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

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  • Laurens Cherchye
  • Timo Kuosmanen
  • Thierry Post

Abstract

The axiomatic literature on technical efficiency measurement has drawn attention to the indication problem of the Debreu-Farrell (DF) measure. We follow a shadow price approach to preserve the DF benchmark while reconciling it with the Koopmans efficiency characterization. First, we define a set of Koopmans efficient references that can be rationalized in a similar way as the DF projection. The indication problem is then captured using a measure of implicit allocative or mix efficiency, also interpretable as a dominance measure in price space. We consequently present a mix-adjusted DF framework for efficiency measurement in which e.g. the Zieschang (1984) procedure can be

Suggested Citation

  • Laurens Cherchye & Timo Kuosmanen & Thierry Post, 2000. "New Tools for Dealing with Errors-in-Variables in DEA," Public Economics Working Paper Series ces0006, Katholieke Universiteit Leuven, Centrum voor Economische Studiën, Working Group Public Economics.
  • Handle: RePEc:wpe:papers:ces0006
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    References listed on IDEAS

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    1. 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.
    2. 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.
    3. William Cooper & Zhimin Huang & Vedran Lelas & Susan Li & Ole Olesen, 1998. "Chance Constrained Programming Formulations for Stochastic Characterizations of Efficiency and Dominance in DEA," Journal of Productivity Analysis, Springer, vol. 9(1), pages 53-79, January.
    4. 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.
    5. 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.
    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. Dieter Gstach, 1998. "Another Approach to Data Envelopment Analysis in Noisy Environments: DEA+," Journal of Productivity Analysis, Springer, vol. 9(2), pages 161-176, March.
    8. Li, Susan X., 1998. "Stochastic models and variable returns to scales in data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 104(3), pages 532-548, February.
    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.
    10. O. B. Olesen & N. C. Petersen, 1995. "Chance Constrained Efficiency Evaluation," Management Science, INFORMS, vol. 41(3), pages 442-457, March.
    11. 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.
    12. Koenker, Roger, 2000. "Galton, Edgeworth, Frisch, and prospects for quantile regression in econometrics," Journal of Econometrics, Elsevier, vol. 95(2), pages 347-374, April.
    13. repec:cor:louvrp:-571 is not listed on IDEAS
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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. W. Cooper & Shanling Li & L. Seiford & Kaoru Tone & R. Thrall & J. Zhu, 2001. "Sensitivity and Stability Analysis in DEA: Some Recent Developments," Journal of Productivity Analysis, Springer, vol. 15(3), pages 217-246, May.
    3. José O. Maldifassi & Agustín De la Cuesta W., 2016. "A two-stage process for explaining the relative efficiency of small and medium-size firms in Chile," International Journal of Entrepreneurship and Innovation Management, Inderscience Enterprises Ltd, vol. 20(1/2), pages 99-116.
    4. Dehnokhalaji, Akram & Korhonen, Pekka J. & Köksalan, Murat & Nasrabadi, Nasim & Wallenius, Jyrki, 2010. "Efficiency analysis to incorporate interval-scale data," European Journal of Operational Research, Elsevier, vol. 207(2), pages 1116-1121, December.
    5. 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 University Rotterdam.
    6. Timo Kuosmanen & Thierry Post, 2002. "Nonparametric Efficiency Analysis under Price Uncertainty: A First-Order Stochastic Dominance Approach," Journal of Productivity Analysis, Springer, vol. 17(3), pages 183-200, May.

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