The effect of mental health on employment is a key policy question, but reliable causal estimates are elusive. Exploiting panel data and extending recent techniques using selection on observables to provide information on selection along unobservables, we estimate that transitioning into poor mental health leads to a 1.6% point reduction in the probability of employment; approximately 10% of the raw employment gap. Selection into mental health is almost entirely based on time-invariant characteristics, rendering fixed effects estimates unbiased in this context, meaning researchers no longer have to rely on the narrow local average treatment effects of most health/work IV studies.

中文翻译：

---

心理健康与就业：使用面板数据的边界方法*

心理健康对就业的影响是一个关键的政策问题，但可靠的因果估计难以捉摸。利用面板数据并扩展最近使用可观察对象选择的技术，以提供有关不可观察对象选择的信息，我们估计过渡到心理健康状况不佳会导致就业概率降低 1.6%；约占原始就业差距的 10%。选择心理健康几乎完全基于时间不变的特征，在这种情况下呈现固定效应估计无偏，这意味着研究人员不再需要依赖大多数健康/工作 IV 研究的狭窄局部平均治疗效果。