An empirical pooling approach for estimating marketing mix elasticities with PIMS data

An empirical pooling approach for estimating marketing mix elasticities with PIMS data

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Article ID: iaor1994869
Country: United States
Volume: 12
Issue: 1
Start Page Number: 103
End Page Number: 124
Publication Date: Dec 1993
Journal: Marketing Science
Authors: , , ,
Keywords: economics, demand, statistics: empirical, statistics: regression
Abstract:

The PIMS (Profit Impact of Marketing Strategies) data entail sparse time-series observations for a large number of strategic business units (SBUs). In order to estimate disaggregate marketing mix elasticities of demand, a natural solution is to pool differnet SBUs. The traditional, a priori approach is to pool together those SBUs which one believes in advance to be very similar with respect to their marketing mix elasticities. The authors propose an alternative maximum likelihood, latent-pooling method for simultaneously pooling, estimating, and testing linear regression models empirically. This method enables the determination of a ‘fuzzy’ pooling scheme, while directly estimating a set of marketing mix elasticities and intertemporal covariances for each pool of SBUs. The present analyses reveal different magnitudes and patterns of marketing mix elasticities for the derived pools. Pool membership is influenced by demand characteristics, business scope, and order of market entry.

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