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

Authors

38

  1. RT
    Rocío Titiunik

    University of Michigan, United States

    5 publications · 781 citations

    5

    h-index

  2. MD
    Matias D. Cattaneo

    University of Michigan, United States

    5 publications · 781 citations

    5

    h-index

  3. LK
    Luke Keele

    University of Pennsylvania, United States

    3 publications · 251 citations

    3

    h-index

  4. GV
    Gonzalo Vázquez-Baré

    University of California, Santa Barbara, United States

    3 publications · 232 citations

    3

    h-index

  5. VC
    Vivian C. Wong

    University of Virginia, United States

    2 publications · 214 citations

    2

    h-index

1–5 of 38

Venues

  1. SSRN Electronic Journal

    Repository · 2 publications · 51 citations

    2

    h-index

  2. Journal of Econometrics

    2 publications · 129 citations

    2

    h-index

  3. Journal of Planning Education and Research

    JPER · 1 publications · 19 citations

    1

    h-index

  4. 1

    h-index

  5. 1

    h-index

1–5