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

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http://hdl.handle.net/10138/335987

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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

Titel: svars: An R Package for Data-Driven Identification in Multivariate Time Series Analysis
Författare: Lange, Alexander; Dalheimer, Bernhard; Herwartz, Helmut; Maxand, Simone
Upphovmannens organisation: Economics
Helsinki Institute of Sustainability Science (HELSUS)
Datum: 2021-03
Språk: eng
Sidantal: 34
Tillhör serie: Journal of Statistical Software
ISSN: 1548-7660
DOI: https://doi.org/10.18637/jss.v097.i05
Permanenta länken (URI): http://hdl.handle.net/10138/335987
Abstrakt: 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.
Subject: 112 Statistics and probability
113 Computer and information sciences
SVAR models
identification
independent components
non-Gaussian maximum likelihood
changes in volatility
smooth transition covariance
R
STRUCTURAL VECTOR AUTOREGRESSIONS
INDEPENDENT COMPONENT ANALYSIS
MONETARY-POLICY SHOCKS
CONDITIONAL HETEROSKEDASTICITY
STATISTICAL IDENTIFICATION
MODELS
BOOTSTRAP
INFERENCE
DYNAMICS
TESTS
Referentgranskad: Ja
Licens: cc_by
Användningsbegränsning: openAccess
Parallelpublicerad version: publishedVersion


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