A Monte Carlo Simulation comparing DEA, SFA and two simple approaches to combine efficiency estimates
In certain circumstances, both researchers and policy makers are faced with the challenge of determining individual eciency scores for each decision making unit (DMU) under consideration. In this study, we use a Monte Carlo experimentation to analyze the optimal approach to determining individual eciency scores. Our rst research objective is a systematic comparison of the two most popular estimation methods, data envelopment (DEA) and stochastic frontier analysis (SFA). Accordingly we extend the existing comparisons in several ways. We are thus able to identify the factors which in uence the performance of the methods and give additional information about the reasons for performance variation. Furthermore, we indicate speci c situations in which an estimation technique proves superior. As none of the methods is in all respects superior, in real word applications, such as energy incentive regulation systems, it is regarded as \best-practice" to combine the estimates obtained from DEA and SFA. Hence in a second step, we compare the approaches to transforming the estimates into eciency scores, with the elementary estimates of the two methods. Our results demonstrate that combination approaches can actually constitute \best-practice" for estimating precise e- ciency scores.
|Date of creation:|
|Date of revision:|
|Contact details of provider:|| Postal: Am Stadtgraben 9, 48143 Münster|
Phone: (02 51) 83-2 29 71
Fax: (02 51) 83-2 29 70
Web page: http://www.wiwi.uni-muenster.de/insiwo
More information through EDIRC
References listed on IDEAS
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.:
- 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.
- Gong, Byeong-Ho & Sickles, Robin C., 1992.
"Finite sample evidence on the performance of stochastic frontiers and data envelopment analysis using panel data,"
Journal of Econometrics,
Elsevier, vol. 51(1-2), pages 259-284.
- Gong, Byeong-Ho & Sickles, Robin C., 1991. "Finite Sample Evidence on the Performance of Stochastic Frontiers and Data Envelopment Analysis Using Panel Data," Working Papers 91-12, C.V. Starr Center for Applied Economics, New York University.
- Timo Kuosmanen & Mika Kortelainen, 2012. "Stochastic non-smooth envelopment of data: semi-parametric frontier estimation subject to shape constraints," Journal of Productivity Analysis, Springer, vol. 38(1), pages 11-28, August.
- Haney, Aoife Brophy & Pollitt, Michael G., 2009.
"Efficiency analysis of energy networks: An international survey of regulators,"
Elsevier, vol. 37(12), pages 5814-5830, December.
- Brophy Haney, A. & Pollitt, M.G., 2009. "Efficiency Analysis of Energy Networks : An International Survey of Regulators," Cambridge Working Papers in Economics 0926, Faculty of Economics, University of Cambridge.
- Adler, Nicole & Yazhemsky, Ekaterina, 2010. "Improving discrimination in data envelopment analysis: PCA-DEA or variable reduction," European Journal of Operational Research, Elsevier, vol. 202(1), pages 273-284, April.
- R. Banker & W. Cooper & E. Grifell-Tajté & Jesús Pastor & Paul Wilson & Eduardo Ley & C. Lovell, 1994. "Validation and generalization of DEA and its uses," TOP: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 2(2), pages 249-314, December.
- Banker, Rajiv D. & Gadh, Vandana M. & Gorr, Wilpen L., 1993. "A Monte Carlo comparison of two production frontier estimation methods: Corrected ordinary least squares and data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 67(3), pages 332-343, June.
When requesting a correction, please mention this item's handle: RePEc:muc:wpaper:201177. See general information about how to correct material in RePEc.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Norbert Hiller)
If references are entirely missing, you can add them using this form.