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The long run, causality, and forecasting in the advertising-sales relationship

✍ Scribed by George P. Zanias

Publisher
John Wiley and Sons
Year
1994
Tongue
English
Weight
638 KB
Volume
13
Category
Article
ISSN
0277-6693

No coin nor oath required. For personal study only.

✦ Synopsis

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 cointegration 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 errorcorrection systems, especially in the case of multi-step forecasting.

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