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
References: Add references at CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
https://docs.google.com/viewer?a=v&pid=sites&srcid ... NjY1MDI2NGJkN2RmMDk0 Full text (application/pdf)

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)
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:ctn:dpaper:2018-10

Access Statistics for this paper

More papers in School of Economics Macroeconomic Discussion Paper Series from School of Economics, University of Cape Town Contact information at EDIRC.
Bibliographic data for series maintained by Kevin Kotze ().