Author: James H. Fowler; Seth J. Hill; Nick Obradovich; Remy Levin
Title: The Effect of Stay-at-Home Orders on COVID-19 Infections in the United States Document date: 2020_4_17
ID: 4s8unfnk_16
Snippet: We identify the effects of stay-at-home orders using variation in the timing of implementation δ τ by counties and municipalities. Our two-way fixed effects regression is equivalent to a difference-in-difference model with variation in treatment timing. Models with variation in treatment timing are known to exhibit bias if the treatment effect is heterogeneous over time. 22 We test for temporal treatment heterogeneity bias by performing a Bacon.....
Document: We identify the effects of stay-at-home orders using variation in the timing of implementation δ τ by counties and municipalities. Our two-way fixed effects regression is equivalent to a difference-in-difference model with variation in treatment timing. Models with variation in treatment timing are known to exhibit bias if the treatment effect is heterogeneous over time. 22 We test for temporal treatment heterogeneity bias by performing a Bacon decomposition. 23 Results from this analysis indicate that this source of bias is moderate (weight of Later Treatment vs. Earlier Control = 0.29) and that bias attenuates our results towards 0, in which case our estimates are a lower bound for the effect of stay-at-home orders on case growth.
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