论文标题
IV的有效t比率推断
Valid t-ratio Inference for IV
论文作者
论文摘要
在单个IV模型中，当前的实践依赖于第一阶段F超过一定阈值（例如10）作为信任T比率推断的标准，即使这产生了抗保守测试。我们表明，真正的5％测试需要大于104.7的F。维持10作为阈值需要用3.43替换临界值1.96。我们重新检查57篇AER论文，发现校正推理导致最初假定具有统计学意义的结果的一半是无关紧要的。我们引入了更强大的测试，即TF过程，该过程提供了依赖F依赖的调整后的T-Ratio临界值。
In the single IV model, current practice relies on the first-stage F exceeding some threshold (e.g., 10) as a criterion for trusting t-ratio inferences, even though this yields an anti-conservative test. We show that a true 5 percent test instead requires an F greater than 104.7. Maintaining 10 as a threshold requires replacing the critical value 1.96 with 3.43. We re-examine 57 AER papers and find that corrected inference causes half of the initially presumed statistically significant results to be insignificant. We introduce a more powerful test, the tF procedure, which provides F-dependent adjusted t-ratio critical values.
