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Purging data before productivity analysis


  • Avkiran, Necmi K.
  • Thoraneenitiyan, Nakhun


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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  • Avkiran, Necmi K. & Thoraneenitiyan, Nakhun, 2010. "Purging data before productivity analysis," Journal of Business Research, Elsevier, vol. 63(3), pages 294-302, March.
  • Handle: RePEc:eee:jbrese:v:63:y:2010:i:3:p:294-302

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    References listed on IDEAS

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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. Wu, Yueh-Cheng & Wei Kiong Ting, Irene & Lu, Wen-Min & Nourani, Mohammad & Kweh, Qian Long, 2016. "The impact of earnings management on the performance of ASEAN banks," Economic Modelling, Elsevier, vol. 53(C), pages 156-165.
    3. Almanza Ramírez, Camilo & Mora, Jhon James & Cendales, Andrés, 2017. "Profit efficiency of banks in Colombia with undesirable output: A directional distance function approach," Economics Discussion Papers 2017-90, Kiel Institute for the World Economy (IfW).
    4. repec:eee:ecofin:v:42:y:2017:i:c:p:531-545 is not listed on IDEAS
    5. Wang, Zhaohua & Li, Yi & Wang, Ke & Huang, Zhimin, 2017. "Environment-adjusted operational performance evaluation of solar photovoltaic power plants: A three stage efficiency analysis," Renewable and Sustainable Energy Reviews, Elsevier, vol. 76(C), pages 1153-1162.
    6. repec:spr:annopr:v:248:y:2017:i:1:d:10.1007_s10479-016-2191-7 is not listed on IDEAS
    7. Moradi-Motlagh, Amir & Babacan, Alperhan, 2015. "The impact of the global financial crisis on the efficiency of Australian banks," Economic Modelling, Elsevier, vol. 46(C), pages 397-406.
    8. 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.
    9. Amir Moradi-Motlagh & Ali Salman Saleh, 2014. "Re-Examining the Technical Efficiency of Australian Banks: A Bootstrap DEA Approach," Australian Economic Papers, Wiley Blackwell, vol. 53(1-2), pages 112-128, June.
    10. Hall, Maximilian J.B. & Kenjegalieva, Karligash A. & Simper, Richard, 2012. "Environmental factors affecting Hong Kong banking: A post-Asian financial crisis efficiency analysis," Global Finance Journal, Elsevier, vol. 23(3), pages 184-201.
    11. Chan, Sok-Gee & Koh, Eric H.Y. & Zainir, Fauzi & Yong, Chen-Chen, 2015. "Market structure, institutional framework and bank efficiency in ASEAN 5," Journal of Economics and Business, Elsevier, vol. 82(C), pages 84-112.


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