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Testing for Productive Efficiency with Errors-in-Variables: with an application to the Dutch electricity sesctor

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  • Kuosmanen, T.
  • Post, G.T.

Abstract

We develop a nonparametric test of productive efficiency that accounts for the possibility of errors-in-variables. The test allows for statistical inference based on the extreme value distribution of the L?? norm. In contrast to the test proposed by Varian, H (1985): 'Nonparametric Analysis of Optimising Behaviour with Measurement Error, Journal of Econometrics 30, 445-458, our test can be computed using simple enumeration algorithms or linear programming. An empirical application for the Dutch electricity sector illustrates the proposed test procedure.

Suggested Citation

  • Kuosmanen, T. & Post, G.T., 2001. "Testing for Productive Efficiency with Errors-in-Variables: with an application to the Dutch electricity sesctor," ERIM Report Series Research in Management ERS-2001-22-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.
    • Handle: RePEc:ems:eureri:88
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    References listed on IDEAS

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    Cited by:

    1. 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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    More about this item

    Keywords

    data envelopment analysis (DEA); errors-in-variables; extreme value theory; hypothesis testing; nonparametric production analysis;
    All these keywords.

    JEL classification:

    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • G3 - Financial Economics - - Corporate Finance and Governance
    • M - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics

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