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Stochastic frontier models: a bayesian perspective

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  • Koop, Gary
  • Osiewalski, Jacek
  • Steel, Mark F.J.
  • Broeck, Julien Van den

Abstract

A Bayesian approach to estimation, prediction and model comparison in composed error production models is presented. A broad range of distributions on the inefficiency term define the contending models, which can either be treated separately or pooled. Posterior results are derived for the individual efficiencies as well as for the parameters, and the differences with the usual sampling-theory approach are highlighted. The required numerical integrations are handled by Monte Carlo methods with Importance Sampling, and an empirical example illustrates the procedures.

Suggested Citation

  • Koop, Gary & Osiewalski, Jacek & Steel, Mark F.J. & Broeck, Julien Van den, 1992. "Stochastic frontier models: a bayesian perspective," UC3M Working papers. Economics 2823, Universidad Carlos III de Madrid. Departamento de Economía.
    • Handle: RePEc:cte:werepe:2823
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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.
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    7. 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.
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