This paper studies robustness of bootstrap inference methods for instrumental variable regression models. In particular …, we compare the uniform weight and implied probability bootstrap approximations for parameter hypothesis test statistics … by applying the breakdown point theory, which focuses on behaviors of the bootstrap quantiles when outliers take …

Bayesian literature, with many variations and some preference for two versions labelled pppost and pcpred. The bootstrap method … develop: an ancillary based p-value designated panc; a special version of the Bayesian pcpred; and a bootstrap based p … bootstrap would require a magnitude more in computation and would perhaps not be accessible. Examples are given to indicate the …

This paper studies robustness of bootstrap inference methods under moment conditions. In particular, we compare the … uniform weight and implied probability bootstraps by analyzing behaviors of the bootstrap quantiles when outliers take … arbitrarily large values, and derive the breakdown points for those bootstrap quantiles. The breakdown point properties …

correlation is proposed. It is based on the bootstrap procedure which is used to estimate confidence intervals of coherence …

component analysis, functional principal component regression, and bootstrap in functional principal component regression …

methods (i.e., the asymptotic distribution versus the bootstrap) have been proposed. In this paper, we compare these methods …

type statistic for testing the parametric form of the conditional variance. The finite sample properties of a bootstrap …

exploiting the dependence structure between the countries with a bootstrap approach. We use a sieve bootstrap approach to account …