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Sensitivity and Stability Analysis in DEA: Some Recent Developments

Author

Listed:
  • W. Cooper
  • Shanling Li
  • L. Seiford
  • Kaoru Tone
  • R. Thrall
  • J. Zhu

Abstract

This papersurveys recently developed analytical methods for studying thesensitivity of DEA results to variations in the data. The focusis on the stability of classification of DMUs (Decision MakingUnits) into efficient and inefficient performers. Early workon this topic concentrated on developing solution methods andalgorithms for conducting such analyses after it was noted thatstandard approaches for conducting sensitivity analyses in linearprogramming could not be used in DEA. However, some of the recentwork we cover has bypassed the need for such algorithms. Evolvingfrom early work that was confined to studying data variationsin only one input or output for only one DMU at a time, the newermethods described in this paper make it possible to determineranges within which all data may be varied for any DMU beforea reclassification from efficient to inefficient status (or vice versa) occurs. Other coverage involves recent extensionswhich include methods for determining ranges of data variationthat can be allowed when all data are varied simultaneously for all DMUs. An initial section delimits the topics to be covered.A final section suggests topics for further research. Copyright Kluwer Academic Publishers 2001

Suggested Citation

  • 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.
  • Handle: RePEc:kap:jproda:v:15:y:2001:i:3:p:217-246
    DOI: 10.1023/A:1011128409257
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    References listed on IDEAS

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    1. Léopold Simar & Paul Wilson, 2000. "Statistical Inference in Nonparametric Frontier Models: The State of the Art," Journal of Productivity Analysis, Springer, vol. 13(1), pages 49-78, January.
    2. Boljuncic, Valter, 1999. "A note on robustness of the efficient DMUs in data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 112(1), pages 240-244, January.
    3. Laurens Cherchye & Timo Kuosmanen & Thierry Post, 2000. "New Tools for Dealing with Errors-in-Variables in DEA," Public Economics Working Paper Series ces0006, Katholieke Universiteit Leuven, Centrum voor Economische Studiën, Working Group Public Economics.
    4. 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.
    5. Léopold Simar & Paul W. Wilson, 1998. "Sensitivity Analysis of Efficiency Scores: How to Bootstrap in Nonparametric Frontier Models," Management Science, INFORMS, vol. 44(1), pages 49-61, January.
    6. Robert Thrall, 2000. "Measures in DEA with an Application to the Malmquist Index," Journal of Productivity Analysis, Springer, vol. 13(2), pages 125-137, March.
    7. Zhu, Joe, 1996. "Robustness of the efficient DMUs in data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 90(3), pages 451-460, May.
    8. 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.
    9. Seiford, Lawrence M. & Zhu, Joe, 1998. "Stability regions for maintaining efficiency in data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 108(1), pages 127-139, July.
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    Keywords

    Efficiency; Data Variations; Sensitivity; Stability;

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