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Semiparametric Bayesian inference for stochastic frontier models
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Griffin, Jim E. and Steel, Mark F. J. (2004) Semiparametric Bayesian inference for stochastic frontier models. Journal of Econometrics, Volume 123 (Number 1). pp. 121-152. doi:10.1016/j.jeconom.2003.11.001 ISSN 0304-4076.
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Official URL: http://dx.doi.org/10.1016/j.jeconom.2003.11.001
Abstract
In this paper we propose a semiparametric Bayesian framework for the analysis of stochastic frontiers and efficiency measurement. The distribution of inefficiencies is modelled nonparametrically through a Dirichlet process prior. We suggest prior distributions and implement a Bayesian analysis through an efficient Markov chain Monte Carlo sampler, which allows us to deal with practically relevant sample sizes. We also consider the case where the efficiency distribution varies with firm characteristics. The methodology is applied to a cost frontier, estimated from a panel data set on 382 U.S. hospitals.
Item Type: | Journal Article | ||||
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Divisions: | Faculty of Science, Engineering and Medicine > Science > Statistics | ||||
Journal or Publication Title: | Journal of Econometrics | ||||
Publisher: | Elsevier BV | ||||
ISSN: | 0304-4076 | ||||
Official Date: | November 2004 | ||||
Dates: |
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Volume: | Volume 123 | ||||
Number: | Number 1 | ||||
Page Range: | pp. 121-152 | ||||
DOI: | 10.1016/j.jeconom.2003.11.001 | ||||
Status: | Peer Reviewed | ||||
Publication Status: | Published | ||||
Access rights to Published version: | Restricted or Subscription Access |
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