -

4 Assessing Welfare and Growth Effects of Grain-based Fuel Ethanol Development in China: A General Equilibrium Framework this model, The elasticity of substitution for the CET function and the Armington function refers to related research by Zhai et al [24] (see Table 4). Table 3. Elasticity of Substitution in the Model Elasticity of Substitution CES Function Initial Value t-statistic Prob. Adjust-R2 Elasticity of Substitution among ( =.8435) Q r( NAL AL ( ) K ) Agricultural labor, Non-agricultural and Capital ( ) Elasticity of Substitution between Consumption and Saving Elasticity of Substitution among Composite Goods, Automobile and Composite Fuel Consumption 4. Model Results D ( C ( ) v ( ) v S ) v v C ( XC AC ( ) FC ) v ( ) N Table 4. Elasticity of Substitution for CET Function and Armington Function 4.. Description of Scenarios Source: Zhai et al (2005) The scenarios of grain-based fuel ethanol expansion are based on China s renewable energy policy. According to China s Medium to Long-term Renewable Energy Development Plan (2020) (Table 2), we use two simulation scenarios: case, where the production of grain-based fuel ethanol increases to 2 million tons, which is the planned target for 200; and case 2, where the output of grain-based fuel ethanol reaches 0 million tons, which is the goal for A baseline scenario was run where grainbased fuel ethanol production was 300,000 tons Results of the Simulation Analysis Elasticity of Substitution for CET Function Elasticity of Substitution for Armington Function Rice Grains Vegetable and Fruit Other Crops Forestry Animal Husbandry Fishery Technical Services for Agriculture Mining Petroleum Manufacture Electricity, Steam and Hot Water Gas Water Fuel Ethanol Construction Road Transport Other Transport Insurance and Finance Commercial Other Services Table 5 shows variations in major macroeconomic indices caused by the production of grainbased fuel ethanol increasing to 2 million tons and 0 million tons

5 Journal of Convergence Information Technology Volume 5, Number 0. December 200 Table 5. Macroeconomic Effects Case Case 2 Case Case 2 Total Absorption (%) Total Investment Change (%) GDP (%) Total Exports (%) Total Consumption by Total Imports (%) Households (%) Total Consumption by Exchange Rate (%) Government (%) Social Equivalent Variations (Million RMB) CPI (%) As shown in Table 5, excessive expansion of grain-based fuel ethanol production has negative effects on social welfare and exchange rates. When the production increases from 2 million tons to 0 million tons, total absorption, GDP, total consumption by households and government, total investment, total export, and total import continue to grow rapidly. However, because of lack of arable land and agricultural technology constraints, grain supply cannot satisfy industrial and domestic food demands. Imbalance between grain supply and demand leads to other commodities price increases and CPI growth. For rapidly rising prices and slowly growing income, residents will reduce consumption expenditure, resulting in social welfare decrease. Therefore, within the permitted conditions of available arable land and agricultural technology, designedly and gradually extending grain-based fuel ethanol enables the achievement of a win-win outcome for both the national economy and the people s livelihood. As we know, the exchange rates are related to international trade. If the production increases to 2 million tons and 0 million tons, trade surpluses descend to million RMB and million RMB from million RMB of the base year. This means that trade surpluses decline by 0.04% and 0.47%, which are the same as the variations in the exchange rate. Table 6 describes variations in the effects on urban and rural households induced by the production of grain-based fuel ethanol rising to 2 million tons and 0 million tons. Table 6. Effects on urban and rural households Case Case 2 Rural Household Urban Household Rural Household Urban Household Consumption (%) Disposable Income (%) Saving (%) Equivalent Variations of Each Household (million RMB) Results show that expansion of grain-based fuel ethanol has positive effects on rural households, including income increase, and accordingly, a rise in consumption and savings, with rural household welfare rising over time. In contrast, urban residents experience negative effects. Since increasing fuel ethanol production boosts grain output and stimulates higher prices of agricultural products, farmers income and consumption are improved; thus, the welfare of rural households increases. Table 7 illustrates variations of labor and capital inputs indices when 2 million tons and 0 million tons of fuel ethanol production are achieved in cases and 2, respectively

6 Assessing Welfare and Growth Effects of Grain-based Fuel Ethanol Development in China: A General Equilibrium Framework Table 7. Effects on Production Factors Case Case 2 Revenue Price Revenue Price Agricultural Labor Non-agricultural Labor Capital As shown in Table 7, with grain production expanding, demand for agricultural labor increases. However, the original agricultural labor supply cannot meet the rapid growth of demand, and this leads to rising wages for agricultural labor, promotes labor mobility, and decreases the urban rural income gap. Compared with the agricultural labor market, urban workers face the problem of reductions in wages and revenue. Consequently, some urban laborers will move to work in the grain production sector Sensitivity Analysis Because this model is used to analyze the effect of fuel ethanol development, the elasticity of substitution between fossil fuel and fuel ethanol is crucial Moreover, because the elasticities of substitution for the CET function and the Armington function referred to other studies, we conducted sensitivity analysis with regard to these parameters. First, we chose to fix the wage rate of non-agricultural labor as the numeraire to perform the sensitivity analysis [2]. The elasticity of substitution between fossil fuel and fuel ethanol was assumed in the interval of After random testing (89 times) with the uniform distribution, we used as the most suitable value for the elasticity of substitution between fossil fuel and fuel ethanol in this model. The testing results are given in Table 8. Table 8. Statistical Results of Elasticity Sensitivity Analysis for Fossil Fuel and Fuel Ethanol GDP Disposable Income Disposable Income Wage Rate of Interest Rate Total Import Total Export of Rural Household of Urban Household Agricultural Labor Mean Standard Deviation Upper Confidence Limit of the % Confidence Interval Lower Confidence Limit of the 95% Confidence Interval Results Based on Initial Elasticity Subsequently, we again used random testing (84 times) with the uniform distribution for the numeraire of fixing CPI. The elasticities of substitution for the CET function and the Armington function were assumed in the interval of 0.~0. The testing results are given in Table

7 Journal of Convergence Information Technology Volume 5, Number 0. December 200 Table 9. Statistical Results of Elasticity Sensitivity Analysis for the CET Function and the Armington Function Total Absorption GDP Disposable Income of Rural Household Disposable Income of Urban Household Wage Rate of Agricultural Labor Wage Rate of Nonagricultural Labor Total Import Total Export Mean Standard Deviation Upper Confidence Limit of the % Confidence Interval Lower Confidence Limit of the 95% Confidence Interval Results Based on Initial Elasticity The sensitivity analysis shows that the qualitative results are not fundamentally different and the model is stable. 5. Conclusions In this study, we assessed the economy-wide effects of expanding grain-based fuel ethanol production on welfare and growth in China with a computable general equilibrium model. Model results show that if the production of grain-based fuel ethanol increases to 2 million tons, the national economy and total social welfare will be boosted. However, excessive expansion, such as if the production jumps to 0 million tons, will depress total social welfare. In addition, the exchange rate will certainly decline with the production expansion. Other effects of encouraging the production of grain-based fuel ethanol are as follows: an improvement in the disposable income and welfare of rural households and a reduced income gap between rural urban households, and a reduction in the revenue and welfare of urban households. Based on these conclusions, it can be deduced that reasonable development of grain-based fuel ethanol will accelerate China s economy, improve rural household income, and mitigate the gap between rich and poor. However, a reasonable alternative plan should be established on the basis of appropriate price fluctuation and no food crisis. 6. References [] Babcock, B. A., Distributional Implications of U.S. Ethanol Policy, Review of Agricultural Economics, Vol. 30, 2008, pp [2] Birur D. K., Hertel T. W. and Tyner W. E., The Biofuel Boom: Implications for World Food Markets, Paper presented at the Food Economy Conference, 8 9 October 2007: The Hague, The Netherlands. [3] Channing, A., Benfica, R., Tarp, F., Thurlow, J. and Uaiene, R., Biofuels, Poverty, and Growth: A Computable General Equilibrium Analysis of Mozambique, Working paper, 2009, growth-mozambiqueede.pdf. [4] de Gorter, H., and Just, D. R., The Social Costs and Benefits of Biofuels: The Intersection of Environmental, Energy and Agricultural Policy. Applied Economic Perspectives and Policy, Vol. 32, No., 200, pp [5] Deutsche Bank, Ethanol in China China s Drive to Alternative Fuels, Company Research, August, 2006, pp. 4. [6] Dixon, P. B., Osborne, S., Rimmer, M. T., The Economy-Wide Effects in the United States of Replacing Crude Petroleum with Biomass, paper submitted for the GTAP Conference, Purdue University, Indiana, [7] Doumax, V., Assessing the Economic Impacts of Biofuels: the Use of Computable General Equilibrium Modeling, Working paper, - 7 -

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