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Assessing Macroeconomic Tail Risk

Author

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  • Francesca Loria
  • Christian Matthes
  • Donghai Zhang

Abstract

Real gross domestic product and industrial production in the United States display substantial asymmetry and tail risk. Is this asymmetry driven by a specific structural shock? Our empirical approach, based on quantile regressions and local projections, suggests otherwise. We find that the tenth percentile of predictive growth distributions responds between three and six times more than the median to monetary policy shocks, financial shocks, uncertainty shocks, and oil price shocks, indicating a common transmission mechanism. We present two data-generating processes that are capable of matching this finding: a threshold vector autoregression model and a non-linear equilibrium model.

Suggested Citation

  • Francesca Loria & Christian Matthes & Donghai Zhang, 2025. "Assessing Macroeconomic Tail Risk," The Economic Journal, Royal Economic Society, vol. 135(665), pages 264-284.
    • Handle: RePEc:oup:econjl:v:135:y:2025:i:665:p:264-284.
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    File URL: http://hdl.handle.net/10.1093/ej/ueae066
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