Publisher
The University of Arizona.Rights
Copyright © is held by the author. Digital access to this material is made possible by the University Libraries, University of Arizona. Further transmission, reproduction, presentation (such as public display or performance) of protected items is prohibited except with permission of the author.Abstract
The primary aim of this dissertation is to identify channels through which economic agents use social preferences such as proclivities towards fairness and inequality to make choices in one-shot and repeated game environments. I am particularly interested in economic situations of strategic interaction that support multiple equilibria. When faced with such situations, economic agents often coordinate on a set of salient outcomes that are smaller than the set of all possible equilibrium outcomes. There is a lack of broad consensus on what makes certain payoff outcomes salient in the minds of agents, while others are ignored. The human decision making involved in this equilibrium selection process interests me, because a better understanding of this mechanism can help us make sharper predictions about the plausible outcomes we should expect to see. I believe models that incorporate social preferences, learning, and bounded rationality are likely to make better predictions in these scenarios than models that assume economic agents are infinitely rational. To examine the questions of how economic agents go about the equilibrium selection process, I use a combination of theory, computation, and laboratory experiments. Each of these three approaches has unique benefits, and complements each other. 1) Economic theory allows us to focus on a specific problem and prove general theorems that hold in all situations that the assumptions allow. Specifically, I am interested in theoretical models that allow for a combination of personal and social preferences for economic agents that weight notions of efficiency, selfishness, and fairness in personal and joint payoff outcomes when undertaking the equilibrium selection process. 2) Computation allows us to run simulations of models that may not have closed-form solutions, or ones that are difficult to grasp analytically. 3) Experiments allow us to test whether outcomes that agents arrive at after undergoing the equilibrium selection process are context dependent, and change based on the nature of the information available to them. They help examine human behavior in a controlled environment, allowing us to focus on the specific aspect of the decision making process in which we are interested. The combination of theory, computation, and experiments helps us look into the black box of the decision making of economic agents undertaking the equilibrium selection process.Type
textElectronic Dissertation
Degree Name
Ph.D.Degree Level
doctoralDegree Program
Graduate CollegeEconomics