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Robust Lorenz Curves: A Semiparametric Approach

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  • Frank A Cowell
  • Maria-Pia Victoria-Feser

Abstract

Lorenz curves and second-order dominance criteria are known to be sensitive to data contamination in the right tail of the distribution. We propose two ways of dealing with the problem: (1) Estimate Lorenz curves using parametric models for income distributions, and (2) Combine empirical estimation with a parametric (robust) estimation of the upper tail of the distribution using the Pareto model. Approach (2) is preferred because of its flexibility. Using simulations we show the dramatic effect of a few contaminated data on the Lorenz ranking and the performance of the robust approach (2). Statistical inference tools are also provided.

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File URL: http://sticerd.lse.ac.uk/dps/darp/DARP50.pdf
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Bibliographic Info

Paper provided by Suntory and Toyota International Centres for Economics and Related Disciplines, LSE in its series STICERD - Distributional Analysis Research Programme Papers with number 50.

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Date of creation: May 2001
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Handle: RePEc:cep:stidar:50

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Web page: http://sticerd.lse.ac.uk/_new/publications/default.asp

Related research

Keywords: Welfare dominance; Lorenz curve; Pareto model; M-estimators.;

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References

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  1. Frank A Cowell & Maria-Pia Victoria-Feser, 2001. "Distributional Dominance with Dirty Data," STICERD - Distributional Analysis Research Programme Papers 51, Suntory and Toyota International Centres for Economics and Related Disciplines, LSE.
  2. McDonald, James B & Ransom, Michael R, 1979. "Functional Forms, Estimation Techniques and the Distribution of Income," Econometrica, Econometric Society, vol. 47(6), pages 1513-25, November.
  3. Frank A Cowell & Maria-Pia Victoria-Feser, 1996. "Welfare Judgements in the Presence Contaminated Data," STICERD - Distributional Analysis Research Programme Papers 13, Suntory and Toyota International Centres for Economics and Related Disciplines, LSE.
  4. Frank Cowell & Maria-Pia Victoria-Feser, 1999. "Statistical inference for welfare under complete and incomplete information," LSE Research Online Documents on Economics 2054, London School of Economics and Political Science, LSE Library.
  5. Frank A. Cowell & Maria-Pia Victoria-Feser, 2002. "Welfare Rankings in the Presence of Contaminated Data," Econometrica, Econometric Society, vol. 70(3), pages 1221-1233, May.
  6. Moyes, Patrick, 1987. "A new concept of Lorenz domination," Economics Letters, Elsevier, vol. 23(2), pages 203-207.
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Cited by:
  1. Frank A. Cowell & Emmanuel Flachaire, 2004. "Income distribution and inequality measurement : the problem of extreme values," Cahiers de la Maison des Sciences Economiques v04101, Université Panthéon-Sorbonne (Paris 1).
  2. Cowell, Frank A. & Victoria-Feser, Maria-Pia, 2006. "Distributional Dominance With Trimmed Data," Journal of Business & Economic Statistics, American Statistical Association, vol. 24, pages 291-300, July.
  3. Frank Cowell & Maria-Pia Victoria-Feser, 2003. "Distribution-Free Inference for Welfare Indices under Complete and Incomplete Information," Journal of Economic Inequality, Springer, vol. 1(3), pages 191-219, December.
  4. Hasegawa, Hikaru & Kozumi, Hideo, 2003. "Estimation of Lorenz curves: a Bayesian nonparametric approach," Journal of Econometrics, Elsevier, vol. 115(2), pages 277-291, August.

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