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The Effect of Sample Size on the Mean Efficiency in DEA: Comment

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  • Matthias Staat

Abstract

Zhang and Bartels (1998) show formallyhow DEA efficiency scores are affected by sample size. They demonstratethat comparing measures of structural inefficiency between samplesof different sizes leads to biased results. This note arguesthat this type of sample size bias has much wider implicationsthan suggested by their example. Models which implicitly restrictthe comparison set like some models for non-discretionary variableslead to biased efficiency scores as well. A reanalysis of theBanker and Morey (1986b) data shows that the efficiency scoresderived there are significantly influenced by the variation insample size implicit in their model. Copyright Kluwer Academic Publishers 2001

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  • Matthias Staat, 2001. "The Effect of Sample Size on the Mean Efficiency in DEA: Comment," Journal of Productivity Analysis, Springer, vol. 15(2), pages 129-137, March.
  • Handle: RePEc:kap:jproda:v:15:y:2001:i:2:p:129-137
    DOI: 10.1023/A:1007826405826
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    References listed on IDEAS

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    1. Yu, Chunyan, 1998. "The effects of exogenous variables in efficiency measurement--A monte carlo study," European Journal of Operational Research, Elsevier, vol. 105(3), pages 569-580, March.
    2. Yun Zhang & Robert Bartels, 1998. "The Effect of Sample Size on the Mean Efficiency in DEA with an Application to Electricity Distribution in Australia, Sweden and New Zealand," Journal of Productivity Analysis, Springer, vol. 9(3), pages 187-204, March.
    3. Ray, Subhash C., 1988. "Data envelopment analysis, nondiscretionary inputs and efficiency: an alternative interpretation," Socio-Economic Planning Sciences, Elsevier, vol. 22(4), pages 167-176.
    4. Ruggiero, John, 1996. "On the measurement of technical efficiency in the public sector," European Journal of Operational Research, Elsevier, vol. 90(3), pages 553-565, May.
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    6. Aristovnik, Aleksander & Yang, Guo-liang & Song, Yao-yao & Ravšelj, Dejan, 2023. "Industrial performance of the top R&D enterprises in world-leading economies: A metafrontier approach," Socio-Economic Planning Sciences, Elsevier, vol. 89(C).
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    10. Julie Harrison & Paul Rouse & Jamie Armstrong, 2012. "Categorical and continuous non-discretionary variables in data envelopment analysis: a comparison of two single-stage models," Journal of Productivity Analysis, Springer, vol. 37(3), pages 261-276, June.
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    13. García-Alonso, Carlos R. & Salvador-Carulla, Luis & Fernández-Rodríguez, Vicente, 2015. "Evaluation of system efficiency using the Monte Carlo DEA: The case of small health areasAuthor-Name: Torres-Jiménez, Mercedes," European Journal of Operational Research, Elsevier, vol. 242(2), pages 525-535.

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