Statistical identification in panel structural vector autoregressive models based on independence criteria

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 experime...

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Bibliographic Details
Published in:Journal of applied econometrics (Chichester, England) Vol. 39; no. 4; pp. 620 - 639
Main Authors: Herwartz, Helmut, Wang, Shu
Format: Journal Article
Language:English
Published: Hoboken, NJ Wiley 01.06.2024
Wiley Periodicals Inc
Subjects:
Autoregressive models
Banking
Central banks
Econometrics
Euro area
Experiments
financial conditions
Heterogeneity
Identification
Independence
independent component analysis
Innovations
Monetary policy
panel data
Robustness
Simulation
Structural models
structural VAR
ISSN:1099-1255, 0883-7252, 1099-1255
Online Access:Get full text
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Summary: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.
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ISSN:1099-1255
0883-7252
1099-1255
DOI:10.1002/jae.3044