| 摘要 | ��
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1. Background and Objective
Korea has been preparing free trading agreement (FTA) with other countries such as U.S.A, EU, and China. Accordingly, it is highly plausible for domestic industries with comparative disadvantage such as agriculture, livestock, and wood sectors may be negatively affected by the agreement. In response with the economic loss in those sectors, government attempts to foster domestic biodiesel industry using Korean rapeseed oil. Thus, we need to evaluate how the free trading could influence micro as well as macro economic variables such as GDP and social welfare. Besides, the impact analysis of the high crude oil price shock on the economy and biodiesel industry would show whether the government supportive policy on the biofuel sector is appropriate in response to multiple impact of high oil shock and FTA shock.
Meanwhile, as international oil prices have skyrocketed in recent years, the demand for biofuels has risen tremendously. In 2007, the world production of biofuels was estimated to be over 56 million kiloliters, which is about 2% of the world gasoline consumption. The OECD/IEA (2006) presumes that biofuel production will reach 7% of the world road fuel consumption by 2030. In parallel with the energy crisis issue, the threat to global food security has been emerging as one of the most critical global issues in 2008. During September 2006 and March 2008, the world wheat price, soybean price, and corn price increased by 183%, 151%, and 133%, respectively. Along with the rise in major grain prices, feed prices for breeding cattle, hogs, and broilers have increased sharply, collectively causing the so-called phenomenon of "ag-flation." Korea began to produce biodiesel commercially in 2006 and the biodiesel production goal to 2012 is 3% of total road diesel fuel consumption. Therefore it is required to investigate how the growth of biofuel industry would affect agricultural market.
2. Purpose of the Study
The goal of this research can be divided into two parts.
The first goal is to evaluate economic impact of free trading as well as government subsidy policy on the biodiesel sector. A static computable general equilibrium model (CGE) for the Korean small open economy is constructed using Korean input-output data in 2003.
The second goal is to quantify the feasible impact of world wide expansion of biofuel production on the agricultural market. More specifically, there are two approaches for the investigation. First approach employes structural vector auto-regression model(SVAR) for the purpose of analyzing how the increase of international oil price could affect bioethanol demand, feed demand for corn, and corn price.
Secondly, we examine how the growth of bioethanol in U.S.A affect corn prices derived by corn demand and corn supply using structural econometric model. Accordingly, we investigate how domestic feed and livestock market could be affected by the increase in the corn price.
3. Major Findings
In the first study, we found that the removal of tariff in the entire industries could worsen agriculture, feed, livestock, and wood industries while improve consumption and gross domestic production. The changes in the consumer's welfare shows that the net welfare gain is positive after the increased welfare gain from the free trading is used for compensating economic losses of agriculture, livestock, and wood industries through the subsidy policy on the biodiesel industry.
The second approach using SVAR model can be summarized as following. As the one unit of standard errors of oil price shock increases, the oil price increases rise upto 10% at the top and disappear as time goes by. Corn demand for bioethanol rises upto 2% at the 10th quarter, and the corn price increases by 2% at the 10th quarter and stabilizes at 1%. Thus we could say that the oil shock could affect bioethanol demand and corn price upto medium and long term.
From the third research, corn price elasticity on the production of bioethanol in U.S.A was estimated as 0.19 at the final harvesting season of 2007/08. The elasticity was estimated as 0.098 at the mean of harvesting periods. In 2011, as the ethanol provision increases as 110 billion gallons, the expected corn price was estimated as $8.0 per bushell. In the structural model for domestic feed and livestock markets, we found that domestic feed price elasticity of the corn price is 0.1, while the elasticity of number of cows for beef on the supply of beef is 0.33, and direct elasticity of beef supply on the corn price is 0.56. The elasticity of supply of milk cow for beef on the feed price is 1.56, which is positive. The reason is that farmers increase the supply of milk cow for beef as the production cost of raising milk cows. In the meantime, the elasticity of supply of pork on the number of male hog is 1.8 and the elasticity of broiler supply on the feed price is 0.35.
4. Policy Implication
We found that the free trading could affect agricultural and related sectors negatively, while the consumer welfare would be improved. Therefore the net social gain from the FTA was expected to be positive, which means Pareto improvement. Hence, government should prepare how we compensate the economic loss of those sectors. On the other hand, the CGE model showed high crude oil prices would offset the positive effect of the FTA. Therefore, fostering biodiesel industry would generate dual effects such as improvement of energy security and compensation to the negatively affected industries by the FTA.
From the empirical quantification for the relationship among, petroleum, biofuel and agricultural industries, we conclude that high oil price affects the rise of biofuel demand which leads to high prices in the agricultural products. Accordingly, we need to re-evaluate the whole plan for fostering biofuel industry. Further more, we should consider how the portfolio of feedstocks for biofuels in Korea should be designed in the longer term. Non-food stock based biofuel technology such as Jatropha plantation, cellulosic biofuel, and algae based biofuels should be encouraged in the future.
136 pages, 37 refs., 35 tabs., 21 Figs., Language: Korean |
