Business Restrictions and COVID Fatalities

39 Pages Posted: 10 Nov 2020

See all articles by Matthew I. Spiegel

Matthew I. Spiegel

Yale University - Yale School of Management, International Center for Finance

Heather Tookes

Yale University - Yale School of Management; Yale University - International Center for Finance

Date Written: November 4, 2020

Abstract

We hand-collect a time-series database of business closures and related restrictions for every county in the United States since March 2020. We then relate these policies to future growth in deaths due to COVID-19. To our knowledge, ours is the most comprehensive database of U.S. COVID-19 business policies that has been assembled to date. Across specifications, stay-at-home orders, mandatory mask requirements, beach and park closures, restaurant closures, and high risk (Level 2) business closures are the policies that most consistently predict lower 4- to 6- week-ahead fatality growth. For example, baseline estimates imply that a county with a mandatory mask policy in place today will experience 4- week and 6- week ahead fatality growth rates that are each 1% lower (respectively) than a county without such an order in place. This relationship is significant, both statistically and in magnitude. It represents 12% of the sample mean of weekly fatality growth. The baseline estimates for stay-at-home, restaurant and high-risk business closures are similar in magnitude to what we find for mandatory mask policies. We fail to find consistent evidence in support of the hypothesis that some of the other business restrictions (such as spa closures, school closures, and the closing of the low- to medium-risk businesses that are typically allowed in Phase I reopenings) predict reduced fatality growth at four-to-six-week horizons. Some policies, such as low- to medium business risk closures may even be counterproductive. To address potential endogeneity concerns, we conduct two tests. First, we exploit the fact that many county regulations are imposed at the state-level through Governors’ executive orders. Following the intuition that smaller counties often inherit state-level regulations that are intended to reduce transmission and deaths in more populous regions, we remove the 5 most populous counties in each state from the sample. In the second test, we match counties that lie near (but not on) state borders to counties in different states that are also near (but not on) state borders and are within 100 miles of that county. Absent policy differences, these nearby counties should see similar trends in virus transmission; making them good controls. We continue to find that stay-at-home, mandatory masks, beach and park closures, restaurant closures, and high risk business closures all predict declines in future fatality growth.

Note: Funding: None.

Declaration of Interests: None.

Suggested Citation

Spiegel, Matthew I. and Tookes, Heather, Business Restrictions and COVID Fatalities (November 4, 2020). Available at SSRN: https://ssrn.com/abstract=3725015 or http://dx.doi.org/10.2139/ssrn.3725015

Matthew I. Spiegel

Yale University - Yale School of Management, International Center for Finance ( email )

135 Prospect Street
P.O. Box 208200
New Haven, CT 06520-8200
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203-432-6017 (Phone)
203-432-8931 (Fax)

HOME PAGE: http://som.yale.edu/~spiegel

Heather Tookes (Contact Author)

Yale University - Yale School of Management ( email )

135 Prospect Street
P.O. Box 208200
New Haven, CT 06520-8200
United States

Yale University - International Center for Finance ( email )

Box 208200
New Haven, CT 06520
United States

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