Brand-level diversion ratios from product-level data

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.