 Wild Bootstrap of the Sample Mean in the Infinite Variance CaseGiuseppe Cavaliere, Iliyan Georgiev and Robert Taylor Econometric Reviews, 2013, vol. 32, issue 2, 204-219 Abstract: It is well known that the standard independent, identically distributed (iid) bootstrap of the mean is inconsistent in a location model with infinite variance (α-stable) innovations. This occurs because the bootstrap distribution of a normalised sum of infinite variance random variables tends to a random distribution. Consistent bootstrap algorithms based on subsampling methods have been proposed but have the drawback that they deliver much wider confidence sets than those generated by the iid bootstrap owing to the fact that they eliminate the dependence of the bootstrap distribution on the sample extremes. In this paper we propose sufficient conditions that allow a simple modification of the bootstrap (Wu, 1986) to be consistent (in a conditional sense) yet to also reproduce the narrower confidence sets of the iid bootstrap. Numerical results demonstrate that our proposed bootstrap method works very well in practice delivering coverage rates very close to the nominal level and significantly narrower confidence sets than other consistent methods. Date: 2013 Downloads: (external link) Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:taf:emetrv:v:32:y:2013:i:2:p:204-219 Ordering information: This journal article can be ordered from DOI: 10.1080/07474938.2012.690660 Access Statistics for this article Econometric Reviews is currently edited by Dr. Essie Maasoumi More articles in Econometric Reviews from Taylor & Francis Journals |
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