Multi-step forecasting in the presence of breaks
Jari Hännikäinen ()
MPRA Paper from University Library of Munich, Germany
This paper analyzes the relative performance of multi-step forecasting methods in the presence of breaks and data revisions. Our Monte Carlo simulations indicate that the type and the timing of the break affect the relative accuracy of the methods. The iterated method typically performs the best in unstable environments, especially if the parameters are subject to small breaks. This result holds regardless of whether data revisions add news or reduce noise. Empirical analysis of real-time U.S. output and inflation series shows that the alternative multi-step methods only episodically improve upon the iterated method.
Keywords: structural breaks; multi-step forecasting; intercept correction; real-time data (search for similar items in EconPapers)
JEL-codes: C22 C53 C82 (search for similar items in EconPapers)
New Economics Papers: this item is included in nep-ets, nep-for and nep-ore
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Working Paper: Multi-step forecasting in the presence of breaks (2014)
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Persistent link: https://EconPapers.repec.org/RePEc:pra:mprapa:55816
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