Estimating Group Effects Using Averages of Observables to Control for Sorting on Unobservables: School and Neighborhood Effects
提出用组均值控制不可观测特征的方法，估计学校与邻里对高中毕业率、大学入学率和永久工资的影响，发现90分位比10分位学校/邻里的效应至少分别提高0.04、0.11和13.7%。
We consider the classic problem of estimating group treatment effects when individuals sort based on observed and unobserved characteristics. Using a standard choice model, we show that controlling for group averages of observed individual characteristics potentially absorbs all the across-group variation in unobservable individual characteristics. We use this insight to bound the treatment effect variance of school systems and associated neighborhoods for various outcomes. Across multiple datasets, we find that a ninetieth versus tenth percentile school/neighborhood increases the high school graduation probability and college enrollment probability by at least 0.04 and 0.11 and permanent wages by 13.7 percent.