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A hierarchical Bayes error correction model to explain dynamic effects

Author

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  • Fok, D.
  • Horváth, C.
  • Paap, R.
  • Franses, Ph.H.B.F.

Abstract

For promotional planning and market segmentation it is important to understand the short-run and long-run effects of the marketing mix on category and brand sales. In this paper we put forward a sales response model to explain the differences in short-run and long-run effects of promotions on sales. The model consists of a vector autoregression rewritten in error-correction format which allows us to disentangle the long-run effects from the short-run effects. In a second level of the model, we correlate the short-run and long-run elasticities with various brand-specific and category-specific characteristics. The model is applied to weekly sales of 100 different brands in 25 product categories. Our empirical results allow us to make generalizing statements on the dynamic effects of promotions in a statistically coherent way.

Suggested Citation

  • Fok, D. & Horváth, C. & Paap, R. & Franses, Ph.H.B.F., 2004. "A hierarchical Bayes error correction model to explain dynamic effects," Econometric Institute Research Papers EI 2004-27, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    • Handle: RePEc:ems:eureir:1476
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    References listed on IDEAS

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    6. Richard Paap & Philip Hans Franses, 2000. "A dynamic multinomial probit model for brand choice with different long-run and short-run effects of marketing-mix variables," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 15(6), pages 717-744.
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    Cited by:

    1. van Heerde, H.J. & Dekimpe, M.G. & Putsis, W.P., 2004. "Marketing Models and the Lucas Critique," ERIM Report Series Research in Management ERS-2004-080-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 University Rotterdam.
    2. 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.

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