
TL;DR
This paper models rigged economies using a toy model to analyze how economic complexity and intervention influence system stability, revealing phases of equilibrium, defusion of cartels, and potential systemic risks from excessive complexity.
Contribution
It introduces a toy model capturing key elements of rigged economies, analyzing phase transitions and stability through Nash equilibria and agent-based simulations.
Findings
Increased intervention shifts economic dynamics from minority to majority games.
Higher economic complexity can spontaneously defuse cartels and consensus.
Excessive complexity leads to large fluctuations threatening system viability.
Abstract
Modern economies evolved from simpler human exchanges into very convoluted systems. Today, a multitude of aspects can be regulated, tampered with, or left to chance; these are economic {\em degrees of freedom} which together shape the flow of wealth. Economic actors can exploit them, at a cost, and bend that flow in their favor. If intervention becomes widespread, microeconomic strategies of different actors can collide or resonate, building into macroeconomic effects. How viable is a `rigged' economy, and how is this viability affected by growing economic complexity and wealth? Here we capture essential elements of `rigged' economies with a toy model. Nash equilibria of payoff matrices in simple cases show how increased intervention turns economic degrees of freedom from minority into majority games through a dynamical phase. These stages are reproduced by agent-based simulations of…
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