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A Monte Carlo Study on the Finite Sample Properties of the Gibbs Sampling Method for a Stochastic Frontier Model

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  • Xingyuan Zhang

Abstract

In this paper we use Monte Carlo study to investigate the finite sample properties of the Bayesian estimator obtained by the Gibbs sampler and its classical counterpart (i.e. the MLE) for a stochastic frontier model. Our Monte Carlo results show that the MSE performance of the estimates of Gibbs sampling are substantially better than that of the MLE. Copyright Kluwer Academic Publishers 2000

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  • Xingyuan Zhang, 2000. "A Monte Carlo Study on the Finite Sample Properties of the Gibbs Sampling Method for a Stochastic Frontier Model," Journal of Productivity Analysis, Springer, vol. 14(1), pages 71-83, July.
    • Handle: RePEc:kap:jproda:v:14:y:2000:i:1:p:71-83
    DOI: 10.1023/A:1007895912705
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    7. Jondrow, James & Knox Lovell, C. A. & Materov, Ivan S. & Schmidt, Peter, 1982. "On the estimation of technical inefficiency in the stochastic frontier production function model," Journal of Econometrics, Elsevier, vol. 19(2-3), pages 233-238, August.
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    Cited by:

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    2. James M. Sfiridis & Kenneth N. Daniels, 2004. "The Relative Cost Efficiency of Stock versus Mutual Thrifts: A Bayesian Approach," The Financial Review, Eastern Finance Association, vol. 39(1), pages 153-179, February.

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