Tail behaviours of multiple-regime threshold AR models with heavy-tailed innovations

Pan Jiazhu () and He Yali ()
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Pan Jiazhu: Department of Mathematics and Statistics, University of Strathclyde, Glasgow G1 1XH, UK
He Yali: School of Mathematics and Statistics, Yangtze Normal University, Chongqing 408100, China

Studies in Nonlinear Dynamics & Econometrics, 2023, vol. 27, issue 3, 377-395

Abstract: This paper studies the tail behaviours of the stationary distribution of multiple-regime threshold AR models with multiple heavy-tailed innovations. It is shown that the marginal tail probability has the same order as that of the innovation with the heaviest tail. Other new results in this paper include the geometric ergodicity and the tail dependence of TAR models with multiple heavy-tailed innovations.

Keywords: ergodicity; heavy-tailed distribution; tail probability; threshold AR model (search for similar items in EconPapers)
JEL-codes: C22 C32 (search for similar items in EconPapers)
Date: 2023
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DOI: 10.1515/snde-2020-0071

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