Explicit decay rate for the Gini index in the repeated averaging model

TL;DR

This paper analyzes the long-term behavior of wealth distribution in a repeated averaging model, proving that the Gini index converges to zero at an explicit rate as the number of agents grows large, using a PDE approach.

Contribution

It provides the first explicit decay rate for the Gini index in the repeated averaging wealth exchange model, linking stochastic dynamics to a PDE and analyzing its convergence.

Findings

Gini index converges to zero over time

Explicit decay rate for the Gini index derived

Connection established between agent-based model and PDE

Abstract

We investigate the repeated averaging model for money exchanges: two agents picked uniformly at random share half of their wealth to each other. It is intuitively convincing that a Dirac distribution of wealth (centered at the initial average wealth) will be the long time equilibrium for this dynamics. In other words, the Gini index should converge to zero. To better understand this dynamics, we investigate its limit as the number of agents goes to infinity by proving the so-called propagation of chaos, which links the stochastic agent-based dynamics to a (limiting) nonlinear partial differential equation (PDE). This deterministic description has a flavor of the classical Boltzmann equation arising from statistical mechanics of dilute gases. We prove its convergence toward its Dirac equilibrium distribution by showing that the associated Gini index of the wealth distribution converges to zero with an explicit rate.