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Integrating spatial dependence into stochastic frontier analysis

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

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/24961/1/MPRA_paper_24961.pdf
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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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  1. 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.
  2. Won Kim, Chong & Phipps, Tim T. & Anselin, Luc, 2003. "Measuring the benefits of air quality improvement: a spatial hedonic approach," Journal of Environmental Economics and Management, Elsevier, vol. 45(1), pages 24-39, January.
  3. 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.
  4. Carmen Fernandez & Gary Koop & M. F. J. Steel, 2004. "A Bayesian analysis of multiple-output production frontiers," ESE Discussion Papers 21, Edinburgh School of Economics, University of Edinburgh.
  5. Alexandra M. Schmidt & Ajax R. B. Moreira & Thais C. O. Fonseca & Steven M. Helfand, 2006. "Spatial Stochastic Frontier Models: accounting for unobserved local determinants of inefficiency," Discussion Papers 1220, Instituto de Pesquisa Econômica Aplicada - IPEA.
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