We examine the impact of early state and local COVID-19 policies to encourage social distancing. Outcomes are daily foot traffic at establishments spanning ten key industries, across which transmission risk varies substantially. Policies include state of emergency declarations, blunt general restrictions such as stay-at-home (SAH) orders, and targeted rules such as restrictions on bars, restaurants, entertainment venues, and schools. Exploiting variation in the timing of policies in difference-in-difference models, we show that much of the decline in foot traffic early in the pandemic was due to private precautionary behavior. SAH orders explain almost none of the foot traffic decline in industries with high risk of virus transmission, but they do explain a substantial share of the decline in moderate- to low-risk industries such as outdoor sports and visits to parks. Targeted restrictions tend to impact intended industries, as well as complementary ones. We show that the impact of targeted restrictions is largest in counties with no SAH restrictions, suggesting that better targeting of public restrictions can have important efficiency gains.

我们研究了早期州和地方的 COVID-19 政策对鼓励保持社交距离的影响。结果是涵盖十个关键行业的机构的每日人流量，这些行业的传播风险差异很大。政策包括紧急状态声明、呆在家里（SAH）命令等生硬的一般限制，以及对酒吧、餐馆、娱乐场所和学校的限制等有针对性的规则。利用双重差分模型中政策时机的变化，我们发现大流行初期人流量的下降很大程度上是由于私人预防行为造成的。 SAH命令几乎不能解释病毒传播高风险行业的人流量下降，但确实可以解释户外运动和公园参观等中低风险行业的很大一部分人流量下降。有针对性的限制往往会影响目标行业以及互补行业。我们表明，有针对性的限制的影响在没有 SAH 限制的县中最大，这表明更有针对性的公共限制可以带来重要的效率提升。