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Non-metric data: a note on a neglected problem in DEA studies

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  • Norbert Hirschauer
  • Oliver Musshoff

Abstract

Data envelopment analysis (DEA) is widely used to compare the empirical performance of public institutions such as law enforcement agencies, judicial authorities or national health care systems. Many DEA analysts, however, ignore the fact that DEA efficiency values are non-metric. They consequently do not hesitate to compute (arithmetic) means. They do not hesitate either to treat DEA values as metric data in econometric analyses. Instead of providing useful insights into the performance of public bodies, the confusion of non-metric data with metric data constitutes a lack of internal validity that may cause serious fallacies. Against this background, we believe that a clear warning against an uncritical processing and interpretation of DEA values is pertinent and should be routinely considered by efficiency analysts as well as referees of efficiency papers. Copyright Springer Science+Business Media New York 2014

Suggested Citation

  • Norbert Hirschauer & Oliver Musshoff, 2014. "Non-metric data: a note on a neglected problem in DEA studies," European Journal of Law and Economics, Springer, vol. 37(3), pages 489-494, June.
    • Handle: RePEc:kap:ejlwec:v:37:y:2014:i:3:p:489-494
    DOI: 10.1007/s10657-013-9429-5
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    References listed on IDEAS

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    1. Kocher, Martin G. & Luptacik, Mikulas & Sutter, Matthias, 2006. "Measuring productivity of research in economics: A cross-country study using DEA," Socio-Economic Planning Sciences, Elsevier, vol. 40(4), pages 314-332, December.
    2. Martin Schneider, 2005. "Judicial Career Incentives and Court Performance: An Empirical Study of the German Labour Courts of Appeal," European Journal of Law and Economics, Springer, vol. 20(2), pages 127-144, September.
    3. Ray,Subhash C., 2012. "Data Envelopment Analysis," Cambridge Books, Cambridge University Press, number 9781107405264.
    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. A. Charnes & W. W. Cooper & E. Rhodes, 1981. "Evaluating Program and Managerial Efficiency: An Application of Data Envelopment Analysis to Program Follow Through," Management Science, INFORMS, vol. 27(6), pages 668-697, June.
    6. Emrouznejad, Ali & Parker, Barnett R. & Tavares, Gabriel, 2008. "Evaluation of research in efficiency and productivity: A survey and analysis of the first 30 years of scholarly literature in DEA," Socio-Economic Planning Sciences, Elsevier, vol. 42(3), pages 151-157, September.
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    Cited by:

    1. Iyad Dhaoui, 2019. "Healthcare system efficiency and its determinants: A two-stage Data Envelopment Analysis (DEA) from MENA countries," Working Papers 1320, Economic Research Forum, revised 21 Aug 2019.
    2. Thijs Jong & Edwin Woerdman, 2016. "European Energy Regulators," Competition and Regulation in Network Industries, , vol. 17(1), pages 2-31, March.

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    More about this item

    Keywords

    Data envelopment analysis; Scales of measurement; Non-metric character of technical efficiency values; C02; C61; H00; K00;
    All these keywords.

    JEL classification:

    • C02 - Mathematical and Quantitative Methods - - General - - - Mathematical Economics
    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis
    • H00 - Public Economics - - General - - - General
    • K00 - Law and Economics - - General - - - General (including Data Sources and Description)

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