Editorial---The Scientific Process at Its Best

I write this editorial to point out a recent “research trilogy” in Marketing Science that shows the scientific process (and author efforts) at its best. In particular, in 2005, an article (the first of the trilogy) was published in Marketing Science, by Besanko, Dube, and Gupta (hereafter BDG), that focused on the issue of crossbrand retail pass-through; that is, are retail prices of competing brands adjusted (by the retailer) in response to a change in the wholesale price of any given brand in the category? BDG address this issue by fitting a reduced-form model (log price regressed on log cost) to data from the well-utilized Dominick’s Finer Foods (DFF) data set on 78 products, 11 product categories across 15 “price zones.” Looking at cross-brand pass-through coefficients, BDG find significant evidence supporting their claim and also describe how these effects vary according to the size/share of the brand. Clearly, this is an important problem with important empirical findings. Then, two years later, the second part of the trilogy was published by McAlister (2007), who raises some concern about BDG (2005) because prices are not set independently across the 15 zones by DFF and, hence, the effective degrees of freedom may not be as assumed in BDG (2005). As a result, McAlister (2007) reports that if the data are not disaggregated to the level of the price zone (as in BDG 2005), one finds a large proportion of nonsignificant elasticities. This was taken as “nonevidence” of cross-brand pass-through and, hence (if you will), the debate. However, just as with BDG (2005) the McAlister data left a number of unanswered issues because no formal test for nonzero elasticities was done, nor were explorations of longer data series performed that may allow for more powerful tests. Clearly, McAlister (2007) is also an important paper, as it re-examined both the methods used and the data generating assumptions of BDG (2005), something that is commonly “swept under the rug,” and it also left more questions to explore. Finally, in 2008 (in this issue), we have the last part of the research trilogy, where Dube and Gupta (DG 2008) reanalyze the original BDG (2005) data, this time using more appropriate hierarchical Bayesian methods (Rossi and Allenby 2003) applied both at the disaggregate store level and at the aggregate chain level (to address concerns raised in McAlister 2007) and using formal Bayes factors to test the null hypothesis of zero cross-brand pass-through elasticities. Their new findings now reinforce BDG’s conclusion (2005) that cross-brand pass-through does exist but at a significantly reduced level than originally claimed. So, why this editorial and why is the DG article “the scientific process at its best?” First and foremost, let us see what the field has gained from this research: 1. The original BDG (2005) paper addressed an important topic, one important enough that another scholar spent the effort to read it carefully and reanalyze it. 2. Through McAlister (2007) we can see the importance of testing hypotheses in only as powerful a way as the data will allow for, and in DG 2008 those methods are applied both to the original BDG 2005 data and to a longer time series of data. So, a reinquiry in this case led to a more appropriate aggregation of the data (and an exploration of the effects of nonaggregation) and a more powerful set of techniques to be applied. 3. As is common, great research sometimes raises more questions than it answers. In this case, my belief is that this empirical “debate” is far from over, but because the authors all invested their time, we now are at a better place at which to continue the discussion.