Controlled School Choice with Soft Bounds and Overlapping Types

School choice programs are implemented to give students/parents an opportunity to choose the public school the students attend. Controlled school choice programs need to provide choices for students/parents while maintaining distributional constraints on the balance on the composition of students, typically in terms of so-cioeconomic status. Previous works show that setting soft-bounds, which flexibly change the priorities of students based on their types, is more appropriate than setting hard-bounds, which strictly limit the number of accepted students for each type. We consider a case where soft-bounds are imposed and one student can belong to multiple types, e.g., "financially-distressed" and "minority" types. We first show that when we apply a model that is a straightforward extension of an existing model for disjoint types, there is a chance that no stable matching exists. Thus, we propose an alternative model and an alternative stability definition, where a school has reserved seats for each type. We show that a stable matching is guaranteed to exist in this model, and develop a mechanism called Deferred Acceptance for Overlapping Types (DA-OT). The DA-OT mechanism is strategy-proof and obtains the student-optimal matching within all stable matchings. Computer simulation results illustrate that the DA-OT outperforms an artificial cap mechanism, where the number of seats for each type is fixed.

[1]  Naoyuki Kamiyama A note on the serial dictatorship with project closures , 2013, Oper. Res. Lett..

[2]  Tayfun Sönmez,et al.  Matching With (Branch‐of‐Choice) Contracts at the United States Military Academy , 2013 .

[3]  Atila Abdulkadiroglu,et al.  School Choice: A Mechanism Design Approach , 2003 .

[4]  Tayfun Sönmez,et al.  Matching with Contracts: Comment , 2013 .

[5]  Craig Boutilier,et al.  Effective sampling and learning for mallows models with pairwise-preference data , 2014, J. Mach. Learn. Res..

[6]  Tamás Fleiner,et al.  A Matroid Approach to Stable Matchings with Lower Quotas , 2012, Math. Oper. Res..

[7]  Makoto Yokoo,et al.  Strategyproof matching with regional minimum and maximum quotas , 2016, Artif. Intell..

[8]  Parag A. Pathak,et al.  Strategy-Proofness versus Efficiency in Matching with Indifferences: Redesigning the NYC High School Match , 2009 .

[9]  Alexander Westkamp An analysis of the German university admissions system , 2013 .

[10]  David Manlove,et al.  The College Admissions problem with lower and common quotas , 2010, Theor. Comput. Sci..

[11]  Alvin E. Roth,et al.  Two-Sided Matching: A Study in Game-Theoretic Modeling and Analysis , 1990 .

[12]  Tayfun Sönmez,et al.  Designing for Diversity: Matching with Slot-Specific Priorities , 2012 .

[13]  Makoto Yokoo,et al.  Strategy-proof matching with regional minimum quotas , 2014, AAMAS.

[14]  J. D. Tubbs Distance Based Binary Matching , 1992 .

[15]  Makoto Yokoo,et al.  Designing Matching Mechanisms under General Distributional Constraints , 2015, EC.

[16]  Faruk Gul,et al.  WALRASIAN EQUILIBRIUM WITH GROSS SUBSTITUTES , 1999 .

[17]  Tamás Fleiner,et al.  A Fixed-Point Approach to Stable Matchings and Some Applications , 2003, Math. Oper. Res..

[18]  Makoto Yokoo,et al.  Strategy-proof mechanisms for two-sided matching with minimum and maximum quotas , 2012, AAMAS.

[19]  David Manlove,et al.  Algorithmics of Matching Under Preferences , 2013, Bull. EATCS.

[20]  F. Kojima,et al.  Efficient Matching under Distributional Constraints: Theory and Applications , 2015 .

[21]  Chien-Chung Huang,et al.  Classified stable matching , 2009, SODA '10.

[22]  Fuhito Kojima,et al.  School choice: Impossibilities for affirmative action , 2012, Games Econ. Behav..

[23]  Paul R. Milgrom,et al.  Designing Random Allocation Mechanisms: Theory and Applications , 2013 .

[24]  Scott Duke Kominers,et al.  Matching with Slot-Specific Priorities: Theory , 2016 .

[25]  Paul R. Milgrom,et al.  Matching with Contracts , 2005 .

[26]  Fahiem Bacchus,et al.  Strategy-Proofness in the Stable Matching Problem with Couples , 2016, AAMAS.

[27]  Nicole Immorlica,et al.  Two-sided matching with partial information , 2013, EC '13.

[28]  Craig Boutilier,et al.  Elicitation and Approximately Stable Matching with Partial Preferences , 2013, IJCAI.

[29]  Isa Emin Hafalir,et al.  Effective affirmative action in school choice , 2011 .

[30]  Francesca Rossi,et al.  Stable matching problems with soft constraints , 2014, AAMAS.

[31]  Tayfun Sönmez,et al.  Games of school choice under the Boston mechanism , 2006 .

[32]  Dorothea Kübler,et al.  Implementing Quotas in University Admissions: An Experimental Analysis , 2011 .

[33]  Makoto Yokoo,et al.  Strategyproof Matching with Minimum Quotas , 2016, TEAC.

[34]  John William Hatfield,et al.  Group incentive compatibility for matching with contracts , 2009, Games Econ. Behav..

[35]  Isa Emin Hafalir,et al.  School Choice with Controlled Choice Constraints: Hard Bounds Versus Soft Bounds , 2011, J. Econ. Theory.

[36]  Tuomas Sandholm,et al.  Online Stochastic Optimization in the Large: Application to Kidney Exchange , 2009, IJCAI.

[37]  Atila Abdulkadiroglu,et al.  College admissions with affirmative action , 2005, Int. J. Game Theory.

[38]  F. Echenique,et al.  How to Control Controlled School Choice , 2014 .

[39]  Shuichi Miyazaki,et al.  The Hospitals/Residents Problem with Lower Quotas , 2014, Algorithmica.