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Bayesian Estimation of Technical Efficiency of a Single Input


  • Lyubov A. Kurkalova
  • Alicia L. Carriquiry


The authors propose estimation of a stochastic production frontier model within a Bayesian framework to obtain the posterior distribution of single-input-oriented technical efficiency at the firm level. This method can be used to estimate the environmental efficiency of agricultural production when the technology interaction with the environment is modeled via public inputs such as soil quality and environmental conditions. All computations are carried out using Markov chain Monte Carlo methods. The approach is illustrated through its application to production data from Ukrainian collective farms.

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  • Lyubov A. Kurkalova & Alicia L. Carriquiry, 2000. "Bayesian Estimation of Technical Efficiency of a Single Input," Food and Agricultural Policy Research Institute (FAPRI) Publications 00-wp254, Food and Agricultural Policy Research Institute (FAPRI) at Iowa State University.
  • Handle: RePEc:ias:fpaper:00-wp254

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    References listed on IDEAS

    1. van den Broeck, Julien & Koop, Gary & Osiewalski, Jacek & Steel, Mark F. J., 1994. "Stochastic frontier models : A Bayesian perspective," Journal of Econometrics, Elsevier, vol. 61(2), pages 273-303, April.
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    Cited by:

    1. Gstach, Dieter, 2005. "Estimating output targets to evaluate output-specific efficiencies: A statistical framework," European Journal of Operational Research, Elsevier, vol. 161(2), pages 564-578, March.

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