A Monte Carlo Analysis of Technical Inefficiency Predictors

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A Monte Carlo Analysis of Technical Inefficiency Predictors

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Kumbhakar, Subal C. (Department of Economics)
Löthgren, Mickael () (Dept. of Economic Statistics, Stockholm School of Economics)

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Subal C. Kumbhakar

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.

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Paper provided by Stockholm School of Economics in its series Working Paper Series in Economics and Finance with number 229.

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Length: 10 pages
Date of creation: 23 Mar 1998
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Handle: RePEc:hhs:hastef:0229

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Find related papers by JEL classification:
C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: General - - - Statistical Simulation Methods
D24 - Microeconomics - - Production and Organizations - - - Production; Capital and Total Factor Productivity; Capacity

This paper has been announced in the following NEP Reports:

NEP-ECM-1998-04-26 (Econometrics)
NEP-EFF-1998-05-28 (Efficiency & Productivity)
NEP-MIC-1998-04-21 (Microeconomics)

References listed on IDEAS
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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. [Downloadable!] (restricted)
William C. Horrace & Peter Schmidt, 2002. "Confidence Statements for Efficiency Estimates from Stochastic Frontier Models," Econometrics 0206006, EconWPA. [Downloadable!]
Aigner, Dennis & Lovell, C. A. Knox & Schmidt, Peter, 1977. "Formulation and estimation of stochastic frontier production function models," Journal of Econometrics, Elsevier, vol. 6(1), pages 21-37, July. [Downloadable!] (restricted)
Olson, Jerome A. & Schmidt, Peter & Waldman, Donald M., 1980. "A Monte Carlo study of estimators of stochastic frontier production functions," Journal of Econometrics, Elsevier, vol. 13(1), pages 67-82, May. [Downloadable!] (restricted)

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(explanations, Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.)

Rafaela Dios-Palomares & Jose Miguel Martínez Paz, 2004. "A spreading method to improve efficiency prediction," Economic Working Papers at Centro de Estudios Andaluces E2004/31, Centro de Estudios Andaluces. [Downloadable!]
Konstantinos Giannakas & Kien C. Tran & Vangelis Tzouvelekas, 2003. "Predicting technical effciency in stochastic production frontier models in the presence of misspecification: a Monte-Carlo analysis," Applied Economics, Taylor and Francis Journals, vol. 35(2), pages 153-161, January. [Downloadable!] (restricted)

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