Liao, WentingSheng, XinGupta, RanganKarmakar, Sayar2024-05-172024-05-172024-05Liao, W., Sheng, X., Gupta, R. et al. 2024, 'Extreme weather shocks and state-level inflation of the United States', Economics Letters, vol. 238, art. 111714, pp. 1-8, doi : 10.1016/j.econlet.2024.111714.0165-1765 (print)1873-7374 (online)10.1016/j.econlet.2024.111714http://hdl.handle.net/2263/96028DATA AVAILABILITY : Data will be made available on request.This study investigates the impact of a metric of extreme weather shocks on 32 state-level inflation rates of the United States (US) over the quarterly period of 1989:01 to 2017:04. In this regard, we first utilize a dynamic factor model with stochastic volatility (DFM-SV) to filter out the national factor from the local components of overall, non-tradable and tradable inflation rates, to ensure that the effect of regional climate risks is not underestimated, given the derived sizeable common component. Second, using impulse responses derived from linear and nonlinear local projections models, we find statistically significant increases in the state (and national) factor of overall inflation rates, with the aggregate effect being driven by the tradable sector relative to the non-tradable one, particularly across the agricultural states in comparison to the non (less)-agricultural ones. Our findings have important policy implications.en© 2024 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC license.Extreme weather shocksInflationUnited States (US)Dynamic factor model with stochastic volatility (DFM-SV)Linear and nonlinear local projectionsImpulse response functionsSDG-08: Decent work and economic growthSDG-13: Climate actionArticle