V. Ramaswamy et al., AN EMPIRICAL POOLING APPROACH FOR ESTIMATING MARKETING MIX ELASTICITIES WITH PIMS DATA, Marketing science, 12(1), 1993, pp. 103-124
The PIMS (Profit Impact of Marketing Strategies) data entail sparse ti
me-series observations for a large number of strategic business units
(SBUs). In order to estimate disaggregate marketing mix elasticities o
f demand, a natural solution is to pool different SBUs. The traditiona
l, a priori approach is to pool together those SBUs which one believes
in advance to be very similar with respect to their marketing mix ela
sticities. We propose an alternative maximum likelihood, latent-poolin
g method for simultaneously pooling, estimating, and testing linear re
gression models empirically. This method enables the determination of
a ''fuzzy'' pooling scheme, while directly estimating a set of marketi
ng mix elasticities and intertemporal covariances for each pool of SBU
s. Our 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.