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Pareto models for top incomes and wealth

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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.

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Acknowledgements

Arthur Charpentier received financial support from the Natural Sciences and Engineering Research Council of Canada (NSERC-2019-07077) and the AXA Research Fund, and Emmanuel Flachaire from the the French National Research Agency (ANR-17-EURE-0020, ANR-17-CE41-0007-02, ANR-19-FRAL-0006)

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  1. Université du Québec à Montréal (UQAM), 201, avenue du Président-Kennedy, Montréal, Québec, H2X 3Y7, Canada

    Arthur Charpentier

  2. Aix-Marseille Université, AMSE, CNRS and EHESS, 5 bd Maurice Bourdet, 13001, Marseille, France

    Emmanuel Flachaire

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  1. Arthur Charpentier
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Charpentier, A., Flachaire, E. Pareto models for top incomes and wealth. J Econ Inequal 20, 1–25 (2022). https://doi.org/10.1007/s10888-021-09514-6

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