Data-Driven Identification of SVAR Models
Description
Implements data-driven identification methods for structural vector autoregressive (SVAR) models as described in Lange et al. (2021) .
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) ), patterns of GARCH (Normadin, M., Phaneuf, L. (2004) ),
independent component analysis (Matteson, D. S, Tsay, R. S., (2013) ), least dependent innovations (Herwartz, H., Ploedt, M., (2016) ),
smooth transition in variances (Luetkepohl, H., Netsunajev, A. (2017) ) or non-Gaussian maximum likelihood (Lanne, M., Meitz, M., Saikkonen, P. (2017) )).