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 framewor
<p>Note: ***, ** and * indicate significance at 1, 5 and 10% level, respectively</p><p>Maximum Likel...
In this paper, we generalize the stochastic frontier model to allow for heterogeneous technologies a...
In this paper we propose a semiparametric Bayesian framework for the analysis of stochastic frontier...
A regression model with deterministic frontier is considered. This type of model has hardly been stu...
A Bayesian approach to estimation, prediction and model comparison in composed error production mode...
Markov chain Monte Carlo (MCMC) methods have become a ubiquitous tool in Bayesian analysis. This pap...
In this chapter, we described a Bayesian approach to efficiency analysis using stochastic frontier m...
Stochastic frontier analysis is a popular tool to assess firm performance. Almost universally it ha...
En este trabajo se analizan y comparan las propiedades de los estimadores máximo verosímil y bayesia...
Stochastic frontier analysis (SFA) is extensively utilized to study production functions and to esti...
In this paper we propose a semiparametric Bayesian framework for the analysis of stochastic frontier...
In the econometric approach to deterministic frontier production mod- els, the use of maximum likel...
The method of maximum likelihood and Bayesian method are widely used in data processing, not only in...
The normal-gamma stochastic frontier model was proposed in Greene (1990) and Beckers and Hammond (19...
Markov chain Monte Carlo (MCMC) methods have become a ubiquitous tool in Bayesian analysis. This pap...
<p>Note: ***, ** and * indicate significance at 1, 5 and 10% level, respectively</p><p>Maximum Likel...
In this paper, we generalize the stochastic frontier model to allow for heterogeneous technologies a...
In this paper we propose a semiparametric Bayesian framework for the analysis of stochastic frontier...
A regression model with deterministic frontier is considered. This type of model has hardly been stu...
A Bayesian approach to estimation, prediction and model comparison in composed error production mode...
Markov chain Monte Carlo (MCMC) methods have become a ubiquitous tool in Bayesian analysis. This pap...
In this chapter, we described a Bayesian approach to efficiency analysis using stochastic frontier m...
Stochastic frontier analysis is a popular tool to assess firm performance. Almost universally it ha...
En este trabajo se analizan y comparan las propiedades de los estimadores máximo verosímil y bayesia...
Stochastic frontier analysis (SFA) is extensively utilized to study production functions and to esti...
In this paper we propose a semiparametric Bayesian framework for the analysis of stochastic frontier...
In the econometric approach to deterministic frontier production mod- els, the use of maximum likel...
The method of maximum likelihood and Bayesian method are widely used in data processing, not only in...
The normal-gamma stochastic frontier model was proposed in Greene (1990) and Beckers and Hammond (19...
Markov chain Monte Carlo (MCMC) methods have become a ubiquitous tool in Bayesian analysis. This pap...
<p>Note: ***, ** and * indicate significance at 1, 5 and 10% level, respectively</p><p>Maximum Likel...
In this paper, we generalize the stochastic frontier model to allow for heterogeneous technologies a...
In this paper we propose a semiparametric Bayesian framework for the analysis of stochastic frontier...