Measuring Technical and Allocative Inefficiency in the Translog Cost System: A Bayesian Approach

Posted: 29 Dec 2004

See all articles by Subal C. Kumbhakar

Subal C. Kumbhakar

State University of New York (SUNY) at Binghamton - Department of Economics

Efthymios G. Tsionas

Athens University of Economics and Business - Department of Economics

Abstract

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.

Keywords: Technical efficiency, translog cost function system, Markov Chain Monte Carlo techniques, panel data, nonlinear random effect models and commercial banks

JEL Classification: C11, C13

Suggested Citation

Kumbhakar, Subal C. and Tsionas, Efthymios (Efthymios) G., Measuring Technical and Allocative Inefficiency in the Translog Cost System: A Bayesian Approach. Available at SSRN: https://ssrn.com/abstract=634241

Subal C. Kumbhakar

State University of New York (SUNY) at Binghamton - Department of Economics ( email )

Binghamton, NY 13902-6000
United States

Efthymios (Efthymios) G. Tsionas (Contact Author)

Athens University of Economics and Business - Department of Economics ( email )

76 Patission Street
GR-10434 Athens
Greece
+301 8203 (Phone)
+301 8203 301 (Fax)

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