Research suggests that people took measures to halt the spread of COVID-19 without waiting for government to tell them
Yesterday, I wrote about how a significant voluntary reduction in consumption–people staying home, shifting to remote work, and taking their kids out of school—occurred before lockdowns were imposed to combat COVID-19.
Economist William J. Luther wrote recently:
In a new paper released last Friday, I analyze Google Mobility data and find that 76.60 percent of the change in residential (+), 75.61 percent in retail and recreation (−), 75.81 percent in workplace (−), 74.42 percent in transit station (−), and 19.58 percent in grocery and pharmacy (−) activity preceded state-level stay-at-home orders. I also estimate that 67.54 to 86.13 percent of the decline in park activity resulted before state-level stay-at-home orders were imposed, though the estimates for the decline in park activity before and after stay-at-home orders warrant less confidence.
The magnitude of change resulting prior to state-level stay-at-home orders implies that much of the consequences would have likely been realized—for better or worse—even if states had not imposed stay-at-home orders. In other words, the marginal effect of state-level stay-at-home orders, at least at the outset, was probably smaller than most people claim.
…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.
Cronin and Evans find that:
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…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. [Emphasis added]
This highlighted point is important. It suggests that individuals can to a large extent be trusted to make sensible decisions themselves regarding public (and private) health. This is pleasing confirmation of the philosophy that people can be trusted to run their own lives.
I noted previously how Minnesotans started returning to their normal lives in advance of Gov. Walz giving them his permission. It seems that it was also true that Americans started taking precautionary measures before their leaders commanded them to. This does, of course lead to an intriguing conclusion. As Luther notes:
The evidence cuts both ways. On the one hand, it means state-level stay-at-home orders probably had a modest effect on slowing the spread of COVID-19. On the other hand, it means state-level stay-at-home orders probably deserve little blame for reducing economic activity.
John Phelan is an economist at the Center of the American Experiment.