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_15
Snippet: A strength of this model is that county-level fixed effects control for all time-invariant α c features of each county that might drive rates of case growth in the epidemic. 21 For example, each county has its own age profile, socioeconomic status, local health care system, base rate of population health, and date on which a first case of COVID-19 was observed. Additionally, time fixed effects control for factors that vary over time. 21 For exam.....
Document: A strength of this model is that county-level fixed effects control for all time-invariant α c features of each county that might drive rates of case growth in the epidemic. 21 For example, each county has its own age profile, socioeconomic status, local health care system, base rate of population health, and date on which a first case of COVID-19 was observed. Additionally, time fixed effects control for factors that vary over time. 21 For example, case rates could be α t affected by changes in the availability of testing nationally, in social behaviors influenced by daily events reported in the media, and national-level policies that vary from one day to the next. Finally, we cluster standard errors u ct at the state level. This adjusts the estimated standard errors for unobservable factors correlated between counties within the same state.
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