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Digital advertising is the economic backbone of the Internet. It allows websites and apps to monetize their userbase without having to charge them fees, while the emergence of targeted ads allows this to be accomplished affordably and with less wasted time wasted.

This advertising is facilitated by intermediaries using the “adtech stack,” through which advertisers and publishers are matched via auctions and ads ultimately are served to relevant users. This intermediation process has advanced enormously over the past three decades. Some now allege, however, that this market is being monopolized by its largest participant: Google.

A lawsuit filed by the State of Texas and nine other states in December 2020 alleges, among other things, that Google has engaged in anticompetitive conduct related to its online display advertising business. Those 10 original state plaintiffs were joined by another four states and the Commonwealth of Puerto Rico in March 2021, while South Carolina and Louisiana have also moved to be added as additional plaintiffs. Google also faces a pending antitrust lawsuit brought by the U.S. Justice Department (DOJ) and 14 states (originally 11) related to the company’s distribution agreements, as well as a separate action by the State of Utah, 35 other states, and the District of Columbia related to its search design.

In recent weeks, it has been reported that the DOJ may join the Texas suit or bring its own similar action against Google in the coming months. If it does, it should learn from the many misconceptions and errors in the Texas complaint that leave it on dubious legal and economic grounds.

​​Relevant market

The Texas complaint identifies at least five relevant markets within the adtech stack that it alleges Google either is currently monopolizing or is attempting to monopolize:

  1. Publisher ad servers;
  2. Display ad exchanges;
  3. Display ad networks;
  4. Ad-buying tools for large advertisers; and
  5. Ad-buying tools for small advertisers.

None of these constitute an economically relevant product market for antitrust purposes, since each “market” is defined according to how superficially similar the products are in function, not how substitutable they are. Nevertheless, the Texas complaint vaguely echoes how markets were conceived in the “Roadmap” for a case against Google’s advertising business, published last year by the Omidyar Network, which may ultimately influence any future DOJ complaint, as well.

The Omidyar Roadmap narrows the market from media advertising to digital advertising, then to the open supply of display ads, which comprises only 9% of the total advertising spending and less than 20% of digital advertising, as shown in the figure below. It then further narrows the defined market to the intermediation of the open supply of display ads. Once the market has been sufficiently narrowed, the Roadmap authors conclude that Google’s market share is “perhaps sufficient to confer market power.”

While whittling down the defined market may achieve the purposes of sketching a roadmap to prosecute Google, it also generates a mishmash of more than a dozen relevant markets for digital display and video advertising. In many of these, Google doesn’t have anything approaching market power, while, in some, Facebook is the most dominant player.

The Texas complaint adopts a non-economic approach to market definition.  It ignores potential substitutability between different kinds of advertising, both online and offline, which can serve as a competitive constraint on the display advertising market. The complaint considers neither alternative forms of display advertising, such as social media ads, nor alternative forms of advertising, such as search ads or non-digital ads—all of which can and do act as substitutes. It is possible, at the very least, that advertisers who choose to place ads on third-party websites may switch to other forms of advertising if the price of third-party website advertising was above competitive levels. To ignore this possibility, as the Texas complaint does, is to ignore the entire purpose of defining the relevant antitrust market altogether.

Offline advertising vs. online advertising

The fact that offline and online advertising employ distinct processes does not consign them to economically distinct markets. Indeed, online advertising has manifestly drawn advertisers from offline markets, just as previous technological innovations drew advertisers from other pre-existing channels.

Moreover, there is evidence that, in some cases, offline and online advertising are substitute products. For example, economists Avi Goldfarb and Catherine Tucker demonstrate that display advertising pricing is sensitive to the availability of offline alternatives. They conclude:

We believe our studies refute the hypothesis that online and offline advertising markets operate independently and suggest a default position of substitution. Online and offline advertising markets appear to be closely related. That said, it is important not to draw any firm conclusions based on historical behavior.

Display ads vs. search ads

There is perhaps even more reason to doubt that online display advertising constitutes a distinct, economically relevant market from online search advertising.

Although casual and ill-informed claims are often made to the contrary, various forms of targeted online advertising are significant competitors of each other. Bo Xing and Zhanxi Lin report firms spread their marketing budgets across these different sources of online marketing, and “search engine optimizers”—firms that help websites to maximize the likelihood of a valuable “top-of-list” organic search placement—attract significant revenue. That is, all of these different channels vie against each other for consumer attention and offer advertisers the ability to target their advertising based on data gleaned from consumers’ interactions with their platforms.

Facebook built a business on par with Google’s thanks in large part to advertising, by taking advantage of users’ more extended engagement with the platform to assess relevance and by enabling richer, more engaged advertising than previously appeared on Google Search. It’s an entirely different model from search, but one that has turned Facebook into a competitive ad platform.

And the market continues to shift. Somewhere between 37-56% of product searches start on Amazon, according to one survey, and advertisers have noticed. This is not surprising, given Amazon’s strong ability to match consumers with advertisements, and to do so when and where consumers are more likely to make a purchase.

‘Open’ display advertising vs. ‘owned-and-operated’ display advertising

The United Kingdom’s Competition and Markets Authority (like the Omidyar Roadmap report) has identified two distinct channels of display advertising, which they term “owned and operated” and “open.” The CMA concludes:

Over half of display expenditure is generated by Facebook, which owns both the Facebook platform and Instagram. YouTube has the second highest share of display advertising and is owned by Google. The open display market, in which advertisers buy inventory from many publishers of smaller scale (for example, newspapers and app providers) comprises around 32% of display expenditure.

The Texas complaint does not directly address the distinction between open and owned and operated, but it does allege anticompetitive conduct by Google with respect to YouTube in a separate “inline video advertising market.” 

The CMA finds that the owned-and-operated channel mostly comprises large social media platforms, which sell their own advertising inventory directly to advertisers or media agencies through self-service interfaces, such as Facebook Ads Manager or Snapchat Ads Manager.  In contrast, in the open display channel, publishers such as online newspapers and blogs sell their inventory to advertisers through a “complex chain of intermediaries.”  Through these, intermediaries run auctions that match advertisers’ ads to publisher inventory of ad space. In both channels, nearly all transactions are run through programmatic technology.

The CMA concludes that advertisers “largely see” the open and the owned-and-operated channels as substitutes. According to the CMA, an advertiser’s choice of one channel over the other is driven by each channel’s ability to meet the key performance metrics the advertising campaign is intended to achieve.

The Omidyar Roadmap argues, instead, that the CMA too narrowly focuses on the perspective of advertisers. The Roadmap authors claim that “most publishers” do not control supply that is “owned and operated.” As a result, they conclude that publishers “such as gardenandgun.com or hotels.com” do not have any owned-and-operated supply and can generate revenues from their supply “only through the Google-dominated adtech stack.” 

But this is simply not true. For example, in addition to inventory in its print media, Garden & Gun’s “Digital Media Kit” indicates that the publisher has several sources of owned-and-operated banner and video supply, including the desktop, mobile, and tablet ads on its website; a “homepage takeover” of its website; branded/sponsored content; its email newsletters; and its social media accounts. Hotels.com, an operating company of Expedia Group, has its own owned-and-operated search inventory, which it sells through its “Travel Ads Sponsored Listing,” as well owned-and-operated supply of standard and custom display ads.

Given that both perform the same function and employ similar mechanisms for matching inventory with advertisers, it is unsurprising that both advertisers and publishers appear to consider the owned-and-operated channel and the open channel to be substitutes.

Advocates of legislative action to “reform” antitrust law have already pointed to the U.S. District Court for the District of Columbia’s dismissal of the state attorneys general’s case and the “conditional” dismissal of the Federal Trade Commission’s case against Facebook as evidence that federal antitrust case law is lax and demands correction. In fact, the court’s decisions support the opposite implication. 

The Risks of Antitrust by Anecdote

The failure of a well-resourced federal regulator, and more than 45 state attorney-general offices, to avoid dismissal at an early stage of the litigation testifies to the dangers posed by a conclusory approach toward antitrust enforcement that seeks to unravel acquisitions consummated almost a decade ago without even demonstrating the factual predicates to support consideration of such far-reaching interventions. The dangers to the rule of law are self-evident. Irrespective of one’s views on the appropriate direction of antitrust law, this shortcut approach would substitute prosecutorial fiat, ideological predilection, and popular sentiment for decades of case law and agency guidelines grounded in the rigorous consideration of potential evidence of competitive harm. 

The paucity of empirical support for the exceptional remedial action sought by the FTC is notable. As the district court observed, there was little systematic effort made to define the economically relevant market or provide objective evidence of market power, beyond the assertion that Facebook has a market share of “in excess of 60%.” Remarkably, the denominator behind that 60%-plus assertion is not precisely defined, since the FTC’s brief does not supply any clear metric by which to measure market share. As the court pointed out, this is a nontrivial task in multi-sided environments in which one side of the potentially relevant market delivers services to users at no charge.  

While the point may seem uncontroversial, it is important to re-appreciate why insisting on a rigorous demonstration of market power is critical to preserving a coherent body of law that provides the market with a basis for reasonably anticipating the likelihood of antitrust intervention. At least since the late 1970s, courts have recognized that “big is not always bad” and can often yield cost savings that ultimately redound to consumers’ benefit. That is: firm size and consumer welfare do not stand in inherent opposition. If courts were to abandon safeguards against suits that cannot sufficiently define the relevant market and plausibly show market power, antitrust litigation could easily be used as a tool to punish successful firms that prevail over competitors simply by being more efficient. In other words: antitrust law could become a tool to preserve competitor welfare at the expense of consumer welfare.

The Specter of No-Fault Antitrust Liability

The absence of any specific demonstration of market power suggests deficient lawyering or the inability to gather supporting evidence. Giving the FTC litigation team the benefit of the doubt, the latter becomes the stronger possibility. If that is the case, this implies an effort to persuade courts to adopt a de facto rule of per se illegality for any firm that achieves a certain market share. (The same concept lies behind legislative proposals to bar acquisitions for firms that cross a certain revenue or market capitalization threshold.) Effectively, any firm that reached a certain size would operate under the presumption that it has market power and has secured or maintained such power due to anticompetitive practices, rather than business prowess. This would effectively convert leading digital platforms into quasi-public utilities subject to continuous regulatory intervention. Such an approach runs counter to antitrust law’s mission to preserve, rather than displace, private ordering by market forces.  

Even at the high-water point of post-World War II antitrust zealotry (a period that ultimately ended in economic malaise), proposals to adopt a rule of no-fault liability for alleged monopolization were rejected. This was for good reason. Any such rule would likely injure consumers by precluding them from enjoying the cost savings that result from the “sweet spot” scenario in which the scale and scope economies of large firms are combined with sufficiently competitive conditions to yield reduced prices and increased convenience for consumers. Additionally, any such rule would eliminate incumbents’ incentives to work harder to offer consumers reduced prices and increased convenience, since any market share preserved or acquired as a result would simply invite antitrust scrutiny as a reward.

Remembering Why Market Power Matters

To be clear, this is not to say that “Big Tech” does not deserve close antitrust scrutiny, does not wield market power in certain segments, or has not potentially engaged in anticompetitive practices.  The fundamental point is that assertions of market power and anticompetitive conduct must be demonstrated, rather than being assumed or “proved” based largely on suggestive anecdotes.  

Perhaps market power will be shown sufficiently in Facebook’s case if the FTC elects to respond to the court’s invitation to resubmit its brief with a plausible definition of the relevant market and indication of market power at this stage of the litigation. If that threshold is satisfied, then thorough consideration of the allegedly anticompetitive effect of Facebook’s WhatsApp and Instagram acquisitions may be merited. However, given the policy interest in preserving the market’s confidence in relying on the merger-review process under the Hart-Scott-Rodino Act, the burden of proof on the government should be appropriately enhanced to reflect the significant time that has elapsed since regulatory decisions not to intervene in those transactions.  

It would once have seemed mundane to reiterate that market power must be reasonably demonstrated to support a monopolization claim that could lead to a major divestiture remedy. Given the populist thinking that now leads much of the legislative and regulatory discussion on antitrust policy, it is imperative to reiterate the rationale behind this elementary principle. 

This principle reflects the fact that, outside collusion scenarios, antitrust law is typically engaged in a complex exercise to balance the advantages of scale against the risks of anticompetitive conduct. At its best, antitrust law weighs competing facts in a good faith effort to assess the net competitive harm posed by a particular practice. While this exercise can be challenging in digital markets that naturally converge upon a handful of leading platforms or multi-dimensional markets that can have offsetting pro- and anti-competitive effects, these are not reasons to treat such an exercise as an anachronistic nuisance. Antitrust cases are inherently challenging and proposed reforms to make them easier to win are likely to endanger, rather than preserve, competitive markets.

Politico has released a cache of confidential Federal Trade Commission (FTC) documents in connection with a series of articles on the commission’s antitrust probe into Google Search a decade ago. The headline of the first piece in the series argues the FTC “fumbled the future” by failing to follow through on staff recommendations to pursue antitrust intervention against the company. 

But while the leaked documents shed interesting light on the inner workings of the FTC, they do very little to substantiate the case that the FTC dropped the ball when the commissioners voted unanimously not to bring an action against Google.

Drawn primarily from memos by the FTC’s lawyers, the Politico report purports to uncover key revelations that undermine the FTC’s decision not to sue Google. None of the revelations, however, provide evidence that Google’s behavior actually harmed consumers.

The report’s overriding claim—and the one most consistently forwarded by antitrust activists on Twitter—is that FTC commissioners wrongly sided with the agency’s economists (who cautioned against intervention) rather than its lawyers (who tenuously recommended very limited intervention). 

Indeed, the overarching narrative is that the lawyers knew what was coming and the economists took wildly inaccurate positions that turned out to be completely off the mark:

But the FTC’s economists successfully argued against suing the company, and the agency’s staff experts made a series of predictions that would fail to match where the online world was headed:

— They saw only “limited potential for growth” in ads that track users across the web — now the backbone of Google parent company Alphabet’s $182.5 billion in annual revenue.

— They expected consumers to continue relying mainly on computers to search for information. Today, about 62 percent of those queries take place on mobile phones and tablets, nearly all of which use Google’s search engine as the default.

— They thought rivals like Microsoft, Mozilla or Amazon would offer viable competition to Google in the market for the software that runs smartphones. Instead, nearly all U.S. smartphones run on Google’s Android and Apple’s iOS.

— They underestimated Google’s market share, a heft that gave it power over advertisers as well as companies like Yelp and Tripadvisor that rely on search results for traffic.

The report thus asserts that:

The agency ultimately voted against taking action, saying changes Google made to its search algorithm gave consumers better results and therefore didn’t unfairly harm competitors.

That conclusion underplays what the FTC’s staff found during the probe. In 312 pages of documents, the vast majority never publicly released, staffers outlined evidence that Google had taken numerous steps to ensure it would continue to dominate the market — including emerging arenas such as mobile search and targeted advertising. [EMPHASIS ADDED]

What really emerges from the leaked memos, however, is analysis by both the FTC’s lawyers and economists infused with a healthy dose of humility. There were strong political incentives to bring a case. As one of us noted upon the FTC’s closing of the investigation: “It’s hard to imagine an agency under more pressure, from more quarters (including the Hill), to bring a case around search.” Yet FTC staff and commissioners resisted that pressure, because prediction is hard. 

Ironically, the very prediction errors that the agency’s staff cautioned against are now being held against them. Yet the claims that these errors (especially the economists’) systematically cut in one direction (i.e., against enforcement) and that all of their predictions were wrong are both wide of the mark. 

Decisions Under Uncertainty

In seeking to make an example out of the FTC economists’ inaccurate predictions, critics ignore that antitrust investigations in dynamic markets always involve a tremendous amount of uncertainty; false predictions are the norm. Accordingly, the key challenge for policymakers is not so much to predict correctly, but to minimize the impact of incorrect predictions.

Seen in this light, the FTC economists’ memo is far from the laissez-faire manifesto that critics make it out to be. Instead, it shows agency officials wrestling with uncertain market outcomes, and choosing a course of action under the assumption the predictions they make might indeed be wrong. 

Consider the following passage from FTC economist Ken Heyer’s memo:

The great American philosopher Yogi Berra once famously remarked “Predicting is difficult, especially about the future.” How right he was. And yet predicting, and making decisions based on those predictions, is what we are charged with doing. Ignoring the potential problem is not an option. So I will be reasonably clear about my own tentative conclusions and recommendation, recognizing that reasonable people, perhaps applying a somewhat different standard, may disagree. My recommendation derives from my read of the available evidence, combined with the standard I personally find appropriate to apply to Commission intervention. [EMPHASIS ADDED]

In other words, contrary to what many critics have claimed, it simply is not the case that the FTC’s economists based their recommendations on bullish predictions about the future that ultimately failed to transpire. Instead, they merely recognized that, in a dynamic and unpredictable environment, antitrust intervention requires both a clear-cut theory of anticompetitive harm and a reasonable probability that remedies can improve consumer welfare. According to the economists, those conditions were absent with respect to Google Search.

Perhaps more importantly, it is worth asking why the economists’ erroneous predictions matter at all. Do critics believe that developments the economists missed warrant a different normative stance today?

In that respect, it is worth noting that the economists’ skepticism appeared to have rested first and foremost on the speculative nature of the harms alleged and the difficulty associated with designing appropriate remedies. And yet, if anything, these two concerns appear even more salient today. 

Indeed, the remedies imposed against Google in the EU have not delivered the outcomes that enforcers expected (here and here). This could either be because the remedies were insufficient or because Google’s market position was not due to anticompetitive conduct. Similarly, there is still no convincing economic theory or empirical research to support the notion that exclusive pre-installation and self-preferencing by incumbents harm consumers, and a great deal of reason to think they benefit them (see, e.g., our discussions of the issue here and here). 

Against this backdrop, criticism of the FTC economists appears to be driven more by a prior assumption that intervention is necessary—and that it was and is disingenuous to think otherwise—than evidence that erroneous predictions materially affected the outcome of the proceedings.

To take one example, the fact that ad tracking grew faster than the FTC economists believed it would is no less consistent with vigorous competition—and Google providing a superior product—than with anticompetitive conduct on Google’s part. The same applies to the growth of mobile operating systems. Ditto the fact that no rival has managed to dislodge Google in its most important markets. 

In short, not only were the economist memos informed by the very prediction difficulties that critics are now pointing to, but critics have not shown that any of the staff’s (inevitably) faulty predictions warranted a different normative outcome.

Putting Erroneous Predictions in Context

So what were these faulty predictions, and how important were they? Politico asserts that “the FTC’s economists successfully argued against suing the company, and the agency’s staff experts made a series of predictions that would fail to match where the online world was headed,” tying this to the FTC’s failure to intervene against Google over “tactics that European regulators and the U.S. Justice Department would later label antitrust violations.” The clear message is that the current actions are presumptively valid, and that the FTC’s economists thwarted earlier intervention based on faulty analysis.

But it is far from clear that these faulty predictions would have justified taking a tougher stance against Google. One key question for antitrust authorities is whether they can be reasonably certain that more efficient competitors will be unable to dislodge an incumbent. This assessment is necessarily forward-looking. Framed this way, greater market uncertainty (for instance, because policymakers are dealing with dynamic markets) usually cuts against antitrust intervention.

This does not entirely absolve the FTC economists who made the faulty predictions. But it does suggest the right question is not whether the economists made mistakes, but whether virtually everyone did so. The latter would be evidence of uncertainty, and thus weigh against antitrust intervention.

In that respect, it is worth noting that the staff who recommended that the FTC intervene also misjudged the future of digital markets.For example, while Politico surmises that the FTC “underestimated Google’s market share, a heft that gave it power over advertisers as well as companies like Yelp and Tripadvisor that rely on search results for traffic,” there is a case to be made that the FTC overestimated this power. If anything, Google’s continued growth has opened new niches in the online advertising space.

Pinterest provides a fitting example; despite relying heavily on Google for traffic, its ad-funded service has witnessed significant growth. The same is true of other vertical search engines like Airbnb, Booking.com, and Zillow. While we cannot know the counterfactual, the vertical search industry has certainly not been decimated by Google’s “monopoly”; quite the opposite. Unsurprisingly, this has coincided with a significant decrease in the cost of online advertising, and the growth of online advertising relative to other forms.

Politico asserts not only that the economists’ market share and market power calculations were wrong, but that the lawyers knew better:

The economists, relying on data from the market analytics firm Comscore, found that Google had only limited impact. They estimated that between 10 and 20 percent of traffic to those types of sites generally came from the search engine.

FTC attorneys, though, used numbers provided by Yelp and found that 92 percent of users visited local review sites from Google. For shopping sites like eBay and TheFind, the referral rate from Google was between 67 and 73 percent.

This compares apples and oranges, or maybe oranges and grapefruit. The economists’ data, from Comscore, applied to vertical search overall. They explicitly noted that shares for particular sites could be much higher or lower: for comparison shopping, for example, “ranging from 56% to less than 10%.” This, of course, highlights a problem with the data provided by Yelp, et al.: it concerns only the websites of companies complaining about Google, not the overall flow of traffic for vertical search.

But the more important point is that none of the data discussed in the memos represents the overall flow of traffic for vertical search. Take Yelp, for example. According to the lawyers’ memo, 92 percent of Yelp searches were referred from Google. Only, that’s not true. We know it’s not true because, as Yelp CEO Jerry Stoppelman pointed out around this time in Yelp’s 2012 Q2 earnings call: 

When you consider that 40% of our searches come from mobile apps, there is quite a bit of un-monetized mobile traffic that we expect to unlock in the near future.

The numbers being analyzed by the FTC staff were apparently limited to referrals to Yelp’s website from browsers. But is there any reason to think that is the relevant market, or the relevant measure of customer access? Certainly there is nothing in the staff memos to suggest they considered the full scope of the market very carefully here. Indeed, the footnote in the lawyers’ memo presenting the traffic data is offered in support of this claim:

Vertical websites, such as comparison shopping and local websites, are heavily dependent on Google’s web search results to reach users. Thus, Google is in the unique position of being able to “make or break any web-based business.”

It’s plausible that vertical search traffic is “heavily dependent” on Google Search, but the numbers offered in support of that simply ignore the (then) 40 percent of traffic that Yelp acquired through its own mobile app, with no Google involvement at all. In any case, it is also notable that, while there are still somewhat fewer app users than web users (although the number has consistently increased), Yelp’s app users view significantly more pages than its website users do — 10 times as many in 2015, for example.

Also noteworthy is that, for whatever speculative harm Google might be able to visit on the company, at the time of the FTC’s analysis Yelp’s local ad revenue was consistently increasing — by 89% in Q3 2012. And that was without any ad revenue coming from its app (display ads arrived on Yelp’s mobile app in Q1 2013, a few months after the staff memos were written and just after the FTC closed its Google Search investigation). 

In short, the search-engine industry is extremely dynamic and unpredictable. Contrary to what many have surmised from the FTC staff memo leaks, this cuts against antitrust intervention, not in favor of it.

The FTC Lawyers’ Weak Case for Prosecuting Google

At the same time, although not discussed by Politico, the lawyers’ memo also contains errors, suggesting that arguments for intervention were also (inevitably) subject to erroneous prediction.

Among other things, the FTC attorneys’ memo argued the large upfront investments were required to develop cutting-edge algorithms, and that these effectively shielded Google from competition. The memo cites the following as a barrier to entry:

A search engine requires algorithmic technology that enables it to search the Internet, retrieve and organize information, index billions of regularly changing web pages, and return relevant results instantaneously that satisfy the consumer’s inquiry. Developing such algorithms requires highly specialized personnel with high levels of training and knowledge in engineering, economics, mathematics, sciences, and statistical analysis.

If there are barriers to entry in the search-engine industry, algorithms do not seem to be the source. While their market shares may be smaller than Google’s, rival search engines like DuckDuckGo and Bing have been able to enter and gain traction; it is difficult to say that algorithmic technology has proven a barrier to entry. It may be hard to do well, but it certainly has not proved an impediment to new firms entering and developing workable and successful products. Indeed, some extremely successful companies have entered into similar advertising markets on the backs of complex algorithms, notably Instagram, Snapchat, and TikTok. All of these compete with Google for advertising dollars.

The FTC’s legal staff also failed to see that Google would face serious competition in the rapidly growing voice assistant market. In other words, even its search-engine “moat” is far less impregnable than it might at first appear.

Moreover, as Ben Thompson argues in his Stratechery newsletter: 

The Staff memo is completely wrong too, at least in terms of the potential for their proposed remedies to lead to any real change in today’s market. This gets back to why the fundamental premise of the Politico article, along with much of the antitrust chatter in Washington, misses the point: Google is dominant because consumers like it.

This difficulty was deftly highlighted by Heyer’s memo:

If the perceived problems here can be solved only through a draconian remedy of this sort, or perhaps through a remedy that eliminates Google’s legitimately obtained market power (and thus its ability to “do evil”), I believe the remedy would be disproportionate to the violation and that its costs would likely exceed its benefits. Conversely, if a remedy well short of this seems likely to prove ineffective, a remedy would be undesirable for that reason. In brief, I do not see a feasible remedy for the vertical conduct that would be both appropriate and effective, and which would not also be very costly to implement and to police. [EMPHASIS ADDED]

Of course, we now know that this turned out to be a huge issue with the EU’s competition cases against Google. The remedies in both the EU’s Google Shopping and Android decisions were severely criticized by rival firms and consumer-defense organizations (here and here), but were ultimately upheld, in part because even the European Commission likely saw more forceful alternatives as disproportionate.

And in the few places where the legal staff concluded that Google’s conduct may have caused harm, there is good reason to think that their analysis was flawed.

Google’s ‘revenue-sharing’ agreements

It should be noted that neither the lawyers nor the economists at the FTC were particularly bullish on bringing suit against Google. In most areas of the investigation, neither recommended that the commission pursue a case. But one of the most interesting revelations from the recent leaks is that FTC lawyers did advise the commission’s leadership to sue Google over revenue-sharing agreements that called for it to pay Apple and other carriers and manufacturers to pre-install its search bar on mobile devices:

FTC staff urged the agency’s five commissioners to sue Google for signing exclusive contracts with Apple and the major wireless carriers that made sure the company’s search engine came pre-installed on smartphones.

The lawyers’ stance is surprising, and, despite actions subsequently brought by the EU and DOJ on similar claims, a difficult one to countenance. 

To a first approximation, this behavior is precisely what antitrust law seeks to promote: we want companies to compete aggressively to attract consumers. This conclusion is in no way altered when competition is “for the market” (in this case, firms bidding for exclusive placement of their search engines) rather than “in the market” (i.e., equally placed search engines competing for eyeballs).

Competition for exclusive placement has several important benefits. For a start, revenue-sharing agreements effectively subsidize consumers’ mobile device purchases. As Brian Albrecht aptly puts it:

This payment from Google means that Apple can lower its price to better compete for consumers. This is standard; some of the payment from Google to Apple will be passed through to consumers in the form of lower prices.

This finding is not new. For instance, Ronald Coase famously argued that the Federal Communications Commission (FCC) was wrong to ban the broadcasting industry’s equivalent of revenue-sharing agreements, so-called payola:

[I]f the playing of a record by a radio station increases the sales of that record, it is both natural and desirable that there should be a charge for this. If this is not done by the station and payola is not allowed, it is inevitable that more resources will be employed in the production and distribution of records, without any gain to consumers, with the result that the real income of the community will tend to decline. In addition, the prohibition of payola may result in worse record programs, will tend to lessen competition, and will involve additional expenditures for regulation. The gain which the ban is thought to bring is to make the purchasing decisions of record buyers more efficient by eliminating “deception.” It seems improbable to me that this problematical gain will offset the undoubted losses which flow from the ban on Payola.

Applying this logic to Google Search, it is clear that a ban on revenue-sharing agreements would merely lead both Google and its competitors to attract consumers via alternative means. For Google, this might involve “complete” vertical integration into the mobile phone market, rather than the open-licensing model that underpins the Android ecosystem. Valuable specialization may be lost in the process.

Moreover, from Apple’s standpoint, Google’s revenue-sharing agreements are profitable only to the extent that consumers actually like Google’s products. If it turns out they don’t, Google’s payments to Apple may be outweighed by lower iPhone sales. It is thus unlikely that these agreements significantly undermined users’ experience. To the contrary, Apple’s testimony before the European Commission suggests that “exclusive” placement of Google’s search engine was mostly driven by consumer preferences (as the FTC economists’ memo points out):

Apple would not offer simultaneous installation of competing search or mapping applications. Apple’s focus is offering its customers the best products out of the box while allowing them to make choices after purchase. In many countries, Google offers the best product or service … Apple believes that offering additional search boxes on its web browsing software would confuse users and detract from Safari’s aesthetic. Too many choices lead to consumer confusion and greatly affect the ‘out of the box’ experience of Apple products.

Similarly, Kevin Murphy and Benjamin Klein have shown that exclusive contracts intensify competition for distribution. In other words, absent theories of platform envelopment that are arguably inapplicable here, competition for exclusive placement would lead competing search engines to up their bids, ultimately lowering the price of mobile devices for consumers.

Indeed, this revenue-sharing model was likely essential to spur the development of Android in the first place. Without this prominent placement of Google Search on Android devices (notably thanks to revenue-sharing agreements with original equipment manufacturers), Google would likely have been unable to monetize the investment it made in the open source—and thus freely distributed—Android operating system. 

In short, Politico and the FTC legal staff do little to show that Google’s revenue-sharing payments excluded rivals that were, in fact, as efficient. In other words, Bing and Yahoo’s failure to gain traction may simply be the result of inferior products and cost structures. Critics thus fail to show that Google’s behavior harmed consumers, which is the touchstone of antitrust enforcement.

Self-preferencing

Another finding critics claim as important is that FTC leadership declined to bring suit against Google for preferencing its own vertical search services (this information had already been partially leaked by the Wall Street Journal in 2015). Politico’s framing implies this was a mistake:

When Google adopted one algorithm change in 2011, rival sites saw significant drops in traffic. Amazon told the FTC that it saw a 35 percent drop in traffic from the comparison-shopping sites that used to send it customers

The focus on this claim is somewhat surprising. Even the leaked FTC legal staff memo found this theory of harm had little chance of standing up in court:

Staff has investigated whether Google has unlawfully preferenced its own content over that of rivals, while simultaneously demoting rival websites…. 

…Although it is a close call, we do not recommend that the Commission proceed on this cause of action because the case law is not favorable to our theory, which is premised on anticompetitive product design, and in any event, Google’s efficiency justifications are strong. Most importantly, Google can legitimately claim that at least part of the conduct at issue improves its product and benefits users. [EMPHASIS ADDED]

More importantly, as one of us has argued elsewhere, the underlying problem lies not with Google, but with a standard asset-specificity trap:

A content provider that makes itself dependent upon another company for distribution (or vice versa, of course) takes a significant risk. Although it may benefit from greater access to users, it places itself at the mercy of the other — or at least faces great difficulty (and great cost) adapting to unanticipated, crucial changes in distribution over which it has no control…. 

…It was entirely predictable, and should have been expected, that Google’s algorithm would evolve. It was also entirely predictable that it would evolve in ways that could diminish or even tank Foundem’s traffic. As one online marketing/SEO expert puts it: On average, Google makes about 500 algorithm changes per year. 500!….

…In the absence of an explicit agreement, should Google be required to make decisions that protect a dependent company’s “asset-specific” investments, thus encouraging others to take the same, excessive risk? 

Even if consumers happily visited rival websites when they were higher-ranked and traffic subsequently plummeted when Google updated its algorithm, that drop in traffic does not amount to evidence of misconduct. To hold otherwise would be to grant these rivals a virtual entitlement to the state of affairs that exists at any given point in time. 

Indeed, there is good reason to believe Google’s decision to favor its own content over that of other sites is procompetitive. Beyond determining and ensuring relevance, Google surely has the prerogative to compete vigorously and decide how to design its products to keep up with a changing market. In this case, that means designing, developing, and offering its own content in ways that partially displace the original “ten blue links” design of its search results page and instead offer its own answers to users’ queries.

Competitor Harm Is Not an Indicator of the Need for Intervention

Some of the other information revealed by the leak is even more tangential, such as that the FTC ignored complaints from Google’s rivals:

Amazon and Facebook privately complained to the FTC about Google’s conduct, saying their business suffered because of the company’s search bias, scraping of content from rival sites and restrictions on advertisers’ use of competing search engines. 

Amazon said it was so concerned about the prospect of Google monopolizing the search advertising business that it willingly sacrificed revenue by making ad deals aimed at keeping Microsoft’s Bing and Yahoo’s search engine afloat.

But complaints from rivals are at least as likely to stem from vigorous competition as from anticompetitive exclusion. This goes to a core principle of antitrust enforcement: antitrust law seeks to protect competition and consumer welfare, not rivals. Competition will always lead to winners and losers. Antitrust law protects this process and (at least theoretically) ensures that rivals cannot manipulate enforcers to safeguard their economic rents. 

This explains why Frank Easterbrook—in his seminal work on “The Limits of Antitrust”—argued that enforcers should be highly suspicious of complaints lodged by rivals:

Antitrust litigation is attractive as a method of raising rivals’ costs because of the asymmetrical structure of incentives…. 

…One line worth drawing is between suits by rivals and suits by consumers. Business rivals have an interest in higher prices, while consumers seek lower prices. Business rivals seek to raise the costs of production, while consumers have the opposite interest…. 

…They [antitrust enforcers] therefore should treat suits by horizontal competitors with the utmost suspicion. They should dismiss outright some categories of litigation between rivals and subject all such suits to additional scrutiny.

Google’s competitors spent millions pressuring the FTC to bring a case against the company. But why should it be a failing for the FTC to resist such pressure? Indeed, as then-commissioner Tom Rosch admonished in an interview following the closing of the case:

They [Google’s competitors] can darn well bring [a case] as a private antitrust action if they think their ox is being gored instead of free-riding on the government to achieve the same result.

Not that they would likely win such a case. Google’s introduction of specialized shopping results (via the Google Shopping box) likely enabled several retailers to bypass the Amazon platform, thus increasing competition in the retail industry. Although this may have temporarily reduced Amazon’s traffic and revenue (Amazon’s sales have grown dramatically since then), it is exactly the outcome that antitrust laws are designed to protect.

Conclusion

When all is said and done, Politico’s revelations provide a rarely glimpsed look into the complex dynamics within the FTC, which many wrongly imagine to be a monolithic agency. Put simply, the FTC’s commissioners, lawyers, and economists often disagree vehemently about the appropriate course of conduct. This is a good thing. As in many other walks of life, having a market for ideas is a sure way to foster sound decision making.

But in the final analysis, what the revelations do not show is that the FTC’s market for ideas failed consumers a decade ago when it declined to bring an antitrust suit against Google. They thus do little to cement the case for antitrust intervention—whether a decade ago, or today.

The Federal Trade Commission and 46 state attorneys general (along with the District of Columbia and the Territory of Guam) filed their long-awaited complaints against Facebook Dec. 9. The crux of the arguments in both lawsuits is that Facebook pursued a series of acquisitions over the past decade that aimed to cement its prominent position in the “personal social media networking” market. 

Make no mistake, if successfully prosecuted, these cases would represent one of the most fundamental shifts in antitrust law since passage of the Hart-Scott-Rodino Act in 1976. That law required antitrust authorities to be notified of proposed mergers and acquisitions that exceed certain value thresholds, essentially shifting the paradigm for merger enforcement from ex-post to ex-ante review.

While the prevailing paradigm does not explicitly preclude antitrust enforcers from taking a second bite of the apple via ex-post enforcement, it has created an assumption among that regulatory clearance of a merger makes subsequent antitrust proceedings extremely unlikely. 

Indeed, the very point of ex-ante merger regulations is that ex-post enforcement, notably in the form of breakups, has tremendous social costs. It can scupper economies of scale and network effects on which both consumers and firms have come to rely. Moreover, the threat of costly subsequent legal proceedings will hang over firms’ pre- and post-merger investment decisions, and may thus reduce incentives to invest.

With their complaints, the FTC and state AGs threaten to undo this status quo. Even if current antitrust law allows it, pursuing this course of action threatens to quash the implicit assumption that regulatory clearance generally shields a merger from future antitrust scrutiny. Ex-post review of mergers and acquisitions does also entail some positive features, but the Facebook complaints fail to consider these complicated trade-offs. This oversight could hamper tech and other U.S. industries.

Mergers and uncertainty

Merger decisions are probabilistic. Of the thousands of corporate acquisitions each year, only a handful end up deemed “successful.” These relatively few success stories have to pay for the duds in order to preserve the incentive to invest.

Switching from ex-ante to ex-post review enables authorities to focus their attention on the most lucrative deals. It stands to reason that they will not want to launch ex-post antitrust proceedings against bankrupt firms whose assets have already been stripped. Instead, as with the Facebook complaint, authorities are far more likely to pursue high-profile cases that boost their political capital.

This would be unproblematic if:

  1. Authorities would commit to ex-post prosecution only of anticompetitive mergers; and
  2. If parties could reasonably anticipate whether their deals would be deemed anticompetitive in the future. 

If those were the conditions, ex-post enforcement would merely reduce the incentive to partake in problematic mergers. It would leave welfare-enhancing deals unscathed. But where firms could not have ex-ante knowledge that a given deal would be deemed anticompetitive, the associated error-costs should weigh against prosecuting such mergers ex post, even if such enforcement might appear desirable. The deterrent effect that would arise from such prosecutions would be applied by the market to all mergers, including efficient ones. Put differently, authorities might get the ex-post assessment right in one case, such as the Facebook proceedings, but the bigger picture remains that they could be wrong in many other cases. Firms will perceive this threat and it may hinder their investments.

There is also reason to doubt that either of the ideal conditions for ex-post enforcement could realistically be met in practice.Ex-ante merger proceedings involve significant uncertainty. Indeed, antitrust-merger clearance decisions routinely have an impact on the merging parties’ stock prices. If management and investors knew whether their transactions would be cleared, those effects would be priced-in when a deal is announced, not when it is cleared or blocked. Indeed, if firms knew a given merger would be blocked, they would not waste their resources pursuing it. This demonstrates that ex-ante merger proceedings involve uncertainty for the merging parties.

Unless the answer is markedly different for ex-post merger reviews, authorities should proceed with caution. If parties cannot properly self-assess their deals, the threat of ex-post proceedings will weigh on pre- and post-merger investments (a breakup effectively amounts to expropriating investments that are dependent upon the divested assets). 

Furthermore, because authorities will likely focus ex-post reviews on the most lucrative deals, their incentive effects can be particularly pronounced. Parties may fear that the most successful mergers will be broken up. This could have wide-reaching effects for all merging firms that do not know whether they might become “the next Facebook.” 

Accordingly, for ex-post merger reviews to be justified, it is essential that:

  1. Their outcomes be predictable for the parties; and that 
  2. Analyzing the deals after the fact leads to better decision-making (fewer false acquittals and convictions) than ex-ante reviews would yield.

If these conditions are not in place, ex-post assessments will needlessly weigh down innovation, investment and procompetitive merger activity in the economy.

Hindsight does not disentangle efficiency from market power

So, could ex-post merger reviews be so predictable and effective as to alleviate the uncertainties described above, along with the costs they entail? 

Based on the recently filed Facebook complaints, the answer appears to be no. We simply do not know what the counterfactual to Facebook’s acquisitions of Instagram and WhatsApp would look like. Hindsight does not tell us whether Facebook’s acquisitions led to efficiencies that allowed it to thrive (a pro-competitive scenario), or whether Facebook merely used these deals to kill off competitors and maintain its monopoly (an anticompetitive scenario).

As Sam Bowman and I have argued elsewhere, when discussing the leaked emails that spurred the current proceedings and on which the complaints rely heavily:

These email exchanges may not paint a particularly positive picture of Zuckerberg’s intent in doing the merger, and it is possible that at the time they may have caused antitrust agencies to scrutinise the merger more carefully. But they do not tell us that the acquisition was ultimately harmful to consumers, or about the counterfactual of the merger being blocked. While we know that Instagram became enormously popular in the years following the merger, it is not clear that it would have been just as successful without the deal, or that Facebook and its other products would be less popular today. 

Moreover, it fails to account for the fact that Facebook had the resources to quickly scale Instagram up to a level that provided immediate benefits to an enormous number of users, instead of waiting for the app to potentially grow to such scale organically.

In fact, contrary to what some have argued, hindsight might even complicate matters (again from Sam and me):

Today’s commentators have the benefit of hindsight. This inherently biases contemporary takes on the Facebook/Instagram merger. For instance, it seems almost self-evident with hindsight that Facebook would succeed and that entry in the social media space would only occur at the fringes of existing platforms (the combined Facebook/Instagram platform) – think of the emergence of TikTok. However, at the time of the merger, such an outcome was anything but a foregone conclusion.

In other words, ex-post reviews will, by definition, focus on mergers where today’s outcomes seem preordained — when, in fact, they were probabilistic. This will skew decisions toward finding anticompetitive conduct. If authorities think that Instagram was destined to become great, they are more likely to find that Facebook’s acquisition was anticompetitive because they implicitly dismiss the idea that it was the merger itself that made Instagram great.

Authorities might also confuse correlation for causality. For instance, the state AGs’ complaint ties Facebook’s acquisitions of Instagram and WhatsApp to the degradation of these services, notably in terms of privacy and advertising loads. As the complaint lays out:

127. Following the acquisition, Facebook also degraded Instagram users’ privacy by matching Instagram and Facebook Blue accounts so that Facebook could use information that users had shared with Facebook Blue to serve ads to those users on Instagram. 

180. Facebook’s acquisition of WhatsApp thus substantially lessened competition […]. Moreover, Facebook’s subsequent degradation of the acquired firm’s privacy features reduced consumer choice by eliminating a viable, competitive, privacy-focused option

But these changes may have nothing to do with Facebook’s acquisition of these services. At the time, nearly all tech startups focused on growth over profits in their formative years. It should be no surprise that the platforms imposed higher “prices” to users after their acquisition by Facebook; they were maturing. Further monetizing their platform would have been the logical next step, even absent the mergers.

It is just as hard to determine whether post-merger developments actually harmed consumers. For example, the FTC complaint argues that Facebook stopped developing its own photo-sharing capabilities after the Instagram acquisition,which the commission cites as evidence that the deal neutralized a competitor:

98. Less than two weeks after the acquisition was announced, Mr. Zuckerberg suggested canceling or scaling back investment in Facebook’s own mobile photo app as a direct result of the Instagram deal.

But it is not obvious that Facebook or consumers would have gained anything from the duplication of R&D efforts if Facebook continued to develop its own photo-sharing app. More importantly, this discontinuation is not evidence that Instagram could have overthrown Facebook. In other words, the fact that Instagram provided better photo-sharing capabilities does necessarily imply that it could also provide a versatile platform that posed a threat to Facebook.

Finally, if Instagram’s stellar growth and photo-sharing capabilities were certain to overthrow Facebook’s monopoly, why do the plaintiffs ignore the competitive threat posed by the likes of TikTok today? Neither of the complaints makes any mention of TikTok,even though it currently has well over 1 billion monthly active users. The FTC and state AGs would have us believe that Instagram posed an existential threat to Facebook in 2012 but that Facebook faces no such threat from TikTok today. It is exceedingly unlikely that both these statements could be true, yet both are essential to the plaintiffs’ case.

Some appropriate responses

None of this is to say that ex-post review of mergers and acquisitions should be categorically out of the question. Rather, such proceedings should be initiated only with appropriate caution and consideration for their broader consequences.

When undertaking reviews of past mergers, authorities do  not necessarily need to impose remedies every time they find a merger was wrongly cleared. The findings of these ex-post reviews could simply be used to adjust existing merger thresholds and presumptions. This would effectively create a feedback loop where false acquittals lead to meaningful policy reforms in the future. 

At the very least, it may be appropriate for policymakers to set a higher bar for findings of anticompetitive harm and imposition of remedies in such cases. This would reduce the undesirable deterrent effects that such reviews may otherwise entail, while reserving ex-post remedies for the most problematic cases.

Finally, a tougher system of ex-post review could be used to allow authorities to take more risks during ex-ante proceedings. Indeed, when in doubt, they could effectively  experiment by allowing  marginal mergers to proceed, with the understanding that bad decisions could be clawed back afterwards. In that regard, it might also be useful to set precise deadlines for such reviews and to outline the types of concerns that might prompt scrutiny  or warrant divestitures.

In short, some form of ex-post review may well be desirable. It could help antitrust authorities to learn what works and subsequently to make useful changes to ex-ante merger-review systems. But this would necessitate deep reflection on the many ramifications of ex-post reassessments. Legislative reform or, at the least, publication of guidance documents by authorities, seem like essential first steps. 

Unfortunately, this is the exact opposite of what the Facebook proceedings would achieve. Plaintiffs have chosen to ignore these complex trade-offs in pursuit of a case with extremely dubious underlying merits. Success for the plaintiffs would thus prove a pyrrhic victory, destroying far more than it intends to achieve.

[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.

This week the Senate will hold a hearing into potential anticompetitive conduct by Google in its display advertising business—the “stack” of products that it offers to advertisers seeking to place display ads on third-party websites. It is also widely reported that the Department of Justice is preparing a lawsuit against Google that will likely include allegations of anticompetitive behavior in this market, and is likely to be joined by a number of state attorneys general in that lawsuit. Meanwhile, several papers have been published detailing these allegations

This aspect of digital advertising can be incredibly complex and difficult to understand. Here we explain how display advertising fits in the broader digital advertising market, describe how display advertising works, consider the main allegations against Google, and explain why Google’s critics are misguided to focus on antitrust as a solution to alleged problems in the market (even if those allegations turn out to be correct).

Display advertising in context

Over the past decade, the price of advertising has fallen steadily while output has risen. Spending on digital advertising in the US grew from $26 billion in 2010 to nearly $130 billion in 2019, an average increase of 20% a year. Over the same period the Producer Price Index for Internet advertising sales declined by nearly 40%. The rising spending in the face of falling prices indicates the number of ads bought and sold increased by approximately 27% a year. Since 2000, advertising spending has been falling as a share of GDP, with online advertising growing as a share of that. The combination of increasing quantity, decreasing cost, and increasing total revenues are consistent with a growing and increasingly competitive market.

Display advertising on third-party websites is only a small subsection of the digital advertising market, comprising approximately 15-20% of digital advertising spending in the US. The rest of the digital advertising market is made up of ads on search results pages on sites like Google, Amazon and Kayak, on people’s Instagram and Facebook feeds, listings on sites like Zillow (for houses) or Craigslist, referral fees paid to price comparison websites for things like health insurance, audio and visual ads on services like Spotify and Hulu, and sponsored content from influencers and bloggers who will promote products to their fans. 

And digital advertising itself is only one of many channels through which companies can market their products. About 53% of total advertising spending in the United States goes on digital channels, with 30% going on TV advertising and the rest on things like radio ads, billboards and other more traditional forms of advertising. A few people still even read physical newspapers and the ads they contain, although physical newspapers’ bigger money makers have traditionally been classified ads, which have been replaced by less costly and more effective internet classifieds, such as those offered by Craigslist, or targeted ads on Google Maps or Facebook.

Indeed, it should be noted that advertising itself is only part of the larger marketing market of which non-advertising marketing communication—e.g., events, sales promotion, direct marketing, telemarketing, product placement—is as big a part as is advertising (each is roughly $500bn globally); it just hasn’t been as thoroughly disrupted by the Internet yet. But it is a mistake to assume that digital advertising is not a part of this broader market. And of that $1tr global market, Internet advertising in total occupies only about 18%—and thus display advertising only about 3%.

Ad placement is only one part of the cost of digital advertising. An advertiser trying to persuade people to buy its product must also do market research and analytics to find out who its target market is and what they want. Moreover, there are the costs of designing and managing a marketing campaign and additional costs to analyze and evaluate the effectiveness of the campaign. 

Nevertheless, one of the most straightforward ways to earn money from a website is to show ads to readers alongside the publisher’s content. To satisfy publishers’ demand for advertising revenues, many services have arisen to automate and simplify the placement of and payment for ad space on publishers’ websites. Google plays a large role in providing these services—what is referred to as “open display” advertising. And it is Google’s substantial role in this space that has sparked speculation and concern among antitrust watchdogs and enforcement authorities.

Before delving into the open display advertising market, a quick note about terms. In these discussions, “advertisers” are businesses that are trying to sell people stuff. Advertisers include large firms such as Best Buy and Disney and small businesses like the local plumber or financial adviser. “Publishers” are websites that carry those ads, and publish content that users want to read. Note that the term “publisher” refers to all websites regardless of the things they’re carrying: a blog about the best way to clean stains out of household appliances is a “publisher” just as much as the New York Times is. 

Under this broad definition, Facebook, Instagram, and YouTube are also considered publishers. In their role as publishers, they have a common goal: to provide content that attracts users to their pages who will act on the advertising displayed. “Users” are you and me—the people who want to read publishers’ content, and to whom advertisers want to show ads. Finally, “intermediaries” are the digital businesses, like Google, that sit in between the advertisers and the publishers, allowing them to do business with each other without ever meeting or speaking.

The display advertising market

If you’re an advertiser, display advertising works like this: your company—one that sells shoes, let’s say—wants to reach a certain kind of person and tell her about the company’s shoes. These shoes are comfortable, stylish, and inexpensive. You use a tool like Google Ads (or, if it’s a big company and you want a more expansive campaign over which you have more control, Google Marketing Platform) to design and upload an ad, and tell Google about the people you want to read—their age and location, say, and/or characterizations of their past browsing and searching habits (“interested in sports”). 

Using that information, Google finds ad space on websites whose audiences match the people you want to target. This ad space is auctioned off to the highest bidder among the range of companies vying, with your shoe company, to reach users matching the characteristics of the website’s users. Thanks to tracking data, it doesn’t just have to be sports-relevant websites: as a user browses sports-related sites on the web, her browser picks up files (cookies) that will tag her as someone potentially interested in sports apparel for targeting later.

So a user might look at a sports website and then later go to a recipe blog, and there receive the shoes ad on the basis of her earlier browsing. You, the shoe seller, hope that she will either click through and buy (or at least consider buying) the shoes when she sees those ads, but one of the benefits of display advertising over search advertising is that—as with TV ads or billboard ads—just seeing the ad will make her aware of the product and potentially more likely to buy it later. Advertisers thus sometimes pay on the basis of clicks, sometimes on the basis of views, and sometimes on the basis of conversion (when a consumer takes an action of some sort, such as making a purchase or filling out a form).

That’s the advertiser’s perspective. From the publisher’s perspective—the owner of that recipe blog, let’s say—you want to auction ad space off to advertisers like that shoe company. In that case, you go to an ad server—Google’s product is called AdSense—give them a little bit of information about your site, and add some html code to your website. These ad servers gather information about your content (e.g., by looking at keywords you use) and your readers (e.g., by looking at what websites they’ve used in the past to make guesses about what they’ll be interested in) and places relevant ads next to and among your content. If they click, lucky you—you’ll get paid a few cents or dollars. 

Apart from privacy concerns about the tracking of users, the really tricky and controversial part here concerns the way scarce advertising space is allocated. Most of the time, it’s done through auctions that happen in real time: each time a user loads a website, an auction is held in a fraction of a second to decide which advertiser gets to display an ad. The longer this process takes, the slower pages load and the more likely users are to get frustrated and go somewhere else.

As well as the service hosting the auction, there are lots of little functions that different companies perform that make the auction and placement process smoother. Some fear that by offering a very popular product integrated end to end, Google’s “stack” of advertising products can bias auctions in favour of its own products. There’s also speculation that Google’s product is so tightly integrated and so effective at using data to match users and advertisers that it is not viable for smaller rivals to compete.

We’ll discuss this speculation and fear in more detail below. But it’s worth bearing in mind that this kind of real-time bidding for ad placement was not always the norm, and is not the only way that websites display ads to their users even today. Big advertisers and websites often deal with each other directly. As with, say, TV advertising, large companies advertising often have a good idea about the people they want to reach. And big publishers (like popular news websites) often have a good idea about who their readers are. For example, big brands often want to push a message to a large number of people across different customer types as part of a broader ad campaign. 

Of these kinds of direct sales, sometimes the space is bought outright, in advance, and reserved for those advertisers. In most cases, direct sales are run through limited, intermediated auction services that are not open to the general market. Put together, these kinds of direct ad buys account for close to 70% of total US display advertising spending. The remainder—the stuff that’s left over after these kinds of sales have been done—is typically sold through the real-time, open display auctions described above.

Different adtech products compete on their ability to target customers effectively, to serve ads quickly (since any delay in the auction and ad placement process slows down page load times for users), and to do so inexpensively. All else equal (including the effectiveness of the ad placement), advertisers want to pay the lowest possible price to place an ad. Similarly, publishers want to receive the highest possible price to display an ad. As a result, both advertisers and publishers have a keen interest in reducing the intermediary’s “take” of the ad spending.

This is all a simplification of how the market works. There is not one single auction house for ad space—in practice, many advertisers and publishers end up having to use lots of different auctions to find the best price. As the market evolved to reach this state from the early days of direct ad buys, new functions that added efficiency to the market emerged. 

In the early years of ad display auctions, individual processes in the stack were performed by numerous competing companies. Through a process of “vertical integration” some companies, such as Google, brought these different processes under the same roof, with the expectation that integration would streamline the stack and make the selling and placement of ads more efficient and effective. The process of vertical integration in pursuit of efficiency has led to a more consolidated market in which Google is the largest player, offering simple, integrated ad buying products to advertisers and ad selling products to publishers. 

Google is by no means the only integrated adtech service provider, however: Facebook, Amazon, Verizon, AT&T/Xandr, theTradeDesk, LumenAd, Taboola and others also provide end-to-end adtech services. But, in the market for open auction placement on third-party websites, Google is the biggest.

The cases against Google

The UK’s Competition and Markets Authority (CMA) carried out a formal study into the digital advertising market between 2019 and 2020, issuing its final report in July of this year. Although also encompassing Google’s Search advertising business and Facebook’s display advertising business (both of which relate to ads on those companies “owned and operated” websites and apps), the CMA study involved the most detailed independent review of Google’s open display advertising business to date. 

That study did not lead to any competition enforcement proceedings, but it did conclude that Google’s vertically integrated products led to conflicts of interest that could lead it to behaving in ways that did not benefit the advertisers and publishers that use it. One example was Google’s withholding of certain data from publishers that would make it easier for them to use other ad selling products; another was the practice of setting price floors that allegedly led advertisers to pay more than they would otherwise.

Instead the CMA recommended the setting up of a “Digital Markets Unit” (DMU) that could regulate digital markets in general, and a code of conduct for Google and Facebook (and perhaps other large tech platforms) intended to govern their dealings with smaller customers.

The CMA’s analysis is flawed, however. For instance, it makes big assumptions about the dependency of advertisers on display advertising, largely assuming that they would not switch to other forms of advertising if prices rose, and it is light on economics. But factually it is the most comprehensively researched investigation into digital advertising yet published.

Piggybacking on the CMA’s research, and mounting perhaps the strongest attack on Google’s adtech offerings to date, was a paper released just prior to the CMA’s final report called “Roadmap for a Digital Advertising Monopolization Case Against Google”, by Yale economist Fiona Scott Morton and Omidyar Network lawyer David Dinielli. Dinielli will testify before the Senate committee.

While the Scott Morton and Dinielli paper is extremely broad, it also suffers from a number of problems. 

One, because it was released before the CMA’s final report, it is largely based on the interim report released months earlier by the CMA, halfway through the market study in December 2019. This means that several of its claims are out of date. For example, it makes much of the possibility raised by the CMA in its interim report that Google may take a larger cut of advertising spending than its competitors, and claims made in another report that Google introduces “hidden” fees that increases the overall cut it takes from ad auctions. 

But in the final report, after further investigation, the CMA concludes that this is not the case. In the final report, the CMA describes its analysis of all Google Ad Manager open auctions related to UK web traffic during the period between 8–14 March 2020 (involving billions of auctions). This, according to the CMA, allowed it to observe any possible “hidden” fees as well. The CMA concludes:

Our analysis found that, in transactions where both Google Ads and Ad Manager (AdX) are used, Google’s overall take rate is approximately 30% of advertisers’ spend. This is broadly in line with (or slightly lower than) our aggregate market-wide fee estimate outlined above. We also calculated the margin between the winning bid and the second highest bid in AdX for Google and non-Google DSPs, to test whether Google was systematically able to win with a lower margin over the second highest bid (which might have indicated that they were able to use their data advantage to extract additional hidden fees). We found that Google’s average winning margin was similar to that of non-Google DSPs. Overall, this evidence does not indicate that Google is currently extracting significant hidden fees. As noted below, however, it retains the ability and incentive to do so. (p. 275, emphasis added)

Scott Morton and Dinielli also misquote and/or misunderstand important sections of the CMA interim report as relating to display advertising when, in fact, they relate to search. For example, Scott Morton and Dinielli write that the “CMA concluded that Google has nearly insurmountable advantages in access to location data, due to the location information [uniquely available to it from other sources].” (p. 15). The CMA never makes any claim of “insurmountable advantage,” however. Rather, to support the claim, Scott Morton and Dinielli cite to a portion of the CMA interim report recounting a suggestion made by Microsoft regarding the “critical” value of location data in providing relevant advertising. 

But that portion of the report, as well as the suggestion made by Microsoft, is about search advertising. While location data may also be valuable for display advertising, it is not clear that the GPS-level data that is so valuable in providing mobile search ad listings (for a nearby cafe or restaurant, say) is particularly useful for display advertising, which may be just as well-targeted by less granular, city- or county-level location data, which is readily available from a number of sources. In any case, Scott Morton and Dinielli are simply wrong to use a suggestion offered by Microsoft relating to search advertising to demonstrate the veracity of an assertion about a conclusion drawn by the CMA regarding display advertising. 

Scott Morton and Dinielli also confusingly word their own judgements about Google’s conduct in ways that could be misinterpreted as conclusions by the CMA:

The CMA reports that Google has implemented an anticompetitive sales strategy on the publisher ad server end of the intermediation chain. Specifically, after purchasing DoubleClick, which became its publisher ad server, Google apparently lowered its prices to publishers by a factor of ten, at least according to one publisher’s account related to the CMA. (p. 20)

In fact, the CMA does not conclude that Google lowering its prices was an “anticompetitive sales strategy”—it does not use these words at all—and what Scott Morton and Dinielli are referring to is a claim by a rival ad server business, Smart, that Google cutting its prices after acquiring Doubleclick led to Google expanding its market share. Apart from the misleading wording, it is unclear why a competition authority should consider it to be “anticompetitive” when prices are falling and kept low, and—as Smart reported to the CMA—its competitor’s response is to enhance its own offering. 

The case that remains

Stripping away the elements of Scott Morton and Dinielli’s case that seem unsubstantiated by a more careful reading of the CMA reports, and with the benefit of the findings in the CMA’s final report, we are left with a case that argues that Google self-preferences to an unreasonable extent, giving itself a product that is as successful as it is in display advertising only because of Google’s unique ability to gain advantage from its other products that have little to do with display advertising. Because of this self-preferencing, they might argue, innovative new entrants cannot compete on an equal footing, so the market loses out on incremental competition because of the advantages Google gets from being the world’s biggest search company, owning YouTube, running Google Maps and Google Cloud, and so on. 

The most significant examples of this are Google’s use of data from other products—like location data from Maps or viewing history from YouTube—to target ads more effectively; its ability to enable advertisers placing search ads to easily place display ads through the same interface; its introduction of faster and more efficient auction processes that sidestep the existing tools developed by other third-party ad exchanges; and its design of its own tool (“open bidding”) for aggregating auction bids for advertising space to compete with (rather than incorporate) an alternative tool (“header bidding”) that is arguably faster, but costs more money to use.

These allegations require detailed consideration, and in a future paper we will attempt to assess them in detail. But in thinking about them now it may be useful to consider the remedies that could be imposed to address them, assuming they do diminish the ability of rivals to compete with Google: what possible interventions we could make in order to make the market work better for advertisers, publishers, and users. 

We can think of remedies as falling into two broad buckets: remedies that stop Google from doing things that improve the quality of its own offerings, thus making it harder for others to keep up; and remedies that require it to help rivals improve their products in ways otherwise accessible only to Google (e.g., by making Google’s products interoperable with third-party services) without inherently diminishing the quality of Google’s own products.

The first camp of these, what we might call “status quo minus,” includes rules banning Google from using data from its other products or offering single order forms for advertisers, or, in the extreme, a structural remedy that “breaks up” Google by either forcing it to sell off its display ad business altogether or to sell off elements of it. 

What is striking about these kinds of interventions is that all of them “work” by making Google worse for those that use it. Restrictions on Google’s ability to use data from other products, for example, will make its service more expensive and less effective for those who use it. Ads will be less well-targeted and therefore less effective. This will lead to lower bids from advertisers. Lower ad prices will be transmitted through the auction process to produce lower payments for publishers. Reduced publisher revenues will mean some content providers exit. Users will thus be confronted with less available content and ads that are less relevant to them and thus, presumably, more annoying. In other words: No one will be better off, and most likely everyone will be worse off.

The reason a “single order form” helps Google is that it is useful to advertisers, the same way it’s useful to be able to buy all your groceries at one store instead of lots of different ones. Similarly, vertical integration in the “ad stack” allows for a faster, cheaper, and simpler product for users on all sides of the market. A different kind of integration that has been criticized by others, where third-party intermediaries can bid more quickly if they host on Google Cloud, benefits publishers and users because it speeds up auction time, allowing websites to load faster. So does Google’s unified alternative to “header bidding,” giving a speed boost that is apparently valuable enough to publishers that they will pay for it.

So who would benefit from stopping Google from doing these things, or even forcing Google to sell its operations in this area? Not advertisers or publishers. Maybe Google’s rival ad intermediaries would; presumably, artificially hamstringing Google’s products would make it easier for them to compete with Google. But if so, it’s difficult to see how this would be an overall improvement. It is even harder to see how this would improve the competitive process—the very goal of antitrust. Rather, any increase in the competitiveness of rivals would result not from making their products better, but from making Google’s product worse. That is a weakening of competition, not its promotion. 

On the other hand, interventions that aim to make Google’s products more interoperable at least do not fall prey to this problem. Such “status quo plus” interventions would aim to take the benefits of Google’s products and innovations and allow more companies to use them to improve their own competing products. Not surprisingly, such interventions would be more in line with the conclusions the CMA came to than the divestitures and operating restrictions proposed by Scott Morton and Dinielli, as well as (reportedly) state attorneys general considering a case against Google.

But mandated interoperability raises a host of different concerns: extensive and uncertain rulemaking, ongoing regulatory oversight, and, likely, price controls, all of which would limit Google’s ability to experiment with and improve its products. The history of such mandated duties to deal or compulsory licenses is a troubled one, at best. But even if, for the sake of argument, we concluded that these kinds of remedies were desirable, they are difficult to impose via an antitrust lawsuit of the kind that the Department of Justice is expected to launch. Most importantly, if the conclusion of Google’s critics is that Google’s main offense is offering a product that is just too good to compete with without regulating it like a utility, with all the costs to innovation that that would entail, maybe we ought to think twice about whether an antitrust intervention is really worth it at all.

Recently-published emails from 2012 between Mark Zuckerberg and Facebook’s then-Chief Financial Officer David Ebersman, in which Zuckerberg lays out his rationale for buying Instagram, have prompted many to speculate that the deal may not have been cleared had antitrust agencies had had access to Facebook’s internal documents at the time.

The issue is Zuckerberg’s description of Instagram as a nascent competitor and potential threat to Facebook:

These businesses are nascent but the networks established, the brands are already meaningful, and if they grow to a large scale they could be very disruptive to us. Given that we think our own valuation is fairly aggressive and that we’re vulnerable in mobile, I’m curious if we should consider going after one or two of them. 

Ebersman objects that a new rival would just enter the market if Facebook bought Instagram. In response, Zuckerberg wrote:

There are network effects around social products and a finite number of different social mechanics to invent. Once someone wins at a specific mechanic, it’s difficult for others to supplant them without doing something different.

These email exchanges may not paint a particularly positive picture of Zuckerberg’s intent in doing the merger, and it is possible that at the time they may have caused antitrust agencies to scrutinise the merger more carefully. But they do not tell us that the acquisition was ultimately harmful to consumers, or about the counterfactual of the merger being blocked. While we know that Instagram became enormously popular in the years following the merger, it is not clear that it would have been just as successful without the deal, or that Facebook and its other products would be less popular today. 

Moreover, it fails to account for the fact that Facebook had the resources to quickly scale Instagram up to a level that provided immediate benefits to an enormous number of users, instead of waiting for the app to potentially grow to such scale organically. 

The rationale

Writing for Pro Market, Randy Picker argued that these emails hint that the acquisition was essentially about taking out a nascent competitor:

Buying Instagram really was about controlling the window in which the Instagram social mechanic invention posed a risk to Facebook … Facebook well understood the competitive risk posed by Instagram and how purchasing it would control that risk.

This is a plausible interpretation of the internal emails, although there are others. For instance, Zuckerberg also seems to say that the purpose is to use Instagram to improve Facebook to make it good enough to fend off other entrants:

If we incorporate the social mechanics they were using, those new products won’t get much traction since we’ll already have their mechanics deployed at scale. 

If this was the rationale, rather than simply trying to kill a nascent competitor, it would be pro-competitive. It is good for consumers if a product makes itself better to beat its rivals by acquiring undervalued assets to deploy them at greater scale and with superior managerial efficiency, even if the acquirer hopes that in doing so it will prevent rivals from ever gaining significant market share. 

Further, despite popular characterization, on its face the acquisition was not about trying to destroy a consumer option, but only to ensure that Facebook was competitively viable in providing that option. Another reasonable interpretation of the emails is that Facebook was wrestling with the age-old make-or-buy dilemma faced by every firm at some point or another. 

Was the merger anticompetitive?

But let us assume that eliminating competition from Instagram was indeed the merger’s sole rationale. Would that necessarily make it anticompetitive?  

Chief among the objections is that both Facebook and Instagram are networked goods. Their value to each user depends, to a significant extent, on the number (and quality) of other people using the same platform. Many scholars have argued that this can create self-reinforcing dynamics where the strong grow stronger – though such an outcome is certainly not a given, since other factors about the service matter too, and networks can suffer from diseconomies of scale as well, where new users reduce the quality of the network.

This network effects point is central to the reasoning of those who oppose the merger: Facebook purportedly acquired Instagram because Instagram’s network had grown large enough to be a threat. With Instagram out of the picture, Facebook could thus take on the remaining smaller rivals with the advantage of its own much larger installed base of users. 

However, this network tipping argument could cut both ways. It is plausible that the proper counterfactual was not duopoly competition between Facebook and Instagram, but either Facebook or Instagram offering both firms’ features (only later). In other words, a possible framing of the merger is that it merely  accelerated the cross-pollination of social mechanics between Facebook and Instagram. Something that would likely prove beneficial to consumers.

This finds some support in Mark Zuckerberg’s reply to David Ebersman:

Buying them would give us the people and time to integrate their innovations into our core products.

The exchange between Zuckerberg and Ebersman also suggests another pro-competitive justification: bringing Instagram’s “social mechanics” to Facebook’s much larger network of users. We can only speculate about what ‘social mechanics’ Zuckerberg actually had in mind, but at the time Facebook’s photo sharing functionality was largely based around albums of unedited photos, whereas Instagram’s core product was a stream of filtered, cropped single images. 

Zuckerberg’s plan to gradually bring these features to Facebook’s users – as opposed to them having to familiarize themselves with an entirely different platform – would likely cut in favor of the deal being cleared by enforcers.

Another possibility is that it was Instagram’s network of creators – the people who had begun to use Instagram as a new medium, distinct from the generic photo albums Facebook had, and who would eventually grow to be known as ‘influencers’ – who were the valuable thing. Bringing them onto the Facebook platform would undoubtedly increase its value to regular users. For example, Kim Kardashian, one of Instagram’s most popular users, joined the service in February 2012, two months before the deal went through, and she was not the first such person to adopt Instagram in this way. We can see the importance of a service’s most creative users today, as Facebook is actually trying to pay TikTok creators to move to its TikTok clone Reels.

But if this was indeed the rationale, not only is this a sign of a company in the midst of fierce competition – rather than one on the cusp of acquiring a monopoly position – but, more fundamentally, it suggests that Facebook was always going to come out on top. Or at least it thought so.

The benefit of hindsight

Today’s commentators have the benefit of hindsight. This inherently biases contemporary takes on the Facebook/Instagram merger. For instance, it seems almost self-evident with hindsight that Facebook would succeed and that entry in the social media space would only occur at the fringes of existing platforms (the combined Facebook/Instagram platform) – think of the emergence of TikTok. However, at the time of the merger, such an outcome was anything but a foregone conclusion.

For instance, critics argue that Instagram no longer competes with Facebook because of the merger. However, it is equally plausible that Instagram only became so successful because of its combination with Facebook (notably thanks to the addition of Facebook’s advertising platform, and the rapid rollout of a stories feature in response to Snapchat’s rise). Indeed, Instagram grew from roughly 24 million at the time of the acquisition to over 1 Billion users in 2018. Likewise, it earned zero revenue at the time of the merger. This might explain why the acquisition was widely derided at the time.

This is critical from an antitrust perspective. Antitrust enforcers adjudicate merger proceedings in the face of extreme uncertainty. All possible outcomes, including the counterfactual setting, have certain probabilities of being true that enforcers and courts have to make educated guesses about, assigning probabilities to potential anticompetitive harms, merger efficiencies, and so on.

Authorities at the time of the merger could not ignore these uncertainties. What was the likelihood that a company with a fraction of Facebook’s users (24 million to Facebook’s 1 billion), and worth $1 billion, could grow to threaten Facebook’s market position? At the time, the answer seemed to be “very unlikely”. Moreover, how could authorities know that Google+ (Facebook’s strongest competitor at the time) would fail? These outcomes were not just hard to ascertain, they were simply unknowable.

Of course, this is preceisly what neo-Brandesian antitrust scholars object to today: among the many seemingly innocuous big tech acquisitions that are permitted each year, there is bound to be at least one acquired firm that might have been a future disruptor. True as this may be, identifying that one successful company among all the others is the antitrust equivalent of finding a needle in a haystack. Instagram simply did not fit that description at the time of the merger. Such a stance also ignores the very real benefits that may arise from such arrangements.

Closing remarks

While it is tempting to reassess the Facebook Instagram merger in light of new revelations, such an undertaking is not without pitfalls. Hindsight bias is perhaps the most obvious, but the difficulties run deeper.

If we think that the Facebook/Instagram merger has been and will continue to be good for consumers, it would be strange to think that we should nevertheless break them up because we discovered that Zuckerberg had intended to do things that would harm consumers. Conversely, if you think a breakup would be good for consumers today, would it change your mind if you discovered that Mark Zuckerberg had the intentions of an angel when he went ahead with the merger in 2012, or that he had angelic intent today?

Ultimately, merger review involves making predictions about the future. While it may be reasonable to take the intentions of the merging parties into consideration when making those predictions (although it’s not obvious that we should), these are not the only or best ways to determine what the future will hold. As Ebersman himself points out in the emails, history is filled with over-optimistic mergers that failed to deliver benefits to the merging parties. That this one succeeded beyond the wildest dreams of everyone involved – except maybe Mark Zuckerberg – does not tell us that competition agencies should have ruled on it differently.

During last week’s antitrust hearing, Representative Jamie Raskin (D-Md.) provided a sound bite that served as a salvo: “In the 19th century we had the robber barons, in the 21st century we get the cyber barons.” But with sound bites, much like bumper stickers, there’s no room for nuance or scrutiny.

The news media has extensively covered the “questioning” of the CEOs of Facebook, Google, Apple, and Amazon (collectively “Big Tech”). Of course, most of this questioning was actually political posturing with little regard for the actual answers or antitrust law. But just like with the so-called robber barons, the story of Big Tech is much more interesting and complex. 

The myth of the robber barons: Market entrepreneurs vs. political entrepreneurs

The Robber Barons: The Great American Capitalists, 1861–1901 (1934) by Matthew Josephson, was written in the midst of America’s Great Depression. Josephson, a Marxist with sympathies for the Soviet Union, made the case that the 19th century titans of industry were made rich on the backs of the poor during the industrial revolution. This idea that the rich are wealthy due to their robbing of the rest of us is an idea that has long outlived Josephson and Marx down to the present day, as exemplified by the writings of Matt Stoller and the politics of the House Judiciary Committee.

In his Myth of the Robber Barons, Burton Folsom, Jr. makes the case that much of the received wisdom on the great 19th century businessmen is wrong. He distinguishes between the market entrepreneurs, which generated wealth by selling newer, better, or less expensive products on the free market without any government subsidies, and the political entrepreneurs, who became rich primarily by influencing the government to subsidize their businesses, or enacting legislation or regulation that harms their competitors. 

Folsom narrates the stories of market entrepreneurs, like Thomas Gibbons & Cornelius Vanderbilt (steamships), James Hill (railroads), the Scranton brothers (iron rails), Andrew Carnegie & Charles Schwab (steel), and John D. Rockefeller (oil), who created immense value for consumers by drastically reducing the prices of the goods and services their companies provided. Yes, these men got rich. But the value society received was arguably even greater. Wealth was created because market exchange is a positive-sum game.

On the other hand, the political entrepreneurs, like Robert Fulton & Edward Collins (steamships), and Leland Stanford & Henry Villard (railroads), drained societal resources by using taxpayer money to create inefficient monopolies. Because they were not subject to the same market discipline due to their favored position, cutting costs and prices were less important to them than the market entrepreneurs. Their wealth was at the expense of the rest of society, because political exchange is a zero-sum game.

Big Tech makes society better off

Today’s titans of industry, i.e. Big Tech, have created enormous value for society. This is almost impossible to deny, though some try. From zero-priced search on Google, to the convenience and price of products on Amazon, to the nominally free social network(s) of Facebook, to the plethora of options in Apple’s App Store, consumers have greatly benefited from Big Tech. Consumers flock to use Google, Facebook, Amazon, and Apple for a reason: they believe they are getting a great deal. 

By and large, the techlash comes from “intellectuals” who think they know better than consumers acting in the marketplace about what is good for them. And as noted by Alec Stapp, Americans in opinion polls consistently put a great deal of trust in Big Tech, at least compared to government institutions:

One of the basic building blocks of economics is that both parties benefit from voluntary exchanges ex ante, or else they would not be willing to engage in it. The fact that consumers use Big Tech to the extent they do is overwhelming evidence of their value. Obfuscations like “market power” mislead more than they inform. In the absence of governmental barriers to entry, consumers voluntarily choosing Big Tech does not mean they have power, it means they provide great service.

Big Tech companies are run by entrepreneurs who must ultimately answer to consumers. In a market economy, profits are a signal that entrepreneurs have successfully brought value to society. But they are also a signal to potential competitors. If Big Tech companies don’t continue to serve the interests of their consumers, they risk losing them to competitors.

Big Tech’s CEOs seem to get this. For instance, Jeff Bezos’ written testimony emphasized the importance of continual innovation at Amazon as a reason for its success:

Since our founding, we have strived to maintain a “Day One” mentality at the company. By that I mean approaching everything we do with the energy and entrepreneurial spirit of Day One. Even though Amazon is a large company, I have always believed that if we commit ourselves to maintaining a Day One mentality as a critical part of our DNA, we can have both the scope and capabilities of a large company and the spirit and heart of a small one. 

In my view, obsessive customer focus is by far the best way to achieve and maintain Day One vitality. Why? Because customers are always beautifully, wonderfully dissatisfied, even when they report being happy and business is great. Even when they don’t yet know it, customers want something better, and a constant desire to delight customers drives us to constantly invent on their behalf. As a result, by focusing obsessively on customers, we are internally driven to improve our services, add benefits and features, invent new products, lower prices, and speed up shipping times—before we have to. No customer ever asked Amazon to create the Prime membership program, but it sure turns out they wanted it. And I could give you many such examples. Not every business takes this customer-first approach, but we do, and it’s our greatest strength.

The economics of multi-sided platforms: How Big Tech does it

Economically speaking, Big Tech companies are (mostly) multi-sided platforms. Multi-sided platforms differ from regular firms in that they have to serve two or more of these distinct types of consumers to generate demand from any of them.

Economist David Evans, who has done as much as any to help us understand multi-sided platforms, has identified three different types:

  1. Market-Makers enable members of distinct groups to transact with each other. Each member of a group values the service more highly if there are more members of the other group, thereby increasing the likelihood of a match and reducing the time it takes to find an acceptable match. (Amazon and Apple’s App Store)
  2. Audience-Makers match advertisers to audiences. Advertisers value a service more if there are more members of an audience who will react positively to their messages; audiences value a service more if there is more useful “content” provided by audience-makers. (Google, especially through YouTube, and Facebook, especially through Instagram)
  3. Demand-Coordinators make goods and services that generate indirect network effects across two or more groups. These platforms do not strictly sell “transactions” like a market maker or “messages” like an audience-maker; they are a residual category much like irregular verbs – numerous, heterogeneous, and important. Software platforms such as Windows and the Palm OS, payment systems such as credit cards, and mobile telephones are demand coordinators. (Android, iOS)

In order to bring value, Big Tech has to consider consumers on all sides of the platform they operate. Sometimes, this means consumers on one side of the platform subsidize the other. 

For instance, Google doesn’t charge its users to use its search engine, YouTube, or Gmail. Instead, companies pay Google to advertise to their users. Similarly, Facebook doesn’t charge the users of its social network, advertisers on the other side of the platform subsidize them. 

As their competitors and critics love to point out, there are some complications in that some platforms also compete in the markets they create. For instance, Apple does place its own apps inits App Store, and Amazon does engage in some first-party sales on its platform. But generally speaking, both Apple and Amazon act as matchmakers for exchanges between users and third parties.

The difficulty for multi-sided platforms is that they need to balance the interests of each part of the platform in a way that maximizes its value. 

For Google and Facebook, they need to balance the interests of users and advertisers. In the case of each, this means a free service for users that is subsidized by the advertisers. But the advertisers gain a lot of value by tailoring ads based upon search history, browsing history, and likes and shares. For Apple and Amazon they need to create platforms which are valuable for buyers and sellers, and balance how much first-party competition they want to have before they lose the benefits of third-party sales.

There are no easy answers to creating a search engine, a video service, a social network, an App store, or an online marketplace. Everything from moderation practices, to pricing on each side of the platform, to the degree of competition from the platform operators themselves needs to be balanced right or these platforms would lose participants on one side of the platform or the other to competitors. 

Conclusion

Representative Raskin’s “cyber barons” were raked through the mud by Congress. But much like the falsely identified robber barons of the 19th century who were truly market entrepreneurs, the Big Tech companies of today are wrongfully maligned.

No one is forcing consumers to use these platforms. The incredible benefits they have brought to society through market processes shows they are not robbing anyone. Instead, they are constantly innovating and attempting to strike a balance between consumers on each side of their platform. 

The myth of the cyber barons need not live on any longer than last week’s farcical antitrust hearing.

This guest post is by Corbin K. Barthold, Senior Litigation Counsel at Washington Legal Foundation.

A boy throws a brick through a bakeshop window. He flees and is never identified. The townspeople gather around the broken glass. “Well,” one of them says to the furious baker, “at least this will generate some business for the windowmaker!”

A reasonable statement? Not really. Although it is indeed a good day for the windowmaker, the money for the new window comes from the baker. Perhaps the baker was planning to use that money to buy a new suit. Now, instead of owning a window and a suit, he owns only a window. The windowmaker’s gain, meanwhile, is simply the tailor’s loss.

This parable of the broken window was conceived by Frédéric Bastiat, a nineteenth-century French economist. He wanted to alert the reader to the importance of opportunity costs—in his words, “that which is not seen.” Time and money spent on one activity cannot be spent on another.

Today Bastiat might tell the parable of the harassed technology company. A tech firm creates a revolutionary new product or service and grows very large. Rivals, lawyers, activists, and politicians call for an antitrust probe. Eventually they get their way. Millions of documents are produced, dozens of depositions are taken, and several hearings are held. In the end no concrete action is taken. “Well,” the critics say, “at least other companies could grow while the firm was sidetracked by the investigation!”

Consider the antitrust case against Microsoft twenty years ago. The case ultimately settled, and Microsoft agreed merely to modify minor aspects of how it sold its products. “It’s worth wondering,” writes Brian McCullough, a generally astute historian of the internet, “how much the flowering of the dot-com era was enabled by the fact that the most dominant, rapacious player in the industry was distracted while the new era was taking shape.” “It’s easy to see,” McCullough says, “that the antitrust trial hobbled Microsoft strategically, and maybe even creatively.”

Should we really be glad that an antitrust dispute “distracted” and “hobbled” Microsoft? What would a focused and unfettered Microsoft have achieved? Maybe nothing; incumbents often grow complacent. Then again, Microsoft might have developed a great search engine or social-media platform. Or it might have invented something that, thanks to the lawsuit, remains absent to this day. What Microsoft would have created in the early 2000s, had it not had to fight the government, is that which is not seen.

But doesn’t obstructing the most successful companies create “room” for new competitors? David Cicilline, the chairman of the House’s antitrust subcommittee, argues that “just pursuing the [Microsoft] enforcement action itself” made “space for an enormous amount of additional innovation and competition.” He contends that the large tech firms seek to buy promising startups before they become full-grown threats, and that such purchases must be blocked.

It’s easy stuff to say. It’s not at all clear that it’s true or that it makes sense. Hindsight bias is rampant. In 2012, for example, Facebook bought Instagram for $1 billion, a purchase that is now cited as a quintessential “killer acquisition.” At the time of the sale, however, Instagram had 27 million users and $0 in revenue. Today it has around a billion users, it is estimated to generate $7 billion in revenue each quarter, and it is worth perhaps $100 billion. It is presumptuous to declare that Instagram, which had only 13 employees in 2012, could have achieved this success on its own.

If distraction is an end in itself, last week’s Big Tech hearing before Cicilline and his subcommittee was a smashing success. Presumably Jeff Bezos, Tim Cook, Sundar Pichai, and Mark Zuckerberg would like to spend the balance of their time developing the next big innovations and staying ahead of smart, capable, ruthless competitors, starting with each other and including foreign firms such as ByteDance and Huawei. Last week they had to put their aspirations aside to prepare for and attend five hours of political theater.

The most common form of exchange at the hearing ran as follows. A representative asks a slanted question. The witness begins to articulate a response. The representative cuts the witness off. The representative gives a prepared speech about how the witness’s answer proved her point.

Lucy Kay McBath, a first-term congresswoman from Georgia, began one such drill with the claim that Facebook’s privacy policy from 2004, when Zuckerberg was 20 and Facebook had under a million users, applies in perpetuity. “We do not and will not use cookies to collect private information from any users,” it said. Has Facebook broken its “promise,” McBath asked, not to use cookies to collect private information? No, Zuckerberg explained (letting the question’s shaky premise slide), Facebook uses only standard log-in cookies.

“So once again, you do not use cookies? Yes or no?” McBath interjected. Having now asked a completely different question, and gotten a response resembling what she wanted—“Yes, we use cookies [on log-in features]”—McBath could launch into her canned condemnation. “The bottom line here,” she said, reading from her page, “is that you broke a commitment to your users. And who can say whether you may or may not do that again in the future?” The representative pressed on with her performance, not noticing or not caring that the person she was pretending to engage with had upset her script.

Many of the antitrust subcommittee’s queries had nothing to do with antitrust. One representative fixated on Amazon’s ties with the Southern Poverty Law Center. Another seemed to want Facebook to interrogate job applicants about their political beliefs. A third asked Zuckerberg to answer for the conduct of Twitter. One representative demanded that social-media posts about unproven Covid-19 treatments be left up, another that they be taken down. Most of the questions that were at least vaguely on topic, meanwhile, were exceedingly weak. The representatives often mistook emails showing that tech CEOs play to win, that they seek to outcompete challengers and rivals, for evidence of anticompetitive harm to consumers. And the panel was often treated like a customer-service hotline. This app developer ran into a difficulty; what say you, Mr. Cook? That third-party seller has a gripe; why won’t you listen to her, Mr. Bezos?

In his opening remarks, Bezos cited a survey that ranked Amazon one of the country’s most trusted institutions. No surprise there. In many places one could have ordered a grocery delivery from Amazon as the hearing started and had the goods put away before it ended. Was Bezos taking a muted dig at Congress? He had every right to—it is one of America’s least trusted institutions. Pichai, for his part, noted that many users would be willing to pay thousands of dollars a year for Google’s free products. Is Congress providing people that kind of value?

The advance of technology will never be an unalloyed blessing. There are legitimate concerns, for instance, about how social-media platforms affect public discourse. “Human beings evolved to gossip, preen, manipulate, and ostracize,” psychologist Jonathan Haidt and technologist Tobias Rose-Stockwell observe. Social media exploits these tendencies, they contend, by rewarding those who trade in the glib put-down, the smug pronouncement, the theatrical smear. Speakers become “cruel and shallow”; “nuance and truth” become “casualties in [a] competition to gain the approval of [an] audience.”

Three things are true at once. First, Haidt and Rose-Stockwell have a point. Second, their point goes only so far. Social media does not force people to behave badly. Assuming otherwise lets individual humans off too easy. Indeed, it deprives them of agency. If you think it is within your power to display grace, love, and transcendence, you owe it to others to think it is within their power as well.

Third, if you really want to see adults act like children, watch a high-profile congressional hearing. A hearing for Attorney General William Barr, held the day before the Big Tech hearing and attended by many of the same representatives, was a classic of the format.

The tech hearing was not as shambolic as the Barr hearing. And the representatives act like sanctimonious halfwits in part to concoct the sick burns that attract clicks on the very platforms built, facilitated, and delivered by the tech companies. For these and other obvious reasons, no one should feel sorry for the four men who spent a Wednesday afternoon serving as props for demagogues. But that doesn’t mean the charade was a productive use of time. There is always that which is not seen.

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.

 

[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 Thomas W. Hazlett, (Hugh H. Macaulay Endowed Professor of Economics, John E. Walker Department of Economics Clemson University)

The brutal toll of the coronavirus pandemic has delivered dramatic public policies. The United States has closed institutions, banned crowds, postponed non-emergency medical procedures and instituted social distancing. All to “flatten the curve” of illness. The measures are expensive, but there is no obvious way to better save lives.

There is evidence that, even without the antivirals or vaccines we hope come soon, we are limiting the spread of COVID-19. Daily death totals for the world appear to be leveling; the most severely impacted countries, Italy and Spain, are seeing declines; the top U.S. hotspot, New York, appears to be peaking (and net new coronavirus hospital admissions fell substantially yesterday). I hope that, looking back, these inferences look reasonable.

But of course I do. Is that rational introspection, or confirmation bias? To try to know, we should look about to see how others are addressing this challenge, and how well they are doing. There are experiments being run, in real time on actual economies, and diversity of results is one of the few blessings conveyed by our coronavirus demon.

Differing approaches to mitigating externalities around the world

It strikes many as entirely off-topic to discuss the efficiency of our measures, as though only the most expensive, draconian remedies work. There is a tendency to stress how little room for optionality there exists. Exhortation seems to be the strategy. No doubt, we are confronted by a classic “public good” challenge, where individuals may impose costs on others. Not intentionally, but perhaps through actions that are short-sighted. If a neighbor fails to take “due care” they needlessly endanger others. To overcome such free riding, we “rally ‘round the flag” to condemn anti-social behavior. That is a community survival trait.

And entirely compatible with the pursuit of efficient rules. Shuttering the marketplace and freezing personal mobility imposes harsh hardships; they are, unsurprisingly, resisted. It is stunning how rapidly our Conventional Wisdom has changed, but as recently as January 29 N.Y. Times’ tech columnist Farhad Manjoo warned us to slow down, to “Beware the Pandemic Panic.” He echoed the World Health Organization’s view that the threat was meek and that we ought focus on “not the illness itself but the amped-up, ill-considered way our frightened world might respond to it.” (See Jonathan Tobin’s nice overview of the errors made, left and right, in the run-up to the lock-down. It notes Manjoo’s reversal in the Times, Feb. 26.) 

When the disease seemed less, we were reluctant to impose costs; as the threat loomed larger, we rushed to make up for lost time. We now pay the price for acting late, but without perfect foresight – our perennial state – that insight does not much help us today or prep us for tomorrow. Keen observation of more efficient ways, and robust public discussion, will. 

Sweden has adopted the hygiene and separation practices familiar to Americans. But the government has stopped short of mandates imposed elsewhere. While college courses have rolled over to the Internet, Sweden has not closed schools for students 16 and under. Bars and restaurants remain open, with gatherings up to 50 approved (the US President has asked crowds to be kept to 10 or less). Life seems almost normal to many – Americans might pay a ton for that. Still, substantial macroeconomic costs remain.  One estimate predicts a 4% decline in 2020 GDP, beating expectations for Europe but similar to U.S. forecasts (see Goldman Sachs’ March 26 report with 2020 U.S. GDP growth projection of -3.8% and -9% for European markets.) Alas, the Swedish fatality rate, population adjusted, is higher than its Scandinavian peers and (as of April 7) about one-half higher than the U.S. See Table.

 COVID-19 Fatality Rates per Million Population, Selected Countries (4.7.20)

CountryDeaths/mil.Days since 1/mil.Daily GrowthGeo. Avg. Weekly Growth/day 
USA38.6161.181.19
Italy284.3351.041.05
Spain298.2271.051.08
Czech Rep.8.2101.131.16
Sweden57.2191.241.19
Switzerland95.6251.071.10
U.K.92.9201.151.19
France154.2251.161.17
Germany24.2171.111.15
Singapore1.131.01.0
S. Korea3.7291.031.02
Japan<1n/an/an/a

Source: https://91-divoc.com/pages/covid-visualization/

The Czech Republic – with a much lower COVID-19 mortality rate – innovated. The Czechs imposed the standard hygiene and social distancing practices, but added a twist: every person, when in public, is obligated to wear a face mask. It need not be medical grade. This sidestep not only spares supplies for crucial medical professionals, who work in close proximity to patients infected with coronavirus, it has unleashed a popular movement to sew home-made masks. That has jump-started social norms to reduce infections by wearing protective gear. And its simple logic is compelling: you protect me, I protect you.

Of course, the masks do not block one hundred percent of potential transmissions – perhaps no more than two-thirds, under favorable conditions, according to a 2013 study in the journal Disaster Medicine and Public Health Preparedness, Testing Homemade Masks for Efficacy: Would they Protect in an Influenza Pandemic?. The findings, showing results for filtering effectiveness using different materials masks, are given in the Table below. They suggest that (a) no masks are perfectly effective in blocking all tiny particles, including infectious biological matter; (b) surgical masks are relatively effective; (c) homemade masks are less effective, but much better than nothing – and should be used in conjunction with other (distancing, hygiene, etc.) practices. Where surgical masks are too expensive or unavailable, cotton face masks (sewn with multiple layers) or vacuum bags (if you can snag them) are useful substitutes. Their role is to suppress rates of disease progression, bending the curve and managing the pandemic.

The decision to encourage and then require masks (with an order effective midnight March 18) led to an enthusiastic campaign to make stylish, personalized gear – soon posted on Insta. It channeled the desire of citizens to both battle coronavirus and yet to continue living their lives. Mask wearing then further served as a reminder to observe additional rules of separation, while discouraging people from touching their face. A video on the virus went viral. It’s beautifully logical and upbeat, as global emergency crisis responses go. Judge for yourself

No doubt more research should be performed; an entire industry of PhD theses from epidemiology to sociology to public health may homestead this topic in the post-Coronavirus world. But we also must pay attention to our experimental results in real time. The Demonstration Effect is, and should be, powerful. Countries such as Slovakia and Belgium saw the Czech Republic’s approach, relative openness (low-cost mitigation), and superior survival rates, and quickly adopted similar policies. 

The U.S. rationale for discouraging mask use

U.S. policy makers initially shielded themselves from the face mask question by issuing the “institutional no.”[1] The American public was instructed by the Center for Disease Control (CDC) to refrain from wearing masks save in the instance where they were infected. There were three reasons. First, that wearing masks would actually harm healthy people not impacted with COVID-19. Second, the masks were ineffective in shielding small aerosol particles, particularly since non-professionals would not wear them properly. Third, the limited supply of high-quality, medical grade face masks should be reserved for doctors, nurses, and other health care workers who, by the nature of their tasks, could not observe “social distancing” or otherwise avoid infected COVID-19 patients. 

The third rationale had an advantage over the first two as not being false. But by the logic used to prioritize medical professional mask protections, buttressed by a modicum of public education, the rest of us would be likely to benefit, as well. The CDC was arguing magnitude and rankings (OK), and then configuring the effectiveness arguments to justify the rankings (not OK). It was a blunder, squandering precious time and undercutting agency credibility.  Moreover, the administrative edict pretended to be scientific when it was crafting (bad) economics. The Czechs and many Asian countries discovered (as disaster preparedness research had already found) that ad hoc masks work reasonably cheaply, quickly and well, and that the population can be protected to a non-trivial degree by producing their own. No need to steal N-95 respirators from frontline warriors; we’ll just make more (lower quality) protection devices.

Tip your cap to the Czech Republic. The story busted out. On March 30, The Guardian wrote: “Czechs get to work making masks after government decree: Czech Republic and Slovakia are only countries in Europe to make coronavirus mask-wearing mandatory.” By April 2, Dr. Ronald Depinho, a former president of M.D. Anderson, was editorializing: “Every American should wear a face mask to defeat Covid-19.” His empirical take was informed by a graphic (popularly Tweeted) showing fatality rates across countries – in general, the mask wearing societies of Asia (Japan, South Korean, Singapore, Taiwan) were seen to be doing relatively well in limiting the COVID-19 carnage. 

Face Masks As Pandemic Defense (4.2.20) Source: STAT

Human experiments are often considered cruel. But when they are run, let us learn from them.  

 U.S. about-face on mask use

And so the U.S. policy flipped. As per TIME:

On April 3, President Trump announced that the CDC now recommends that the general population wear non-medical masks—meaning fabric that covers one’s nose and mouth, like bandanas or cut T-shirts—when they must leave their homes to go to places like the grocery store. The measure is voluntary. The mayors of Los Angeles and New York City have already made similar recommendations. In other parts of the country, it’s not voluntary: for example, officials in Laredo, Texas have said they can fine people up to $1,000 when residents do not wear a face covering in public.

Kudos to the agency. Mistakes will be made, and it’s a great idea to fix them. But it is also instructive to see where the policy was on March 4, when TIME ran a story on how the CDC was having to combat widespread public demand for masks. There had been a retail run on masks, wiping out inventories at stores, Amazon and everywhere else; many healthy people were ignoring the request not to mask up in public; celebrities like Gwyneth Paltrow and Bella Hadid were posting their pix online. And here’s the chilling part, and it’s sadly symptomatic: the magazine fully took the agency’s side on the science and had no trouble finding additional expert authority to suppress the urge to investigate. Instead, the issue was settled by decree and then embellished as factual necessity:

“It seems kind of intuitively obvious that if you put something—whether it’s a scarf or a mask—in front of your nose and mouth, that will filter out some of these viruses that are floating around out there,” says Dr. William Schaffner, professor of medicine in the division of infectious diseases at Vanderbilt University. The only problem: that’s not likely to be effective against respiratory illnesses like the flu and COVID-19. If it were, “the CDC would have recommended it years ago,” he says. “It doesn’t, because it makes science-based recommendations.”

About that, TIME wrote: “The science, according to the CDC, says that surgical masks won’t stop the wearer from inhaling small airborne particles, which can cause infection. Nor do these masks form a snug seal around the face.” The harm was not simply a run on supplies that would deprive health workers of necessary protective gear.

“Seriously people- STOP BUYING MASKS!” tweeted Dr. Jerome Adams, the U.S. Surgeon General, on Feb. 29. “They are NOT effective in preventing general public… Adams said that wearing a mask can even increase your risk of getting the virus.

This extended into the psychological realm:

Lynn Bufka, a clinical psychologist and senior director for practice, research and policy at the American Psychological Association, suspects that people are clinging to masks for the same reason they knock on wood or avoid walking under ladders. “Even if experts are saying it’s really not going to make a difference, a little [part of] people’s brains is thinking, well, it’s not going to hurt. Maybe it’ll cut my risk just a little bit, so it’s worth it to wear a mask,” she says. In that sense, wearing a mask is a “superstitious behavior”…

Earth to Experts: superstitions run in multiple directions. See: the current view of the CDC as a correction of their previous one. And note the new TIME, quoting quite a different expert view on April 6.

“Now with the realization that there are individuals who are asymptomatic, and those asymptomatic individuals can spread infection, it’s hard to make the recommendation that only ill individuals wear masks in the community setting for protection, because it’s not clear who is ill and who is not,” says Allison Aiello, a professor of epidemiology at the University of North Carolina at Chapel Hill’s Gillings School of Global Public Health, who has researched the efficacy of masks.

Another conventional view that COVID-19 spread needed person-to-person contact, touching or close-in exchange (via coughing, breathing). But now it appears to be the case that the virus hangs around in the air, and that dosing (how much you inhale) matters greatly. A well person who encounters a passing microbe might catch a mild case of COVID-19, whereas sitting next to an infected person for five hours on a bus or airplane will trigger severe infection. In this environment, the logic for masks swells.

Scientific inquiry continues. The World Health Organization posted (March 27) that there was insufficient evidence to say whether COVID-19 travels airborne for any distance. What is the action take-away? Nature (April 2) puts the state of debate like this:

[E]xperts that work on airborne respiratory illnesses and aerosols say that gathering unequivocal evidence for airborne transmission could take years and cost lives. We shouldn’t “let perfect be the enemy of convincing”, says Michael Osterholm, an infectious-disease epidemiologist at the University of Minnesota in Minneapolis. “In the mind of scientists working on this, there’s absolutely no doubt that the virus spreads in the air,” says aerosol scientist Lidia Morawska at the Queensland University of Technology in Brisbane, Australia. “This is a no-brainer.”

Nature notes that those working in the area recommended masks as a policy response. 

Challenge the orthodoxy of the expert class, encourage intellectual diversity

Challenging orthodoxy is key to science; how else are errors uncovered or innovations discovered? On the frontiers there cannot be utter consensus. If there is, the thinkers have yet to probe nearly far enough. Safi Bakhall, in his remarkable Loonshots: Nurturing the Crazy Ideas that Win Wars, Cure Diseases and Transform Industries (2019), quotes Nobel Laureate in Medicine, Sir James Black: “it’s not a good drug unless it’s been killed at least three times” (45).  The history of progress is pocked with failure, dispute, and persistence. Only then does a great breakthrough survive the Three Deaths.

Professor Zeynep Tufekci, of Information Sciences at the University of North Carolina, came to see her research to suggest that lives could be saved by the mass market adoption of simple, non-medical masks in the United States. She broke the ice on the N.Y. Times op-ed page with her March 17 gem: “Why Telling People They Don’t Need Masks Backfired: To help manage the shortage, the authorities sent a message that made them untrustworthy.” 

Dr. Zeynep Tufekci, a professor of information science who specializes in the social effects of technology.

She put pieces of the puzzle together and made rational comparisons:

[P]laces like Hong Kong and Taiwan that jumped to action early with social distancing and universal mask wearing have the pandemic under much greater control, despite having significant travel from mainland China. Hong Kong health officials credit universal mask wearing as part of the solution and recommend universal mask wearing. In fact, Taiwan responded to the coronavirus by immediately ramping up mask production.

I’d wager Zeynep deserves a promotion, if not a Medal of Freedom. Because the fear is that this sort of commentary in the public forum will spark the opposite reaction. She believed, based on her scholarly study, that mass mask adoption might save lives, but cost her own, academically speaking. In a nifty interview with tech explainer Ben Thompson published April 2 on Stratechery,[2] Zeynep confides in how her thinking progressed. 

I watched somewhat flabbergasted over the next few months as the recommendation not to wear masks got harder and harder. Instead of getting softer as the epidemic became a pandemic and saying, well, we should see, we should reevaluate, I started seeing all these messages, like people wouldn’t know how to wear masks and they would infect themselves more and also there is a big shortage of masks, and that all came together in a very frustrating moment for me. The idea that people wouldn’t figure out how to wear a surgical mask or N95s, which are those medical grade masks that we’re now reserving only for hospitals and medical workers, is kind of ridiculous. People don’t wash their hands correctly either, right? So when the pandemic hit, we have songs to get people to wash them for the right amount and we teach them how, people can obviously learn how to wear masks correctly. And as you know, people in Hong Kong can do it, in Taiwan can do it.

But I wanted somebody else from the medical fields to write this. I wanted an epidemiologist, I wanted a virologist to come out and say, look, all these health authorities in Hong Kong and Taiwan, in South Korea, in Japan where it’s kind of customary, there are all these places with lower spread… You don’t even know if you’re sick, so the recommendation of wear this if you’re sick made no sense.

So here’s how I came to write it, even though it wasn’t my place to write this, and I really kind of dragged my foot a little bit, because… I’m not an epidemiologist. I don’t have a degree in virology, I’m not the person: I wrote it because none of the doctors could write it…. I said we have to talk about this, we have to change this conversation… So I wrote the piece pretty much making the case against what was then the CDC and the World Health Organization guidelines, and I braced for the biggest backlash of my life… and I thought, I’m going to get in so much trouble over this, I’m going to be canceled, I’m going to have the huge backlash… I thought this might be the end of my writing career as I knew it… but I just have to say this, I have to say my truth.

I hope Zeynep remains asymptomatic. No – actually, I hope she is a star. If she survives and flourishes, maybe diversity of thought, and alert empirical analysis, comparing realistic options during real-time social stress, can make a splash. If so, I hope it becomes airborne.


[1] The term is attributed to Amazon CEO Jeff Bezos in Brad Stone, “The Everything Store: Jeff Bezos in the Age of Amazon” (2013). It refers to the tendency of any organization, particularly large and complicated ones, to reflexively dismiss new ideas and their sources. It is a twist on the classic NIH (Not Invented Here) problem.

[2] Subscription-required – I recommend it.