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Comparing Efficiency Across Markets: An Extension and Critique of the Zhang and Bartels (1998) Methodology

Author

Listed:
  • Ruben Chumpitaz

    (IESEG School of Management, LEM-CNRS (UMR 8179))

  • Kristiaan Kerstens

    () (CNRS-LEM (UMR 8179), IESEG School of Management)

  • Nicholas Paparoidamis
  • Matthias Staat

    (University of Mannheim)

Abstract

The use of non-parametric frontier methods for the evaluation of product market efficiency in heterogeneous markets seems to have gained some popularity recently. However, the statistical properties of these frontier estimators have been largely ignored. The main point is that nonparametric frontier estimators are biased and that the degree of bias depends on specific sample properties, most importantly sample size and number of dimensions of the model. To investigate the effect of this bias on comparing market efficiency, this contribution estimates the efficiency for several datasets for two main product categories. Following Zhang and Bartels (1998), these results comprise re-estimates for the larger samples limiting their size to that of the smaller samples when the model dimensions for different samples are identical. Furthermore, sample sizes are adjusted to mitigate the eventual differences in dimensions in specification. This allows comparing market efficiency for different markets on a more equal footing, since it reduces the bias effect to a minimum making the comparison of market efficiency possible. However, the article also points out the critical limitations of this Zhang and Bartels (1998) approach in certain respects. Apart from reporting these negative results, we also offer some suggestions for future work.

Suggested Citation

  • Ruben Chumpitaz & Kristiaan Kerstens & Nicholas Paparoidamis & Matthias Staat, 2010. "Comparing Efficiency Across Markets: An Extension and Critique of the Zhang and Bartels (1998) Methodology," Working Papers 2010-ECO-01, IESEG School of Management.
  • Handle: RePEc:ies:wpaper:e201001
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    Keywords

    Market Efficiency; Heterogeneous Product Markets; Bias; Monte-Carlo Simulation;

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