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Bayesian stochastic frontier analysis using WinBUGS

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  • Jim Griffin

    ()

  • Mark Steel

    ()

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. Although WinBUGS may not be that efficient for more complicated models, it does make Bayesian inference with stochastic frontier models easily accessible for applied researchers and its generic structure allows for a lot of flexibility in model specification. Copyright Springer Science+Business Media, LLC 2007

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File URL: http://hdl.handle.net/10.1007/s11123-007-0033-y
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Bibliographic Info

Article provided by Springer in its journal Journal of Productivity Analysis.

Volume (Year): 27 (2007)
Issue (Month): 3 (June)
Pages: 163-176

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Handle: RePEc:kap:jproda:v:27:y:2007:i:3:p:163-176

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Web page: http://www.springerlink.com/link.asp?id=100296

Related research

Keywords: Efficiency; Markov chain Monte Carlo; Model comparison; Regularity; Software; C11; C23; D24;

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References

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  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.
  2. 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.
  3. Jim E. Griffin & Mark F.J. Steel, 2002. "Semiparametric Bayesian Inference for Stochastic Frontier Models," Econometrics 0209001, EconWPA, revised 18 Sep 2002.
  4. Stevenson, Rodney E., 1980. "Likelihood functions for generalized stochastic frontier estimation," Journal of Econometrics, Elsevier, vol. 13(1), pages 57-66, May.
  5. 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.
  6. Efthymios G. Tsionas, 2002. "Stochastic frontier models with random coefficients," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 17(2), pages 127-147.
  7. KOOP, Gary & STEEL, Mark F. & OSIEWALSKI, Jacek, 1994. "Posterior Analysis of Stochastic Frontier Models using Gibbs Sampling," CORE Discussion Papers 1994061, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
  8. Dorfman, Jeffrey H. & Koop, Gary, 2005. "Current developments in productivity and efficiency measurement," Journal of Econometrics, Elsevier, vol. 126(2), pages 233-240, June.
  9. Greene, William H., 1990. "A Gamma-distributed stochastic frontier model," Journal of Econometrics, Elsevier, vol. 46(1-2), pages 141-163.
  10. 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.
  11. 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.
  12. 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.
  13. Lyubov A. Kurkalova & Alicia Carriquiry, 2002. "An Analysis of Grain Production Decline During the Early Transition in Ukraine: A Bayesian Inference," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 84(5), pages 1256-1263.
  14. 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.
  15. 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.
  16. KOOP , Gary & OSIEWALSKI , Jacek & STEEL , Mark, 1995. "Bayesian Efficiency Analysis through Individual Effects : Hospital Cost Frontiers," CORE Discussion Papers 1995036, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
  17. J. Griffin & M. Steel, 2008. "Flexible mixture modelling of stochastic frontiers," Journal of Productivity Analysis, Springer, vol. 29(1), pages 33-50, February.
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Citations

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Cited by:
  1. Seongho Song & David Yi, 2011. "The fundraising efficiency in U.S. non-profit art organizations: an application of a Bayesian estimation approach using the stochastic frontier production model," Journal of Productivity Analysis, Springer, vol. 35(2), pages 171-180, April.
  2. Goto, Mika & Makhija, Anil K., 2007. "The Impact of Competition and Corporate Structure on Productive Efficiency: The Case of the U.S. Electric Utility Industry, 1990-2004," Working Paper Series 2007-10, Ohio State University, Charles A. Dice Center for Research in Financial Economics.
  3. Tabak, Benjamin M. & Langsch Tecles, Patricia, 2010. "Estimating a Bayesian stochastic frontier for the Indian banking system," International Journal of Production Economics, Elsevier, vol. 125(1), pages 96-110, May.
  4. Bellio, Ruggero & Grassetti, Luca, 2011. "Semiparametric stochastic frontier models for clustered data," Computational Statistics & Data Analysis, Elsevier, vol. 55(1), pages 71-83, January.
  5. Patricia Tecles & Benjamin M. Tabak, 2010. "Determinants of Bank Efficiency: the case of Brazil," Working Papers Series 210, Central Bank of Brazil, Research Department.
  6. Philippe K Widmer & Peter Zweifel & Mehdi Farsi, 2010. "Accounting For Heterogeneity In The Measurement of Hospital Performance," Economics Discussion / Working Papers 10-21, The University of Western Australia, Department of Economics.
  7. Hajargasht, Gholamreza & Coelli, Tim & Rao, D.S. Prasada, 2008. "A dual measure of economies of scope," Economics Letters, Elsevier, vol. 100(2), pages 185-188, August.
  8. Tonini, Axel & Matus, Silvia Saravia & Gomez y Paloma, Sergio, 2011. "A Bayesian Total Factor Productivity Analysis of Tropical Agricultural Systems in Central-Western Africa And South-East Asia," 2011 International Congress, August 30-September 2, 2011, Zurich, Switzerland 116088, European Association of Agricultural Economists.
  9. Philippe K. Widmer, 2011. "Does prospective payment increase hospital (in)efficiency? Evidence from the Swiss hospital sector," ECON - Working Papers 053, Department of Economics - University of Zurich.
  10. Jose L. Gallizo & Jordi Moreno & Ioana Iuliana Pop (Grigorescu), 2011. "Banking Efficiency And European Integration. Implications Of The Banking Reform In Romania," Annales Universitatis Apulensis Series Oeconomica, Faculty of Sciences, "1 Decembrie 1918" University, Alba Iulia, vol. 2(13), pages 25.
  11. 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.

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