Introduction

In many merger cases, the core competition concern is that the loss of rivalry between two merging competitors may render it profitable for the merged business to unilaterally worsen its offer by raising prices, or reducing quality, range or service. Competition authorities frequently use merger control tools (such as diversion ratios, price indices and merger simulation) to assess the closeness of competition between rivals. However, are these merger control tools, which have evolved over time, still fit for purpose in 2022?

Whilst unilateral effects can arise in other market contexts (such as in homogeneous goods where firms mainly compete on the supply side in terms of costs and capacity), in practice unilateral effects most often arise in differentiated goods/services markets. Such differentiation can arise due to differences in product characteristics (i.e. differences in objective product features, but also due to more intangible matters such as brand image), and/or by geography (where customers travel to nearby retailers/wholesalers or service providers, or suppliers make deliveries to local customers).

In differentiated markets, it may be difficult for the merging parties to assess whether their merger is likely to be viewed as anti-competitive. This is because there may be no clear product or geographic boundaries to the relevant market and, however the market is defined, market shares may not capture the closeness of competition between different suppliers. For example, if the market is defined broadly to include various differentiated alternatives, then market shares may understate the rivalry between the parties. However, if the market is defined narrowly, then market shares may fail to capture the strength of competition from other rivals. This point is explicitly recognised in the Competition and Markets Authority's ("CMA") Merger Assessment Guidelines of 2021:

"In many cases, especially those involving differentiated products, there is often no 'bright line' that can or should be drawn. Rather, it can be more helpful to describe the constraint posed by different categories of product or supplier as sitting on a continuum between 'strong' and 'weak'."1

Consequently, merger control tools in differentiated markets have increasingly focused on how a merger between rivals may create an incentive to increase prices or otherwise worsen their offer. In particular, firms may be close competitors, depending on the extent to which they win/lose sales between one another when they vary their prices (which may be measured using diversion ratios), and the loss of this rivalry may create an incentive for the merged firm to increase the parties' prices (which depend on gross profit margins as well as diversion ratios, which can be combined together in simple pricing indices that focus on incentives rather than price effects). Merger simulation takes this further by estimating actual price increases, but these estimates depend on additional data and assumptions. On the other hand, mergers between competitors may generate efficiencies that may offset any anti-competitive incentives to increase prices.

As emphasised above, in differentiated markets, customer demand-side behaviour is of particular importance to assessing the risk of the merged business having unilateral incentives to worsen its offer.2 However, as a spoiler, the three case studies presented in this chapter illustrate how supply-side factors need to be considered alongside information on demand-side constraints to assess overall competitive effects, even where barriers to entry and expansion are high:3

  • In Bottomline Technologies (DE), INC/Experian Limited Merger (2020), the CMA cleared the merger unconditionally despite the parties' high combined market shares. This decision rested on the existence of clear evidence that Experian's Payment Gateway product was a weak competitor (as it had not received investment or been actively promoted), and that the parties were not close competitors.
  • In T-Mobile NL/Tele2 NL Merger (2018), the European Commission (the "Commission") cleared the merger unconditionally as the parties' static incentives to increase prices were modest and one of the merging parties was in decline. This was not a failing firm case, but a case where the merger counterfactual of declining rivalry was important to the clearance decision. In short, this case illustrates that supply-side competitive dynamics still matter in differentiated markets.
  • In FCA/PSA (2020), the Commission reached an adverse finding in relation to the parties' overlapping businesses in the supply of light commercial vehicles ("LCVs") in various countries where the parties were close competitors, having regard to both national market shares and analysis of the closeness of competition. The Commission also considered supply-side factors, including whether merger efficiencies may provide off-setting incentives, and the relevance of market share volatility and overall European market shares (rather than purely market shares in individual Member States). Supply-side factors were also relevant to assessing appropriate remedies, with the Commission accepting two targeted remedies, which required the merged business to improve the competitiveness of a rival (Toyota) through an extension of an existing cooperation agreement, and to allow rivals to expand by accessing PSA's/FCA's repair and maintenance networks.

The remainder of this chapter is divided into three parts:

  1. Section 2 provides an overview of the main quantitative tools that European competition authorities4 have used to assess the merging firms' incentives to increase prices or otherwise worsen their offer in differentiated markets, namely diversion ratios, upward pricing pressure ("UPP") indices and merger simulations. This section draws particularly on two recent academic articles by Valletti and Zenger5 and Miller and Sheu,6 covering the main tools used and their advantages and limitations.
  2. Section 3 then presents three case studies highlighting how the Commission and CMA have applied these tools in practice, and the relevance of other factors to their conclusions.
  3. Section 4 concludes, including highlighting the key lessons for practitioners and parties contemplating mergers, and answering the titular question of whether the tools are still fit for purpose.

Overview of different merger control analyses

This section provides an overview of the different quantitative tools competition authorities use to assess the closeness of competition between rival suppliers and their static incentives to worsen their offer, including diversion ratios, UPP tests, and merger simulation. Each sub-section summarises the methodology and the underlying evidence required, as well as the advantages and limitations with each tool.

Diversion ratios

Diversion ratios measure the degree of substitution between products, providing insight on the degree of competition between two firms. A diversion ratio is the proportion of sales or revenues that are captured by firm 2, when firm 1 raises price (or reduces quality, range or service – or ceases business). If a diversion ratio is high, two firms (or products) are close substitutes and may exercise a strong competitive constraint on each other.

The intuition is that if one firm increases its prices, customers would largely switch to their closest competitors. If there is high diversion between two merging firms, then postmerger the parties will internalise/capture the revenue that would have otherwise diverted to a rival. All else equal, this may increase their incentive to raise prices or otherwise reduce quality, range or service post-merger. If diversion is low, firms (or products) are less likely to be close substitutes, and a price increase is unlikely to generate high diversion to the rival firm. Therefore, in the context of a merger, diversion ratios may provide insight for competition authorities when both defining the relevant market (both product and geographic dimensions) and estimating potential price effects.

Valletti and Zenger note that diversion ratios can be calculated using the following evidence:7

  1. Switching data: sales data from different firms in a market can be used to understand switching patterns following changes in price (e.g. temporary promotions). In some markets, this data may be straightforward to interpret, but firms' sales might be influenced by a variety of other factors such that the impact of price changes may be difficult to isolate, and some changes in purchasing patterns may reflect changes in customers' requirements, rather than changes in firms' relative prices.
  2. Bidding data: the number and identities of firms that participate in bids, and which firms win or lose these bids, can indicate which firms are close competitors. However, this information may not be available to individual competitors, or only be partially available.
  3. Customer surveys: competition authorities or merging parties may conduct surveys to assess the closeness of different products, by asking hypothetical questions on how consumers would react following an increase in price or a temporary closure of a firm or local store. This approach helps competition authorities understand hypothetical demand patterns following a price increase/change in the market or if a product/outlet ceases to be available. However, these questions are hypothetical and stated preferences may substantially differ from revealed preferences – i.e. what consumers would actually do in practice.
  4. Event studies: competition authorities may investigate consumers' actual reactions to a temporary shutdown of a plant or a store, providing insight on the second-best choice available. However, this type of analysis will capture diversion for all customers, rather than the diversion for marginal, price-sensitive customers that one wishes to measure.
  5. Demand estimation: based on the parties' sales data, diversion ratios can be derived using the estimated own- and cross-price elasticities. If products are close substitutes, their prices will likely be strongly correlated, and their diversion ratios should be high. However, this analysis may be complex, and requires further data and assumptions.

Where multiple approaches or data sources are available, it is important to consider which is likely to be the most accurate/robust measure of actual diversion and the extent of any sensitivities.

Footnotes

1. CMA Merger Assessment Guidelines, 2021, at para. 9.4.

2. In some differentiated markets, large retailers or other purchasers may have countervailing buyer power over large suppliers of differentiated goods/services. However, this should not be presumed (and small purchasers may lack such buyer power), and a merger may reduce customers' buyer power by reducing the number of independent options to which customers can threaten to switch. In addition, depending on the circumstances, other supply-side factors can also be particularly relevant, especially when the underlying product suppliers are large and can dictate the terms of distribution and trade. See, for example, the CMA's decision in JD Sports/ Footasylum (2021), where Nike and Adidas had significant control of the distribution and presentation of their products by retailers, which arguably could have mitigated any attempt by the parties to worsen their offer post-merger (see JD Sports/Footasylum Phase 2 Final Report, para. 9.25). On the facts of the case, the CMA concluded that these supplier constraints were insufficient.

3. For example, Valletti and Zenger emphasise that "adverse merger effects can only materialize if these is some form of barriers to entry" (see Valletti, Tommaso and Zenger, Hans (2021), "Mergers with Differentiated Products: Where Do We Stand?", Review of Industrial Organization, 58, issue 1, pp 179–212). Tommaso Valletti served as Chief Competition Economist at the European Commission from 2016–2019.

4. These tools are in fact used by many competition authorities globally, including the U.S. Department of Justice and Federal Trade Commission and the Japanese Fair Trade Commission. Indeed, the two articles particularly referenced in the chapter by Valletti and Zenger (op. cit., Note 3) and Miller and Sheu are written in the context of an edition of the Review of Industrial Organization which focuses on a 10th anniversary review of the 2010 U.S. Horizontal Merger Guidelines (Nathan H. Miller and Gloria Sheu (2021), "Quantitative Methods for Evaluating the Unilateral Effects of Mergers", Review of Industrial Organization, 58, issue 1, pp 143–177).

5. Op. cit., Note 3.

6. Op. cit., Note 4.

7. Op. cit., Note 3, p. 4. The CMA's Merger Assessment Guidelines also indicate that assessment of closeness of competition may be informed from a diverse range of other sources, including information on product characteristics or uses, internal documents (e.g. which competitors do they monitor or respond to), and evidence as to effects of previous, similar mergers or entry/exit (e.g. if previous mergers/exit led to higher prices) (see para. 4.13).

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