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Data envelopment analysis with stochastic data

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  • John Ruggiero

    (University of Dayton)

Abstract

Data envelopment analysis (DEA) has proven to be a useful technique in evaluating the efficiency of decision making units that produce multiple-outputs using multiple-inputs. However, the ability to estimate efficiency reliably is hampered in the presence of measurement error and other statistical noise. A main and legitimate criticism of all deterministic models is the inability to separate out measurement error from inefficiency, both of which are unobserved. In this paper, we consider panel data models of efficiency estimation. One DEA model that has been used averages cross-sectional efficiency estimates across time and has been shown to work relatively well. In this paper, it is shown that this approach leads to biased efficiency estimates and provide an alternative model that corrects this problem. The approaches are compared using simulated data for illustrative purposes.

Suggested Citation

  • John Ruggiero, 2004. "Data envelopment analysis with stochastic data," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 55(9), pages 1008-1012, September.
    • Handle: RePEc:pal:jorsoc:v:55:y:2004:i:9:d:10.1057_palgrave.jors.2601779
    DOI: 10.1057/palgrave.jors.2601779
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    References listed on IDEAS

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    1. 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.
    2. O. B. Olesen & N. C. Petersen, 1995. "Chance Constrained Efficiency Evaluation," Management Science, INFORMS, vol. 41(3), pages 442-457, March.
    3. Gong, Byeong-Ho & Sickles, Robin C., 1992. "Finite sample evidence on the performance of stochastic frontiers and data envelopment analysis using panel data," Journal of Econometrics, Elsevier, vol. 51(1-2), pages 259-284.
    4. Ruggiero, John, 1999. "Efficiency estimation and error decomposition in the stochastic frontier model: A Monte Carlo analysis," European Journal of Operational Research, Elsevier, vol. 115(3), pages 555-563, June.
    5. Banker, Rajiv D. & Gadh, Vandana M. & Gorr, Wilpen L., 1993. "A Monte Carlo comparison of two production frontier estimation methods: Corrected ordinary least squares and data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 67(3), pages 332-343, June.
    6. Ondrich, Jan & Ruggiero, John, 2001. "Efficiency measurement in the stochastic frontier model," European Journal of Operational Research, Elsevier, vol. 129(2), pages 434-442, March.
    7. W W Cooper & H Deng & Z Huang & S X Li, 2002. "Chance constrained programming approaches to technical efficiencies and inefficiencies in stochastic data envelopment analysis," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 53(12), pages 1347-1356, December.
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    Cited by:

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    15. Necmiddin Bagdadioglu & Catherine Waddams Price & Thomas Weyman-Jones, 2006. "Measuring Potential Gains from Mergers among Electricity Distribution Companies in Turkey using a Non-Parametric Model," Working Paper series, University of East Anglia, Centre for Competition Policy (CCP) 2006-13, Centre for Competition Policy, University of East Anglia, Norwich, UK..
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    stochastic frontier; DEA;

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