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A New Inequality Measure that is Sensitive to Extreme Values and Asymmetries

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  • McAleer, M.J.
  • Ryu, H.K.
  • Slottje, D.J.

Abstract

There is a vast literature on the selection of an appropriate index of income inequality and on what desirable properties such a measure (or index) should contain. The Gini index is, of course, the most popular. There is a concurrent literature on the use of hypothetical statistical distributions to approximate and describe an observed distribution of incomes. Pareto and others observed early on that incomes tend to be heavily right-tailed in their distribution. These asymmetries led to approximating the observed income distributions with extreme value hypothetical statistical distributions, such as the Pareto distribution. But these income distribution functions (IDFs) continue to be described with a single index (such as the Gini) that poorly detect the extreme values present in the underlying empirical IDF. This paper introduces a new inequality measure to supplement, but not to replace, the Gini that measures more accurately the inherent asymmetries and extreme values that are present in observed income distributions. The new measure is based on a third-order term of a Legendre polynomial from the logarithm of a share function (or Lorenz curve). We advocate using the two measures together to provide a better description of inequality inherent in empirical income distributions with extreme values.

Suggested Citation

  • McAleer, M.J. & Ryu, H.K. & Slottje, D.J., 2017. "A New Inequality Measure that is Sensitive to Extreme Values and Asymmetries," Econometric Institute Research Papers EI2017-28, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
  • Handle: RePEc:ems:eureir:102548
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    1. Ryu, Hang K. & Slottje, Daniel J., 1996. "Two flexible functional form approaches for approximating the Lorenz curve," Journal of Econometrics, Elsevier, vol. 72(1-2), pages 251-274.
    2. Basmann, R. L. & Hayes, K. J. & Slottje, D. J., 1991. "The Lorenz curve and the mobility function," Economics Letters, Elsevier, vol. 36(1), pages 105-111, May.
    3. Thomas Piketty, 1995. "Social Mobility and Redistributive Politics," The Quarterly Journal of Economics, Oxford University Press, vol. 110(3), pages 551-584.
    4. Basmann, R. L. & Slottje, D. J., 1987. "A new index of income inequality : The B measure," Economics Letters, Elsevier, vol. 24(4), pages 385-389.
    5. James B. McDonald, 2008. "Some Generalized Functions for the Size Distribution of Income," Economic Studies in Inequality, Social Exclusion, and Well-Being, in: Duangkamon Chotikapanich (ed.), Modeling Income Distributions and Lorenz Curves, chapter 3, pages 37-55, Springer.
    6. Cowell, Frank & Flachaire, Emmanuel, 2002. "Sensitivity of inequality measures to extreme values," LSE Research Online Documents on Economics 2213, London School of Economics and Political Science, LSE Library.
    7. Cowell, Frank A. & Flachaire, Emmanuel, 2007. "Income distribution and inequality measurement: The problem of extreme values," Journal of Econometrics, Elsevier, vol. 141(2), pages 1044-1072, December.
    8. Zellner, Arnold & Highfield, Richard A., 1988. "Calculation of maximum entropy distributions and approximation of marginalposterior distributions," Journal of Econometrics, Elsevier, vol. 37(2), pages 195-209, February.
    9. Ryu, Hang K., 1993. "Maximum entropy estimation of density and regression functions," Journal of Econometrics, Elsevier, vol. 56(3), pages 397-440, April.
    10. Ryu, Hang Keun, 2013. "A bottom poor sensitive Gini coefficient and maximum entropy estimation of income distributions," Economics Letters, Elsevier, vol. 118(2), pages 370-374.
    11. James B. Mcdonald & Jeff Sorensen & Patrick A. Turley, 2013. "Skewness And Kurtosis Properties Of Income Distribution Models," Review of Income and Wealth, International Association for Research in Income and Wealth, vol. 59(2), pages 360-374, June.
    12. Maasoumi, Esfandiar, 1986. "The Measurement and Decomposition of Multi-dimensional Inequality," Econometrica, Econometric Society, vol. 54(4), pages 991-997, July.
    13. Slottje, D J, 1987. "Relative Price Changes and Inequality in the Size Distribution of Various Components of Income: A Multidemensional Approach," Journal of Business & Economic Statistics, American Statistical Association, vol. 5(1), pages 19-26, January.
    14. Maasoumi, Esfandiar, 1989. "Continuously distributed attributes and measures of multivariate inequality," Journal of Econometrics, Elsevier, vol. 42(1), pages 131-144, September.
    15. Ryu, Hang K. & Slottje, Daniel J., 2017. "Maximum entropy estimation of income distributions from Basmann’s weighted geometric mean measure," Journal of Econometrics, Elsevier, vol. 199(2), pages 221-231.
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    4. Sungik Kang & Ja-Hoon Koo, 2023. "Exploring Social Capital Level in Regions with Large and Increasing Wealth Inequality: Lesson from Seoul, South Korea," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 168(1), pages 165-183, August.

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    More about this item

    Keywords

    Inequality Index; Extreme value distributions; Maximum entropy method; Orthonormal basis; Legendre polynomials;
    All these keywords.

    JEL classification:

    • D31 - Microeconomics - - Distribution - - - Personal Income and Wealth Distribution
    • D63 - Microeconomics - - Welfare Economics - - - Equity, Justice, Inequality, and Other Normative Criteria and Measurement

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