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Theory and Applications of TAR Model with Two Threshold Variables

Author

Listed:
  • Haiqiang Chen
  • Terence Chong
  • Jushan Bai

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 article 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

  • Haiqiang Chen & Terence Chong & Jushan Bai, 2012. "Theory and Applications of TAR Model with Two Threshold Variables," Econometric Reviews, Taylor & Francis Journals, vol. 31(2), pages 142-170.
  • Handle: RePEc:taf:emetrv:v:31:y:2012:i:2:p:142-170
    DOI: 10.1080/07474938.2011.607100
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    Cited by:

    1. Chen, Haiqiang & Li, Yingxing & Lin, Ming & Zhu, Yanli, 2018. "A Regime Shift Model with Nonparametric Switching Mechanism," IRTG 1792 Discussion Papers 2018-020, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    2. Stefan Avdjiev & Zheng Zeng, 2014. "Credit growth, monetary policy and economic activity in a three-regime TVAR model," Applied Economics, Taylor & Francis Journals, vol. 46(24), pages 2936-2951, August.
    3. 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.
    4. 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.
    5. 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.
    6. Haiqiang Chen & Terence Tai Leung Chong & Yingni She, 2014. "A principal component approach to measuring investor sentiment in China," Quantitative Finance, Taylor & Francis Journals, vol. 14(4), pages 573-579, April.
    7. Klingelhöfer, Jan & Sun, Rongrong, 2018. "China's regime-switching monetary policy," Economic Modelling, Elsevier, vol. 68(C), pages 32-40.
    8. Ni Shuxia & Xia Qiang & Liu Jinshan, 2018. "Bayesian Subset Selection for Two-Threshold Variable Autoregressive Models," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 22(4), pages 1-16, September.
    9. Xinyu Zhang & Dong Li & Howell Tong, 2024. "On the Least Squares Estimation of Multiple-Threshold-Variable Autoregressive Models," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 42(1), pages 215-228, January.
    10. 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.
    11. repec:wyi:journl:002214 is not listed on IDEAS
    12. Chong Terence Tai-Leung & Chen Haiqiang & Wong Tsz-Nga & Yan Isabel Kit-Ming, 2018. "Estimation and inference of threshold regression models with measurement errors," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 22(2), pages 1-16, April.
    13. 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.
    14. 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.
    15. 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.
    16. repec:ags:cfcp15:344261 is not listed on IDEAS
    17. Terence T.L. Chong & Isabel K. Yan, 2018. "Forecasting currency crises with threshold models," International Economics, CEPII research center, issue 156, pages 156-174.
    18. 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).
    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. Jan G. De Gooijer & Marcella Niglio, 2025. "Weighted forecasts from SETARs with single- and multiple thresholds," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 34(4), pages 663-686, September.
    21. 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).
    22. 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.
    23. Jean-Marc Le Caillec, 2021. "Threshold autoregressive model blind identification based on array clustering," Post-Print hal-03210735, HAL.
    24. Seo, Myung Hwan & Shin, Yongcheol, 2016. "Dynamic panels with threshold effect and endogeneity," Journal of Econometrics, Elsevier, vol. 195(2), pages 169-186.
    25. 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.

    More about this item

    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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