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Lorenz Curve Interpolation and the Gini Coefficient


  • Nicholas Rohde

    () (University of Queensland)


This article presents a simple non-polynomial spline that may be used to construct Lorenz curves from grouped data. The spline is naturally convex and works by determining a series of piecewise segments that may be joined to give a smooth and continuous Lorenz curve. The method is illustrated with an empirical example using income decile data from the Philippines from 1991-2003 where the proposed technique is used alongside other parametric and non-parametric methods. We also use the spline to approximate some known Lorenz curves and assess the technique by comparing the estimated Gini coefficient to the known Gini. Our findings suggest that the method is an attractive addition to the body of techniques used for developing Lorenz curves from grouped data.

Suggested Citation

  • Nicholas Rohde, 2010. "Lorenz Curve Interpolation and the Gini Coefficient," Journal of Income Distribution, Journal of Income Distribution, vol. 19(2), pages 111-123, June.
  • Handle: RePEc:jid:journl:y:2010:v:19:i:2:p:111-123

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    More about this item


    Gini coefficient; interpolation; Lorenz curve; spline;

    JEL classification:

    • C10 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - General
    • D63 - Microeconomics - - Welfare Economics - - - Equity, Justice, Inequality, and Other Normative Criteria and Measurement
    • I32 - Health, Education, and Welfare - - Welfare, Well-Being, and Poverty - - - Measurement and Analysis of Poverty


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