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Productivity change using growth accounting and frontier-based approaches – Evidence from a Monte Carlo analysis

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  • Giraleas, Dimitris
  • Emrouznejad, Ali
  • Thanassoulis, Emmanuel
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    Abstract

    This study presents some quantitative evidence from a number of simulation experiments on the accuracy of the productivity growth estimates derived from growth accounting (GA) and frontier-based methods (namely data envelopment analysis-, corrected ordinary least squares-, and stochastic frontier analysis-based malmquist indices) under various conditions. These include the presence of technical inefficiency, measurement error, misspecification of the production function (for the GA and parametric approaches) and increased input and price volatility from one period to the next. The study finds that the frontier-based methods usually outperform GA, but the overall performance varies by experiment. Parametric approaches generally perform best when there is no functional form misspecification, but their accuracy greatly diminishes otherwise. The results also show that the deterministic approaches perform adequately even under conditions of (modest) measurement error and when measurement error becomes larger, the accuracy of all approaches (including stochastic approaches) deteriorates rapidly, to the point that their estimates could be considered unreliable for policy purposes.

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    Bibliographic Info

    Article provided by Elsevier in its journal European Journal of Operational Research.

    Volume (Year): 222 (2012)
    Issue (Month): 3 ()
    Pages: 673-683

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    Handle: RePEc:eee:ejores:v:222:y:2012:i:3:p:673-683

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

    Related research

    Keywords: Data envelopment analysis; Productivity and competitiveness; Monte Carlo analysis; Stochastic frontier analysis; Growth accounting;

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    10. Portela, Maria C.A.S. & Thanassoulis, Emmanuel, 2010. "Malmquist-type indices in the presence of negative data: An application to bank branches," Journal of Banking & Finance, Elsevier, vol. 34(7), pages 1472-1483, July.
    11. Balk, B.M., 2008. "Measuring Productivity Change without Neoclassical Assumptions: A Conceptual Analysis," ERIM Report Series Research in Management ERS-2008-077-MKT, 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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    Cited by:
    1. Hurlin, Christophe & Minea, Alexandru, 2013. "Is public capital really productive? A methodological reappraisal," European Journal of Operational Research, Elsevier, vol. 228(1), pages 122-130.
    2. Lin, Winston T. & Chuang, Chia-Hung, 2013. "Investigating and comparing the dynamic patterns of the business value of information technology over time," European Journal of Operational Research, Elsevier, vol. 228(1), pages 249-261.
    3. Kerstens, Kristiaan & Van de Woestyne, Ignace, 2014. "Comparing Malmquist and Hicks–Moorsteen productivity indices: Exploring the impact of unbalanced vs. balanced panel data," European Journal of Operational Research, Elsevier, vol. 233(3), pages 749-758.
    4. Kao, Chiang & Liu, Shiang-Tai, 2014. "Measuring performance improvement of Taiwanese commercial banks under uncertainty," European Journal of Operational Research, Elsevier, vol. 235(3), pages 755-764.

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