Modeling and Forecasting Macroeconomic Downside Risk

Davide Delle Monache, Andrea De Polis and Ivan Petrella

Journal of Business & Economic Statistics, 2024, vol. 42, issue 3, 1010-1025

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.

Date: 2024
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Related works:
Working Paper: Modeling and Forecasting Macroeconomic Downside Risk (2022)
Working Paper: Modeling and forecasting macroeconomic downside risk (2021)
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DOI: 10.1080/07350015.2023.2277171

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