Total shutdowns, targeted restrictions, or individual responsibility: How to promote social distancing in the COVID-19 Era?

Abstract

We examine the impact of early state and local COVID-19 policies to encourage social distancing. Outcomes are daily foot traffic at establishments spanning ten key industries, across which transmission risk varies substantially. Policies include state of emergency declarations, blunt general restrictions such as stay-at-home (SAH) orders, and targeted rules such as restrictions on bars, restaurants, entertainment venues, and schools. Exploiting variation in the timing of policies in difference-in-difference models, we show that much of the decline in foot traffic early in the pandemic was due to private precautionary behavior. SAH orders explain almost none of the foot traffic decline in industries with high risk of virus transmission, but they do explain a substantial share of the decline in moderate- to low-risk industries such as outdoor sports and visits to parks. Targeted restrictions tend to impact intended industries, as well as complementary ones. We show that the impact of targeted restrictions is largest in counties with no SAH restrictions, suggesting that better targeting of public restrictions can have important efficiency gains.

Keywords: COVID-19; Foot traffic; Stay at home.

Fig. 1

Fraction of the Population Covered by Various Social Distancing Ordinances, and the Fraction that Live in a County that have experienced their First COVID-19 Case and Death.

Fig. 2

The natural log of daily foot traffic for nonessential retail stores, for various groupings, SafeGraph Data.

Fig. 3

Policy, First Death, and First Case Impact on Nonessential Retail Foot Traffic, SafeGraph Data.

Fig. 4

Restaurant Dine-in Ban on Restaurant Foot Traffic, SafeGraph Data.

Fig. A1

Natural log of daily foot traffic by industry group and the at home rate, 1/1/2020 to 5/15/2020, SafeGraph Data.

Fig. A2

Actual series and OLS estimates of Eq. (1) for non-essential. Retail ln(Daily Foot Traffic) and At home rate at the structural break period, and the F-test at different structural breaks, SafeGraph Data.

Fig. A3

Natural log of daily foot traffic by industry group and at home rate, Indexed by the days in relation to the earliest SOE declaration, SafeGraph Data.

Fig. A4

Natural log of daily foot traffic by industry group and At Home Rate, Indexed by the days in relation to earlies SAH order, SafeGraph Data.

Fig. A5

Daily foot traffic index (Day -1 = 1.00) and at home rate by industry group and county-level SAH status, indexed by the days in relation to earliest SOE order, SafeGraph Data.

Fig. A5

Daily foot traffic index (Day -1 = 1.00) and at home rate by industry group and county-level SAH status, indexed by the days in relation to earliest SOE order, SafeGraph Data.

Fig. A6

SAH impact on various foot traffic measures, no controls, SafeGraph Data.

Fig. A7

Policy, first death, and first case impact on bar foot traffic, SafeGraph Data.

Fig. A8

Policy, first death, and first case impact on restaurant foot traffic, SafeGraph Data.

Fig. A9

Policy, first death, and first case impact on hotel foot traffic, SafeGraph Data.

Fig. A10

Policy, first death, and first case impact on church foot traffic, SafeGraph Data.

Fig. A11

Policy, first death, and first case impact on indoor entertainment foot traffic, SafeGraph Data.

Fig. A12

Policy, first death, and first case impact on essential retail foot traffic, SafeGraph Data.

Fig. A13

Policy, first death, and first case impact on business services foot traffic, SafeGraph Data

Fig. A14

Policy, first death, and first case impact on nature park foot traffic, SafeGraph Data.

Fig. A15

Policy, first death, and first case impact on outdoor sporting foot traffic, SafeGraph Data.

Fig. A16

Policy, first death, and first case impact on share of population staying at home all day, SafeGraph Data.