Bayesian Econometrics

Bayesian Econometrics is a branch of econometrics that applies Bayesian principles of probability and inference to the estimation and testing of economic models, distinguishing itself by incorporating prior information into the analysis of data.

2.3K

Publications

183K

Citations

3.1K

Authors

1.3K

Institutions

Publications per year

2017–2026

462

Authors

3.1K

  1. GK
    Gary Koop

    University of Strathclyde, United Kingdom

    53 publications · 3.4K citations

    34

    h-index

  2. AZ
    Arnold Zellner

    University of Chicago, United States

    34 publications · 6.1K citations

    27

    h-index

  3. JG
    John Geweke

    University of Technology Sydney, Australia

    30 publications · 5.4K citations

    24

    h-index

  4. MF
    Mark F. J. Steel

    University of Warwick, United Kingdom

    26 publications · 2.2K citations

    19

    h-index

  5. MV
    Mattias Villani

    Stockholm University, Sweden

    22 publications · 1.9K citations

    18

    h-index

1–5 of 3.1K

Venues

  1. Journal of Econometrics

    119 publications · 9.5K citations

    52

    h-index

  2. SSRN Electronic Journal

    Repository · 236 publications · 12.3K citations

    50

    h-index

  3. Journal of Applied Econometrics

    86 publications · 11K citations

    44

    h-index

  4. Journal of the American Statistical Association

    83 publications · 8.6K citations

    41

    h-index

  5. Journal of Business and Economic Statistics

    JBES · 99 publications · 9.3K citations

    40

    h-index

1–5