ABSTRACT
Using daily census block group level data from the U.S., this paper investigates the welfare costs of staying at home due to COVID-19 across socioeconomic and demographic groups. The investigation is based on an economic model of which implications suggest that the welfare costs of staying at home increase with the stay-at-home probabilities of individuals. The empirical results provide evidence for significant heterogeneity across census block groups regarding the welfare effects of staying at home. This heterogeneity is further used to obtain measures of welfare changes for different socioeconomic and demographic groups at the national level.
Acknowledgments
The author would like to thank the editors, Davy Janssens and Chang Hyeon Joh, as well as two anonymous referees for their helpful comments and suggestions. The usual disclaimer applies.
Disclosure statement
No potential conflict of interest was reported by the author(s).
Notes
1 The web page is https://www.safegraph.com/.
2 The web page is https://www.census.gov/programs-surveys/acs.