Inequality, Aspirations, and Social Comparisons

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We develop a model of adaptive learning with social comparisons. Actors are more likely to choose actions that recently yielded satisfactory payoffs; satisfaction is evaluated relative to an aspiration level that reflects previous payoffs and possibly other players’ payoffs. This captures the phenomenon of social comparison viareference groups. We show that if agents compare themselves to those who are receiving higher payoffs then in stable outcomes all payoffs must be equal. If, however, agents’ aspirations are driven by less ambitious social comparisons then very unequal distributions can be stable. We apply our general results to collective action problems in socio-political hierarchies and derive conditions for stable exploitation. Finally, we develop a computational model, which shows that increases in payoff inequality make outcomes less stable.