Presented By: Department of Economics
Econometrics: Partial Identification of the Distribution of Treatment Effects with an Application to the Knowledge Is Power Program (KIPP)
Brigham Frandsen, Brigham Young University
Abstract:
We bound the distribution of treatment effects under plausible and testable assumptions on the joint distribution of potential outcomes, namely that potential outcomes are stochastically increasing. We show how to test the empirical restrictions implied by those assumptions. The resulting bounds substantially sharpen the classical bounds based on Frechet-Hoeffding limits. We apply our method to identify bounds on the distribution of effects of attending a Knowledge is Power Program (KIPP) charter school on student academic achievement, and find that a substantial majority of students’ math achievement benefitted from attendance, especially those who would have fared poorly in a traditional classroom.
We bound the distribution of treatment effects under plausible and testable assumptions on the joint distribution of potential outcomes, namely that potential outcomes are stochastically increasing. We show how to test the empirical restrictions implied by those assumptions. The resulting bounds substantially sharpen the classical bounds based on Frechet-Hoeffding limits. We apply our method to identify bounds on the distribution of effects of attending a Knowledge is Power Program (KIPP) charter school on student academic achievement, and find that a substantial majority of students’ math achievement benefitted from attendance, especially those who would have fared poorly in a traditional classroom.
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