KOPS - The Institutional Repository of the University of Konstanz

Identification of Structural Vector Autoregressions by Stochastic Volatility

Identification of Structural Vector Autoregressions by Stochastic Volatility

Cite This

Files in this item

Files Size Format View

There are no files associated with this item.

BERTSCHE, Dominik, Robin BRAUN, 2020. Identification of Structural Vector Autoregressions by Stochastic Volatility. In: Journal of Business & Economic Statistics. Taylor & Francis. ISSN 0735-0015. eISSN 1537-2707. Available under: doi: 10.1080/07350015.2020.1813588

@article{Bertsche2020Ident-51727, title={Identification of Structural Vector Autoregressions by Stochastic Volatility}, year={2020}, doi={10.1080/07350015.2020.1813588}, issn={0735-0015}, journal={Journal of Business & Economic Statistics}, author={Bertsche, Dominik and Braun, Robin} }

<rdf:RDF xmlns:dcterms="http://purl.org/dc/terms/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#" xmlns:bibo="http://purl.org/ontology/bibo/" xmlns:dspace="http://digital-repositories.org/ontologies/dspace/0.1.0#" xmlns:foaf="http://xmlns.com/foaf/0.1/" xmlns:void="http://rdfs.org/ns/void#" xmlns:xsd="http://www.w3.org/2001/XMLSchema#" > <rdf:Description rdf:about="https://kops.uni-konstanz.de/rdf/resource/123456789/51727"> <dcterms:issued>2020</dcterms:issued> <dc:contributor>Bertsche, Dominik</dc:contributor> <dcterms:abstract xml:lang="eng">We propose to exploit stochastic volatility for statistical identification of structural vector autoregressive models (SV-SVAR). We discuss full and partial identification of the model and develop efficient EM algorithms for maximum likelihood inference. Simulation evidence suggests that the SV-SVAR works well in identifying structural parameters also under misspecification of the variance process, particularly if compared to alternative heteroscedastic SVARs. We apply the model to study the importance of oil supply shocks for driving oil prices. Since shocks identified by heteroscedasticity may not be economically meaningful, we exploit the framework to test instrumental variable restrictions which are overidentifying in the heteroscedastic model. Our findings suggest that conventional supply shocks are negligible, while news shocks about future supply account for almost all the variation in oil prices.</dcterms:abstract> <dcterms:isPartOf rdf:resource="https://kops.uni-konstanz.de/rdf/resource/123456789/46"/> <dc:contributor>Braun, Robin</dc:contributor> <foaf:homepage rdf:resource="http://localhost:8080/jspui"/> <dcterms:title>Identification of Structural Vector Autoregressions by Stochastic Volatility</dcterms:title> <dc:language>eng</dc:language> <dspace:isPartOfCollection rdf:resource="https://kops.uni-konstanz.de/rdf/resource/123456789/46"/> <dc:creator>Bertsche, Dominik</dc:creator> <dc:creator>Braun, Robin</dc:creator> <dcterms:available rdf:datatype="http://www.w3.org/2001/XMLSchema#dateTime">2020-11-11T08:18:28Z</dcterms:available> <bibo:uri rdf:resource="https://kops.uni-konstanz.de/handle/123456789/51727"/> <void:sparqlEndpoint rdf:resource="http://localhost/fuseki/dspace/sparql"/> <dc:date rdf:datatype="http://www.w3.org/2001/XMLSchema#dateTime">2020-11-11T08:18:28Z</dc:date> </rdf:Description> </rdf:RDF>

This item appears in the following Collection(s)

Search KOPS


Browse

My Account