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Detecting structural changes under nonstationary volatility

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  • Wu, Jilin

Abstract

This paper shows that the U-statistic for moment condition stability proposed by Juhl and Xiao (2013) can be used to test against structural changes in regression coefficients under nonstationary volatility. We investigate the power property under the alternative, and prove that the test is consistent against single break, multiple breaks and smooth structural changes. Finally, we advocate using a bootstrap method to improve its size performance in finite samples.

Suggested Citation

  • Wu, Jilin, 2016. "Detecting structural changes under nonstationary volatility," Economics Letters, Elsevier, vol. 146(C), pages 151-154.
  • Handle: RePEc:eee:ecolet:v:146:y:2016:i:c:p:151-154
    DOI: 10.1016/j.econlet.2016.07.039
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    References listed on IDEAS

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    1. Alejandro Justiniano & Giorgio E. Primiceri, 2008. "The Time-Varying Volatility of Macroeconomic Fluctuations," American Economic Review, American Economic Association, vol. 98(3), pages 604-641, June.
    2. Jean-Yves Pitarakis, 2004. "Least squares estimation and tests of breaks in mean and variance under misspecification," Econometrics Journal, Royal Economic Society, vol. 7(1), pages 32-54, June.
    3. Jushan Bai & Pierre Perron, 1998. "Estimating and Testing Linear Models with Multiple Structural Changes," Econometrica, Econometric Society, vol. 66(1), pages 47-78, January.
    4. Thomas Mikosch & Cătălin Stărică, 2004. "Nonstationarities in Financial Time Series, the Long-Range Dependence, and the IGARCH Effects," The Review of Economics and Statistics, MIT Press, vol. 86(1), pages 378-390, February.
    5. Pierre Perron & Yohei Yamamoto & Jing Zhou, 2020. "Testing jointly for structural changes in the error variance and coefficients of a linear regression model," Quantitative Economics, Econometric Society, vol. 11(3), pages 1019-1057, July.
    6. Bin Chen & Yongmiao Hong, 2012. "Testing for Smooth Structural Changes in Time Series Models via Nonparametric Regression," Econometrica, Econometric Society, vol. 80(3), pages 1157-1183, May.
    7. Juhl, Ted & Xiao, Zhijie, 2013. "Nonparametric Tests Of Moment Condition Stability," Econometric Theory, Cambridge University Press, vol. 29(1), pages 90-114, February.
    8. Ke‐Li Xu, 2015. "Testing for structural change under non‐stationary variances," Econometrics Journal, Royal Economic Society, vol. 18(2), pages 274-305, June.
    9. Andrews, Donald W K & Ploberger, Werner, 1994. "Optimal Tests When a Nuisance Parameter Is Present Only under the Alternative," Econometrica, Econometric Society, vol. 62(6), pages 1383-1414, November.
    10. Dennis Kristensen, 2012. "Non‐parametric detection and estimation of structural change," Econometrics Journal, Royal Economic Society, vol. 15(3), pages 420-461, October.
    11. Ploberger, Werner & Kramer, Walter, 1992. "The CUSUM Test with OLS Residuals," Econometrica, Econometric Society, vol. 60(2), pages 271-285, March.
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    More about this item

    Keywords

    Structural changes; Nonstationary volatility; Wild bootstrap;
    All these keywords.

    JEL classification:

    • G10 - Financial Economics - - General Financial Markets - - - General (includes Measurement and Data)
    • C01 - Mathematical and Quantitative Methods - - General - - - Econometrics
    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading

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