svars: An R Package for Data-Driven Identification in Multivariate Time Series Analysis

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dc.contributor.author Lange, Alexander
dc.contributor.author Dalheimer, Bernhard
dc.contributor.author Herwartz, Helmut
dc.contributor.author Maxand, Simone
dc.date.accessioned 2021-11-03T10:42:01Z
dc.date.available 2021-11-03T10:42:01Z
dc.date.issued 2021-03
dc.identifier.citation Lange , A , Dalheimer , B , Herwartz , H & Maxand , S 2021 , ' svars: An R Package for Data-Driven Identification in Multivariate Time Series Analysis ' , Journal of Statistical Software , vol. 97 , no. 5 . https://doi.org/10.18637/jss.v097.i05
dc.identifier.other PURE: 142703692
dc.identifier.other PURE UUID: 2a294eea-3f6c-447c-bbdd-980d50736d86
dc.identifier.other WOS: 000656565600001
dc.identifier.other ORCID: /0000-0002-3153-7922/work/102574142
dc.identifier.uri http://hdl.handle.net/10138/335987
dc.description.abstract Structural vector autoregressive (SVAR) models are frequently applied to trace the contemporaneous linkages among (macroeconomic) variables back to an interplay of orthogonal structural shocks. Under Gaussianity the structural parameters are unidentified without additional (often external and not data-based) information. In contrast, the often reasonable assumption of heteroskedastic and/or non-Gaussian model disturbances offers the possibility to identify unique structural shocks. We describe the R package svars which implements statistical identification techniques that can be both heteroskedasticity-based or independence-based. Moreover, it includes a rich variety of analysis tools that are well known in the SVAR literature. Next to a comprehensive review of the theoretical background, we provide a detailed description of the associated R functions. Furthermore, a macroeconomic application serves as a step-by-step guide on how to apply these functions to the identification and interpretation of structural VAR models. en
dc.format.extent 34
dc.language.iso eng
dc.relation.ispartof Journal of Statistical Software
dc.rights cc_by
dc.rights.uri info:eu-repo/semantics/openAccess
dc.subject 112 Statistics and probability
dc.subject 113 Computer and information sciences
dc.subject SVAR models
dc.subject identification
dc.subject independent components
dc.subject non-Gaussian maximum likelihood
dc.subject changes in volatility
dc.subject smooth transition covariance
dc.subject R
dc.subject STRUCTURAL VECTOR AUTOREGRESSIONS
dc.subject INDEPENDENT COMPONENT ANALYSIS
dc.subject MONETARY-POLICY SHOCKS
dc.subject CONDITIONAL HETEROSKEDASTICITY
dc.subject STATISTICAL IDENTIFICATION
dc.subject MODELS
dc.subject BOOTSTRAP
dc.subject INFERENCE
dc.subject DYNAMICS
dc.subject TESTS
dc.title svars: An R Package for Data-Driven Identification in Multivariate Time Series Analysis en
dc.type Article
dc.contributor.organization Economics
dc.contributor.organization Helsinki Institute of Sustainability Science (HELSUS)
dc.description.reviewstatus Peer reviewed
dc.relation.doi https://doi.org/10.18637/jss.v097.i05
dc.relation.issn 1548-7660
dc.rights.accesslevel openAccess
dc.type.version publishedVersion
dc.identifier.url https://cran.r-project.org/web/packages/svars/vignettes/svars.pdf

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