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

DOI10.1080/03610918.2012.743564zbMath1333.62184OpenAlexW2008303222MaRDI QIDQ5418898

Francisco J. Ortega, Jose M. Gavilan

Publication date: 30 May 2014

Published in: Communications in Statistics - Simulation and Computation (Search for Journal in Brave)

Full work available at URL: https://idus.us.es/handle//11441/70548

zbMATH Keywords

Monte Carlomaximum likelihoodstochastic frontierBayesian estimator

Mathematics Subject Classification ID

Point estimation (62F10) Bayesian inference (62F15) Linear inference, regression (62J99) Production models (90B30)

Uses Software

• FRONTIER

Cites Work

• Maximum likelihood estimation of econometric frontier functions
• Formulation and estimation of stochastic frontier production function models
• Stochastic frontier models. A Bayesian perspective
• Efficiency Estimation from Cobb-Douglas Production Functions with Composed Error

This page was built for publication: A Comparison Between Maximum Likelihood and Bayesian Estimation of Stochastic Frontier Production Models