Multi-Cutoff Rd Designs with Observations Located at Each Cutoff: Problems and Solutions
51 Pages Posted: 4 Feb 2022
Date Written: January 1, 2022
In RD designs with multiple cutoffs, the identification of an average causal effect across cutoffs may be problematic if a marginally exposed subject is located exactly at each cutoff. This occurs whenever a fixed number of treatment slots is allocated starting from the subject with the highest (or lowest) value of the score, until exhaustion. Exploiting the ``within’’ variability at each cutoff is the safest and likely efficient option. Alternative strategies exist, but they do not always guarantee identification of a meaningful causal effect and are less precise. To illustrate our findings, we revisit the study of Pop-Eleches and Urquiola (2013).
Keywords: multiple cutoffs, Normalizing-and-Pooling, Regression Discontinuity
JEL Classification: C01
Suggested Citation: Suggested Citation