svars: Data-Driven Identification of SVAR Models

Implements data-driven identification methods for structural vector autoregressive (SVAR) models. 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>), least dependent innovations (Herwartz, H., Ploedt, M., (2016) <doi:10.1016/j.jimonfin.2015.11.001>) or non-Gaussian maximum likelihood (Lanne, M., Meitz, M., Saikkonen, P. (2017) <doi:10.1016/j.jeconom.2016.06.002>).

Version: 1.0.0
Imports: vars, expm, reshape2, ggplot2, copula, clue, pbapply, steadyICA, tsDyn, DEoptim
Published: 2017-11-09
Author: Alexander Lange [aut, cre], Bernhard Dalheimer [aut], Helmut Herwartz [aut], Simone Maxand [aut], Hannes Riebl [ctb]
Maintainer: Alexander Lange <alexander.lange at uni-goettingen.de>
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
NeedsCompilation: no
Materials: README
In views: TimeSeries
CRAN checks: svars results

Downloads:

Reference manual: svars.pdf
Package source: svars_1.0.0.tar.gz
Windows binaries: r-devel: svars_1.0.0.zip, r-release: svars_1.0.0.zip, r-oldrel: svars_1.0.0.zip
OS X El Capitan binaries: r-release: svars_1.0.0.tgz
OS X Mavericks binaries: r-oldrel: svars_1.0.0.tgz

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