A comparison between maximum likelihood and Bayesian estimation of stochastic frontier production models

In this paper, the finite sample properties of the maximum likelihood and Bayesian estimators of the half-normal stochastic frontier production function are analyzed and compared through a Monte Carlo study. The results show that the Bayesian estimator should be used in preference to the maximum lik...

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Detalhes bibliográficos
Autores: Ortega, Francisco J., Gavilán Ruiz, José Manuel
Tipo de documento: artigo
Estado:Versión aceptada para publicación
Data de publicação:2014
País:España
Recursos:Universidad de Sevilla (US)
Repositório:idUS. Depósito de Investigación de la Universidad de Sevilla
OAI Identifier:oai:idus.us.es:11441/70548
Acesso em linha:https://hdl.handle.net/11441/70548
https://doi.org/10.1080/03610918.2012.743564
Access Level:Acceso aberto
Palavra-chave:Bayesian estimator
Maximum likelihood
Monte Carlo
Stochastic frontier
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spelling A comparison between maximum likelihood and Bayesian estimation of stochastic frontier production modelsOrtega, Francisco J.Gavilán Ruiz, José ManuelBayesian estimatorMaximum likelihoodMonte CarloStochastic frontierIn this paper, the finite sample properties of the maximum likelihood and Bayesian estimators of the half-normal stochastic frontier production function are analyzed and compared through a Monte Carlo study. The results show that the Bayesian estimator should be used in preference to the maximum likelihood owing to the fact that the mean square error performance is substantially better in the Bayesian frameworkTaylor & FrancisEconomía Aplicada I2014info:eu-repo/semantics/articleinfo:eu-repo/semantics/acceptedVersionapplication/pdfapplication/pdfhttps://hdl.handle.net/11441/70548https://doi.org/10.1080/03610918.2012.743564reponame:idUS. Depósito de Investigación de la Universidad de Sevillainstname:Universidad de Sevilla (US)InglésCommunications in Statistics - Simulation and Computation, 43 (7), 1714-1725.https://doi.org/10.1080/03610918.2012.743564info:eu-repo/semantics/openAccessoai:idus.us.es:11441/705482026-06-17T12:51:07Z
dc.title.none.fl_str_mv A comparison between maximum likelihood and Bayesian estimation of stochastic frontier production models
title A comparison between maximum likelihood and Bayesian estimation of stochastic frontier production models
spellingShingle A comparison between maximum likelihood and Bayesian estimation of stochastic frontier production models
Ortega, Francisco J.
Bayesian estimator
Maximum likelihood
Monte Carlo
Stochastic frontier
title_short A comparison between maximum likelihood and Bayesian estimation of stochastic frontier production models
title_full A comparison between maximum likelihood and Bayesian estimation of stochastic frontier production models
title_fullStr A comparison between maximum likelihood and Bayesian estimation of stochastic frontier production models
title_full_unstemmed A comparison between maximum likelihood and Bayesian estimation of stochastic frontier production models
title_sort A comparison between maximum likelihood and Bayesian estimation of stochastic frontier production models
dc.creator.none.fl_str_mv Ortega, Francisco J.
Gavilán Ruiz, José Manuel
author Ortega, Francisco J.
author_facet Ortega, Francisco J.
Gavilán Ruiz, José Manuel
author_role author
author2 Gavilán Ruiz, José Manuel
author2_role author
dc.contributor.none.fl_str_mv Economía Aplicada I
dc.subject.none.fl_str_mv Bayesian estimator
Maximum likelihood
Monte Carlo
Stochastic frontier
topic Bayesian estimator
Maximum likelihood
Monte Carlo
Stochastic frontier
description In this paper, the finite sample properties of the maximum likelihood and Bayesian estimators of the half-normal stochastic frontier production function are analyzed and compared through a Monte Carlo study. The results show that the Bayesian estimator should be used in preference to the maximum likelihood owing to the fact that the mean square error performance is substantially better in the Bayesian framework
publishDate 2014
dc.date.none.fl_str_mv 2014
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/acceptedVersion
format article
status_str acceptedVersion
dc.identifier.none.fl_str_mv https://hdl.handle.net/11441/70548
https://doi.org/10.1080/03610918.2012.743564
url https://hdl.handle.net/11441/70548
https://doi.org/10.1080/03610918.2012.743564
dc.language.none.fl_str_mv Inglés
language_invalid_str_mv Inglés
dc.relation.none.fl_str_mv Communications in Statistics - Simulation and Computation, 43 (7), 1714-1725.
https://doi.org/10.1080/03610918.2012.743564
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
application/pdf
dc.publisher.none.fl_str_mv Taylor & Francis
publisher.none.fl_str_mv Taylor & Francis
dc.source.none.fl_str_mv reponame:idUS. Depósito de Investigación de la Universidad de Sevilla
instname:Universidad de Sevilla (US)
instname_str Universidad de Sevilla (US)
reponame_str idUS. Depósito de Investigación de la Universidad de Sevilla
collection idUS. Depósito de Investigación de la Universidad de Sevilla
repository.name.fl_str_mv
repository.mail.fl_str_mv
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score 15,301603

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