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  • 标题:Biofuels: Potential Production Capacity, Effects on Grain and Livestock Sectors, and Implications for Food Prices and Consumers
  • 本地全文:下载
  • 作者:Hayes, Dermot J. ; Babcock, Bruce A. ; Fabiosa, Jacinto F.
  • 期刊名称:Journal of Food Distribution Research
  • 印刷版ISSN:0047-245X
  • 出版年度:2009
  • 卷号:40
  • 期号:4
  • 出版社:Food Distribution Research Society
  • 摘要:We examined four evolution paths of the biofuel sector using a partial equilibrium world agricultural sector model in CARD that includes the new RFS in the 2007 EISA, a two-way relationship between fossil energy and biofuel markets, and a new trend toward corn oil extraction in ethanol plants. At one extreme, one scenario eliminates all support to the biofuel sector when the energy price is low, while the other extreme assumes no distribution bottleneck in ethanol demand growth when the energy price is high. The third scenario considers a pure market force driving ethanol demand growth because of the high energy price, while the last is a policy-induced shock with removal of the biofuel tax credit when the energy price is high. Standard results hold where the biofuel sector expands with higher energy price, raising the prices of most agricultural commodities through demand side adjustment channels for primary feedstocks and supply side adjustment channels for substitute crops and livestock. On the other hand, the biofuel sector shrinks coupled with opposite impacts on agricultural commodities with the removal of all support including the tax credit. Also, we find that given distribution bottlenecks, cellulosic ethanol crowds marketing channels resulting in a corn-based ethanol price that is discounted. The blenders’ credit and consumption mandates provide a price floor for ethanol and for corn. Finally, the tight linkage between the energy and agricultural sectors resulting from the expanding biofuel sector may raise the possibility of spillover effects of OPEC’s market power on the agricultural sector.
  • 关键词:biofuel;EISA;ethanol;tax credit;world agricultural sector model
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