We provide evidence on the least biased ways to identify causal effects in situations where there are multiple outcomes that all depend on the same endogenous regressor and a reasonable but potentially contaminated instrumental variable that is available. Simulations provide suggestive evidence on the complementarity of instrumental variable (IV) and latent factor methods and how this complementarity depends on the number of outcome variables and the degree of contamination in the IV. We apply the causal inference methods to assess the impact of mental illness on work absenteeism and disability, using the National Comorbidity Survey Replication.

中文翻译：

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使用带有和不带有工具变量的潜在因子模型估算内源性治疗效果

我们提供的证据表明，在有多个结果都取决于相同的内生回归因子和可用但合理但可能受到污染的工具变量的情况下，使用最小偏差的方法来确定因果关系。模拟为工具变量（IV）和潜在因子方法的互补性以及这种互补性如何取决于结果变量的数量和IV中的污染程度提供了有益的证据。我们使用因果关系推断方法，使用“全国合并症调查复制”来评估精神疾病对工作旷工和残疾的影响。