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Identifying Suspicious Efficient Units in DEA Models

Author

Listed:
  • Krivonozhko, Vladimir E.

    (National University of Science and Technology «MISiS»)

  • Førsund, Finn R.

    () (Dept. of Economics, University of Oslo)

  • Lychev, Andrey V.

    (National University of Science and Technology «MISiS»)

Abstract

Applications of the DEA models show that inadequate results may arise in some cases, two of these inadequacies being: a) too many efficient units may appear in some DEA models; b) a DEA model may show an inefficient unit from the point of view of experts as an efficient one. The purpose of this paper is to identify suspicious units that may unduly become efficient. The concept of a terminal unit is introduced for such units. It is shown by establishing theorems how units can be identified as terminal units and how different definitions of suspicious units are related. An approach for improving the adequacy of DEA models based on terminal units is suggested, and an example shown based on a real-life data set for Russian banks.

Suggested Citation

  • Krivonozhko, Vladimir E. & Førsund, Finn R. & Lychev, Andrey V., 2012. "Identifying Suspicious Efficient Units in DEA Models," Memorandum 30/2012, Oslo University, Department of Economics.
  • Handle: RePEc:hhs:osloec:2012_030
    as

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    File URL: https://www.sv.uio.no/econ/english/research/unpublished-works/working-papers/pdf-files/2012/memo-30-2012.pdf
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    References listed on IDEAS

    as
    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. Brockett, P. L. & Charnes, A. & Cooper, W. W. & Huang, Z. M. & Sun, D. B., 1997. "Data transformations in DEA cone ratio envelopment approaches for monitoring bank performances," European Journal of Operational Research, Elsevier, vol. 98(2), pages 250-268, April.
    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. Førsund, Finn R. & Kittelsen, Sverre A. & Krivonozhko, Vladimir E., 2007. "Farrell Revisited: Visualising the DEA Production Frontier," Memorandum 15/2007, Oslo University, Department of Economics.
    5. Wei, Quanling & Yan, Hong & Xiong, Lin, 2008. "A bi-objective generalized data envelopment analysis model and point-to-set mapping projection," European Journal of Operational Research, Elsevier, vol. 190(3), pages 855-876, November.
    6. Thompson, Russell G. & Langemeier, Larry N. & Lee, Chih-Tah & Lee, Euntaik & Thrall, Robert M., 1990. "The role of multiplier bounds in efficiency analysis with application to Kansas farming," Journal of Econometrics, Elsevier, vol. 46(1-2), pages 93-108.
    7. Thanassoulis, Emmanuel & Kortelainen, Mika & Allen, Rachel, 2012. "Improving envelopment in Data Envelopment Analysis under variable returns to scale," European Journal of Operational Research, Elsevier, vol. 218(1), pages 175-185.
    8. Dag Edvardsen & Finn Førsund & Sverre Kittelsen, 2008. "Far out or alone in the crowd: a taxonomy of peers in DEA," Journal of Productivity Analysis, Springer, vol. 29(3), pages 201-210, June.
    9. E. Thanassoulis & R. Allen, 1998. "Simulating Weights Restrictions in Data Envelopment Analysis by Means of Unobserved DMUs," Management Science, INFORMS, vol. 44(4), pages 586-594, April.
    10. Allen, R. & Thanassoulis, E., 2004. "Improving envelopment in data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 154(2), pages 363-379, April.
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    More about this item

    Keywords

    Data Envelopment Analysis (DEA); Terminal units; Efficiency; Weight restrictions; Domination cones;

    JEL classification:

    • C44 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Operations Research; Statistical Decision Theory
    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis
    • C67 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Input-Output Models
    • D24 - Microeconomics - - Production and Organizations - - - Production; Cost; Capital; Capital, Total Factor, and Multifactor Productivity; Capacity

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