Bayesian Inference and Gibbs Sampling in Generalized True Random-Effects Models

Kamil Makieła

Central European Journal of Economic Modelling and Econometrics, 2017, vol. 9, issue 1, 69-95

Abstract: The paper investigates Bayesian approach to estimate generalized true random-effects models (GTRE). The analysis shows that under suitably defined priors for transient and persistent inefficiency terms the posterior characteristics of such models are well approximated using simple Gibbs sampling. No model re-parameterization is required. The proposed modification not only allows us to make more reasonable (less informative) assumptions as regards prior transient and persistent inefficiency distribution but also appears to be more reliable in handling especially noisy datasets. Empirical application furthers the research into stochastic frontier analysis using GTRE models by examining the relationship between inefficiency terms in GTRE, true random-effects, generalized stochastic frontier and a standard stochastic frontier model.

Keywords: generalized true random-effects model; stochastic frontier analysis; Gibbs sampling; Bayesian inference; cost efficiency; transient and persistent efficiency (search for similar items in EconPapers)
JEL-codes: C11 C23 C51 D24 (search for similar items in EconPapers)
Date: 2017
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Citations: View citations in EconPapers (2)

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Persistent link: https://EconPapers.repec.org/RePEc:psc:journl:v:9:y:2017:i:1:p:69-95

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