[This post adapts elements of “Technology Mergers and the Market for Corporate Control,” forthcoming in the Missouri Law Review.]

In recent years, a growing chorus of voices has argued that existing merger rules fail to apprehend competitively significant mergers, either because they fall below existing merger-filing thresholds or because they affect innovation in ways that are purportedly ignored.

These fears are particularly acute in the pharmaceutical and tech industries, where several high-profile academic articles and reports claim to have identified important gaps in current merger-enforcement rules, particularly with respect to acquisitions involving nascent and potential competitors (here, here, and here, among many others).

Such fears have led activists, lawmakers, and enforcers to call for tougher rules, including the introduction of more stringent merger-filing thresholds and other substantive changes, such as the inversion of the burden of proof when authorities review mergers and acquisitions involving digital platforms.

However, as we discuss in a recent working paper—forthcoming in the Missouri Law Review and available on SSRN—these proposals tend to overlook the important tradeoffs that would ensue from attempts to decrease the number of false positives under existing merger rules and thresholds.

The paper draws from two key strands of economic literature that are routinely overlooked (or summarily dismissed) by critics of the status quo.

For a start, antitrust enforcement is not costless. In the case of merger enforcement, not only is it expensive for agencies to detect anticompetitive deals but, more importantly, overbearing rules may deter beneficial merger activity that creates value for consumers.

Second, critics tend to overlook the possibility that incumbents’ superior managerial or other capabilities (i.e., what made them successful in the first place) makes them the ideal acquisition partners for entrepreneurs and startup investors looking to sell.

The result is a body of economic literature that focuses almost entirely on hypothetical social costs, while ignoring the redeeming benefits of corporate acquisitions, as well as the social cost of enforcement.

Kill Zones

One of the most significant allegations leveled against large tech firms is that their very presence in a market may hinder investments, entry, and innovation, creating what some have called a “kill zone.” The strongest expression in the economic literature of this idea of a kill zone stems from a working paper by Sai Krishna Kamepalli, Raghuram Rajan, and Luigi Zingales.

The paper makes two important claims, one theoretical and one empirical. From a theoretical standpoint, the authors argue that the prospect of an acquisition by a dominant platform deters consumers from joining rival platforms, and that this, in turn, hampers the growth of these rivals. The authors then test a similar hypothesis empirically. They find that acquisitions by a dominant platform—such as Google or Facebook—decrease investment levels and venture capital deals in markets that are “similar” to that of the target firm.

But both findings are problematic. For a start, Zingales and his co-authors’ theoretical model is premised on questionable assumptions about the way in which competition develops in the digital space. The first is that early adopters of new platforms—called “techies” in the authors’ parlance—face high switching costs because of their desire to learn these platforms in detail. As an initial matter, it would appear facially contradictory that “techies” both are the group with the highest switching costs and that they switch the most. The authors further assume that “techies” would incur lower adoption costs if they remained on the incumbent platform and waited for the rival platform to be acquired.

Unfortunately, while these key behavioral assumptions drive the results of the theoretical model, the paper presents no evidence to support their presence in real-world settings. In that sense, the authors commit the same error as previous theoretical work concerning externalities, which have tended to overestimate their frequency.

Second, the empirical analysis put forward in the paper is unreliable for policymaking purposes. The authors notably find that:

[N]ormalized VC investments in start-ups in the same space as the company acquired by Google and Facebook drop by over 40% and the number of deals falls by over 20% in the three years following an acquisition.

However, the results of this study are derived from the analysis of only nine transactions. The study also fails to clearly show that firms in the treatment and controls are qualitatively similar. In a nutshell, the study compares industry acquisitions exceeding $500 million to Facebook and Google’s acquisitions that exceed that amount. This does not tell us whether the mergers in both groups involved target companies with similar valuations or similar levels of maturity. This does not necessarily invalidate the results, but it does suggest that policymakers should be circumspect in interpreting those results.

Finally, the paper fails to demonstrate evidence that existing antitrust regimes fail to achieve an optimal error-cost balance. The central problem is that the paper has indeterminate welfare implications. For instance, as the authors note, the declines in investment in spaces adjacent to the incumbent platforms occurred during a time of rapidly rising venture capital investment, both in terms of the number of deals and dollars invested. It is entirely plausible that venture capital merely shifted to other sectors.

Put differently, on its own terms, the evidence merely suggests that acquisitions by Google and Facebook affected the direction of innovation, not its overall rate. And there is little to suggest that this shift was suboptimal, from a welfare standpoint.

In short, as the authors themselves conclude: “[i]t would be premature to draw any policy conclusion on antitrust enforcement based solely on our model and our limited evidence.”

Mergers and Potential Competition

Scholars have also posited more direct effects from acquisitions of startups or nascent companies by incumbent technology market firms.

Some scholars argue that incumbents might acquire rivals that do not yet compete with them directly, in order to reduce the competitive pressure they will face in the future. In his paper “Potential Competition and Antitrust Analysis: Monopoly Profits Exceed Duopoly Profits,” Steven Salop argues:

Acquisitions of potential or nascent competitors by a dominant firm raise inherent anticompetitive concerns. By eliminating the procompetitive impact of the entry, an acquisition can allow the dominant firm to continue to exercise monopoly power and earn monopoly profits. The dominant firm also can neutralize the potential innovation competition that the entrant would provide.

However, these antitrust theories of harm suffer from several important flaws. They rest upon several restrictive assumptions that are not certain to occur in real-world settings. Most are premised on the notion that, in a given market, monopoly profits generally exceed joint duopoly profits. This allegedly makes it profitable, and mutually advantageous, for an incumbent to protect its monopoly position by preemptively acquiring potential rivals.

Accordingly, under these theories, anticompetitive mergers are only possible when the acquired rival could effectively challenge the incumbent. But these are, of course, only potential challengers; there is no guarantee that any one of them could or would mount a viable competitive threat.

Less obviously, it must be the case that the rival can hope to share only duopoly profits, as opposed to completely overthrowing the incumbent or surpassing them with a significantly larger share of the market. Where competition is “for the market” itself, monopoly maintenance would fail to explain a rival’s decision to sell.  Because there would be no asymmetry between the expected profits of the incumbent and the rival, monopoly maintenance alone would not give rise to mutually advantageous deals.

Second, potential competition does not always increase consumer welfare.  Indeed, while the presence of potential competitors might increase price competition, it can also have supply-side effects that cut in the opposite direction.

For example, as Nobel laureate Joseph Stiglitz observed, a monopolist threatened by potential competition may invest in socially wasteful R&D efforts or entry-deterrence mechanisms, and it may operate at below-optimal scale in anticipation of future competitive entry.

There are also pragmatic objections. Analyzing a merger’s effect on potential competition would compel antitrust authorities and courts to make increasingly speculative assessments concerning the counterfactual setting of proposed acquisitions.

In simple terms, it is far easier to determine whether a merger between McDonald’s and Burger King would lead to increased hamburger prices in the short run than it is to determine whether a gaming platform like Steam or the Epic Games Store might someday compete with video-streaming or music-subscription platforms like Netflix or Spotify. It is not that the above models are necessarily wrong, but rather that applying them to practical cases would require antitrust enforcers to estimate mostly unknowable factors.

Finally, the real test for regulators is not just whether they can identify possibly anticompetitive mergers, but whether they can do so in a cost-effective manner. Whether it is desirable to implement a given legal test is not simply a function of its accuracy, the cost to administer it, and the respective costs of false positives and false negatives. It also critically depends on how prevalent the conduct is that adjudicators would be seeking to foreclose.

Consider two hypothetical settings. Imagine there are 10,000 tech mergers in a given year, of which either 1,000 or 2,500 are anticompetitive (the remainder are procompetitive or competitively neutral). Suppose that authorities can either attempt to identify anticompetitive mergers with 75% accuracy, or perform no test at all—i.e., letting all mergers go through unchallenged.

If there are 1,000 anticompetitive mergers, applying the test would result in 7,500 correct decisions and 2,500 incorrect ones (2,250 false positives and 250 false negatives). Doing nothing would lead to 9,000 correct decisions and 1,000 false negatives. If the number of anticompetitive deals were 2,500, applying the test would lead to the same number of incorrect decisions as not applying it (1,875 false positives and 625 false negatives, versus 2,500 false negatives). The advantage would tilt toward applying the test if anticompetitive mergers were even more widespread.

This hypothetical example holds a simple lesson for policymakers: the rarer the conduct that they are attempting to identify, the more accurate their identification method must be, and the more costly false negatives must be relative to false positives.

As discussed below, current empirical evidence does not suggest that anticompetitive mergers of this sort are particularly widespread, nor does it offer accurate heuristics to detect the ones that are. Finally, there is little sense that the cost of false negatives significantly outweighs that of false positives. In short, there is currently little evidence to suggest that tougher enforcement would benefit consumers.

Killer Acquisitions

Killer acquisitions are, effectively, a subset of the “potential competitor” mergers discussed in the previous section. As defined by Colleen Cunningham, Florian Ederer, and Song Ma, they are those deals where “an incumbent firm may acquire an innovative target and terminate the development of the target’s innovations to preempt future competition.”

Cunningham, Ederer, and Ma’s highly influential paper on killer acquisitions has been responsible for much of the recent renewed interest in the effect that mergers exert on innovation. The authors studied thousands of pharmaceutical mergers and concluded that between 5.3% and 7.4% of them were killer acquisitions. As they write:

[W]e empirically compare development probabilities of overlapping acquisitions, which are, in our theory, motivated by a mix of killer and development intentions, and non-overlapping acquisitions, which are motivated only by development intentions. We find an increase in acquisition probability and a decrease in post-acquisition development for overlapping acquisitions and interpret that as evidence for killer acquisitions. […]

[W]e find that projects acquired by an incumbent with an overlapping drug are 23.4% less likely to have continued development activity compared to drugs acquired by non-overlapping incumbents.

From a policy standpoint, the question is what weight antitrust authorities, courts, and legislators should give to these findings. Stated differently, does the paper provide sufficient evidence to warrant reform of existing merger-filing thresholds and review standards? There are several factors counseling that policymakers should proceed with caution.

To start, the study’s industry-specific methodology means that it may not be a useful guide to understand acquisitions in other industries, like the tech sector, for example.

Second, even if one assumes that the findings of Cunningham, et al., are correct and apply with equal force in the tech sector (as some official reports have), it remains unclear whether the 5.3–7.4% of mergers they describe warrant a departure from the status quo.

Antitrust enforcers operate under uncertainty. The critical policy question is thus whether this subset of anticompetitive deals can be identified ex-ante. If not, is there a heuristic that would enable enforcers to identify more of these anticompetitive deals without producing excessive false positives?

The authors focus on the effect that overlapping R&D pipelines have on project discontinuations. In the case of non-overlapping mergers, acquired projects continue 17.5% of the time, while this number is 13.4% when there are overlapping pipelines. The authors argue that this gap is evidence of killer acquisitions. But it misses the bigger picture: under the authors’ own numbers and definition of a “killer acquisition,” a vast majority of overlapping acquisitions are perfectly benign; prohibiting them would thus have important social costs.

Third, there are several problems with describing this kind of behavior as harmful. Indeed, Cunningham, et al., acknowledge that this kind of behavior could increase innovation by boosting the returns to innovation.

And even if one ignores incentives to innovate, product discontinuations can improve consumer welfare. This question ultimately boils down to identifying the counterfactual to a merger. As John Yun writes:

For instance, an acquisition that results in a discontinued product is not per se evidence of either consumer harm or benefit. The answer involves comparing the counterfactual world without the acquisition with the world with the acquisition. The comparison includes potential efficiencies that were gained from the acquisition, including integration of intellectual property, the reduction of transaction costs, economies of scope, and better allocation of skilled labor.

One of the reasons R&D project discontinuation may be beneficial is simply cost savings. R&D is expensive. Pharmaceutical firms spend up to 27.8% of their annual revenue on R&D. Developing a new drug has an estimated median cost of $985.3 million. Cost-cutting—notably as it concerns R&D—is thus a critical part of pharmaceutical (as well as tech) companies’ businesses. As a report by McKinsey concludes:

The recent boom in M&A in the pharma industry is partly the result of attempts to address short-term productivity challenges. An acquiring or merging company typically designs organization-wide integration programs to capture synergies, especially in costs. Such programs usually take up to three years to complete and deliver results.

Another report finds that:

Maximizing the efficiency of production labor and equipment is one important way top-quartile drugmakers break out of the pack. Their rates of operational-equipment effectiveness are more than twice those of bottom-quartile companies (Exhibit 1), and when we looked closely we found that processes account for two-thirds of the difference.

In short, pharmaceutical companies do not just compete along innovation-related parameters, though these are obviously important, but also on more traditional grounds such as cost-rationalization. Accordingly, as the above reports suggest, pharmaceutical mergers are often about applying an incumbent’s superior managerial efficiency to the acquired firm’s assets through operation of the market for corporate control.

This cost-cutting (and superior project selection) ultimately enables companies to offer lower prices, thereby benefiting consumers and increasing their incentives to invest in R&D in the first place by making successfully developed drugs more profitable.

In that sense, Henry Manne’s seminal work relating to mergers and the market for corporate control sheds at least as much light on pharmaceutical (and tech) mergers as the killer acquisitions literature. And yet, it is hardly ever mentioned in modern economic literature on this topic.

While Colleen Cunningham and her co-authors do not entirely ignore these considerations, as we discuss in our paper, their arguments for dismissing them are far from watertight.

A natural extension of the killer acquisitions work is to question whether mergers of this sort also take place in the tech industry. Interest in this question is notably driven by the central role that digital markets currently occupy in competition-policy discussion, but also by the significant number of startup acquisitions that take place in the tech industry. However, existing studies provide scant evidence that killer acquisitions are a common occurrence in these markets.

This is not surprising. Unlike in the pharmaceutical industry—where drugs need to go through a lengthy and visible regulatory pipeline before they can be sold—incumbents in digital industries will likely struggle to identify their closest rivals and prevent firms from rapidly pivoting to seize new commercial opportunities. As a result, the basic conditions for killer acquisitions to take place (i.e., firms knowing they are in a position to share monopoly profits) are less likely to be present; it also would be harder to design research methods to detect these mergers.

The empirical literature on killer acquisitions in the tech sector is still in its infancy. But, as things stand, no study directly examines whether killer acquisitions actually take place in digital industries (i.e., whether post-merger project discontinuations are more common in overlapping than non-overlapping tech mergers). This is notably the case for studies by Axel Gautier & Joe Lamesch, and Elena Argentesi and her co-authors. Instead, these studies merely show that product discontinuations are common after an acquisition by a big tech company.

To summarize, while studies of this sort might suggest that the clearance of certain mergers might not have been optimal, it is hardly a sufficient basis on which to argue that enforcement should be tightened.

The reason for this is simple. The fact that some anticompetitive mergers may have escaped scrutiny and/or condemnation is never a sufficient basis to tighten rules. For that, it is also necessary to factor in the administrative costs of increased enforcement, as well as potential false convictions to which it might give rise. As things stand, economic research on killer acquisitions in the tech sector does not warrant tougher antitrust enforcement, though it does show the need for further empirical research on the topic.

Conclusion

Many proposed merger-enforcement reforms risk throwing the baby out with the bathwater. Mergers are largely beneficial to society (here, here and here); anticompetitive ones are rare; and there is little way, at the margin, to tell good from bad. To put it mildly, there is a precious baby that needs to be preserved and relatively little bathwater to throw out.

Take the fulcrum of policy debates that is the pharmaceutical industry. It is not hard to point to pharmaceutical mergers (or long-term agreements) that have revolutionized patient outcomes. Most recently, Pfizer and BioNTech’s efforts to successfully market an mRNA vaccine against COVID-19 offers a case in point.

The deal struck by both firms could naïvely be construed as bearing hallmarks of a killer acquisition or an anticompetitive agreement (long-term agreements can easily fall into either of these categories). Pfizer was a powerful incumbent in the vaccine industry; BioNTech threatened to disrupt the industry with new technology; and the deal likely caused Pfizer to forgo some independent R&D efforts. And yet, it also led to the first approved COVID-19 vaccine and groundbreaking advances in vaccine technology.

Of course, the counterfactual is unclear, and the market might be more competitive absent the deal, just as there might be only one approved mRNA vaccine today instead of two—we simply do not know. More importantly, this counterfactual was even less knowable at the time of the deal. And much the same could be said about countless other pharmaceutical mergers.

The key policy question is how authorities should handle this uncertainty. Critics of the status quo argue that current rules and thresholds leave certain anticompetitive deals unchallenged. But these calls for tougher enforcement fail to satisfy the requirements of the error-cost framework. Critics have so far failed to show that, on balance, mergers harm social welfare—even overlapping ones or mergers between potential competitors—just as they are yet to suggest alternative institutional arrangements that would improve social welfare.

In other words, they mistakenly analyze purported false negatives of merger-enforcement regimes in isolation. In doing so, they ignore how measures that aim to reduce such judicial errors may lead to other errors, as well as higher enforcement costs. In short, they paint a world where policy decisions involve facile tradeoffs, and this undermines their policy recommendations.

Given these significant limitations, this body of academic research should be met with an appropriate degree of caution. For all the criticism it has faced, the current merger-review system is mostly a resounding success. It is administrable, predictable, and timely. Yet it also eliminates a vast majority of judicial errors: even its critics concede that false negatives make up only a tiny fraction of decisions. Policymakers must decide whether the benefits from catching the very few arguably anticompetitive mergers that currently escape prosecution outweigh the significant costs that are required to achieve this goal. There is currently little evidence to suggest that this is, indeed, the case.

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