This paper proposes a bootstrap unit root test in models with GARCH(1,1) errors and establishes its asymptotic validity … under mild moment and distributional restrictions. While the proposed bootstrap test for a unit root shares the power … particular, the bootstrap procedure does not require explicit estimation of nuisance parameters that enter the distribution of …

one input and one output, and previous bootstrap methods proposed for inference have not been proven consistent, making … result is then used to prove that two different bootstrap procedures (one based on sub-sampling, the other based on smoothing …) provide consistent inference. The smooth bootstrap requires smoothing the irregularly-bounded density of inputs and outputs as …

The paper develops the bootstrap theory and extends the asymptotic theory of rank estimators, such as the Maximum Rank … asymptotic distributions can be consistently estimated by the nonparametric bootstrap. We investigate the accuracy of inference … based on the asymptotic approximation and the bootstrap, and provide bounds on the associated error. In the case of MRC and …

different bootstrap tests. In the context of static linear regression modelstwo of these are shown to have serious size and …

In this paper we analyse bootstrap procedures for systems cointegration tests with a prior adjustment for deterministic … the bootstrap test procedures are derived and their small sample properties are studied. The simulation study also …

In this paper, we introduce a method of generating bootstrap samples with unknown patterns of cross …-sectional/spatial dependence, which we call the spatial dependent wild bootstrap. This method is a spatial counterpart to the wild dependent … bootstrap of Shao (2010) and generates data by multiplying a vector of independently and identically distributed external …