different bootstrap tests. In the context of static linear regression modelstwo of these are shown to have serious size and …

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 …

coverage for small sample sizes, a simple bootstrap procedure is designed based on the leading term of the Bahadur … demonstrated that the bootstrap procedure considerably outperforms the asymptotic bands in terms of coverage accuracy. Finally, the … bootstrap confidence corridors are used to study the efficacy of the National Supported Work Demonstration, which is a …

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 …

In this paper, we propose an algorithmic approach based on resampling and bootstrap techniques to measuring the …

bootstrap approximation of the squared error of prediction of Shao (1996) to factor-augmented regressions. We show that this …