Implications of Stochastic Transmission Rates for Managing Pandemic Risks
将随机传播冲击引入流行病模型，通过资产定价框架连接企业估值与感染动态，估计了COVID-19的基本再生数和传播波动性，发现确定性模型存在偏差，且缓解政策和高疫苗到达率对估值至关重要。
Abstract We introduce aggregate transmission shocks to an epidemic model and link firm valuations to infections via an asset pricing framework with vaccines. Infections lower earnings growth but firms can mitigate damages. We estimate a large reproduction number ${\mathcal R}_0$ and transmission volatility for COVID-19. Using these estimates, we quantify the bias of deterministic approximations based on ${\mathcal R}_0$. Our model generates predictions consistent with the data: unexpected infection resurgence, nonmonotonic mitigation policies, and higher price-to-earnings ratios during a pandemic. Valuations would be significantly lower absent mitigation and a high vaccine arrival rate.