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Improving The Reliability Of Bootstrap Tests With The Fast Double Bootstrap

James MacKinnon and Russell Davidson

No 1044, Working Paper from Economics Department, Queen's University

Abstract: We first propose two procedures for estimating the rejection probabilities of bootstrap tests in Monte Carlo experiments without actually computing a bootstrap test for each replication. These procedures are only about twice as expensive (per replication) as estimating rejection probabilities forasymptotic tests. We then propose a new procedure for computing bootstrap P values that will often be more accurate than ordinary ones. This "fast double bootstrap" is closely related to the double bootstrap, but it is far less computationally demanding. Simulation results for three different cases suggest that this procedure can be very useful in practice.

Keywords: bootstrap test; double bootstrap; Monte Carlo experiment; rejection frequency (search for similar items in EconPapers)
JEL-codes: C12 C15 (search for similar items in EconPapers)
Pages: 34 pages
Date: 2006-03
New Economics Papers: this item is included in nep-ecm
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (17)

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https://www.econ.queensu.ca/sites/econ.queensu.ca/files/qed_wp_1044.pdf First version 2006 (application/pdf)

Related works:
Journal Article: Improving the reliability of bootstrap tests with the fast double bootstrap (2007) Downloads
Working Paper: Improving the reliability of bootstrap tests with the fast double bootstrap (2006) Downloads
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