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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Vydáno v:Journal of applied econometrics (Chichester, England) Ročník 39; číslo 4; s. 620 - 639
Hlavní autoři: Herwartz, Helmut, Wang, Shu
Médium: Journal Article
Jazyk:angličtina
Vydáno: Hoboken, NJ Wiley 01.06.2024
Wiley Periodicals Inc
Témata:
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
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Shrnutí: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.
Bibliografie:ObjectType-Article-1
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ISSN:1099-1255
0883-7252
1099-1255
DOI:10.1002/jae.3044