The effectiveness of COVID deaths to COVID policies: A robust conditional approach

Abstract

This paper examines the effectiveness of four major COVID-19 social distancing policies, (i) shelter-in-place orders (SIPO), (ii) non-essential business closures, (iii) mandatory quarantine for travelers, and (iv) bans on large gatherings, on both COVID cases and COVID deaths. Results indicate that states are highly ineffective in producing the fraction of the population that does not have COVID-19 or the fraction of the population that does not die from COVID-19. We find that having any form of social distancing policies increases the fraction of the population not considered a positive COVID-19 case by 23.5 percentage points. Results also show that having any of the four major social distancing policies reduces the fraction of the population who has died of COVID-19 by 1.3 percentage points between March 1, 2020 and September 1, 2020; during the first 100 days, effectiveness would improve by 2.1 percentage points. Evidence suggests that there is no effective uniform national COVID-19 social distancing policy. Furthermore, conditional efficiency regressions after 100 days suggest that behavioral noncompliance and premature expiration of social distancing policies both negatively impact effectiveness. Partial regression plots suggest that bans on large gatherings and the closure of non-essential businesses were the two most impactful COVID-19 social distancing policies.

Keywords: COVID-19; Conditional order-m estimator; Order- $\alpha$; Production efficiency; Shelter-in-place.