Conditional Average Treatment Effect Estimation
Conditional Average Treatment Effect Estimation is a causal inference method that identifies the expected treatment effect for a unit conditional on its specific covariate values, distinguishing itself from average treatment effect estimation by enabling heterogeneous effect assessment across subpopulations defined by observed characteristics.
319
Publications
31.7K
Citations
833
Authors
454
Institutions
Publications per year
2017–2026
166
Variants
Cate Estimation
Parents
319
Semiparametric Difference-in-Differences Estimators
Alberto Abadie · The Review of Economic Studies · 2004 · 2.3K citations
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Massachusetts Institute of Technology, United States
7 publications · 499 citations
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454
Stanford University
Stanford, United States
19 h-index
45 publications
7.9K citations
University of California, Berkeley
Berkeley, United States
17 h-index
38 publications
7.5K citations
Harvard University
Cambridge, United States
15 h-index
33 publications
5.4K citations

Johns Hopkins University
Baltimore, United States
15 h-index
31 publications
2.1K citations

National Bureau of Economic Research
Cambridge, United States
13 h-index
21 publications
9.3K citations
University of Chicago
Chicago, United States
13 h-index
19 publications
3.1K citations
University of Washington
Seattle, United States
10 h-index
14 publications
804 citations
Yale University
New Haven, United States
9 h-index
10 publications
652 citations
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Repository · 24 publications · 609 citations
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14 publications · 779 citations
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Repository · 12 publications · 326 citations
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Repository · 8 publications · 1.7K citations
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JBES · 8 publications · 2K citations
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