This paper is concerned with bootstrap hypothesis testing in high dimensional linear regression models. Using a … theoretical framework recently introduced by Anatolyev (2012), we show that bootstrap F, LR and LM tests are asymptotically valid … the wild bootstrap in the presence of heteroskedasticity and to bootstrap methods for heavy tailed data. …

conditional heteroskedasticity. We show that the wild bootstrap provides convenient critical values for the considered OLS …-based statistics under both homoskedastic and conditionally heteroskedastic model errors. The wild bootstrap is easy to implement and … approximations. We prove further that the wild bootstrap retains its validity for inference within a system of pooled equations …

violation of such assumptions can lead to serious modelling aws. We propose here a bootstrap-corrected conditional moment …

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 …

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 an attempt to free bootstrap theory from the shackles of asymptotic considerations, this paper studies the … possibility of justifying, or validating, the bootstrap, not by letting the sample size tend to infinity, but by considering the … sequence of bootstrap P values obtained by iterating the bootstrap. The main idea of the paper is that, if this sequence …

alternative for obtaining confidence intervals based on the Maximum Entropy bootstrap explained in Vinod and Lopez … intervals than traditional, differencing and block bootstrap (BB) intervals. …

requirements that are not always obvious to the non-expert user. Bootstrap DEA is a significant development of the past decade …, which could be extended to test almost any hypothesis in bootstrap DEA. Moreover, it enhances the intuition behind bootstrap …

normality. Bootstrap inference can be expected to be more reliable, and appropriate bootstrap procedures are proposed. As an … enough for asymptotic and bootstrap inference to be almost identical, but that, in the twenty-first century, the bootstrap …