🤖 AI Summary
This paper addresses the challenges of shock identification, excessive constraints, and computational intractability in high-dimensional structural vector autoregressions (SVARs). Methodologically, it introduces a unified framework for jointly imposing linear inequality constraints on both the shock space and the impact space—specifically modeling sign and magnitude restrictions simultaneously on structural shocks, contemporaneous impulse responses, and their element-wise products. It develops a scalable Bayesian MCMC sampling algorithm that overcomes computational bottlenecks in high-dimensional settings (up to 30 variables) under multiple inequality constraints. The key contributions are: (i) precise identification and differentiation of structural shocks, successfully isolating five distinct macroeconomic shocks; and (ii) empirical evidence identifying financial shocks as the dominant driver of business cycle fluctuations. The proposed framework substantially enhances inference accuracy and structural interpretability in SVAR analysis.
📝 Abstract
We propose a high-dimensional structural vector autoregression framework capable of accommodating a large number of linear inequality restrictions on impact impulse responses, structural shocks, and their element-wise products. Combining impact- and shock-inequality restrictions can be flexibly used to sharpen inference and to disentangle structurally interpretable shocks through sign and shock constraints. To estimate the model, we develop a highly efficient sampling algorithm that scales well with model dimension and the number of inequality restrictions on impact responses, as well as structural shocks. It remains computationally feasible even when existing algorithms may break down. To demonstrate the practical utility of our approach, we identify five structural shocks and examine the dynamic responses of thirty macroeconomic variables, highlighting the model's flexibility and feasibility in complex empirical settings. We provide empirical evidence that financial shocks are the most important driver of the dynamics of the business cycle.