Bayesian Instrumental Variables

Bayesian Instrumental Variables is a statistical modeling framework within Bayesian econometrics that incorporates instrumental variables to address endogeneity, distinguished by its use of prior distributions and posterior inference to estimate causal effects in simultaneous equation models.

41

Publications

2K

Citations

76

Authors

54

Institutions

Publications per year

2017–2026

5

Authors

76

  1. AZ
    Arnold Zellner

    University of Chicago, United States

    4 publications · 340 citations

    4

    h-index

  2. LF
    Lennart F. Hoogerheide

    Erasmus University Rotterdam, Netherlands

    4 publications · 263 citations

    4

    h-index

  3. HK
    Herman K. van Dijk

    Erasmus University Rotterdam, Netherlands

    3 publications · 212 citations

    3

    h-index

  4. AR
    Andrés Ramírez Hassan

    Universidad EAFIT, Colombia

    3 publications · 81 citations

    3

    h-index

  5. MF
    Mark F. J. Steel

    University of Warwick, United Kingdom

    2 publications · 29 citations

    2

    h-index

1–5 of 76

Venues

  1. Journal of Econometrics

    9 publications · 634 citations

    9

    h-index

  2. SSRN Electronic Journal

    Repository · 3 publications · 135 citations

    3

    h-index

  3. Econometric Reviews

    2 publications · 52 citations

    2

    h-index

  4. Journal of Applied Econometrics

    2 publications · 77 citations

    2

    h-index

  5. RePEc: Research Papers in Economics

    Repository · 2 publications · 55 citations

    2

    h-index

1–5