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Computationally Efficient Double Bootstrap Variance Estimation

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Author Info

  • Karlsson, Sune

    ()
    (Department of Economic Statistics)

  • Löthgren, Mickael

    ()
    (Department of Economic Statistics)

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.

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Bibliographic Info

Paper provided by Stockholm School of Economics in its series Working Paper Series in Economics and Finance with number 151.

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Length: 14 pages
Date of creation: Jan 1997
Date of revision:
Publication status: Published in Computational Statistics & Data Analysis, 2000, pages 237-247.
Handle: RePEc:hhs:hastef:0151

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Related research

Keywords: Bootstrap-t; confidence intervals; influence function; non-parametric bootstrap;

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  1. Karlsson, Sune & Löthgren, Mickael, 1997. "Computationally Efficient Double Bootstrap Variance Estimation," Working Paper Series in Economics and Finance, Stockholm School of Economics 151, Stockholm School of Economics.
  2. Vinod, H. D., 1995. "Double bootstrap for shrinkage estimators," Journal of Econometrics, Elsevier, Elsevier, vol. 68(2), pages 287-302, August.
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Cited by:
  1. Karlsson, Sune & Lothgren, Mickael, 2000. "Computationally efficient double bootstrap variance estimation," Computational Statistics & Data Analysis, Elsevier, Elsevier, vol. 33(3), pages 237-247, May.

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