Ivashchenko, SergeyCekin, Semih EmreKotze, KevinGupta, Rangan2020-03-272020-12Ivashchenko, S., Çekin, S.E., Kotzé, K. et al. Forecasting with Second-Order Approximations and Markov-Switching DSGE Models. Computational Economics 56, 747–771 (2020). https://doi.org/10.1007/s10614-019-09941-8.0927-7099 (print)1572-9974 (online)10.1007/s10614-019-09941-8http://hdl.handle.net/2263/73842This 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).en© Springer Science+Business Media New York 2019. The original publication is available at : http://link.springer.comjournal/10614.Regime-switchingSecond-order approximationNon-linear MS-DSGE estimationForecastingDynamic stochastic general equilibrium (DSGE)Postprint Article