论文标题
延期接受的偏好估计和部分学校排名
Preference Estimation in Deferred Acceptance with Partial School Rankings
论文作者
论文摘要
由于其策略证明，递延的接受算法是一种流行的学校分配机制。但是，由于应用成本，策略证明失败了，导致了识别问题。在本文中，我通过开发一个新的阈值等级设置来解决此标识问题，该设置将整个等级顺序列表模拟为单步实用程序最大化问题。我将此框架应用于智利的学生作业。该论文有三个关键贡献。我开发了一种递归算法来计算我的一步决策模型的可能性。通过将外部价值和预期入学概率纳入线性成本框架来解决部分识别。经验应用显示，尽管学校接近是学校选择的重要变量，但学生能力对于对高学术成绩学校的排名至关重要。结果表明，旨在提高学生能力的辅导等政策干预措施可以帮助增加智利质量质量更好的学校低收入学生的代表。
The Deferred Acceptance algorithm is a popular school allocation mechanism thanks to its strategy proofness. However, with application costs, strategy proofness fails, leading to an identification problem. In this paper, I address this identification problem by developing a new Threshold Rank setting that models the entire rank order list as a one-step utility maximization problem. I apply this framework to study student assignments in Chile. There are three critical contributions of the paper. I develop a recursive algorithm to compute the likelihood of my one-step decision model. Partial identification is addressed by incorporating the outside value and the expected probability of admission into a linear cost framework. The empirical application reveals that although school proximity is a vital variable in school choice, student ability is critical for ranking high academic score schools. The results suggest that policy interventions such as tutoring aimed at improving student ability can help increase the representation of low-income low-ability students in better quality schools in Chile.
