A Bayesian panel vector autoregression to analyze the impact of climate shocks on high-income economies

Florian Huber, Tamás Krisztin, Michael Pfarrhofer

The Annals of Applied Statistics · 2023 · Volume 17 · Issue 2

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.

Keywords

Climate change impacts, commodity markets, factor stochastic volatility models, food security, hierarchical modeling, second keyword

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