Modeling the economic effects of the pandemic in a data-driven agent-based framework
Guest Lecture by Anton Pichler (CSH)
A introduction to a dynamic disequilibrium agent-based model (ABM) that was used to forecast the economics of the Covid-19 pandemic. This model was designed to understand the upstream and downstream propagation of the industry-specific demand and supply shocks caused by Covid-19, which were exceptional in their severity, suddenness and heterogeneity across industries. We used this model to forecast sectoral and aggregate economic activity for the United Kingdom during the early phase of the pandemic. This work demonstrates that an out of equilibrium model calibrated against national accounting data can serve as a useful real time policy evaluation and forecasting tool.
A further extension of this modelling framework to a large-scale, data-driven ABM of the New York metropolitan area that simulates both, epidemic and economic outcomes across industries, occupations, and income levels. This coupled epidemic-economic model is designed to address the potential tradeoff between economy and health which has been a key issue faced by policymakers. Our results show that lockdown policies affect different social groups very heterogeneously in terms of income and infections.
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- del Rio-Chanona et al. 2020: Supply and demand shocks in the COVID-19 pandemic. Oxford Rev Econ Policy. https://doi.org/10.1093/oxrep/graa033
- Pichler & Farmer 2021. Simultaneous supply and demand constraints in input–output networks. Economic Systems Research. https://doi.org/10.1080/09535314.2021.1926934
- Pichler et al. 2022. Forecasting the propagation of pandemic shocks with a dynamic input-output model. J Economic Dynamics & Control. https://doi.org/10.1016/j.jedc.2022.104527