between nominal and actual finite sample significance levels. The use of the bootstrap overcomes this problem for general … approaches that lead to asymptotically pivotal test statistics. Power comparisons are made for bootstrap tests and modified …

This paper uses Monte Carlo simulation analysis to study the finite-sample behavior of bootstrap estimators and tests … tailored to handle heteroskedasticity. Our results show that weighted bootstrap methods can be successfully used to estimate … test and of Bartlett and Edgeworth-corrected tests. The bootstrap test was found to be robust against unfavorable …

The main contribution of this paper is a proof of the asymptotic validity of the application of the bootstrap to AR … establishing that a suitably constructed bootstrap estimator will have the same limit distribution as the least-squares estimator … robust standard errors or the bootstrap approximation of the distribution of autoregressive parameters. A simulation study …

results suggest that applied researchers are best off using nonparametric bootstrap intervals for impulse responses …

bootstrap tests are employed, assuming that the conditional means and variances of the model are correctly specified. The …

practical importance. For a simple case alternative bootstrap methods are proposed which provide correct results asymptotically. …

In this paper we compare Bartlett-corrected, bootstrap, and fast double bootstrap tests on maximum likelihood estimates … of cointegration parameters. The key result is that both the bootstrap and the Bartlett-corrected tests must be based on … sizes commonly available; the fast double bootstrap test minimizes size bias, while the Bartlett-corrected test is somehow …