disturbances,where the heteroskedasticity and autocorrelation are of unknown form. A particular version of the wild bootstrap can … dependent wild bootstrap. Here, we extend this new method, and link it to the well-known HAC covariance estimator, in much the … same way as one can link the wild bootstrap to the HCCME. It works very well even with sample sizes smaller than 50, and …

shown that a bootstrap approximation to the sampling distribution of the weighted least squares estimate is valid, which …-sample properties of this new estimator as well as the improvements in performance realized by bootstrap confidence intervals. …

estimation, especially, when researchers use bootstrap to estimate standard errors, which may be wrong without a global estimator …

the same time they propose a statistically grounded bootstrap based two-stage estimator that eliminates the above …

investigated. The methods are based on a bootstrap algorithm that adjusts mean and skewness of the bootstrap distribution of the …