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 …

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 …

The bootstrap is a convenient tool for calculating standard errors of the parameter estimates of complicated … econometric models. Unfortunately, the bootstrap can be very time-consuming. In a recent paper, Honoré and Hu (2017), we propose a … "Poor (Wo)man's Bootstrap" based on one-dimensional estimators. In this paper, we propose a modified, simpler method and …

bootstrap, which involve the new CRVEs, jackknife-based bootstrap data-generating processes, or both. Extensive simulation …

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

This paper shows how to bootstrap hypothesis tests in the context of the Parks (Efficient estimation of a system of … that the bootstrap outperforms Parks's top competitor. The Parks estimator has been a workhorse for the analysis of panel …