Computationally Efficient Double Bootstrap Variance Estimation

Sune Karlsson () and Mickael Löthgren ()
Additional contact information
Mickael Löthgren: Department of Economic Statistics, Postal: Stockholm School of Economics, Box 6501, 113 83 Stockholm, Sweden

No 151, SSE/EFI Working Paper Series in Economics and Finance from Stockholm School of Economics

Abstract: The double bootstrap provides a useful tool for bootstrapping approximately pivotal quantities by using an "inner" bootstrap loop to estimate the variance. When the estimators are computationally intensive, the double bootstrap may become infeasible. We propose the use of a new variance estimator for the nonparametric bootstrap which effectively removes the requirement to perform the inner loop of the double bootstrap. Simulation results indicate that the proposed estimator produce bootstrap-t confidence intervals with coverage accuracy which replicates the coverage accuracy for the standard double bootstrap.

Keywords: Bootstrap-t; confidence intervals; influence function; non-parametric bootstrap (search for similar items in EconPapers)
JEL-codes: C14 C15 (search for similar items in EconPapers)
Pages: 14 pages
Date: 1997-01
References: Add references at CitEc
Citations: View citations in EconPapers (1)

Published in Computational Statistics & Data Analysis, 2000, pages 237-247.

Downloads: (external link)
http://swopec.hhs.se/hastef/papers/hastef0151.code.zip Gauss code for paper (application/zip)
http://swopec.hhs.se/hastef/papers/hastef0151.readme.txt Read me file (text/plain)

Related works:
Journal Article: Computationally efficient double bootstrap variance estimation (2000)
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:hhs:hastef:0151

Access Statistics for this paper

More papers in SSE/EFI Working Paper Series in Economics and Finance from Stockholm School of Economics The Economic Research Institute, Stockholm School of Economics, P.O. Box 6501, 113 83 Stockholm, Sweden. Contact information at EDIRC.
Bibliographic data for series maintained by Helena Lundin ().