Climate risks and forecastability of US inflation: Evidence from dynamic quantile model averaging

This study examines the impact of climate-related risks on the inflation rates of the United States, focusing on the overall Consumer Price Index (CPI) and its significant components, namely food and beverages and housing inflation. Employing quantile regression models and a comprehensive dataset spanning from January 1985 to September 2022, we analyze five specific climate risk factors alongside traditional macroeconomic predictors. Our findings indicate that models incorporating individual climate risks generally outperform those considering only macroeconomic factors. However, model combination strategies that integrate all five climate risk measures consistently deliver superior forecasting performance. Furthermore, climate risks exert differential impacts on food & beverage inflation and housing inflation. In the short- and medium-term, climate risks are more likely to influence food & beverage inflation, while over the medium- and long-term, they predominantly affect housing inflation. This research highlights the crucial role of climate factors in forecasting inflation, suggesting potential avenues for enhancing economic policy-making in light of evolving climate conditions.