Pareto Dominance of Deferred Acceptance through Early Decision

An early decision market is governed by rules that allow each student to apply to (at most) one college and require the student to attend this college if admitted. This market is ubiquitous in college admissions in the United States. We model this market as an extensive-form game of perfect information and study a refinement of subgame perfect equilibrium (SPE) that induces undominated Nash equilibria in every subgame (SPUE). Our main result shows that this game can be used to define a decentralized matching mechanism that weakly Pareto dominates student-proposing deferred acceptance

Essays on Microeconomic Theory.

The present work collects three essays on microeconomic theory. In the first essay, I study a model in which a finite number of men and women look for future spouses via random meetings. I ask whether equilibrium marriage outcomes are stable matchings when search frictions are small. The answer is they can but need not be. For any stable matching there is an equilibrium leading to it almost surely. However unstable---even Pareto-dominated---matchings may still arise with positive probability. In addition, inefficiency due to delay may remain significant despite vanishing search frictions. Finally, a condition is identified under which all equilibria are outcome equivalent, stable, and efficient. In the second essay, a joint work Kfir Eliaz, we model a competition between two teams as an all-pay auction with incomplete information. The teams may differ in size and individuals exert effort to increase the performance of one's own team via an additively separable aggregation function. The team with a higher performance wins, and its members enjoy the prize as a public good. The value of the prize is identical to members of the same team but is unknown to the other team. We show that there exists a unique monotone equilibrium in which everyone actively participates, and in this equilibrium a bigger team is more likely to win if the aggregation function is concave, less likely if convex, or equally likely if linear. In the third essay, I study a situation in which a group of people working on a common objective want to share information. Oftentimes information sharing via precise communication is impossible and instead information is aggregated by institutions within which communication is coarse. The paper proposes a unified framework for modeling a general class of such information-aggregating institutions. Within this class, it is shown that institution A outperforms institution B for any common objective if and only if the underlying communication infrastructure of A can be obtained from that of B by a sequence of elementary operations. Each operation either removes redundant communication instruments from B or introduces effective ones to it.PhDEconomicsUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/133250/1/wqg_1.pd

Smart-Dating in Speed-Dating: How a Simple Search Model Can Explain Matching Decisions

How do people in a romantic matching situation choose a potential partner? We study this question in a new model of matching under search frictions, which we estimate using data from an existing speed dating experiment. We find that attraction is mostly in the eye of the beholder and that the attraction between two potential partners has a tendency to be mutual. These results are supported by a direct measure of subjective attraction. We also simulate the estimated model, and it predicts rejection patterns, matching rates, and sorting outcomes that fit the data very well. Our results are consistent with the hypothesis that people in a dating environment act strategically and have at least an implicit understanding of the nature of the frictions and of the strategic equilibrium

Multi-agent Learning For Game-theoretical Problems

Multi-agent systems are prevalent in the real world in various domains. In many multi-agent systems, interaction among agents is inevitable, and cooperation in some form is needed among agents to deal with the task at hand. We model the type of multi-agent systems where autonomous agents inhabit an environment with no global control or global knowledge, decentralized in the true sense. In particular, we consider game-theoretical problems such as the hedonic coalition formation games, matching problems, and Cournot games. We propose novel decentralized learning and multi-agent reinforcement learning approaches to train agents in learning behaviors and adapting to the environments. We use game-theoretic evaluation criteria such as optimality, stability, and resulting equilibria