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A Monte Carlo Analysis of Technical Inefficiency Predictors

Subal Kumbhakar and Mickael Löthgren ()
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Mickael Löthgren: Dept. of Economic Statistics, Stockholm School of Economics, Postal: Stockholm School of Economics, P.O. Box 6501, S-113 83 Stockholm, Sweden

No 229, SSE/EFI Working Paper Series in Economics and Finance from Stockholm School of Economics

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 (search for similar items in EconPapers)
JEL-codes: C15 D24 (search for similar items in EconPapers)
Pages: 10 pages
Date: 1998-03-23
New Economics Papers: this item is included in nep-ecm, nep-eff and nep-mic
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (5)

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