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New Tools for Dealing with Errors-in-Variables in DEA

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Author Info

  • Laurens CHERCHYE
  • Timo KUOSMANEN
  • Thierry POST

Abstract

We develop a series of novel conceptual tools to systematically account for errors-in-variables in Data Envelopment Analysis (DEA). These tools allow for statistical inference while requiring minimal statistical distribution assumptions, and therefore constitute a valuable addition to the tools currently available for dealing with errors-in-variables. An empirical application for large European Union financial institutions illustrates the proposed approach.

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File URL: http://www.econ.kuleuven.be/eng/ew/discussionpapers/Dps00/Dps0006.pdf
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Bibliographic Info

Paper provided by Katholieke Universiteit Leuven, Centrum voor Economische Studiën in its series Center for Economic Studies - Discussion papers with number ces0006.

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Date of creation: Mar 2000
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Handle: RePEc:ete:ceswps:ces0006

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Related research

Keywords: Data Envelopment Analysis (DEA); errors-in-variables; efficiency depth; robust reference sets; financial institutions;

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References

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  1. Koenker, Roger, 2000. "Galton, Edgeworth, Frisch, and prospects for quantile regression in econometrics," Journal of Econometrics, Elsevier, vol. 95(2), pages 347-374, April.
  2. Gong, Linguo & Sun, Bruce, 1995. "Efficiency measurement of production operations under uncertainty," International Journal of Production Economics, Elsevier, vol. 39(1-2), pages 55-66, April.
  3. Berger, Allen N. & Humphrey, David B., 1997. "Efficiency of financial institutions: International survey and directions for future research," European Journal of Operational Research, Elsevier, vol. 98(2), pages 175-212, April.
  4. Per Andersen & Niels Christian Petersen, 1993. "A Procedure for Ranking Efficient Units in Data Envelopment Analysis," Management Science, INFORMS, vol. 39(10), pages 1261-1264, October.
  5. O. B. Olesen & N. C. Petersen, 1995. "Chance Constrained Efficiency Evaluation," Management Science, INFORMS, vol. 41(3), pages 442-457, March.
  6. Charnes, A. & Neralic, L., 1990. "Sensitivity analysis of the additive model in data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 48(3), pages 332-341, October.
  7. 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.
  8. Kuosmanen, Timo & Post, Thierry, 2003. "Measuring economic efficiency with incomplete price information," European Journal of Operational Research, Elsevier, vol. 144(2), pages 454-457, January.
  9. Zhu, Joe, 1996. "Robustness of the efficient DMUs in data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 90(3), pages 451-460, May.
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Cited by:
  1. Maria Sousa & Borko Stošić, 2005. "Technical Efficiency of the Brazilian Municipalities: Correcting Nonparametric Frontier Measurements for Outliers," Journal of Productivity Analysis, Springer, vol. 24(2), pages 157-181, October.
  2. Kuosmanen, T. & Post, G.T., 2001. "Non-Parametric Tests for Firm Efficiency in Case of Errors-in-Variables," ERIM Report Series Research in Management ERS-2001-06-F&A, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus Uni.

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