Dealing with Financial Instability under a DSGE modeling approach with Banking Intermediation: a predictability analysis versus TVP-VARs

In DSGE literature there has been an increasing awareness on the role that the banking sector can play in macroeconomic activity. In most of recent works, purely financial instabilities and frictions are derived from intermediaries that affect the real economy by means of a credit channel or a balance sheet channel. We model financial intermediation as in Gertler and Karadi (2011) to take into account the bank leverage constraint in the propagation of shocks to the real economy. Within this framework, the evolution of estimated shocks and the instabilities in the structural parameters show that time-variation should be crucial in any attempted empirical analysis. However, DSGE modelling usually fails to take into account inherent nonlinearities of the economy, especially in crisis time periods. Hence, we propose a novel time-varying parameter (TVP) state-space estimation method for VAR processes both for homoskedastic and heteroskedastic error structures. We conduct an exhaustive empirical exercise that includes the comparison of the out-of-sample predictive performance of the estimated DSGE model with that of standard VARs, Bayesian VARs and TVP-VARs. Overall, a first attempt is made to find macro-financial micro-founded DSGE models as well as adaptive TVP-VARs, which are able to deal with financial instabilities via incorporating banking intermediation.