characterize their quantile breakdown point. For the moving block bootstrap and the subsampling, we find a very low quantile …We study the robustness of block resampling procedures for time series. We first derive a set of formulas to … breakdown point. A similar robustness problem arises in relation to data-driven methods for selecting the block size in …

This paper considers an empirical likelihood method to estimate the parameters of the quantile regression (QR) models … regression models. Our results are extensions of the previous results of Chen and Hall (1993) to the regression contexts. Monte … than the confidence regions that can be constructed from the smoothed bootstrap method recently suggested by Horowitz (1998) …

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 …

This paper shows how to bootstrap hypothesis tests in the context of the Parks (Efficient estimation of a system of … regression equations when disturbances are both serially and contemporaneously correlated 1967) estimator. It then demonstrates … that the bootstrap outperforms Parks's top competitor. The Parks estimator has been a workhorse for the analysis of panel …

This paper shows how to bootstrap hypothesis tests in the context of the Parks’s (1967) Feasible Generalized Least … Squares estimator. It then demonstrates that the bootstrap outperforms FGLS(Parks)’s top competitor. The FGLS(Parks) estimator … has been a workhorse for the analysis of panel data and seemingly unrelated regression equation systems because it allows …