A Method for Disentangling Multiple Treatments from a Regression Discontinuity Design

Michael Gilraine

Journal of Labor Economics, 2020, vol. 38, issue 4, 1267 - 1311

Abstract: In many settings, a policy discontinuity comprises several treatments that cannot be separately identified using a standard regression discontinuity design. I propose a method for identifying distinct treatment components from a single discontinuity by exploiting the asymmetry between entities entering versus exiting treatment. Using data from New York City for 2009–13, I apply my strategy to the discontinuity associated with the introduction of class size caps—a widespread approach for reducing class sizes. I find that class size reductions increase student achievement, although these gains are counteracted by a newly hired teacher effect. The method has broad potential applicability.

Date: 2020
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