Sloan School of Management, Massachusetts Institute of Technology, Cambridge, MA 02142.
Initiative on the Digital Economy, Massachusetts Institute of Technology, Cambridge, MA 02142.
Proc Natl Acad Sci U S A. 2020 Aug 18;117(33):19837-19843. doi: 10.1073/pnas.2009522117. Epub 2020 Jul 30.
Social distancing is the core policy response to coronavirus disease 2019 (COVID-19). But, as federal, state and local governments begin opening businesses and relaxing shelter-in-place orders worldwide, we lack quantitative evidence on how policies in one region affect mobility and social distancing in other regions and the consequences of uncoordinated regional policies adopted in the presence of such spillovers. To investigate this concern, we combined daily, county-level data on shelter-in-place policies with movement data from over 27 million mobile devices, social network connections among over 220 million Facebook users, daily temperature and precipitation data from 62,000 weather stations, and county-level census data on population demographics to estimate the geographic and social network spillovers created by regional policies across the United States. Our analysis shows that the contact patterns of people in a given region are significantly influenced by the policies and behaviors of people in other, sometimes distant, regions. When just one-third of a state's social and geographic peer states adopt shelter-in-place policies, it creates a reduction in mobility equal to the state's own policy decisions. These spillovers are mediated by peer travel and distancing behaviors in those states. A simple analytical model calibrated with our empirical estimates demonstrated that the "loss from anarchy" in uncoordinated state policies is increasing in the number of noncooperating states and the size of social and geographic spillovers. These results suggest a substantial cost of uncoordinated government responses to COVID-19 when people, ideas, and media move across borders.
社交距离是针对 2019 年冠状病毒病(COVID-19)的核心政策反应。但是,随着联邦、州和地方政府开始在全球范围内开放企业并放宽就地避难所命令,我们缺乏关于一个地区的政策如何影响其他地区的流动性和社交距离的定量证据,以及在存在这种溢出效应的情况下采取不协调的区域政策的后果。为了调查这一问题,我们将关于就地避难所政策的每日县级数据与来自 2700 多万移动设备的移动数据、来自 2200 多万 Facebook 用户的社交网络连接、来自 62000 个气象站的每日温度和降水数据以及县级人口普查数据相结合,以估算美国各地的区域政策所产生的地理和社交网络溢出效应。我们的分析表明,一个特定地区的人们的联系模式会受到其他地区,甚至是遥远地区的人们的政策和行为的显著影响。当一个州三分之一的社交和地理同行州采取就地避难所政策时,它会导致该州的流动性减少,这相当于该州自己的政策决策。这些溢出效应是由这些州的同行旅行和距离行为介导的。一个用我们的实证估计值校准的简单分析模型表明,在协调州政策时,“无政府状态的损失”随着非合作州的数量和社会与地理溢出效应的规模而增加。这些结果表明,当人员、思想和媒体跨越国界流动时,协调应对 COVID-19 的政府反应会带来巨大的成本。