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

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  • Villas-Boas, Sofia Berto

Abstract

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.

Suggested Citation

  • Villas-Boas, Sofia Berto, 2007. "Using Retail Scanner Data for Upstream Merger Analysis: Counterfactual Experiments in the Retail Coffee Market," CUDARE Working Papers 7163, University of California, Berkeley, Department of Agricultural and Resource Economics.
    • Handle: RePEc:ags:ucbecw:7163
    DOI: 10.22004/ag.econ.7163
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    2. Villas-Boas, Sofia Berto, 2007. "Wholesale Price Discrimination: Inference and Simulation," CUDARE Working Papers 7166, University of California, Berkeley, Department of Agricultural and Resource Economics.

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