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)).

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