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A new approach to multi-step forecasting using dynamic stochastic general equilibrium models

Author

Listed:
  • George Kapetanious

    (Bank of England)

  • Simon Price

    (Bank of England)

  • Konstantinos Theodoridis

    (Bank of England)

Abstract

DSGE models are of interest because they offer structural interpretations, but are also increasingly used for forecasting. Estimation often proceeds by methods which involve building the likelihood by one-step ahead (h=1) prediction errors. However in principle this can be done using different horizons where h>1. Using the well-known model of Smets and Wouters (2007), for h=1 classical ML parameter estimates are similar to those originally reported. As h extends some estimated parameters change, but not to an economically significant degree. Forecast performance is often improved, in several cases significantly.

Suggested Citation

  • George Kapetanious & Simon Price & Konstantinos Theodoridis, 2015. "A new approach to multi-step forecasting using dynamic stochastic general equilibrium models," Bank of England working papers 567, Bank of England.
    • Handle: RePEc:boe:boeewp:0567
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    References listed on IDEAS

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    Cited by:

    1. Michal Franta, 2016. "Iterated Multi-Step Forecasting with Model Coefficients Changing Across Iterations," Working Papers 2016/05, Czech National Bank, Research and Statistics Department.

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    Keywords

    DSGE models; multi-step prediction errors; forecasting.;
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