DP15109 Modeling and Forecasting Macroeconomic Downside Risk

Author(s): Andrea De Polis, Davide Delle Monache, Ivan Petrella
Publication Date: July 2020
Date Revised: February 2022
Keyword(s): Business cycle, Downside risk, financial conditions, score driven models, Skewness
JEL(s): C53, E32, E44
Programme Areas: Monetary Economics and Fluctuations
Link to this Page: cepr.org/active/publications/discussion_papers/dp.php?dpno=15109

We model permanent and transitory changes of the predictive density of US GDP growth. A substantial increase in downside risk to US economic growth emerges over the last 30 years, associated with the long-run growth slowdown started in the early 2000s. Conditional skewness moves procyclically, implying negatively skewed predictive densities ahead and during recessions, often anticipated by deteriorating financial conditions. Conversely, positively skewed distributions characterize expansions. The modelling framework ensures robustness to tail events, allows for both dense or sparse predictor designs, and delivers competitive out-of-sample (point, density and tail) forecasts, improving upon standard benchmarks.