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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.

Suggested Citation

  • 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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    10. Chong, Terence Tai-Leung & Lam, Tau-Hing & Yan, Isabel Kit-Ming, 2012. "Is the Chinese stock market really inefficient?," China Economic Review, Elsevier, vol. 23(1), pages 122-137.
    11. Arturo Lamadrid-Contreras & N.R. Ramírez-Rondán, 2018. "Panel Models with Two Threshold Variables: The Case of Financial Constraints," Working Papers 128, Peruvian Economic Association.
    12. Terence T.L. Chong & Isabel K. Yan, 2018. "Forecasting currency crises with threshold models," International Economics, CEPII research center, issue 156, pages 156-174.
    13. 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.
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    15. 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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    18. Jean-Marc Le Caillec, 2021. "Threshold autoregressive model blind identification based on array clustering," Post-Print hal-03210735, HAL.
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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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