A hierarchical Bayes error correction model to explain dynamic effects
AbstractFor 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.
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Bibliographic InfoPaper provided by Erasmus University Rotterdam, Econometric Institute in its series Econometric Institute Report with number EI 2004-27.
Date of creation: 12 Aug 2004
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vector autoregression; sales; hierarchical Bayes; short and long run effects;
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