Wealth Dynamics on Complex Networks

TL;DR

This paper investigates how the structure of transaction networks influences wealth distribution, revealing that network topology can produce the mixed distributions observed in real economies.

Contribution

It demonstrates that complex network topologies with heterogeneous link densities can generate wealth distributions similar to empirical data, extending previous models.

Findings

Fully connected networks produce power-law wealth distributions.

Disconnected networks yield log-normal wealth distributions.

Heterogeneous network topologies explain mixed empirical wealth distributions.

Abstract

We study a model of wealth dynamics [Bouchaud and M\'ezard 2000, \emph{Physica A} \textbf{282}, 536] which mimics transactions among economic agents. The outcomes of the model are shown to depend strongly on the topological properties of the underlying transaction network. The extreme cases of a fully connected and a fully disconnected network yield power-law and log-normal forms of the wealth distribution respectively. We perform numerical simulations in order to test the model on more complex network topologies. We show that the mixed form of most empirical distributions (displaying a non-smooth transition from a log-normal to a power-law form) can be traced back to a heterogeneous topology with varying link density, which on the other hand is a recently observed property of real networks.