The Effect of Large-Scale Anti-Contagion Policies on the Coronavirus (COVID-19) Pandemic

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

We estimate a multiple regression version of Equation 6 using ordinary least squares. We include a vector of sub-national unit-fixed effects θ 0 (i.e. varying intercepts captured as coefficients to dummy variables) to account for all time-invariant factors that affect the local growth rate of infections, such as differences in demographics, socio-economic status, culture, or health systems. 24 We include a vector of day-of-week-fixed effects δ to account for weekly patterns in the growth rate of infections that are common across locations within a country. We include a separate singleday dummy variable each time there is an abrupt change in the availability of COVID-19 testing or a change in the procedure to diagnose positive cases. Such changes generally manifest as a discontinuous jump in infections and a re-scaling of subsequent infection rates (e.g. See China in Figure 1 ), effects that are flexibly absorbed by a single-day dummy variable because the dependent variable is the first-difference of the logarithm of infections. Denote the vector of these testing dummies µ.