Collaborative Research: School Choice and College Admissions: Theory and Experiments

本提案要求获得一项为期三年的拨款，以支持密歇根大学和卡内基-梅隆大学在匹配理论和实验方面的研究项目。拟议中的部分研究将在中国进行，与上海交通大学的秦向东和清华大学的石宗凯合作。本项目是由美国国家科学基金SES-0720943和学校基金支持的工作的延伸。这一研究成果有可能对美国的择校改革和中国的大学招生改革产生直接影响。(1)智力价值：pi建议对应用于学校选择问题的一系列匹配机制进行理论和实验研究：波士顿机制，这是实践中最常用和最突出的学校选择算法之一，以及两种具有优越理论特性的替代方案？盖尔-沙普利机制和改良的波士顿机制。实验数据将为择校背景下的一系列机制提供严格的评估。然后，pi提出了大学招生机制的实验研究，并在中国使用了变体。对这些机制的理论和实验研究对于促进知识的发展至关重要。机制不能纯粹根据理论来评估，因为人们可能不会按预期使用它们。它们也不能像在现实世界中使用那样进行评估，因为我们无法接触到人。真正的偏好。实验对于理解机制如何运作至关重要。值得注意的是，无论这些假设是被证实还是被拒绝，这些发现都将指导理论和实践。(2)更广泛的影响：在过去的二十年里，择校一直是最重要和最广泛争论的话题之一。在当前关于学校改革的辩论中，选择权已经成为国家议程的首要议题。波士顿机制是几个率先实施择校计划的城市使用的一种突出算法，但其性能尚未得到彻底评估。随着越来越多的州通过立法，强制实行地区内或地区间的选择，迫切需要对这一机制以及其他机制进行评估，以便提出有意义的政策建议。同样，中国的大学录取机制也出现了一系列新的匹配问题，这些问题每年影响着1000多万高中毕业生的教育和劳动力市场结果。这项研究计划有可能通过影响学生与学校和大学的匹配方式来造福社会。只有在本科生和研究生的参与下，才能成功和及时地完成所提出的实验计划。自1999年以来，Chen一直通过密歇根大学的本科生研究机会计划和NSF REU计划与本科生一起工作。每年将继续招收1-2名本科生参与本研究项目。本科新生将有机会参与项目的大部分阶段，包括文献综述、协助进行实验和初步数据分析。分析大数据集需要研究生的辛勤工作和奉献精神。因此，pi计划每年为该项目安排一名研究生研究助理。鼓励研究生参加会议和研讨会，向研究界展示他们的研究成果。研究生将学习实验研究的整个过程，从实验设计、执行、数据分析到写作和报告。

This proposal requests a three-year grant to support a program of research in matching theory and experiments at the University of Michigan and Carnegie-Mellon University. Part of the proposed research will be conducted in China, in collaboration with Xiangdong Qin at Shanghai Jiao Tong University and Zongkai Shi at Tsinghua University. This program is an extension of workthat has been supported by NSF grant SES-0720943 and university funds. The proposed research is likely to have direct impact on the school choice reform in the U.S. and college admissions reform in China.(1) Intellectual merit: The PIs propose to conduct theoretical and experimental studies of a family of matching mechanisms applied to the school choice problem: the Boston mechanism, which is one of the most commonly used and prominent school choice algorithms in practice, and two alternatives which have superior theoretical properties ? the Gale-Shapley mechanism and the modified Boston mechanism. Data from the experiment will provide a rigorous evaluation of the family of mechanisms in the school choice context. The PIs then propose experimental studies of the college admissions mechanisms, with variants used in China. Both the theoretical and the experimental studies of these mechanisms are essential to advancing knowledge. Mechanisms cannot be evaluated purely on theoretical grounds, because people may not use them as intended. Nor can they be evaluated as used in the real world, because we donot have access to people?s true preferences. Experiments are vital to understanding how mechanisms will perform. It is important to note that the findings will guide both theory and practice regardless of whether the hypotheses are confirmed or rejected.(2) Broader impacts: School choice has been one of the most important and most widely debated topics in the past twenty years. In the current debate on school reform, choice has moved to the top of the national agenda. The Boston mechanism is a prominent algorithm used in several cities pioneering the school choice program, but its performance has not been thoroughly evaluated. As more states have passed legislation mandating intra- or inter-district choice, it is urgent to evaluate this mechanism as well as alternative mechanisms in order to make meaningful policy recommendations. Similarly, college admissions mechanisms in China present a new class of matching problems which influence the education and labor market outcomes of more than 10 million high school seniors every year. The research proposal has the potential to benefit society by influencing the method by which students are matched with schools and colleges. The successful and timely completion of the proposed experimental program is only possible with the involvement of undergraduate and graduate students. Chen has been working with undergraduatestudents through the Undergraduate Research Opportunities Program at the University of Michigan since 1999 and the NSF REU program. The PIs will continue to include 1-2 undergraduate students in this research project every year. New undergraduate students will have the opportunity to become involved in most phases of the project, including literature review, assistance in conducting experiments and preliminary data analysis. Analysis of large data sets requires the hard work and dedication of graduate students. Therefore, the PIs plan to get one graduate student research assistant for each year of the project. Graduate students are encouraged to participate in conferences and workshops to present their research to the research community. Graduate students will learn the entire process of experimental research, from experimental design, execution, data analysis to writing and presentation.