A Method for Disentangling Multiple Treatments from a Regression Discontinuity Design

A-Tier
Journal: Journal of Labor Economics
Year: 2020
Volume: 38
Issue: 4
Pages: 1267 - 1311

Score contribution per author:

4.022 = (α=2.01 / 1 authors) × 2.0x A-tier

α: calibrated so average coauthorship-adjusted count equals average raw count

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.

Technical Details

RePEc Handle
repec:ucp:jlabec:doi:10.1086/706740
Journal Field
Labor
Author Count
1
Added to Database
2026-01-25