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

Author(s)
Tamás Krisztin, Florian Huber, Michael Pfarrhofer
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.

Organisation(s)
Department of Economics
External organisation(s)
Paris-Lodron Universität Salzburg, International Institute for Applied Systems Analysis
Journal
The Annals of Applied Statistics
Volume
17
Pages
1543-1573
No. of pages
31
ISSN
1932-6157
DOI
https://doi.org/10.1214/22-AOAS1681
Publication date
09-2022
Peer reviewed
Yes
Austrian Fields of Science 2012
502025 Econometrics, 502018 Macroeconomics
Keywords
ASJC Scopus subject areas
Statistics and Probability, Statistics, Probability and Uncertainty, Modelling and Simulation
Portal url
https://ucrisportal.univie.ac.at/en/publications/55de0d69-1290-4508-93d6-7eccdb2594b3