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

In this paper we assess the impact of climate shocks on futures markets for agricultural commodities and a set macroeconomic quantities multiple high-income economies. To capture relations among countries, markets, shocks, proposes parsimonious methods to estimate high-dimensional panel vector autoregressions. We assume that coefficients associated with domestic lagged endogenous variables arise from Gaussian mixture model while further parsimony is achieved using suitable global-local shrinkage priors several regions parameter space. Our results point toward pronounced global reactions key shocks. Moreover, empirical findings highlight substantial linkages between regionally located commodity markets.