Cargando…

Learning from deregulation: The asymmetric impact of lockdown and reopening on risky behavior during COVID‐19

During the coronavirus disease 2019 (COVID‐19) pandemic, states issued and then rescinded stay‐at‐home orders that restricted mobility.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 activit...

Descripción completa

Detalles Bibliográficos
Autores principales: Glaeser, Edward L., Jin, Ginger Z., Leyden, Benjamin T., Luca, Michael
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8242873/
https://www.ncbi.nlm.nih.gov/pubmed/34226759
http://dx.doi.org/10.1111/jors.12539
Descripción
Sumario:During the coronavirus disease 2019 (COVID‐19) pandemic, states issued and then rescinded stay‐at‐home orders that restricted mobility.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.