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

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  • Helmut Herwartz
  • Shu Wang

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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  • Helmut Herwartz & Shu Wang, 2024. "Statistical identification in panel structural vector autoregressive models based on independence criteria," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 39(4), pages 620-639, June.
    • Handle: RePEc:wly:japmet:v:39:y:2024:i:4:p:620-639
    DOI: 10.1002/jae.3044
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