We construct a framework for integrated epi-econ assessment: theory, calibration to micro-, macro-, and epi-data, and numerical methods for quantitative policy evaluation. The model has an explicit microeconomic, market-based structure. It highlights trade- offs, within period and over time, associated with activities that involve both valuable social interaction and harmful disease transmission. We compare market solutions with socially optimal allocations. Our calibration to covid-19 implies that households shift their leisure and work activities away from social interactions. This is especially true for older individuals, who are more vulnerable to disease. The optimal allocation may or may not involve lockdown and changes the time allocations significantly across age groups. In this trade-off, people’s social leisure time becomes an important factor, aside from deaths and GDP. We finally compare optimal responses to different viruses (SARS, seasonal flu) and argue that, going forward, economic analysis ought to be an integral element behind epidemiological policy.

We quantify the unemployment-risk channel in business-cycle fluctuations, whereby an initial contractionary shock is amplified through workers reducing their demand in fear of unemployment. We document two stylized facts on how unemployment and unemployment risk respond to identified demand and supply shocks in US data. First, separation and job-finding rates play similar important roles in accounting for the overall unemployment response. Second, separations are more important early on, while job-finding rates respond with a lag. We show how a tractable heterogeneous-agent new-Keynesian model with a frictional labor market matches both facts once we include endogenous separations and sluggish vacancy creation. Relative to a model with exogenous separations and free entry, our framework attributes almost twice as large a share of output fluctuations to the inefficient unemployment-risk channel, and thus gives a larger role to stabilization policy.