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.

中文翻译：

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基于自举的异方差鲁棒测试有多可靠？

我们开发了关于线性回归模型中基于野生引导的异方差稳健性检验大小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，可用于剔除对于给定测试问题不可靠的测试，因为它们实质上过度拒绝。这使我们能够在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。