More Opportunities than Wealth: A Network of Power and Frustration
Benoit Mahault, Avadh Saxena, Cristiano Nisoli

TL;DR
This paper presents an agent-based model exploring how power, frustration, and network constraints influence wealth distribution, revealing polarization, class formation, and cyclical social dynamics.
Contribution
It introduces a novel network-based framework incorporating power and frustration dynamics to analyze wealth inequality and social class emergence.
Findings
Complete libertarian settings lead to wealth polarization.
Network constraints modify wealth distribution outcomes.
Power and frustration ratios induce different social regimes.
Abstract
We introduce a minimal agent-based model to qualitatively conceptualize the allocation of limited wealth among more abundant opportunities. We study the interplay of power, satisfaction and frustration in distribution, concentration, and inequality of wealth. Our framework allows us to compare subjective measures of frustration and satisfaction to collective measures of fairness in wealth distribution, such as the Lorenz curve and the Gini index. We find that a completely libertarian, law-of-the-jungle setting, where every agent can acquire wealth from, or lose wealth to, anybody else invariably leads to a complete polarization of the distribution of wealth vs. opportunity. The picture is however dramatically modified when hard constraints are imposed over agents, and they are limited to share wealth with neighbors on a network. We then propose an out of equilibrium dynamics {\it of}…
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Taxonomy
TopicsComplex Systems and Time Series Analysis · Opinion Dynamics and Social Influence · Evolutionary Game Theory and Cooperation
