Modeling and Forecasting Macroeconomic Downside Risk

Davide Delle Monache, Andrea De Polis and Ivan Petrella

No 15109, CEPR Discussion Papers from C.E.P.R. Discussion Papers

Abstract: 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.

Keywords: Business cycle; Downside risk; Skewness; Score driven models; Financial conditions (search for similar items in EconPapers)
JEL-codes: C53 E32 E44 (search for similar items in EconPapers)
Date: 2022-02
New Economics Papers: this item is included in nep-cwa, nep-for, nep-mac and nep-rmg
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Citations: View citations in EconPapers (25)

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Related works:
Journal Article: Modeling and Forecasting Macroeconomic Downside Risk (2024)
Working Paper: Modeling and forecasting macroeconomic downside risk (2021)
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