Expecting the unexpected: Stressed scenarios for economic growth (Replication data)

The choice of severe yet plausible stress scenarios is based on the joint probability distribution of the underlying factors driving growth, which are extracted with a multi-level Dynamic Factor Model (DFM) from a wide set of domestic/worldwide and/or macroeconomic/financial variables.

All together, we provide a risk management tool that allows for a complete visualization of the dynamics of the growth densities under average scenarios and extreme scenarios. We calculate Growth-in-Stress (GiS) measures, defined as the 5% quantile of the stressed growth densities, and show that GiS is a useful and complementary tool to Growth-at-Risk (GaR) when policymakers wish to carry out a multi-dimensional scenario analysis.