Scaling in local to global condensation of wealth on sparse networks

TL;DR

This paper investigates how network structure influences wealth inequality dynamics, revealing phases of growth and suppression driven by local interactions, redistribution, and network connectivity, using empirical, theoretical, and modeling approaches.

Contribution

It introduces a model combining Yard-Sale exchanges with redistribution on sparse networks, analyzing the phases of wealth inequality growth and suppression with new scaling insights.

Findings

Wealth inequality ceases to grow when local interactions dominate.

Redistribution suppresses extreme wealth concentration.

Network sparsity leads to distinct phases in wealth inequality dynamics.

Abstract

The prevalence of wealth inequality propels us to characterize its origin and progression, via empirical and theoretical studies. The Yard-Sale(YS) model, in which a portion of the smaller wealth is transferred between two individuals, culminates in the concentration of almost all wealth to a single individual, while distributing rest of the wealth with a power-law of exponent one. By incorporating redistribution to the model, in which the transferred wealth is proportional to the sender's wealth, we show that such extreme inequality is suppressed if the frequency ratio of redistribution to the YS-type exchange exceeds the inverse of the population size. Studying our model on a sparsely-connected population, we find that the wealth inequality ceases to grow for a period, when local rich nodes can no longer acquire wealth from their broke nearest neighbors. Subsequently, inequality resumes growth due to the redistribution effect by allowing locally amassed wealth to move and coalesce. Analyzing the Langevin equations and the coalescing random walk on complex networks, we elucidate the scaling behaviors of wealth inequality in those multiple phases. These findings reveal the influence of network structure on wealth distribution, offering a novel perspective on wealth inequality.