Credible School Value-Added with Undersubscribed School Lotteries
利用学校分配机制中的随机性，提出两种策略来测量学校增值，解决学校未满额时的识别难题，并在丹佛和纽约市的数据中验证了方法的可靠性。
Abstract 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.