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Theory and Applications of TAR Model with Two Threshold Variables

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  • Chen, Haiqiang
  • Chong, Terence Tai Leung
  • Bai, Jushan

Abstract

A growing body of threshold models has been developed over the past two decades to capture the nonlinear movement of financial time series. Most of these models, however, contain a single threshold variable only. In many empirical applications, models with two or more threshold variables are needed. This paper develops a new threshold autoregressive model which contains two threshold variables. A likelihood ratio test is proposed to determine the number of regimes in the model. The finite-sample performance of the estimators is evaluated and an empirical application is provided.

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  • Chen, Haiqiang & Chong, Terence Tai Leung & Bai, Jushan, 2012. "Theory and Applications of TAR Model with Two Threshold Variables," MPRA Paper 54527, University Library of Munich, Germany.
    • Handle: RePEc:pra:mprapa:54527
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    6. Xiaobing Zheng & Kun Liang & Qiang Xia & Dabin Zhang, 2022. "Best Subset Selection for Double-Threshold-Variable Autoregressive Moving-Average Models: The Bayesian Approach," Computational Economics, Springer;Society for Computational Economics, vol. 59(3), pages 1175-1201, March.
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    10. Zhang, Xinyu & Li, Dong & Tong, Howell, 2023. "On the least squares estimation of multiple-threshold-variable autoregressive models," LSE Research Online Documents on Economics 118377, London School of Economics and Political Science, LSE Library.
    11. Mo Zhou & Liang Peng & Rongmao Zhang, 2021. "Empirical likelihood test for the application of swqmele in fitting an arma‐garch model," Journal of Time Series Analysis, Wiley Blackwell, vol. 42(2), pages 222-239, March.
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    13. Seo, Myung Hwan & Shin, Yongcheol, 2016. "Dynamic panels with threshold effect and endogeneity," Journal of Econometrics, Elsevier, vol. 195(2), pages 169-186.
    14. Chong, Terence Tai Leung & Yan, Isabel K., 2014. "Estimating and Testing Threshold Regression Models with Multiple Threshold Variables," MPRA Paper 54732, University Library of Munich, Germany.
    15. Eugene Msizi Buthelezi & Phocenah Nyatanga, 2023. "Threshold of the CAPB That Can Be Attributed to Fiscal Consolidation Episodes in South Africa," Economies, MDPI, vol. 11(6), pages 1-26, May.
    16. Apergis, Nicholas & Eleftheriou, Sofia, 2016. "Gold returns: Do business cycle asymmetries matter? Evidence from an international country sample," Economic Modelling, Elsevier, vol. 57(C), pages 164-170.
    17. Aye, Goodness C. & Kotur, Lydia N. & Ayoola, Josephine B., 2024. "Beyond the threshold: Unraveling the effects of economic policy uncertainty on agricultural growth in Nigeria," IAAE 2024 Conference, August 2-7, 2024, New Delhi, India 344261, International Association of Agricultural Economists (IAAE).
    18. Terence T.L. Chong & Isabel K. Yan, 2018. "Forecasting currency crises with threshold models," International Economics, CEPII research center, issue 156, pages 156-174.
    19. Donayre, Luiggi & Panovska, Irina, 2018. "U.S. wage growth and nonlinearities: The roles of inflation and unemployment," Economic Modelling, Elsevier, vol. 68(C), pages 273-292.
    20. Alogoskoufis, George & Malliaris, A.G. & Stengos, Thanasis, 2023. "The scope and methodology of economic and financial asymmetries," The Journal of Economic Asymmetries, Elsevier, vol. 27(C).
    21. Monica Dudian & Mihaela Mosora & Cosmin Mosora & Stefanija Birova, 2017. "Oil Price and Economic Resilience. Romania’s Case," Sustainability, MDPI, vol. 9(2), pages 1-8, February.
    22. Jean-Marc Le Caillec, 2021. "Threshold autoregressive model blind identification based on array clustering," Post-Print hal-03210735, HAL.
    23. Ma, Tao & Zhou, Zhou & Abdulhai, Baher, 2015. "Nonlinear multivariate time–space threshold vector error correction model for short term traffic state prediction," Transportation Research Part B: Methodological, Elsevier, vol. 76(C), pages 27-47.

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    More about this item

    Keywords

    Threshold Autoregressive Model; Misspecification; Likelihood Ratio Test; Bootstrapping.;
    All these keywords.

    JEL classification:

    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models
    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes

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