Bayesian Estimation of Technical Efficiency of a Single Input
AbstractThe 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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Bibliographic InfoPaper provided by Food and Agricultural Policy Research Institute (FAPRI) at Iowa State University in its series Food and Agricultural Policy Research Institute (FAPRI) Publications with number 00-wp254.
Date of creation: Nov 2000
Date of revision:
Other versions of this item:
- Lyubov A. Kurkalova & Alicia L. Carriquiry, 2000. "Bayesian Estimation of Technical Efficiency of a Single Input," Center for Agricultural and Rural Development (CARD) Publications 00-wp254, Center for Agricultural and Rural Development (CARD) at Iowa State University.
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- Koop, Gary & Osiewalski, Jacek & Steel, Mark F.J. & Broeck, Julien Van den, .
"Stochastic frontier models: a bayesian perspective,"
Open Access publications from Universidad Carlos III de Madrid
info:hdl:10016/2823, Universidad Carlos III de Madrid.
- 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.
- 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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