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Semiparametric Stepwise Regression to Estimate Sales Promotion Effects

  • Winfried J. Steiner
  • Christiane Belitz
  • Stefan Lang
Part of the Studies in Classification, Data Analysis, and Knowledge Organization book series (STUDIES CLASS)

Abstract

Kalyanam and Shively (1998) and van Heerde et al. (2001) have proposed semiparametric models to estimate the influence of price promotions on brand sales, and both obtained superior performance for their models compared to strictly parametric modeling. Following these researchers, we suggest another semiparametric framework which is based on penalized B-splines to analyze sales promotion effects flexibly. Unlike these researchers, we introduce a stepwise procedure with simultaneous smoothing parameter choice for variable selection. Applying this stepwise routine enables us to deal with product categories with many competitive items without imposing restrictions on the competitive market structure in advance. We illustrate the new methodology in an empirical application using weekly store-level scanner data.

Keywords

Product Category Semiparametric Model Sales Promotion Price Promotion Start Model 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer Berlin · Heidelberg 2006

Authors and Affiliations

  • Winfried J. Steiner
    • 1
  • Christiane Belitz
    • 2
  • Stefan Lang
    • 3
  1. 1.Department of MarketingUniversity of RegensburgRegensburgGermany
  2. 2.Department of StatisticsUniversity of MunichMunichGermany
  3. 3.Institute of Empirical Economic ResearchUniversity of LeipzigLeipzigGermany

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