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Identifying Suspicious Efficient Units in DEA Models

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Author Info

  • 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.

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Bibliographic Info

Paper provided by Oslo University, Department of Economics in its series Memorandum with number 30/2012.

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Length: 32 pages
Date of creation: 07 Nov 2012
Date of revision:
Handle: RePEc:hhs:osloec:2012_030

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Postal: Department of Economics, University of Oslo, P.O Box 1095 Blindern, N-0317 Oslo, Norway
Phone: 22 85 51 27
Fax: 22 85 50 35
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Web page: http://www.oekonomi.uio.no/indexe.html
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Related research

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

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References

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  1. 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.
  2. 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.
  3. 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.
  4. Allen, R. & Thanassoulis, E., 2004. "Improving envelopment in data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 154(2), pages 363-379, April.
  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. 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.
  7. 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.
  8. 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.
  9. 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.
  10. 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.
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