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A Consistent Test For Conditional Heteroskedasticity In Time-Series Regression Models

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  • Hsiao, Cheng
  • Li, Qi

Abstract

We show that the standard consistent test for testing the null of conditional homoskedasticity (against conditional heteroskedasticity) can be generalized to a time-series regression model with weakly dependent data and with generated regressors. The test statistic is shown to have an asymptotic normal distribution under the null hypothesis of conditional homoskedastic error. We also discuss extension of our test to the case of testing the null of a parametrically specified conditional variance. We advocate using a bootstrap method to overcome the issue of slow convergence of this test statistic to its limiting distribution.

Suggested Citation

  • Hsiao, Cheng & Li, Qi, 2001. "A Consistent Test For Conditional Heteroskedasticity In Time-Series Regression Models," Econometric Theory, Cambridge University Press, vol. 17(1), pages 188-221, February.
    • Handle: RePEc:cup:etheor:v:17:y:2001:i:01:p:188-221_17
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    Cited by:

    1. Juhl, Ted & Xiao, Zhijie, 2009. "Tests for changing mean with monotonic power," Journal of Econometrics, Elsevier, vol. 148(1), pages 14-24, January.
    2. Tianshun Yan & Liping Zhang, 2020. "A comparative study of several bootstrap-based tests for the volatility in continuous-time diffusion models," Portuguese Economic Journal, Springer;Instituto Superior de Economia e Gestao, vol. 19(1), pages 33-47, January.
    3. E Fe-Rodriguez & C D Orme, 2005. "The Asymptotic Equivalence of Kernel-based Nonparametric Conditional Moment Test Statistics," Economics Discussion Paper Series 0504, Economics, The University of Manchester.
    4. repec:hum:wpaper:sfb649dp2008-007 is not listed on IDEAS
    5. Jaeun Shin, 2005. "Stock Returns and Volatility in Emerging Stock Markets," International Journal of Business and Economics, School of Management Development, Feng Chia University, Taichung, Taiwan, vol. 4(1), pages 31-43, April.
    6. Henderson, Daniel J. & Sheehan, Alice, 2018. "Kernel-based testing with skewed and heavy-tailed data: Evidence from a nonparametric test for heteroskedasticity," Economics Letters, Elsevier, vol. 172(C), pages 8-11.
    7. E. Fe-Rodríguez & C. Orme, 2006. "On the sensitivity of Kernel-based Conditional Moment Tests to Unconsidered Local Alternatives," Economics Discussion Paper Series 0606, Economics, The University of Manchester.
    8. Jeong, Kiho & Härdle, Wolfgang Karl, 2008. "A consistent nonparametric test for causality in quantile," SFB 649 Discussion Papers 2008-007, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    9. Juhl, Ted & Xiao, Zhijie, 2005. "A nonparametric test for changing trends," Journal of Econometrics, Elsevier, vol. 127(2), pages 179-199, August.
    10. Grobys, Klaus, 2023. "A multifractal model of asset (in)variances," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 85(C).

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