Multi-cutoff RD designs with observations located at each cutoff: problems and solutions

Margherita Fort, Andrea Ichino, Enrico Rettore and Giulio Zanella

No 16974, CEPR Discussion Papers from Centre for Economic Policy Research

Abstract: 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: Regression discontinuity; Multiple cutoffs; Normalizing-and-pooling (search for similar items in EconPapers)
JEL-codes: C01 (search for similar items in EconPapers)
Date: 2022-01
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Working Paper: Multicutoff RD designs with observations located at each cutoff: problems and solutions (2022)
Working Paper: Multi-Cutoff RD Designs with Observations Located at Each Cutoff: Problems and Solutions (2022)
Working Paper: Multi-cutoff RD designs with observations located at each cutoff: problems and solutions (2022)
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