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The wild bootstrap, tamed at last

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  • Russell Davidson
  • Emmanuel Flachaire

Abstract

Various versions of the wild bootstrap are studied as applied to regression models with heteroskedastic errors. It is shown that some versions can be qualified as 'tamed', in the sense that the statistic bootstrapped is asymptotically independent of the distribution of the wild bootstrap DGP. This can, in one very specific case, lead to perfect bootstrap inference, and leads to substantial reduction in the error in the rejection probability of a bootstrap test much more generally. However, the version of the wild bootstrap with this desirable property does not benefit from the skewness correction afforded by the most popular version of the wild bootstrap in the literature. Edgeworth expansions and simulation experiments are used to show why this defect does not prevent the preferred version from having the smallest error in rejection probability in small and medium-sized samples. It is concluded that this preferred version should always be used in practice.

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File URL: http://eprints.lse.ac.uk/6560/
File Function: Open access version.
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Bibliographic Info

Paper provided by London School of Economics and Political Science, LSE Library in its series LSE Research Online Documents on Economics with number 6560.

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Length: 39 pages
Date of creation: Feb 2001
Date of revision:
Handle: RePEc:ehl:lserod:6560

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Related research

Keywords: Wild bootstrap; heteroskedasticity consistent covariance matrix estimator; size distortion.;

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References

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  1. FLACHAIRE, Emmanuel, 1999. "A better way to bootstrap pairs," CORE Discussion Papers 1999024, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
  2. Davidson, R. & Mackinnon, J.G., 1996. "The Size Distorsion of Bootstrap Tests," G.R.E.Q.A.M. 96a15, Universite Aix-Marseille III.
  3. MacKinnon, James G. & White, Halbert, 1985. "Some heteroskedasticity-consistent covariance matrix estimators with improved finite sample properties," Journal of Econometrics, Elsevier, vol. 29(3), pages 305-325, September.
  4. Russell Davidson & James G. MacKinnon, 1994. "Graphical Methods for Investigating the Size and Power of Hypothesis Tests," Working Papers 903, Queen's University, Department of Economics.
  5. Joel L. Horowitz, 1996. "Bootstrap Methods in Econometrics: Theory and Numerical Performance," Econometrics 9602009, EconWPA, revised 05 Mar 1996.
  6. repec:fth:louvco:9924 is not listed on IDEAS
  7. White, Halbert, 1980. "A Heteroskedasticity-Consistent Covariance Matrix Estimator and a Direct Test for Heteroskedasticity," Econometrica, Econometric Society, vol. 48(4), pages 817-38, May.
  8. Chesher, Andrew & Jewitt, Ian, 1987. "The Bias of a Heteroskedasticity Consistent Covariance Matrix Estimator," Econometrica, Econometric Society, vol. 55(5), pages 1217-22, September.
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