Threshold Autoregressive Models

Threshold Autoregressive Models is a class of nonlinear time series models that extends autoregressive processes by introducing regime-switching behavior governed by threshold values of past observations, allowing the model dynamics to change based on whether a specified threshold variable falls within distinct intervals.

421

Publications

33.5K

Citations

668

Authors

438

Institutions

Publications per year

2017–2026

63

Authors

668

  1. HT
    Howell Tong

    London School of Economics and Political Science, United Kingdom

    11 publications · 739 citations

    11

    h-index

  2. KC
    Kung‐Sik Chan

    University of Iowa, United States

    11 publications · 2.6K citations

    11

    h-index

  3. BE
    Bruce E. Hansen

    University of Wisconsin–Madison, United States

    11 publications · 7.3K citations

    10

    h-index

  4. SL
    Shiqing Ling

    Hong Kong University of Science and Technology, Hong Kong SAR China

    10 publications · 674 citations

    10

    h-index

  5. SP
    Simon Potter

    Federal Reserve Bank of New York, United States

    9 publications · 625 citations

    9

    h-index

1–5 of 668

Venues

  1. Journal of Time Series Analysis

    26 publications · 1.9K citations

    19

    h-index

  2. 16

    h-index

  3. Journal of Business and Economic Statistics

    JBES · 15 publications · 2.3K citations

    14

    h-index

  4. RePEc: Research Papers in Economics

    Repository · 20 publications · 615 citations

    14

    h-index

  5. SSRN Electronic Journal

    Repository · 18 publications · 378 citations

    13

    h-index

1–5