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Natural disasters as macroeconomic tail risks

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  • Chavleishvili, Sulkhan
  • Moench, Emanuel

Abstract

We introduce quantile and moment impulse response functions for structural quantile vector autoregressive models. We use them to study how climate-related natural disasters affect the predictive distribution of output growth and inflation. Disasters strongly shift the forecast distribution particularly in the tails. They result in an initial sharp increase of the downside risk for growth, followed by a temporary rebound. Upside risk to inflation increases markedly for a few months and then subsides. As a result, natural disasters have a persistent impact on the conditional variance and skewness of macroeconomic aggregates which standard linear models estimating conditional mean dynamics fail to match. We perform a scenario analysis to evaluate the hypothetical effects of more frequent large disasters on the macroeconomy due to increased atmospheric carbon concentration. Our results indicate a substantially higher conditional volatility of growth and inflation as well as increased upside risk to inflation particularly in a scenario where only currently pledged climate policies are implemented.

Suggested Citation

  • Chavleishvili, Sulkhan & Moench, Emanuel, 2025. "Natural disasters as macroeconomic tail risks," Journal of Econometrics, Elsevier, vol. 247(C).
  • Handle: RePEc:eee:econom:v:247:y:2025:i:c:s0304407624002653
    DOI: 10.1016/j.jeconom.2024.105914
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    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • Q54 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Climate; Natural Disasters and their Management; Global Warming

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