TY - JOUR
T1 - Natural disasters as macroeconomic tail risks
AU - Chavleishvili, Sulkhan
AU - Moench, Emanuel
N1 - Publisher Copyright:
© 2024
PY - 2025/1
Y1 - 2025/1
N2 - 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.
AB - 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.
KW - Counterfactual distribution forecasts
KW - Disaster scenario analysis
KW - Quantile vector autoregression
UR - http://www.scopus.com/inward/record.url?scp=85211038077&partnerID=8YFLogxK
U2 - 10.1016/j.jeconom.2024.105914
DO - 10.1016/j.jeconom.2024.105914
M3 - Journal article
AN - SCOPUS:85211038077
SN - 0304-4076
VL - 247
JO - Journal of Econometrics
JF - Journal of Econometrics
M1 - 105914
ER -