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An epsilon-based measure of efficiency in DEA

Author

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  • Miki Tsutsui

    (Central Research Institute of Electric Power Industry)

  • Kaoru Tone

    (National Graduate Institute for Policy Studies)

Abstract

Firstly, we discuss differences between Farrell and Pareto-Koopmans efficiency measures in DEA, and propose a composite method for discriminating them. Then, we extend the method to so-called “epsilon based-measure (EBM).” The EBM can examine the robustness and stability of efficiency measure of DMUs regarding parametric change of input multiplier variables. Lastly, we propose a scheme for selecting an appropriate value of epsilon with recourse to actual cost shares of input resources.

Suggested Citation

  • Miki Tsutsui & Kaoru Tone, 2009. "An epsilon-based measure of efficiency in DEA," GRIPS Discussion Papers 09-13, National Graduate Institute for Policy Studies.
    • Handle: RePEc:ngi:dpaper:09-13
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    References listed on IDEAS

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    1. Charnes, A. & Cooper, W. W. & Huang, Z. M. & Sun, D. B., 1990. "Polyhedral Cone-Ratio DEA Models with an illustrative application to large commercial banks," Journal of Econometrics, Elsevier, vol. 46(1-2), pages 73-91.
    2. Tsutsui, Miki & Goto, Mika, 2009. "A multi-division efficiency evaluation of U.S. electric power companies using a weighted slacks-based measure," Socio-Economic Planning Sciences, Elsevier, vol. 43(3), pages 201-208, September.
    3. Charnes, A. & Cooper, W. W. & Rhodes, E., 1978. "Measuring the efficiency of decision making units," European Journal of Operational Research, Elsevier, vol. 2(6), pages 429-444, November.
    4. Russell G. Thompson & F. D. Singleton & Robert M. Thrall & Barton A. Smith, 1986. "Comparative Site Evaluations for Locating a High-Energy Physics Lab in Texas," Interfaces, INFORMS, vol. 16(6), pages 35-49, December.
    5. W. Cooper & L. Seiford & K. Tone & J. Zhu, 2007. "Some models and measures for evaluating performances with DEA: past accomplishments and future prospects," Journal of Productivity Analysis, Springer, vol. 28(3), pages 151-163, December.
    6. W. Cooper & Shanling Li & L. Seiford & Kaoru Tone & R. Thrall & J. Zhu, 2001. "Sensitivity and Stability Analysis in DEA: Some Recent Developments," Journal of Productivity Analysis, Springer, vol. 15(3), pages 217-246, May.
    7. Charnes, A. & Cooper, W. W. & Golany, B. & Seiford, L. & Stutz, J., 1985. "Foundations of data envelopment analysis for Pareto-Koopmans efficient empirical production functions," Journal of Econometrics, Elsevier, vol. 30(1-2), pages 91-107.
    8. William W. Cooper & Lawrence M. Seiford & Kaoru Tone, 2007. "Data Envelopment Analysis," Springer Books, Springer, edition 0, number 978-0-387-45283-8, October.
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    Cited by:

    1. Yanhong Liu & Jia Lei & Yihua Zhang, 2021. "A Study on the Sustainable Relationship among the Green Finance, Environment Regulation and Green-Total-Factor Productivity in China," Sustainability, MDPI, vol. 13(21), pages 1-27, October.
    2. Heping Ding & Yuxia Guo & Xue Wu & Cui Wang & Yu Zhang & Hongjun Liu & Yujia Liu & Aiyong Lin & Fagang Hu, 2022. "Data-Driven Resource Efficiency Evaluation and Improvement of the Logistics Industry in 30 Chinese Provinces and Cities," Sustainability, MDPI, vol. 14(15), pages 1-23, August.

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    Keywords

    Farrell efficiency; Pareto-Koopmans efficiency; stability analysis; EBM;
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