Model Robustness Testing

Model Robustness Testing is a methodological framework within revenue forecast evaluation that assesses the stability and reliability of a forecasting model under varying assumptions, data perturbations, or structural changes to determine its resilience to uncertainty and misspecification.

246

Publications

16K

Citations

671

Authors

391

Institutions

Publications per year

2017–2026

72

Authors

671

  1. RT
    Robert Tetlow

    Federal Reserve, United States

    4 publications · 78 citations

    4

    h-index

  2. FC
    Fabio Canova

    Universitat Pompeu Fabra, Spain

    3 publications · 60 citations

    3

    h-index

  3. JF
    Jon Faust

    Federal Reserve Board of Governors, United States

    3 publications · 858 citations

    3

    h-index

  4. BR
    Barbara Rossi

    Barcelona School of Economics, Spain

    3 publications · 100 citations

    3

    h-index

  5. CS
    Chengjin Sun

    Shanghai Jiao Tong University, China

    2 publications · 120 citations

    2

    h-index

1–5 of 671

Venues

  1. SSRN Electronic Journal

    Repository · 14 publications · 512 citations

    12

    h-index

  2. Journal of Econometrics

    7 publications · 1K citations

    7

    h-index

  3. 6

    h-index

  4. Economics Letters

    5 publications · 105 citations

    5

    h-index

  5. arXiv (Cornell University)

    Repository · 4 publications · 298 citations

    4

    h-index

1–5