 Exploring Monetary Policy Shocks with Large-Scale Bayesian VARsDimitris Korobilis Working Papers from Business School - Economics, University of Glasgow Abstract: I introduce a high-dimensional Bayesian vector autoregressive (BVAR) framework designed to estimate the effects of conventional monetary policy shocks. The model captures structural shocks as latent factors, enabling computationally efficient estimation in high-dimensional settings through a straightforward Gibbs sampler. By incorporating time variation in the effects of monetary policy while maintaining tractability, the methodology offers a flexible and scalable approach to empirical macroeconomic analysis using BVARs, well-suited to handle data irregularities observed in recent times. Applied to the U.S. economy, I identify monetary shocks using a combination of high-frequency surprises and sign restrictions, yielding results that are robust across a wide range of specification choices. The findings indicate that the Federal Reserve’s influence on disaggregated consumer prices fluctuated significantly during the 2022–24 high-inflation period, shedding new light on the evolving dynamics of monetary policy transmission. Keywords: Disaggregated consumer prices; Latent factors; High-dimensional Bayesian VAR; Time-varying parameters; Sign restrictions; High frequency data (search for similar items in EconPapers) Downloads: (external link) Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:gla:glaewp:2025_09 Access Statistics for this paper More papers in Working Papers from Business School - Economics, University of Glasgow Contact information at EDIRC. |
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