model checking. A residual-based bootstrap method is provided and demonstrated as an effective way to approximate the …

compares very favorably to bootstrap bias-correction, both in terms of bias and mean squared error. In non-stationary models …

normality. Bootstrap inference can be expected to be more reliable, and appropriate bootstrap procedures are proposed. As an … enough for asymptotic and bootstrap inference to be almost identical, but that, in the twenty-first century, the bootstrap …

This paper evaluates bootstrap inference methods for quantile regression panel data models. We propose to construct … confidence intervals for the parameters of interest using percentile bootstrap with pairwise resampling. We study three different … bootstrapping procedures. First, the bootstrap samples are constructed by resampling only from cross-sectional units with …

compares very favorably to bootstrap bias-correction, both in terms of bias and mean squared error. In non-stationary models …

samples than the confidence regions that can be constructed from the smoothed bootstrap method recently suggested by Horowitz …

fixed link functions. In this paper we consider a bootstrap specification test that detects nonparametric deviations of the … link function. The bootstrap is used with the aim to find a more accurate distribution under the null than the normal … we show that the bootstrap is able to capture the negative bias and the skewness of the test statistic. It yields better …