EPJ B Topical review - Twenty-five years of random asset exchange modeling

Over the last twenty-five years, there has emerged within the subfield of econophysics a sizeable and important literature (hereinafter the “random asset exchange” literature) concerned with the application of stochastic processes to model wealth and income distributions. In a new Topical Review published in EPJ B, written by Max Greenberg (University of Massachusetts Amherst, USA) and H. Oliver Gao (Cornell University, USA), the random asset exchange literature as a whole is comprehensively exposited for the first time.

This review covers the core taxonomy of random asset exchange models — defining terms such as “kinetic wealth exchange,” “theft and fraud,” and “yard sale” — as well as notable adjustments made to these foundational frameworks to capture the effects of specific system dynamics such as networks, strategic behavior, redistribution, and class division. The achievements of the literature, including the establishment of the apparent universality of exponential distributions of wealth and income with inverse power law (Pareto) tails, are enumerated and discussed, as are its drawbacks and limitations. Finally, the case is made that the future of random asset exchange modeling should include the incorporation of explicit economic processes for the sake of gaining more explanatory power. As the significance and versatility of the random asset exchange framework becomes increasingly recognized across disciplines, from economics to computer science and civil and environmental engineering, this review serves as a timely introduction to researchers from all backgrounds interested in the econophysical approach to modeling economic inequality.

Greenberg M. and Gao H. O., Twenty-five years of random asset exchange modeling
Eur. Phys. J. B 97:69 (2024). https://doi.org/10.1140/epjb/s10051-024-00695-3

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