We propose the construction of conditional growth densities under stressed factor
scenarios to assess the level of exposure of an economy to small probability but
potentially catastrophic economic and/or financial scenarios, which can be either
domestic or international. 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. The unprecedented economic shock brought by the COVID19
pandemic provides a natural environment to assess the vulnerability of US growth
with the proposed methodology.
