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[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).
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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.