functionals of kernel-type estimators (1 < p < ∞) and is easy to implement in general, mainly due to its recourse to the bootstrap … method. The bootstrap procedure is based on nonparametric bootstrap applied to kernel-based test statistics, with estimated … "contact sets". We provide regularity conditions under which the bootstrap test is asymptotically valid uniformly over a large …

combination of a bootstrap procedure and new selection algorithms. These methods yield tests that have correct asymptotic size and …

validity of a test based on block multiplier bootstrap in the case of dependent data under some general mixing conditions. …

validity of a test based on block multiplier bootstrap in the case of dependent data under some general mixing conditions. …

The bootstrap is a method for estimating the distribution of an estimator or test statistic by resampling one's data or … a model estimated from the data. Under conditions that hold in a wide variety of econometric applications, the bootstrap … bootstrap provides a way to carry out inference in certain settings where obtaining analytic distributional approximations is …