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 …

error distributions. These regression-based variable-addition tests are implemented using asymptotic and bootstrap critical …

to implement the tests using a modified wild bootstrap procedure. The paper theoretically justifies the proposed tests …

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

-to-noise ratios. We also present a bootstrap method that gives confidence interval estimates for (conditional) expectations of … “wrongly” skewed residuals, even when the variance of the inefficiency process is nonzero. Both our bagging and bootstrap …

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 …