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Brand-level diversion ratios from product-level data

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  • Lydia Cheung

Abstract

The diversion ratio is a key ingredient for merger analysis, as mentioned in the new Horizontal Merger Guidelines (2010) in the US and similar documents abroad. It is a measure of substitutability between merging goods, which determines the potential for price increase post-merger. This paper derives ready-to-use expressions for brand-level aggregated elasticities and diversion ratios, to be used with product-level data. I use the nested logit model and consider three different ways that nested products are grouped into brands, because most brands contain many individual goods, some of which form nests of higher similarity. While rich high-frequency data on the product level become increasingly available, a lot of relevant antitrust analyses, such as merger price effects, are conducted at the brand level. This paper fills a gap in the practitioner's toolkit, valuing ease of use without sacrificing richness of micro-data.

Suggested Citation

  • Lydia Cheung, 2017. "Brand-level diversion ratios from product-level data," New Zealand Economic Papers, Taylor & Francis Journals, vol. 51(2), pages 177-192, May.
    • Handle: RePEc:taf:nzecpp:v:51:y:2017:i:2:p:177-192
    DOI: 10.1080/00779954.2017.1298662
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    1. Daljord, Øystein & Sørgard, Lars, 2011. "Single-product versus uniform SSNIPs," International Review of Law and Economics, Elsevier, vol. 31(2), pages 142-146, June.
    2. Christopher Conlon & Julie Holland Mortimer, 2021. "Empirical properties of diversion ratios," RAND Journal of Economics, RAND Corporation, vol. 52(4), pages 693-726, December.
    3. Steven T. Berry, 1994. "Estimating Discrete-Choice Models of Product Differentiation," RAND Journal of Economics, The RAND Corporation, vol. 25(2), pages 242-262, Summer.
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    6. Christopher T. Conlon & Julie Holland Mortimer, 2013. "An Experimental Approach to Merger Evaluation," NBER Working Papers 19703, National Bureau of Economic Research, Inc.
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