Information and fairness in resource allocation problems
Abstract/Contents
- Abstract
- This thesis explores the role of information and fairness in resource allocation settings with applications for social good. The thesis has two parts. At a high level, the first part asks whether and how we can use information as a natural lever to maximize social welfare in the presence of strategic incentives. More specifically, we consider a mechanism design model of objects and agents arriving over time. Agents have private types and waiting costs. We show that the welfare-maximizing mechanism can be implemented in two simple ways that both require some pooling of information. Furthermore, we partially extend this result to a setup where agents have heterogeneous outside options. The second part asks whether and how inherent informational differences across different individuals can explain documented disparities in the allocation of social goods, and if so, what alternative policies can mitigate such disparities. Motivated by disparities in college admissions, we introduce a theoretical framework to study how a decision-maker, concerned with both merit and diversity, selects candidates under imperfect information, limited capacity, and possibly legal constraints. We apply this framework to study the tradeoffs of existing policies (dropping standardized testing, using the top percent rule) as well as to find the optimal selection policy for a generalized optimization problem.
Description
| Type of resource | text |
|---|---|
| Form | electronic resource; remote; computer; online resource |
| Extent | 1 online resource. |
| Place | California |
| Place | [Stanford, California] |
| Publisher | [Stanford University] |
| Copyright date | 2022; ©2022 |
| Publication date | 2022; 2022 |
| Issuance | monographic |
| Language | English |
Creators/Contributors
| Author | Monachou, Faidra Georgia |
|---|---|
| Degree supervisor | Ashlagi, Itai |
| Thesis advisor | Ashlagi, Itai |
| Thesis advisor | Lo, Irene, (Management science professor) |
| Thesis advisor | Weintraub, Gabriel |
| Degree committee member | Lo, Irene, (Management science professor) |
| Degree committee member | Weintraub, Gabriel |
| Associated with | Stanford University, Department of Management Science and Engineering |
Subjects
| Genre | Theses |
|---|---|
| Genre | Text |
Bibliographic information
| Statement of responsibility | Faidra Monachou. |
|---|---|
| Note | Submitted to the Department of Management Science and Engineering. |
| Thesis | Thesis Ph.D. Stanford University 2022. |
| Location | https://purl.stanford.edu/fb926gp8555 |
Access conditions
- Copyright
- © 2022 by Faidra Georgia Monachou
- License
- This work is licensed under a Creative Commons Attribution Non Commercial No Derivatives 3.0 Unported license (CC BY-NC-ND).
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