Replication data for: Estimating Group Effects Using Averages of Observables to Control for Sorting on Unobservables: School and Neighborhood Effects

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 90th versus 10th 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.