THE DISTRIBUTIONAL EFFECTS OF COVID‐19 AND OPTIMAL MITIGATION POLICIES
构建了一个量化异质性主体生命周期流行病模型，研究COVID-19及其缓解政策的总体和分配效应。发现居家补贴优于封锁，帕累托改进政策可在不减少产出的情况下将死亡人数降低近45%，表明经济与健康目标之间的权衡可能被误解。
Abstract This article develops a quantitative heterogeneous agent–life cycle–epidemiological model that is used to study the aggregate and distributional consequences of COVID‐19 and mitigation policies. First, a stay‐at‐home subsidy is preferred to a lockdown because it reduces deaths by more and output by less. Second, Pareto‐improving policies can reduce deaths by nearly 45% without any reduction in output relative to no public mitigation. Finally, it is possible to simultaneously improve public health and economic outcomes, suggesting that debates regarding a trade‐off between economic and health objectives may be misguided.