On the Ability to Disentangle the Two Errors in the Normal/Half -Normal Stochastic Frontier Model
In this paper, a simulation experiment is carried out in the framework of the normal/half -normal stochastic frontier model in order to analyse its ability to disentangle the two types of errors that form the composite error. According to the results obtained through the mean bias and the mean squar...
| Autores: | , |
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| Tipo de recurso: | artículo |
| Estado: | Versión publicada |
| Fecha de publicación: | 2015 |
| País: | España |
| Institución: | Universidad de Sevilla (US) |
| Repositorio: | idUS. Depósito de Investigación de la Universidad de Sevilla |
| OAI Identifier: | oai:idus.us.es:11441/70569 |
| Acceso en línea: | https://hdl.handle.net/11441/70569 |
| Access Level: | acceso abierto |
| Palabra clave: | Production Models Stochastic Frontier Maximum Likelihood Monte Carlo Modelos de producción Frontera estocástica Máxima verosimilitud |
| Sumario: | In this paper, a simulation experiment is carried out in the framework of the normal/half -normal stochastic frontier model in order to analyse its ability to disentangle the two types of errors that form the composite error. According to the results obtained through the mean bias and the mean squared error of the parameters and efficiencies, and via Spearman rank correlation between actual and estimated efficiencies, a good performance of the model is only obtained when considering medium -sized or large samples and the variance of the inefficiencies highly contributes to that of the composite error. The problems of wrong skewness and absence of random error are also addressed. The influence on the results of selecting a wrong distribution for the inefficienc y term is also analysed |
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