Numerical Tools for the Bayesian Analysis of Stochastic Frontier Models

J. Osiewalski, M.F.J. Steel

Research output: Working paperDiscussion paperOther research output

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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.
Original languageEnglish
Place of PublicationTilburg
PublisherEconometrics
Number of pages17
Volume1996-03
Publication statusPublished - 1996

Publication series

NameCentER Discussion Paper
Volume1996-03

Fingerprint

Stochastic Frontier
Bayesian Analysis
Numerical Integration Methods
Gibbs Sampling
Panel Data
Sampling Methods
Monte Carlo method
Cross section
Model

Keywords

  • Monte Carlo Technique
  • Numerical Integration

Cite this

Osiewalski, J., & Steel, M. F. J. (1996). Numerical Tools for the Bayesian Analysis of Stochastic Frontier Models. (CentER Discussion Paper; Vol. 1996-03). Tilburg: Econometrics.
Osiewalski, J. ; Steel, M.F.J. / Numerical Tools for the Bayesian Analysis of Stochastic Frontier Models. Tilburg : Econometrics, 1996. (CentER Discussion Paper).
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Osiewalski, J & Steel, MFJ 1996 'Numerical Tools for the Bayesian Analysis of Stochastic Frontier Models' CentER Discussion Paper, vol. 1996-03, Econometrics, Tilburg.

Numerical Tools for the Bayesian Analysis of Stochastic Frontier Models. / Osiewalski, J.; Steel, M.F.J.

Tilburg : Econometrics, 1996. (CentER Discussion Paper; Vol. 1996-03).

Research output: Working paperDiscussion paperOther research output

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AB - 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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KW - Numerical Integration

M3 - Discussion paper

VL - 1996-03

T3 - CentER Discussion Paper

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Osiewalski J, Steel MFJ. Numerical Tools for the Bayesian Analysis of Stochastic Frontier Models. Tilburg: Econometrics. 1996. (CentER Discussion Paper).