Credible School Value-Added with Undersubscribed School Lotteries

• 成果类型: Article
• 署名作者: Angrist, Joshua; Hull, Peter; Pathak, Parag A.; Walters, Christopher
• 署名单位: Massachusetts Institute of Technology (MIT); National Bureau of Economic Research; Brown University; University of California System; University of California Berkeley
• 刊物名称: REVIEW OF ECONOMICS AND STATISTICS
• ISSN/ISSBN: 0034-6535
• DOI: 10.1162/rest_a_01149
• 发表日期: 2024-01
• 页码: 1-19
• 关键词: impacts; college; DESIGN; models; CHOICE; tests

摘要

We introduce two empirical strategies harnessing the randomness in school assignment mechanisms to measure school value-added. The first estimator controls for the probability of school assignment, treating take-up as ignorable. We test this assumption using randomness in assignments. The second approach uses assignments as instrumental variables (IVs) for low-dimensional models of value-added and forms empirical Bayes posteriors from these IV estimates. Both strategies solve the underidentification challenge arising from school undersubscription. Models controlling for assignment risk and lagged achievement in Denver and New York City yield reliable value-added estimates. Estimates from models with lower-quality achievement controls are improved by IV.