Forecasting with Second-Order Approximations and Markov-Switching DSGE Models

  • Sergey Ivashchenko
  • Semih Emre Çekin
  • Kevin KotzéEmail author
  • Rangan Gupta


This paper considers 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. 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).


Regime-switching Second-order approximation Non-linear MS-DSGE estimation Forecasting 

JEL Classifications

C13 C32 E37 



The authors would like to thank the anonymous referees for valuable comments. All remaining errors are ours.

Supplementary material

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Supplementary material 1 (pdf 1968 KB)


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Authors and Affiliations

  1. 1.The Institute of Regional Economy ProblemsRussian Academy of SciencesSt. PetersburgRussia
  2. 2.National Research University Higher School of EconomicsSt. PetersburgRussia
  3. 3.The Faculty of EconomicsSaint-Petersburg State UniversitySt. PetersburgRussia
  4. 4.Financial Research Institute, Ministry of Finance, Russian FederationMoscowRussia
  5. 5.Department of EconomicsTurkish-German UniversityIstanbulTurkey
  6. 6.School of EconomicsUniversity of Cape TownRondeboschSouth Africa
  7. 7.Department of EconomicsUniversity of PretoriaPretoriaSouth Africa

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