Distribution of the wealth of the richest persons in the world

Abstract

The aim of this paper is to examine the probability distribution of wealth of the richest persons in the world based on estimates from the CEOWORLD magazine's rich list for March 2019. Since one can safely assume that there are a tiny number of people out of the whole world's population in this list, we basically deal with the very right tail of the wealth distribution, which should according to the Pickands-Balkema-de Haan theorem follow a generalized Pareto distribution. We discuss in this paper not only different estimates of this distribution with an emphasis on the shape parameter per se but also their behavior throughout bootstrap samples. Among the main findings is the observation based on the maximum to sum plot and parametric estimates that there is high probability of infinite variance. This could have a serious impact on estimates of inequality measures. The whole distribution follows nearly a Pareto distribution, whereas the very right tail is closer to an exponential. The bootstrap technique confirms that maximum likelihood estimates are almost normally distributed, but they overestimate variance. Estimates via the method of L-moments diverge from the normal distribution. The correlation of the parameter estimates is moderately negative, which is demonstrated in a simultaneous confidence region.