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Pareto models for top incomes and wealth

Author

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  • Arthur Charpentier

    (UQAM - Université du Québec à Montréal = University of Québec in Montréal)

  • Emmanuel Flachaire

    (AMSE - Aix-Marseille Sciences Economiques - EHESS - École des hautes études en sciences sociales - AMU - Aix Marseille Université - ECM - École Centrale de Marseille - CNRS - Centre National de la Recherche Scientifique)

Abstract

Top incomes are often related to Pareto distribution. To date, economists have mostly used Pareto Type I distribution to model the upper tail of income and wealth distribution. It is a parametric distribution, with interesting properties, that can be easily linked to economic theory. In this paper, we first show that modeling top incomes with Pareto Type I distribution can lead to biased estimation of inequality, even with millions of observations. Then, we show that the Generalized Pareto distribution and, even more, the Extended Pareto distribution, are much less sensitive to the choice of the threshold. Thus, they can provide more reliable results. We discuss different types of bias that could be encountered in empirical studies and, we provide some guidance for practice. To illustrate, two applications are investigated, on the distribution of income in South Africa in 2012 and on the distribution of wealth in the United States in 2013.

Suggested Citation

  • Arthur Charpentier & Emmanuel Flachaire, 2022. "Pareto models for top incomes and wealth," Post-Print hal-03649428, HAL.
    • Handle: RePEc:hal:journl:hal-03649428
    DOI: 10.1007/s10888-021-09514-6
    Note: View the original document on HAL open archive server: https://amu.hal.science/hal-03649428
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    Cited by:

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    2. Haiyuan Wan & Yangcheng Yu, 2023. "Correction of China's income inequality for missing top incomes," Review of Development Economics, Wiley Blackwell, vol. 27(3), pages 1769-1791, August.
    3. Wildauer, Rafael & Heck, Ines & Kapeller, Jakob, 2023. "Was Pareto right? Is the distribution of wealth thick-tailed?," Greenwich Papers in Political Economy 38597, University of Greenwich, Greenwich Political Economy Research Centre.
    4. Pérez-Oviedo, Wilson & Cajas-Guijarro, John & Pinzón-Venegas, Kathia, 2024. "Corruption, unemployment, and clientelism: A Political Economy approach," Economic Modelling, Elsevier, vol. 135(C).
    5. Arturo Ramos & Till Massing & Atushi Ishikawa & Shouji Fujimoto & Takayuki Mizuno, 2023. "Composite distributions in the social sciences: A comparative empirical study of firms' sales distribution for France, Germany, Italy, Japan, South Korea, and Spain," Papers 2301.09438, arXiv.org.
    6. Mathias Silva, 2023. "Parametric models of income distributions integrating misreporting and non-response mechanisms," AMSE Working Papers 2311, Aix-Marseille School of Economics, France.
    7. John C. Stevenson, 2024. "Death, Taxes, and Inequality. Can a Minimal Model Explain Real Economic Inequality?," Papers 2406.13789, arXiv.org, revised Nov 2024.
    8. Frederico Caeiro & Ayana Mateus, 2023. "A New Class of Generalized Probability-Weighted Moment Estimators for the Pareto Distribution," Mathematics, MDPI, vol. 11(5), pages 1-17, February.
    9. Frank Cowell & Emmanuel Flachaire, 2021. "Inequality Measurement: Methods and Data," Post-Print hal-03589066, HAL.

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    Keywords

    Pareto distribution; Top incomes; Inequality measures;
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