This paper deals with inferring key parameters on marketing response at a true high frequency while data are partly or fully available only at a lower frequency aggregate levels. The familiar Koyck model turns out to be very useful for this purpose. Assuming this model for the high-frequency data makes it possible to infer the high-frequency parameters from modified Koyck type models when lower frequency data are available. This means that inference using the Koyck model is robust to temporal aggregation.

Advertising response, Carryover effect, Current effect, Temporal aggregation, Total effect,
Journal of Marketing Analytics
Department of Econometrics

Franses, Ph.H.B.F. (2021). Marketing response and temporal aggregation. Journal of Marketing Analytics. doi:10.1057/s41270-020-00102-7