Optimal forecasts in the presence of structural breaks

Mohammad Pesaran, Andreas Pick and Mikhail Pranovich

Journal of Econometrics, 2013, vol. 177, issue 2, 134-152

Abstract: This paper considers the problem of forecasting under continuous and discrete structural breaks and proposes weighting observations to obtain optimal forecasts in the MSFE sense. We derive optimal weights for one step ahead forecasts. Under continuous breaks, our approach largely recovers exponential smoothing weights. Under discrete breaks, we provide analytical expressions for optimal weights in models with a single regressor, and asymptotically valid weights for models with more than one regressor. It is shown that in these cases the optimal weight is the same across observations within a given regime and differs only across regimes. In practice, where information on structural breaks is uncertain, a forecasting procedure based on robust optimal weights is proposed. The relative performance of our proposed approach is investigated using Monte Carlo experiments and an empirical application to forecasting real GDP using the yield curve across nine industrial economies.

Keywords: Forecasting; Structural breaks; Optimal weights; Robust optimal weights; Exponential smoothing (search for similar items in EconPapers)
JEL-codes: C22 C53 (search for similar items in EconPapers)
Date: 2013
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (95)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:econom:v:177:y:2013:i:2:p:134-152

DOI: 10.1016/j.jeconom.2013.04.002

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