M. Christen et al., USING MARKET-LEVEL DATA TO UNDERSTAND PROMOTION EFFECTS IN A NONLINEAR MODEL, Journal of marketing research, 34(3), 1997, pp. 322-334
The authors show analytically, empirically, and numerically through si
mulation that the estimated effects from linearly aggregated market-le
vel data differ substantially from comparable effects that are obtaine
d from store-level data. The magnitude of this difference renders mark
et-level data largely unsuitable for econometric modeling, unless the
marketing manager compensates for the bias that results from the incom
patible aggregation. The authors introduce a new approach, a relativel
y simple debiasing procedure derived from simulated data, They show th
at this debiasing approach results in substantially improved parameter
estimates. They illustrate the value of the procedure by applying ii
to scanner data for powdered detergents and comparing the debiased par
ameter estimates to results obtained from store-level da la and an alt
ernative aggregation method that maintains homogeneity for selected pr
omotional activities.