A Bayesian analysis of multiple-output production frontiers
In this paper we develop Bayesian tools for estimating multi-output production frontiers in applications where only input and output data are available. Firm-specific inefficiency is measured relative to such frontiers. Our work has important differences from the existing literature, which either as...
| Autores: | , , |
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| Tipo de recurso: | artículo |
| Estado: | Versión aceptada para publicación |
| Fecha de publicación: | 2000 |
| País: | España |
| Institución: | Consejo Superior de Investigaciones Científicas (CSIC) |
| Repositorio: | DIGITAL.CSIC. Repositorio Institucional del CSIC |
| OAI Identifier: | oai:digital.csic.es:10261/341951 |
| Acceso en línea: | http://hdl.handle.net/10261/341951 https://api.elsevier.com/content/abstract/scopus_id/0002293819 |
| Access Level: | acceso abierto |
| Palabra clave: | Banking data Efficiency Markov chain Monte Carlo Productivity |
| Sumario: | In this paper we develop Bayesian tools for estimating multi-output production frontiers in applications where only input and output data are available. Firm-specific inefficiency is measured relative to such frontiers. Our work has important differences from the existing literature, which either assumes a classical econometric perspective with restrictive functional form assumptions, or a non-stochastic approach which directly estimates the output distance function. Bayesian inference is implemented using a Markov chain Monte Carlo algorithm. A banking application shows the ease and practicality of our approach. © 2000 Elsevier Science S.A. All rights reserved. |
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