Regulatory Comments

ICLE Comments on Canada Competition Bureau’s Update of the Merger Enforcement Guidelines

Introduction

We thank the Government of Canada and the Competition Bureau for the opportunity to comment on its review of the Merger Enforcement Guidelines (Guidelines).[1] The International Center for Law & Economics (ICLE) is a nonprofit, nonpartisan global research and policy center founded with the goal of building the intellectual foundations for sensible, economically grounded policy. ICLE promotes the use of law & economics methodologies to inform public-policy debates and has longstanding expertise in the evaluation of competition law and policy. ICLE’s interest is to ensure that competition law remains grounded in clear rules, established precedent, a record of evidence, and sound economic analysis.

The consultation asks us to navigate a world in the aftermath of Bills C-56[2] and C-59[3] (Bills). The Bills introduced changes to Canadian competition law that are, in our view, severely misguided. The most problematic of these changes are encoding structural presumptions in the Competition Act and jettisoning the efficiency exemption in merger review. In our view, these changes signal a worrying turn away from sound economic analysis and toward formalistic line-drawing based on market structure. Notwithstanding these complaints, the changes are now fait accompli—at least, until the next legislative reform. The question therefore becomes one of mitigating their damage. We believe that the Guidelines could have a role to play in this regard. This is, by and large, how we have framed our comments (Comments) to the Competition Bureau’s consultation (Consultation).

Our Comments focus primarily on the following aspects of the Guidelines:

1. Mergers that increase market share or concentration;
2. Monopsony power in labor markets;
3. Digital platforms, multi-sided markets, and network effects;
4. Non-price effects and privacy;
5. Innovation and dynamic competition; and
6. The repeal of the efficiency exemption.

In its ongoing efforts to ensure that antitrust law in general, and merger control in particular, remain tethered to sound principles of economics, law, and due process, ICLE has submitted responses to consultations and published papers, articles, and reports in a number of jurisdictions. These include the European Union, the United States, Brazil, the Republic of Korea, the United Kingdom, India, and Canada. In January 2024, for example, ICLE submitted comments[4] to the Competition Bureau’s public consultation on its “Artificial Intelligence and Competition” discussion paper.[5] These and other publications are available on ICLE’s website.[6]

I. Mergers that Increase Market Share or Concentration

Bill C-59 incorporated structural presumptions into the Competition Act’s merger-review process.[7] As the Consultation notes, structural presumptions are, at best, an imperfect proxy for market power and, at worst, a misleading one.[8]

The assumption that “too much” concentration is harmful assumes both that a market’s structure is what determines economic outcomes, and that it is possible to know what the “right” amount of concentration is. As economists have understood since at least the 1970s (and despite an extremely vigorous, but futile, effort to show otherwise), market structure does not determine economic outcomes.[9]

Once perfect knowledge of technology and price is abandoned, [competitive intensity] may increase, decrease, or remain unchanged as the number of firms in the market is increased.… [I]t is presumptuous to conclude… that markets populated by fewer firms perform less well or offer competition that is less intense.[10]

This view is well-supported, and is held by scholars across the political spectrum.[11] The absence of correlation between increased concentration and either anticompetitive causes or deleterious economic effects is also demonstrated by a recent influential empirical paper from Shanat Ganapati. Ganapati finds that the increase in industry concentration in U.S. non-manufacturing sectors between 1972 and 2012 was “related to an offsetting and positive force—these oligopolies are likely due to technical innovation or scale economies. [The] data suggests that national oligopolies are strongly correlated with innovations in productivity.”[12] In the end, Ganapati found, increased concentration resulted from beneficial growth in firm size in productive industries that “expand[s] real output and hold[s] down prices, raising consumer welfare, while maintaining or reducing [these firms’] workforces.”[13] Sam Peltzman’s research on increasing concentration in manufacturing finds that it has, on average, been associated with both increased productivity growth and widening margins of price over input costs. These two effects offset each other, leading to “trivial” net price effects.

Further, the presence of harmful effects in industries with increased concentration cannot be readily extrapolated to other industries. Thus, while some studies have plausibly shown that an increase in concentration in a particular case has led to higher prices (which has been found true in only a minority of the relevant literature), assuming the same result from an increase in concentration in other industries or other contexts is simply not justified:

The most plausible competitive or efficiency theory of any particular industry’s structure and business practices is as likely to be idiosyncratic to that industry as the most plausible strategic theory with market power.[14]

As Chad Syverson aptly summarized:

Perhaps the deepest conceptual problem with concentration as a measure of market power is that it is an outcome, not an immutable core determinant of how competitive an industry or market is… As a result, concentration is worse than just a noisy barometer of market power. Instead, we cannot even generally know which way the barometer is oriented.[15]

In other words, depending on the nature and dynamics of the market in question, competition may well be protected under conditions that preserve a certain number of competitors in the relevant market. But competition may also be protected under conditions in which a single winner takes all on the merits of their business.[16] It is reductive, and bad policy, to presume that a certain number of competitors is always and everywhere conducive to better economic outcomes, or indicative of anticompetitive harm.

None of this means that concentration measures have no use in merger enforcement. Instead, it demonstrates that market concentration is often unrelated to antitrust enforcement, because it is driven by factors endogenous to each industry. As indicated earlier, the limited value of structural presumptions in elucidating competitive outcomes is recognized in the Consultation—at least, in theory. It is also recognized in the context of agreements and arrangements in s.90.3 of the Competition Act, which states that “for the purpose of subsections (1) and (2), the Tribunal shall not make the finding solely on the basis of evidence of concentration or market share.”

And yet it, is not entirely clear—in the aftermath of Bill C-59, and especially following the elimination of the efficiencies defense—how defendants could rebut the structural presumption laid down in s.92, other than by refuting the market-concentration calculus put forward by the Bureau. This essentially turns merger review under the Competition Act into a formalistic exercise where—despite assurances to the contrary—market structure is outcome-determinative. It also jars with the logic that applies to conduct under s. 90.1, thereby rendering the Competition Act conceptually rudderless.

The Guidelines can mitigate the unintended consequences of Bill C-59 by relativizing the value of structural presumptions. This can be done by clarifying that market structure is only a proxy for determining whether a transaction significantly lessens competition; explaining how structural presumptions can be rebutted; and clarifying that there is no “one size fits all” presumption across all industries. The overarching theme should be this: merger review is not a tool to organize markets along the Bureau’s preferred structural composition, but merely a tentative indication preceding a full-blow analysis.

Conversely, if the Guidelines double-down on Bill C-59’s structural turn, Canada risks stifling the dynamism of its own economy and destroying the significant benefits that accrue from procompetitive transactions, which account for the vast majority of mergers.[17] As Aaron Wudrick—former director of the Domestic Policy Programme at the Macdonald-Laurier Institute and now director of policy for MP Pierre Poilievre—has pointed out, “[structural presumptions] are very bad a idea, and [are] essentially evidence-free populism run amok.”[18] This echoes our arguments about the flimsy connection between market structure and economic performance. Similarly, Wudrick argues that:

The very premise is faulty, because concentration measures alone—as opposed to market power—are a poor proxy for the level of competition that prevails in a given market. I understand this can seem counterintuitive to a lot of people in the abstract, but in practice, it makes more sense: say you have one competitor, in particular, offering lower prices, higher quality, or newer cutting-edge products, so they end up breaking from the pack. They gain customers, and their market share rises. So this higher concentration is actually signaling more, rather than less, competition![19]

A formalistic adherence to market structure, in a misguided attempt to cater to populist anti-bigness sentiment, can penalize precisely those companies that, as Wudrick puts it, “break from the pack.” Consumers would, in turn, be left worse off “due to the unintended consequences in this populist rush to ‘get’ the big guys.”[20]

This form of populism may momentarily assuage some of the political pressure stemming from the high cost of living, but the “victory” is bound to be a Pyrrhic one—both as the economic harms of a flawed economic policy become apparent, and as consumers become aware that they are expected to foot the bill. With the impending change of administration in the United States, the populist “neo-Brandeisian moment” may have passed in that country,[21] and Canada would be unwise to replicate it at its lowest ebb.

II. Monopsony Power in Labor Markets

The Bureau’s recognition of the importance of monopsony power in labor markets is a welcome development. The recent changes to the Competition Act that explicitly include labor as a “product” for the purposes of merger review appropriately reflect the importance of labor-market competition.[22] As the Bureau acknowledges, the economic literature is increasingly concerned with how employers may exercise market power over their workforce, influencing wages, benefits, and working conditions.[23]

Before getting to the explicit guidance, however, it would be worthwhile to take a fuller look at the economic literature.[24] The Bureau cites papers that find high concentration levels.[25] It is worth recognizing that one of these papers is restricted only to manufacturing, while the other relies on online job-posting data. The administrative data directly measure employment levels and shares, instead of being restricted to online vacancies as a proxy for employment.

This distinction matters, because employment shares are the natural counterpart of market shares—a cornerstone of antitrust enforcement. Concentration measures based on vacancies will be systematically higher than those based on employment, because not all firms will hire in any given period (in addition to any other issues with the data sample). Using the most direct comparison available, the governmental microdata finds an average Herfindahl–Hirschman Index (HHI) roughly one-tenth as large as that found using vacancy data. For example, Elizabeth Weber Handwerker and Matthew Dey directly compare the concentration measures in their data to the 26 occupations studied by Jose Azar, Iona Marinescu, and Marshall Steinbaum.[26] They find an HHI in the private sector of 0.0383, compared to 0.3157 in Azar, Marinescu, & Steinbaum.

The point is not to take a firm stance on the level of concentration in labor markets, especially labor markets in Canada, but instead to recognize nuances in the literature.

When thinking about the connection between concentration and wages, rather than concentration in isolation, it is also worth noting that most papers (including those cited by the Bureau) that find lower wages in markets with higher employer concentration do not differentiate rural from urban labor markets.[27] Rural and urban labor markets can differ significantly in terms of their economic structures, job opportunities, and wage levels. Any regression of wages on concentration is likely picking up something unrelated to concentration directly.

There is good evidence that employer concentration does not lead to depressed wages. For example, Ivan Kirov and James Traina find that rising markdowns (the gap between worker productivity and wages) are more strongly associated with technology-related factors—such as automation and managerial practices—than with employer concentration.[28] Moreover, they caution that:

These results suggest the workhorse assumptions behind some of the labor-market power literature might need reevaluation, particularly work that uses cross-sectional variation to infer trends in labor-market power. Concentration is likely an inappropriate measure of labor-market power in this case.

Their critique underscores the limitations of relying heavily on concentration metrics to assess labor-market competition, especially when making claims about trends over time. As Steven Berry, Martin Gaynor, and Fiona Scott Morton write:

A main difficulty in [the monopsony power literature] is that most of the existing studies of monopsony and wages follow the structure-conduct-performance paradigm; that is, they argue that greater concentration of employers can be applied to labor markets and then proceed to estimate regressions of wages on measures of concentration. For the same reasons we discussed above, studies like this may provide some interesting descriptions of concentration and wages but are not ultimately informative about whether monopsony power has grown and is depressing wages.[29]

This is not to say that indirect evidence of market power is entirely without value. These studies can provide useful background information to guide antitrust policy. Moreover, antitrust law itself often relies on indirect measures of market power, such as concentration ratios and HHIs. In the case of antitrust enforcement, however, these measures are typically derived from carefully defined relevant markets. Defining the relevant market for labor is a complex task that requires considering such factors as job characteristics, worker skills, worker mobility, and geographic scope. There is currently little consensus among labor economists about the best way to define labor markets for antitrust purposes.

While the Bureau points to true features of labor markets around search frictions, the conclusion “that labour markets may be narrow” is premature, if “may” means more than mere possibility. There are also features of labor markets that push in the opposite direction. Often, the relevant market cannot be narrowed to even a handful of readily identifiable companies. For the vast majority of workers, a great number of potential employers would remain following a merger. This “potential competition”—the range of feasible employers that present an outside option to the merged companies’ present employees—limits the merged firm’s ability to exercise monopsony power in its labor negotiations. While we are not aware of publicly available data that would more comprehensively illustrate worker flows among different companies (and industries), such flows of retail workers into and out of roughly adjacent labor markets make intuitive sense. As economist Kevin Murphy has explained:

If you look at where people go when they leave a firm or where people come from when they go to the firm, often very diffuse. People go many, many different places. If you look at employer data and you ask where do people go when they leave, often you’ll find no more than five percent of them go to any one firm, that they go all over the place. And some go in the same industry. Some go in other industries. Some change occupations. Some don’t. You look at plant closings, where people go. Again, not so often a big concentration of where they go to. If you look at data on where people are hired from, you see much the same patterns. That’s kind of a much more diffuse nature.[30]

Fundamentally, the labor-economics literature has offered little guidance to date on how to define markets in labor cases. Concentration varies greatly, depending on the exact definition of the relevant market, especially the geographic market. It is virtually impossible to know what outside options to include in the relevant market, and it may not always be possible to identify even where such potential employers are located (e.g., are commuting zones better proxies for the relevant geographic labor market than metropolitan areas?). These market-definition issues are far more acute in monopsony cases than in traditional monopoly cases, both because the intrinsic question of substitutes is more complicated and because there is far less precedent to guide parties and enforcers. That makes enforcers’ jobs more difficult. But if the goal is to promote competition, instead of simply reducing the number of mergers, it is important to recognize the difficulties, rather than assume they do not exist.

If the Guidelines wish to stress labor markets and monopsony, it is also worth noting the differences. Suppose, for now, that a merger either generates efficiency gains or market power, but not both. In a monopoly case, if there are efficiency gains from a merger, the quantity sold in the output market will increase. With sufficient data, the agencies will be able to see (or estimate) the efficiencies directly in the output market. Efficiency gains result in either greater output at lower unit cost, or else product-quality improvements that increase consumer demand. In contrast, if the merger simply enhances monopoly power without efficiency gains, the quantity sold will decrease, either because the merging parties raise prices or quality declines. The empirical implication of the merger is seen directly in the market in question

The monopsony case is, however, rather more complicated. Ultimately, we can be certain of the effects of monopsony only by looking at the output market, not the input market where the monopsony power is claimed. Consider, again, a merger that generates either efficiency gains or market (in this case, monopsony) power. A merger that creates monopsony power will necessarily reduce the prices and quantity purchased of inputs like labor and materials. But this same effect (reduced prices and quantities for inputs) would also be observed if the merger is efficiency-enhancing. If there are efficiency gains, the merged entity may purchase fewer of one or more inputs than the parties did pre-merger. For example, if the efficiency gains arise from the elimination of redundancies in a hospital merger, the hospital will buy fewer inputs, hire fewer technicians, or purchase fewer medical supplies.

We have seen there are scale efficiencies associated with hospital mergers. As work from the U.S. Federal Trade Commission (FTC) Bureau of Economics explains, there can be scale efficiencies associated with “surgical procedures that exhibit a volume-outcome relationship.”[31] Typically, these are high-risk, complex procedures. “By consolidating such procedures at fewer hospitals, or by sending experienced personnel from one hospital to another, a system potentially can reap the benefits of increased scale.”[32] That is, reassignment of personnel and/or consolidation of procedures (and attendant personnel) at fewer hospitals can facilitate more efficient and higher-quality provision of services, even as it may decrease labor demand in certain geographic markets. This may even reduce the wages of technicians or the price of medical supplies, even if the newly merged hospitals do not exercise any market power to suppress wages.[33]

Taking these complications, which go beyond the concerns in standard monopoly cases, the Guidelines should also explicitly acknowledge the interactions among output markets and input markets, and what they mean for the assessment of merger efficiencies. Monopsony markets do not present a mirror image of monopoly markets. Merger reviews should therefore assess both input markets (e.g., labor) and output markets (e.g., products) simultaneously. In other words, considering some effects outside the relevant market is essential when evaluating effects in labor markets. The assessment of efficiencies must also take into account the potential offsetting effects on workers from lower wages (or slower wage growth), which is not explicitly addressed in this guidance.

III. Digital Platforms, Multi-Sided Markets and Network Effects

As a general note, it is highly doubtful that digital platforms truly warrant an overhaul of existing merger-review principles, or a lex specialis. Indeed, it is unlikely that these markets exhibit any greater tendency toward anticompetitive conduct than others. In fact, these industries—if we can call them that—tend to perform comparatively better than others. As Herbert Hovenkamp has noted, when deciding which industries they should pursue, antitrust authorities typically focus on those that are characterized by poor economic performance. By contrast:

With Big Tech, we’re looking at probably the most productive part of the economy. The rate of innovation is high. They spend a lot of money on R&D. They are among the largest patent holders. There’s very little evidence of collusion. They seem to be competing with each other quite strongly. They pay their workers relatively well and have fairly educated workforces. None of this is a sign that these are industries we should be pursuing. That doesn’t mean they don’t do some anti-competitive things. But the whole idea that we should be targeting Big Tech strikes me as fundamentally wrong-headed.[34]

As Geoffrey Manne and Dirk Auer have argued, antitrust enforcers’ hostility toward digital platforms may be fueled more by dystopian populism than actual evidence of widespread harm.[35] When revisiting the Guidelines, the Bureau should not fall for some of the fallacies that paint digital platforms as uniquely problematic or prone to anticompetitive conduct.

For instance, the Consultation states that strong network effects may make markets prone to “tipping,” especially when combined with economies of scale and the use of large volumes of data. This is an argument that has become increasingly common, and the Competition Bureau is certainly not the first to raise it. The crux of the argument is that “the collection and use of data creates a feedback loop of more data, which ultimately insulates incumbent platforms from entrants who, but for their data disadvantage, might offer a better product.”[36] This self-reinforcing cycle purportedly leads to market domination by a single firm.[37] Thus, it is argued that, e.g., Google’s “ever-expanding control of user personal data, and that data’s critical value to online advertisers, creates an insurmountable barrier to entry for new competition.”[38]

But it is important to note the conceptual problems these claims face. Because data can be used to improve the quality of products and/or to subsidize their use, the idea that data serves as an entry barrier suggests that any product improvement or price reduction made by an incumbent could be problematic for any new entrant. This is tantamount to the argument that competition itself is a cognizable barrier to entry. Of course, it would be a curious approach to antitrust if competition were treated as a problem, as it would imply that firms should under-compete—i.e., should forego consumer-welfare enhancements—in order to inculcate a greater number of firms in a given market simply for its own sake.[39]

Meanwhile, actual economic studies of data-network effects have been few and far between, with scant empirical evidence to support the theory.[40] Andrei Hagiu and Julian Wright’s theoretical paper offers perhaps the most comprehensive treatment of the topic to date.[41] The authors ultimately conclude that data-network effects can be of varying magnitudes and with varying effects on firms’ incumbency advantage.[42] They cite Grammarly (an AI writing-assistance tool) as a potential example: “As users make corrections to the suggestions offered by Grammarly, its language experts and artificial intelligence can use this feedback to continue to improve its future recommendations for all users.”[43]

Despite the paucity of evidence, however, policymakers and antitrust enforcers have been keen to embrace data-driven network-effect theories of harm. For example, it is remarkable that, in its section on “[t]he data advantage for incumbents,” the Furman Report created for the UK government cited only two empirical economic studies, and those studies offer directly contradictory conclusions with respect to the question of the strength of data advantages.[44] Nevertheless, the Furman Report concludes that data “may confer a form of unmatchable advantage on the incumbent business, making successful rivalry less likely,”[45] and adopts without reservation “convincing” evidence from non-economists that have no apparent empirical basis.[46]

This trend is likewise evident in other jurisdictions, including the EU and the United States.[47] Unfortunately, these concerns rest on little-to-no empirical evidence, either in the economic literature or the underlying case records. Accordingly, it is important that the Guidelines recognize the procompetitive aspects of so-called digital platforms, network effects, and data, rather than treating their mere existence as a smoking gun that signals anticompetitive harm. While data could, in certain circumstances, confer on a company the ability and incentive to foreclose rivals, this should be tempered by the recognition that data can also be (i) the source of procompetitive conduct that enhances consumer welfare and (ii) not an insurmountable barrier to entry.

On the latter point, consider generative AI. Given common assumptions about the advantages conferred by data and data-driven network effects, it would be reasonable to assume that firms like Google, Meta, and Amazon should be in pole position to dominate the burgeoning market for generative AI. After all, these firms have not only been at the forefront of the field for the better part of a decade, but they also have access to vast troves of data, the likes of which their rivals could only dream when they launched their own services.

To date, however, this is not how things have unfolded—although it bears noting that these markets remain in flux and the competitive landscape is susceptible to change. The first significantly successful generative-AI service was arguably not from either Meta—which had been working on chatbots for years and had access to, arguably, the world’s largest database of actual chats—or Google. Instead, the breakthrough came from a previously unknown firm called OpenAI.

This raises several crucial questions: how have these AI upstarts managed to be so successful, and is their success just a flash in the pan before Web 2.0 giants catch up and overthrow them? While we cannot answer either of these questions dispositively, we offer what we believe to be some relevant observations concerning the role and value of data in digital markets.

A first important observation is that empirical studies suggest that data exhibits diminishing marginal returns. In other words, past a certain point, acquiring more data does not confer a meaningful edge to the acquiring firm. As Catherine Tucker put it following a review of the literature: “Empirically there is little evidence of economies of scale and scope in digital data in the instances where one would expect to find them.”[48]

Likewise, following a survey of the empirical literature on the topic, Manne & Auer conclude that:

Available evidence suggests that claims of “extreme” returns to scale in the tech sector are greatly overblown. Not only are the largest expenditures of digital platforms unlikely to become proportionally less important as output increases, but empirical research strongly suggests that even data does not give rise to increasing returns to scale, despite routinely being cited as the source of this effect.[49]

Ultimately, establishing a business model to extract and organize the right information is more important than simply owning vast troves of data.[50] Even in those instances where high-quality data is an essential parameter of competition, it does not follow that having vaster databases or more users on a platform necessarily leads to better information for the platform.

Indeed, if data ownership consistently conferred a significant competitive advantage, these new firms would not be where they are today. This does not, of course, mean that data is worthless. Rather, it means that competition authorities should not assume that merely possessing data is a dispositive competitive advantage, absent compelling empirical evidence to support such a finding. In this light, the Guidelines should seek to accurately reflect the nuances surrounding data-driven advantages.

A second potential area of concern relates to conglomerate or non-horizontal mergers. The Consultation indicates that these may be important in mergers involving digital platforms, given the complementarity of the products involved. The Competition Bureau should be careful, however, not to treat every merger involving a digital platform as a de facto horizontal merger under the flawed assumption that, but for the acquisition, one of the merging firms likely would launch its own competing vertical product.[51] Similarly, if “digital ecosystems” are defined broadly to include any products that are actually or potentially complimentary, and if strengthening a “digital ecosystem” makes a merger suspect of anticompetitive harm, then virtually any acquisition involving a digital platform could, in theory, be deemed anticompetitive insofar as it would give the acquiring firm the ability (and incentive) to, e.g., give preferential treatment to its complementary product over those of rivals.

This logic could apply to anything from Amazon’s acquisition of robot vacuum cleaners (Amazon could preference its own vacuum cleaners on Marketplace); AI partnerships (Apple could “tie” an AI to its iOS); maps services (Google Maps); etc. It is easy to see the problem with this theory: it has no obvious limiting principles. Any two products could potentially be complementary in the boundless domain of “digital ecosystems.” Of course, in a given case, under specific facts and circumstances, a large, diversified tech firm might consider or achieve entry into a vertical, or “complimentary” market. But a possibility under some facts and circumstances is a far cry from a general likelihood.

The implication of this research[52] is that mergers between firms that are either vertically related or active in unrelated markets routinely or typically have significant horizontal effects.[53] This can be the case, either when merging firms are potential competitors or when they compete in innovation markets (i.e., they have overlapping R&D pipelines, or may have them in the future).[54] Endorsing this approach to merger review wholeheartedly, however, would have profound policy ramifications. Indeed, should authorities assume the counterfactual to a merger is that the acquirer will compete with the target directly, then every merger effectively becomes a horizontal one. This would obfuscate the well-established, fundamental conceptual difference between horizontal and vertical mergers.

A horizontal merger combines firms that compete in the same relevant market, which necessarily reduces the number of firms engaged in head-to-head competition and may eliminate substitutes. That reduction inherently tends to increase prices, but the price effect may be trivial. In addition, market responses (competitive repositioning or new entry) or other benefits of the merger (savings in transaction and other costs, enhanced investment incentives) may neutralize or offset the impetus to higher prices. But because those benefits are not automatic (and the reduction of direct competition is), they must be proven, rather than assumed, if the merger otherwise poses a significant risk of anticompetitive effects.

A vertical merger, by contrast, combines firms with an upstream or downstream (e.g., seller-buyer) relationship—that is, “firms or assets at different stages of the same supply chain.”[55] Examples include a manufacturer acquiring a distributor or a firm that provides a manufacturing input. The economic consequences of combining complements rather than substitutes are fundamentally different. Whereas the first-order effect of a horizontal merger is upward pricing pressure, the first-order effect of a vertical merger is downward pricing pressure. Vertical mergers typically entail the elimination of double marginalization, which is akin to downward pricing pressure (and often considered alongside efficiencies).[56]

Vertical integration also typically internalizes externalities in research and development, resulting in greater investment.[57] Like horizontal mergers, vertical mergers also often confer other benefits, such as operational and transactional efficiencies.[58] Thus, while both types of mergers can create benefits from cost savings, their intrinsic effects move in opposite directions: higher prices and less investment with horizontal mergers, and lower prices and more investment with vertical mergers.

Here, once again, the Competition Bureau should be careful not to fall prey to alarmist theories of harm, generalizations with little basis in reality, and anti-tech commotion. To avoid stifling procompetitive mergers that result in the integration of complimentary products from which consumers benefit (as well as foreclosing an important exit strategy for startups),[59] the Guidelines should be very clear as to which conglomerate mergers are problematic, and under which circumstances. Otherwise, the Competition Act risks throwing the baby out with the bathwater.

IV. Non-Price Effects and Privacy

The Bureau intends the revised Guidelines to focus on non-price effects,[60] with a clear emphasis on privacy. As the Consultation notes:

Future merger reviews may examine privacy as a non-price dimension of competition which may be harmed when competition is lessened or prevented. It may be challenging to measure impacts on privacy. As such, it may be helpful for the guidelines to include information on the aspects of privacy that may be affected by mergers, including:

• transparency regarding data practices,

• whether meaningful consent is obtained,

• the extent of data collection,

• the use or sharing of collected data,

• storage and retention terms,

• encryption and protection,

• data portability rights, or

• other parameters.[61]

While this is reasonable, in principle, and in line with antitrust law’s best practices and the consumer-welfare standard, it also merits caution.[62] The U.S. 2010 Horizontal Merger Guidelines (2010 HMGs), for example, recognized that anticompetitive effects may “be manifested in non-price terms and conditions that adversely affect consumers.”[63] This, of course, includes effects on consumer privacy. The theory behind this is that a merger between two entities—one that is more privacy-protective and one that is less—could lead to less privacy overall (framed here as more data collection for targeted advertising) because there would be one less firm to put competitive pressure on the newly merged firm. Thus, competition authorities reviewing such mergers are encouraged to consider the impact on privacy as part of their analysis.

For example, in Google’s 2007 acquisition of DoubleClick, the FTC explicitly considered the impact of the transaction on “non-price attributes of competition, such as consumer privacy.”[64] While a merger has never been blocked solely due to privacy concerns, it clearly can be analyzed as a form of non-price competition. The lack of enforcement on these grounds may, however, be due to the clear difficulties in applying such a framework.

First, non-price effects may be difficult to measure. As Doug Melamed and Nicolas Petit have pointed out:

Like all decision-makers, antitrust agencies and courts are constrained in their ability to discover facts that are imperfectly observable (e.g., successful entry deterrence), measurable (e.g., product quality) or predictable (e.g., innovation and technological progress). Some data are easier to obtain, and some facts are easier to establish. So public and private antitrust enforcers have, for reason of prudence or pragmatism, focused on price and output effects.[65]

Second, product-quality effects can be extremely difficult to distinguish from price effects. Quality-adjusted price is usually the touchstone by which antitrust regulators assess prices for competitive-effects analysis. Disentangling (allegedly) anticompetitive quality effects from simultaneous (neutral or pro-competitive) price effects is, at best, an imprecise exercise. For this reason, it is very difficult to prove a product-quality case alone and would require connecting the degradation of a particular element of product quality to a net gain in advantage for the monopolist.

This means, for example, that the price of free access for users of multi-sided platforms must be balanced against the cost of data collection.[66] For instance, most users of digital apps and websites strongly prefer free access in exchange for their data, as evidenced by the fact that very few pay for subscription models that eschew data collection. The consumer-welfare standard would require looking at the quality-adjusted price to consider whether a merger would help or harm consumers on privacy grounds. One of the tradeoffs inherent in this exercise is whether blocking a potential merger could mean higher prices for many users in the name of protecting privacy.

For example, imagine a hypothetical device maker with high levels of privacy protection that charges more for its products and requires fee-based access to apps in the app marketplace for its devices. Imagine this device maker is acquired by a rival that has lower-cost devices and mostly “free” apps in its stores, which are cross-subsidized via targeted ads powered by data collection. If an antitrust-enforcement agency rejects this acquisition on privacy grounds, there would be a potential cost to those consumers who would have experienced lower prices for the devices and free apps. Determining the tradeoffs among device and app selection, price, and privacy for the consumer-welfare analysis in such a case would be extremely difficult.

Invariably, product quality can be measured on more than one dimension. For instance, product quality could include both function and aesthetics: A watch’s quality lies in both its ability to tell time, as well as how nice it looks on your wrist. A non-price-effects analysis involving product quality across multiple dimensions becomes exceedingly difficult if there is a tradeoff in consumer welfare between the dimensions. Thus, for example, a smaller watch battery may improve its aesthetics, but also reduce its reliability. Any such analysis would necessarily involve a complex and imprecise comparison of the relative magnitudes of harm/benefit to consumers who prioritize one type of quality over another.

All other things being equal, it is plausible that consumers would prefer more privacy. But not only are there potential tradeoffs between price and privacy online, but there could be an important tradeoff between privacy and other product qualities, such as how well an algorithm for a search engine or a social-media news feed works. One of the reasons many users prefer Google over the more privacy-oriented DuckDuckGo, for instance, is because of how well the search algorithm works—empowered, in part, by data collected online.[67]

For enforcers, this again leads to a question of how to consider tradeoffs under the consumer-welfare standard. Without more information, it will be very difficult to determine whether consumers care more about data collection or the other product qualities that data collection could empower. The preferences among users about the relative weighting of product features is, moreover, likely to be highly heterogeneous, making a generalized assessment of given features exceedingly difficult.

In sum, the question of antitrust-relevant product quality really comes down to the relative numbers of, and magnitude of harm to, consumers who prefer more privacy protection versus those who prefer a better product experience and/or a lower price. To make out an antitrust case based on privacy harms, antitrust regulators would have to compare the magnitude of harms to what appears to be a small group of privacy-sensitive consumers (who have not otherwise protected themselves by using marketplace tools like tracking-blockers or the opt-out options provided by major ad networks and data brokers) to the benefits received by the supermajority of consumers who are less privacy-sensitive. Beyond the enormous difficulty of performing such analysis, it seems extraordinarily unlikely that the harms would outweigh the benefits, on net.

A final consideration is also important. When considering using competition law, enforcers should consider that Canada already has an extensive data-privacy legal framework.[68] Accordingly, any attempt to harness competition law to protect privacy should be cautious about possible unintended effects, such as barriers to competition or the generation of high compliance costs due to possible redundancies, lack of legal clarity or predictability, or even contradictions.

V. Innovation and Dynamic Competition

The Bureau’s emphasis on innovation effects in merger review is well-placed, as dynamic competition through innovation represents a crucial dimension of market rivalry that can have significant consequences for consumer welfare.[69] The relationship between market structure and innovation is, however, often ambiguous—requiring careful analysis, rather than broad presumptions. Bill C-59’s aggressive stance against concentration[70] might undercut dynamic competition, as size and scale are often conducive to innovation.

The economic literature examining the relationship between market structure and innovation presents mixed findings that defy simple characterization. As Richard Gilbert notes in his survey of the empirical literature, studies “do not reach a consensus, other than to note that innovation effects can differ dramatically for firms that are at different levels of technological sophistication.”

Table 6.1 summarizes the conclusions from these interindustry studies for the effects of competition and industry structure on innovation. Unfortunately, these studies do not reach a consensus, other than to note that innovation effects can differ dramatically for firms that are at different levels of technological sophistication. Although some studies find a positive relationship between measures of innovation and competition (alternatively, a negative relationship between innovation and industry concentration), others find that the relationship exhibits an inverted-U, with the largest effects at moderate levels of industry concentration or competition, and at least one study reports a negative relationship between competition (measured by Chinese import penetration) and innovation (measured by citation-weighted patents and R&D investment. One consistent finding is that an increase in competition has less of a beneficial effect, and may have a negative effect, on innovation incentives for firms that are far behind the industry technological frontier.[71]

This ambiguity is reflected in seemingly contradictory findings across industries. For instance, Ronald Goettler and Brett Gordon[72] found that concentration led to higher innovation rates in semiconductors, while Mitsuru Igami reached the opposite conclusion when studying the hard-disk-drive industry.[73]

Perhaps most notably, the seminal work of Philippe Aghion et al. identified an inverted-U relationship between competition and innovation.[74] This finding, however, warrants careful interpretation. While increased competition may spur innovation up to a point, the relationship varies significantly across industries and depends on numerous factors, including firms’ relative technological positioning. The relationship that holds true for the economy as a whole does not necessarily apply in any given case. While the research on market structure and innovation does not directly apply to mergers, it illustrates similar tradeoffs involved.

Looking at mergers directly, if there is an emerging consensus, it is that protecting innovation requires a nuanced, context-dependent approach, rather than blanket presumptions about market structure. Drawing directly from Marc Bourreau et al., we can develop a more nuanced understanding of the relationship between mergers and innovation.[75] The authors demonstrate that the impact of mergers on incentives for innovation can be decomposed into two fundamental effects: a market-power effect and an externality effect. This decomposition helps explain why blanket presumptions about merger effects on innovation may be misleading.

The market-power effect captures how changes in output following a merger affect innovation incentives. Specifically, when a merger reduces output, it typically diminishes firms’ incentives to innovate when innovation would increase their margins (Bourreau et al., 2024). But the authors also show that this effect’s magnitude and direction can vary depending on how the merger affects the return to investment per-unit of output.

The externality effect, meanwhile, encompasses two distinct mechanisms. First, merged entities internalize the impact of each firm’s innovation on the other firm’s demand—what the authors deem the “innovation diversion effect.” Second, mergers affect firms’ margins and therefore their incentives to innovate when innovation increases sales, termed the “demand expansion effect” (Bourreau et al., 2024). Importantly, the authors demonstrate that the externality effect’s direction depends on the relative magnitude of price-diversion versus innovation-diversion ratios.

This framework helps to explain why policies that uniformly restrict mergers may have unintended consequences for innovation. Igor Letina, Armin Schmutzler, and Regina Seibel demonstrate that prohibiting acquisitions can have a weakly negative effect on innovation, even when such policies may enhance static competition.[76] Their research identifies that this effect operates through multiple channels, including reduced incentives for startup investment when exit through acquisition is foreclosed. This finding suggests that merger policy must carefully balance static competition benefits against potential dynamic innovation effects.

The Guidelines should therefore avoid adopting what might be called a “structuralist innovation presumption”—i.e., the assumption that more firms in a market will necessarily produce greater innovation. Such a presumption would be at odds with the economic literature. The Guidelines should also recognize that innovation effects may sometimes diverge from price effects. A merger might increase market power, while simultaneously enhancing innovation output through various mechanisms, including:

1. Greater ability to internalize R&D spillovers;
2. Enhanced capacity to undertake large, risky investments; and
3. Improved ability to coordinate complementary innovative assets.

The telecommunications industry provides instructive evidence of such divergent effects. Research examining “4-to-3” mobile-carrier mergers has found that, while price effects were ambiguous, capital expenditures—a key proxy for investment and innovation —consistently increased post-merger.[77] This aligns with findings that markets with three facilities-based operators often saw the highest levels of per-firm investment, suggesting stronger incentives for infrastructure development and technological advancement. Similarly, Elena Patel and Nathan Seegert found that “hospitals in concentrated markets increased investment by 5.1 percent more than firms in competitive markets.”[78]

To properly assess innovation effects, the Guidelines should adopt a framework that:

1. Evaluates both short-term price effects and longer-term dynamic efficiency gains;
2. Considers the full range of innovation-related variables, including R&D investment, patent activity, and new product introductions;
3. Accounts for industry-specific factors that may influence the relationship between concentration and innovation;
4. Recognizes that incumbent firms, and not just new entrants, can be important sources of innovation; and
5. Maintains flexibility in market definition when analyzing innovation markets, particularly for early-stage R&D.

VI. The Repeal of the Efficiency Exception

Bill C-56 repealed the efficiency defense in Canadian merger review. Prior to the repeal, this provision meant that a merger’s anticompetitive effects could be weighed against cost savings. As Aaron Wudrick has argued: “[The efficiency defense] was an explicit acknowledgment that there are tradeoffs involved in competition.”[79] Indeed, tradeoffs under uncertainty are endemic in competition law. This is magnified in the context of merger review where, rather than addressing past misconduct, authorities must predict whether a transaction is likely to harm competition in the future.

The repeal of the efficiency defense was unfortunate. But while efficiencies are no longer relevant under s.96 of the Competition, as Wudrick points out, an efficiency defense can arguably still be invoked as “other factors” under s.93 of the Competition Act.[80] If this is the case, as it should indeed be interpreted, the Guidelines should expressly state this, and clearly establish how and when this should be claimed and proved (and who bears the burden of proof). This would help economic agents to have predictability (a fundamental characteristic of the rule of law), whether in the planning of their investments, in the structuring of their operations, or as part of the merger-control procedure.

Efficiency, after all, is the basic objective of antitrust law. Competition is not an end in itself, but rather a means to an end. We protect competition because market competition is generally the most effective way to ensure the efficient allocation of resources.[81] That is why most competition-enforcement regimes recognize that a merger that may have significant anticompetitive effects should nevertheless be permitted if it would also result in efficiency improvements that are greater than the anticompetitive effects.[82]

Efficiencies, of course, are difficult to quantify and verify. The burden of proof of the efficiencies gained through the merger should be mainly on the merging firms, considering they are the lowest-cost producer of such information.

Considering the wording of s.93, the Guidelines could follow the structure of, and include similar rules and procedures as, the European Commission’s Guidelines on the assessment of horizontal mergers,[83] which establish that:

… the Commission performs an overall competitive appraisal of the merger. In making this appraisal, the Commission takes into account the factors mentioned in Article 2(1), including the development of technical and economic progress provided that it is to the consumers’ advantage and does not form an obstacle to competition.[84]

The Commission’s guidelines, however, include a high burden of proof to accept these efficiencies, establishing that “efficiencies should be substantial and timely, and should, in principle, benefit consumers in those relevant markets where it is otherwise likely that competition concerns would occur.”[85] The bar shouldn’t be set that high, given that most mergers are pro-competitive. Projections of efficiencies should be accepted if they can be verified by reasonable means and under a preponderance-of-the-evidence standard.

VII. So-Called ‘Killer Acquisitions’ Don’t Merit a Departure from Current Standards

The consultation asks if the current guidelines “sufficiently address mergers involving nascent competitors,” which may include so-called “killer acquisitions.” While the “killer acquisitions” theory has captured the attention of scholars and authorities, and some consider them a material risk to competition (particularly in technology markets),[86] the evidence of real harm is weak. This is because the “killer acquisitions” theory does not differentiate between legitimate and efficient discontinuations of acquired products and the elimination of potential competitors.[87] Acquisitions of nascent and potential competitors undertaken with the intention of reducing competition have also been described as “killer acquisitions,” even if the acquisitions do not involve products being discontinued.[88]

Along similar lines, it is sometimes argued that large tech firms create so-called “kill zones” around their core businesses.[89] All of these practices are said to harm innovation by deterring competitors from investing in innovations that compete with incumbents.[90] The overarching theme of the above research is that existing antitrust doctrine is ill-equipped to handle these practices or, at the very least, that antitrust law should be enforced more vigorously in these settings.

But while the above research identifies important and potentially harmful conduct that cannot be dismissed out of hand, it is important to recognize its inherent limitations when it comes to informing normative policy decisions. Indeed, there is a vast difference between identifying categories of conduct that sometimes harm consumers and being able to isolate individual instances of anticompetitive behavior.[91] The above is merely a restatement of the error-cost framework, which highlights that the existence of false negatives is not a sufficient condition for heightened intervention:

The fact—if it can be proved—that there were some false negatives does not imply that there has been underenforcement with respect to the optimal level of enforcement. In other words, in the digital space the argument can be made that an optimal merger policy on average leads to ex-post “underenforcement.” Moreover, even if the level of enforcement has been lower than optimal, one must be careful not to swing to the opposite side, especially in high-tech industries. The chilling effect on innovation could be significant.[92]

Instead, it must always be the case that a change to the standards of government intervention to prevent more of these false negatives (with their inherent tradeoffs) ultimately increases social welfare overall.[93]

Take the example of Google. The company has acquired at least 270 companies over the last two decades.[94] It has been argued that some of Google’s acquisitions—including those of YouTube, Waze, and DoubleClick—may have been anticompetitive.[95] The real test for regulators, however, is whether they could reliably identify which of Google’s 270 acquisitions are actually anticompetitive, and to do so under a decision rule that causes less harm to consumers from false positives than is caused by the current false negatives.[96] If the anticompetitive mergers are such a tiny percentage of total mergers, and if identifying them a priori is difficult, then a precautionary-principle strategy that results in many false positives would likely not merit the benefits from blocking one or two anticompetitive mergers.

Indeed, but for Google and Facebook’s investments in YouTube and Instagram, respectively, it is far from clear that a mere “video-hosting service” or “photo-sharing app” would have grown into the robust competitors that advocates assume. Apart from the potential synergies arising from the combination of these products with the acquiring companies’ other products,[97] corporate control by the acquiring company may lead to these firms being better managed. This concept of M&A as creating a “market for corporate control” adds an important new dimension to the understanding of the tradeoffs involved in merger control.[98]

These anticompetitive theories of harm can be separated into three broad categories: (1) large incumbents have become so dominant in their primary markets that venture capitalists decline to fund startups that compete head-on, reducing potential competition; (2) large incumbents acquire potential competitors or non-competitor startups so as to reduce the competition along several dimensions, and (3) incumbents purchase competitors to shut down their overlapping innovation pipelines (i.e., “killer acquisitions”). With this in mind, applying the error-cost framework should lead policymakers to carefully consider the following questions when evaluating the merits and policy implications of economic research in this space:

1. Do the papers advancing these theories identify categories of conduct that, on average, harm consumer welfare?
2. If not, do the papers identify additional factors that would enable authorities to infer the existence of anticompetitive effects in individual cases?
3. If so, would it be feasible for authorities to add these factors to their analysis (in terms of time and resources)?
4. Finally, would prohibiting these practices at an individual or category level prevent efficiencies that would otherwise outweigh these anticompetitive harms? And could these efficiencies be analyzed on a case-by-case basis?

In addition to these error-cost-related questions, we must also question whether the results of these studies are relevant outside the specific markets they examine, and whether they give sufficient weight to countervailing procompetitive justifications.

The above suggests that authorities should consider the full picture before doing away with existing presumptions. For instance, while lowering merger-filing thresholds may enable enforcers to review and block some anticompetitive mergers that currently go unchallenged, it will also have other costs for which enforcement agencies must account. Indeed, lowering filing thresholds will significantly increase the number of mergers that agencies must review. This will increase enforcement costs, delay the clearance of some socially beneficial deals, and stretch agency resources (potentially leading to certain deals receiving less attention than is currently the case, which may increase both false positives and negatives).

[1] Reviewing the Merger Enforcement Guidelines,  Government of Canada, The Competition Bureau (Nov. 7, 2024), https://competition-bureau.canada.ca/how-we-foster-competition/education-and-outreach/reviewing-merger-enforcement-guidelines.

[2] An Act to Amend the Excise Tax Act and the Competition Act, 2023 (Bill C-56)(Can.).

[3] An Act to Implement Certain Provisions of the Fall Economic Statement Tabled in Parliament on November 21, 2023 and Certain Provisions of the Budget Tabled in Parliament on March 28, 2023 (Bill C-59)(Can.).

[4] Geoffrey A. Manne, Dirk Auer, Aaron Wudrick, & Mario Zúñiga, Comments of the International Center for Law & Economics and the Macdonald-Laurier Institute: Competition Bureau Canada Public Consultation on ‘Artificial Intelligence and Competition’ Discussion Paper, Int’l. Ctr. Law Econ (Aug. 13, 2024), available at https://laweconcenter.org/wp-content/uploads/2024/08/Comments-of-the-ICLE-Merger-Consultarion-AUS.pdf.

[5] Artificial Intelligence and Competition Discussion Paper, Competition Bureau of Canada (Mar. 20, 2024), https://competition-bureau.canada.ca/how-we-foster-competition/education-and-outreach/artificial-intelligence-and-competition.

[6] International Center for Law & Economics, https://laweconcenter.org.

[7] Competition Act, 1985 (R.S.C., C-34) s.92.2. (Can.).

[8] (“Market concentration is a useful, but imperfect, indicator of the competitive harm that may result from a merger”).

[9] See Harold Demsetz, Industry Structure, Market Rivalry, and Public Policy, 16 J.L. & Econ. 1 (1973); see also, e.g., Richard Schmalensee, Inter-Industry Studies of Structure and Performance, in 2 Handbook of Industrial Organization 951-1009 (Richard Schmalensee & Robert Willig, eds., 1989); William N. Evans, Luke M. Froeb, & Gregory J. Werden, Endogeneity in the Concentration-Price Relationship: Causes, Consequences, and Cures, 41 J. Indus. Econ. 431 (1993); Steven Berry, Market Structure and Competition, Redux, FTC Micro Conference (Nov. 2017), available at https://www.ftc.gov/system/files/documents/public_events/1208143/22_-_steven_berry_keynote.pdf; Nathan Miller et al., On the Misuse of Regressions of Price on the HHI in Merger Review, 10 J. Antitrust Enforcement 248 (2022).

[10] Harold Demsetz, The Intensity and Dimensionality of Competition, in Harold Demsetz, The Economics of The Business Firm: Seven Critical Commentaries 137, 140-41 (1995).

[11] Supra note 9.

[12] Shanat Ganapati, Growing Oligopolies, Prices, Output, and Productivity, 13(3) Am. Econ. J. Microecon. 309-327, 324 (Aug. 2021).

[13] Id., at 309.

[14] Timothy F. Bresnahan, Empirical Studies of Industries with Market Power, in HANDBOOK OF INDUSTRIAL ORGANIZATION, 1011, 1053-54 (Richard Schmalensee & Robert Willig, eds., 1989).

[15] Chad Syverson, Macroeconomics and Market Power: Context, Implications, and Open Questions, 33(3) J. Econ. Perspect. 23-43, 26 (2019).

[16] Nicolas Petit & Lazar Radic, The Necessity of the Consumer Welfare Standard in Antitrust Analysis, ProMarket (Dec. 18, 2023), https://www.promarket.org/2023/12/18/the-necessity-of-a-consumer-welfare-standard-in-antitrust-analysis.

[17] For example, in the EU, 94% of mergers are cleared without commitments, whereas only about 6% are allowed with remedies, and less than 0.5% of mergers are blocked or withdrawn by the parties. See Joanna Piechucka, Tomaso Duso, Klaus Gugler, & Pauline Affeldt, Using Compensating Efficiencies to Assess EU Merger Policy, VoxEU (Jan. 10, 2022), https://cepr.org/voxeu/columns/using-compensating-efficiencies-assess-eu-merger-policy; see also, Robert Kulick & Andre Card, Mergers, Industries, and Innovation: Evidence from R&D Expenditure and Patent Applications, NERA Economic Consulting (Feb. 2023), available at https://www.uschamber.com/assets/documents/NERAMergers-and-Innovation-Feb-2023.pdf (finding that mergers are responsible for as much as $13.5 billion in increased research and development expenditure annually).

[18] Aaron Wudrick, The View from Canada: A TOTM Q&A with Aaron Wudrick, Truth on the Market (Jun. 12, 2024), https://truthonthemarket.com/2024/06/12/the-view-from-canada-a-totm-qa-with-aaron-wudrick.

[19] Id.

[20] Id.

[21] On the uncertain legacy of neo-Brandeisianism, see Dirk Auer & Lazar Radic, The Legacy of Neo-Brandeisianism: History or Footnote? Network Law Review (Jul. 9, 2024) https://www.networklawreview.org/auer-radic-brandeisianism.

[22] Supra note 1.

[23] See, e.g., Suresh Naidu, Eric A. Posner, & Glen Weyl, Antitrust Remedies for Labor Market Power, 132 Harv. L. Rev. 536 (2018).

[24] For a full review of the labor-monopsony literature and how it relates to antitrust, see Brian C. Albrecht, Dirk Auer, & Geoffrey A. Manne, Labor Monopsony and Antitrust Enforcement: A Cautionary Tale, ICLE White Paper No. 2024-05-01, available at https://laweconcenter.org/wp-content/uploads/2024/05/Labor-Monopsony-Antitrust-final-.pdf.

[25] Supra note 1 (citing Jose Azar, Iona Marinescu, & Marshall Steinbaum, Labor Market Concentration, 57 J. Hum. Res. S167, S197 (Supp. 2022).

[26] See Elizabeth Weber Handwerker & Matthew Dey, Some Facts About Concentrated Labor Markets in the United States, 63 Indus. Rel. 132, 135 (2023).

[27] Efraim Benmelech, Nittai K. Bergman, & Hyunseob Kim, Strong Employers and Weak Employees, How Does Employer Concentration Affect Wages?, 57 J. Hum. Res. S200 (Supp. 2022)

[28] Ivan Kirov & James Traina, Labor Market Power and Technological Change in US Manufacturing, conference paper for Institute for Labor Economics (Oct. 2022), at 42, available at https://conference.iza.org/conference_files/Macro_2022/traina_j33031.pdf.

[29] Steven Berry, Martin Gaynor, & Fiona Scott Morton, Do Increasing Markups Matter? Lessons from Empirical Industrial Organization, 33 J. Econ. Persp. 44, 57 (2019) (emphasis added).

[30] Transcript: Public Workshop on Competition in Labor Markets, Antitrust Div. of the U.S. Justice Dep’t (Sep. 23, 2019), available at https://www.justice.gov/atr/page/file/1209071/download.

[31] Keith Brand, Martin Gaynor, Patrick McAlvanah, David Schmidt, & Elizabeth Schneirov, Economics at the FTC: Office Supply Retailers Redux, Health Care Quality Efficiencies Analysis, and Litigation of an Alleged Get Rich Quick Scheme, 45 Rev. Indus. Org. 325 (2014).

[32] Id.

[33] Some efficiency-enhancing mergers will be identifiable, of course. For example, if the merger raises quantities and prices for all inputs, that must be efficiency-enhancing. The problem, as always, is with the hard cases.

[34] Herbert Hovenkamp, What Big-Tech Antitrust Gets Wrong, Financial Times (Jan. 19, 2024), https://www.ft.com/content/4eec8bc3-c892-4704-ae66-a4432c6d4fd7.

[35] Geoffrey A. Manne & Dirk Auer, Antitrust Dystopia and Antitrust Nostalgia: Alarmist Theories of Harm in Digital Markets and Their Origins, 28 Geo. Mason. L. Rev. 1281, 1286 (2021). (“Underlying this pessimism is a pervasive assumption that new technologies will somehow undermine the competitiveness of markets, imperil innovation, and entrench dominant technology firms for decades to come. This is a form of antitrust dystopia. For its proponents, the future ushered in by digital platforms will be a bleak one—despite abundant evidence that information technology and competition in technology markets have played significant roles in the positive transformation of society”).

[36] John M. Yun, The Role of Big Data in Antitrust, in The Global Antitrust Institute Report on the Digital Economy (Joshua D. Wright & Douglas H. Ginsburg, eds., Nov. 11, 2020) at 233, https://gaidigitalreport.com/2020/08/25/big-data-and-barriers-to-entry/#_ftnref50; see also, e.g., Robert Wayne Gregory, Ola Henfridsson, Evgeny Kaganer, & Harris Kyriakou, The Role of Artificial Intelligence and Data Network Effects for Creating User Value, 46 Acad. Of. Mgmt. Rev. 534 (2020), final pre-print version at 4, http://wrap.warwick.ac.uk/134220 (“A platform exhibits data network effects if, the more that the platform learns from the data it collects on users, the more valuable the platform becomes to each user.”); see also Karl Schmedders, José Parra-Moyano, & Michael Wade, Why Data Aggregation Laws Could be the Answer to Big Tech Dominance, Silicon Republic (Feb. 6, 2024), https://www.siliconrepublic.com/enterprise/data-ai-aggregation-laws-regulation-big-tech-dominancecompetition-antitrust-imd.

[37] See also Consultation. (“Strong network effects may make certain digital markets prone to ‘tipping’ (where a single dominant firm, or group of firms, emerges in the market), especially when combined with economies of scale and scope or the use of large volumes of data.”).

[38] Nathan Newman, Search, Antitrust, and the Economics of the Control of User Data, 31 Yale J. Reg. 401, 409 (2014) (emphasis added); see also id. at 420 & 423 (“While there are a number of network effects that come into play with Google, [‘its intimate knowledge of its users contained in its vast databases of user personal data’] is likely the most important one in terms of entrenching the company’s monopoly in search advertising…. Google’s overwhelming control of user data… might make its dominance nearly unchallengeable.”).

[39] See also Yun, supra note 36, at 229 (“[I]nvestments in big data can create competitive distance between a firm and its rivals, including potential entrants, but this distance is the result of a competitive desire to improve one’s product.”).

[40] For a review of the literature on increasing returns to scale in data (this topic is broader than data-network effects), see Manne & Auer, supra note 35, at 1281, 1344.

[41] Andrei Hagiu & Julian Wright, Data-Enabled Learning, Network Effects, and Competitive Advantage, 54 Rand J. Econ. 638 (2023).

[42] Id. at 639. The authors conclude that “Data-enabled learning would seem to give incumbent firms a competitive advantage. But how strong is this advantage and how does it differ from that obtained from more traditional mechanisms…”

[43] Id.

[44] See Jason Furman, Diane Coyle, Amelia Fletcher, Derek McAuley, & Philip Marsden (Dig. Competition Expert Panel), Unlocking Digital Competition (2019), at 32-35 (“Furman Report”), available at https://assets.publishing.service.gov.uk/government/uploads/system/uploads/attachment_data/file/785547/unlocking_digital_competition_furman_review_web.pdf.

[45] Id. at 34.

[46] Id. at 35. To its credit, it should be noted, the Furman Report counsels caution before mandating access to data as a remedy to promote competition. See id. at 75. With that said, the Furman Report maintains that such a remedy should be on the table, because “the evidence suggests that large data holdings are at the heart of the potential for some platform markets to be dominated by single players and for that dominance to be entrenched in a way that lessens the potential for competition for the market.” Id. In fact, the evidence does not show this.

[47] See, e.g., Natasha Lomas, EU Checking if Microsoft’s OpenAI Investment Falls Under Merger Rules, TechCrunch (Jan. 9, 2024), https://techcrunch.com/2024/01/09/openai-microsoft-eu-merger-rules; Amended Complaint, In the Matter of Meta Platforms Inc., Mark Zuckerberg, & Within Unlimited Inc. (No. 605837), Fed. Trade Comm’n. (Oct. 13, 2022), at 11, available at https://www.ftc.gov/system/files/ftc_gov/pdf/D09411%20-%20AMENDED%20COMPLAINT%20FILED%20BY%20COUNSEL%20SUPPORTING%20THE%20COMPLAINT%20-%20PUBLIC%20%281%29_0.pdf.

[48] Catherine Tucker, Digital Data, Platforms and the Usual [Antitrust] Suspects: Network Effects, Switching Costs, Essential Facility, 54 Rev. Indus. Org. 683, 686 (2019).

[49] Auer & Manne, supra note 35, at 1345.

[50] See Yun, supra note 36, at 235 (“Even if data is primarily responsible for a platform’s quality improvements, these improvements do not simply materialize with the presence of more data—which differentiates the idea of data-driven network effects from direct network effects. A firm needs to intentionally transform raw, collected data into something that provides analytical insights. This transformation involves costs including those associated with data storage, organization, and analytics, which moves the idea of collecting more data away from a strict network effect to more of a ‘data opportunity.’”).

[51] See, e.g., Cristina Caffarra, Gregory S. Crawford, & Tommaso Valletti, “How Tech Rolls”: Potential Competition and “Reverse” Killer Acquisitions, Antitrust Chronicle (May 26, 2020) (“Large digital platforms in particular have exceptional abilities to pursue organic expansion but also opportunities to ‘roll up’ (willing) startups to ‘get there faster’, ‘buying’ instead of expending effort in rival innovation. Foregoing such effort is never good for consumers and society as a whole: while innovative effort is costly, it will often yield multiple providers and differentiated services, with socially desirable properties.”).

[52] Id.

[53] See, e.g., Steven C. Salop, Potential Competition and Antitrust Analysis: Monopoly Profits Exceed Duopoly Profits, Working Paper (Apr. 28, 2021), available at https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3839631; see also C. Scott Hemphill & Tim Wu, Nascent Competitors, 168 U. Pa. L. Rev. 1879 (2019).

[54] See, e.g., Salop, id. See also Giulio Federico, Gregor Langus, & Tommaso Valletti, Horizontal Mergers and Product Innovation, 59 Int’l J. Indus. Org. 1 (2018).

[55] U.S. Dep’t of Justice, Antitrust Div. & F.T.C., Vertical Merger Guidelines 1 (2020).

[56] David Reiffen & Michael Vita, Comment: Is There New Thinking on Vertical Mergers? 63 Antitrust L.J. 917, 920 (1995).

[57] Henry Ogden Armour & David J. Teece, Vertical Integration and Technological Innovation, 62 Rev. Econ. & Stat. 470 (1980).

[58] Dennis W. Carlton, Transaction Costs and Competition Policy, 73 Int’l J. Indus. Org. 1 (2019); Oliver Williamson, The Economic Institutions of Capitalism 86 (1985).

[59] On this point, see Sam Bowman & Sam Dimitriu, Better Together: The Procompetitive Effects of Mergers in Tech, The Entrepreneurs Network (Sep. 13, 2021), https://www.tenentrepreneurs.org/research/better-together-the-procompetitive-effects-of-mergers-in-tech (arguing that acquisition is a key route to exit for entrepreneurs).

[60] Supra note 1, Section 2.8.

[61] Id.

[62] On non-price dimensions of the consumer-welfare standard, see Nicolas Petit & Lazar Radic, The Superiority of the Consumer Welfare Standard, EUI Law Working Paper 2024/20, 16-19 (2024).

[63] U.S. Dep’t of Justice & F.T.C., Horizontal Merger Guidelines (2010), available at https://www.justice.gov/sites/default/files/atr/legacy/2010/08/19/hmg-2010.pdf.

[64] Statement of the Federal Trade Commission, Google/DoubleClick, No. 071-0170, available at https://www.ftc.gov/system/files/documents/public_statements/418081/071220googledc-commstmt.pdf.

[65] Douglas A. Melamed & Nicolas Petit, The Misguided Attack on the Consumer Welfare Standard in the Age of Platform Markets. 54 Rev. Indus. Org. 741, 753 (2019).

[66] See, e.g., Alastair R. Beresford, Dorothea Ku?bler, & So?ren Preibusch, Unwillingness to Pay for Privacy: A Field Experiment (SFB 649 Discussion Paper 2011-010, 2011), available at https://ftp.iza.org/dp5017.pdf; Jens Grossklags & Alessandro Acquisti, When 25 Cents Is Too Much: An Experiment on Willingness-to-Sell and Willingness-to-Protect Personal Information, in Proceedings of the Sixth Workshop on the Economics of Information Security (2007), available at https://econinfosec.org/archive/weis2007/papers/66.pdf; Mary Ellen Gordon, The History of App Pricing, and Why Most Apps are Free, The Flurry Blog (Jul. 18, 2013), http://blog.flurry.com/bid/99013/The-History-of-App-Pricing-AndWhy-Most-Apps-Are-Free.

[67] Though not the only important explanation of the quality of the algorithm, data collection—especially for indexing purposes—has been a bigger driver of Google’s success. See, e.g., Daisuke Wakabayashi, Google Dominates Thanks to an Unrivaled View of the Web, N.Y. Times (Dec. 14, 2020), https://www.nytimes.com/2020/12/14/technology/howgoogle-dominates.html.

[68] See, e.g., Canada’s Privacy Act, the Charter of Rights and Freedoms, the Criminal Code, local government’s personal information-protection laws, the Personal Information Protection and Electronic Documents Act (PIPEDA), among others.

[69] See, e.g., Consultation. (“The Competition Tribunal previously described innovation as ‘the most important type of competition’ and confirmed that harm to dynamic competition and innovation can be central to a finding of substantial prevention or lessening of competition”)(references omitted for coherence).

[70] See generally, Section I.

[71] Richard J. Gilbert, Innovation Matters: Competition Policy for the High-Technology Economy, 116 (2020)

[72] Ronald L. Goettler & Brett R. Gordon, Does AMD Spur Intel to Innovate More?, 119 J. Pol. Econ. 1141, 1141 (2011)

[73] Mitsuru Igami, Estimating the Innovator’s Dilemma: Structural Analysis of Creative Destruction in the Hard Disk Drive Industry, 1981–1998, 125 J. Pol. Econ. 798, 798 (2017)

[74] Philippe Aghion, Nick Bloom, Richard Blundell, Rachel Griffith, & Peter Howitt, Competition and Innovation: An Inverted-U Relationship, 120 Q. J. Econ. 702 (2005).

[75] Marc Bourreau, Bruno Jullien, & Yassine Lefouili, Horizontal Mergers and Incremental Innovation, HAL Open Science (2024), available at https://hal.science/hal-04790973v1/document.

[76] Igor Letina, Armin Schmutzler, & Regina Seibel, Killer Acquisitions and Beyond: Policy Effects on Innovation Strategies, 65 Int. Ec. Rev. 591-622 (Feb. 20, 2024), https://onlinelibrary.wiley.com/doi/10.1111/iere.12689.

[77] Eric Fruits, Justin (Gus) Hurwitz, Geoffrey A. Manne, Julian Morris, & Alec Stapp, Static and Dynamic Effects of Mergers: A Review of the Empirical Evidence in the Wireless Telecommunications Industry, OECD Directorate for Financial and Enterprise Affairs Competition Committee, Global Forum on Competition, DAF/COMP/GF(2019)13 (Sep. 4, 2020), available at https://one.oecd.org/document/DAF/COMP/GF(2019)13/en/pdf.

[78] Elena Patel & Nathan Seegert, Does Market Power Encourage or Discourage Investment? Evidence From the Hospital Market, 63 J.L. Econ. 667, 667 (2020)

[79] Supra note 18.

[80] Id. See also Competition Act, s.93(h).

[81] OECD, Interim Report on Convergence of Competition Policies, GD(94)64, at Annex, para. 4

[82] Id. See, e.g., the 2010 HMGs and European Commission’s Merger Regulation, Council Regulation No. 139/2004 (Jan. 20, 2004).

[83] Guidelines on the Assessment of Horizontal Mergers Under the Council Regulation on the Control of Concentrations Between Undertakings, C 31/03, European Commission (2004).

[84] Id., para 76.

[85] Id., para 79.

[86] Jonathan Barnett, “Killer Acquisitions” Reexamined: Economic Hyperbole in the Age of Populist Antitrust, 3 U. Chic. Law Rev. 39 (2023), at 42.

[87] See, e.g., Axel Gautier & Joe Lamesch, Mergers in the Digital Economy, 54 Info. Econ. & Pol’y (2000) (“There are three reasons to discontinue a product post acquisition: the product is not as successful as expected, the acquisition was not motivated by the product itself but by the target’s assets or R&D effort, or by the elimination of a potential competitive threat. While our data does not enable us to screen between these explanations, the present analysis shows that most of the startups are killed in their infancy.”).

[88] John M. Yun, Potential Competition, Nascent Competitors, and Killer Acquisitions, 18 Global Antitrust Institute Report on the Digital Economy 652, 652–53 (2020).

[89] Sai Krishna Kamepalli, Raghuram Rajan, & Luigi Zingales, Kill Zone (NBER Working Paper 85, 2020), at 40

[90] Colleen Cunningham, Florian Ederer, & Song Ma, Killer Acquisitions, 129 J. Pol. Econ. 649-702 (2021), at 694.

[91] It remains important to distinguish conduct that harms consumers overall from conduct that merely harms certain parameters of competition, while improving others. In other words, antitrust law should prohibit conduct when the category to which that conduct belongs is generally harmful to consumers and/or when harmful occurrences of that conduct can be readily distinguished. See, e.g., Eric Fruits et al., supra note 77 at 18 (“Studies that do not consider these [non-price] effects are incomplete for purposes of evaluating the mergers’ consumer welfare effects, and [are] all-too easily used by advocates to misleadingly predict negative consumer outcomes. This is not necessarily a criticism of the studies themselves, which generally do not make comprehensive policy conclusions. The reality is that it is exceptionally difficult to comprehensively study even price effects, such that a well conducted study of price effects alone is a valuable contribution to the literature. Nevertheless, in the context of evaluating prospective transactions, the results of such studies must be discounted to account for their exclusion of non-price effects.”).

[92] Luís Cabral, Merger Policy in Digital Industries (CEPR Discussion Paper No. DP14785, May 2020), at 12, https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3612854.

[93] See Carl Shapiro, Antitrust in a Time of Populism, 61 Int’l J. Indus. Org. 714, 741 (2018).

[94] See id. at 740.

[95] Id.

[96] Id.

[97] For example, YouTube’s search and recommendations engines being developed by Google, the world’s leading internet-search company, or Instagram’s ad platform being integrated with Facebook’s.

[98] See Henry G. Manne, Mergers and the Market for Corporate Control, 73 J. Pol. Econ. 110 (1965), at 117–19.