Why Did US Governors Delay Lockdowns Against COVID-19? Disease Science vs Learning, Cascades, and Political Polarization
17 Pages Posted: 14 Apr 2020 Last revised: 16 Jun 2020
Date Written: April 13, 2020
As COVID-19 ravaged the US in the first quarter of 2020, the US lacked a uniform mandatory policy for containing its spread. Governors facing enormous opposing pressures from businesses and medical professionals adopted various policies, especially lockdowns. The authors statistically analyze the ensuing variance in governors’ decisions as a function of four predictors and several control variables. They draw their four predictors from medical science and behavioral theories of political polarization, social learning, and information cascades. The conventional wisdom is that, following medical science, governors ordered lockdown primarily on the percent of their state’s population infected with COVID-19. Contrary to this premise, the authors find other variables have higher influence including the following:
1) The political affiliation of the governor had a big effect on the hazard of a lockdown – on any day, a democratic governor was three times more likely than a republican governor to order a lockdown.
2) Social learning played an important role. Governors of states afflicted later by COVID-19 acted much faster than those who were afflicted earlier; for every day later COVID-19 started in a state, a governor was 1.4 times more likely to order a lockdown.
3) Actions of some governors triggered mini-cascades, sparking multiple governors to order lockdowns in their states in the next three days.
4) The percentage of the state’s population infected with COVID-19 (a measure of belief in the science of disease transmission) had a weak effect on the governors’ decisions.
Keywords: Lockdown, COVID-19, Coronavirus, Democrat, Republican, US Governors, Social Distancing, Hazard model, Healthcare policy, Theory of Infectious Disease, Lockdown, COVID-19, coronavirus, Democrat, Republican, US Governors, Social Distancing, Hazard model, Healthcare policy, Theory of Infectious Disease
JEL Classification: I1, I18, M30, O33, D80, P16, Z1
Suggested Citation: Suggested Citation