论文标题
基于引导的异方差鲁棒测试的可靠性如何？
How Reliable are Bootstrap-based Heteroskedasticity Robust Tests?
论文作者
论文摘要
我们开发了有关基于野生引导的杂型杂质性鲁棒测试的理论有限样本结果。特别是，这些结果提供了有效的诊断检查，可以用来清除对给定测试问题不可靠的测试，从而使它们实质上过度置换。这使我们能够在一项广泛的数值研究中评估各种基于野生引导的测试的可靠性。
We develop theoretical finite-sample results concerning the size of wild bootstrap-based heteroskedasticity robust tests in linear regression models. In particular, these results provide an efficient diagnostic check, which can be used to weed out tests that are unreliable for a given testing problem in the sense that they overreject substantially. This allows us to assess the reliability of a large variety of wild bootstrap-based tests in an extensive numerical study.
