Numerical Tools for the Bayesian Analysis of Stochastic Frontier Models

J. Osiewalski, M.F.J. Steel

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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

Keywords

  • Monte Carlo Technique
  • Numerical Integration

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