Multiple Instrumental Variables

Multiple Instrumental Variables is a methodological framework in econometrics and causal inference that extends the instrumental variables approach by employing more than one instrument to identify and estimate causal effects, thereby improving efficiency and enabling tests of instrument validity under stronger assumptions.

49

Publications

8.8K

Citations

114

Authors

96

Institutions

Publications per year

2017–2026

18

Authors

114

  1. ES
    Eleanor Sanderson

    University of Bristol, United Kingdom

    4 publications · 848 citations

    4

    h-index

  2. AT
    Alexander Torgovitsky

    University of Chicago, United States

    4 publications · 183 citations

    4

    h-index

  3. MM
    Magne Mogstad

    University of Chicago, United States

    4 publications · 183 citations

    4

    h-index

  4. CR
    Christopher R. Walters

    University of California, Berkeley, United States

    3 publications · 166 citations

    3

    h-index

  5. SB
    Stephen Burgess

    University of Cambridge, United Kingdom

    3 publications · 1.7K citations

    3

    h-index

1–5 of 114

Venues

  1. Journal of Econometrics

    3 publications · 758 citations

    3

    h-index

  2. SSRN Electronic Journal

    Repository · 3 publications · 107 citations

    3

    h-index

  3. Statistics in Medicine

    3 publications · 1.7K citations

    3

    h-index

  4. Econometrica

    2 publications · 3.4K citations

    2

    h-index

  5. Journal of Labor Economics

    JOLE · 2 publications · 914 citations

    2

    h-index

1–5