A Monte Carlo Study of Old and New Frontier Methods for Efficiency Measurement
AbstractThis study presents the results of an extensive Monte Carlo experiment to compare different methods of efficiency analysis. In addition to traditional parametric-stochastic and nonparametric-deterministic methods recently developed robust nonparametric-stochastic methods are considered. The experimental design comprises a wide variety of situations with different returns-to-scale regimes, substitution elasticities and outlying observations. As the results show, the new robust nonparametric-stochastic methods should not be used without cross-checking by other methods like stochastic frontier analysis or data envelopment analysis. These latter methods appear quite robust in the experiments.
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Bibliographic InfoPaper provided by Darmstadt Technical University, Department of Business Administration, Economics and Law, Institute of Economics (VWL) in its series Darmstadt Discussion Papers in Economics with number 48892.
Date of creation: Feb 2011
Date of revision:
Publication status: Published in Darmstadt Discussion Papers in Economics . 200 (2011-02)
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Monte Carlo experiment; efficiency measurement; nonparametric stochastic methods;
This paper has been announced in the following NEP Reports:
- NEP-ALL-2011-02-19 (All new papers)
- NEP-CIS-2011-02-19 (Confederation of Independent States)
- NEP-ECM-2011-02-19 (Econometrics)
- NEP-EFF-2011-02-19 (Efficiency & Productivity)
- NEP-ORE-2011-02-19 (Operations Research)
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.:
- Johannes Van Biesebroeck, 2007.
"ROBUSTNESS OF PRODUCTIVITY ESTIMATES -super-* ,"
Journal of Industrial Economics,
Wiley Blackwell, vol. 55(3), pages 529-569, 09.
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