Marketing data appear in a variety of forms. An often-seen form is time-series data, like sales per month, prices over the last few years, market shares per week. Time-series data can be summarized in time-series models. In this chapter we review a few of these, focusing in particular on domains that have received considerable attention in the marketing literature. These are (1) the use of persistence modelling and (2) the use of state space models.

Additional Metadata
Keywords Marketing, Persistence, State Space, Time Series
JEL Time-Series Models; Dynamic Quantile Regressions (jel C22), Statistical Decision Theory; Operations Research (jel C44), Business Administration and Business Economics; Marketing; Accounting (jel M), Marketing (jel M31)
Publisher Erasmus Research Institute of Management
Persistent URL hdl.handle.net/1765/7984
Series ERIM Report Series Research in Management
Journal ERIM report series research in management Erasmus Research Institute of Management
Citation
Dekimpe, M.G, Franses, Ph.H.B.F, Hanssens, D.M, & Naik, P. (2006). Time-Series Models in Marketing (No. ERS-2006-049-MKT). ERIM report series research in management Erasmus Research Institute of Management. Erasmus Research Institute of Management. Retrieved from http://hdl.handle.net/1765/7984