Article ID: | iaor19951353 |
Country: | United Kingdom |
Volume: | 13 |
Issue: | 7 |
Start Page Number: | 601 |
End Page Number: | 610 |
Publication Date: | Dec 1994 |
Journal: | International Journal of Forecasting |
Authors: | Zanias G.P. |
Keywords: | marketing, forecasting: applications |
Co-integration analysis is used in a study of the advertising and sales relationship using the Lydia Pinkham data set. The series are shown to have a valid long-run relationship while Granger-causality runs in both directions. The latter is found by using a causality test involving the co-integration restrictions which seem to constitute a crucial part of such tests in the case of co-integrated variables. A comparison with previous models shows that forecasting co-integrated series is more accurate with error-correction systems, especially in the case of multi-step forecasting.