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Modelling and Forecasting Macroeconomic Downside Risk

Author

Listed:
  • Delle-Monache, Davide

    (Bank of Italy)

  • De-Polis, Andrea

    (University of Warwick)

  • Petrella, Ivan

    (University of Warwick)

Abstract

We investigate the relation between downside risk to the economy and the financial markets within a fully parametric model. We characterize the complete predictive distribution of GDP growth employing a Skew-t distribution with time- varying location, scale, and shape, for which we model both secular trends and cyclical changes. Episodes of downside risk are characterized by increasing negative asymmetry, which emerges as a clear feature of the data. Negatively skewed pre- dictive distributions arise ahead and during recessions, and tend to be anticipated by tightening of financial conditions. Indicators of excess leverage and household credit outstanding are found to be significant drivers of downside risk. Moreover, the Great Recession marks a significant shift in the unconditional distribution of GDP growth, which has featured a distinct negative skewness since then. The model delivers competitive out-of-sample (point and density) forecasts, improving upon standard benchmarks, especially due to financial conditions providing a strong signal of increasing downside risk.

Suggested Citation

  • Delle-Monache, Davide & De-Polis, Andrea & Petrella, Ivan, 2020. "Modelling and Forecasting Macroeconomic Downside Risk," EMF Research Papers 34, Economic Modelling and Forecasting Group.
    • Handle: RePEc:wrk:wrkemf:34
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    More about this item

    Keywords

    business cycles ; financial conditions ; downside risk ; skewness ; score-driven models ;
    All these keywords.

    JEL classification:

    • E37 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Forecasting and Simulation: Models and Applications

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