Marketing response and temporal aggregation

Philip Hans Franses*

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

1 Citation (Scopus)


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.

Original languageEnglish
Pages (from-to)111-117
Number of pages7
JournalJournal of Marketing Analytics
Issue number2
Publication statusPublished - 8 Feb 2021

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