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A Function for Size Distribution of Incomes

In: Modeling Income Distributions and Lorenz Curves

Author

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  • S. K. Singh
  • G. S. Maddala

Abstract

The paper derives a function that describes the size distribution of incomes. The two functions most often used are the Pareto and the lognormal. The Pareto function fits the data fairly well towards the higher levels but the fit is poor towards the low income levels. The lognormal fits the lower income levels better but its fit towards the upper end is far from satisfactory. There have been other distributions suggested by Champernowne, Rutherford, and others, but even these do not result in any considerable improvement. The present paper derives a distribution that is a generalization of the Pareto distribution and the Weibull distribution used in analyses of equipment failures. The distribution fits actual data remarkably well compared with the Pareto and the lognormal.

Suggested Citation

  • S. K. Singh & G. S. Maddala, 2008. "A Function for Size Distribution of Incomes," Economic Studies in Inequality, Social Exclusion, and Well-Being, in: Duangkamon Chotikapanich (ed.), Modeling Income Distributions and Lorenz Curves, chapter 2, pages 27-35, Springer.
    • Handle: RePEc:spr:esichp:978-0-387-72796-7_2
    DOI: 10.1007/978-0-387-72796-7_2
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    Citations

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    Cited by:

    1. Rafael González-Val & Arturo Ramos & Fernando Sanz-Gracia & María Vera-Cabello, 2015. "Size distributions for all cities: Which one is best?," Papers in Regional Science, Wiley Blackwell, vol. 94(1), pages 177-196, March.
    2. Vanesa Jorda & José María Sarabia & Markus Jäntti, 2021. "Inequality measurement with grouped data: Parametric and non‐parametric methods," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 184(3), pages 964-984, July.
    3. Vanesa Jorda & Jos Mar a Sarabia & Markus J ntti, 2020. "Estimation of Income Inequality from Grouped Data," LIS Working papers 804, LIS Cross-National Data Center in Luxembourg.
    4. Tutz, Gerhard & Berger, Moritz, 2020. "The effect of explanatory variables on income: A tool that allows a closer look at the differences in income," Econometrics and Statistics, Elsevier, vol. 16(C), pages 28-41.
    5. Zhang, Yue & Wang, Wenxiong & Feng, Yanfei, 2022. "Impact of different models of rural land consolidation on rural household poverty vulnerability," Land Use Policy, Elsevier, vol. 114(C).
    6. Faustino Prieto & Jos'e Mar'ia Sarabia & Enrique Calder'in-Ojeda, 2020. "The risk of death in newborn businesses during the first years in market," Papers 2011.11776, arXiv.org.

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