We develop a multi-sectoral matching model to predict the impact of the lockdown on the US unemployment, considering the heterogeneity of workers to account for the contrasted impacts across various types of jobs. We show that separations and business closures that hit the workers with the first...

We develop a multi-sectoral matching model to predict the impact of the lockdown on the US unemployment, considering the heterogeneity of workers to account for the contrasted impacts across various types of jobs. We show that separations and business closures that hit the workers with the first...

We develop a general equilibrium model with matching frictions that predicts the impact of the COVID-19 lockdown on US unemployment, while accounting for the contrasted impacts across various job types. The model is calibrated on the subprime experience and is then used to identify the...