A generalized statistical model for the size distribution of wealth

TL;DR

This paper extends a k-generalized statistical mechanics model to accurately describe wealth distribution, providing closed-form functions and demonstrating superior fit to U.S. wealth data from 1984 to 2009.

Contribution

The paper introduces a generalized model for wealth distribution based on statistical mechanics, with closed-form solutions and improved data fitting over existing models.

Findings

Excellent agreement with U.S. wealth data from 1984 to 2009

Model outperforms previous wealth distribution models

Provides probabilistic functions and inequality measures in closed form

Abstract

In a recent paper in this journal [J. Stat. Mech. (2009) P02037] we proposed a new, physically motivated, distribution function for modeling individual incomes having its roots in the framework of the k-generalized statistical mechanics. The performance of the k-generalized distribution was checked against real data on personal income for the United States in 2003. In this paper we extend our previous model so as to be able to account for the distribution of wealth. Probabilistic functions and inequality measures of this generalized model for wealth distribution are obtained in closed form. In order to check the validity of the proposed model, we analyze the U.S. household wealth distributions from 1984 to 2009 and conclude an excellent agreement with the data that is superior to any other model already known in the literature.