SSE/EFI Working Paper Series in Economics and Finance
Computationally Efficient Double Bootstrap Variance Estimation
() and Mickael Löthgren
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; (follow links to similar papers)
JEL-Codes: C14; C15; (follow links to similar papers)
14 pages, January 1997
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- This paper is published as:
Karlsson, Sune and Mickael Löthgren, (2000), 'Computationally Efficient Double Bootstrap Variance Estimation', Computational Statistics & Data Analysis, Vol. 33, pages 237-247
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