Bayesian Stochastic Frontier Analysis Using WinBUGS

Jim Griffin and Mark Steel

Econometrics from University Library of Munich, Germany

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.

Keywords: Efficiency; Markov chain Monte Carlo; Model comparison; Regularity; Software (search for similar items in EconPapers)
JEL-codes: C11 C14 C23 (search for similar items in EconPapers)
Pages: 19 pages
Date: 2005-09-04
New Economics Papers: this item is included in nep-ecm
Note: Type of Document - pdf; pages: 19
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Citations: View citations in EconPapers (1)

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https://econwpa.ub.uni-muenchen.de/econ-wp/em/papers/0509/0509004.pdf (application/pdf)

Related works:
Journal Article: Bayesian stochastic frontier analysis using WinBUGS (2007)
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Persistent link: https://EconPapers.repec.org/RePEc:wpa:wuwpem:0509004

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