10 Things the American Innovation and Choice Online Act Gets Wrong - International Center for Law & Economics
Focus Areas:    Antitrust | Competition | FTC

10 Things the American Innovation and Choice Online Act Gets Wrong

Truth on the Market View Original

The Senate Judiciary Committee is set to debate S. 2992, the American Innovation and Choice Online Act (or AICOA) during a markup session Thursday. If passed into law, the bill would force online platforms to treat rivals’ services as they would their own, while ensuring their platforms interoperate seamlessly.

The bill marks the culmination of misguided efforts to bring Big Tech to heel, regardless of the negative costs imposed upon consumers in the process. ICLE scholars have written about these developments in detail since the bill was introduced in October.

Below are 10 significant misconceptions that underpin the legislation.

1. There Is No Evidence that Self-Preferencing Is Generally Harmful

Self-preferencing is a normal part of how platforms operate, both to improve the value of their core products and to earn returns so that they have reason to continue investing in their development.

Platforms’ incentives are to maximize the value of their entire product ecosystem, which includes both the core platform and the services attached to it. Platforms that preference their own products frequently end up increasing the total market’s value by growing the share of users of a particular product. Those that preference inferior products end up hurting their attractiveness to users of their “core” product, exposing themselves to competition from rivals.

As Geoff Manne concludes, the notion that it is harmful (notably to innovation) when platforms enter into competition with edge providers is entirely speculative. Indeed, a range of studies show that the opposite is likely true. Platform competition is more complicated than simple theories of vertical discrimination would have it, and there is certainly no basis for a presumption of harm.

Consider a few examples from the empirical literature:

  1. Li and Agarwal (2017) find that Facebook’s integration of Instagram led to a significant increase in user demand both for Instagram itself and for the entire category of photography apps. Instagram’s integration with Facebook increased consumer awareness of photography apps, which benefited independent developers, as well as Facebook.
  2. Foerderer, et al. (2018) find that Google’s 2015 entry into the market for photography apps on Android created additional user attention and demand for such apps generally.
  3. Cennamo, et al. (2018) find that video games offered by console firms often become blockbusters and expand the consoles’ installed base. As a result, these games increase the potential for all independent game developers to profit from their games, even in the face of competition from first-party games.
  4. Finally, while Zhu and Liu (2018) is often held up as demonstrating harm from Amazon’s competition with third-party sellers on its platform, its findings are actually far from clear-cut. As co-author Feng Zhu noted in the Journal of Economics & Management Strategy: “[I]f Amazon’s entries attract more consumers, the expanded customer base could incentivize more third‐ party sellers to join the platform. As a result, the long-term effects for consumers of Amazon’s entry are not clear.”

2. Interoperability Is Not Costless

There are many things that could be interoperable, but aren’t. The reason not everything is interoperable is because interoperability comes with costs, as well as benefits. It may be worth letting different earbuds have different designs because, while it means we sacrifice easy interoperability, we gain the ability for better designs to be brought to market and for consumers to have choice among different kinds.

As Sam Bowman has observed, there are often costs that prevent interoperability from being worth the tradeoff, such as that:

  1. It might be too costly to implement and/or maintain.
  2. It might prescribe a certain product design and prevent experimentation and innovation.
  3. It might add too much complexity and/or confusion for users, who may prefer not to have certain choices.
  4. It might increase the risk of something not working, or of security breaches.
  5. It might prevent certain pricing models that increase output.
  6. It might compromise some element of the product or service that benefits specifically from not being interoperable.

In a market that is functioning reasonably well, we should be able to assume that competition and consumer choice will discover the desirable degree of interoperability among different products. If there are benefits to making your product interoperable that outweigh the costs of doing so, that should give you an advantage over competitors and allow you to compete them away. If the costs outweigh the benefits, the opposite will happen: consumers will choose products that are not interoperable.

In short, we cannot infer from the mere absence of interoperability that something is wrong, since we frequently observe that the costs of interoperability outweigh the benefits.

3. Consumers Often Prefer Closed Ecosystems

Digital markets could have taken a vast number of shapes. So why have they gravitated toward the very characteristics that authorities condemn? For instance, if market tipping and consumer lock-in are so problematic, why is it that new corners of the digital economy continue to emerge via closed platforms, as opposed to collaborative ones?

Indeed, if recent commentary is to be believed, it is the latter that should succeed, because they purportedly produce greater gains from trade. And if consumers and platforms cannot realize these gains by themselves, then we should see intermediaries step into that breach. But this does not seem to be happening in the digital economy.

The naïve answer is to say that the absence of “open” systems is precisely the problem. What’s harder is to try to actually understand why. As I have written, there are many reasons that consumers might prefer “closed” systems, even when they have to pay a premium for them.

Take the example of app stores. Maintaining some control over the apps that can access the store notably enables platforms to easily weed out bad players. Similarly, controlling the hardware resources that each app can use may greatly improve device performance. In other words, centralized platforms can eliminate negative externalities that “bad” apps impose on rival apps and on consumers. This is especially true when consumers struggle to attribute dips in performance to an individual app, rather than the overall platform.

It is also conceivable that consumers prefer to make many of their decisions at the inter-platform level, rather than within each platform. In simple terms, users arguably make their most important decision when they choose between an Apple or Android smartphone (or a Mac and a PC, etc.). In doing so, they can select their preferred app suite with one simple decision.

They might thus purchase an iPhone because they like the secure App Store, or an Android smartphone because they like the Chrome Browser and Google Search. Forcing too many “within-platform” choices upon users may undermine a product’s attractiveness. Indeed, it is difficult to create a high-quality reputation if each user’s experience is fundamentally different. In short, contrary to what antitrust authorities seem to believe, closed platforms might be giving most users exactly what they desire.

Too often, it is simply assumed that consumers benefit from more openness, and that shared/open platforms are the natural order of things. What some refer to as “market failures” may in fact be features that explain the rapid emergence of the digital economy. Ronald Coase said it best when he quipped that economists always find a monopoly explanation for things that they simply fail to understand.

4. Data Portability Can Undermine Security and Privacy

As explained above, platforms that are more tightly controlled can be regulated by the platform owner to avoid some of the risks present in more open platforms. Apple’s App Store, for example, is a relatively closed and curated platform, which gives users assurance that apps will meet a certain standard of security and trustworthiness.

Along similar lines, there are privacy issues that arise from data portability. Even a relatively simple requirement to make photos available for download can implicate third-party interests. Making a user’s photos more broadly available may tread upon the privacy interests of friends whose faces appear in those photos. Importing those photos to a new service potentially subjects those individuals to increased and un-bargained-for security risks.

As Sam Bowman and Geoff Manne observe, this is exactly what happened with Facebook and its Social Graph API v1.0, ultimately culminating in the Cambridge Analytica scandal. Because v1.0 of Facebook’s Social Graph API permitted developers to access information about a user’s friends without consent, it enabled third-party access to data about exponentially more users. It appears that some 270,000 users granted data access to Cambridge Analytica, from which the company was able to obtain information on 50 million Facebook users.

In short, there is often no simple solution to implement interoperability and data portability. Any such program—whether legally mandated or voluntarily adopted—will need to grapple with these and other tradeoffs.

5. Network Effects Are Rarely Insurmountable

Several scholars in recent years have called for more muscular antitrust intervention in networked industries on grounds that network externalities, switching costs, and data-related increasing returns to scale lead to inefficient consumer lock-in and raise entry barriers for potential rivals (see herehere, and here). But there are countless counterexamples where firms have easily overcome potential barriers to entry and network externalities, ultimately disrupting incumbents.

Zoom is one of the most salient instances. As I wrote in April 2019 (a year before the COVID-19 pandemic):

To get to where it is today, Zoom had to compete against long-established firms with vast client bases and far deeper pockets. These include the likes of Microsoft, Cisco, and Google. Further complicating matters, the video communications market exhibits some prima facie traits that are typically associated with the existence of network effects.

Geoff Manne and Alec Stapp have put forward a multitude of other examples,  including: the demise of Yahoo; the disruption of early instant-messaging applications and websites; and MySpace’s rapid decline. In all of these cases, outcomes did not match the predictions of theoretical models.

More recently, TikTok’s rapid rise offers perhaps the greatest example of a potentially superior social-networking platform taking significant market share away from incumbents. According to the Financial Times, TikTok’s video-sharing capabilities and powerful algorithm are the most likely explanations for its success.

While these developments certainly do not disprove network-effects theory, they eviscerate the belief, common in antitrust circles, that superior rivals are unable to overthrow incumbents in digital markets. Of course, this will not always be the case. The question is ultimately one of comparing institutions—i.e., do markets lead to more or fewer error costs than government intervention? Yet, this question is systematically omitted from most policy discussions.

6. Profits Facilitate New and Exciting Platforms

As I wrote in August 2020, the relatively closed model employed by several successful platforms (notably Apple’s App Store, Google’s Play Store, and the Amazon Retail Platform) allows previously unknown developers/retailers to rapidly expand because (i) users do not have to fear their apps contain some form of malware and (ii) they greatly reduce payments frictions, most notably security-related ones.

While these are, indeed, tremendous benefits, another important upside seems to have gone relatively unnoticed. The “closed” business model also gives firms significant incentives to develop new distribution mediums (smart TVs spring to mind) and to improve existing ones. In turn, this greatly expands the audience that software developers can reach. In short, developers get a smaller share of a much larger pie.

The economics of two-sided markets are enlightening here. For example, Apple and Google’s app stores are what Armstrong and Wright (here and here) refer to as “competitive bottlenecks.” That is, they compete aggressively (among themselves, and with other gaming platforms) to attract exclusive users. They can then charge developers a premium to access those users.

This dynamic gives firms significant incentive to continue to attract and retain new users. For instance, if Steve Jobs is to be believed, giving consumers better access to media such as eBooks, video, and games was one of the driving forces behind the launch of the iPad.

This model of innovation would be seriously undermined if developers and consumers could easily bypass platforms, as would likely be the case under the American Innovation and Choice Online Act.

7. Large Market Share Does Not Mean Anticompetitive Outcomes

Scholars routinely cite the putatively strong concentration of digital markets to argue that Big Tech firms do not face strong competition. But this is a non sequitur. Indeed, as economists like Joseph Bertrand and William Baumol have shown, what matters is not whether markets are concentrated, but whether they are contestable. If a superior rival could rapidly gain user traction, that alone will discipline incumbents’ behavior.

Markets where incumbents do not face significant entry from competitors are just as consistent with vigorous competition as they are with barriers to entry. Rivals could decline to enter either because incumbents have aggressively improved their product offerings or because they are shielded by barriers to entry (as critics suppose). The former is consistent with competition, the latter with monopoly slack.

Similarly, it would be wrong to presume, as many do, that concentration in online markets is necessarily driven by network effects and other scale-related economies. As ICLE scholars have argued elsewhere (herehere and here), these forces are not nearly as decisive as critics assume (and it is debatable that they constitute barriers to entry).

Finally, and perhaps most importantly, many factors could explain the relatively concentrated market structures that we see in digital industries. The absence of switching costs and capacity constraints are two such examples. These explanations, overlooked by many observers, suggest digital markets are more contestable than is commonly perceived.

Unfortunately, critics’ failure to meaningfully grapple with these issues serves to shape the “conventional wisdom” in tech-policy debates.

8. Vertical Integration Generally Benefits Consumers

Vertical behavior of digital firms—whether through mergers or through contract and unilateral action—frequently arouses the ire of critics of the current antitrust regime. Many such critics point to a few recent studies that cast doubt on the ubiquity of benefits from vertical integration. But the findings of these few studies are regularly overstated and, even if taken at face value, represent a just minuscule fraction of the collected evidence, which overwhelmingly supports vertical integration.

There is strong and longstanding empirical evidence that vertical integration is competitively benign. This includes widely acclaimed work by economists Francine Lafontaine (former director of the Federal Trade Commission’s Bureau of Economics under President Barack Obama) and Margaret Slade, whose meta-analysis led them to conclude:

[U]nder most circumstances, profit-maximizing vertical integration decisions are efficient, not just from the firms’ but also from the consumers’ points of view. Although there are isolated studies that contradict this claim, the vast majority support it. Moreover, even in industries that are highly concentrated so that horizontal considerations assume substantial importance, the net effect of vertical integration appears to be positive in many instances. We therefore conclude that, faced with a vertical arrangement, the burden of evidence should be placed on competition authorities to demonstrate that that arrangement is harmful before the practice is attacked.

In short, there is a substantial body of both empirical and theoretical research showing that vertical integration (and the potential vertical discrimination and exclusion to which it might give rise) is generally beneficial to consumers. While it is possible that vertical mergers or discrimination could sometimes cause harm, the onus is on the critics to demonstrate empirically where this occurs. No legitimate interpretation of the available literature would offer a basis for imposing a presumption against such behavior.

9. There Is No Such Thing as Data Network Effects

Although data does not have the self-reinforcing characteristics of network effects, there is a sense that acquiring a certain amount of data and expertise is necessary to compete in data-heavy industries. It is (or should be) equally apparent, however, that this “learning by doing” advantage rapidly reaches a point of diminishing returns.

This is supported by significant empirical evidence. As was shown by the survey pf the empirical literature that Geoff Manne and I performed (published in the George Mason Law Review), data generally entails diminishing marginal returns:

Critics who argue that firms such as Amazon, Google, and Facebook are successful because of their superior access to data might, in fact, have the causality in reverse. Arguably, it is because these firms have come up with successful industry-defining paradigms that they have amassed so much data, and not the other way around. Indeed, Facebook managed to build a highly successful platform despite a large data disadvantage when compared to rivals like MySpace.

Companies need to innovate to attract consumer data or else consumers will switch to competitors, including both new entrants and established incumbents. As a result, the desire to make use of more and better data drives competitive innovation, with manifestly impressive results. The continued explosion of new products, services, and apps is evidence that data is not a bottleneck to competition, but a spur to drive it.

10.  Antitrust Enforcement Has Not Been Lax

The popular narrative has it that lax antitrust enforcement has led to substantially increased concentration, strangling the economy, harming workers, and expanding dominant firms’ profit margins at the expense of consumers. Much of the contemporary dissatisfaction with antitrust arises from a suspicion that overly lax enforcement of existing laws has led to record levels of concentration and a concomitant decline in competition. But both beliefs—lax enforcement and increased anticompetitive concentration—wither under more than cursory scrutiny.

As Geoff Manne observed in his April 2020 testimony to the House Judiciary Committee:

The number of Sherman Act cases brought by the federal antitrust agencies, meanwhile, has been relatively stable in recent years, but several recent blockbuster cases have been brought by the agencies and private litigants, and there has been no shortage of federal and state investigations. The vast majority of Section 2 cases dismissed on the basis of the plaintiff’s failure to show anticompetitive effect were brought by private plaintiffs pursuing treble damages; given the incentives to bring weak cases, it cannot be inferred from such outcomes that antitrust law is ineffective. But, in any case, it is highly misleading to count the number of antitrust cases and, using that number alone, to make conclusions about how effective antitrust law is. Firms act in the shadow of the law, and deploy significant legal resources to make sure they avoid activity that would lead to enforcement actions. Thus, any given number of cases brought could be just as consistent with a well-functioning enforcement regime as with an ill-functioning one.

The upshot is that naïvely counting antitrust cases (or the purported lack thereof), with little regard for the behavior that is deterred or the merits of the cases that are dismissed does not tell us whether or not antitrust enforcement levels are optimal.

Further reading:

Law review articles

Issue briefs

Shorter pieces