This paper considers an empirical likelihood method to estimate the parameters of the quantile regression (QR) models … regression models. Our results are extensions of the previous results of Chen and Hall (1993) to the regression contexts. Monte … than the confidence regions that can be constructed from the smoothed bootstrap method recently suggested by Horowitz (1998). …

This paper considers the problem of choosing the number of bootstrap repetitions B for bootstrap standard errors … desired level of accuracy. Accuracy is measured by the percentage deviation of the bootstrap standard error estimate …, confidence interval endpoint(s), test's critical value, or test's p-value based on B bootstrap simulations from the corresponding …

This paper studies robustness of bootstrap inference methods for instrumental variable regression models. In particular …, we compare the uniform weight and implied probability bootstrap approximations for parameter hypothesis test statistics … by applying the breakdown point theory, which focuses on behaviors of the bootstrap quantiles when outliers take …

This paper studies robustness of bootstrap inference methods under moment conditions. In particular, we compare the … uniform weight and implied probability bootstraps by analyzing behaviors of the bootstrap quantiles when outliers take … arbitrarily large values, and derive the breakdown points for those bootstrap quantiles. The breakdown point properties …

to be asymptotically conservative. The power of GMS tests is compared to that of subsampling, m out of n bootstrap, and … to have asymptotic power that dominates that of subsampling, m out of n bootstrap, and PA tests. Subsampling and m out of … n bootstrap tests are shown to have asymptotic power that dominates that of PA tests. …

identified. For a specified class of test statistics, this paper establishes the uniform asymptotic validity of subsampling, m … out of n bootstrap, and "plug-in asymptotic" tests and confidence intervals for such parameters. Establishing uniform …

We propose a new method of testing stochastic dominance that improves on existing tests based on the standard bootstrap … or subsampling. The method admits prospects involving infinite as well as finite dimensional unknown parameters, so that … the variables are allowed to be residuals from nonparametric and semiparametric models. The proposed bootstrap tests have …

methods (i.e., the asymptotic distribution versus the bootstrap) have been proposed. In this paper, we compare these methods …

and second order stochastic dominance in the general k-prospect case. Our method is based on subsampling bootstrap. We …

-t, parametric bootstrap confidence intervals for Markov time series processes. These bounds show that the parametric bootstrap for … comparable to those obtained by the parametric and nonparametric bootstrap for iid data and are better than those obtained by the … block bootstrap for time series. Additional results are given for Wald-based confidence regions. The paper also shows that k …