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 …

-range dependencies are present only in the intraday volatility but not in the intraday returns. Finally, the robustness of these findings …

regression models in both randomized controlled trials and observational studies. In this paper, a unified GIMT framework is … regression. Although all GIMTs exhibited good level and power performance for the larger sample sizes, GIMT statistics with fewer …

This paper studies estimation and inference for linear quantile regression models with generated regressors. We suggest …

of the regression model. …

) inference with respect to possible endogeneity in the explanatory variables of the usual k-variate linear multiple regression …

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 …

rejection regions can be calculated by a simple parametric bootstrap procedure, when the sample size is small. The size and …