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  • 标题:Bayesian Inference and Gibbs Sampling in Generalized True Random-Effects Models
  • 本地全文:下载
  • 作者:Kamil Makieła
  • 期刊名称:Central European Journal of Economic Modelling and Econometrics
  • 印刷版ISSN:2080-0886
  • 电子版ISSN:2080-119X
  • 出版年度:2017
  • 期号:1
  • 页码:69-95
  • 语种:English
  • 出版社:Polska Akademia Nauk
  • 摘要:The paper investigates Bayesian approach to estimate generalized truerandom-effects models (GTRE). The analysis shows that under suitably definedpriors for transient and persistent inefficiency terms the posterior characteristicsof such models are well approximated using simple Gibbs sampling. No modelre-parameterization is required. The proposed modification not only allowsus to make more reasonable (less informative) assumptions as regards priortransient and persistent inefficiency distribution but also appears to be morereliable in handling especially noisy datasets. Empirical application furthersthe research into stochastic frontier analysis using GTRE models by examiningthe relationship between inefficiency terms in GTRE, true random-effects,generalized stochastic frontier and a standard stochastic frontier model.
  • 关键词:generalized true random-effects model;stochastic frontier analysis;Gibbs sampling;Bayesian inference;cost efficiency;transient and persistent efficiency
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