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Bayesian Stochastic Frontier Analysis Using WinBUGS

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Author Info
Jim Griffin (University of Warwick)
Mark Steel (University of Warwick)

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Abstract

Markov chain Monte Carlo (MCMC) methods have become a ubiquitous tool in Bayesian analysis. This paper implements MCMC methods for Bayesian analysis of stochastic frontier models using the WinBUGS package, a freely available software. General code for cross-sectional and panel data are presented and various ways of summarizing posterior inference are discussed. Several examples illustrate that analyses with models of genuine practical interest can be performed straightforwardly and model changes are easily implemented.

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Publisher Info
Paper provided by EconWPA in its series Econometrics with number 0509004.

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Length: 19 pages
Date of creation: 04 Sep 2005
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Handle: RePEc:wpa:wuwpem:0509004

Note: Type of Document - pdf; pages: 19
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Web page: http://129.3.20.41

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Related research
Keywords: Efficiency; Markov chain Monte Carlo; Model comparison; Regularity; Software;

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Find related papers by JEL classification:
C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: General - - - Bayesian Analysis
C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: General - - - Semiparametric and Nonparametric Methods
C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data

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References listed on IDEAS
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
  1. Fernandez C. & Koop G. & Steel M.F.J., 2002. "Multiple-Output Production With Undesirable Outputs: An Application to Nitrogen Surplus in Agriculture," Journal of the American Statistical Association, American Statistical Association, vol. 97, pages 432-442, June. [Downloadable!] (restricted)
    Other versions:
  2. Karl C. Ennsfellner & Danielle Lewis & Randy I. Anderson, 2004. "Production Efficiency in the Austrian Insurance Industry: A Bayesian Examination," Journal of Risk & Insurance, The American Risk and Insurance Association, vol. 71(1), pages 135-159. [Downloadable!] (restricted)
  3. Christensen, Laurits R & Greene, William H, 1976. "Economies of Scale in U.S. Electric Power Generation," Journal of Political Economy, University of Chicago Press, vol. 84(4), pages 655-76, August. [Downloadable!] (restricted)
  4. Terrell, Dek, 1996. "Incorporating Monotonicity and Concavity Conditions in Flexible Functional Forms," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 11(2), pages 179-94, March-Apr. [Downloadable!] (restricted)
  5. Griffin, J. E. & Steel, M. F. J., 2004. "Semiparametric Bayesian inference for stochastic frontier models," Journal of Econometrics, Elsevier, vol. 123(1), pages 121-152, November. [Downloadable!] (restricted)
    Other versions:
  6. Kurkalova, Lyubov A & Carriquiry, Alicia, 2002. " An Analysis of Grain Production Decline during the Early Transition in Ukraine: A Bayesian Inference," American Journal of Agricultural Economics, American Agricultural Economics Association, vol. 84(5), pages 1256-63. [Downloadable!] (restricted)
  7. Meeusen, Wim & van den Broeck, Julien, 1977. "Efficiency Estimation from Cobb-Douglas Production Functions with Composed Error," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 18(2), pages 435-44, June. [Downloadable!] (restricted)
  8. 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. [Downloadable!] (restricted)
  9. Stevenson, Rodney E., 1980. "Likelihood functions for generalized stochastic frontier estimation," Journal of Econometrics, Elsevier, vol. 13(1), pages 57-66, May. [Downloadable!] (restricted)
  10. Kumbhakar, Subal C. & Tsionas, Efthymios G., 2005. "Measuring technical and allocative inefficiency in the translog cost system: a Bayesian approach," Journal of Econometrics, Elsevier, vol. 126(2), pages 355-384, June. [Downloadable!] (restricted)
  11. Koop, Gary & Osiewalski, Jacek & Steel, Mark F. J., 1997. "Bayesian efficiency analysis through individual effects: Hospital cost frontiers," Journal of Econometrics, Elsevier, vol. 76(1-2), pages 77-105. [Downloadable!] (restricted)
  12. Efthymios G. Tsionas, 2002. "Stochastic frontier models with random coefficients," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 17(2), pages 127-147. [Downloadable!]
  13. Dorfman, Jeffrey H. & Koop, Gary, 2005. "Current developments in productivity and efficiency measurement," Journal of Econometrics, Elsevier, vol. 126(2), pages 233-240, June. [Downloadable!] (restricted)
  14. J. Griffin & M. Steel, 2008. "Flexible mixture modelling of stochastic frontiers," Journal of Productivity Analysis, Springer, vol. 29(1), pages 33-50, February. [Downloadable!] (restricted)
  15. Greene, William H., 1990. "A Gamma-distributed stochastic frontier model," Journal of Econometrics, Elsevier, vol. 46(1-2), pages 141-163. [Downloadable!] (restricted)
  16. David J. Spiegelhalter & Nicola G. Best & Bradley P. Carlin & Angelika van der Linde, 2002. "Bayesian measures of model complexity and fit," Journal Of The Royal Statistical Society Series B, Royal Statistical Society, vol. 64(4), pages 583-639. [Downloadable!] (restricted)
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Cited by:
(explanations, Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.)

  1. Juan Martín & Concepción Román & Augusto Voltes-Dorta, 2009. "A stochastic frontier analysis to estimate the relative efficiency of Spanish airports," Journal of Productivity Analysis, Springer, vol. 31(3), pages 163-176, June. [Downloadable!] (restricted)
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