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Isograph and LaSiPiKa Distribution: The Comparative Morphology of Income Inequalities and Intelligible Parameters of 53 LIS Countries 1967-2020

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  • Louis Chauvel

Abstract

The isograph methodology is developed here with associated distributions, indicators of inequality, additional results, and is implemented on 53 LIS countries (with an annex covering 655 LIS country-year samples). The gb2 and other classical distributions (FC, Dagum, Singh-Maddala) are presented along with new proposals, including gb2 subfamilies with p=1/q and p=q, the LaSi distribution to fit the quasi-linear isograph cases of level lambda and slope sigma, and finally the LaSiPiKa that completes LaSi with a polarization term of intensity pi and location kappa. This latest proposal fits better the cases of distributions with sharp flexible profiles in the isograph and provides independent intelligible parameters. The analysis is systematized to 655 samples to show the invariant patterns and significant changes. More complicated distributional shapes can be fitted with hand-tailored additional terms. Working with isograph and LaSiPiKa distributions is a way to diversify and deepen inequality analyses with a larger conceptualization of “morphology of inequality,” not reduced to a Gini (or the like) measure.

Suggested Citation

  • Louis Chauvel, 2023. "Isograph and LaSiPiKa Distribution: The Comparative Morphology of Income Inequalities and Intelligible Parameters of 53 LIS Countries 1967-2020," LIS Working papers 852, LIS Cross-National Data Center in Luxembourg.
  • Handle: RePEc:lis:liswps:852
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    References listed on IDEAS

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    1. 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.
    2. Cowell, F.A., 2000. "Measurement of inequality," Handbook of Income Distribution, in: A.B. Atkinson & F. Bourguignon (ed.), Handbook of Income Distribution, edition 1, volume 1, chapter 2, pages 87-166, Elsevier.
    3. McDonald, James B. & Xu, Yexiao J., 1995. "A generalization of the beta distribution with applications," Journal of Econometrics, Elsevier, vol. 69(2), pages 427-428, October.
    4. Buhong Zheng, 2018. "Almost Lorenz dominance," Social Choice and Welfare, Springer;The Society for Social Choice and Welfare, vol. 51(1), pages 51-63, June.
    5. Bourguignon, Francois, 1979. "Decomposable Income Inequality Measures," Econometrica, Econometric Society, vol. 47(4), pages 901-920, July.
    6. Stanislaw Maciej Kot & Piotr Paradowski, 2022. "The Atlas of Inequality Aversion: Theory and Empirical Evidence from the Luxembourg Income Study Database," LIS Working papers 826, LIS Cross-National Data Center in Luxembourg.
    7. Louis Chauvel & Anne Hartung & Eyal Bar-Haim & Philippe Van Kerm, 2019. "Income and Wealth Above the Median: New Measurements and Results for Europe and the United States," Research on Economic Inequality, in: What Drives Inequality?, volume 27, pages 89-104, Emerald Group Publishing Limited.
    8. Stephen P. Jenkins, 2009. "Distributionally‐Sensitive Inequality Indices And The Gb2 Income Distribution," Review of Income and Wealth, International Association for Research in Income and Wealth, vol. 55(2), pages 392-398, June.
    9. Thitithep Sitthiyot & Kanyarat Holasut, 2020. "A simple method for measuring inequality," Palgrave Communications, Palgrave Macmillan, vol. 6(1), pages 1-9, December.
    10. Stanislaw Maciej Kot & Piotr R. Paradowski, 2022. "The atlas of inequality aversion: theory and empirical evidence on 55 countries from the Luxembourg Income Study database," Equilibrium. Quarterly Journal of Economics and Economic Policy, Institute of Economic Research, vol. 17(2), pages 261-316, June.
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    More about this item

    JEL classification:

    • D31 - Microeconomics - - Distribution - - - Personal Income and Wealth Distribution
    • C16 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Econometric and Statistical Methods; Specific Distributions
    • C46 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Specific Distributions

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