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

There are some country-specific adjustments to Equation 7 due to idiosyncratic differences between samples. In China, we code policy parameters using weekly lags based on the date that the policy is first implemented in locality i. As discussed in the main text, this is done to understand the temporal dynamics of the response to policy in the one country where policy has been enacted the longest and in the most consistent way. Weekly lags are used because the incubation period COVID-19 is thought to be 5-6 days. 4 Econometrically, this means the effect of a policy implemented one week ago is allowed to differ arbitrarily from the effect of a policy implemented two weeks ago, etc. These effects are all estimated simultaneously. Also in China, we omit day-of-week effects because there is no evidence to suggest they are present in the data -this could be due to the fact that the outbreak of COVID-19 began during a national holiday and workers never returned to work. In Iran, we estimate a separate effect of policies implemented in Tehran that is allowed to differ from the effect in other locations by creating Tehran-specific dummy variable that is interacted with both policy variables. This is implemented because of the stark and significantly different effect of policies in Tehran relative to effects in other parts of the country.