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svars  

Data-Driven Identification of SVAR Models
View on CRAN: Click here


Download and install svars package within the R console
Install from CRAN:
install.packages("svars")

Install from Github:
library("remotes")
install_github("cran/svars")

Install by package version:
library("remotes")
install_version("svars", "1.3.12")



Attach the package and use:
library("svars")
Maintained by
Alexander Lange
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2017-11-09
Latest Update: 2025-09-03
Description:
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>)).
How to cite:
Alexander Lange (2017). svars: Data-Driven Identification of SVAR Models. R package version 1.3.12, https://cran.r-project.org/web/packages/svars. Accessed 18 Sep. 2026.
Previous versions and publish date:
(2026-07-09 07:11), 1.0.0 (2017-11-09 12:36), 1.0.1 (2017-12-13 10:37), 1.1.0 (2018-01-16 13:25), 1.1.1 (2018-02-14 18:56), 1.1.2 (2018-03-06 11:28), 1.2.0 (2018-06-07 19:43), 1.2.1 (2018-08-08 16:40), 1.2.2 (2018-11-17 15:10), 1.3.0 (2019-06-28 17:00), 1.3.1 (2019-07-26 00:20), 1.3.2 (2019-09-10 18:20), 1.3.3 (2020-01-09 19:50), 1.3.4 (2020-11-12 07:00), 1.3.5 (2020-11-23 11:50), 1.3.6 (2021-01-13 14:50), 1.3.7 (2021-03-19 00:30), 1.3.8 (2021-08-06 17:40), 1.3.9 (2022-02-04 16:00), 1.3.11 (2023-02-06 11:00)
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