Instrumental Variables Estimation

Instrumental Variables Estimation is a statistical method used in econometrics and causal inference that belongs to the class of techniques designed to address endogeneity in regression models, distinguished by its use of instrumental variables—exogenous variables that are correlated with the explanatory variables but uncorrelated with the error term—to produce consistent parameter estimates.

3.2K

Publications

373.8K

Citations

5.6K

Authors

2K

Institutions

Publications per year

2017–2026

1K

Variants

Iv Estimation

Authors

5.6K

  1. JD
    Joshua D. Angrist

    Massachusetts Institute of Technology, United States

    49 publications · 25.2K citations

    37

    h-index

  2. JJ
    James J. Heckman

    University of Chicago, United States

    33 publications · 8.8K citations

    27

    h-index

  3. GW
    Guido W. Imbens

    Stanford University, United States

    30 publications · 17.1K citations

    25

    h-index

  4. DS
    Dylan S. Small

    University of Pennsylvania, United States

    25 publications · 2.3K citations

    19

    h-index

  5. WK
    Whitney K. Newey

    Massachusetts Institute of Technology, United States

    17 publications · 8.2K citations

    16

    h-index

1–5 of 5.6K

Venues

  1. SSRN Electronic Journal

    Repository · 348 publications · 16.3K citations

    60

    h-index

  2. Econometrica

    83 publications · 33.5K citations

    59

    h-index

  3. Journal of Econometrics

    96 publications · 32.4K citations

    49

    h-index

  4. RePEc: Research Papers in Economics

    Repository · 138 publications · 6.7K citations

    40

    h-index

  5. The Review of Economics and Statistics

    42 publications · 8.9K citations

    31

    h-index

1–5