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Testing over-representation of observations in subsets of a DEA technology

  • Asmild, Mette


    (ORMS Group)

  • Hougaard, Jens Leth

    (Department of Operations Management)

  • Olesen, Ole B.


    (Department of Business and Economics)

This paper proposes a test for whether data are over-represented in a given production zone, i.e. a subset of a production possibility set which has been estimated using the non-parametric Data Envelopment Analysis (DEA) approach. A binomial test is used that relates the number of observations inside such a zone to a discrete probability weighted relative volume of that zone. A Monte Carlo simulation illustrates the performance of the proposed test statistic and suggests good estimation of both facet probabilities and the assumed common inefficiency distribution in a three dimensional input space.

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Paper provided by Department of Business and Economics, University of Southern Denmark in its series Discussion Papers of Business and Economics with number 2/2010.

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Length: 27 pages
Date of creation: 01 May 2010
Date of revision:
Handle: RePEc:hhs:sdueko:2010_002
Contact details of provider: Postal: Department of Business and Economics, University of Southern Denmark, Campusvej 55, DK-5230 Odense M, Denmark
Phone: 65 50 32 33
Fax: 65 50 32 37
Web page:

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  1. Simar, L. & Wilson, P.W., . "Sensitivity analysis of efficiency scores: how to bootstrap in nonparametric frontier models," CORE Discussion Papers RP 1304, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
  2. Nam Anh Tran & Gerald Shively & Paul Preckel, 2010. "A new method for detecting outliers in Data Envelopment Analysis," Applied Economics Letters, Taylor & Francis Journals, vol. 17(4), pages 313-316.
  3. Simar, L. & Wilson, P.W., 1999. "Statistical Inference in Nonparametric Frontier Models: the State of the Art," Papers 9904, Catholique de Louvain - Institut de statistique.
  4. Ole Olesen & N. Petersen, 2003. "Identification and Use of Efficient Faces and Facets in DEA," Journal of Productivity Analysis, Springer, vol. 20(3), pages 323-360, November.
  5. David C. Wheelock & Paul W. Wilson, 1996. "Technical progress, inefficiency and productivity change in U.S. banking, 1984-1993," Working Papers 1994-021, Federal Reserve Bank of St. Louis.
  6. Peter Bogetoft & Jens Hougaard, 2003. "Rational Inefficiencies," Journal of Productivity Analysis, Springer, vol. 20(3), pages 243-271, November.
  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.
  8. J. Hartigan, 1985. "Statistical theory in clustering," Journal of Classification, Springer, vol. 2(1), pages 63-76, December.
  9. Simar, L. & Wilson, P.W., 1998. "A General Methodology for Bootstrapping in Nonparametric Frontier Models," Papers 9811, Catholique de Louvain - Institut de statistique.
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