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A Note on Imposing Strong Complementary Slackness Conditions in DEA

Author

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  • Krivonozhko, Vladimir

    (Institute for Systems Analysis, Russian Academy of Sciences, Moscow)

  • R. Førsund, Finn

    (Dept. of Economics, University of Oslo)

  • V. Lychev, Andrey

    (Accounts Chamber of the Russian Federation, Moscow)

Abstract

A new DEA model has been introduced recently combining the primal and the dual models in order to impose strong complementary slackness conditions. It was claimed that a reference set that contains the maximum number of efficient units can then be determined. The model is very interesting as a theoretical idea. However, not only does the computational burden increase significantly, but it seems also that the basic matrices may be inherently ill-conditioned, leading to wrong results. Numerical experiments have been carried out on two real datasets of medium size with 163 and 920 units. These experiments show pervasive existence of ill-conditioned matrices leading to obviously wrong estimates of efficiency scores, and units declared as efficient reference units while actually being inefficient.

Suggested Citation

  • Krivonozhko, Vladimir & R. Førsund, Finn & V. Lychev, Andrey, 2011. "A Note on Imposing Strong Complementary Slackness Conditions in DEA," Memorandum 17/2010, Oslo University, Department of Economics.
    • Handle: RePEc:hhs:osloec:2010_017
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    References listed on IDEAS

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    1. Vladimir Krivonozhko & Finn Førsund & Andrey Lychev, 2012. "Returns-to-scale properties in DEA models: the fundamental role of interior points," Journal of Productivity Analysis, Springer, vol. 38(2), pages 121-130, October.
    2. Sueyoshi, Toshiyuki & Goto, Mika, 2010. "Measurement of a linkage among environmental, operational, and financial performance in Japanese manufacturing firms: A use of Data Envelopment Analysis with strong complementary slackness condition," European Journal of Operational Research, Elsevier, vol. 207(3), pages 1742-1753, December.
    3. V E Krivonozhko & O B Utkin & A V Volodin & I A Sablin & M Patrin, 2004. "Constructions of economic functions and calculations of marginal rates in DEA using parametric optimization methods," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 55(10), pages 1049-1058, October.
    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. Finn Førsund & Lennart Hjalmarsson & Vladimir Krivonozhko & Oleg Utkin, 2007. "Calculation of scale elasticities in DEA models: direct and indirect approaches," Journal of Productivity Analysis, Springer, vol. 28(1), pages 45-56, October.
    6. Sueyoshi, Toshiyuki & Sekitani, Kazuyuki, 2009. "An occurrence of multiple projections in DEA-based measurement of technical efficiency: Theoretical comparison among DEA models from desirable properties," European Journal of Operational Research, Elsevier, vol. 196(2), pages 764-794, July.
    7. Sueyoshi, Toshiyuki & Sekitani, Kazuyuki, 2007. "The measurement of returns to scale under a simultaneous occurrence of multiple solutions in a reference set and a supporting hyperplane," European Journal of Operational Research, Elsevier, vol. 181(2), pages 549-570, September.
    8. Sueyoshi, Toshiyuki & Sekitani, Kazuyuki, 2007. "Measurement of returns to scale using a non-radial DEA model: A range-adjusted measure approach," European Journal of Operational Research, Elsevier, vol. 176(3), pages 1918-1946, February.
    9. R. D. Banker & A. Charnes & W. W. Cooper, 1984. "Some Models for Estimating Technical and Scale Inefficiencies in Data Envelopment Analysis," Management Science, INFORMS, vol. 30(9), pages 1078-1092, September.
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    Cited by:

    1. Krivonozhko, Vladimir E. & Førsund, Finn R. & Lychev, Andrey V., 2014. "Measurement of returns to scale using non-radial DEA models," European Journal of Operational Research, Elsevier, vol. 232(3), pages 664-670.
    2. Mehdiloozad, Mahmood & Mirdehghan, S. Morteza & Sahoo, Biresh K. & Roshdi, Israfil, 2015. "On the identification of the global reference set in data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 245(3), pages 779-788.
    3. Andrey V. Lychev, 2023. "Synthetic Data Generation for Data Envelopment Analysis," Data, MDPI, vol. 8(10), pages 1-25, September.
    4. Grebel, Thomas & Stützer, Michael, 2014. "Assessment of the environmental performance of European countries over time: Addressing the role of carbon leakage and nuclear waste," Ilmenau Economics Discussion Papers 90, Ilmenau University of Technology, Institute of Economics.

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    More about this item

    Keywords

    Data envelopment analysis; BCC model; DEA/SCSC model; strong complementary slackness conditions;
    All these keywords.

    JEL classification:

    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis
    • D20 - Microeconomics - - Production and Organizations - - - General

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