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 …

. They are better when selecting estimators that minimise mean squared error. However, using a simple bootstrap is at least …

This paper applies a novel bootstrap method, the kernel block bootstrap, to quasi-maximum likelihood estimation of …" bootstrap. We investigate the first order asymptotic properties of the kernel block bootstrap method for quasi …-maximum likelihood demonstrating, in particular, its consistency and the first-order asymptotic validity of the bootstrap approximation …

This article generalizes and extends the kernel block bootstrap (KBB) method of Parente and Smith (2018, 2021) to … moment conditions. KBB procedures that employ bootstrap distributions with generalised empirical likelihood implied … bootstrap distributions in the extant literature. Simulation experiments reveal that critical values arising from the empirical …