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Hybrid bootstrap aided unit root testing

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  • C. Jentsch
  • J.-P. Kreiss
  • P. Mantalos
  • E. Paparoditis

Abstract

In this paper, we propose a hybrid bootstrap procedure for augmented Dickey-Fuller (ADF) tests for the presence of a unit root. This hybrid proposal combines a time domain parametric autoregressive fit to the data and a nonparametric correction applied in the frequency domain to capture features that are possibly not represented by the parametric model. It is known that considerable size and power problems can occur in small samples for unit root testing in the presence of an MA parameter using critical values of the asymptotic Dickey-Fuller distribution. The benefit of the sieve bootstrap in this situation has been investigated by Chang and Park (J Time Ser Anal 24:379–400, 2003 ). They showed asymptotic validity as well as substantial improvements for small sample sizes, but the actual sizes of their bootstrap tests were still quite far away from the nominal size. The finite sample performances of our procedure are extensively investigated through Monte Carlo simulations and compared to the sieve bootstrap approach. Regarding the size of the tests, our results show that the hybrid bootstrap remarkably outperforms the sieve bootstrap. Copyright Springer-Verlag 2012

Suggested Citation

  • C. Jentsch & J.-P. Kreiss & P. Mantalos & E. Paparoditis, 2012. "Hybrid bootstrap aided unit root testing," Computational Statistics, Springer, vol. 27(4), pages 779-797, December.
    • Handle: RePEc:spr:compst:v:27:y:2012:i:4:p:779-797
    DOI: 10.1007/s00180-011-0290-0
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    References listed on IDEAS

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    1. Anders Rygh Swensen, 2003. "Bootstrapping unit root tests for integrated processes," Journal of Time Series Analysis, Wiley Blackwell, vol. 24(1), pages 99-126, January.
    2. Yoosoon Chang & Joon Y. Park, 2003. "A Sieve Bootstrap For The Test Of A Unit Root," Journal of Time Series Analysis, Wiley Blackwell, vol. 24(4), pages 379-400, July.
    3. Dickey, David A & Fuller, Wayne A, 1981. "Likelihood Ratio Statistics for Autoregressive Time Series with a Unit Root," Econometrica, Econometric Society, vol. 49(4), pages 1057-1072, June.
    4. Schwert, G William, 2002. "Tests for Unit Roots: A Monte Carlo Investigation," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(1), pages 5-17, January.
    5. Jentsch, Carsten & Kreiss, Jens-Peter, 2010. "The multiple hybrid bootstrap -- Resampling multivariate linear processes," Journal of Multivariate Analysis, Elsevier, vol. 101(10), pages 2320-2345, November.
    6. Zacharias Psaradakis, 2001. "Bootstrap Tests for an Autoregressive Unit Root in the Presence of Weakly Dependent Errors," Journal of Time Series Analysis, Wiley Blackwell, vol. 22(5), pages 577-594, September.
    7. Kaizô I. BeltraTo & Peter Bloomfield, 1987. "Determining The Bandwidth Of A Kernel Spectrum Estimate," Journal of Time Series Analysis, Wiley Blackwell, vol. 8(1), pages 21-38, January.
    8. Efstathios Paparoditis & Dimitris N. Politis, 2003. "Residual-Based Block Bootstrap for Unit Root Testing," Econometrica, Econometric Society, vol. 71(3), pages 813-855, May.
    9. Hall, Peter & Horowitz, Joel L, 1996. "Bootstrap Critical Values for Tests Based on Generalized-Method-of-Moments Estimators," Econometrica, Econometric Society, vol. 64(4), pages 891-916, July.
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