Inference via Kernel Smoothing of Bootstrap P Values

Jeffrey Racine and James MacKinnon

No 273530, Queen's Economics Department Working Papers from Queen's University - Department of Economics

Abstract: Resampling methods such as the bootstrap are routinely used to esti- mate the ¯nite-sample null distributions of a range of test statistics. We present a simple and tractable way to perform classical hypothesis tests based upon a kernel estimate of the CDF of the bootstrap statistics. This approach has a number of appealing features: i) it can perform well when the number of bootstraps is ex- tremely small, ii) it is approximately exact, and iii) it can yield substantial power gains relative to the conventional approach. The proposed approach is likely to be useful when the statistic being bootstrapped is computationally expensive.

Keywords: Financial; Economics (search for similar items in EconPapers)
Pages: 17
Date: 2006-03
References: Add references at CitEc
Citations:

Downloads: (external link)
https://ageconsearch.umn.edu/record/273530/files/qed_wp_1054.pdf (application/pdf)

Related works:
Journal Article: Inference via kernel smoothing of bootstrap P values (2007)
Working Paper: Inference Via Kernel Smoothing Of Bootstrap P Values (2006)
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:ags:quedwp:273530

DOI: 10.22004/ag.econ.273530

Access Statistics for this paper

More papers in Queen's Economics Department Working Papers from Queen's University - Department of Economics Contact information at EDIRC.
Bibliographic data for series maintained by AgEcon Search ().