Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/217645 
Year of Publication: 
2018
Citation: 
[Journal:] Journal of Central Banking Theory and Practice [ISSN:] 2336-9205 [Volume:] 7 [Issue:] 2 [Publisher:] De Gruyter Open [Place:] Warsaw [Year:] 2018 [Pages:] 73-98
Publisher: 
De Gruyter Open, Warsaw
Abstract: 
A medium-scale nonlinear dynamic stochastic general equilibrium (DSGE) model was estimated (54 variables, 29 state variables, 7 observed variables). The model includes an observed variable for stock market returns. The root-mean square error (RMSE) of the in-sample and out-of-sample forecasts was calculated. The nonlinear DSGE model with measurement errors outperforms AR (1), VAR (1) and the linearised DSGE in terms of the quality of the out-of-sample forecasts. The nonlinear DSGE model without measurement errors is of a quality equal to that of the linearised DSGE model.
Subjects: 
Nonlinear DSGE
Quadratic Kalman Filter
Out-of-sample forecasts.
JEL: 
E32
E37
E44
E47
Persistent Identifier of the first edition: 
Creative Commons License: 
cc-by-nc-nd Logo
Document Type: 
Article

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