Archives For petit-moligopoly-symposium

[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.

[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.]

To mark the release of Nicolas Petit’s “Big Tech and the Digital Economy: The Moligopoly Scenario”, Truth on the Market and  International Center for Law & Economics (ICLE) are hosting some of the world’s leading scholars and practitioners of competition law and economics to discuss some of the book’s themes.

In his book, Petit offers a “moligopoly” framework for understanding competition between large tech companies that may have significant market shares in their ‘home’ markets but nevertheless compete intensely in adjacent ones. Petit argues that tech giants coexist as both monopolies and oligopolies in markets defined by uncertainty and dynamism, and offers policy tools for dealing with the concerns people have about these markets that avoid crude “big is bad” assumptions and do not try to solve non-economic harms with the tools of antitrust.

This symposium asks contributors to give their thoughts either on the book as a whole or on a selected chapter that relates to their own work. In it we hope to explore some of Petit’s arguments with different perspectives from our contributors.

Confirmed Participants

As in the past (see examples of previous TOTM blog symposia here), we’ve lined up an outstanding and diverse group of scholars to discuss these issues, including:

  • Kelly Fayne, Antitrust Associate, Latham & Watkins
  • Shane Greenstein, Professor of Business Administration; Co-chair of the HBS Digital Initiative, Harvard Business School
  • Peter Klein, Professor of Entrepreneurship and Chair, Department of Entrepreneurship and Corporate Innovation, Baylor University
  • William Kovacic, Global Competition Professor of Law and Policy; Director, Competition Law Center, George Washington University Law
  • Kai-Uwe Kuhn, Academic Advisor, University of East Anglia
  • Richard Langlois, Professor of Economics, University of Connecticut
  • Doug Melamed, Professor of the Practice of Law, Stanford law School
  • David Teece, Professor in Global Business, University of California’s Haas School of Business (Berkeley); Director, Center for Global Strategy; Governance and Faculty Director, Institute for Business Innovation

Thank you again to all of the excellent authors for agreeing to participate in this interesting and timely symposium.

Look for the first posts starting later today, October 12, 2020.