Modeling and forecasting macroeconomic downside risk

Delle Monache, Davide and De Polis, Andrea and Petrella, Ivan (2024) Modeling and forecasting macroeconomic downside risk. Journal of Business and Economic Statistics, 42 (3). pp. 1010-1025. ISSN 0735-0015 (https://doi.org/10.1080/07350015.2023.2277171)

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Abstract

We model permanent and transitory changes of the predictive density of U.S. GDP growth. A substantial increase in downside risk to U.S. 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 modeling 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.

ORCID iDs

Delle Monache, Davide, De Polis, Andrea ORCID logoORCID: https://orcid.org/0000-0002-0483-2643 and Petrella, Ivan;
CORE (COnnecting REpositories)