This dissertation consists of three essays on reputation and repeated games. Reputation models typically assume players have full memory of past events, yet in many applications this assumption does not hold. In the first chapter, I explore two different relaxations of the assumption that history is perfectly observed in the context of Ely and Välimäki's (2003) mechanic game, where reputation (with full history observation) is clearly bad for all players. First I consider "limited history," where short-run players see only the most recent T periods. For large T, the full history equilibrium behavior always holds due to an "echo" effect (for high discount factors); for small T, the repeated static equilibrium exists. Second I consider "fading history," where short-run players randomly sample past periods with probabilities that "fade" toward zero for older periods. When fading is faster than a fairly lax threshold, the long-run player always acts myopically, a result that holds more generally for reputation games where the long-run player has a strictly dominant stage game action. This finding suggests that reputational incentives may be too weak to affect long-run player behavior in some realistic word-of-mouth environments. The second chapter develops general theoretical tools to study incomplete information games where players observe only finitely many recent periods. I derive a recursive characterization of the set of equilibrium payoffs, which allows analysis of both stationary and (previously unexplored) non-stationary equilibria. I also introduce "quasi-Markov perfection," an equilibrium refinement which is a necessary condition of any equilibrium that is "non-fragile" (purifiable), i.e., robust to small, additively separable and independent perturbations of payoffs. These tools are applied to two examples. The first is a product choice game with 1-period memory of the firm's actions, obtaining a complete characterization of the exact minimum and maximum purifiable equilibrium payoffs for almost all discount factors and prior beliefs on an "honest" Stackelberg commitment type, which shows that non-stationary equilibria expand the equilibrium set. The second is the same game with long memory: in all stationary and purifiable equilibria, the long-run player obtains exactly the Stackelberg payoff so long as the memory is longer than a threshold dependent on the prior. These results show that the presence of the honest type (even for arbitrarily small prior beliefs) qualitatively changes the equilibrium set for any fixed discount factor above a threshold independent of the prior, thereby not requiring extreme patience. The third chapter studies the question of why drug trafficking organizations inflict violence on each other, and why conflict breaks out under some government crackdowns and not others, in a repeated games context. Violence between Mexican drug cartels soared following the government's anti-cartel offensive starting in 2006, but not under previous crackdowns. I construct a theoretical explanation for these observations and previous empirical research. I develop a duopoly model where the firms have the capacity to make costly attacks on each other. The firms use the threat of violence to incentivize inter-cartel cooperation, and under imperfect monitoring, violence occurs on the equilibrium path of a high payoff equilibrium. When a "corrupt" government uses the threat of law enforcement as a punishment for uncooperative behavior, violence is not needed as frequently to achieve high payoffs. When government cracks down indiscriminately, the firms may return to frequent violence as a way of ensuring cooperation and high payoffs, even if the crackdown makes drug trafficking otherwise less profitable. / text
| Identifer | oai:union.ndltd.org:UTEXAS/oai:repositories.lib.utexas.edu:2152/30940 |
| Date | 04 September 2015 |
| Creators | Sperisen, Benjamin Leonard |
| Contributors | Wiseman, Thomas E., 1974- |
| Source Sets | University of Texas |
| Language | English |
| Detected Language | English |
| Type | Thesis |
| Format | application/pdf |
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