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Time-Series Models in Marketing

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Author Info

  • Dekimpe, M.G.
  • Franses, Ph.H.B.F.
  • Hanssens, D.M.
  • Naik, P.

Abstract

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.

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Bibliographic Info

Paper provided by Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam. in its series Research Paper with number ERS-2006-049-MKT.

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Date of creation: 20 Sep 2006
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Handle: RePEc:dgr:eureri:30008950

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Web page: http://www.erim.eur.nl/

Related research

Keywords: Marketing; Persistence; State Space; Time Series;

This paper has been announced in the following NEP Reports:

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Cited by:
  1. Wieringa, Jaap E. & Horvath, Csilla, 2005. "Computing level-impulse responses of log-specified VAR systems," International Journal of Forecasting, Elsevier, vol. 21(2), pages 279-289.
  2. Horváth, Csilla & Wieringa, Jaap E., 2003. "Combining time series and cross sectional data for the analysis of dynamic marketing systems," Research Report 03F13, University of Groningen, Research Institute SOM (Systems, Organisations and Management).
  3. Mercedes Esteban Bravo & Gökhan Yildirim & Jose Vidal-Sanz, 2011. "Can we curb retail sales volatility through marketing mix actions?," Business Economics Working Papers wb112407, Universidad Carlos III, Departamento de Economía de la Empresa.
  4. Tomohiro Ando, 2008. "Measuring the baseline sales and the promotion effect for incense products: a Bayesian state-space modeling approach," Annals of the Institute of Statistical Mathematics, Springer, vol. 60(4), pages 763-780, December.
  5. Sergio, Brasini & Marzia, Freo & Giorgio, Tassinari, 2008. "An analysis of the role of liking on the memorial response to advertising," MPRA Paper 12342, University Library of Munich, Germany.
  6. Netzer, Oded & Lattin, James M. & Srinivasan, V. "Seenu", 2007. "A Hidden Markov Model of Customer Relationship Dynamics," Research Papers 1904r, Stanford University, Graduate School of Business.
  7. De Gooijer, Jan G. & Hyndman, Rob J., 2006. "25 years of time series forecasting," International Journal of Forecasting, Elsevier, vol. 22(3), pages 443-473.
  8. Dekimpe, M.G. & Hanssens, D.M., 2003. "Persistence Modeling for Assessing Marketing Strategy Performance," Research Paper ERS-2003-088-MKT, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus Uni.
  9. Koen Pauwels & Imran Currim & Marnik Dekimpe & Dominique Hanssens & Natalie Mizik & Eric Ghysels & Prasad Naik, 2004. "Modeling Marketing Dynamics by Time Series Econometrics," Marketing Letters, Springer, vol. 15(4), pages 167-183, December.
  10. Vicente Esteve & Francisco Requena, 2006. "A Cointegration Analysis of Car Advertising and Sales Data in the Presence of Structural Change," International Journal of the Economics of Business, Taylor and Francis Journals, vol. 13(1), pages 111-128.
  11. Dekimpe, Marnik & Hanssens, DM, 2005. "Persistence models and marketing strategy," Open Access publications from Katholieke Universiteit Leuven urn:hdl:123456789/120752, Katholieke Universiteit Leuven.
  12. Pauwels, Koen & Currim, Imran & Dekimpe, Marnik & Ghysels, Eric & Hanssens, Dominique M & Mizik, Natalie & Naik, Prasad, 2005. "Modeling marketing dynamics by time series econometrics," Open Access publications from Katholieke Universiteit Leuven urn:hdl:123456789/121335, Katholieke Universiteit Leuven.

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