Please use this identifier to cite or link to this item: http://hdl.handle.net/10419/37129
Authors: 
Heinen, Florian
Sibbertsen, Philipp
Kruse, Robinson
Year of Publication: 
2009
Series/Report no.: 
Diskussionspapiere der Wirtschaftswissenschaftlichen Fakultät // Wirtschaftswissenschaftliche Fakultät, Leibniz Universität Hannover 433
Abstract: 
We consider the problem of forecasting time series with long memory when the memory parameter is subject to a structural break. By means of a large-scale Monte Carlo study we show that ignoring such a change in persistence leads to substantially reduced forecasting precision. The strength of this effect depends on whether the memory parameter is increasing or decreasing over time. A comparison of six forecasting strategies allows us to conclude that pre-testing for a change in persistence is highly recommendable in our setting. In addition we provide an empirical example which underlines the importance of our findings.
JEL: 
C15
C22
C53
Document Type: 
Working Paper

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