$\kappa$-generalized models of income and wealth distributions: A survey

TL;DR

This survey reviews the $ppa$-generalized distribution models for income and wealth, highlighting their analytical properties, relationships with other distributions, and empirical success in fitting real-world data.

Contribution

It provides a comprehensive overview of $ppa$-generalized models, including their extensions and empirical applications in income and wealth distribution analysis.

Findings

Models align well with observed income and wealth data

The $ppa$-generalized distribution captures key features of income and wealth distributions

Extensions improve modeling of wealth data

Abstract

The paper provides a survey of results related to the "$\kappa$-generalized distribution", a statistical model for the size distribution of income and wealth. Topics include, among others, discussion of basic analytical properties, interrelations with other statistical distributions as well as aspects that are of special interest in the income distribution field, such as the Gini index and the Lorenz curve. An extension of the basic model that is most able to accommodate the special features of wealth data is also reviewed. The survey of empirical applications given in this paper shows the $\kappa$-generalized models of income and wealth to be in excellent agreement with the observed data in many cases.