多学区择校：在多个领域博弈
Multi-District School Choice: Playing on Several Fields
AI总结：
本文将Pathak和Sönmez的经典择校匹配模型扩展至双学区场景，分析学生类型与申请约束的影响，发现原有核心结论发生反转，相关现象普遍存在于大型随机市场。
摘要：
我们将Pathak和Sönmez（2008）的开创性模型扩展到包含多个学区的场景，每个学区各自运行独立的集中匹配机制，本研究重点关注双学区情形。在该场景下，除了每名学生分为真诚型或老练型外，还分为受约束型——仅能申请居住所在学区内的学校，以及不受约束型——可选择任意单一学区并在该学区内提交申请。我们发现Pathak和Sönmez（2008）的若干核心结论发生了质性反转：一名老练学生可能希望真诚学生转变为老练型；无论另一学区采用何种机制，老练学生都可能更倾向于自己所在学区采用延迟接受（Deferred Acceptance）机制而非波士顿机制（Boston Mechanism）。我们还进一步研究了学生对其他学生约束水平的偏好。上述诸多现象在大型随机市场中大量存在。
英文摘要：
We extend the seminal model of Pathak and Sönmez (2008) to a setting with multiple school districts, each running its own separate centralized match, and focus on the case of two districts. In our setting, in addition to each student being either sincere or sophisticated, she is also either constrained - able to apply only to schools within her own district of residence - or unconstrained - able to choose any single district within which to apply. We show that several key results from Pathak and Sönmez (2008) qualitatively flip: A sophisticated student may prefer for a sincere student to become sophisticated, and a sophisticated student may prefer for her own district to use Deferred Acceptance over the Boston Mechanism, irrespective of the mechanism used by the other district. We furthermore investigate the preferences of students over the constraint levels of other students. Many of these phenomena appear abundantly in large random markets.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
