🤖 AI Summary
This study addresses the challenges of identifying country-specific macroeconomic shocks and their international transmission in multi-country systems—namely, the curse of dimensionality, heavy computational burden, and proliferating identification restrictions—by proposing a Bayesian Structural Matrix Autoregressive (BSMAR) framework. The approach exploits the natural matrix structure of international macroeconomic data to disentangle cross-variable and cross-country dependencies, enabling parsimonious modeling of large systems. It innovatively integrates conventional SVAR identification strategies with a novel method for identifying contemporaneous international spillovers, coherently accommodating zero restrictions, sign restrictions, and ordering constraints. Empirical analysis using quarterly data from 15 economies reveals substantial heterogeneity in cross-border shock transmission and demonstrates that demand shocks play a more prominent role than supply shocks in generating international spillovers.
📝 Abstract
Understanding how macroeconomic shocks propagate across countries requires structural models that can jointly identify country-specific shocks and their international transmission. Yet extending structural vector autoregressions (SVARs) to large multi-country systems is challenging due to rapidly increasing dimensionality, computational costs, and the proliferation of identifying restrictions. This paper develops a Bayesian Structural Matrix Autoregression (BSMAR) framework that exploits the natural matrix structure of international macroeconomic data. By separating dependence across economic variables from dependence across countries, the framework provides a parsimonious representation that substantially reduces the dimensionality of large structural systems. We develop a Bayesian sampling algorithm for posterior inference that accommodates zero, sign, and ranking (magnitude) restrictions, allowing established SVAR identification schemes to be combined with a novel approach to identifying contemporaneous international spillovers. Applying the model to quarterly data for 15 economies, we find substantial heterogeneity in international shock transmission, with demand shocks playing a more prominent role than supply shocks in generating cross-country spillovers.