Forecasting using a Nonlinear DSGE Model

Sergey Ivashchenko and Rangan Gupta

Journal of Central Banking Theory and Practice, 2018, vol. 7, issue 2, 73-98

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.

Keywords: Nonlinear DSGE; Quadratic Kalman Filter; Out-of-sample forecasts. (search for similar items in EconPapers)
JEL-codes: E32 E37 E44 E47 (search for similar items in EconPapers)
Date: 2018
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Citations: View citations in EconPapers (1)

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Working Paper: Forecasting using a Nonlinear DSGE Model (2016)
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Persistent link: https://EconPapers.repec.org/RePEc:cbk:journl:v:7:y:2018:i:2:p:73-98

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