Natural Disasters as Macroeconomic Tail Risks
44 Pages Posted: 20 Dec 2023 Last revised: 27 Nov 2024
Date Written: September 09, 2023
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.
Keywords: Quantile vector autoregression, counterfactual distribution forecasts, disaster scenario analysis
JEL Classification: C22, Q54
Suggested Citation: Suggested Citation
Chavleishvili, Sulkhan and Moench, Emanuel, Natural Disasters as Macroeconomic Tail Risks (September 09, 2023). Available at SSRN: https://ssrn.com/abstract=4657195 or http://dx.doi.org/10.2139/ssrn.4657195
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