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

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

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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:
Keywords: marketing, forecasting: applications
Abstract:

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.

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