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Far out or alone in the crowd: Classification of selfevaluators in DEA

Author

Listed:
  • Edvardsen, Dag Fjeld

    (The Norwegian Building Research Institute, Norway)

  • Føsund, Finn R.

    (Department of Economics)

  • Kittelsen, Sverre A.C.

    (The Frisch Centre, Norway)

Abstract

The units found strongly efficient in DEA studies on efficiency can be divided into self-evaluators and active peers, depending on whether the peers are referencing any inefficient units or not. The contribution of the paper starts with subdividing the selfevaluators into interior and exterior ones. The exterior self-evaluators are efficient “by default”; there is no firm evidence from observations for the classification. These units should therefore not been regarded as efficient, and be removed from the observations on efficiency scores when performing a two-stage analysis of explaining the distribution of the scores. A method for classifying self-evaluators based on the additive DEA model is developed. The application to municipal nursing- and home care services of Norway shows significant effects of removing exterior self-evaluators from the data when doing a two-stage analysis.

Suggested Citation

  • Edvardsen, Dag Fjeld & Føsund, Finn R. & Kittelsen, Sverre A.C., 2009. "Far out or alone in the crowd: Classification of selfevaluators in DEA," HERO Online Working Paper Series 2003:7, University of Oslo, Health Economics Research Programme.
  • Handle: RePEc:hhs:oslohe:2003_007
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    File URL: http://www.hero.uio.no/publicat/2003/HERO2003_7.pdf
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    References listed on IDEAS

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    1. Edvardsen, Dag Fjeld & Forsund, Finn R., 2003. "International benchmarking of electricity distribution utilities," Resource and Energy Economics, Elsevier, vol. 25(4), pages 353-371, October.
    2. Finn Førsund & Nikias Sarafoglou, 2002. "On the Origins of Data Envelopment Analysis," Journal of Productivity Analysis, Springer, vol. 17(1), pages 23-40, January.
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    4. Seitz, Wesley D, 1971. "Productive Efficiency in the Steam-Electric Generating Industry," Journal of Political Economy, University of Chicago Press, vol. 79(4), pages 878-886, July-Aug..
    5. 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.
    6. Simar, Leopold & Wilson, Paul W., 2007. "Estimation and inference in two-stage, semi-parametric models of production processes," Journal of Econometrics, Elsevier, vol. 136(1), pages 31-64, January.
    7. 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. Førsund, Finn R. & Kittelsen, Sverre A.C & Lindseth, Frode, 2005. "Efficiency And Productivity Of Norwegian Tax Offices," Memorandum 29/2005, Oslo University, Department of Economics.

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    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
    • D24 - Microeconomics - - Production and Organizations - - - Production; Cost; Capital; Capital, Total Factor, and Multifactor Productivity; Capacity
    • I19 - Health, Education, and Welfare - - Health - - - Other
    • L32 - Industrial Organization - - Nonprofit Organizations and Public Enterprise - - - Public Enterprises; Public-Private Enterprises

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