svars

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)).

Last 30 days

This package has been downloaded 1,025 times in the last 30 days. Now we’re talking! This work is officially 'heard of in academic circles', just like those wild research papers on synthetic bananas. The following heatmap shows the distribution of downloads per day. Yesterday, it was downloaded 14 times.

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Last 365 days

This package has been downloaded 11,129 times in the last 365 days. The academic equivalent of having a dedicated subreddit. There are fans, and maybe even a few trolls! The day with the most downloads was Nov 13, 2024 with 125 downloads.

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