HOW RELIABLE ARE BOOTSTRAP-BASED HETEROSKEDASTICITY ROBUST TESTS?
研究了线性回归模型中基于野自助法的异方差稳健检验的有限样本性质，提出一种诊断方法来判断检验是否可靠，并通过数值实验评估了多种检验的可靠性。
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.