Thesis advisor: M. Utku Ünver / Thesis advisor: M. Bumin Yenmez / This dissertation consists of two essays in market design. In the first chapter, we study affirmative action policies in college admissions and hiring. A college or firm makes admissions or hiring decisions in which each candidate is characterized by priority ranking and type, which may depend on race, gender, or socioeconomic status. The admissions or hiring committee faces a trade-off between meritocracy and diversity: while a merit-first choice rule may admit candidates of the same type, a diversity-first choice rule may be unfair due to priority violations. To formalize this trade-off, we introduce a measure of meritocracy and a measure of diversity for choice rules. Then, we investigate how to resolve the tension between them. A choice rule that uses both reserves and quotas can be viewed as a compromise and is a generalization of the two extreme rules. The first result is comparative statics for this class of choice rules: we show that as parameters change and the choice rule becomes more meritorious, it also becomes less diverse. The second result is a characterization of the choice rule, which may help admissions or hiring committees to decide their policies.
In the second chapter, we introduce a method to measure manipulability of a matching mechanism and use theory and simulation to study constrained mechanisms in school choice. First, we show that the implications from existing measures are strongly dependent on the full preference domain assumption. Our measure is more robust. The implications from existing measures can be carried over as well: while the recent school admissions reforms did not fully eliminate incentives to manipulate, they discouraged manipulation. Second, we use simulations for quantitative analysis. Our results support the recent school admissions reforms quantitatively, as well as qualitatively: they largely eliminated the incentives to manipulate. In addition, while the qualitative implications from theory are parallel to existing measures, the quantitative implications from simulations confirm a significant difference. / Thesis (PhD) — Boston College, 2021. / Submitted to: Boston College. Graduate School of Arts and Sciences. / Discipline: Economics.
| Identifer | oai:union.ndltd.org:BOSTON/oai:dlib.bc.edu:bc-ir_109090 |
| Date | January 2021 |
| Creators | Imamura, Kenzo |
| Publisher | Boston College |
| Source Sets | Boston College |
| Language | English |
| Detected Language | English |
| Type | Text, thesis |
| Format | electronic, application/pdf |
| Rights | Copyright is held by the author, with all rights reserved, unless otherwise noted. |
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