Bai-perron Test

The Bai-Perron Test is a statistical method for identifying multiple structural breaks in a regression model by simultaneously estimating the number and location of breakpoints, distinguishing it from single-break tests through its ability to detect and accommodate more than one change point in the data.

35

Publications

3K

Citations

73

Authors

47

Institutions

Publications per year

2017–2026

13

Variants

Bai-perron Procedure

Authors

73

  1. PP
    Pierre Perrón

    Boston University, United States

    4 publications · 1.7K citations

    4

    h-index

  2. JB
    Jushan Bai

    Columbia University, United States

    3 publications · 1.5K citations

    3

    h-index

  3. MS
    Marcos Souto

    International Monetary Fund, United States

    2 publications · 39 citations

    2

    h-index

  4. CS
    Carlos Santos

    University of Oxford, United Kingdom

    2 publications · 25 citations

    2

    h-index

  5. TS
    Todd Sandler

    The University of Texas at Dallas, United States

    2 publications · 162 citations

    2

    h-index

1–5 of 73

Venues

  1. SSRN Electronic Journal

    Repository · 2 publications · 53 citations

    2

    h-index

  2. Sustainability

    2 publications · 56 citations

    2

    h-index

  3. Journal of Forecasting

    2 publications · 76 citations

    2

    h-index

  4. Economics Letters

    1 publications · 204 citations

    1

    h-index

  5. Macroeconomics and Finance in Emerging Market Economies

    MFEME · 1 publications · 38 citations

    1

    h-index

1–5