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Fitting Parametric Lorenz Curves to Grouped Income Distributions--A Critical Note

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  • Schader, Martin
  • Schmid, Friedrich
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    Abstract

    The paper surveys various parametric Lorenz curves to be fitted to ground income data in order to obtain an estimate for the Gini measure of inequality. The curves are fitted to 16 sets of empirical income data. The results are compared to the results of the purely nonparametric method (due to Gastwirth) of computing lower and upper bounds for the Gini measure. It is shown that most of the parametric curves are unreliable in that they may produce estimates outside the bounds.

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    Bibliographic Info

    Article provided by Springer in its journal Empirical Economics.

    Volume (Year): 19 (1994)
    Issue (Month): 3 ()
    Pages: 361-70

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    Handle: RePEc:spr:empeco:v:19:y:1994:i:3:p:361-70

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    Cited by:
    1. Tom Van Ourti & Philip Clarke, 2008. "The Bias of the Gini Coefficient due to Grouping," Tinbergen Institute Discussion Papers 08-095/3, Tinbergen Institute.
    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.
    3. Ogwang, Tomson & Rao, U. L. Gouranga, 2000. "Hybrid models of the Lorenz curve," Economics Letters, Elsevier, vol. 69(1), pages 39-44, October.
    4. Le–Le Zou, 2012. "The impacting factors of vulnerability to natural hazards in China: an analysis based on structural equation model," Natural Hazards, International Society for the Prevention and Mitigation of Natural Hazards, vol. 62(1), pages 57-70, May.

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