How Effective Is Social Distancing?

Covid Economics, Vetted and Real-Time Papers 59: 118-148

52 Pages Posted: 28 Aug 2020 Last revised: 15 Apr 2021

Date Written: August 25, 2020

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.

Note: Funding: The research is funded by the Australian Government Research Training Program (RTP) Scholarship

Declaration of Interest: None to declare

Keywords: causal inference; COVID-19; heterogeneous; social distancing; treatment effects

JEL Classification: C30, C31, H0, I10

Suggested Citation

Huang, Difang, How Effective Is Social Distancing? (August 25, 2020). Covid Economics, Vetted and Real-Time Papers 59: 118-148, Available at SSRN: https://ssrn.com/abstract=3680321 or http://dx.doi.org/10.2139/ssrn.3680321

Difang Huang (Contact Author)

Monash University ( email )

900 Dandenong Road
Caulfield East
Melbourne, Victoria 3145
Australia

HOME PAGE: http://difang-huang.github.io

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