Measuring technical and allocative inefficiency in the translog cost system: a Bayesian approach.

In this paper, we propose simulation-based Bayesian inference procedures in a cost system that includes the cost function and the cost share equations augmented to accommodate technical and allocative inefficiency. Markov chain Monte Carlo techniques are proposed and implemented for Bayesian inferen...

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Detalles Bibliográficos
Publicado en:	Journal of Econometrics Vol. 126; no. 2; pp. 355 - 385
Autores principales:	Kumbhakar, Subal C., Tsionas, Efthymios G.
Formato:	Artículo
Publicado:	Elsevier Science June 2005
Materias:	Mathematical models Industrial efficiency Bayesian analysis Mathematical models of economics Cost Resource allocation > Mathematical models
Acceso en línea:	Ver este registro en EBSCOhost

Descripción
Sumario:	In this paper, we propose simulation-based Bayesian inference procedures in a cost system that includes the cost function and the cost share equations augmented to accommodate technical and allocative inefficiency. Markov chain Monte Carlo techniques are proposed and implemented for Bayesian inferences on costs of technical and allocative inefficiency, input price distortions and over- (under-) use of inputs. We show how to estimate a well-specified translog system (in which the error terms in the cost and cost share equations are internally consistent) in a random effects framework. The new methods are illustrated using panel data on U.S. commercial banks. Copyright (c) 2004 Elsevier B.V.