A joint impulse response function for vector autoregressive models

Bibliographic Data

ID21541763
AuthorsThomas F P Wiesen (0000-0003-4892-4707, University of Maine, corresponding author), Paul M Beaumont (0000-0001-8065-3260, Florida State University)
Year2024
Volume66
Issue4
Pages1553-1585
Publication date2024-04-01
Open AccessYes
TypeARTICLE
VenueEmpirical Economics (JOURNAL)
Journal identifiersISSN: 0377-7332 • E-ISSN: 1435-8921
PublisherSpringer Science and Business Media LLC (PUBLISHER)
DOI10.1007/s00181-023-02496-6
OpenAlexW4387129365
LanguageEN
Citations received2
References cited53

Many applications call for measuring the response due to shocks from several variables at once. We introduce a joint impulse response function (jIRF) that is independent of the order of the variables and allows for simultaneous shocks from multiple variables in the VAR, rather than one at a time as in the generalized IRF. The proposed jIRF controls for the cross-correlations of the several simultaneous shocks. As an application of the jIRF, we study the effect of the COVID-19 pandemic on trans-Atlantic volatility transmissions across large financial institutions and show that simply summing the generalized IRFs overestimates volatility transmissions

Autoregressive model · Econometrics · Economics · Impulse response · Mathematical analysis · Vector autoregression · Financial Risk and Volatility Modeling · Market Dynamics and Volatility · Mathematics · Monetary Policy and Economic Impact

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