What the Boltzmann Money Game Teaches Us about Statistical Mechanics (and Maybe Economics)

Motivated by discussions with John F. Stanton, this Viewpoint explains why a large class of fair or reversible "money games", i.e., stochastic models of wealth redistribution among agents, lead to steady states described by canonical and microcanonical distributions. The games considered include, for example, games in which more than two agents can be simultaneously involved in money transfers (similarly to many-body collisions in chemical kinetics) and in which amounts transferred between agents are random. At the same time, money games that break time reversal symmetry can also lead to canonical/microcanonical distributions, as illustrated by an explicit example.

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Publication Details

Journal
The Journal of Physical Chemistry Letters
Published
2025-09-25
DOI
https://doi.org/10.1021/acs.jpclett.5c02426
Primary Topic
Complex Systems and Time Series Analysis
Type
article
Field-Weighted Citation Impact
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article

What the Boltzmann Money Game Teaches Us about Statistical Mechanics (and Maybe Economics)

Dmitrii E. Makarov
The Journal of Physical Chemistry Letters
Complex Systems and Time Series Analysis
article

What the Boltzmann Money Game Teaches Us about Statistical Mechanics (and Maybe Economics)

Dmitrii E. Makarov
article en

Abstract

Motivated by discussions with John F. Stanton, this Viewpoint explains why a large class of fair or reversible "money games", i.e., stochastic models of wealth redistribution among agents, lead to steady states described by canonical and microcanonical distributions. The games considered include, for example, games in which more than two agents can be simultaneously involved in money transfers (similarly to many-body collisions in chemical kinetics) and in which amounts transferred between agents are random. At the same time, money games that break time reversal symmetry can also lead to canonical/microcanonical distributions, as illustrated by an explicit example.

The Journal of Physical Chemistry LettersVol. 16(38)
The University of Texas at Austin (US)
Openalex Percentile: Top 65%
Complex Systems and Time Series Analysis
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