  We identify the effectiveness of social distancing policies in 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 policies, where we control time-varying, observed and
unobserved, state-level heterogeneities. Using panel data on infection and
deaths in all US states from February 20 to April 20, 2020, we find that
stay-at-home orders and other types of social distancing policies significantly
reduced the growth rate of infection and deaths. We show that the effects are
time-varying and range from the weakest at the beginning of policy intervention
to the strongest by the end of our sample period. We also found that social
distancing policies were more effective in states with higher income, better
education, more white people, more democratic voters, and higher CNN
viewership.
