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Dependent wild bootstrap for the empirical process

Author

Listed:
  • Doukhan, Paul
  • Lang, Gabriel
  • Leucht, Anne
  • Neumann, Michael H.

Abstract

In this paper, we propose a model-free bootstrap method for the empirical process under absolute regularity. More precisely, consistency of an adapted version of the so-called dependent wild bootstrap, that was introduced by Shao (2010) and is very easy to implement, is proved under minimal conditions on the tuning parameter of the procedure. We apply our results to construct confidence intervals for unknown parameters and to approximate critical values for statistical tests. A simulation study shows that our method is competitive to standard block bootstrap methods in finite samples.

Suggested Citation

  • Doukhan, Paul & Lang, Gabriel & Leucht, Anne & Neumann, Michael H., 2014. "Dependent wild bootstrap for the empirical process," Working Papers 35246, University of Mannheim, Department of Economics.
    • Handle: RePEc:mnh:wpaper:35246
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    References listed on IDEAS

    as
    1. Leucht, Anne & Neumann, Michael H., 2013. "Dependent wild bootstrap for degenerate U- and V-statistics," Journal of Multivariate Analysis, Elsevier, vol. 117(C), pages 257-280.
    2. Shao, Xiaofeng, 2010. "The Dependent Wild Bootstrap," Journal of the American Statistical Association, American Statistical Association, vol. 105(489), pages 218-235.
    3. Sharipov, Olimjon Sh. & Wendler, Martin, 2013. "Normal limits, nonnormal limits, and the bootstrap for quantiles of dependent data," Statistics & Probability Letters, Elsevier, vol. 83(4), pages 1028-1035.
    4. Doukhan, Paul & Louhichi, Sana, 1999. "A new weak dependence condition and applications to moment inequalities," Stochastic Processes and their Applications, Elsevier, vol. 84(2), pages 313-342, December.
    5. Dehling, Herold & Wendler, Martin, 2010. "Central limit theorem and the bootstrap for U-statistics of strongly mixing data," Journal of Multivariate Analysis, Elsevier, vol. 101(1), pages 126-137, January.
    6. Shao, Xiaofeng, 2011. "A bootstrap-assisted spectral test of white noise under unknown dependence," Journal of Econometrics, Elsevier, vol. 162(2), pages 213-224, June.
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    Cited by:

    1. Smeekes, S. & Urbain, J.R.Y.J., 2014. "A multivariate invariance principle for modified wild bootstrap methods with an application to unit root testing," Research Memorandum 008, Maastricht University, Graduate School of Business and Economics (GSBE).

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    More about this item

    Keywords

    Absolute regularity ; bootstrap ; empirical process ; time series ; V -statistics ; quantiles ; Kolmogorov-Smirnov test;
    All these keywords.

    JEL classification:

    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General

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