March 25, 2014

Reduced-rank time-varying vector autoregressions

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.
No title

Read also: CPB Discussion Paper 271 'Time variation in the dynamic effects of unanticipated changes in tax policy'.

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.

Authors

Joris de Wind
Luca Gambetti