Multi-cutoff RD designs with observations located at each cutoff: problems and solutions
Enrico Rettore () and
No 278, "Marco Fanno" Working Papers from Dipartimento di Scienze Economiche "Marco Fanno"
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)
Pages: 49 pages
New Economics Papers: this item is included in nep-ecm
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (4) Track citations by RSS feed
Downloads: (external link)
Working Paper: Multi-cutoff RD designs with observations located at each cutoff: problems and solutions (2022)
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)
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
Persistent link: https://EconPapers.repec.org/RePEc:pad:wpaper:0278
Access Statistics for this paper
More papers in "Marco Fanno" Working Papers from Dipartimento di Scienze Economiche "Marco Fanno" Contact information at EDIRC.
Bibliographic data for series maintained by Raffaele Dei Campielisi ().