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The joint measurement of technical and allocative inefficiencies: an application of Bayesian inference in nonlinear random-effects models.
- Article from:
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Journal of the American Statistical Association
- Article date:
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September 1, 2005
- Author:
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;
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Copyright informationCOPYRIGHT 2005 American Statistical Association. This material is published under license from the publisher through the Gale Group, Farmington Hills, Michigan. All inquiries regarding rights should be directed to the Gale Group. (Hide copyright information)
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This article estimates technical and allocative inefficiencies and increase in costs therefrom of individual firms using a translog cost system consisting of the cost function and the cost share equations. We call it a nonlinear random-effects system because technical and allocative inefficiencies are random (hence the term random effects) and are separated from the random noise terms appearing in each equation of the system, and because the inefficiency terms appear in the system in a highly nonlinear fashion, which helps in separating them from random errors. We use Bayesian inference procedures based on Markov chain Monte Carlo (MCMC) techniques to estimate the proposed system. ...
<0), then we can say that bank i is underusing (overusing) the jth input (relative to input 5). The extent of overuse and underuse cannot be determined from the numerical values of [[xi].sub.j,i]. All we can say from the numerical values of [[xi].sub.j,i] is that if [[xi].sub.j,i]>
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