Forecasting using a Nonlinear DSGE Model

Sergey Ivashchenko and Rangan Gupta

No 201659, Working Papers from University of Pretoria, Department of Economics

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 (search for similar items in EconPapers)
JEL-codes: E32 E37 E44 E47 (search for similar items in EconPapers)
Pages: 21 pages
Date: 2016-08
New Economics Papers: this item is included in nep-cse, nep-dge, nep-ets, nep-mac and nep-ore
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Journal Article: Forecasting using a Nonlinear DSGE Model (2018)
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Persistent link: https://EconPapers.repec.org/RePEc:pre:wpaper:201659

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