European Business Schools Librarian's Group

SSE/EFI Working Paper Series in Economics and Finance,
Stockholm School of Economics

No 229: A Monte Carlo Analysis of Technical Inefficiency Predictors

Subal C. Kumbhakar and Mickael Löthgren ()
Additional contact information
Subal C. Kumbhakar: Department of Economics, Postal: University of Texas at Austin, Austin, Texas 78712-1173, USA
Mickael Löthgren: Dept. of Economic Statistics, Stockholm School of Economics, Postal: Stockholm School of Economics, P.O. Box 6501, S-113 83 Stockholm, Sweden

Abstract: This paper studies performance of both point and interval predictors of technical inefficiency in the stochastic production frontier model using a Monte Carlo experiment. In point prediction we use the Jondrow et al. (1980) point predictor of technical inefficiency, while for interval prediction the Horrace and Schmidt (1996) and Hjalmarsson et al. (1996) results are used. When ML estimators are used we find negative bias in point predictions. MSEs are found to decline as the sample size increases. The mean empirical coverage accuracy of the confidence intervals are significantly below the theoretical confidence level for all values of the variance ratio.

Keywords: Bias; MSE; Point and Interval Estimators; Stochastic Production Frontier

JEL-codes: C15; D24

10 pages, March 23, 1998

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