Multi-Cutoff Rd Designs with Observations Located at Each Cutoff: Problems and Solutions

50 Pages Posted: 19 May 2022

See all articles by Margherita Fort

Margherita Fort

University of Bologna; Ifo Institute, CESifo (Center for Economic Studies and Ifo Institute), Ifo Institute; IZA

Andrea Ichino

European University Institute

Enrico Rettore

University of Padua; IRVAPP

Giulio Zanella

University of Bologna

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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

JEL Classification: C01

Suggested Citation

Fort, Margherita and Ichino, Andrea and Rettore, Enrico and Zanella, Giulio, Multi-Cutoff Rd Designs with Observations Located at Each Cutoff: Problems and Solutions. IZA Discussion Paper No. 15051, Available at SSRN: https://ssrn.com/abstract=4114595 or http://dx.doi.org/10.2139/ssrn.4114595

Margherita Fort (Contact Author)

University of Bologna ( email )

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Ifo Institute, CESifo (Center for Economic Studies and Ifo Institute), Ifo Institute ( email )

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Andrea Ichino

European University Institute ( email )

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Enrico Rettore

University of Padua ( email )

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IRVAPP ( email )

Via Santa Croce 77
Trento, I-38122
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Giulio Zanella

University of Bologna ( email )

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Bologna, 40100
Italy

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