Research Design Meets Market Design: Using Centralized Assignment for Impact Evaluation

Abstract

A growing number of school districts use centralized assignment mechanisms to allocate school seats in a manner that reflects student preferences and school priorities. Many of these assignment schemes use lotteries to ration seats when schools are oversubscribed. The resulting random assignment opens the door to credible quasi-experimental research designs for the evaluation of school effectiveness. Yet the question of how best to separate the lottery-generated variation integral to such designs from non-random preferences and priorities remains open. This paper develops easily-implemented empirical strategies that fully exploit the random assignment embedded in the widely-used deferred acceptance mechanism and its variants. We use these methods to evaluate charter schools in Denver, one of a growing number of districts that integrate charter and traditional public schools in a unified assignment system. The resulting estimates show large achievement gains from charter school attendance. Our approach expands the scope for impact evaluation by maximizing the number of students and schools that can be studied using random assignment. We also show how to use DA to identify causal effects in models with multiple school sectors.