prove the asymptotic validity of a wild bootstrap implementation. The proposed tests work for a null hypothesis of either no … determine the appropriate level of clustering. Simulations suggest that the bootstrap tests perform very well under the null …

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

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 …

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 …

bootstrap algorithm to implement the proposed test and show its asymptotic validity. The proposed test procedure can apply to …

under are highly nonstandard due to the inherent irregular natures of the problem, and then construct bootstrap critical …

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 …