Abstract

This paper develops a unified model of policy diffusion to analyze the speed of adoption of statewide lockdown policies within a federal system during the COVID-19 pandemic. The modified unified model was built to improve our understanding of policy diffusion in contexts where existing models fall short. The authors highlight three main policy diffusion channels: regional, vertical, and internal. The paper shows the empirical test of the model across US states and finds that vertical effects, such as higher approval ratings for President Donald Trump, as well as a comparatively high proportion of COVID-19 federal funding support, bear a strong positive association with the speed of statewide lockdown adoption policies. In addition, certain internal effects are also important - higher governor approval ratings are positively associated with the speed of statewide lockdown adoption policies, as are state and local spending, democratic state governments, and population awareness of the virus. However, other internal factors, such as the stringency of statewide lockdown policies and the relative proportion of COVID-19 deaths in a state, were minimally associated with the speed of lockdown policy adoption. Surprisingly, unlike past studies, horizontal regional effects did not play a significant role in the presented analysis - the speed of adoption of lockdown policies by neighboring states bears no association with the speed of policy adoption of statewide lockdowns. Overall, the results suggest a strong influence of political factors on the speed of statewide lockdown adoption policies in the US.