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Genetically Modified Crops, an Input Distance Function Approach

  • Gardner, Justin G.
  • Nehring, Richard F.
  • Nelson, Carl H.

Our initial findings indicate that GM crops do not contribute to the decline of traditional family farms. We make a significant methodological impact by using the within transformation to remove unobserved individual effects and demonstrate that the within transformation results in ML estimates that are identical to OLS estimates.

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File URL: http://purl.umn.edu/6800
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Paper provided by Southern Agricultural Economics Association in its series 2008 Annual Meeting, February 2-6, 2008, Dallas, Texas with number 6800.

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Date of creation: 2008
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Handle: RePEc:ags:saeaed:6800
Contact details of provider: Web page: http://www.saea.org/
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  1. Tim Coelli & Sergio Perelman, 2000. "Technical efficiency of European railways: a distance function approach," Applied Economics, Taylor & Francis Journals, vol. 32(15), pages 1967-1976.
  2. Bernard, John C. & Pesek, John D., Jr. & Fan, Chunbo, 2004. "Performance Results and Characteristics of Adopters of Genetically Engineered Soybeans in Delaware," Agricultural and Resource Economics Review, Northeastern Agricultural and Resource Economics Association, vol. 33(2), October.
  3. Hoppe, Robert A. & Perry, Janet E. & Banker, David E., 2000. "ERS Farm Typology for a Diverse Agricultural Sector," Agricultural Information Bulletins 33657, United States Department of Agriculture, Economic Research Service.
  4. Mundlak, Yair, 2001. "Production and supply," Handbook of Agricultural Economics, in: B. L. Gardner & G. C. Rausser (ed.), Handbook of Agricultural Economics, edition 1, volume 1, chapter 1, pages 3-85 Elsevier.
  5. Mundlak, Yair, 1996. "Production Function Estimation: Reviving the Primal," Econometrica, Econometric Society, vol. 64(2), pages 431-38, March.
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