This paper proposes a novel approach to introduce time-variation in the variances of the structural shocks of DSGE models. The variances are allowed to evolve over time via an observation-driven updating equation. The estimation of the resulting DSGE model can be easily performed by maximum likelihood without the need of time-consuming simulation-based methods. An empirical application to a DSGE model with time-varying volatility for structural shocks shows a significant improvement in the accuracy of density forecasts.
This paper proposes a novel approach to introduce time-variation in the variances of the structural shocks of DSGE models. The variances are allowed to evolve over time via an observation-driven updating equation. The estimation of the resulting DSGE model can be easily performed by maximum likelihood without the need of time-consuming simulation-based methods. An empirical application to a DSGE model with time-varying volatility for structural shocks shows a significant improvement in the accuracy of density forecasts. (C) 2018 Elsevier B.V. All rights reserved.
DSGE Models with observation-driven time-varying volatility
Giovanni Angelini
;
2018-01-01
Abstract
This paper proposes a novel approach to introduce time-variation in the variances of the structural shocks of DSGE models. The variances are allowed to evolve over time via an observation-driven updating equation. The estimation of the resulting DSGE model can be easily performed by maximum likelihood without the need of time-consuming simulation-based methods. An empirical application to a DSGE model with time-varying volatility for structural shocks shows a significant improvement in the accuracy of density forecasts. (C) 2018 Elsevier B.V. All rights reserved.I documenti in ARCA sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.