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Numerical tools for the Bayesian analysis of stochastic frontier models

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Author Info
Osiewalski, J.
Steel, M. (Tilburg University, Center for Economic Research)

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Abstract

In this paper we describe the use of modern numerical integration methods for making posterior inferences in composed error stochastic frontier models for panel data or individual cross-sections. Two Monte Carlo methods have been used in practical applications. We survey these two methods in some detail and argue that Gibbs sampling methods can greatly reduce the computational difficulties involved in analyzing such models.

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Paper provided by Tilburg University, Center for Economic Research in its series Discussion Paper with number 3.

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Date of creation: 1996
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Handle: RePEc:dgr:kubcen:19963

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Keywords: Numerical Integration;

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. Geweke, John, 1989. "Bayesian Inference in Econometric Models Using Monte Carlo Integration," Econometrica, Econometric Society, vol. 57(6), pages 1317-39, November. [Downloadable!] (restricted)
  2. John Geweke, . "Posterior Simulators in Econometrics," Computing in Economics and Finance 1996 _019, Society for Computational Economics. [Downloadable!]
  3. Koop, Gary & Osiewalski, Jacek & Steel, Mark F J, 2000. "Modeling the Sources of Output Growth in a Panel of Countries," Journal of Business & Economic Statistics, American Statistical Association, vol. 18(3), pages 284-99, July.
  4. John Geweke, 1991. "Evaluating the accuracy of sampling-based approaches to the calculation of posterior moments," Staff Report 148, Federal Reserve Bank of Minneapolis. [Downloadable!]
  5. Koop, G. & Osiewalski, J. & Steel, M.F.J., 1995. "The Components of Output Growth: A Croos-Country Analysis," Papers 9517, Tilburg - Center for Economic Research.
  6. Greene, William H., 1990. "A Gamma-distributed stochastic frontier model," Journal of Econometrics, Elsevier, vol. 46(1-2), pages 141-163. [Downloadable!] (restricted)
  7. Schmidt, Peter & Sickles, Robin C, 1984. "Production Frontiers and Panel Data," Journal of Business & Economic Statistics, American Statistical Association, vol. 2(4), pages 367-74, October.
  8. RITTERÊ, Christian & SIMARÊ, Leopold, 1994. "Pitfalls of Normal-Gamma Stochastic Frontier Models," CORE Discussion Papers 1994041, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
  9. Koop, Gary & Osiewalski, Jacek & Steel, Mark F J, 1994. "Bayesian Efficiency Analysis with a Flexible Form: The AIM Cost Function," Journal of Business & Economic Statistics, American Statistical Association, vol. 12(3), pages 339-46, July.
  10. John F. Geweke, 1995. "Posterior simulators in econometrics," Working Papers 555, Federal Reserve Bank of Minneapolis. [Downloadable!]
  11. Bauer, Paul W., 1990. "Recent developments in the econometric estimation of frontiers," Journal of Econometrics, Elsevier, vol. 46(1-2), pages 39-56. [Downloadable!] (restricted)
  12. KOOPÊ , Gary & OSIEWALSKI, Jacek & STEELÊ, MarkÊ, 1995. "Measuring the Sources of Output Growth in a Panel of Countries," CORE Discussion Papers 1995042, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
  13. 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)
  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. [Downloadable!] (restricted)
  15. 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)
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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. Myungsup Kim & Yangseon Kim & Peter Schmidt, 2006. "On the Accuracy of Bootstrap Confidence Intervals for Efficiency Levels in Stochastic Frontier Models with Panel Data," Working Papers 0704, University of Crete, Department of Economics. [Downloadable!]
    Other versions:
  2. Supawat Rungsuriyawiboon & Chris O’Donnell, 2004. "Curvature-Constrained Estimates of Technical Efficiency and Returns to Scale for U.S. Electric Utilities," CEPA Working Papers Series WP072004, School of Economics, University of Queensland, Australia. [Downloadable!]
  3. Fernandez, C. & Osiewalski, J. & Steel, M., 1996. "On the use of panel data in bayesian stochastic frontier models," Discussion Paper 17, Tilburg University, Center for Economic Research. [Downloadable!]
  4. 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. [Downloadable!]
    Other versions:
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