The use of spline functions for forecasting in the presence of structural changes: a cautionary tale
A number of methods have been suggested to improve forecasts for data sets subject to structural breaks. This article explains why one such procedure, the spline function technique, may not be a natural candidate. An example is given where data that appeared to be well forecast using spline functions performed poorly beyond a very short forecasting horizon.
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Volume (Year): 2 (1995)
Issue (Month): 10 ()
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