Effective affirmative action in school choice

Abstract

The prevalent affirmative action policy in school choice limits the number of admitted majority students to give minority students higher chances to attend their desired schools. There have been numerous efforts to reconcile affirmative action policies with celebrated matching mechanisms such as the deferred acceptance and top trading cycles algorithms. Nevertheless, it is theoretically shown that under these algorithms, the policy based on majority quotas may be detrimental to minorities. Using simulations, we find that this is a more common phenomenon rather than a peculiarity. To circumvent the inefficiency caused by majority quotas, we offer a different interpretation of the affirmative action policies based on minority reserves. With minority reserves, schools give higher priority to minority students up to the point that the minorities fill the reserves. We compare the welfare effects of these policies. The deferred acceptance algorithm with minority reserves Pareto dominates the one with majority quotas. Our simulations, which allow for correlations between student preferences and school priorities, indicate that minorities are, on average, better off with minority reserves while adverse effects on majorities are mitigated.

Matching With (Branch-of-Choice) Contracts at the United States Military Academy

“…The first feature alone is not novel and it has been extensively utilized in the context of school choice with affirmative action. Examples of such applications include controlled choice models of Abdulkadiroglu and Sönmez (2003) with majority quotas and Hafalir, Yenmez, and Yildirim (2011) with minority reserves, 29 as well as the school choice model of Westkamp (2011) with complex constraints. However, in contrast to cadet-branch matching, object priorities satisfy the substitutes condition in all of these earlier applications.…”

“…30 28 Biró, Fleiner, Irving, and Manlove (2010) reported that college admissions in Hungary have a similar feature, where part of the slots at each department are state-financed while the rest are privately financed. 29 Hafalir, Yenmez, and Yildirim (2011) considered a school choice model where minority students are favored at a fraction of slots at each school. Rather than fully blocking the access of majority students, they advocated favorable treatment of minority students for these slots through increased priority.…”

“…Loosely speaking, both models advocate the use of "soft caps," although they differ in two critical ways. In contrast to our model, (1) the set of favored agents is exogenous, and (2) the resulting object priorities satisfy the standard substitutes condition in Hafalir, Yenmez, and Yildirim (2011). 30 School districts that rely on such priority structures include Boston, Chicago, New York City, and Providence.…”

Matching with slot-specific priorities: Theory

“…In this paper, we develop a general framework for handling these sorts of slot-specific priority structures. 3 Our model embeds classical priority matching settings (e.g., Balinski andSönmez 1999, Abdulkadiroglu andSönmez 2003), models of affirmative action (e.g., Kojima 2012, Hafalir et al 2013, and the cadetbranch matching framework (Sönmez andSwitzer 2013, Sönmez 2013), as well as a new market design problem we introduce: airline seat upgrade allocation. 4,5 We show how markets with slot-specific priorities can be cleared by the cumulative offer mechanism, which generalizes agent-proposing deferred acceptance Milgrom 2005, Hatfield andKojima 2010).…”

Dual-Donor Organ Exchange

“…saving nearly 230-300 additional liver patients in South Korea alone (see the last line of Table IV in Section 3.2 and Table VI in Appendix B.2. Increasingly, economists are taking advantage of advances in technology to design new or improved allocation mechanisms in applications as diverse as entry-level labor markets (Roth and Peranson (1999)), spectrum auctions (Milgrom (2000)), internet auctions (Edelman, Ostrovsky, and Schwarz (2007), Varian (2007)), school choice (Abdulkadiroglu and Sönmez (2003)), kidney exchange (Roth, Sönmez, and Ünver (2004, 2007), course allocation (Sönmez and Ünver (2010), Budish and Cantillon (2012)), affirmative action (Kojima (2012), Hafalir, Yenmez, and Yildirim (2013), Echenique and Yenmez (2015)), cadet-branch matching (Sönmez and Switzer (2013), Sönmez (2013)), refugee matching (Moraga and Rapoport (2014), Jones and Teytelboym (2016)), and assignment of arrival slots (Schummer and Vohra (2013), Schummer and Abizada (2017)). Our paper contributes to the emerging field of market design by introducing a new application in dual-donor organ exchange, and also to transplantation literature by introducing three novel transplantation modalities.…”