svars: Data-Driven Identification of SVAR Models

Implements data-driven identification methods for structural vector autoregressive (SVAR) models as described in Lange et al. (2021) <doi:10.18637/jss.v097.i05>. Based on an existing VAR model object (provided by e.g. VAR() from the 'vars' package), the structural impact matrix is obtained via data-driven identification techniques (i.e. changes in volatility (Rigobon, R. (2003) <doi:10.1162/003465303772815727>), patterns of GARCH (Normadin, M., Phaneuf, L. (2004) <doi:10.1016/j.jmoneco.2003.11.002>), independent component analysis (Matteson, D. S, Tsay, R. S., (2013) <doi:10.1080/01621459.2016.1150851>), least dependent innovations (Herwartz, H., Ploedt, M., (2016) <doi:10.1016/j.jimonfin.2015.11.001>), smooth transition in variances (Luetkepohl, H., Netsunajev, A. (2017) <doi:10.1016/j.jedc.2017.09.001>) or non-Gaussian maximum likelihood (Lanne, M., Meitz, M., Saikkonen, P. (2017) <doi:10.1016/j.jeconom.2016.06.002>)).

Version: 1.3.9
Depends: R (≥ 2.10), vars (≥ 1.5.3)
Imports: expm, reshape2, ggplot2, copula, clue, pbapply, steadyICA, DEoptim, zoo, strucchange, Rcpp
LinkingTo: Rcpp, RcppArmadillo
Suggests: testthat (≥ 2.1.0), tsDyn
Published: 2022-02-04
Author: Alexander Lange [aut, cre], Bernhard Dalheimer [aut], Helmut Herwartz [aut], Simone Maxand [aut], Hannes Riebl [ctb]
Maintainer: Alexander Lange <alexander.lange at>
License: MIT + file LICENSE
NeedsCompilation: yes
Citation: svars citation info
In views: TimeSeries
CRAN checks: svars results


Reference manual: svars.pdf
Vignettes: Data-Driven Identification of SVAR Models


Package source: svars_1.3.9.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
macOS binaries: r-release (arm64): svars_1.3.9.tgz, r-release (x86_64): svars_1.3.9.tgz, r-oldrel: svars_1.3.9.tgz
Old sources: svars archive


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