US状态中的锁定效应：一种人工反事实方法
Lockdown effects in US states: an artificial counterfactual approach
摘要：
我们采用了一种人为的反事实方法来评估封锁对美国一些州病例和死亡人数短期演变的影响。为此，我们探讨了美国各州采取封锁政策的不同时间，并将其分为治疗组和对照组。对于每一个被处理的状态，我们构建一个人工的反事实。平均而言，在非常短期内，如果不实施封锁政策，反事实的累积案件数量将增加两倍。
英文摘要：
We adopt an artificial counterfactual approach to assess the impact of lockdowns on the short-run evolution of the number of cases and deaths in some US states. To do so, we explore the different timing in which US states adopted lockdown policies, and divide them among treated and control groups. For each treated state, we construct an artificial counterfactual. On average, and in the very short-run, the counterfactual accumulated number of cases would be two times larger if lockdown policies were not implemented.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
