Bayesian Production Models

Bayesian Production Models is a formal framework in production theory that integrates Bayesian inference to dynamically update production parameter estimates and decision-making under uncertainty, distinguishing itself from classical production models through its probabilistic learning mechanism and incorporation of prior knowledge.

85

Publications

3.7K

Citations

216

Authors

117

Institutions

Publications per year

2017–2026

22

Authors

216

  1. GK
    Gary Koop

    University of Strathclyde, United Kingdom

    7 publications · 332 citations

    7

    h-index

  2. MF
    Mark F. J. Steel

    University of Warwick, United Kingdom

    6 publications · 473 citations

    6

    h-index

  3. CF
    Carmen Fernández

    Universitat de València, Spain

    3 publications · 148 citations

    3

    h-index

  4. LR
    Leonardo Rey Vega

    Universidad de Buenos Aires, Argentina

    2 publications · 36 citations

    2

    h-index

  5. JB
    Jon Brodziak

    NOAA National Marine Fisheries Service Pacific Islands Fisheries Science Center, United States

    2 publications · 48 citations

    2

    h-index

1–5 of 216

Venues

  1. 4

    h-index

  2. Management Science

    3 publications · 289 citations

    3

    h-index

  3. Journal of Econometrics

    3 publications · 114 citations

    3

    h-index

  4. Journal of Agricultural Economics

    JAE · 3 publications · 108 citations

    3

    h-index

  5. RePEc: Research Papers in Economics

    Repository · 3 publications · 55 citations

    3

    h-index

1–5