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.
Volume (Year): 2 (1995)
Issue (Month): 10 ()
|Contact details of provider:|| Web page: http://www.tandfonline.com/RAEL20|
|Order Information:||Web: http://www.tandfonline.com/pricing/journal/RAEL20|
When requesting a correction, please mention this item's handle: RePEc:taf:apeclt:v:2:y:1995:i:10:p:409-411. See general information about how to correct material in RePEc.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Michael McNulty)
If references are entirely missing, you can add them using this form.