Statistical identification in panel structural vector autoregressive models based on independence criteria (replication data)

DOI

This paper introduces a novel panel approach to structural vector autoregressive analysis. For identification, we impose independence of structural innovations at the pooled level. We demonstrate robustness of the method under cross-sectional correlation and heterogeneity through simulation experiments. In an empirical application on monetary policy transmission in the Euro area, we find that bond spreads rise significantly after an unexpected monetary tightening. Furthermore, the central bank responds to offset effects of adverse financial shocks. Additionally, we document sizable heterogeneity in country-specific output responses.

Identifier
DOI https://doi.org/10.15456/jae.2024044.1425287131
Metadata Access https://www.da-ra.de/oaip/oai?verb=GetRecord&metadataPrefix=oai_dc&identifier=oai:oai.da-ra.de:779339
Provenance
Creator Herwartz, Helmut; Wang, Shu
Publisher ZBW - Leibniz Informationszentrum Wirtschaft
Publication Year 2024
Rights Creative Commons Attribution 4.0 (CC-BY); Download
OpenAccess true
Contact ZBW - Leibniz Informationszentrum Wirtschaft
Representation
Language English
Resource Type Collection
Discipline Economics