Archives For Competition law

[TOTM: The following is part of a symposium by TOTM guests and authors marking the release of Nicolas Petit’s “Big Tech and the Digital Economy: The Moligopoly Scenario.” The entire series of posts is available here.

This post is authored by Peter Klein (Professor of Entrepreneurship, Baylor University).
]

Nicolas Petit’s insightful and provocative book ends with a chapter on “Big Tech’s Novel Harms,” asking whether antitrust is the appropriate remedy for popular (and academic) concerns about privacy, fake news, and hate speech. In each case, he asks whether the alleged harms are caused by a lack of competition among platforms – which could support a case for breaking them up – or by the nature of the underlying technologies and business models. He concludes that these problems are not alleviated (and may even be exacerbated) by applying competition policy and suggests that regulation, not antitrust, is the more appropriate tool for protecting privacy and truth.

What kind of regulation? Treating digital platforms like public utilities won’t work, Petit argues, because the product is multidimensional and competition takes place on multiple margins (the larger theme of the book): “there is a plausible chance that increased competition in digital markets will lead to a race to the bottom, in which price competition (e.g., on ad markets) will be the winner, and non-price competition (e.g., on privacy) will be the loser.” Utilities regulation also provides incentives for rent-seeking by less efficient rivals. Retail regulation, aimed at protecting small firms, may end up helping incumbents instead by raising rivals’ costs.

Petit concludes that consumer protection regulation (such as Europe’s GDPR) is a better tool for guarding privacy and truth, though it poses challenges as well. More generally, he highlights the vast gulf between the economic analysis of privacy and speech and the increasingly loud calls for breaking up the big tech platforms, which would do little to alleviate these problems.

As in the rest of the book, Petit’s treatment of these complex issues is thoughtful, careful, and systematic. I have more fundamental problems with conventional antitrust remedies and think that consumer protection is problematic when applied to data services (even more so than in other cases). Inspired by this chapter, let me offer some additional thoughts on privacy and the nature of data which speak to regulation of digital platforms and services.

First, privacy, like information, is not an economic good. Just as we don’t buy and sell information per se but information goods (books, movies, communications infrastructure, consultants, training programs, etc.), we likewise don’t produce and consume privacy but what we might call privacy goods: sunglasses, disguises, locks, window shades, land, fences and, in the digital realm, encryption software, cookie blockers, data scramblers, and so on.

Privacy goods and services can be analyzed just like other economic goods. Entrepreneurs offer bundled services that come with varying degrees of privacy protection: encrypted or regular emails, chats, voice and video calls; browsers that block cookies or don’t; social media sites, search engines, etc. that store information or not; and so on. Most consumers seem unwilling to sacrifice other functionality for increased privacy, as suggested by the small market shares held by DuckDuckGo, Telegram, Tor, and the like suggest. Moreover, while privacy per se is appealing, there are huge efficiency gains from matching on buyer and seller characteristics on sharing platforms, digital marketplaces, and dating sites. There are also substantial cost savings from electronic storage and sharing of private information such as medical records and credit histories. And there is little evidence of sellers exploiting such information to engage in price discrimination. (Aquisti, Taylor, and Wagman, 2016 provide a detailed discussion of many of these issues.)

Regulating markets for privacy goods via bans on third-party access to customer data, mandatory data portability, and stiff penalties for data breaches is tricky. Such policies could make digital services more valuable, but it is not obvious why the market cannot figure this out. If consumers are willing to pay for additional privacy, entrepreneurs will be eager to supply it. Of course, bans on third-party access and other forms of sharing would require a fundamental change in the ad-based revenue model that makes free or low-cost access possible, so platforms would have to devise other means of monetizing their services. (Again, many platforms already offer ad-free subscriptions, so it’s unclear why those who prefer ad-based, free usage should be prevented from doing so.)

What about the idea that I own “my” data and that, therefore, I should have full control over how it is used? Some of the utilities-based regulatory models treat platforms as neutral storage places or conduits for information belonging to users. Proposals for data portability suggest that users of technology platforms should be able to move their data from platform to platform, downloading all their personal information from one platform then uploading it to another, then enjoying the same functionality on the new platform as longtime users.

Of course, there are substantial technical obstacles to such proposals. Data would have to be stored in a universal format – not just the text or media users upload to platforms, but also records of all interactions (likes, shares, comments), the search and usage patterns of users, and any other data generated as a result of the user’s actions and interactions with other users, advertisers, and the platform itself. It is unlikely that any universal format could capture this information in a form that could be transferred from one platform to another without a substantial loss of functionality, particularly for platforms that use algorithms to determine how information is presented to users based on past use. (The extreme case is a platform like TikTok which uses usage patterns as a substitute for follows, likes, and shares, portability to construct a “feed.”)

Moreover, as each platform sets its own rules for what information is allowed, the import functionality would have to screen the data for information allowed on the original platform but not the new (and the reverse would be impossible – a user switching from Twitter to Gab, for instance, would have no way to add the content that would have been permitted on Gab but was never created in the first place because it would have violated Twitter rules).

There is a deeper, philosophical issue at stake, however. Portability and neutrality proposals take for granted that users own “their” data. Users create data, either by themselves or with their friends and contacts, and the platform stores and displays the data, just as a safe deposit box holds documents or jewelry and a display case shows of an art collection. I should be able to remove my items from the safe deposit box and take them home or to another bank, and a “neutral” display case operator should not prevent me from showing off my preferred art (perhaps subject to some general rules about obscenity or harmful personal information).

These analogies do not hold for user-generated information on internet platforms, however. “My data” is a record of all my interactions with platforms, with other users on those platforms, with contractual partners of those platforms, and so on. It is co-created by these interactions. I don’t own these records any more than I “own” the fact that someone saw me in the grocery store yesterday buying apples. Of course, if I have a contract with the grocer that says he will keep my purchase records private, and he shares them with someone else, then I can sue him for breach of contract. But this isn’t theft. He hasn’t “stolen” anything; there is nothing for him to steal. If a grocer — or an owner of a tech platform — wants to attract my business by monetizing the records of our interactions and giving me a cut, he should go for it. I still might prefer another store. In any case, I don’t have the legal right to demand this revenue stream.

Likewise, “privacy” refers to what other people know about me – it is knowledge in their heads, not mine. Information isn’t property. If I know something about you, that knowledge is in my head; it’s not something I took from you. Of course, if I obtained or used that info in violation of a prior agreement, then I’m guilty of breach, and I use that information to threaten or harass you, I may be guilty of other crimes. But the popular idea that tech companies are stealing and profiting from something that’s “ours” isn’t right.

The concept of co-creation is important, because these digital records, like other co-created assets, can be more or less relationship specific. The late Oliver Williamson devoted his career to exploring the rich variety of contractual relationships devised by market participants to solve complex contracting problems, particularly in the face of asset specificity. Relationship-specific investments can be difficult for trading parties to manage, but they typically create more value. A legal regime in which only general-purpose, easily redeployable technologies were permitted would alleviate the holdup problem, but at the cost of a huge loss in efficiency. Likewise, a world in which all digital records must be fully portable reduces switching costs, but results in technologies for creating, storing, and sharing information that are less valuable. Why would platform operators invest in efficiency improvements if they cannot capture some of that value by means of proprietary formats, interfaces, sharing rules, and other arrangements?  

In short, we should not be quick to assume “market failure” in the market for privacy goods (or “true” news, whatever that is). Entrepreneurs operating in a competitive environment – not the static, partial-equilibrium notion of competition from intermediate micro texts but the rich, dynamic, complex, and multimarket kind of competition described in Petit’s book – can provide the levels of privacy and truthiness that consumers prefer.

[TOTM: The following is part of a symposium by TOTM guests and authors marking the release of Nicolas Petit’s “Big Tech and the Digital Economy: The Moligopoly Scenario.” The entire series of posts is available here.

This post is authored by Shane Greenstein (Professor of Business Administration, Harvard Business School).
]

In his book, Nicolas Petit approaches antitrust issues by analyzing their economic foundations, and he aspires to bridge gaps between those foundations and the common points of view. In light of the divisiveness of today’s debates, I appreciate Petit’s calm and deliberate view of antitrust, and I respect his clear and engaging prose.

I spent a lot of time with this topic when writing a book (How the Internet Became Commercial, 2015, Princeton Press). If I have something unique to add to a review of Petit’s book, it comes from the role Microsoft played in the events in my book.

Many commentators have speculated on what precise charges could be brought against Facebook, Google/Alphabet, Apple, and Amazon. For the sake of simplicity, let’s call these the “big four.” While I have no special insight to bring to such speculation, for this post I can do something different, and look forward by looking back. For the time being, Microsoft has been spared scrutiny by contemporary political actors. (It seems safe to presume Microsoft’s managers prefer to be left out.) While it is tempting to focus on why this has happened, let’s focus on a related issue: What shadow did Microsoft’s trials cast on the antitrust issues facing the big four?

Two types of lessons emerged from Microsoft’s trials, and both tend to be less appreciated by economists. One set of lessons emerged from the media flood of the flotsam and jetsam of sensationalistic factoids and sound bites, drawn from Congressional and courtroom testimony. That yielded lessons about managing sound and fury – i.e., mostly about reducing the cringe-worthy quotes from CEOs and trial witnesses.

Another set of lessons pertained to the role and limits of economic reasoning. Many decision makers reasoned by analogy and metaphor. That is especially so for lawyers and executives. These metaphors do not make economic reasoning wrong, but they do tend to shape how an antitrust question takes center stage with a judge, as well as in the court of public opinion. These metaphors also influence the stories a CEO tells to employees.

If you asked me to forecast how things will go for the big four, based on what I learned from studying Microsoft’s trials, I forecast that the outcome depends on which metaphor and analogy gets the upper hand.

In that sense, I want to argue that Microsoft’s experience depended on “the fox and shepherd problem.” When is a platform leader better thought of as a shepherd, helping partners achieve a healthy outcome, or as a fox in charge of a henhouse, ready to sacrifice a partner for self-serving purposes? I forecast the same metaphors will shape experience of the big four.

Gaps and analysis

The fox-shepherd problem never shows up when a platform leader is young and its platform is small. As the platform reaches bigger scale, however, the problem becomes more salient. Conflicts of interests emerge and focus attention on platform leadership.

Petit frames these issues within a Schumpeterian vision. In this view, firms compete for dominant positions over time, potentially with one dominant firm replacing another. Potential competition has a salutary effect if established firms perceive a threat from the future shadow of such competitors, motivating innovation. In this view, antitrust’s role might be characterized as “keeping markets open so there is pressure on the dominant firm from potential competition.”

In the Microsoft trial economists framed the Schumpeterian tradeoff in the vocabulary of economics. Firms who supply complements at one point could become suppliers of substitutes at a later point if they are allowed to. In other words, platform leaders today support complements that enhance the value of the platform, while also having the motive and ability to discourage those same business partners from developing services that substitute for the platform’s services, which could reduce the platform’s value. Seen through this lens, platform leaders inherently face a conflict of interest, and antitrust law should intervene if platform leaders could place excessive limitations on existing business partners.

This economic framing is not wrong. Rather, it is necessary, but not sufficient. If I take a sober view of events in the Microsoft trial, I am not convinced the economics alone persuaded the judge in Microsoft’s case, or, for that matter, the public.

As judges sort through the endless detail of contracting provisions, they need a broad perspective, one that sharpens their focus on a key question. One central question in particular inhabits a lot of a judge’s mindshare: how did the platform leader use its discretion, and for what purposes? In case it is not obvious, shepherds deserve a lot of discretion, while only a fool gives a fox much license.

Before the trial, when it initially faced this question from reporters and Congress, Microsoft tried to dismiss the discussion altogether. Their representatives argued that high technology differs from every other market in its speed and productivity, and, therefore, ought to be thought of as incomparable to other antitrust examples. This reflected the high tech elite’s view of their own exceptionalism.

Reporters dutifully restated this argument, and, long story short, it did not get far with the public once the sensationalism started making headlines, and it especially did not get far with the trial judge. To be fair, if you watched recent congressional testimony, it appears as if the lawyers for the big four instructed their CEOs not to try it this approach this time around.

Origins

Well before lawyers and advocates exaggerate claims, the perspective of both sides usually have some merit, and usually the twain do not meet. Most executives tend to remember every detail behind growth, and know the risks confronted and overcome, and usually are reluctant to give up something that works for their interests, and sometimes these interests can be narrowly defined. In contrast, many partners will know examples of a rule that hindered them, and point to complaints that executives ignored, and aspire to have rules changed, and, again, their interests tend to be narrow.

Consider the quality-control process today for iPhone apps as an example. The merits and absurdity of some of Apples conduct get a lot of attention in online forums, especially the 30% take for Apple. Apple can reasonably claim the present set of rules work well overall, and only emerged after considerable experimentation, and today they seek to protect all who benefit from the entire system, like a shepherd. It is no surprise however, that some partners accuse Apple of tweaking rules to their own benefit, and using the process to further Apple’s ambitions at the expense of the partner’s, like a fox in a henhouse. So it goes.

More generally, based on publically available information, all of the big four already face this debate. Self-serving behavior shows up in different guise in different parts of the big four’s business, but it is always there. As noted, Apple’s apps compete with the apps of others, so it has incentives to shape distribution of other apps. Amazon’s products compete with some products coming from its third—party sellers, and it too faces mixed incentives. Google’s services compete with online services who also advertise on their search engine, and they too face issues over their charges for listing on the Play store. Facebook faces an additional issues, because it has bought firms that were trying to grow their own platforms to compete with Facebook.

Look, those four each contain rather different businesses in their details, which merits some caution in making a sweeping characterization. My only point: the question about self-serving behavior arises in each instance. That frames a fox-shepherd problem for prosecutors in each case.

Lessons from prior experience

Circling back to lessons of the past for antitrust today, the Shepherd-Fox problem was one of the deeper sources of miscommunication leading up to the Microsoft trial. In the late 1990s Microsoft could reasonably claim to be a shepherd for all its platform’s partners, and it could reasonably claim to have improved the platform in ways that benefited partners. Moreover, for years some of the industry gossip about their behavior stressed misinformed nonsense. Accordingly, Microsoft’s executives had learned to trust their own judgment and to mistrust the complaints of outsiders. Right in line with that mistrust, many employees and executives took umbrage to being characterized as a fox in a henhouse, dismissing the accusations out of hand.

Those habits-of-mind poorly positioned the firm for a court case. As any observer of the trial knowns, When prosecutors came looking, they found lots of examples that looked like fox-like behavior. Onerous contract restrictions and cumbersome processes for business partners produced plenty of bad optics in court, and fueled the prosecution’s case that the platform had become too self-serving at the expense of competitive processes. Prosecutors had plenty to work with when it came time to prove motive, intent, and ability to misuse discretion. 

What is the lesson for the big four? Ask an executive in technology today, and sometimes you will hear the following: As long as a platform’s actions can be construed as friendly to customers, the platform leader will be off the hook. That is not wrong lessons, but it is an incomplete one. Looking with hindsight and foresight, that perspective seems too sanguine about the prospects for the big four. Microsoft had done plenty for its customers, but so what? There was plenty of evidence of acting like a fox in a hen-house. The bigger lesson is this: all it took were a few bad examples to paint a picture of a pattern, and every firm has such examples.

Do not get me wrong. I am not saying a fox and hen-house analogy is fair or unfair to platform leaders. Rather, I am saying that economists like to think the economic trade-off between the interests of platform leaders, platform partners, and platform customers emerge from some grand policy compromise. That is not how prosecutors think, nor how judges decide. In the Microsoft case there was no such grand consideration. The economic framing of the case only went so far. As it was, the decision was vulnerable to metaphor, shrewdly applied and convincingly argued. Done persuasively, with enough examples of selfish behavior, excuses about “helping customers” came across as empty.

Policy

Some advocates argue, somewhat philosophically, that platforms deserve discretion, and governments are bound to err once they intervene. I have sympathy with that point of view, but only up to a point. Below are two examples from outside antitrust where government routinely do not give the big four a blank check.

First, when it started selling ads, Google banned ads for cigarettes, porn and alcohol, and it downgraded in its quality score for websites that used deceptive means to attract users. That helped the service foster trust with new users, enabling it to grow. After it became bigger should Google have continued to have unqualified discretion to shepherd the entire ad system? Nobody thinks so. A while ago the Federal Trade Commission decided to investigate deceptive online advertising, just as it investigates deceptive advertising in other media. It is not a big philosophical step to next ask whether Google should have unfettered discretion to structure the ad business, search process, and related e-commerce to its own benefit.

Here is another example, this one about Facebook. Over the years Facebook cycled through a number of rules for sharing information with business partners, generally taking a “relaxed” attitude enforcing those policies. Few observers cared when Facebook was small, but many governments started to care after Facebook grew to billions of users. Facebook’s lax monitoring did not line up with the preferences of many governments. It should not come as a surprise now that many governments want to regulate Facebook’s handling of data. Like it or not, this question lies squarely within the domain of government privacy policy. Again, the next step is small. Why should other parts of its business remain solely in Facebook’s discretion, like its ability to buy other businesses?

This gets us to the other legacy of the Microsoft case: As we think about future policy dilemmas, are there a general set of criteria for the antitrust issues facing all four firms? Veterans of court cases will point out that every court case is its own circus. Just because Microsoft failed to be persuasive in its day does not imply any of the big four will be unpersuasive.

Looking back on the Microsoft trial, it did not articulate a general set of principles about acceptable or excusable self-serving behavior from a platform leader. It did not settle what criteria best determine when a court should consider a platform leader’s behavior closer to that of a shepherd or a fox. The appropriate general criteria remains unclear.

[TOTM: The following is part of a symposium by TOTM guests and authors marking the release of Nicolas Petit’s “Big Tech and the Digital Economy: The Moligopoly Scenario.” The entire series of posts is available here.

This post is authored by Richard N. Langlois
(Professor of Economics, University of Connecticut).]

Market share has long been the talisman of antitrust economics.  Once we properly define what “the product” is, all we have to do is look at shares in the relevant market.  In such an exercise, today’s high-tech firms come off badly.  Each of them has a large share of the market for some “product.” What I appreciate about Nicolas Petit’s notion of “moligopoly” is that it recognizes that genuine competition is a far more complex and interesting phenomenon, one that goes beyond the category of “the product.”

In his chapter 4, Petit lays out how this works with six of today’s large high-tech companies, adding Netflix to the usual Big Five of Amazon, Apple, Facebook, Google, and Microsoft.  If I understand properly, what he means by “moligopoly” is that these large firms have their hands in many different relevant markets.  Because they seem to be selling different “products,” they don’t seem to be competing with one another.  Yet, in a fundamental sense, they are very much competing with one another, and perhaps with firms that do not yet exist.  

In this view, diversification is at the heart of competition.  Indeed, Petit wonders at one point whether we are in a new era of “conglomeralism.”  I would argue that the diversified high-tech firms we see today are actually very unlike the conglomerates of the late twentieth century.  In my view, the earlier conglomerates were not equilibrium phenomena but rather short-lived vehicles for the radical restructuring of the American economy in the post- Bretton Woods era of globalization.  A defining characteristic of those firms was that their diversification was unrelated, not just in terms of the SIC codes of their products but also in terms of their underlying capabilities.  If we look only at the products on the demand side, today’s high-tech firms might also seem to reflect unrelated diversification.  In fact, however, unlike in the twentieth-century conglomerates, the activities of present-day high-tech firms are connected on the supply side by a common set of capabilities involving the deployment of digital technology. 

Thus the boundaries of markets can shift and morph unexpectedly.  Enterprises that may seem entirely different actually harbor the potential to invade one other’s territory (or invade new territory – “competing against non-consumption”).  What Amazon can do, Google can do; and so can Microsoft.  The arena is competitive not because firms have a small share of relevant markets but because all of them sit beneath four or five damocletian swords, suspended by the thinnest of horsehairs.  No wonder the executives of high-tech firms sound paranoid.

Petit speculates that today’s high-tech companies have diversified (among other reasons) because of complementarities.  That may be part of the story.  But as Carliss Baldwin argues (and as Petit mentions in passing), we can think about the investments high-tech firms seem to be making as options – experiments that may or may not pay off.  The more uncertain the environment, the more valuable it is to have many diverse options.  A decade or so after the breakup of AT&T, the “baby Bells” were buying into landline, cellular, cable, satellite, and many other things, not because, as many thought at the time, that these were complementary, but because no one had any idea what would be important in the future (including whether there would be any complementarities).  As uncertainty resolved, these lines of business became more specialized, and the babies unbundled.  (As I write, AT&T, the baby Bell that snagged the original company name, is probably about to sell off DirectTV at a loss.)  From this perspective, the high degree of diversification we observe today implies not control of markets but the opposite – existential uncertainty about the future.

I wonder whether this kind of competition is unique to the age of the Internet.  There is an entire genre of business-school case built around an epiphany of the form: “we thought we were in the X business, but we were really in the Y business all along!”  I have recently read (listened to, technically) Marc Levinson’s wonderful history of containerized shipping.  Here the real competition occurred across modes of transport, not within existing well-defined markets.  The innovators came to realize that they were in the logistics business, not in the trucking business or the railroad business or the ocean-shipping business.  (Some of the most interesting parts of the story were about how entrepreneurship happens in a heavily regulated environment.  At one point early in the story, Malcolm McLean, the most important of these entrepreneurs, had to buy up other trucking firms just to obtain the ICC permits necessary to redesign routes efficiently.)  Of course, containerized shipping is also a modular system that some economists have accused of being a general-purpose technology like the Internet.

[TOTM: The following is part of a symposium by TOTM guests and authors marking the release of Nicolas Petit’s “Big Tech and the Digital Economy: The Moligopoly Scenario.” The entire series of posts is available here.

This post is authored by Doug Melamed (Professor of the Practice of Law, Stanford law School).
]

The big digital platforms make people uneasy.  Part of the unease is no doubt attributable to widespread populist concerns about large and powerful business entities.  Platforms like Facebook and Google in particular cause unease because they affect sensitive issues of communications, community, and politics.  But the platforms also make people uneasy because they seem boundless – enduring monopolies protected by ever-increasing scale and network economies, and growing monopolies aided by scope economies that enable them to conquer complementary markets.  They provoke a discussion about whether antitrust law is sufficient for the challenge.

Nicolas Petit’s Big Tech and the Digital Economy: The Moligopoly Scenario provides an insightful and valuable antidote to this unease.  While neither Panglossian nor comprehensive, Petit’s analysis persuasively argues that some of the concerns about the platforms are misguided or at least overstated.  As Petit sees it, the platforms are not so much monopolies in discrete markets – search, social networking, online commerce, and so on – as “multibusiness firms with business units in partly overlapping markets” that are engaged in a “dynamic oligopoly game” that might be “the socially optimal industry structure.”  Petit suggests that we should “abandon or at least radically alter traditional antitrust principles,” which are aimed at preserving “rivalry,” and “adapt to the specific non-rival economics of digital markets.”  In other words, the law should not try to diminish the platforms’ unique dominance in their individual sectors, which have already tipped to a winner-take-all (or most) state and in which protecting rivalry is not “socially beneficial.”  Instead, the law should encourage reductions of output in tipped markets in which the dominant firm “extracts a monopoly rent” in order to encourage rivalry in untipped markets. 

Petit’s analysis rests on the distinction between “tipped markets,” in which “tech firms with observed monopoly positions can take full advantage of their market power,” and “untipped markets,” which are “characterized by entry, instability and uncertainty.”  Notably, however, he does not expect “dispositive findings” as to whether a market is tipped or untipped.  The idea is to define markets, not just by “structural” factors like rival goods and services, market shares and entry barriers, but also by considering “uncertainty” and “pressure for change.”

Not surprisingly, given Petit’s training and work as a European scholar, his discussion of “antitrust in moligopoly markets” includes prescriptions that seem to one schooled in U.S. antitrust law to be a form of regulation that goes beyond proscribing unlawful conduct.  Petit’s principal concern is with reducing monopoly rents available to digital platforms.  He rejects direct reduction of rents by price regulation as antithetical to antitrust’s DNA and proposes instead indirect reduction of rents by permitting users on the inelastic side of a platform (the side from which the platform gains most of its revenues) to collaborate in order to gain countervailing market power and by restricting the platforms’ use of vertical restraints to limit user bypass. 

He would create a presumption against all horizontal mergers by dominant platforms in order to “prevent marginal increases of the output share on which the firms take a monopoly rent” and would avoid the risk of defining markets narrowly and thus failing to recognize that platforms are conglomerates that provide actual or potential competition in multiple partially overlapping commercial segments. By contrast, Petit would restrict the platforms’ entry into untipped markets only in “exceptional circumstances.”  For this, Petit suggests four inquiries: whether leveraging of network effects is involved; whether platform entry deters or forecloses entry by others; whether entry by others pressures the monopoly rents; and whether entry into the untipped market is intended to deter entry by others or is a long-term commitment.

One might question the proposition, which is central to much of Petit’s argument, that reducing monopoly rents in tipped markets will increase the platforms’ incentives to enter untipped markets.  Entry into untipped markets is likely to depend more on expected returns in the untipped market, the cost of capital, and constraints on managerial bandwidth than on expected returns in the tipped market.  But the more important issue, at least from the perspective of competition law, is whether – even assuming the correctness of all aspects of Petit’s economic analysis — the kind of categorical regulatory intervention proposed by Petit is superior to a law enforcement regime that proscribes only anticompetitive conduct that increases or threatens to increase market power.  Under U.S. law, anticompetitive conduct is conduct that tends to diminish the competitive efficacy of rivals and does not sufficiently enhance economic welfare by reducing costs, increasing product quality, or reducing above-cost prices.

If there were no concerns about the ability of legal institutions to know and understand the facts, a law enforcement regime would seem clearly superior.  Consider, for example, Petit’s recommendation that entry by a platform monopoly into untipped markets should be restricted only when network effects are involved and after taking into account whether the entry tends to protect the tipped market monopoly and whether it reflects a long-term commitment.  Petit’s proposed inquiries might make good sense as a way of understanding as a general matter whether market extension by a dominant platform is likely to be problematic.  But it is hard to see how economic welfare is promoted by permitting a platform to enter an adjacent market (e.g., Amazon entering a complementary product market) by predatory pricing or by otherwise unprofitable self-preferencing, even if the entry is intended to be permanent and does not protect the platform monopoly. 

Similarly, consider the proposed presumption against horizontal mergers.  That might not be a good idea if there is a small (10%) chance that the acquired firm would otherwise endure and modestly reduce the platform’s monopoly rents and an equal or even smaller chance that the acquisition will enable the platform, by taking advantage of economies of scope and asset complementarities, to build from the acquired firm an improved business that is much more valuable to consumers.  In that case, the expected value of the merger in welfare terms might be very positive.  Similarly, Petit would permit acquisitions by a platform of firms outside the tipped market as long as the platform has the ability and incentive to grow the target.  But the growth path of the target is not set in stone.  The platform might use it as a constrained complement, while an unaffiliated owner might build it into something both more valuable to consumers and threatening to the platform.  Maybe one of these stories describes Facebook’s acquisition of Instagram.

The prototypical anticompetitive horizontal merger story is one in which actual or potential competitors agree to share the monopoly rents that would be dissipated by competition between them. That story is confounded by communications that seem like threats, which imply a story of exclusion rather than collusion.  Petit refers to one such story.  But the threat story can be misleading.  Suppose, for example, that Platform sees Startup introduce a new business concept and studies whether it could profitably emulate Startup.  Suppose further that Platform concludes that, because of scale and scope economies available to it, it could develop such a business and come to dominate the market for a cost of $100 million acting alone or $25 million if it can acquire Startup and take advantage of its existing expertise, intellectual property, and personnel.  In that case, Platform might explain to Startup the reality that Platform is going to take the new market either way and propose to buy Startup for $50 million (thus offering Startup two-thirds of the gains from trade).  Startup might refuse, perhaps out of vanity or greed, in which case Platform as promised might enter aggressively and, without engaging in predatory or other anticompetitive conduct, drive Startup from the market.  To an omniscient law enforcement regime, there should be no antitrust violation from either an acquisition or the aggressive competition.  Either way, the more efficient provider prevails so the optimum outcome is realized in the new market.  The merger would have been more efficient because it would have avoided wasteful duplication of startup costs, and the merger proposal (later characterized as a threat) was thus a benign, even procompetitive, invitation to collude.  It would be a different story of course if Platform could overcome Startup’s first mover advantage only by engaging in anticompetitive conduct.

The problem is that antitrust decision makers often cannot understand all the facts.  Take the threat story, for example.  If Startup acquiesces and accepts the $50 million offer, the decision maker will have to determine whether Platform could have driven Startup from the market without engaging in predatory or anticompetitive conduct and, if not, whether absent the merger the parties would have competed against one another.  In other situations, decision makers are asked to determine whether the conduct at issue would be more likely than the but-for world to promote innovation or other, similarly elusive matters.

U.S. antitrust law accommodates its unavoidable uncertainty by various default rules and practices.  Some, like per se rules and the controversial Philadelphia National Bank presumption, might on occasion prohibit conduct that would actually have been benign or even procompetitive.  Most, however, insulate from antitrust liability conduct that might actually be anticompetitive.  These include rules applicable to predatory pricing, refusals to deal, two-sided markets, and various matters involving patents.  Perhaps more important are proof requirements in general.  U.S. antitrust law is based on the largely unexamined notion that false positives are worse than false negatives and thus, for the most part, puts the burden of uncertainty on the plaintiff.

Petit is proposing, in effect, an alternative approach for the digital platforms.  This approach would not just proscribe anticompetitive conduct.  It would, instead, apply to specific firms special rules that are intended to promote a desired outcome, the reduction in monopoly rents in tipped digital markets.  So, one question suggested by Petit’s provocative study is whether the inevitable uncertainty surrounding issues of platform competition are best addressed by the kinds of categorical rules Petit proposes or by case-by-case application of abstract legal principles.  Put differently, assuming that economic welfare is the objective, what is the best way to minimize error costs?

Broadly speaking, there are two kinds of error costs: specification errors and application errors.  Specification errors reflect legal rules that do not map perfectly to the normative objectives of the law (e.g., a rule that would prohibit all horizontal mergers by dominant platforms when some such mergers are procompetitive or welfare-enhancing).  Application errors reflect mistaken application of the legal rule to the facts of the case (e.g., an erroneous determination whether the conduct excludes rivals or provides efficiency benefits).   

Application errors are the most likely source of error costs in U.S. antitrust law.  The law relies largely on abstract principles that track the normative objectives of the law (e.g., conduct by a monopoly that excludes rivals and has no efficiency benefit is illegal). Several recent U.S. antitrust decisions (American Express, Qualcomm, and Farelogix among them) suggest that error costs in a law enforcement regime like that in the U.S. might be substantial and even that case-by-case application of principles that require applying economic understanding to diverse factual circumstances might be beyond the competence of generalist judges.  Default rules applicable in special circumstances reduce application errors but at the expense of specification errors.

Specification errors are more likely with categorical rules, like those suggested by Petit.  The total costs of those specification errors are likely to exceed the costs of mistaken decisions in individual cases because categorical rules guide firm conduct in general, not just in decided cases, and rules that embody specification errors are thus likely to encourage undesirable conduct and to discourage desirable conduct in matters that are not the subject of enforcement proceedings.  Application errors, unless systematic and predictable, are less likely to impose substantial costs beyond the costs of mistaken decisions in the decided cases themselves.  Whether any particular categorical rules are likely to have error costs greater than the error costs of the existing U.S. antitrust law will depend in large part on the specification errors of the rules and on whether their application is likely to be accompanied by substantial application costs.

As discussed above, the particular rules suggested by Petit appear to embody important specification errors.  They are likely also to lead to substantial application errors because they would require determination of difficult factual issues.  These include, for example, whether the market at issue has tipped, whether the merger is horizontal, and whether the platform’s entry into an untipped market is intended to be permanent.  It thus seems unlikely, at least from this casual review, that adoption of the rules suggested by Petit will reduce error costs.

 Petit’s impressive study might therefore be most valuable, not as a roadmap for action, but as a source of insight and understanding of the facts – what Petit calls a “mental model to help decision makers understand the idiosyncrasies of digital markets.”  If viewed, not as a prescription for action, but as a description of the digital world, the Moligopoly Scenario can help address the urgent matter of reducing the costs of application errors in U.S. antitrust law.

The writing is on the wall for Big Tech: regulation is coming. At least, that is what the House Judiciary Committee’s report into competition in digital markets would like us to believe. 

The Subcommittee’s Majority members, led by Rhode Island’s Rep. David Cicilline, are calling for a complete overhaul of America’s antitrust and regulatory apparatus. This would notably entail a break up of America’s largest tech firms, by prohibiting them from operating digital platforms and competing on them at the same time. Unfortunately, the report ignores the tremendous costs that such proposals would impose upon consumers and companies alike. 

For several years now, there has been growing pushback against the perceived “unfairness” of America’s tech industry: of large tech platforms favoring their own products at the expense of entrepreneurs who use their platforms; of incumbents acquiring startups to quash competition; of platforms overcharging  companies like Epic Games, Spotify, and the media, just because they can; and of tech companies that spy on their users and use that data to sell them things they don’t need. 

But this portrayal of America’s tech industry obscures an inconvenient possibility: supposing that these perceived ills even occur, there is every chance that the House’s reforms would merely exacerbate the status quo. The House report gives short shrift to this eventuality, but it should not.

Over the last decade, the tech sector has been the crown jewel of America’s economy. And while firms like Amazon, Google, Facebook, and Apple, may have grown at a blistering pace, countless others have flourished in their wake.

Google and Apple’s app stores have given rise to a booming mobile software industry. Platforms like Youtube and Instagram have created new venues for advertisers and ushered in a new generation of entrepreneurs including influencers, podcasters, and marketing experts. Social media platforms like Facebook and Twitter have disintermediated the production of news media, allowing ever more people to share their ideas with the rest of the world (mostly for better, and sometimes for worse). Amazon has opened up new markets for thousands of retailers, some of which are now going public. The recent $3.4 billion Snowflake IPO may have been the biggest public offering of a tech firm no one has heard of.

The trillion dollar question is whether it is possible to regulate this thriving industry without stifling its unparalleled dynamism. If Rep. Cicilline’s House report is anything to go by, the answer is a resounding no.

Acquisition by a Big Tech firm is one way for startups to rapidly scale and reach a wider audience, while allowing early investors to make a quick exit. Self-preferencing can enable platforms to tailor their services to the needs and desires of users (Apple and Google’s pre-installed app suites are arguably what drive users to opt for their devices). Excluding bad apples from a platform is essential to gain users’ trust and build a strong reputation. Finally, in the online retail space, copying rival products via house brands provides consumers with competitively priced goods and helps new distributors enter the market. 

All of these practices would either be heavily scrutinized or outright banned under the Subcommittee ’s proposed reforms. Beyond its direct impact on the quality of online goods and services, this huge shift would threaten the climate of permissionless innovation that has arguably been key to Silicon Valley’s success. 

More fundamentally, these reforms would mostly protect certain privileged rivals at the expense of the wider industry. Take Apple’s App Store: Epic Games and others have complained about the 30% Commission charged by Apple for in-app purchases (as is standard throughout the industry). Yet, as things stand, roughly 80% of apps pay no commission at all. Tackling this 30% commission — for instance by allowing developers to bypass Apple’s in-app payment processing — would almost certainly result in larger fees for small developers. In short, regulation could significantly impede smaller firms.

Fortunately, there is another way. For decades, antitrust law — guided by the judge-made consumer welfare standard — has been the cornerstone of economic policy in the US. During that time, America built a tech industry that is the envy of the world. This should give pause to would-be reformers. There is a real chance overbearing regulation will permanently hamper America’s tech industry. With competition from China more intense than ever, it is a risk that the US cannot afford to take.

Earlier this year the UK government announced it was adopting the main recommendations of the Furman Report into competition in digital markets and setting up a “Digital Markets Taskforce” to oversee those recommendations being put into practice. The Competition and Markets Authority’s digital advertising market study largely came to similar conclusions (indeed, in places it reads as if the CMA worked backwards from those conclusions).

The Furman Report recommended that the UK should overhaul its competition regime with some quite significant changes to regulate the conduct of large digital platforms and make it harder for them to acquire other companies. But, while the Report’s panel is accomplished and its tone is sober and even-handed, the evidence on which it is based does not justify the recommendations it makes.

Most of the citations in the Report are of news reports or simple reporting of data with no analysis, and there is very little discussion of the relevant academic literature in each area, even to give a summary of it. In some cases, evidence and logic are misused to justify intuitions that are just not supported by the facts.

Killer acquisitions

One particularly bad example is the report’s discussion of mergers in digital markets. The Report provides a single citation to support its proposals on the question of so-called “killer acquisitions” — acquisitions where incumbent firms acquire innovative startups to kill their rival product and avoid competing on the merits. The concern is that these mergers slip under the radar of current merger control either because the transaction is too small, or because the purchased firm is not yet in competition with the incumbent. But the paper the Report cites, by Colleen Cunningham, Florian Ederer and Song Ma, looks only at the pharmaceutical industry. 

The Furman Report says that “in the absence of any detailed analysis of the digital sector, these results can be roughly informative”. But there are several important differences between the drug markets the paper considers and the digital markets the Furman Report is focused on. 

The scenario described in the Cunningham, et al. paper is of a patent holder buying a direct competitor that has come up with a drug that emulates the patent holder’s drug without infringing on the patent. As the Cunningham, et al. paper demonstrates, decreases in development rates are a feature of acquisitions where the acquiring company holds a patent for a similar product that is far from expiry. The closer a patent is to expiry, the less likely an associated “killer” acquisition is. 

But tech typically doesn’t have the clear and predictable IP protections that would make such strategies reliable. The long and uncertain development and approval process involved in bringing a drug to market may also be a factor.

There are many more differences between tech acquisitions and the “killer acquisitions” in pharma that the Cunningham, et al. paper describes. SO-called “acqui-hires,” where a company is acquired in order to hire its workforce en masse, are common in tech and explicitly ruled out of being “killers” by this paper, for example: it is not harmful to overall innovation or output overall if a team is moved to a more productive project after an acquisition. And network effects, although sometimes troubling from a competition perspective, can also make mergers of platforms beneficial for users by growing the size of that platform (because, of course, one of the points of a network is its size).

The Cunningham, et al. paper estimates that 5.3% of pharma acquisitions are “killers”. While that may seem low, some might say it’s still 5.3% too much. However, it’s not obvious that a merger review authority could bring that number closer to zero without also rejecting more mergers that are good for consumers, making people worse off overall. Given the number of factors that are specific to pharma and that do not apply to tech, it is dubious whether the findings of this paper are useful to the Furman Report’s subject at all. Given how few acquisitions are found to be “killers” in pharma with all of these conditions present, it seems reasonable to assume that, even if this phenomenon does apply in some tech mergers, it is significantly rarer than the ~5.3% of mergers Cunningham, et al. find in pharma. As a result, the likelihood of erroneous condemnation of procompetitive mergers is significantly higher. 

In any case, there’s a fundamental disconnect between the “killer acquisitions” in the Cunningham, et al. paper and the tech acquisitions described as “killers” in the popular media. Neither Facebook’s acquisition of Instagram nor Google’s acquisition of Youtube, which FTC Commissioner Rohit Chopra recently highlighted, would count, because in neither case was the acquired company “killed.” Nor were any of the other commonly derided tech acquisitions — e.g., Facebook/Whatsapp, Google/Waze, Microsoft.LinkedIn, or Amazon/Whole Foods — “killers,” either. 

In all these high-profile cases the acquiring companies expanded the service and invested more in them. One may object that these services would have competed with their acquirers had they remained independent, but this is a totally different argument to the scenarios described in the Cunningham, et al. paper, where development of a new drug is shut down by the acquirer ostensibly to protect their existing product. It is thus extremely difficult to see how the Cunningham, et al. paper is even relevant to the digital platform context, let alone how it could justify a wholesale revision of the merger regime as applied to digital platforms.

A recent paper (published after the Furman Report) does attempt to survey acquisitions by Google, Amazon, Facebook, Microsoft, and Apple. Out of 175 acquisitions in the 2015-17 period the paper surveys, only one satisfies the Cunningham, et al. paper’s criteria for being a potentially “killer” acquisition — Facebook’s acquisition of a photo sharing app called Masquerade, which had raised just $1 million in funding before being acquired.

In lieu of any actual analysis of mergers in digital markets, the Report falls back on a puzzling logic:

To date, there have been no false positives in mergers involving the major digital platforms, for the simple reason that all of them have been permitted. Meanwhile, it is likely that some false negatives will have occurred during this time. This suggests that there has been underenforcement of digital mergers, both in the UK and globally. Remedying this underenforcement is not just a matter of greater focus by the enforcer, as it will also need to be assisted by legislative change.

This is very poor reasoning. It does not logically follow that the (presumed) existence of false negatives implies that there has been underenforcement, because overenforcement carries costs as well. Moreover, there are strong reasons to think that false positives in these markets are more costly than false negatives. A well-run court system might still fail to convict a few criminals because the cost of accidentally convicting an innocent person was so high.

The UK’s competition authority did commission an ex post review of six historical mergers in digital markets, including Facebook/Instagram and Google/Waze, two of the most controversial in the UK. Although it did suggest that the review process could have been done differently, it also highlighted efficiencies that arose from each, and did not conclude that any has led to consumer detriment.

Recommendations

The Report is vague about which mergers it considers to have been uncompetitive, and apart from the aforementioned text it does not really attempt to justify its recommendations around merger control. 

Despite this, the Report recommends a shift to a ‘balance of harms’ approach. Under the current regime, merger review focuses on the likelihood that a merger would reduce competition which, at least, gives clarity about the factors to be considered. A ‘balance of harms’ approach would require the potential scale (size) of the merged company to be considered as well. 

This could give basis for blocking any merger at all on ‘scale’ grounds. After all, if a photo editing app with a sharing timeline can grow into the world’s second largest social network, how could a competition authority say with any confidence that some other acquisition might not prevent the emergence of a new platform on a similar scale, however unlikely? This could provide a basis for blocking almost any acquisition by an incumbent firm, and make merger review an even more opaque and uncertain process than it currently is, potentially deterring efficiency-raising mergers or leading startups that would like to be acquired to set up and operate overseas instead (or not to be started up in the first place).

The treatment of mergers is just one example of the shallowness of the Report. In many other cases — the discussions of concentration and barriers to entry in digital markets, for example — big changes are recommended on the basis of a handful of papers or less. Intuition repeatedly trumps evidence and academic research.

The Report’s subject is incredibly broad, of course, and one might argue that such a limited, casual approach is inevitable. In this sense the Report may function perfectly well as an opening brief introducing the potential range of problems in the digital economy that a rational competition authority might consider addressing. But the complexity and uncertainty of the issues is no reason to eschew rigorous, detailed analysis before determining that a compelling case has been made. Adopting the Report’s assumptions — and in many cases that is the very most one can say of them — of harm and remedial recommendations on the limited bases it offers is sure to lead to erroneous enforcement of competition law in a way that would reduce, rather than enhance, consumer welfare.

The Wall Street Journal reports that Amazon employees have been using data from individual sellers to identify products to compete with with its own ‘private label’ (or own-brand) products, such as AmazonBasics, Presto!, and Pinzon.

It’s implausible that this is an antitrust problem, as some have suggested. It’s extremely common for retailers to sell their own private label products and use data on how other products in their stores have sold to help development and marketing. They account for about 14–17% of overall US retail sales, and for an estimated 19% of Walmart’s and Kroger’s sales and 29% of Costco’s sales of consumer packaged goods. 

And Amazon accounts for 39% of US e-commerce spending, and about 6% of all US retail spending. Any antitrust-based argument against Amazon doing this should also apply to Walmart, Kroger and Costco as well. In other words, the case against Amazon proves too much. Alec Stapp has a good discussion of these and related facts here.

However, it is interesting to think about the underlying incentives facing Amazon here, and in particular why Amazon’s company policy is not to use individual seller data to develop products (rogue employees violating this policy, notwithstanding). One possibility is that it is a way for Amazon to balance its competition with some third parties with protections for others that it sees as valuable to its platform overall.

Amazon does use aggregated seller data to develop and market its products. If two or more merchants are selling a product, Amazon’s employees can see how popular it is. This might seem like a trivial distinction, but it might exist for good reason. It could be because sellers of unique products actually do have the bargaining power to demand that Amazon does not use their data to compete with them, or for public relations reasons, although it’s not clear how successful that has been. 

But another possibility is that it may be a self-imposed restraint. Amazon sells its own private label products partially because doing so is profitable (even when undercutting rivals), partially to fill holes in product lines (like clothing, where 11% of listings were Amazon private label as of November 2018), and partially because it increases users’ likelihood to use Amazon if they expect to find a reliable product from a brand they trust. According to the Journal, they account for less than 1% of Amazon’s product sales, in contrast to the 19% of revenues ($54 billion) Amazon makes from third party seller services, which includes Marketplace commissions. Any analysis that ignores that Amazon has to balance those sources of revenue, and so has to tread carefully, is deficient. 

With “commodity” products (like, say, batteries and USB cables), where multiple sellers are offering very similar or identical versions of the same thing, private label competition works well for both Amazon and consumers. By Amazon’s own rules it can enter this market using aggregated data, but this doesn’t give it a significant advantage, since that data is easily obtainable from multiple sources, including Amazon itself, which makes detailed aggregated sales data freely available to third-party retailers

But to the extent that Amazon competes against innovative third-party sellers (typically manufacturers doing direct sales, as opposed to pure retailers simply re-selling others’ products), there is a possibility that the prospect of having to compete with Amazon may diminish their incentive to develop new products and sell them on Amazon’s platform. 

This is the strongest argument that is made against private label offerings in general. When they involve some level of copying an innovative product, where the innovator has been collecting above-normal profits and those profits are what spur the innovation in the first place, a private label product that comes along and copies the product effectively free rides on the innovation and captures some of its return. That may get us less innovation than society—or a platform trying to host as many innovative products as possible—would like.

While the Journal conflates these two kinds of products, Amazon’s own policies may be tailored specifically to take account of the distinction, and maximise the total value of its marketplace to consumers.

This is nominally the focus of the Journal story: a car trunk organiser company with an (apparently) innovative product says that Amazon moving in to compete with its own AmazonBasics version competed away many of its sales. In this sort of situation, the free-rider problem described above might apply where future innovation is discouraged. Why bother to invent things like this if you’re just going to have your invention ripped off?

Of course, many such innovations are protected by patents. But there may be valuable innovations that are not, and even patented innovations are not perfectly protected given the costs of enforcement. But a platform like Amazon can adopt rules that fine-tune the protections offered by the legal system in an effort to increase the value of the platform for both innovators and consumers alike.

And that may be why Amazon has its rule against using individual seller data to compete: to allow creators of new products to collect more rents from their inventions, with a promise that, unless and until their product is commodified by other means (as indicated by the product being available from multiple other sellers), Amazon won’t compete against such sellers using any special insights it might have from that seller using Amazon’s Marketplace. 

This doesn’t mean Amazon refuses to compete (or refuses to allow others to compete); it has other rules that sometimes determine that boundary, as when it enters into agreements with certain brands to permit sales of the brand on the platform only by sellers authorized by the brand owner. Rather, this rule is a more limited—but perhaps no less important—one that should entice innovators to use Amazon’s platform to sell their products without concern that doing so will create a special risk that Amazon can compete away their returns using information uniquely available to it. In effect, it’s a promise that innovators won’t lose more by choosing to sell on Amazon rather than through other retail channels.. 

Like other platforms, to maximise its profits Amazon needs to strike a balance between being an attractive place for third party merchants to sell their goods, and being attractive to consumers by offering as many inexpensive, innovative, and reliable products as possible. Striking that balance is challenging, but a rule that restrains the platform from using its unique position to expropriate value from innovative sellers helps to protect the income of genuinely innovative third parties, and induces them to sell products consumers want on Amazon, while still allowing Amazon (and third-party sellers) to compete with commodity products. 

The fact that Amazon has strong competition online and offline certainly acts as an important constraint here, too: if Amazon behaved too badly, third parties might not sell on it at all, and Amazon would have none of the seller data that is allegedly so valuable to it.

But even in a world where Amazon had a huge, sticky customer base that meant it was not an option to sell elsewhere—which the Journal article somewhat improbably implies—Amazon would still need third parties to innovate and sell things on its platform. 

What the Journal story really seems to demonstrate is the sort of genuine principal-agent problem that all large businesses face: the company as a whole needs to restrain its private label section in various respects but its agents in the private label section want to break those rules to maximise their personal performance (in this case, by launching a successful new AmazonBasics product). It’s like a rogue trader at a bank who breaks the rules to make herself look good by, she hopes, getting good results.This is just one of many rules that a platform like Amazon has to preserve the value of its platform. It’s probably not the most important one. But understanding why it exists may help us to understand why simple stories of platform predation don’t add up, and help to demonstrate the mechanisms that companies like Amazon use to maximise the total value of their platform, not just one part of it.

[TOTM: The following is part of a blog series by TOTM guests and authors on the law, economics, and policy of the ongoing COVID-19 pandemic. The entire series of posts is available here.

This post is authored by Ramaz Samrout, (Principal, REIM Strategies; Lay Member, Competition Tribunal of Canada)]

At a time when nations are engaged in bidding wars in the worldwide market to alleviate the shortages of critical medical necessities for the Covid-19 crisis, it certainly bares the question, have free trade and competition policies resulting in efficient global integrated market networks gone too far? Did economists and policy makers advocating for efficient competitive markets not foresee a failure of the supply chain in meeting a surge in demand during an inevitable global crisis such as this one?

The failures in securing medical supplies have escalated a global health crisis to geopolitical spats fuelled by strong nationalistic public sentiments. In the process of competing to acquire highly treasured medical equipment, governments are confiscating, outbidding, and diverting shipments at the risk of not adhering to the terms of established free trade agreements and international trading rules, all at the cost of the humanitarian needs of other nations.

Since the start of the Covid-19 crisis, all levels of government in Canada have been working on diversifying the supply chain for critical equipment both domestically and internationally. But, most importantly, these governments are bolstering domestic production and an integrated domestic supply network recognizing the increasing likelihood of tightening borders impacting the movement of critical products.

For the past 3 weeks in his daily briefings, Canada’s Prime Minister, Justin Trudeau, has repeatedly confirmed the Government’s support of domestic enterprises that are switching their manufacturing lines to produce critical medical supplies and of other “made in Canada” products.

As conditions worsen in the US and the White House hardens its position towards collaboration and sharing for the greater global humanitarian good—even in the presence of a recent bilateral agreement to keep the movement of essential goods fluid—Canada’s response has become more retaliatory. Now shifting to a message emphasizing that the need for “made in Canada” products is one of extreme urgency.

On April 3rd, President Trump ordered Minnesota-based 3M to stop exporting medical-grade masks to Canada and Latin America; a decision that was enabled by the triggering of the 1950 Defence Production Act. In response, Ontario Premier, Doug Ford, stated in his public address:

Never again in the history of Canada should we ever be beholden to companies around the world for the safety and wellbeing of the people of Canada. There is nothing we can’t build right here in Ontario. As we get these companies round up and we get through this, we can’t be going over to other sources because we’re going to save a nickel.

Premier Ford’s words ring true for many Canadians as they watch this crisis unfold and wonder where would it stop if the crisis worsens? Will our neighbour to the south block shipments of a Covid-19 vaccine when it is developed? Will it extend to other essential goods such as food or medicine? 

There are reports that the decline in the number of foreign workers in farming caused by travel restrictions and quarantine rules in both Canada and the US will cause food production shortages, which makes the actions of the White House very unsettling for Canadians.  Canada’s exports to the US constitute 75% of total Canadian exports, while imports from the US constitute 46%. Canada’s imports of food and beverages from the US were valued at US $24 billion in 2018 including: prepared foods, fresh vegetables, fresh fruits, other snack foods, and non-alcoholic beverages.

The length and depth of the crisis will determine to what extent the US and Canadian markets will experience shortages in products. For Canada, the severity of the pandemic in the US could result in further restrictions on the border. And it is becoming progressively more likely that it will also result in a significant reduction in the volume of necessities crossing the border between the two nations.

Increasingly, the depth and pain experienced from shortages in necessities will shape public sentiment towards free trade and strengthen mainstream demands of more nationalistic and protectionist policies. This will result in more pressure on political and government establishments to take action.

The reliance on free trade and competition policies favouring highly integrated supply chain networks is showing cracks in meeting national interests in this time of crisis. This goes well beyond the usual economic factors of contention between countries of domestic employment, job loss and resource allocation. The need for correction, however, risks moving the pendulum too far to the side of protectionism.

Free trade setbacks and global integration disruptions would become the new economic reality to ensure that domestic self-sufficiency comes first. A new trade trend has been set in motion and there is no going back from some level of disintegrating globalised supply chain productions.

How would domestic self-sufficiency be achieved? 

Would international conglomerates build local plants and forgo their profit maximizing strategies of producing in growing economies that offer cheap wages and resources in order to avoid increased protectionism?

Will the Canada-United States-Mexico Agreement (CUSMA) known as the NEW NAFTA, which until today has not been put into effect, be renegotiated to allow for production measures for securing domestic necessities in the form of higher tariffs, trade quotas, and state subsidies?

Are advanced capitalist economies willing to create State-Owned Industries to produce domestic products for what it deems necessities?

Many other trade policy variations and options focused on protectionism are possible which could lead to the creation of domestic monopolies. Furthermore, any return to protected national production networks will reduce consumer welfare and eventually impede technological advancements that result from competition. 

Divergence between free trade agreements and competition policy in a new era of protectionism.

For the past 30 years, national competition laws and policies have increasingly become an integrated part of free trade agreements, albeit in the form of soft competition law language, making references to the parties’ respective competition laws, and the need for transparency, procedural fairness in enforcement, and cooperation.

Similarly, free trade objectives and frameworks have become part of the design and implementation of competition legislation and, subsequently, case law. Both of which are intended to encourage competitive market systems and efficiency, an implied by-product of open markets.

In that regard, the competition legal framework in Canada, the Competition Act, seeks to maintain and strengthen competitive market forces by encouraging maximum efficiency in the use of economic resources. Provisions to determine the level of competitiveness in the market consider barriers to entry, among them, tariff and non-tariff barriers to international trade. These provisions further direct adjudicators to examine free trade agreements currently in force and their role in facilitating the current or future possibility of an international incumbent entering the market to preserve or increase competition. And it goes further to also assess the extent of an increase in the real value of exports, or substitution of domestic products for imported products.

It is evident in the design of free trade agreements and competition legislation that efficiency, competition in price, and diversification of products is to be achieved by access to imported goods and by encouraging the creation of global competitive suppliers.

Therefore, the re-emergence of protectionist nationalistic measures in international trade will result in a divergence between competition laws and free trade agreements. Such setbacks would leave competition enforcers, administrators, and adjudicators grappling with the conflict between the economic principles set out in competition law and the policy objectives that could be stipulated in future trade agreements. 

The challenge ahead facing governments and industries is how to correct for the cracks in the current globalized competitive supply networks that have been revealed during this crisis without falling into a trap of nationalism and protectionism.

This is the fourth, and last, in a series of TOTM blog posts discussing the Commission’s recently published Google Android decision (the first post can be found here, and the second here, and the third here). It draws on research from a soon-to-be published ICLE white paper.

The previous parts of this series have mostly focused on the Commission’s factual and legal conclusions. However, as this blog post points out, the case’s economic underpinnings also suffer from important weaknesses.

Two problems are particularly salient: First, the economic models cited by the Commission (discussed in an official paper, but not directly in the decision) poorly match the underlying facts. Second, the Commission’s conclusions on innovation harms are out of touch with the abundant economic literature regarding the potential link between market structure and innovation.

The wrong economic models

The Commission’s Chief Economist team outlined its economic reasoning in an article published shortly after the Android decision was published. The article reveals that the Commission relied upon three economic papers to support its conclusion that Google’s tying harmed consumer welfare.

Each of these three papers attempts to address the same basic problem. Ever since the rise of the Chicago-School, it is widely accepted that a monopolist cannot automatically raise its profits by entering an adjacent market (i.e. leveraging its monopoly position), for instance through tying. This has sometimes been called the single-monopoly-profit theory. In more recent years, various scholars have refined this Chicago-School intuition, and identified instances where the theory fails.

While the single monopoly profit theory has been criticized in academic circles, it is important to note that the three papers cited by the Commission accept its basic premise. They thus attempt to show why the theory fails in the context of the Google Android case. 

Unfortunately, the assumptions upon which they rely to reach this conclusion markedly differ from the case’s fact pattern. These papers thus offer little support to the Commission’s economic conclusions.

For a start, the authors of the first paper cited by the Commission concede that their own model does not apply to the Google case:

Actual antitrust cases are fact-intensive and our model does not perfectly fit with the current Google case in one important aspect.

The authors thus rely on important modifications, lifted from a paper by Frederico Etro and Cristina Caffara (the second paper cited by the Commission), to support their conclusion that Google’s tying was anticompetitive. 

The second paper cited by the Commission, however, is equally problematic

The authors’ underlying intuition is relatively straightforward: because Google bundles its suite of Google Apps (including Search) with the Play Store, a rival search engine would have to pay a premium in order to be pre-installed and placed on the home screen, because OEMs would have to entirely forgo Google’s suite of applications. The key assumption here is that OEMs cannot obtain the Google Play app and pre-install and place favorably a rival search app

But this is simply not true of Google’s contractual terms. The best evidence is that rivals search apps have indeed concluded deals with OEMs to pre-install their search apps, without these OEMs losing access to Google’s suite of proprietary apps. Google’s contractual terms simply do not force OEMs to choose between the Google Play app and the pre-installation of a rival search app. Etro and Caffara’s model thus falls flat.

More fundamentally, even if Google’s contractual terms did prevent OEMs from pre-loading rival apps, the paper’s conclusions would still be deeply flawed. The authors essentially assume that the only way for consumers to obtain a rival app is through pre-installation. But this is a severe misreading of the prevailing market conditions. 

Users remain free to independently download rival search apps. If Google did indeed purchase exclusive pre-installation, users would not have to choose between a “full Android” device and one with a rival search app but none of Google’s apps. Instead, they could download the rival app and place it alongside Google’s applications. 

A more efficient rival could even provide side payments, of some sort, to encourage consumers to download its app. Exclusive pre-installation thus generates a much smaller advantage than Etro and Caffara assume, and their model fails to reflect this.

Finally, the third paper by Alexandre de Cornière and Greg Taylor, suffers from the exact same problem. The authors clearly acknowledge that their findings only hold if OEMs (and consumers) are effectively prevented from (pre-)installing applications that compete with Google’s apps. In their own words:

Upstream firms offer contracts to the downstream firm, who chooses which component(s) to use and then sells to consumers. For our theory to apply, the following three conditions need to hold: (i) substitutability between the two versions of B leads the downstream firm to install at most one version.

The upshot is that all three of the economic models cited by the Commission cease to be relevant in the specific context of the Google Android decision. The Commission is thus left with little to no economic evidence to support its finding of anticompetitive effects.

Critics might argue that direct downloads by consumers are but a theoretical possibility. Yet nothing could be further from the truth. Take the web browser market: The Samsung Internet Browser has more than 1 Billion downloads on Google’s Play Store. The Opera, Opera Mini and Firefox browsers each have over a 100 million downloads. The Brave browser has more than 10 million downloads, but is growing rapidly.

In short the economic papers on which the Commission relies are based on a world that does not exist. They thus fail to support the Commission’s economic findings.

An incorrect view of innovation

In its decision, the Commission repeatedly claimed that Google’s behavior stifled innovation because it prevented rivals from entering the market. However, the Commission offered no evidence to support its assumption that reduced market entry on would lead to a decrease in innovation:

(858) For the reasons set out in this Section, the Commission concludes that the tying of the Play Store and the Google Search app helps Google to maintain and strengthen its dominant position in each national market for general search services, increases barriers to entry, deters innovation and tends to harm, directly or indirectly, consumers.

(859) First, Google’s conduct makes it harder for competing general search services to gain search queries and the respective revenues and data needed to improve their services.

(861) Second, Google’s conduct increases barriers to entry by shielding Google from competition from general search services that could challenge its dominant position in the national markets for general search services:

(862) Third, by making it harder for competing general search services to gain search queries including the respective revenues and data needed to improve their services, Google’s conduct reduces the incentives of competing general search services to invest in developing innovative features, such as innovation in algorithm and user experience design.

In a nutshell, the Commission’s findings rest on the assumption that barriers to entry and more concentrated market structures necessarily reduce innovation. But this assertion is not supported by the empirical economic literature on the topic.

For example, a 2006 paper published by Richard Gilbert surveys 24 empirical studies on the topic. These studies examine the link between market structure (or firm size) and innovation. Though earlier studies tended to identify a positive relationship between concentration, as well as firm size, and innovation, more recent empirical techniques found no significant relationship. Gilbert thus suggests that:

These econometric studies suggest that whatever relationship exists at a general economy-wide level between industry structure and R&D is masked by differences across industries in technological opportunities, demand, and the appropriability of inventions.

This intuition is confirmed by another high-profile empirical paper by Aghion, Bloom, Blundell, Griffith, and Howitt. The authors identify an inverted-U relationship between competition and innovation. Perhaps more importantly, they point out that this relationship is affected by a number of sector-specific factors.

Finally, reviewing fifty years of research on innovation and market structure, Wesley Cohen concludes that:

Even before one controls for industry effects, the variance in R&D intensity explained by market concentration is small. Moreover, whatever relationship that exists in cross sections becomes imperceptible with the inclusion of controls for industry characteristics, whether expressed as industry fixed effects or in the form of survey-based and other measures of industry characteristics such as technological opportunity, appropriability conditions, and demand. In parallel to a decades-long accumulation of mixed results, theorists have also spawned an almost equally voluminous and equivocal literature on the link between market structure and innovation.[16]

The Commission’s stance is further weakened by the fact that investments in the Android operating system are likely affected by a weak appropriability regime. In other words, because of its open source nature, it is hard for Google to earn a return on investments in the Android OS (anyone can copy, modify and offer their own version of the OS). 

Loosely tying Google’s proprietary applications to the OS is arguably one way to solve this appropriability problem. Unfortunately, the Commission brushed these considerations aside. It argued that Google could earn some revenue from the Google Play app, as well as other potential venues. However, the Commission did not question whether these sources of income were even comparable to the sums invested by Google in the Android OS. It is thus possible that the Commission’s decision will prevent Google from earning a positive return on some future investments in the Android OS, ultimately causing it to cut back its investments and slowing innovation.

The upshot is that the Commission was simply wrong to assume that barriers to entry and more concentrated market structures would necessarily reduce innovation. This is especially true, given that Google may struggle to earn a return on its investments, absent the contractual provisions challenged by the Commission.

Conclusion

In short, the Commission’s economic analysis was severely lacking. It relied on economic models that had little to say about the market it which Google and its rivals operated. Its decisions thus reveals the inherent risk of basing antitrust decisions upon overfitted economic models. 

As if that were not enough, the Android decision also misrepresents the economic literature concerning the link (or absence thereof) between market structure and innovation. As a result, there is no reason to believe that Google’s behavior reduced innovation.

The Department of Justice began its antitrust case against IBM on January 17, 1969. The DOJ sued under the Sherman Antitrust Act, claiming IBM tried to monopolize the market for “general-purpose digital computers.” The case lasted almost thirteen years, ending on January 8, 1982 when Assistant Attorney General William Baxter declared the case to be “without merit” and dropped the charges. 

The case lasted so long, and expanded in scope so much, that by the time the trial began, “more than half of the practices the government raised as antitrust violations were related to products that did not exist in 1969.” Baltimore law professor Robert Lande said it was “the largest legal case of any kind ever filed.” Yale law professor Robert Bork called it “the antitrust division’s Vietnam.”

As the case dragged on, IBM was faced with increasingly perverse incentives. As NYU law professor Richard Epstein pointed out (emphasis added), 

Oddly, enough IBM was able to strengthen its antitrust-related legal position by reducing its market share, which it achieved through raising prices. When the suit was discontinued that share had fallen dramatically since 1969 from about 50 percent of the market to 37 percent in 1982. Only after the government suit ended did IBM lower its prices in order to increase market share.

Source: Levy & Welzer

In an interview with Vox, Tim Wu claimed that without the IBM case, Apple wouldn’t exist and we might still be using mainframe computers (emphasis added):

Vox: You said that Apple wouldn’t exist without the IBM case.

Wu: Yeah, I did say that. The case against IBM took 13 years and we didn’t get a verdict but in that time, there was the “policeman at the elbow” effect. IBM was once an all-powerful company. It’s not clear that we would have had an independent software industry, or that it would have developed that quickly, the idea of software as a product, [without this case]. That was one of the immediate benefits of that excavation.

And then the other big one is that it gave a lot of room for the personal computer to get started, and the software that surrounds the personal computer — two companies came in, Apple and Microsoft. They were sort of born in the wake of the IBM lawsuit. You know they were smart guys, but people did need the pressure off their backs.

Nobody is going to start in the shadow of Facebook and get anywhere. Snap’s been the best, but how are they doing? They’ve been halted. I think it’s a lot harder to imagine this revolutionary stuff that happened in the ’80s. If IBM had been completely unwatched by regulators, by enforcement, doing whatever they wanted, I think IBM would have held on and maybe we’d still be using mainframes, or something — a very different situation.

Steven Sinofsky, a former Microsoft executive and current Andreessen Horowitz board partner, had a different take on the matter, attributing IBM’s (belated) success in PCs to its utter failure in minicomputers (emphasis added):

IBM chose to prevent third parties from interoperating with mainframes sometimes at crazy levels (punch card formats). And then chose to defend until the end their business model of leasing … The minicomputer was a direct threat not because of technology but because of those attributes. I’ve heard people say IBM went into PCs because the antitrust loss caused them to look for growth or something. Ha. PCs were spun up because IBM was losing Minis. But everything about the PC was almost a fluke organizationally and strategically. The story of IBM regulation is told as though PCs exist because of the case.

The more likely story is that IBM got swamped by the paradigm shift from mainframes to PCs. IBM was dominant in mainframe computers which were sold to the government and large enterprises. Microsoft, Intel, and other leaders in the PC market sold to small businesses and consumers, which required an entirely different business model than IBM was structured to implement.

ABB – Always Be Bundling (Or Unbundling)

“There’s only two ways I know of to make money: bundling and unbundling.” – Jim Barksdale

In 1969, IBM unbundled its software and services from hardware sales. As many industry observers note, this action precipitated the rise of the independent software development industry. But would this have happened regardless of whether there was an ongoing antitrust case? Given that bundling and unbundling is ubiquitous in the history of the computer industry, the answer is likely yes.

As the following charts show, IBM first created an integrated solution in the mainframe market, controlling everything from raw materials and equipment to distribution and service. When PCs disrupted mainframes, the entire value chain was unbundled. Later, Microsoft bundled its operating system with applications software. 

Source: Clayton Christensen

The first smartphone to disrupt the PC market was the Apple iPhone — an integrated solution. And once the technology became “good enough” to meet the average consumer’s needs, Google modularized everything except the operating system (Android) and the app store (Google Play).

Source: SlashData
Source: Jake Nielson

Another key prong in Tim Wu’s argument that the government served as an effective “policeman at the elbow” in the IBM case is that the company adopted an open model when it entered the PC market and did not require an exclusive license from Microsoft to use its operating system. But exclusivity is only one term in a contract negotiation. In an interview with Playboy magazine in 1994, Bill Gates explained how he was able to secure favorable terms from IBM (emphasis added):

Our restricting IBM’s ability to compete with us in licensing MS-DOS to other computer makers was the key point of the negotiation. We wanted to make sure only we could license it. We did the deal with them at a fairly low price, hoping that would help popularize it. Then we could make our move because we insisted that all other business stay with us. We knew that good IBM products are usually cloned, so it didn’t take a rocket scientist to figure out that eventually we could license DOS to others. We knew that if we were ever going to make a lot of money on DOS it was going to come from the compatible guys, not from IBM. They paid us a fixed fee for DOS. We didn’t get a royalty, even though we did make some money on the deal. Other people paid a royalty. So it was always advantageous to us, the market grew and other hardware guys were able to sell units.

In this version of the story, IBM refrained from demanding an exclusive license from Microsoft not because it was fearful of antitrust enforcers but because Microsoft made significant concessions on price and capped its upside by agreeing to a fixed fee rather than a royalty. These economic and technical explanations for why IBM wasn’t able to leverage its dominant position in mainframes into the PC market are more consistent with the evidence than Wu’s “policeman at the elbow” theory.

In my next post, I will discuss the other major antitrust case that came to an end in 1982: AT&T.

Big Tech continues to be mired in “a very antitrust situation,” as President Trump put it in 2018. Antitrust advocates have zeroed in on Facebook, Google, Apple, and Amazon as their primary targets. These advocates justify their proposals by pointing to the trio of antitrust cases against IBM, AT&T, and Microsoft. Elizabeth Warren, in announcing her plan to break up the tech giants, highlighted the case against Microsoft:

The government’s antitrust case against Microsoft helped clear a path for Internet companies like Google and Facebook to emerge. The story demonstrates why promoting competition is so important: it allows new, groundbreaking companies to grow and thrive — which pushes everyone in the marketplace to offer better products and services.

Tim Wu, a law professor at Columbia University, summarized the overarching narrative recently (emphasis added):

If there is one thing I’d like the tech world to understand better, it is that the trilogy of antitrust suits against IBM, AT&T, and Microsoft played a major role in making the United States the world’s preeminent tech economy.

The IBM-AT&T-Microsoft trilogy of antitrust cases each helped prevent major monopolists from killing small firms and asserting control of the future (of the 80s, 90s, and 00s, respectively).

A list of products and firms that owe at least something to the IBM-AT&T-Microsoft trilogy.

(1) IBM: software as product, Apple, Microsoft, Intel, Seagate, Sun, Dell, Compaq

(2) AT&T: Modems, ISPs, AOL, the Internet and Web industries

(3) Microsoft: Google, Facebook, Amazon

Wu argues that by breaking up the current crop of dominant tech companies, we can sow the seeds for the next one. But this reasoning depends on an incorrect — albeit increasingly popular — reading of the history of the tech industry. Entrepreneurs take purposeful action to produce innovative products for an underserved segment of the market. They also respond to broader technological change by integrating or modularizing different products in their market. This bundling and unbundling is a never-ending process.

Whether the government distracts a dominant incumbent with a failed lawsuit (e.g., IBM), imposes an ineffective conduct remedy (e.g., Microsoft), or breaks up a government-granted national monopoly into regional monopolies (e.g., AT&T), the dynamic nature of competition between tech companies will far outweigh the effects of antitrust enforcers tilting at windmills.

In a series of posts for Truth on the Market, I will review the cases against IBM, AT&T, and Microsoft and discuss what we can learn from them. In this introductory article, I will explain the relevant concepts necessary for understanding the history of market competition in the tech industry.

Competition for the Market

In industries like tech that tend toward “winner takes most,” it’s important to distinguish between competition during the market maturation phase — when no clear winner has emerged and the technology has yet to be widely adopted — and competition after the technology has been diffused in the economy. Benedict Evans recently explained how this cycle works (emphasis added):

When a market is being created, people compete at doing the same thing better. Windows versus Mac. Office versus Lotus. MySpace versus Facebook. Eventually, someone wins, and no-one else can get in. The market opportunity has closed. Be, NeXT/Path were too late. Monopoly!

But then the winner is overtaken by something completely different that makes it irrelevant. PCs overtook mainframes. HTML/LAMP overtook Win32. iOS & Android overtook Windows. Google overtook Microsoft.

Tech antitrust too often wants to insert a competitor to the winning monopolist, when it’s too late. Meanwhile, the monopolist is made irrelevant by something that comes from totally outside the entire conversation and owes nothing to any antitrust interventions.

In antitrust parlance, this is known as competing for the market. By contrast, in more static industries where the playing field doesn’t shift so radically and the market doesn’t tip toward “winner take most,” firms compete within the market. What Benedict Evans refers to as “something completely different” is often a disruptive product.

Disruptive Innovation

As Clay Christensen explains in the Innovator’s Dilemma, a disruptive product is one that is low-quality (but fast-improving), low-margin, and targeted at an underserved segment of the market. Initially, it is rational for the incumbent firms to ignore the disruptive technology and focus on improving their legacy technology to serve high-margin customers. But once the disruptive technology improves to the point it can serve the whole market, it’s too late for the incumbent to switch technologies and catch up. This process looks like overlapping s-curves:

Source: Max Mayblum

We see these S-curves in the technology industry all the time:

Source: Benedict Evans

As Christensen explains in the Innovator’s Solution, consumer needs can be thought of as “jobs-to-be-done.” Early on, when a product is just good enough to get a job done, firms compete on product quality and pursue an integrated strategy — designing, manufacturing, and distributing the product in-house. As the underlying technology improves and the product overshoots the needs of the jobs-to-be-done, products become modular and the primary dimension of competition moves to cost and convenience. As this cycle repeats itself, companies are either bundling different modules together to create more integrated products or unbundling integrated products to create more modular products.

Moore’s Law

Source: Our World in Data

Moore’s Law is the gasoline that gets poured on the fire of technology cycles. Though this “law” is nothing more than the observation that “the number of transistors in a dense integrated circuit doubles about every two years,” the implications for dynamic competition are difficult to overstate. As Bill Gates explained in a 1994 interview with Playboy magazine, Moore’s Law means that computer power is essentially “free” from an engineering perspective:

When you have the microprocessor doubling in power every two years, in a sense you can think of computer power as almost free. So you ask, Why be in the business of making something that’s almost free? What is the scarce resource? What is it that limits being able to get value out of that infinite computing power? Software.

Exponentially smaller integrated circuits can be combined with new user interfaces and networks to create new computer classes, which themselves represent the opportunity for disruption.

Bell’s Law of Computer Classes

Source: Brad Campbell

A corollary to Moore’s Law, Bell’s law of computer classes predicts that “roughly every decade a new, lower priced computer class forms based on a new programming platform, network, and interface resulting in new usage and the establishment of a new industry.” Originally formulated in 1972, we have seen this prediction play out in the birth of mainframes, minicomputers, workstations, personal computers, laptops, smartphones, and the Internet of Things.

Understanding these concepts — competition for the market, disruptive innovation, Moore’s Law, and Bell’s Law of Computer Classes — will be crucial for understanding the true effects (or lack thereof) of the antitrust cases against IBM, AT&T, and Microsoft. In my next post, I will look at the DOJ’s (ultimately unsuccessful) 13-year antitrust battle with IBM.

Qualcomm is currently in the midst of a high-profile antitrust case against the FTC. At the heart of these proceedings lies Qualcomm’s so-called “No License, No Chips” (NLNC) policy, whereby it purportedly refuses to sell chips to OEMs that have not concluded a license agreement covering its underlying intellectual property. According to the FTC and Qualcomm’s opponents, this ultimately thwarts competition in the chipset market.

Against this backdrop, Mark Lemley, Douglas Melamed, and Steven Salop penned a high-profile amicus brief supporting the FTC’s stance. 

We responded to their brief in a Truth on the Market blog post, and this led to a series of blog exchanges between the amici and ourselves. 

This post summarizes these exchanges.

1. Amicus brief supporting the FTC’s stance, and ICLE brief in support of Qualcomm’s position

The starting point of this blog exchange was an Amicus brief written by Mark Lemley, Douglas Melamed, and Steven Salop (“the amici”) , and signed by 40 law and economics scholars. 

The amici made two key normative claims:

  • Qualcomm’s no license, no chips policy is unlawful under well-established antitrust principles: 
    Qualcomm uses the NLNC policy to make it more expensive for OEMs to purchase competitors’ chipsets, and thereby disadvantages rivals and creates artificial barriers to entry and competition in the chipset markets.”
  • Qualcomm’s refusal to license chip-set rivals reinforces the no license, no chips policy and violates the antitrust laws:
    Qualcomm’s refusal to license chipmakers is also unlawful, in part because it bolsters the NLNC policy.16 In addition, Qualcomm’s refusal to license chipmakers increases the costs of using rival chipsets, excludes rivals, and raises barriers to entry even if NLNC is not itself illegal.

It is important to note that ICLE also filed an amicus brief in these proceedings. Contrary to the amici, ICLE’s scholars concluded that Qualcomm’s behavior did not raise any antitrust concerns and was ultimately a matter of contract law and .

2. ICLE response to the Lemley, Melamed and Salop Amicus brief.

We responded to the amici in a first blog post

The post argued that the amici failed to convincingly show that Qualcomm’s NLNC policy was exclusionary. We notably highlighted two important factors.

  • First, Qualcomm could not use its chipset position and NLNC policy to avert the threat of FRAND litigation, thus extracting supracompetitve royalties:
    Qualcomm will be unable to charge a total price that is significantly above the price of rivals’ chips, plus the FRAND rate for its IP (and expected litigation costs).”
  • Second, Qualcomm’s behavior did not appear to fall within standard patterns of strategic behavior:
    The amici attempt to overcome this weakness by implicitly framing their argument in terms of exclusivity, strategic entry deterrence, and tying […]. But none of these arguments totally overcomes the flaw in their reasoning.” 

3. Amici’s counterargument 

The amici wrote a thoughtful response to our post. Their piece rested on two main arguments:

  • The Amici underlined that their theory of anticompetitive harm did not imply any form of profit sacrifice on Qualcomm’s part (in the chip segment):
    Manne and Auer seem to think that the concern with the no license/no chips policy is that it enables inflated patent royalties to subsidize a profit sacrifice in chip sales, as if the issue were predatory pricing in chips.  But there is no such sacrifice.
  • The deleterious effects of Qualcomm’s behavior were merely a function of its NLNC policy and strong chipset position. In conjunction, these two factors deterred OEMs from pursuing FRAND litigation:
    Qualcomm is able to charge more than $2 for the license only because it uses the power of its chip monopoly to coerce the OEMs to give up the option of negotiating in light of the otherwise applicable constraints on the royalties it can charge.

4. ICLE rebuttal

We then responded to the amici with the following points:

  • We agreed that it would be a problem if Qualcomm could prevent OEMs from negotiating license agreements in the shadow of FRAND litigation:
    The critical question is whether there is a realistic threat of litigation to constrain the royalties commanded by Qualcomm (we believe that Lemley et al. agree with us on this point).”
  • However, Qualcomm’s behavior did not preclude OEMs from pursuing this type of strategy:
    We believe the following facts support our assertion:
    OEMs have pursued various litigation strategies in order to obtain lower rates on Qualcomm’s IP. […]
    For the most part, Qualcomm’s threats to cut off chip supplies were just that: threats. […]
    OEMs also wield powerful threats. […]
    Qualcomm’s chipsets might no longer be “must-buys” in the future.”

 5. Amici’s surrebuttal

The amici sent us a final response (reproduced here in full) :

In their original post, Manne and Auer argued that the antitrust argument against Qualcomm’s no license/no chips policy was based on bad economics and bad law.  They now seem to have abandoned that argument and claim instead – contrary to the extensive factual findings of the district court – that, while Qualcomm threatened to cut off chips, it was a paper tiger that OEMs could, and knew they could, ignore.  The implication is that the Ninth Circuit should affirm the district court on the no license/ no chips issue unless it sets aside the court’s fact findings.  That seems like agreement with the position of our amicus brief.

We will not in this post review the huge factual record.  We do note, however, that Manne and Auer cite in support of their factual argument only that 3 industry giants brought and then settled litigation against Qualcomm.  But all 3 brought antitrust litigation; their doing so hardly proves that contract litigation or what Manne and Auer call “holdout” were viable options for anyone, much less for smaller OEMs.  The fact that Qualcomm found it necessary to actually cut off only one OEM – and then it only took the OEM only 7 days to capitulate – certainly does not prove that Qualcomm’s threats lacked credibility.   Notably, Manne and Auer do not claim that any OEMs bought chips from competitors of Qualcomm (although Apple bought some chips from Intel for a short while). No license/no chips appears to have been a successful, coercive policy, not an easily ignored threat.                                                                                                                                              

6. Concluding remarks

First and foremost, we would like to thank the Amici for thoughtfully engaging with us. This is what the law & economics tradition is all about: moving the ball forward by taking part in vigorous, multidisciplinary, debates.

With that said, we do feel compelled to leave readers with two short remarks. 

First, contrary to what the amici claim, we believe that our position has remained the same throughout these debates. 

Second, and more importantly, we think that everyone agrees that the critical question is whether OEMs were prevented from negotiating licenses in the shadow of FRAND litigation. 

We leave it up to Truth on the Market readers to judge which side of this debate is correct.