|This centre is a member of The LSE Research Laboratory [RLAB]: CASE | CVER | CEP | SERC | STICERD||Cookies?|
Paper No' DARP 058: | Full paper
Save Reference as: BibTeX File | EndNote Import File
Keywords: Wild bootstrap; heteroskedasticity consistent covariance matrix estimator, size distortion.
Is hard copy/paper copy available? YES - Paper Copy Still In Print.
This Paper is published under the following series: Distributional Analysis Research Programme
Share this page: Google Bookmarks | Facebook | Twitter
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.
Copyright © RLAB & LSE 2003 - 2017 | LSE, Houghton Street, London WC2A 2AE | Contact: RLAB | Site updated 18 December 2017