Now showing 1 - 3 of 3
  • Publication
    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.
    Scopus© Citations 11  334
  • Publication
    Forecasting with Instabilities: an Application to DSGE Models with Financial Frictions
    (University College Dublin. School of Economics, 2015-10) ; ;
    This paper examines whether the presence of parameter instabilities in dynamic stochastic general equilibrium (DSGE) models affects their forecasting performance. We apply this analysis to medium-scale DSGE models with and without financial frictions for the US economy. Over the forecast period 2001-2013, the models augmented with financial frictions lead to an improvement in forecasts for inflation and the short term interest rate, while for GDP growth rate the performance depends on the horizon/period. We interpret this finding taking into account parameters instabilities. Fluctuation test shows that models with financial frictions outperform in forecasting inflation but not the GDP growth rate.
      639
  • Publication
    Dealing with Financial Instability under a DSGE modeling approach with Banking Intermediation: a predictability analysis versus TVP-VARs
    (University College Dublin. School of Economics, 2016-08) ; ; ;
    In the dynamic stochastic general equilibrium (DSGE) literature there has been an increasing awareness on the role that the banking sector can play in macroeconomic activity. We present a DSGE model with financial intermediation as in Gertler and Karadi (2011). The estimation of shocks and of the structural parameters shows that time-variation should be crucial in any attempted empirical analysis. Since DSGE modelling usually fails to take into account inherent nonlinearities of the economy, 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 to compare the out-of-sample predictive performance of the estimated DSGE model with that of standard ARs, VARs, Bayesian VARs and TVP-VARs. We find that the TVP-VAR provides the best forecasting performance for the series of GDP and net worth of financial intermediaries for all steps-ahead, while the DSGE model outperforms the other specifications in forecasting inflation and the federal funds rate at shorter horizons.
      486