Directed Graphs and Variable Selection in Large Vector Autoregressive Models

Bertsche, Dominik; Brüggemann, Ralf; Kascha, Christian

Directed Graphs and Variable Selection in Large Vector Autoregressive Models

Dateien

Bertsche_2-3v0y8gfx8bn91.pdfGröße: 922.97 KBDownloads: 13

Datum

2023

Autor:innen

Bertsche, Dominik

Brüggemann, Ralf

Kascha, Christian

Open Access-Veröffentlichung

Open Access Hybrid

Sammlungen

Wirtschaftswissenschaften

Publikationstyp

Zeitschriftenartikel

Publikationsstatus

Published

Erschienen in

Journal of Time Series Analysis. Wiley. 2023, 44(2), pp. 223-246. ISSN 0143-9782. eISSN 1467-9892. Available under: doi: 10.1111/jtsa.12664

Zusammenfassung

We represent the dynamic relation among variables in vector autoregressive (VAR) models as directed graphs. Based on these graphs, we identify so-called strongly connected components (SCCs). Using this graphical representation, we consider the problem of variable choice. We use the relations among the strongly connected components to select variables that need to be included in a VAR if interest is in impulse response analysis of a given set of variables. Our theoretical contributions show that the set of selected variables from the graphical method coincides with the set of variables that is multi-step causal for the variables of interest by relating the paths in the graph to the coefficients of the ‘direct’ VAR representation. An empirical application illustrates the usefulness of the suggested approach: Including the selected variables into a small US monetary VAR is useful for impulse response analysis as it avoids the well-known ‘price-puzzle’.

Fachgebiet (DDC)

330 Wirtschaft

Schlagwörter

Vector autoregression, Variable selection, Directed graphs, Multi-step causality, Impulse response analysis

Zitieren

ISO 690

BERTSCHE, Dominik, Ralf BRÜGGEMANN, Christian KASCHA, 2023. Directed Graphs and Variable Selection in Large Vector Autoregressive Models. In: Journal of Time Series Analysis. Wiley. 2023, 44(2), pp. 223-246. ISSN 0143-9782. eISSN 1467-9892. Available under: doi: 10.1111/jtsa.12664

BibTex

@article{Bertsche2023Direc-58175,
  year={2023},
  doi={10.1111/jtsa.12664},
  title={Directed Graphs and Variable Selection in Large Vector Autoregressive Models},
  number={2},
  volume={44},
  issn={0143-9782},
  journal={Journal of Time Series Analysis},
  pages={223--246},
  author={Bertsche, Dominik and Brüggemann, Ralf and Kascha, Christian},
  note={Financial support by the Deutsche Forschungsgemeinschaft, Grant number BR 2941/3-1 is gratefully acknowledged.}
}

RDF

<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/server/rdf/resource/123456789/58175">
    <void:sparqlEndpoint rdf:resource="http://localhost/fuseki/dspace/sparql"/>
    <dcterms:abstract xml:lang="eng">We represent the dynamic relation among variables in vector autoregressive (VAR) models as directed graphs. Based on these graphs, we identify so-called strongly connected components (SCCs). Using this graphical representation, we consider the problem of variable choice. We use the relations among the strongly connected components to select variables that need to be included in a VAR if interest is in impulse response analysis of a given set of variables. Our theoretical contributions show that the set of selected variables from the graphical method coincides with the set of variables that is multi-step causal for the variables of interest by relating the paths in the graph to the coefficients of the ‘direct’ VAR representation. An empirical application illustrates the usefulness of the suggested approach: Including the selected variables into a small US monetary VAR is useful for impulse response analysis as it avoids the well-known ‘price-puzzle’.</dcterms:abstract>
    <dc:creator>Brüggemann, Ralf</dc:creator>
    <dc:contributor>Brüggemann, Ralf</dc:contributor>
    <dcterms:available rdf:datatype="http://www.w3.org/2001/XMLSchema#dateTime">2022-07-27T12:03:59Z</dcterms:available>
    <dc:rights>terms-of-use</dc:rights>
    <dc:contributor>Bertsche, Dominik</dc:contributor>
    <dcterms:hasPart rdf:resource="https://kops.uni-konstanz.de/bitstream/123456789/58175/1/Bertsche_2-3v0y8gfx8bn91.pdf"/>
    <bibo:uri rdf:resource="https://kops.uni-konstanz.de/handle/123456789/58175"/>
    <dcterms:title>Directed Graphs and Variable Selection in Large Vector Autoregressive Models</dcterms:title>
    <dcterms:issued>2023</dcterms:issued>
    <dc:creator>Kascha, Christian</dc:creator>
    <foaf:homepage rdf:resource="http://localhost:8080/"/>
    <dcterms:isPartOf rdf:resource="https://kops.uni-konstanz.de/server/rdf/resource/123456789/46"/>
    <dc:date rdf:datatype="http://www.w3.org/2001/XMLSchema#dateTime">2022-07-27T12:03:59Z</dc:date>
    <dc:language>eng</dc:language>
    <dspace:isPartOfCollection rdf:resource="https://kops.uni-konstanz.de/server/rdf/resource/123456789/46"/>
    <dspace:hasBitstream rdf:resource="https://kops.uni-konstanz.de/bitstream/123456789/58175/1/Bertsche_2-3v0y8gfx8bn91.pdf"/>
    <dcterms:rights rdf:resource="https://rightsstatements.org/page/InC/1.0/"/>
    <dc:creator>Bertsche, Dominik</dc:creator>
    <dc:contributor>Kascha, Christian</dc:contributor>
  </rdf:Description>
</rdf:RDF>

Kommentar zur Publikation

Financial support by the Deutsche Forschungsgemeinschaft, Grant number BR 2941/3-1 is gratefully acknowledged.

Universitätsbibliographie

Ja

Begutachtet

Ja