Private Precaution and Public Restrictions: What Drives Social Distancing and Industry Foot Traffic in the COVID-19 Era? / Christopher J. Cronin, William N. Evans.

By:

Cronin, Christopher J

Contributor(s):

Material type: Text

TextSeries: Working Paper Series (National Bureau of Economic Research) ; no. w27531.Publication details: Cambridge, Mass. National Bureau of Economic Research 2020.Description: 1 online resource: illustrations (black and white)Subject(s):

Online resources:

Available additional physical forms:

Hardcopy version available to institutional subscribers

Abstract: We examine the role of state and local policies to encourage social distancing, including stay at home orders, public school closures, and restrictions on restaurants, entertainment, and large social gatherings. Outcomes come from cell phone records and include foot traffic in six industries (essential and nonessential retail, entertainment, hotel, restaurant, and business services) plus the fraction of cell phones that are home all day. Structural break models show mobility series at the national and state levels start to change dramatically in a short window from March 8-14, well before state or local restrictions of note are in place. In difference-in-difference models, declarations of state of emergency reduce foot traffic and increase social distancing. Stay at home restrictions explain a modest fraction of the change in behavior across outcomes. Industry-specific restrictions have large impacts. For example, restrictions on dining in restaurants reduce traffic in restaurants, hotels, and nonessential retail. Private, self-regulating behavior explains more than three-quarters of the decline in foot traffic in most industries. Restrictive regulation explains half the decline in foot traffic in essential retail and 75 percent of the increase in the fraction home all day. In this latter result, public school closings have a substantial effect.

Tags from this library: No tags from this library for this title. Log in to add tags.

Average rating: 0.0 (0 votes)

Holdings
Item type	Home library	Collection	Call number	Status	Date due	Barcode	Item holds
Working Paper	Biblioteca Digital	Colección NBER	nber w27531 (Browse shelf(Opens below))	Not For Loan

Total holds: 0

Collection: Colección NBER Close shelf browser (Hides shelf browser)

Previous	No cover image available	No cover image available	No cover image available	No cover image available	No cover image available	No cover image available	No cover image available	Next
Previous	nber w27529 The Real Effects of Modern Information Technologies /	nber w2753 Altruism, Rivalry and Crowding-Out in the Nonprofit Firm's Supply of Charity Services: The Case of Hospitals /	nber w27530 The Impact of the WWI Agricultural Boom and Bust on Female Opportunity Cost and Fertility /	nber w27531 Private Precaution and Public Restrictions: What Drives Social Distancing and Industry Foot Traffic in the COVID-19 Era? /	nber w27532 Adaptive Control of COVID-19 Outbreaks in India: Local, Gradual, and Trigger-based Exit Paths from Lockdown /	nber w27533 Concentration Screens for Horizontal Mergers /	nber w27534 Relabeling, Retirement and Regret /	Next

July 2020.

We examine the role of state and local policies to encourage social distancing, including stay at home orders, public school closures, and restrictions on restaurants, entertainment, and large social gatherings. Outcomes come from cell phone records and include foot traffic in six industries (essential and nonessential retail, entertainment, hotel, restaurant, and business services) plus the fraction of cell phones that are home all day. Structural break models show mobility series at the national and state levels start to change dramatically in a short window from March 8-14, well before state or local restrictions of note are in place. In difference-in-difference models, declarations of state of emergency reduce foot traffic and increase social distancing. Stay at home restrictions explain a modest fraction of the change in behavior across outcomes. Industry-specific restrictions have large impacts. For example, restrictions on dining in restaurants reduce traffic in restaurants, hotels, and nonessential retail. Private, self-regulating behavior explains more than three-quarters of the decline in foot traffic in most industries. Restrictive regulation explains half the decline in foot traffic in essential retail and 75 percent of the increase in the fraction home all day. In this latter result, public school closings have a substantial effect.