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Numerical Tools for the Bayesian Analysis of Stochastic Frontier Models

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Author Info

  • Osiewalski, J.
  • Steel, M.F.J.

    (Tilburg University, Center for Economic Research)

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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Bibliographic Info

Paper provided by Tilburg University, Center for Economic Research in its series Discussion Paper with number 1996-03.

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Date of creation: 1996
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Handle: RePEc:dgr:kubcen:199603

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Web page: http://center.uvt.nl

Related research

Keywords: Monte Carlo Technique; Numerical Integration;

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Cited by:
  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.
  2. Fernández, C. & Osiewalski, J. & Steel, M.F.J., 1996. "On the Use of Panel Data in Bayesian Stochastic Frontier Models," Discussion Paper 1996-17, Tilburg University, Center for Economic Research.
  3. Fernandez, Carmen & Osiewalski, Jacek & Steel, Mark F. J., 1997. "On the use of panel data in stochastic frontier models with improper priors," Journal of Econometrics, Elsevier, vol. 79(1), pages 169-193, July.
  4. Lambarraa, Fatima, 2011. "Dynamic Efficiency Analysis of Spanish Outdoor and Greenhouse Horticulture Sector," 2011 International Congress, August 30-September 2, 2011, Zurich, Switzerland 114408, European Association of Agricultural Economists.

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