Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/189325 
Year of Publication: 
2006
Series/Report no.: 
Queen's Economics Department Working Paper No. 1044
Publisher: 
Queen's University, Department of Economics, Kingston (Ontario)
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 for asymptotic 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.
Subjects: 
bootstrap test
double bootstrap
Monte Carlo experiment
rejection frequency
fast double bootstrap
FDB
JEL: 
C12
C15
Document Type: 
Working Paper

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