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Forecasting with second-order approximations and Markov-switching DSGE models

Sergey Ivashchenko, Semih Çekin, Kevin Kotze () and Rangan Gupta ()

No 2018-10, School of Economics Macroeconomic Discussion Paper Series from School of Economics, University of Cape Town

Abstract: 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).

Date: 2018
New Economics Papers: this item is included in nep-dge, nep-for and nep-ore
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Related works:
Journal Article: Forecasting with Second-Order Approximations and Markov-Switching DSGE Models (2020) Downloads
Working Paper: Forecasting with Second-Order Approximations and Markov Switching DSGE Models (2018)
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