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

 

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Opened Access A comparison between maximum likelihood and Bayesian estimation of stochastic frontier production models
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Author: Ortega, Francisco J.
Gavilán Ruiz, José Manuel
Department: Universidad de Sevilla. Departamento de Economía Aplicada I
Date: 2014
Published in: Communications in Statistics - Simulation and Computation, 43 (7), 1714-1725.
Document type: Article
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
Cite: Ortega, F.J. y Gavilán Ruiz, J.M. (2014). A comparison between maximum likelihood and Bayesian estimation of stochastic frontier production models. Communications in Statistics - Simulation and Computation, 43 (7), 1714-1725.
Size: 422.5Kb
Format: PDF

URI: https://hdl.handle.net/11441/70548

DOI: 10.1080/03610918.2012.743564

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