The micro-economic effects of COVID-19 containment measures: A simple model and evidence from China

Optimizing the trade-off between economic growth and public health is a major goal of public administration, especially during public health events. Although containment measures are widely used to combat the Covid-19 outbreak, it is still debated how the measures affect the economy. Using a simplified susceptible-infected-recovered (SIR) model, this study investigates the dynamic impact of lockdown policy on social costs during the epidemic and the underlying mechanism, revealing that the lockdown policy has both a "shutdown effect" and an "anti-epidemic effect", and should be implemented and lifted in a timely manner. Based on a micro-level dataset of 57,547 private enterprises in China in 2020, this study provided empirical evidence for the presence of negative "shutdown effect" and positive "anti-epidemic effect" of lockdown on reopening, both of which are in part mediated by labor input, factor mobility, and market demand recovery. Furthermore, the shutdown effect is weaker in regions with sufficient testing and quarantine resources, government capacity and preference for targeted response, whereas the anti-epidemic effect is stronger in densely populated areas with relatively low public compliance. Additionally, digital measures can aid in the containment of epidemics. The findings not only contribute to a better understanding of the rationality and effectiveness of the lockdown policy, but also provides practical evidence and implications for the government to improve the synergistic efficiency of epidemic control tools and strengthen the resilience of local economic growth.