Structural Break Modeling

Structural Break Modeling is a statistical methodology that identifies and adjusts for abrupt changes in the underlying structure of time series data, distinguishing itself by explicitly accounting for non-stationarities caused by exogenous shocks or regime shifts in the context of forecasting models.

934

Publications

63.9K

Citations

1.6K

Authors

926

Institutions

Publications per year

2017–2026

257

Authors

1.6K

  1. PP
    Pierre Perrón

    Boston University, United States

    14 publications · 8.7K citations

    13

    h-index

  2. PK
    Paresh Kumar Narayan

    Deakin University, Australia

    13 publications · 1.4K citations

    12

    h-index

  3. AT
    Allan Timmermann

    University of California San Diego, United States

    12 publications · 1.4K citations

    12

    h-index

  4. LA
    Luis A. Gil‐Alana

    Universidad de Navarra, Spain

    10 publications · 416 citations

    10

    h-index

  5. DF
    David F. Hendry

    University of Oxford, United Kingdom

    9 publications · 375 citations

    9

    h-index

1–5 of 1.6K

Venues

  1. SSRN Electronic Journal

    Repository · 76 publications · 3K citations

    28

    h-index

  2. Applied Economics

    40 publications · 1.6K citations

    26

    h-index

  3. Journal of Econometrics

    28 publications · 2K citations

    22

    h-index

  4. RePEc: Research Papers in Economics

    Repository · 43 publications · 1.7K citations

    20

    h-index

  5. Journal of Applied Econometrics

    17 publications · 3.3K citations

    16

    h-index

1–5