Improving Transparency and Verifiability in School Admissions: Theory and Experiment
中文摘要
参与集中招生程序的学生通常无法获取用于确定其匹配学校的信息，例如其他学生的偏好或学校优先级。这可能导致学生怀疑其匹配结果是否被正确计算（“可验证性问题”），或者在更深层次上怀疑所承诺的招生程序是否确实被采用（“透明度问题”）。在一个涵盖多种流行应用的模型中，我们展示了如何通过向学生提供适当反馈而不披露诸如其他学生偏好或学校优先级等敏感信息来解决这些问题。具体而言，我们表明可验证性问题可以通过以下方式解决：（1）公开传达“分数线”（即被每所学校录取所需的最低分数），或（2）采用传达丰富“体验性”信息的“单校”偏好征集程序。在我们的主要结果中，我们表明透明度问题可以通过同时使用分数线和单校征集程序来解决。我们在实验室实验中找到了对这些解决方案的有力支持，并展示了如何将其应用于涉及顶级交易循环（top trading cycles）以及延期接受和立即接受的流行学校招生场景。本文由行为经济学与决策分析领域编辑Yan Chen接受。资助：作者感谢瑞士国家科学基金会[项目 100018_207722]的财务支持。所表达的观点仅代表个人，不代表所在组织的观点。补充材料：在线附录和数据文件可在 https://doi.org/10.1287/mnsc.2023.00105 获取。
Abstract
Students participating in centralized admissions procedures do not typically have access to the information used to determine their matched school, such as other students’ preferences or school priorities. This can lead to doubts about whether their matches were computed correctly (the “verifiability problem”) or, at a deeper level, whether the promised admissions procedure was even used (the “transparency problem”). In a model that spans many popular applications, we show how these problems can be addressed by providing appropriate feedback to students without disclosing sensitive information like other students’ preferences or school priorities. In particular, we show that the verifiability problem can be solved by (1) publicly communicating “cutoffs” (the minimum scores required to be eligible for each school) or (2) using “single-school” preference elicitation procedures that convey rich “experiential” information. In our main result, we show that the transparency problem can be solved by using cutoffs and single-school elicitation procedures together. We find strong support for these solutions in a laboratory experiment and show how they can be implemented for popular school admissions applications involving top trading cycles, and deferred and immediate acceptance. This paper was accepted by Yan Chen, behavioral economics and decision analysis. Funding: The authors acknowledge financial support from the Swiss National Science Foundation [Project 100018_207722]. Views expressed are personal and do not reflect the views of the organization. Supplemental Material: The online appendix and data files are available at https://doi.org/10.1287/mnsc.2023.00105 .