European Business Schools Librarian's Group

SSE/EFI Working Paper Series in Economics and Finance,
Stockholm School of Economics

No 151: Computationally Efficient Double Bootstrap Variance Estimation

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

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

JEL-codes: C14; C15

14 pages, January 1997

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