The standard time-varying VAR workhorse suffers from overparameterization, which is a serious problem as it limits the number of variables and lags that can be incorporated in the model.
Read also: <a href="http://www.cpb.nl/en/publication/time-variation-dynamic-effects-in-the-unanticipated-changes-in-tax-policy">CPB Discussion Paper 271</a> '<em>Time variation in the dynamic effects of unanticipated changes in tax policy</em>'.
As a solution for the overparameterization problem, we propose a new, more parsimonious time-varying VAR model setup with which we can reliably estimate larger models including more variables and/or more lags than was possible until now. The new model setup implies cross-equation restrictions on the time variation that are empirically supported, theoretically appealing, and make the Bayesian estimation procedure much faster.
