Kernel Weighting

Kernel Weighting is a nonparametric estimation technique in regression discontinuity designs that assigns differential weights to observations based on their proximity to the cutoff, using a kernel function to determine the weighting scheme.

87

Publications

6.8K

Citations

212

Authors

117

Institutions

Publications per year

2017–2026

36

Authors

212

  1. MP
    M. P. Wand

    UNSW Sydney, Australia

    3 publications · 1.5K citations

    3

    h-index

  2. NS
    Neil Shephard

    University of Oxford, United Kingdom

    3 publications · 1.6K citations

    3

    h-index

  3. FD
    Francisco de A.T. de Carvalho

    Universidade Federal de Pernambuco, Brazil

    3 publications · 95 citations

    3

    h-index

  4. MR
    Marcelo R.P. Ferreira

    Universidade Federal da Paraíba, Brazil

    3 publications · 95 citations

    3

    h-index

  5. LW
    Lingxiao Wang

    University of Maryland, College Park, United States

    2 publications · 57 citations

    2

    h-index

1–5 of 212

Venues

  1. arXiv (Cornell University)

    Repository · 5 publications · 64 citations

    5

    h-index

  2. 4

    h-index

  3. The Annals of Statistics

    4 publications · 1.4K citations

    4

    h-index

  4. SSRN Electronic Journal

    Repository · 3 publications · 179 citations

    3

    h-index

  5. Pattern Recognition

    3 publications · 62 citations

    3

    h-index

1–5