Social Comparisons in Games
Stanford Graduate School of Business
Northwestern University - Kellogg School of Management
Michael M. Ting
Columbia University - Department of Political Science
We develop a model of adaptive learning in normal form games with social comparisons. Actors in the model adjust their behavior by aspiration-based adaptation: they are more likely to choose actions that recently yielded satisfactory payoffs and are less likely to repeat those that resulted in unsatisfactory payoffs.
Satisfaction is evaluated relative to an aspiration level that reflects previous payoffs. Aspirations, however, may depend not only on individual experiences but also on other players' payoffs. Thus, the model captures the effect of an important kind of social comparison, provided by exogenous reference groups. We show that under a variety of simple emulation patterns the presence of social comparisons significantly constrains the set of stable outcomes. In particular, if reference groups are sufficiently dense then in every stable outcome all players receive identical payoffs.
Number of Pages in PDF File: 20
Keywords: social comparison, adaptation, satisfying
Date posted: January 22, 2008