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The Small-Sample Bias of the Gini Coefficient: Results and Implications for Empirical Research

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Author Info
George Deltas (University of Illinois, Urbana-Champaign.)

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Abstract

The Gini coefficient is a downward-biased measure of inequality in small populations when income is generated by one of three common distributions. The paper discusses the sources of bias and argues that this property is far more general. This has implications for (i) the comparison of inequality among subsamples, some of which may be small, and (ii) the use of the Gini in measuring firm size inequality in markets with a small number of firms. The small-sample bias has often led to misperceptions about trends in industry concentration. A small-sample adjustment results in a reduced bias, which can no longer be signed. This remaining bias rises with the dispersion and falls with increasing skewness of the distribution. Finally, an empirical example illustrates the importance of using the adjusted Gini. In this example it is shown that, controlling for market characteristics, larger shipping cartels include a set of firms that is stochastically identical (in terms of relative size) to those of smaller shipping cartels. Copyright (c) 2003 President and Fellows of Harvard College and the Massachusetts Institute of Technology.

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File URL: http://www.mitpressjournals.org/doi/pdfplus/10.1162/rest.2003.85.1.226
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Publisher Info
Article provided by MIT Press in its journal Review of Economics and Statistics.

Volume (Year): 85 (2003)
Issue (Month): 1 (01)
Pages: 226-234
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Handle: RePEc:tpr:restat:v:85:y:2003:i:1:p:226-234

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  1. John Golden, 2008. "A Simple Geometric Approach to Approximating the Gini Coefficient," Journal of Economic Education, Helen Dwight Reid Foundation, vol. 39(1), pages 68-77. [Downloadable!]
  2. Tom Van Ourti & Philip Clarke, 2008. "The Bias of the Gini Coefficient due to Grouping," Tinbergen Institute Discussion Papers 08-095/3, Tinbergen Institute. [Downloadable!]
  3. Heshmati, Almas, 2004. "Data Issues and Databases Used in Analysis of Growth, Poverty and Economic Inequality," IZA Discussion Papers 1263, Institute for the Study of Labor (IZA). [Downloadable!]
  4. César Martinelli & Rich Sicotte, 2004. "Voting in Cartels: Theory and Evidence from the Shipping Industry," Levine's Bibliography 122247000000000598, UCLA Department of Economics. [Downloadable!]
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  5. David E. Giles, 2005. "The Bias of Inequality Measures in Very Small Samples: Some Analytic Results," Econometrics Working Papers 0514, Department of Economics, University of Victoria. [Downloadable!]
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