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>), 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: | 1.3.3 |
| 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), knitr, rmarkdown, tsDyn |
| Published: | 2020-01-09 |
| 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: | 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_1.3.3.tar.gz |
| Windows binaries: | r-devel: svars_1.3.3.zip, r-release: svars_1.3.3.zip, r-oldrel: svars_1.3.3.zip |
| macOS binaries: | r-release: svars_1.3.3.tgz, r-oldrel: svars_1.3.3.tgz |
| Old sources: | svars archive |
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