Unemployment Effects of Stay-at-Home Orders: Evidence from High Frequency Claims Data
- Author(s): Baek, ChaeWon;
- McCrory, Peter B;
- Messer, Todd;
- Mui, Preston
- et al.
Published Web Locationhttps://irle.berkeley.edu/unemployment-effects-of-stay-at-home-orders-evidence-from-high-frequency-claims-data/
Epidemiological models projected that, without effective mitigation strategies, upwards of 2 million Americans were at risk of death from the COVID-19 pandemic. Heeding the warning, in mid-March 2020, state and local officials in the United States began issuing Stay-at-Home (SAH) orders, instructing people to remain at home except to do essential tasks or to do work deemed essential. By April 4th, 2020, nearly 95% of the U.S. population was under such orders. Over the same three week period, initial claims for unemployment spiked to unprecedented levels. In this paper, we use the high-frequency, decentralized implementation of SAH orders, along with high-frequency unemployment insurance (UI) claims, to disentangle the relative effect of SAH orders from the general economic disruption wrought by the pandemic that affected all regions similarly. We find that, all else equal, each week of Stay-at-Home exposure increased a state’s weekly initial UI claims by 1.9% of its employment level relative to other states. Ignoring cross-regional spillovers, a back-of-the-envelope calculation implies that, of the 17 million UI claims made between March 14 and April 4, only 4 million were attributable to the Stay-at-Home orders. This evidence suggests that the direct effect of SAH orders accounted for a substantial, but minority share, of the overall initial rise in unemployment claims. We present a stylized currency union model to provide conditions under which this estimate represents an upper or lower bound for aggregate employment losses attributable to SAH orders.