Ivashchenko, SergeyÇekin, Semih EmreKotze, KevinGupta, RanganÇekin, Semih Emre2021-01-082021-01-0820200927-70991572-9974http://doi.org/10.1007/s10614-019-09941-8https://hdl.handle.net/20.500.12846/182Cekin, Semih Emre/0000-0003-4637-3112; Kotze, Kevin/0000-0002-7968-266XWOS:000493933300002This 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).eninfo:eu-repo/semantics/closedAccessRegime-SwitchingSecond-Order ApproximationNon-Linear Ms-Dsge EstimationForecastingArticle56410.1007/s10614-019-09941-8747771Q3Q2WOS:0004939333000022-s2.0-85074861844