| 来源类型 | Working Paper |
| 规范类型 | 报告 |
| DOI | 10.3386/w22109 |
| 来源ID | Working Paper 22109 |
| Explicit vs. Statistical Preferential Treatment in Affirmative Action: Theory and Evidence from Chicago's Exam Schools | |
| Umut Dur; Parag A. Pathak; Tayfun Sönmez | |
| 发表日期 | 2016-03-28 |
| 出版年 | 2016 |
| 语种 | 英语 |
| 摘要 | Affirmative action schemes must confront the tension between admitting the highest scoring applicants and ensuring diversity. In Chicago's affirmative action system for exam schools, applicants are divided into one of four socioeconomic tiers based on the characteristics of their neighborhood. Applicants can be admitted to a school either through a slot reserved for their tier or through a merit slot. Equity considerations motivate equal percentage reserves for each tier, but there is a large debate on the total size of these reserve slots relative to merit slots. An issue that has received much less attention is the order in which slots are processed. Since the competition for merit slots is influenced directly by the allocation to tier slots, equal size reserves are not sufficient to eliminate explicit preferential treatment. We characterize processing rules that are tier-blind. While explicit preferential treatment is ruled out under tier-blind rules, it is still possible to favor certain tiers, by exploiting the distribution of scores across tiers, a phenomenon we call statistical preferential treatment. We characterize the processing order that is optimal for the most disadvantaged tier assuming that these applicants systematically have lower scores. This policy processes merit slots prior to any slots reserved for tiers. Our main result implies that Chicago has been providing an additional boost to the disadvantaged tier beyond their reserved slots. Using data from Chicago, we show that the bias due to processing order for the disadvantaged tier is comparable to that from the 2012 decrease in the size of the merit reserve. |
| 主题 | Microeconomics ; Game Theory ; Market Structure and Distribution ; Health, Education, and Welfare ; Education |
| URL | https://www.nber.org/papers/w22109 |
| 来源智库 | National Bureau of Economic Research (United States) |
| 引用统计 | |
| 资源类型 | 智库出版物 |
| 条目标识符 | http://119.78.100.153/handle/2XGU8XDN/579783 |
| 推荐引用方式 GB/T 7714 | Umut Dur,Parag A. Pathak,Tayfun Sönmez. Explicit vs. Statistical Preferential Treatment in Affirmative Action: Theory and Evidence from Chicago's Exam Schools. 2016. |
| 条目包含的文件 | ||||||
| 文件名称/大小 | 资源类型 | 版本类型 | 开放类型 | 使用许可 | ||
| w22109.pdf（1452KB） | 智库出版物 | 限制开放 | CC BY-NC-SA | 浏览 | ||
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