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Purging data before productivity analysis

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  • Avkiran, Necmi K.
  • Thoraneenitiyan, Nakhun
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    Abstract

    Studies of productivity often ignore measurement error and fail to distinguish between exogenous and endogenous factors in adjusting for the environment. This failure may misguide managerial decisions on benchmarking, ranking, and remuneration. For example, common relative efficiency techniques such as data envelopment analysis (DEA) assume away the measurement error. This article combines DEA with stochastic frontier analysis in a synergistic multiple-stage analysis to purge the estimate of managerial performance of measurement error and exogenous factors. Removing the impact of measurement error indicates the largest rise in productivity. Removing the impact of exogenous factors raises discriminatory power. The method offers a number of innovations over other studies in the literature. The article is also the first to investigate the profit efficiency of the commercial banks in the United Arab Emirates.

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    Bibliographic Info

    Article provided by Elsevier in its journal Journal of Business Research.

    Volume (Year): 63 (2010)
    Issue (Month): 3 (March)
    Pages: 294-302

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    Handle: RePEc:eee:jbrese:v:63:y:2010:i:3:p:294-302

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    Web page: http://www.elsevier.com/locate/jbusres

    Related research

    Keywords: Productivity Purging data Measurement error Environment;

    References

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    Cited by:
    1. Avkiran, Necmi K., 2011. "Association of DEA super-efficiency estimates with financial ratios: Investigating the case for Chinese banks," Omega, Elsevier, vol. 39(3), pages 323-334, June.
    2. Maximilian J. B. Hall & Karligash A. Kenjegalieva & Richard Simper, 2008. "Environmental Factors Affecting Hong Kong Banking: A Post-Asian Financial Crisis Efficiency Analysis," Working Papers 122008, Hong Kong Institute for Monetary Research.
    3. Avkiran, Necmi K. & Goto, Mika, 2011. "A tool for scrutinizing bank bailouts based on multi-period peer benchmarking," Pacific-Basin Finance Journal, Elsevier, vol. 19(5), pages 447-469, November.

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