Over the past 20 years, as part of the merger review process, antitrust agencies have increasingly turned to economic tools such as diversion and pricing pressure analyses to help determine which mergers to investigate, and then to further identify which mergers to challenge. A key input in these analyses is an estimate of the profit margin that the merging firms earn on incremental sales (“incremental margin”). All else being equal, the higher the merging firms’ pre-merger incremental margins, the likelier the analysis will be to predict significant price increases post-merger.
Obtaining and compiling the information required to estimate incremental margins can be difficult in practice. Thus, antitrust economists often use proxies based on measures found in aggregate accounting data, such as the difference between price and the cost of goods sold (the gross margin) or the difference between price and average variable costs. However, as noted by economists in other contexts, such proxies sometimes provide a poor measure of a firm’s market power and a poor measure of performance in an industry.
In this article, we offer our views on how best to estimate incremental margins given the shortcomings of measures based on aggregate accounting data.
A discussion of diversion analysis, an economic tool commonly used in antitrust analysis and described in the Merger Guidelines, illustrates the importance of accurate estimation of incremental margins. Consider two firms (A and B) selling differentiated products, competing on prices as under Bertrand competition, facing linear demand, and having marginal costs that are constant with respect to output.
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The authors are economists on the staff of the U.S. Federal Trade Commission. This article reflects the views of the authors and does not necessarily reflect the views of the U.S. Federal Trade Commission or any individual Commissioner. Malcolm Coate, Arthur Del Buono, Jeffrey Fischer, Daniel Greenfield, Kevin Hearle, Subbu Ramanarayanan, Paolo Ramezzana, David Schmidt, Aileen Thompson, and Nathan Wilson provided helpful comments and suggestions. Remaining errors are the authors’.
