The authors investigate the measurement of the sales-advertising relationship with temporally aggregated data. Previous work has produced encouraging results for recovering micro-level parameters of the brand loyal model from data aggregated over time, but the Koyck model has not been studied in this context. The authors develop methods for recovering micro parameters of the Koyck model and extend the results for the brand loyal model. The results are supported by simulation experiments examining both asymptotic and small-sample properties.
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References
1.
BassFrank M., and LeoneRobert P. (1983a), “Temporal Aggregation, the Data Interval Bias, and Empirical Estimation of Bimonthly Relations from Annual Data,”Management Science, 29(January), 1–11.
2.
BassFrank M., and LeoneRobert P. (1986), “Estimating Micro Relationships from Macro Data: A Comparative Study of Two Approximations of the Brand Loyal Model Under Temporal Aggregation,”Journal of Marketing Research, 23(August), 291–7.
3.
ClarkeDarrall G. (1976), “Econometric Measurement of the Duration of Advertising Effect on Sales,”Journal of Marketing Research, 13(November), 345–57.
4.
MoriguchiC. (1970), “Aggregation Over Time in Macroeco-nomic Relations,”International Economics Review (October), 427–40.
5.
PaldaKristian (1964), The Measurement of Cumulative Advertising Effects.Englewood Cliffs, NJ: Prentice-Hall, Inc.
6.
WeinbergCharles B., and WeissDoyle L. (1982), “On the Econometric Measurement of the Duration of Advertising Effect on Sales,”Journal of Marketing Research, 19(November), 585–91.
7.
WeissDoyle L., WeinbergCharles B., and WindalPierre M. (1983), “The Effects of Serial Correlation and Data Aggregation on Advertising Measurement,”Journal of Marketing Research, 20(August), 268–79.
