Bayesian inference for order determination of double threshold variables autoregressive models

Zheng Xiaobing, Xia Qiang () and Liang Rubing ()
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Zheng Xiaobing: College of Mathematics and Informatics, South China Agricultural University, Guangzhou 510642, China
Xia Qiang: College of Mathematics and Informatics, South China Agricultural University, Guangzhou 510642, China
Liang Rubing: College of Mathematics and Informatics, South China Agricultural University, Guangzhou 510642, China

Studies in Nonlinear Dynamics & Econometrics, 2023, vol. 27, issue 4, 567-587

Abstract: The reversible-jump Markov chain Monte Carlo (RJMCMC) algorithm can generate a jump Markov chain in the parameter space of different dimensions, and select a suitable model effectively. In this paper, when the order of the double threshold variables autoregressive (DT-AR) is unknown, the RJMCMC method is designed to identify the order of the DT-AR model in this paper. The simulation experiments and the real example show that the proposed method works well in identifying the order and estimating the parameters of the DT-AR model simultaneously.

Keywords: Bayesian inference; DT-AR model; MCMC algorithm; reversible-jump; unknown order (search for similar items in EconPapers)
JEL-codes: C11 C13 (search for similar items in EconPapers)
Date: 2023
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DOI: 10.1515/snde-2020-0096

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