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Forecasting in a Non-Linear DSGE Model

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  • Sergey Ivashchenko

Abstract

A medium-scale nonlinear dynamic stochastic general equilibrium (DSGE) model is estimated (54 variables, 29 state variables, 7 observed variables). The model includes a observed variable for stock market returns. The root-mean square error (RMSE) of the in-sample and out-of-sample forecasts is calculated. The nonlinear DSGE model with measurement errors outperforms AR (1), VAR (1) and the linearized DSGE in terms of the quality of the out-of-sample forecasts. The nonlinear DSGE model without measurement errors is actually of a quality equal to that of the linearized DSGE model.

Suggested Citation

  • Sergey Ivashchenko, 2014. "Forecasting in a Non-Linear DSGE Model," EUSP Department of Economics Working Paper Series 2014/02, European University at St. Petersburg, Department of Economics.
    • Handle: RePEc:eus:wpaper:ec2014_02
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    References listed on IDEAS

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    Cited by:

    1. Sergey Ivashchenko & Rangan Gupta, 2017. "Near-Rational Expectations: How Far are Surveys from Rationality?," Journal of Economics and Econometrics, Economics and Econometrics Society, vol. 60(1), pages 1-27.
    2. Sergey Ivashchenko & Rangan Gupta, 2017. "Near-Rational Expectations: How Far are Surveys from Rationality?," Journal of Economics and Econometrics, Economics and Econometrics Society, vol. 60(1), pages 1-27.

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    More about this item

    Keywords

    nonlinear DSGE; Quadratic Kalman Filter; QKF; out-of-sample forecasts;
    All these keywords.

    JEL classification:

    • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles
    • E37 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Forecasting and Simulation: Models and Applications
    • E44 - Macroeconomics and Monetary Economics - - Money and Interest Rates - - - Financial Markets and the Macroeconomy
    • E47 - Macroeconomics and Monetary Economics - - Money and Interest Rates - - - Forecasting and Simulation: Models and Applications

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