Author: Solomon Hsiang; Daniel Allen; Sebastien Annan-Phan; Kendon Bell; Ian Bolliger; Trinetta Chong; Hannah Druckenmiller; Andrew Hultgren; Luna Yue Huang; Emma Krasovich; Peiley Lau; Jaecheol Lee; Esther Rolf; Jeanette Tseng; Tiffany Wu
Title: The Effect of Large-Scale Anti-Contagion Policies on the Coronavirus (COVID-19) Pandemic Document date: 2020_3_27
ID: gtfx5cp4_67
Snippet: is the (which was not peer-reviewed) The copyright holder for this preprint . demographics), day-of-week-effects, and adjustments based on the way in which infection cases are reported. This counterfactual does not account for changes in information that are triggered by policy deployment, since those should be considered a pathway through which policies affect outcomes, as discussed in the main text. When we report an average "no policy" growth .....
Document: is the (which was not peer-reviewed) The copyright holder for this preprint . demographics), day-of-week-effects, and adjustments based on the way in which infection cases are reported. This counterfactual does not account for changes in information that are triggered by policy deployment, since those should be considered a pathway through which policies affect outcomes, as discussed in the main text. When we report an average "no policy" growth rate of infections (Figure 2A) , it is the average value of these predictions for all observations in the original sample. Location-and-day specific counterfactual predictions (Ä no policy cit ), accounting for the covariance of errors in estimated parameters, are shown as red markers in Figure 3 .
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