The authors put forth a sales response model to explain the differences in immediate and dynamic effects of promotional prices and regular prices on sales. The model consists of a vector autoregression that is rewritten in error correction format, which allows the authors to disentangle the immediate effects from the dynamic effects. In a second level of the model, the immediate price elasticities, the cumulative promotional price elasticity, and the long-term regular price elasticity are correlated with various brand-specific and category-specific characteristics. The model is applied to seven years of data on weekly sales of 100 different brands in 25 product categories. The authors find many significant moderating effects on the elasticity of price promotions. Brands in categories that are characterized by high price differentiation and that constitute a lower share of budget are less sensitive to price discounts. Deep price discounts increase the immediate price sensitivity of customers. The authors also find significant effects for the cumulative elasticity. The immediate effect of a regular price change is often close to zero. The long-term effect of such a regular price decrease usually amounts to an increase in sales. This is especially true in categories that are characterized by a large price dispersion and frequent price promotions and for hedonic, nonperishable products.

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Keywords Bayesian statistical decision theory, consumer goods, consumers (research), consumption (economics), elasticity (economics), hierarchical Bayes, long-term effects, marketing mix, marketing research, mathematical models, promotional price, regression analysis, regular price, sales, statistical decision, vector autoregression
Persistent URL,
Series ERIM Top-Core Articles
Journal Journal of Marketing Research
Fok, D, Horváth, C, Paap, R, & Franses, Ph.H.B.F. (2006). A Hierarchical Bayes Error Correction Model to Explain Dynamic Effects of Price Changes. Journal of Marketing Research (Vol. 43, pp. 443–461). doi:10.1509/jmkr.43.3.443