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Size distortions of the wild bootstrapped HCCME-based LM test for serial correlation in the presence of asymmetric conditional heteroskedasticity

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  • Klaus Grobys

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Abstract

This paper investigates the size distortions of HCCME-based tests for serial correlation and the wild bootstrapped counterparts in the presence of asymmetric conditional heteroskedasticity. Thereby, asymmetric effects are allowed to enter the residual process of the dynamic regression model in both the GARCH parameterization and the innovation process. Monte Carlo evidence reported in this paper indicates that wild bootstrap versions of the LM test for serial correlation tend to overreject the null hypothesis, but the problem is generally not very serious. Copyright Springer-Verlag Berlin Heidelberg 2015

Suggested Citation

  • Klaus Grobys, 2015. "Size distortions of the wild bootstrapped HCCME-based LM test for serial correlation in the presence of asymmetric conditional heteroskedasticity," Empirical Economics, Springer, vol. 48(3), pages 1189-1202, May.
  • Handle: RePEc:spr:empeco:v:48:y:2015:i:3:p:1189-1202
    DOI: 10.1007/s00181-014-0817-7
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    References listed on IDEAS

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    1. Breusch, T S, 1978. "Testing for Autocorrelation in Dynamic Linear Models," Australian Economic Papers, Wiley Blackwell, vol. 17(31), pages 334-355, December.
    2. Goncalves, Silvia & Kilian, Lutz, 2004. "Bootstrapping autoregressions with conditional heteroskedasticity of unknown form," Journal of Econometrics, Elsevier, vol. 123(1), pages 89-120, November.
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    10. White, Halbert, 1980. "A Heteroskedasticity-Consistent Covariance Matrix Estimator and a Direct Test for Heteroskedasticity," Econometrica, Econometric Society, vol. 48(4), pages 817-838, May.
    11. Chesher, Andrew & Jewitt, Ian, 1987. "The Bias of a Heteroskedasticity Consistent Covariance Matrix Estimator," Econometrica, Econometric Society, vol. 55(5), pages 1217-1222, September.
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    More about this item

    Keywords

    Asymmetric heteroskedasticity; Serial correlation; Wild bootstrap; HCCME-based LM test; Simulation; C15; C32;

    JEL classification:

    • C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General
    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models

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