Using Retail Scanner Data for Upstream Merger Analysis: Counterfactual Experiments in the Retail Coffee Market

The typical situation faced by antitrust authorities is to analyze and rule on a proposed merger by two or more manufacturers using scanner data at retail-level in a particular industry. This paper presents a simple framework to assess merger welfare effects in markets where both upstream and downstream firms make pricing decisions. I start with a benchmark model of manufacturers’ and retailers’ sequential pricing behavior. Then using counterfactual experiments, I explore the relationship between downstream retailer pricing models and the resulting estimates of upstream mergers. This exercise is done in the absence of wholesale prices looking at scanner data for the ground coffee category sold at several retail chains in Germany. I find that not considering retail pricing explicitly implies simulated changes in welfare that are significantly different given the underlying model of retail pricing behavior. For instance, through counterfactual simulations I find that, if retailers behave as Bertrand-Nash the welfare estimates are not significantly different from those obtained when not considering retailers, but when retail pricing departs from Nash-pricing behavior the welfare estimates can be significantly different from those estimated without considering retailer models explicitly.


Issue Date:
2007
Publication Type:
Working or Discussion Paper
PURL Identifier:
http://purl.umn.edu/7163
Total Pages:
28
JEL Codes:
C13; L13; L41
Series Statement:
CUDARE Working Paper
1030




 Record created 2017-04-01, last modified 2017-08-23

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