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A Comparison Between Maximum Likelihood and Bayesian Estimation of Stochastic Frontier Production Models

2013; Taylor & Francis; Volume: 43; Issue: 7 Linguagem: Inglês

10.1080/03610918.2012.743564

ISSN

1532-4141

Autores

Francisco Javier Ortega Irizo, José Manuel Gavilán Ruiz,

Tópico(s)

Capital Investment and Risk Analysis

Resumo

Abstract 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. Keywords: Bayesian estimatorMaximum likelihoodMonte CarloStochastic frontierMathematics Subject Classification: 62J9962F1062F1568U2091B3891B82

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