Matching Estimators

Matching Estimators is a statistical method in nonparametric econometrics that belongs to the class of causal inference techniques, distinguished by its use of observed covariates to pair treated and control units in order to estimate treatment effects under the assumption of unconfoundedness.

429

Publications

79.6K

Citations

673

Authors

413

Institutions

Publications per year

2017–2026

84

Authors

673

  1. ML
    Michael Lechner

    University of St.Gallen, Switzerland

    19 publications · 2.3K citations

    15

    h-index

  2. AA
    Alberto Abadie

    Harvard University, United States

    13 publications · 7.4K citations

    12

    h-index

  3. GW
    Guido W. Imbens

    Stanford University, United States

    13 publications · 7.6K citations

    12

    h-index

  4. DB
    Donald B. Rubin

    Harvard University, United States

    11 publications · 2.5K citations

    11

    h-index

  5. JJ
    James J. Heckman

    University of Chicago, United States

    10 publications · 11.2K citations

    10

    h-index

1–5 of 673

Venues

  1. SSRN Electronic Journal

    Repository · 56 publications · 2.9K citations

    28

    h-index

  2. Journal of the American Statistical Association

    19 publications · 5.7K citations

    18

    h-index

  3. The Review of Economics and Statistics

    16 publications · 8.9K citations

    15

    h-index

  4. RePEc: Research Papers in Economics

    Repository · 18 publications · 3.3K citations

    14

    h-index

  5. Biometrics

    10 publications · 2.4K citations

    10

    h-index

1–5