Bayesian estimation of the half-normal regression model with deterministic frontier

A regression model with deterministic frontier is considered. This type of model has hardly been studied, partly owing to the difficulty in the application of maximum likelihood estimation since this is a non-regular model. As an alternative, the Bayesian methodology is proposed and analysed. Through the Gibbs algorithm, the inference of the parameters of the model and of the individual efficiencies are relatively straightforward. The results of the simulations indicate that the utilized method performs reasonably well.

[1]  W. Meeusen,et al.  Efficiency Estimation from Cobb-Douglas Production Functions with Composed Error , 1977 .

[2]  D. Aigner,et al.  P. Schmidt, 1977,?Formulation and estimation of stochastic frontier production function models,? , 1977 .

[3]  A. Alvarez,et al.  Technical efficiency and farm size: a conditional analysis , 2004 .

[4]  John Whiteman,et al.  BENCHMARKING TELECOMMUNICATIONS USING DATA ENVELOPMENT ANALYSIS , 1993 .

[5]  G. Battese,et al.  ESTIMATION OF A PRODUCTION FRONTIER MODEL: WITH APPLICATION TO THE PASTORAL ZONE OF EASTERN AUSTRALIA , 1977 .

[6]  Léopold Simar,et al.  How to improve the performances of DEA/FDH estimators in the presence of noise? , 2007 .

[7]  Francisco Javier Ortega Irizo,et al.  Algunas observaciones acerca del uso de software en la estimación del modelo Half-Normal , 2011 .

[8]  M. Farrell.  The Measurement of Productive Efficiency , 1957 .

[9]  Adrian F. M. Smith,et al.  Sampling-Based Approaches to Calculating Marginal Densities , 1990 .

[10]  Rafael A. Cuesta.  A Production Model With Firm-Specific Temporal Variation in Technical Inefficiency: With Application to Spanish Dairy Farms , 2000 .

[11]  Francisco Javier Ortega Irizo,et al.  Comparing bayesian and corrected least-squares estimators in frontier production models , 2009 .

[12]  A. U.S.,et al.  FORMULATION AND ESTIMATION OF STOCHASTIC FRONTIER PRODUCTION FUNCTION MODELS , 2001 .

[13]  Timothy Coelli,et al.  An Introduction to Efficiency and Productivity Analysis , 1997 .

[14]  Peter Schmidt,et al.  A Monte Carlo study of estimators of stochastic frontier production functions , 1980 .

[15]  Arthur Pewsey.  Improved Likelihood Based Inference for the General Half-Normal Distribution , 2004 .

[16]  L. Devroye.  Non-Uniform Random Variate Generation , 1986 .

[17]  T. Coelli.  Estimators and hypothesis tests for a stochastic frontier function: A Monte Carlo analysis , 1995 .

[18]  W. Greene.  Maximum likelihood estimation of econometric frontier functions , 1980 .

[19]  H. Jeffreys,et al.  Theory of probability , 1896 .

[20]  M. Steel,et al.  Stochastic frontier models: a bayesian perspective , 1994 .

[21]  Joseph G. Ibrahim,et al.  Monte Carlo Methods in Bayesian Computation , 2000 .

[22]  Jim E. Griffin,et al.  Bayesian stochastic frontier analysis using WinBUGS , 2007 .

[23]  P. Schmidt,et al.  Estimation and inference in parametric deterministic frontier models , 2013 .

[24]  N. L. Johnson,et al.  Continuous Univariate Distributions. , 1995 .

[25]  G. C. Tiao,et al.  Bayesian inference in statistical analysis , 1973 .