Multi-cutoff Designs
Multi-Cutoff Designs is a regression discontinuity design variant that employs multiple threshold values of a running variable to assign treatment and identify causal effects, distinguishing it from single-cutoff designs by enabling estimation across heterogeneous thresholds within a unified framework.
20
Publications
2.1K
Citations
38
Authors
27
Institutions
Publications per year
2017–2026
7
Variants
Multiple Cutoff Designs
20
Interpreting Regression Discontinuity Designs with Multiple Cutoffs
Matias D. Cattaneo, Luke Keele, Rocío Titiunik et al. · The Journal of Politics · 2016 · 207 citations
A Practical Guide to Regression Discontinuity
Robin Jacob, Pei Zhu, Marie‐Andrée Somers et al. · MDRC · 2012 · 200 citations
1–5 of 20
38
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University of California, Santa Barbara, United States
3 publications · 232 citations
3
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2
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1–5 of 38
27
Princeton University
Princeton, United States
4 h-index
8 publications
1.1K citations
University of Pennsylvania
Philadelphia, United States
2 h-index
2 publications
44 citations
University of California, Santa Barbara
Santa Barbara, United States
2 h-index
2 publications
25 citations
University of Michigan
Ann Arbor, United States
2 h-index
4 publications
640 citations
Northwestern University
Evanston, United States
2 h-index
5 publications
513 citations
University of California, Merced
Merced, United States
1 h-index
2 publications
170 citations

University of British Columbia
Vancouver, Canada
1 h-index
1 publications
79 citations
Dana-Farber/Harvard Cancer Center
Boston, United States
1 h-index
1 publications
79 citations
1–8 of 27
Repository · 2 publications · 51 citations
2
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2 publications · 129 citations
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JPER · 1 publications · 19 citations
1
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1 publications · 12 citations
1
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1 publications · 129 citations
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