The analysis of coordinated effects of a merger typically answers two questions: First, what is the harm of coordination in the post-merger world? Second, what is the probability that firms will choose to coordinate? Coordinated and unilateral effects analysis both generally predict market outcomes under scenarios of greater concentration and/or collusive pricing. Coordinated effects analysis faces the additional challenge of assessing the post-merger incremental risk associated with each possible coordinated outcome.
The central economic theory underlying coordinated effects in antitrust enforcement comes from Stigler (1964). Stigler’s contribution was to establish a list of practical obstacles to coordination with broad applicability across schemes and markets. He enumerated the necessary elements of coordination: agreement on an outcome (price or market shares) and the detection and punishment of deviations. These elements are more likely to be sustained under certain market conditions, such as homogeneous products, small buyers making frequent purchases, and common knowledge of the prices sellers offer to buyers. Stigler’s analysis applies to differentiated products markets and procurement markets and to a broad range of coordinated behavior, including explicit, unlawful collusion and “conscious parallelism” expected to arise under oligopolistic competition (Chamberlin, 1933).
The US Horizontal Merger Guidelines (“Guidelines”) gradually incorporated Stigler’s ideas, focusing on the incremental risk of collusive behavior when considering coordinated effects. The 1984 Guidelines were the first to acknowledge coordinated effects in line with Stigler’s theory, highlighting the conditions that allow firms to “quickly detect and retaliate against deviations from the agreed prices…” The 1992 Guidelines flag “the nature of the procurement process” as potentially relevant. The 2010 Guidelines define coordination to include “parallel accommodating conduct…not motivated by retaliation or deterrence nor intended to sustain an agreed-upon market outcome…” In any case, the risk of coordination depends on, “the strength and predictability of rivals’ responses to a price change or other competitive initiative.” The Guidelines’ emphasis on risk encompasses future coordination that might not be readily detected or fall foul of the Sherman Act (Hovenkamp, 2018).
The agencies and courts assess the risk of post-merger coordination using qualitative and quantitative analysis. Qualitative analyses speak to how coordination would be carried out in the post-merger world. Agency challenges and court rulings highlight risk factors for coordination in line with Stigler’s theory. For example: (1) Markets are more susceptible to coordinated effects when products are more homogeneous. Archer-Daniels-Midland was allowed to lease additional capacity for the production of high fructose corn syrup (HFCS) on the grounds that “significant differences in costs and product mix among firms in the HFCS industry” made future coordination unlikely. (2) The risk of coordination is greater when the market consists of small buyers. In FTC v. University Health, the merging hospitals argued that their customers were large insurance companies who would block any attempted price increase. However, the court reasoned that the relevant buyers were individual patients who have no purchasing power. (3) Coordination is more likely when demand is stable because deviations from the coordinated policy are easier to detect. On the other hand, demand fluctuations may hinder the government’s ability to detect collusion in historical data, as in FTC v. Arch Coal. (4) A merger is more likely to produce coordinated effects when the target firm is a “maverick” with a history of deviating from the pricing behavior of its competitors. The role of Northwest Airlines as a maverick was pivotal in blocking its acquisition by Continental Airlines. (5) Finally, the Agencies look out for a history of coordination (explicit or tacit), as in US v. Premdor, Inc., et al., where the government’s complaint noted that Premdor’s subsidiaries had previously pled guilty to price-fixing.
Quantitative models provide methods for quantifying the outcomes (e.g., prices, profits) of collusive arrangements (including no collusion) as well as the risk of these arrangements occurring. In principle, both can be measured using some of the same merger simulation models applied to unilateral effects. However, in the context of coordinated effects, the modeler generally specifies which firms will collude and to what extent, and assigns a probability to each possible combination pre- and post-merger. Quantitative tools can accommodate less-than-perfect collusion and conscious parallelism: for example, Miller, Sheu, and Weinberg (2021) study a quantitative price leadership game in a retrospective analysis of the Miller/Coors merger, complementing an earlier study that estimates a conduct parameter that captures varying degrees of collusion. As for the probability of collusion, Kovacic et al. (2009) propose to measure the risk of coordinated effects based on the incremental profitability of collusion for subsets of firms in the post-merger world. Research on methods for quantitative assessment of coordinated effects is ongoing.
