Distribution of the wealth of the richest persons in the world
- DOI
- 10.2991/amse-19.2019.17How to use a DOI?
- Keywords
- CEOWORLD magazine’s Rich List, Pickands-Balkema-de Haan theorem, generalized Pareto distribution, parameter estimates, bootstrap
- 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.
- Copyright
- © 2019, the Authors. Published by Atlantis Press.
- Open Access
- This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).
Cite this article
TY - CONF AU - Adam Čabla AU - Filip Habarta PY - 2019/10 DA - 2019/10 TI - Distribution of the wealth of the richest persons in the world BT - Proceedings of the 22nd International Scientific Conference on Applications of Mathematics and Statistics in Economics (AMSE 2019) PB - Atlantis Press SP - 158 EP - 169 SN - 2589-6644 UR - https://doi.org/10.2991/amse-19.2019.17 DO - 10.2991/amse-19.2019.17 ID - Čabla2019/10 ER -