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 …

proper 'INAR residuals' to formulate a valid model-based bootstrap scheme. In this paper, we propose a general INAR …-type bootstrap procedure. Based on mild regularity conditions and suitable meta assumptions, we prove bootstrap consistency of our … and semi-parametric implementations of the INAR bootstrap scheme. The latter approach is based on a semi …

We develop some asymptotic theory for applications of block bootstrap resampling schemes to multivariate integrated and … cointegrated time series. It is proved that a multivariate, continuous-path block bootstrap scheme applied to a full rank … block resampling scheme, the so-called residual based block bootstrap, is investigated and its validity for approximating …

parameter estimators and address bootstrap inference as well. Our results are important for correct inference on VAR statistics … also show that wild and pairwise bootstrap schemes fail in the presence of conditional heteroskedasticity if inference on … moments' structure of the error terms. In contrast, the residual-based moving block bootstrap results in asymptotically valid …

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 …