Causal Impact Decomposition

Causal Impact Decomposition is a methodological framework within causal forecasting that identifies and quantifies the distinct contributions of individual causal factors to an observed outcome by isolating their temporal and structural effects from confounding influences.

61

Publications

6.4K

Citations

147

Authors

117

Institutions

Publications per year

2017–2026

25

Authors

147

  1. DR
    David Reiley

    University of California, Berkeley, United States

    3 publications · 83 citations

    3

    h-index

  2. RA
    Randall A. Lewis

    Google (United States), United States

    3 publications · 83 citations

    3

    h-index

  3. JE
    Joseph Engelberg

    University of California San Diego, United States

    2 publications · 1.2K citations

    2

    h-index

  4. CA
    Christopher A. Parsons

    University of Southern California, United States

    2 publications · 1.2K citations

    2

    h-index

  5. RS
    Ron Smith

    Birkbeck, University of London, United Kingdom

    2 publications · 40 citations

    2

    h-index

1–5 of 147

Venues

  1. SSRN Electronic Journal

    Repository · 6 publications · 274 citations

    6

    h-index

  2. RePEc: Research Papers in Economics

    Repository · 4 publications · 85 citations

    4

    h-index

  3. Epidemiology

    3 publications · 259 citations

    3

    h-index

  4. Sociological Methods & Research

    SMR · 2 publications · 78 citations

    2

    h-index

  5. 1

    h-index

1–5