Optimally Controlling an Epidemic

Martín Gonzalez-Eiras, Dirk Niepelt
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引用次数: 6

Abstract

We propose a flexible model of infectious dynamics with a single endogenous state variable and economic choices. We characterize equilibrium, optimal outcomes, static and dynamic externalities, and prove the following: (i) A lockdown generically is followed by policies to stimulate activity. (ii) Re-infection risk lowers the activity level chosen by the government early on and, for small static externalities, implies too cautious equilibrium steady-state activity. (iii) When a cure arrives deterministically, optimal policy is dis-continuous, featuring a light/strict lockdown when the arrival date exceeds/falls short of a specific value. Calibrated to the ongoing COVID-19 pandemic the baseline model and a battery of robustness checks and extensions imply (iv) lockdowns for 3-4 months, with activity reductions by 25-40 percent, and (v) substantial welfare gains from optimal policy unless the government lacks instruments to stimulate activity after a lockdown.
最佳控制流行病
我们提出了一个具有单一内生状态变量和经济选择的灵活的传染动力学模型。我们描述了均衡、最优结果、静态和动态外部性,并证明了以下几点:(i)封锁之后通常会有刺激活动的政策。(ii)再感染风险降低了政府早期选择的活动水平,对于较小的静态外部性,意味着过于谨慎的平衡稳态活动。(iii)当解药确定到达时,最优策略是不连续的,即当到达日期超过/少于特定值时,采取轻度/严格封锁。根据正在进行的COVID-19大流行,基线模型和一系列稳健性检查和扩展表明:(iv)封锁3-4个月,活动减少25% - 40%,以及(v)除非政府缺乏在封锁后刺激活动的工具,否则最优政策会带来可观的福利收益。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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