Forecasting with Second-Order Approximations and Markov Switching DSGE Models

Sergey Ivashchenko, Semih Çekin, Kevin Kotze and Rangan Gupta
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Semih Çekin: Department of Economics, Turkish-German University, Istanbul, Turkey

No 201862, Working Papers from University of Pretoria, Department of Economics

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).

Keywords: Regime-switching; second-order approximation; non-linear MS-DSGE estimation; forecasting (search for similar items in EconPapers)
JEL-codes: C13 C32 E37 (search for similar items in EconPapers)
Pages: 16 pages
Date: 2018-09
New Economics Papers: this item is included in nep-dge, nep-for, nep-mac and nep-ore
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Related works:
Journal Article: Forecasting with Second-Order Approximations and Markov-Switching DSGE Models (2020)
Working Paper: Forecasting with second-order approximations and Markov-switching DSGE models (2018)
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Persistent link: https://EconPapers.repec.org/RePEc:pre:wpaper:201862

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