Monotone Methods in Reputations: Behavioral Predictions and Reputation Sustainability

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This award funds research in economic theory. The PI wants to advance the use of game theory to understand how strategic decision makers build and maintain reputations. The research focuses on understanding how a long lived individual, firm, or organization will make decisions when it faces a series of short lived opponents who have less information about relevant facts. The project will focus on developing specific predictions that can be tested with data. The research seeks to answer specific questions. First, when can decision makers sustain reputations? Second, how will decision makers behave when reputation building is costly and monitoring is noisy? Third, how can we best test the predictions of reputation models given limited availability of data on long-term interactions? The principal investigator will answer these questions by using monotone methods. The first project introduces interdependent values to the study of reputations. This expands the applicability of reputation results to a richer set of informational environments. The project will give robust predictions on player’s behaviors in addition to their payoffs. The second project will examine whether and how interdependent values can contribute to the sustainability of reputations. The goal is to relate long run outcomes (such as reputation sustainability) to primitives, including the supermodularity or submodularity of stage-game payoffs, and players’ beliefs about the payoff relevant state. The third project develops an alternative framework to study reputations. This framework may help us better understand players’ reputation building behaviors. It also can yield sharp predictions on a long-run player’s action frequencies that apply not only to all of his equilibrium strategies, but also to all equilibrium best replies. This means that the prediction can be tested by observing a realized path of equilibrium play.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.