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.
|Number of pages||7|
|Journal||Journal of Marketing Analytics|
|Publication status||Published - 8 Feb 2021|
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© 2021, The Author(s).