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An Economic Approach to Generalizing Findings from Regression-Discontinuity Designs

An Economic Approach to Generalizing Findings from Regression-Discontinuity Designs <p>ABSTRACT:</p><p>Regression-discontinuity (RD) designs estimate treatment effects only around a cutoff. This paper shows what can be learned about average treatment effects for the treated (ATT), untreated (ATUT), and population (ATE) if the cutoff was chosen to maximize the net gain from treatment. Without capacity constraints, the RD estimate bounds the ATT from below and the ATUT from above, implying bounds for the ATE, and optimality of the cutoff rules out constant treatment effects. Bounds are typically looser if the capacity constraint binds. Testable implications of cutoff optimality are derived. The results are demonstrated using previous RD studies.</p> http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Journal of Human Resources University of Wisconsin Press

An Economic Approach to Generalizing Findings from Regression-Discontinuity Designs

Journal of Human Resources , Volume 54 (4) – Nov 7, 2019

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Publisher
University of Wisconsin Press
Copyright
© Board of Regents of the University of Wisconsin System
ISSN
1548-8004

Abstract

<p>ABSTRACT:</p><p>Regression-discontinuity (RD) designs estimate treatment effects only around a cutoff. This paper shows what can be learned about average treatment effects for the treated (ATT), untreated (ATUT), and population (ATE) if the cutoff was chosen to maximize the net gain from treatment. Without capacity constraints, the RD estimate bounds the ATT from below and the ATUT from above, implying bounds for the ATE, and optimality of the cutoff rules out constant treatment effects. Bounds are typically looser if the capacity constraint binds. Testable implications of cutoff optimality are derived. The results are demonstrated using previous RD studies.</p>

Journal

Journal of Human ResourcesUniversity of Wisconsin Press

Published: Nov 7, 2019

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