Optimal Mitigation Policies in a Pandemic: Social Distancing and Working from Home

Abstract

We study an economy's response to an unexpected epidemic. The spread of the disease can be mitigated by reducing consumption and hours worked in the office. Working from home is subject to learning-by-doing. Private agents' rational incentives are relatively weak and fatalistic. The planner recognizes infection and congestion externalities and implements front-loaded mitigation. Under our calibration, the planner reduces cumulative fatalities by 48$\%$ compared to 24$\%$ by private agents, although with a sharper drop in consumption. Our model can replicate key industry and/or occupational-level patterns and explain how large variations in outcomes across regions can stem from small initial differences.