COVID-Town: An Integrated Economic-Epidemiological Agent-Based Model

I develop a novel macroeconomic epidemiological agent-based model to study the impact of the COVID-19 pandemic under varying policy scenarios.

Agents differ with regard to their profession, family status and age and interact with other agents at home, work or during leisure activities, behave according to boundedly rational rules, and are connected to each other via various social networks.

The model allows to implement and test actually used or counterfactual policies such as closing schools or the leisure industry explicitly in the model in order to explore their impact on the spread of the virus, and their economic consequences. The model is calibrated with German statistical data on time use, demography, households, firm demography, employment, company profits and wages.

I set up a baseline scenario based on the German containment policies and fit the epidemiological parameters of the simulation to the observed German death curve and an estimated infection curve of the first COVID-19 wave. I then experiment with alternative epidemiological and fiscal policy scenarios.