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Detecting Technological Heterogeneity in New York Dairy Farms

  • del Corral, Julio
  • Alvarez, Antonio
  • Tauer, Loren W.

Agricultural studies have often differentiated and estimated different technologies within a sample of farms. The common approach is to use observable farm characteristics to split the sample into several groups and subsequently estimate different functions for each group. Alternatively, unique technologies can be determined by econometric procedures such as latent class models. This paper compares the results of a latent class model with the use of a priori information to split the sample using dairy farm data in the application. Latent class separation appears to be a superior method of separating heterogeneous technologies.

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File URL: http://purl.umn.edu/49293
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Paper provided by Agricultural and Applied Economics Association in its series 2009 Annual Meeting, July 26-28, 2009, Milwaukee, Wisconsin with number 49293.

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Date of creation: 29 Apr 2009
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Handle: RePEc:ags:aaea09:49293
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  1. Jondrow, James & Knox Lovell, C. A. & Materov, Ivan S. & Schmidt, Peter, 1982. "On the estimation of technical inefficiency in the stochastic frontier production function model," Journal of Econometrics, Elsevier, vol. 19(2-3), pages 233-238, August.
  2. Ahmad, Munir & Boris E., Bravo-Ureta, 1995. "An econometric decomposition of dairy output growth," MPRA Paper 37678, University Library of Munich, Germany.
  3. Kompas, Tom & Che, Tuong Nhu, 2006. "Technology choice and efficiency on Australian dairy farms," Australian Journal of Agricultural and Resource Economics, Australian Agricultural and Resource Economics Society, vol. 50(1), March.
  4. Nobuhiko Fuwa & Christopher Edmonds & Pabitra Banik, 2007. "Are small-scale rice farmers in eastern India really inefficient? Examining the effects of microtopography on technical efficiency estimates," Agricultural Economics, International Association of Agricultural Economists, vol. 36(3), pages 335-346, 05.
  5. Luis Orea & Subal C. Kumbhakar, 2004. "Efficiency measurement using a latent class stochastic frontier model," Empirical Economics, Springer, vol. 29(1), pages 169-183, January.
  6. Carol Newman & Alan Matthews, 2006. "The productivity performance of Irish dairy farms 1984–2000: a multiple output distance function approach," Journal of Productivity Analysis, Springer, vol. 26(2), pages 191-205, October.
  7. Tauer, Loren W., 1993. "Short-Run And Long-Run Efficiencies Of New York Dairy Farms," Agricultural and Resource Economics Review, Northeastern Agricultural and Resource Economics Association, vol. 22(1), April.
  8. Greene, William, 2005. "Reconsidering heterogeneity in panel data estimators of the stochastic frontier model," Journal of Econometrics, Elsevier, vol. 126(2), pages 269-303, June.
  9. Aigner, Dennis & Lovell, C. A. Knox & Schmidt, Peter, 1977. "Formulation and estimation of stochastic frontier production function models," Journal of Econometrics, Elsevier, vol. 6(1), pages 21-37, July.
  10. Kelvin Balcombe & Iain Fraser & Mizanur Rahman & Laurence Smith, 2007. "Examining the technical efficiency of rice producers in Bangladesh," Journal of International Development, John Wiley & Sons, Ltd., vol. 19(1), pages 1-16.
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