Abstract
In this paper we assess the impact of climate shocks on futures markets for agricultural commodities and a set of macroeconomic quantities for multiple high-income economies. To capture relations among countries, markets, and climate shocks, this paper proposes parsimonious methods to estimate high-dimensional panel vector autoregressions. We assume that coefficients associated with domestic lagged endogenous variables arise from a Gaussian mixture model while further parsimony is achieved using suitable global-local shrinkage priors on several regions of the parameter space. Our results point toward pronounced global reactions of key macroeconomic quantities to climate shocks. Moreover, the empirical findings highlight substantial linkages between regionally located shocks and global commodity markets.
Funding Statement
The authors gratefully acknowledge financial support from the Oesterreichische Nationalbank (Jubilaeumsfond grant no. 17650), the Austrian Science Fund (FWF): ZK 35, the European Union’s Horizon 2020 research and innovation programme under grant agreements No 776479 and No 820712.
Acknowledgments
This paper is a substantially revised version of a manuscript titled “Dealing with cross-country heterogeneity in panel VARs using finite mixture models.”
Citation
Florian Huber. Tamás Krisztin. Michael Pfarrhofer. "A Bayesian panel vector autoregression to analyze the impact of climate shocks on high-income economies." Ann. Appl. Stat. 17 (2) 1543 - 1573, June 2023. https://doi.org/10.1214/22-AOAS1681
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