How Effective Is Social Distancing?

Abstract

We identify the dynamic effects of social distancing policy on reducing the transmission of the COVID-19 spread. We build a model that measures the relative frequency and geographic distribution of the virus growth rate and provides hypothetical infection distribution in the states that enacted the social distancing policy, where we control all time-varying, observed and unobserved, state-level heterogeneities. We apply our model to a panel of weekly COVID-19 infection cases and deaths of all states in the United States from February 20 to April 20, 2020, and find that during our sample period, social distancing intervention is effective in reducing the weekly growth rate in cases by 9.8% and in deaths by 7.0%. We show that the effects are time-varying that range from the weakest at the beginning of policy intervention to the strongest by the end of our sample period. We further demonstrate that the effects are cross-sectional heterogeneous as the states with higher income, higher education, more White people, more democratic voters, and higher CNN viewership have a more considerable reduction in the infection growth rate.