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Testing for Structural Change of Predictive Regression Model to Threshold Predictive Regression Model

Author

Listed:
  • Fukang Zhu

    (School of Mathematics, Jilin University, Changchun, Jilin 130012, China)

  • Mengya Liu

    (School of Mathematics, Jilin University, Changchun, Jilin 130012, China)

  • Shiqing Ling

    (Department of Mathematics, Hong Kong University of Science and Technology, Hong Kong, China)

  • Zongwu Cai

    (Department of Economics, The University of Kansas, Lawrence, KS 66045, USA)

Abstract
This paper investigates two test statistics for structural changes and thresh- olds in predictive regression models. The generalized likelihood ratio (GLR) test is proposed for the stationary predictor and the generalized F test is suggested for the unit root predictor. Under the null hypothesis of no structural change and threshold, it is shown that the GLR test statistic converges to a function of a centered Gaussian process, and the generalized F test statistic converges to a function of Brownian motions. A Bootstrap method is proposed to obtain the critical values of test statistics. Simulation studies and a real example are given to assess the performances of the tests.

Suggested Citation

  • Fukang Zhu & Mengya Liu & Shiqing Ling & Zongwu Cai, 2020. "Testing for Structural Change of Predictive Regression Model to Threshold Predictive Regression Model," WORKING PAPERS SERIES IN THEORETICAL AND APPLIED ECONOMICS 202021, University of Kansas, Department of Economics, revised Dec 2020.
    • Handle: RePEc:kan:wpaper:202021
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    Download full text from publisher

    File URL: http://www2.ku.edu/~kuwpaper/2020Papers/202021.pdf
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    References listed on IDEAS

    as
    1. Ivo Welch & Amit Goyal, 2008. "A Comprehensive Look at The Empirical Performance of Equity Premium Prediction," The Review of Financial Studies, Society for Financial Studies, vol. 21(4), pages 1455-1508, July.
    2. Cai, Zongwu & Wang, Yunfei, 2014. "Testing predictive regression models with nonstationary regressors," Journal of Econometrics, Elsevier, vol. 178(P1), pages 4-14.
    3. Giuseppe Cavaliere & Iliyan Georgiev, 2020. "Inference Under Random Limit Bootstrap Measures," Econometrica, Econometric Society, vol. 88(6), pages 2547-2574, November.
    4. Fukang Zhu & Zongwu Cai & Liang Peng, 2014. "Predictive regressions for macroeconomic data," Papers 1404.7642, arXiv.org.
    5. Phillips, Peter C B, 1988. "Regression Theory for Near-Integrated Time Series," Econometrica, Econometric Society, vol. 56(5), pages 1021-1043, September.
    6. Iliyan Georgiev & David I. Harvey & Stephen J. Leybourne & A. M. Robert Taylor, 2019. "A Bootstrap Stationarity Test for Predictive Regression Invalidity," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 37(3), pages 528-541, July.
    7. Georgiev, Iliyan & Harvey, David I. & Leybourne, Stephen J. & Taylor, A.M. Robert, 2018. "Testing for parameter instability in predictive regression models," Journal of Econometrics, Elsevier, vol. 204(1), pages 101-118.
    8. Hansen, Bruce E, 1996. "Inference When a Nuisance Parameter Is Not Identified under the Null Hypothesis," Econometrica, Econometric Society, vol. 64(2), pages 413-430, March.
    9. Michael Jansson & Marcelo J. Moreira, 2006. "Optimal Inference in Regression Models with Nearly Integrated Regressors," Econometrica, Econometric Society, vol. 74(3), pages 681-714, May.
    10. Jean-Yves Pitarakis, 2017. "A Simple Approach for Diagnosing Instabilities in Predictive Regressions," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 79(5), pages 851-874, October.
    11. Zongwu Cai & Ying Fang & Ming Lin & Jia Su, 2019. "Inferences for a Partially Varying Coefficient Model With Endogenous Regressors," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 37(1), pages 158-170, January.
    12. Jushan Bai & Pierre Perron, 1998. "Estimating and Testing Linear Models with Multiple Structural Changes," Econometrica, Econometric Society, vol. 66(1), pages 47-78, January.
    13. Cai, Zongwu & Wang, Yunfei & Wang, Yonggang, 2015. "Testing Instability In A Predictive Regression Model With Nonstationary Regressors," Econometric Theory, Cambridge University Press, vol. 31(5), pages 953-980, October.
    14. Chen, Haiqiang, 2015. "Robust Estimation And Inference For Threshold Models With Integrated Regressors," Econometric Theory, Cambridge University Press, vol. 31(4), pages 778-810, August.
    15. István Berkes & Lajos Horváth & Shiqing Ling & Johannes Schauer, 2011. "Testing for structural change of AR model to threshold AR model," Journal of Time Series Analysis, Wiley Blackwell, vol. 32(5), pages 547-565, September.
    16. Zongwu Cai & Haiqiang Chen & Xiaosai Liao, 2020. "A New Robust Inference for Predictive Quantile Regression," WORKING PAPERS SERIES IN THEORETICAL AND APPLIED ECONOMICS 202002, University of Kansas, Department of Economics, revised Feb 2020.
    17. Mehmet Caner & Bruce E. Hansen, 2001. "Threshold Autoregression with a Unit Root," Econometrica, Econometric Society, vol. 69(6), pages 1555-1596, November.
    18. Jesùs Gonzalo & Jean-Yves Pitarakis, 2017. "Inferring the Predictability Induced by a Persistent Regressor in a Predictive Threshold Model," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 35(2), pages 202-217, April.
    19. Andrews, Donald W K, 1993. "Tests for Parameter Instability and Structural Change with Unknown Change Point," Econometrica, Econometric Society, vol. 61(4), pages 821-856, July.
    20. repec:taf:jnlbes:v:30:y:2012:i:2:p:229-241 is not listed on IDEAS
    21. Bingduo Yang & Xiaohui Liu & Liang Peng & Zongwu Cai, 2021. "Unified Tests for a Dynamic Predictive Regression," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 39(3), pages 684-699, July.
    22. Breitung, Jörg & Demetrescu, Matei, 2015. "Instrumental variable and variable addition based inference in predictive regressions," Journal of Econometrics, Elsevier, vol. 187(1), pages 358-375.
    23. Hansen, Bruce E., 2000. "Testing for structural change in conditional models," Journal of Econometrics, Elsevier, vol. 97(1), pages 93-115, July.
    24. Alexandros Kostakis & Tassos Magdalinos & Michalis P. Stamatogiannis, 2015. "Robust Econometric Inference for Stock Return Predictability," The Review of Financial Studies, Society for Financial Studies, vol. 28(5), pages 1506-1553.
    25. Ke Zhu & Shiqing Ling, 2012. "Likelihood ratio tests for the structural change of an AR(p) model to a Threshold AR(p) model," Journal of Time Series Analysis, Wiley Blackwell, vol. 33(2), pages 223-232, March.
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    More about this item

    Keywords

    Bootstrap method; Generalized F-test; Generalized likelihood ratio test; Predictive regression; Structural change; Threshold model.;
    All these keywords.

    JEL classification:

    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C58 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Financial Econometrics
    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates

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