Upward Price Pressure, Merger Simulation, and Merger Simulation Light

Michael Noel, Mar 14, 2011

Every year, the Federal Trade Commission("FTC")and the Antitrust Division of the Department of Justice ("DOJ") are notified of thousands of mergers.  Investigating which mergers are likely to have anticompetitive effects is a difficult, data-intensive, and resource-consuming task. Screens are necessary to target the truly problematic mergers and economize on scarce agency resources.

The agencies have historically relied in part upon a screen for unilateral effects based on the market shares of the merging firms. The 1997 merger guidelines state that, in concentrated industries, if the new merged firm would attain a market share of at least 35 percent the merger would be presumptively anticompetitive. The specific figure has since been dropped in the 2010 guidelines.

As has long been noted by economists, market share screens rely on the inherently difficult and artificial exercise of defining a relevant market from which to construct market shares.  Market definition exercises must make a discrete "in or out" decision for each product from what is generally a continuum of substitute products, and market shares are sensitive to where this cutoff is drawn.

Recently, Joseph Farrell and Carl Shapiro (hereafter "FS") introduced a new screen known as Upward Price Pressure ("UPP") to flag potential unilateral effects. The screen requires as inputs estimates of diversion ratios, markups, and post-merger cost efficiency expectations.

On theoretic grounds, UPP has many advantages over traditional market-share based screens and represents a potentially important step forward for merger enforcement policy. UPP is rooted in the economic theory of profit maximization (for Bertrand competition), and attempts to directly gauge the post-merger pricing incentives of a merging firm. In general it does not require defining a relevant antitrust market.

UPP has several limitations, though. Like market-share based screens, it only seeks to predict whether prices will rise, but not by how much, when it is actually the latter we actually care about. Also, the data requirements are more stringent for UPP than for market-based screens, which may limit its use. Finally, UPP is yet to be fully tested and optimized empirically.

In this article, I consider the advantages and limitations of implementing UPP in practice, discuss the relationship between UPP and merger simulation, and ultimately argue in favor of a "merger simulation light" style screen, based on UPP, that I think holds the most promise for effective merger screening practice.

 

 

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