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

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Tarih

2020

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Yayıncı

Springer

Erişim Hakkı

info:eu-repo/semantics/closedAccess

Özet

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).

Açıklama

Cekin, Semih Emre/0000-0003-4637-3112; Kotze, Kevin/0000-0002-7968-266X
WOS:000493933300002

Anahtar Kelimeler

Regime-Switching, Second-Order Approximation, Non-Linear Ms-Dsge Estimation, Forecasting

Kaynak

Computational Economics

WoS Q Değeri

Q3

Scopus Q Değeri

Q2

Cilt

56

Sayı

4

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