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Forecasting with Second-Order Approximations and Markov Switching DSGE Models

Author

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  • Sergey Ivashchenko

    (The Institute of Regional Economy Problems (Russian Academy of Sciences), St. Petersburg, Russia; National Research University Higher School of Economics, St. Petersburg, Russia; The Faculty of Economics of Saint-Petersburg State University, St. Petersburg, Russia and Financial Research Institute, Ministry of Finance, Russian Federation, Moscow, Russia.)

  • Semih Emre Çekin

    (Department of Economics, Turkish-German University, Istanbul, Turkey)

  • Kevin Kotzé

    (School of Economics, University of Cape Town, Rondebosch, South Africa.)

  • Rangan Gupta

    (Department of Economics, University of Pretoria, Pretoria, South Africa)

Abstract

This paper compares the out-of-sample forecasting performance of first- and second- order perturbation approximations for DSGE models that incorporate Markov-switching behaviour in the policy reaction function and the volatility of shocks. These results are compared to those of a model that does not incorporate any regime-switching. The results suggest that second-order approximations provide an improved forecasting performance in models that do not allow for regime-switching, while for the MS-DSGE models, a first-order approximation would appear to provide better out-of-sample properties. In addition, we find that over short-horizons, the MS-DSGE models provide superior forecasting results when compared to those models that do not allow for regime-switching (at both perturbation orders).

Suggested Citation

  • Sergey Ivashchenko & Semih Emre Çekin & Kevin Kotzé & Rangan Gupta, 2018. "Forecasting with Second-Order Approximations and Markov Switching DSGE Models," Working Papers 201862, University of Pretoria, Department of Economics.
    • Handle: RePEc:pre:wpaper:201862
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    Cited by:

    1. Çekin, Semih Emre & Ivashchenko, Sergey & Gupta, Rangan & Lee, Chien-Chiang, 2024. "Real-time forecast of DSGE models with time-varying volatility in GARCH form," International Review of Financial Analysis, Elsevier, vol. 93(C).

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    More about this item

    Keywords

    Regime-switching; second-order approximation; non-linear MS-DSGE estimation; forecasting;
    All these keywords.

    JEL classification:

    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • E37 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Forecasting and Simulation: Models and Applications

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