The Numerical Performance of Fast Bootstrap Procedures
Computational Economics
The Numerical Performance of Fast Bootstrap Procedures
Computational Economics
Computational Statistics & Data Analysis
A bootstrap panel unit root test under cross-sectional dependence, with an application to PPP
Computational Statistics & Data Analysis
Computational Statistics & Data Analysis
Bootstrap and fast double bootstrap tests of cointegration rank with financial time series
Computational Statistics & Data Analysis
Homogeneity tests for several Poisson populations
Computational Statistics & Data Analysis
Modified fast double sieve bootstraps for ADF tests
Computational Statistics & Data Analysis
Computational Statistics & Data Analysis
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Two procedures are proposed for estimating the rejection probabilities (RPs) 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 RPs for asymptotic tests. Then a new procedure is proposed for computing bootstrap P values that will often be more accurate than ordinary ones. This ''fast double bootstrap'' (FDB) is closely related to the double bootstrap, but it is far less computationally demanding. Simulation results for three different cases suggest that the FDB can be very useful in practice.