Forecasting using a Nonlinear DSGE Model

Artikel

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.

Object Details

• Language: Englisch

References and Relationships

• Bibliographic citation: Journal: Journal of Central Banking Theory and Practice ; ISSN: 2336-9205 ; Volume: 7 ; Year: 2018 ; Issue: 2 ; Pages: 73-98 ; Warsaw: De Gruyter Open

Classification and Topics

• Classification: Wirtschaft ; Business Fluctuations; Cycles ; Prices, Business Fluctuations, and Cycles: Forecasting and Simulation: Models and Applications ; Financial Markets and the Macroeconomy ; Money and Interest Rates: Forecasting and Simulation: Models and Applications
• Subject: Nonlinear DSGE ; Quadratic Kalman Filter ; Out-of-sample forecasts.

Contributors, Places and Time

• Event: Geistige Schöpfung
• (who): Ivashchenko, Sergey ; Gupta, Rangan
• Event: Veröffentlichung
• (who): De Gruyter Open
• (where): Warsaw
• (when): 2018

Further information

• DOI: doi:10.2478/jcbtp-2018-0013
• Handle: http://hdl.handle.net/10419/217645
• Last update: 10.03.2025, 11:42 AM CET