To slow the spread of COVID-19, many countries are shutting down non-essential sectors of the economy. Older individuals have the most to gain from slowing virus diffusion. Younger workers in sectors that are shuttered have the most to lose.
Over the last 15 years, 11 states have restricted employers' access to the credit reports of job applicants.
We study a dynamic macro model to capture the trade-off between policies that simultaneously decrease output and the rate of infection transmission.
Exploiting results from the literature on non-parametric identification, we make three methodological contributions to the empirical literature estimating the matching function, commonly used to map unemployment and vacancies into hires.