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Integrating spatial dependence into stochastic frontier analysis

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  • Areal, Francisco J
  • Balcombe, Kelvin
  • Tiffin, R

Abstract

An approach to incorporate spatial dependence into Stochastic Frontier analysis is developed and applied to a sample of 215 dairy farms in England and Wales. A number of alternative specifications for the spatial weight matrix are used to analyse the effect of these on the estimation of spatial dependence. Estimation is conducted using a Bayesian approach and results indicate that spatial dependence is present when explaining technical inefficiency.

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File URL: http://mpra.ub.uni-muenchen.de/24961/
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Bibliographic Info

Paper provided by University Library of Munich, Germany in its series MPRA Paper with number 24961.

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Date of creation: 2010
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Handle: RePEc:pra:mprapa:24961

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Keywords: Spatial dependence; technical efficiency; Bayesian; spatial weight matrix;

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  1. Tim J. Coelli & Chris O'Donnell, 2003. "A Bayesian Approach To Imposing Curvature On Distance Functions," CEPA Working Papers Series WP032003, School of Economics, University of Queensland, Australia.
  2. Brummer, B. & Glauben, T. & Lu, W., 2006. "Policy reform and productivity change in Chinese agriculture: A distance function approach," Journal of Development Economics, Elsevier, vol. 81(1), pages 61-79, October.
  3. Fernandez, Carmen & Koop, Gary & Steel, Mark, 2000. "A Bayesian analysis of multiple-output production frontiers," Journal of Econometrics, Elsevier, vol. 98(1), pages 47-79, September.
  4. Kim, Chong Won & Phipps, Tim T. & Anselin, Luc, 1998. "Measuring The Benefits Of Air Quality Improvement: A Spatial Hedonic Approach," 1998 Annual meeting, August 2-5, Salt Lake City, UT 20959, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
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