Forecasting economic crises: The Great Recession, the sovereign debt crisis, and COVID-19 in the euro area

Abstract

This study investigates the potential of agent-based modelling to forecast economic crises, addressing the failure of standard macroeconomic models to predict the 2008 financial crisis and capture crisis dynamics. While dynamic stochastic general equilibrium models have incorporated financial frictions, solving them typically requires linearisation around steady states, which suppresses the non-linear feedback loops through which crises emerge. Agent-based models avoid this limitation by numerically simulating heterogeneous agents, preserving non-linear dynamics without approximation. We develop such an agent-based model for the euro area and show that out-of-sample forecasts outperform benchmarks. We further demonstrate that the model can forecast economic crises without exogenous shocks and accurately reproduce crisis dynamics. The model endogenously predicts the onset of the Great Recession, explains the persistence of the sovereign debt crisis, and reproduces the sharp contraction and swift recovery of the COVID-19 recession. The findings suggest that preserving non-linear feedback loops is essential for crisis prediction. • The research develops an agent-based model for the euro area to forecast crises. • The model outperforms standard benchmarks in out-of-sample forecasts. • The model endogenously predicts the Great Recession without external shocks. • The analysis explains the debt crisis’s persistence and COVID-19 recession dynamics. • The findings suggest next-generation models require heterogeneity and feedbacks.