Monotonic regression based on Bayesian P-splines: an application to estimating price response functions from store-level scanner data - Andreas Brezger; Winfried J. Steiner (Ludwig-Maximilians-Universität München, Sonderforschungsbereich 386 - Statistische Analyse diskreter Strukturen, 2003)
Generalized additive models have become a widely used instrument for flexible regression analysis. In many practical situations, however, it is desirable to restrict the flexibility of nonparametric estimation in order to accommodate a presumed monotonic relationship between a covariate and the response variable. For example, consumers usually will buy less of a brand if its price increases, and therefore one expects a brand's unit sales to be a decreasing function in own price. We follow a Bayesian approach using penalized B-splines and incorporate the assumption of monotonicity in a natural way by an appropriate specification of the respective prior distributions. We illustrate the methodology in an empirical application modeling demand for a brand of orange juice and show that imposing monotonicity constraints for own- and cross-item price effects improves the predictive validity of the estimated sales response function considerably.
urn:nbn:de:bvb:19-epub-1709-7
Keywords: 519; Generalized Additive Model; Markov Chain Monte Carlo; Sales Promotion; Own- and Cross-Item Price Effects; Asymmetric Quality Tier Competition; Bayes-Statistik; Nichtparametrisches Verfahren; Einzelhandelspreispolitik; Preis; Absatz; USA