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.
2018
171
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10278/3703672
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