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Daily data at the U.S. county level suggest that coronavirus disease 2019 (COVID-19) cases and deaths are lower in counties where a higher share of people have stayed in the same county (or travelled less to other counties). This observation is tested formally by using a difference-in-difference design controlling for county-fixed effects and time-fixed effects, where weekly changes in COVID-19 cases or deaths are regressed on weekly changes in the share of people who have stayed in the same county during the previous 14 days. A counterfactual analysis based on the formal estimation results suggests that staying in the same county has the potential of reducing total weekly COVID-19 cases and deaths in the U.S. as much as by 139,503 and by 23,445, respectively.

This paper models and estimates bilateral trade patterns of U.S. states in a CES framework and identi…es the elasticity of substitution across goods, elasticity of substitution across varieties of each good, and the good-speci…c elasticity of distance measures by using markup values obtained from the production side. Compared to empirical international trade literature, the elasticity of substitution estimates are lower across both goods and varieties, while the elasticity of distance estimates are higher. Although home-bias e¤ects at the state level are signi…cant, there is evidence for decreasing e¤ects over time.JEL Classi…cation: F12, R12, R32

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