We propose a generalization of the wild bootstrap of Wu (1986) and Liu (1988) based upon perturbing the scores of M …-estimators. This "score bootstrap" procedure avoids recomputing the estimator in each bootstrap iteration, making it substantially less … costly to compute than the conventional nonparametric bootstrap, particularly in complex nonlinear models. Despite this …

methods for inference. However, no formal justification for the use of the bootstrap has been provided. Here we show that the … bootstrap is in general not valid, even in the simple case with a single continuous covariate when the estimator is root … neighbor matching, the standard conditions for the bootstrap are not satisfied, leading the bootstrap variance to diverge from …

bootstrap procedure is proposed to test distributional hypotheses, such as equality of distributions, first-order stochastic …

total variation distance between a bootstrap distribution and the normal distribution parameterized by the point estimate … sample of recent empirical articles that use a bootstrap for inference, we find that the conventional normal approximation is …

bootstrap procedure for conducting inference about the conditional pricing errors as well as the shapes of the factor loading …

expansions and bootstrap validity are not tied to the weak instrument framework, but instead depends on which test statistic is … bootstrap method fails when instruments are weak, since it replaces parameters with inconsistent estimators. Contrary to this … notion, we provide a theoretical proof that guarantees the validity of the bootstrap for the score test, as well as the …

We examine the higher order properties of the wild bootstrap (Wu, 1986) in a linear regression model with stochastic … regressors. We find that the ability of the wild bootstrap to provide a higher order refinement is contingent upon whether the … errors are mean independent of the regressors or merely uncorrelated. In the latter case, the wild bootstrap may fail to …

models simultaneously rather than sequentially, and do not require reestimation of models as part of a bootstrap procedure …

-reject, however, with few (5-30) clusters. We investigate inference using cluster bootstrap-t procedures that provide asymptotic …