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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| Veröffentlicht in: | Journal of applied econometrics (Chichester, England) Jg. 39; H. 4; S. 620 - 639 |
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| Hauptverfasser: | , |
| Format: | Journal Article |
| Sprache: | Englisch |
| Veröffentlicht: |
Hoboken, NJ
Wiley
01.06.2024
Wiley Periodicals Inc |
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| ISSN: | 1099-1255, 0883-7252, 1099-1255 |
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| Abstract | 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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| AbstractList | 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. 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. |
| Author | Wang, Shu Herwartz, Helmut |
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| Snippet | This paper introduces a novel panel approach to structural vector autoregressive analysis. For identification, we impose independence of structural innovations... Summary This paper introduces a novel panel approach to structural vector autoregressive analysis. For identification, we impose independence of structural... |
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| SubjectTerms | 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 |
| Title | Statistical identification in panel structural vector autoregressive models based on independence criteria |
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