On the Statistical Physics of Wealth Distribution

Fuente: arXiv
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Main Authors: Wagner, Joel, Cheong, Siew Ann, Priesemann, Viola
Format: Preprint
Published: 2025
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author Wagner, Joel
Cheong, Siew Ann
Priesemann, Viola
author_facet Wagner, Joel
Cheong, Siew Ann
Priesemann, Viola
contents Asset exchange models (AEMs) provide a physics-inspired framework for studying wealth formation. These models capture wealth distribution dynamics via pairwise money exchanges, yielding steady-state distributions from exponential to heavy-tailed power laws. However, empirical validation remains limited due to scarce real-world transaction data. Here, we bridge this gap by analyzing spectral properties of Markov transition matrices from both AEMs and Ethereum blockchain data, enabling quantitative comparison of model and empirical exchange dynamics. We assess thermodynamic equilibrium in exchange processes - specifically, detailed balance - and derive steady-state wealth distributions from transition matrices. We find that equilibrium systems' spectra contain only real eigenvalues and link Ethereum price changes to spectral shifts. We also investigate external factors (e.g., taxes), showing that advantages for richer individuals make wealth evolution path-dependent on initial distributions. Our work establishes a quantitative framework for validating AEMs with real data, advancing economic modeling and understanding of wealth formation.
format Preprint
id arxiv_https___arxiv_org_abs_2509_00573
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle On the Statistical Physics of Wealth Distribution
Wagner, Joel
Cheong, Siew Ann
Priesemann, Viola
Physics and Society
Asset exchange models (AEMs) provide a physics-inspired framework for studying wealth formation. These models capture wealth distribution dynamics via pairwise money exchanges, yielding steady-state distributions from exponential to heavy-tailed power laws. However, empirical validation remains limited due to scarce real-world transaction data. Here, we bridge this gap by analyzing spectral properties of Markov transition matrices from both AEMs and Ethereum blockchain data, enabling quantitative comparison of model and empirical exchange dynamics. We assess thermodynamic equilibrium in exchange processes - specifically, detailed balance - and derive steady-state wealth distributions from transition matrices. We find that equilibrium systems' spectra contain only real eigenvalues and link Ethereum price changes to spectral shifts. We also investigate external factors (e.g., taxes), showing that advantages for richer individuals make wealth evolution path-dependent on initial distributions. Our work establishes a quantitative framework for validating AEMs with real data, advancing economic modeling and understanding of wealth formation.
title On the Statistical Physics of Wealth Distribution
topic Physics and Society
url https://arxiv.org/abs/2509.00573