The use of spline functions for forecasting in the presence of structural changes: a cautionary tale

Abstract

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.