id	author	title	date	pages	extension	mime	words	sentences	flesch	summary	cache	txt
cord-275281-baxst5an	Dimke, C.	Working from a distance: Who can afford to stay home during COVID-19? Evidence from mobile device data	2020-07-26		.txt	text/plain	1802	125	62	We match census block group level Safegraph mobile device data with demographic data from the American Community Survey to identify trends amongst different subgroups of the population. Our method yields up-to-date estimates of time spent at home across demographic groups, a classification unavailable using mobile device data alone. (2020) , who document heterogeneous mobility by income quintiles, 25 by evaluating education levels and occupations with the ability to work from home. We classify each CBG based on the composition of the population along the following characteristics: education, 40 household income, and occupations with ability to work from home. . https://doi.org/10.1101 We explore the heterogeneity of this response along education, income, and ability to work from home (Figure 1 ). We find that those with Bachelor's degrees or higher, household incomes greater than $100,000, and a greater ability to work from home spent significantly more time at home relative to the rest 100 of the population.	./cache/cord-275281-baxst5an.txt	./txt/cord-275281-baxst5an.txt