[Research Paper]Bayesian Stochastic Frontier Analysis Using WinBUGS

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收藏 2013-11-10

Bayesian stochastic frontier analysis using WinBUGS

J.E. Griffin¤ and M.F.J. Steel
Department of Statistics, University of Warwick, Coventry, CV4 7AL, U.K.

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. Although WinBUGS may not be that efficient for more complicated
models, it does make Bayesian inference with stochastic frontier models easily accessible for applied
researchers and its generic structure allows for a lot of flexibility in model specification.

Keywords: Efficiency, Markov chain Monte Carlo, Model comparison, Regularity, Software