In this paper we investigate bootstrap-based methods for bias-correcting the first-stage parameter estimates used in … some recently developed bootstrap implementations of the co-integration rank tests of Johansen (1996). In order to do so we … the corresponding parameter esti- mates taken across a large number of auxiliary bootstrap replications. A number of …

manner, we propose a model-based (semiparametric)bootstrap method to approximate critical values of the test and verify its …

In this paper, we propose a model-free bootstrap method for the empirical process under absolute regularity. More … precisely, consistency of an adapted version of the so-called dependent wild bootstrap, that was introduced by Shao (2010) and … simulation study shows that our method is competitive to standard block bootstrap methods in finite samples. …

The concept of the autoregressive (AR) sieve bootstrap is investigated for the case of spatial processes in Z2. This … procedure fits AR models of increasing order to the given data and, via resampling of the residuals, generates bootstrap … criterion which allows to decide whether the AR sieve bootstrap asymptotically works for a specific statistic of interest or not …

shown that a bootstrap approximation to the sampling distribution of the weighted least squares estimate is valid, which …-sample properties of this new estimator as well as the improvements in performance realized by bootstrap confidence intervals. …