Pareto Models for Top Incomes

Arthur Charpentier () and Emmanuel Flachaire
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Arthur Charpentier: CREM - Centre de recherche en économie et management - UNICAEN - Université de Caen Normandie - NU - Normandie Université - UR - Université de Rennes - CNRS - Centre National de la Recherche Scientifique, DMS - Département de Mathématiques et de statistique [UdeM- Montréal] - UQAM - Université du Québec à Montréal = University of Québec in Montréal

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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 an attractive property, that can be easily linked to economic theory. In this paper, we first show that modelling top incomes with Pareto Type I distribution can lead to severe over-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 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.

Keywords: Pareto distribution; top incomes; inequality measures (search for similar items in EconPapers)
Date: 2019-05-31
New Economics Papers: this item is included in nep-hme
Note: View the original document on HAL open archive server: https://hal.science/hal-02145024
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Citations: View citations in EconPapers (11)

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Working Paper: Pareto Models for Top Incomes (2019)
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