Inference for Product Competition and Separable Demand

Adam N. Smith (), Peter E. Rossi () and Greg M. Allenby ()
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Adam N. Smith: UCL School of Management, University College London, London E14 5AA, United Kingdom
Peter E. Rossi: Anderson School of Management, University of California, Los Angeles, Los Angeles, California 90095
Greg M. Allenby: Fisher College of Business, Ohio State University, Columbus, Ohio 43210

Marketing Science, 2019, vol. 38, issue 4, 690-710

Abstract: This paper presents a methodology for identifying groups of products that exhibit similar patterns in demand and responsiveness to changes in price using store-level sales data. We use the concept of economic separability as the basis for establishing similarity between products and build a weakly separable model of aggregate demand. A common issue with separable demand models is that the partition of products into separable groups must be known a priori, which severely shrinks the set of admissible substitution patterns. We develop a methodology that allows the partition to be an estimated model parameter. In particular, we specify a log-linear demand system in which weak separability induces equality restrictions on a subset of cross-price elasticity parameters. An advantage of our approach is that we are able to find groups of separable products rather than just test whether a given set of groups is separable. Our method is applied to two aggregate, store-level data sets. We find evidence that the separable structure of demand can be inconsistent with category labels, which has implications for optimal category marketing strategies.

Keywords: price elasticities; category demand; dimension reduction; random partition models; Bayesian inference (search for similar items in EconPapers)
Date: 2019
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Citations: View citations in EconPapers (6)

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Persistent link: https://EconPapers.repec.org/RePEc:inm:ormksc:v:38:y:2019:i:4:p:690-710

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