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

Arbeitspapier

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).

Angaben zum Objekt

• Sprache: Englisch

Verweise und Beziehungen

• Erschienen in: Series: IZA Discussion Papers ; No. 15051

Klassifikation und Themen

• Klassifikation: Wirtschaft ; Econometrics
• Thema: regression discontinuity ; multiple cutoffs ; normalizing-and-pooling

Beteiligte, Orts- und Zeitangaben

• Ereignis: Geistige Schöpfung
• (wer): Fort, Margherita ; Ichino, Andrea ; Rettore, Enrico ; Zanella, Giulio
• Ereignis: Veröffentlichung
• (wer): Institute of Labor Economics (IZA)
• (wo): Bonn
• (wann): 2022

Weitere Informationen

• Handle: http://hdl.handle.net/10419/250712
• Letzte Aktualisierung: 10.03.2025, 11:41 MEZ