Learning from deregulation: The asymmetric impact of lockdown and reopening on risky behavior during COVID-19.
| Autor: | Glaeser EL; Department of Economics Harvard University Cambridge Massachusetts USA.; NBER Cambridge Massachusetts USA., Jin GZ; NBER Cambridge Massachusetts USA.; Department of Economics University of Maryland College Park Maryland USA., Leyden BT; Dyson School of Applied Economics and Management Cornell University Ithaca New York USA.; CESifo Munich Germany., Luca M; NBER Cambridge Massachusetts USA.; Harvard Business School Harvard University Boston Massachusetts USA. |
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| Jazyk: | angličtina |
| Zdroj: | Journal of regional science [J Reg Sci] 2021 Sep; Vol. 61 (4), pp. 696-709. Date of Electronic Publication: 2021 Jun 07. |
| DOI: | 10.1111/jors.12539 |
| Abstrakt: | During the coronavirus disease 2019 (COVID-19) pandemic, states issued and then rescinded stay-at-home orders that restricted mobility. We develop a model of learning by deregulation, which predicts that lifting stay-at-home orders can signal that going out has become safer. Using restaurant activity data, we find that the implementation of stay-at-home orders initially had a limited impact, but that activity rose quickly after states' reopenings. The results suggest that consumers inferred from reopening that it was safer to eat out. The rational, but mistaken inference that occurs in our model may explain why a sharp rise of COVID-19 cases followed reopening in some states. (© 2021 The Authors. Journal of Regional Science published by Wiley Periodicals LLC.) |
| Databáze: | MEDLINE |
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