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What is a search engine?

Dirk Auer —  21 October 2020 — 1 Comment

What is a search engine? This might seem like an innocuous question, but it lies at the heart of the US Department of Justice and state Attorneys’ General antitrust complaint against Google, as well as the European Commission’s Google Search and Android decisions. It is also central to a report published by the UK’s Competition & Markets Authority (“CMA”). To varying degrees, all of these proceedings are premised on the assumption that Google enjoys a monopoly/dominant position over online search. But things are not quite this simple. 

Despite years of competition decisions and policy discussions, there are still many unanswered questions concerning the operation of search markets. For example, it is still unclear exactly which services compete against Google Search, and how this might evolve in the near future. Likewise, there has only been limited scholarly discussion as to how a search engine monopoly would exert its market power. In other words, what does a restriction of output look like on a search platform — particularly on the user side

Answering these questions will be essential if authorities wish to successfully bring an antitrust suit against Google for conduct involving search. Indeed, as things stand, these uncertainties greatly complicate efforts (i) to rigorously define the relevant market(s) in which Google Search operates, (ii) to identify potential anticompetitive effects, and (iii) to apply the quantitative tools that usually underpin antitrust proceedings.

In short, as explained below, antitrust authorities and other plaintiffs have their work cut out if they are to prevail in court.

Consumers demand information 

For a start, identifying the competitive constraints faced by Google presents authorities and plaintiffs with an important challenge.

Even proponents of antitrust intervention recognize that the market for search is complex. For instance, the DOJ and state AGs argue that Google dominates a narrow market for “general search services” — as opposed to specialized search services, content sites, social networks, and online marketplaces, etc. The EU Commission reached the same conclusion in its Google Search decision. Finally, commenting on the CMA’s online advertising report, Fiona Scott Morton and David Dinielli argue that: 

General search is a relevant market […]

In this way, an individual specialized search engine competes with a small fraction of what the Google search engine does, because a user could employ either for one specific type of search. The CMA concludes that, from the consumer standpoint, a specialized search engine exerts only a limited competitive constraint on Google.

(Note that the CMA stressed that it did not perform a market definition exercise: “We have not carried out a formal market definition assessment, but have instead looked at competitive constraints across the sector…”).

In other words, the above critics recognize that search engines are merely tools that can serve multiple functions, and that competitive constraints may be different for some of these. But this has wider ramifications that policymakers have so far overlooked. 

When quizzed about his involvement with Neuralink (a company working on implantable brain–machine interfaces), Elon Musk famously argued that human beings already share a near-symbiotic relationship with machines (a point already made by others):

The purpose of Neuralink [is] to create a high-bandwidth interface to the brain such that we can be symbiotic with AI. […] Because we have a bandwidth problem. You just can’t communicate through your fingers. It’s just too slow.

Commentators were quick to spot this implications of this technology for the search industry:

Imagine a world when humans would no longer require a device to search for answers on the internet, you just have to think of something and you get the answer straight in your head from the internet.

As things stand, this example still belongs to the realm of sci-fi. But it neatly illustrates a critical feature of the search industry. 

Search engines are just the latest iteration (but certainly not the last) of technology that enables human beings to access specific pieces of information more rapidly. Before the advent of online search, consumers used phone directories, paper maps, encyclopedias, and other tools to find the information they were looking for. They would read newspapers and watch television to know the weather forecast. They went to public libraries to undertake research projects (some still do), etc.

And, in some respects, the search engine is already obsolete for many of these uses. For instance, virtual assistants like Alexa, Siri, Cortana and Google’s own Google Assistant offering can perform many functions that were previously the preserve of search engines: checking the weather, finding addresses and asking for directions, looking up recipes, answering general knowledge questions, finding goods online, etc. Granted, these virtual assistants partly rely on existing search engines to complete tasks. However, Google is much less dominant in this space, and search engines are not the sole source on which virtual assistants rely to generate results. Amazon’s Alexa provides a fitting example (here and here).

Along similar lines, it has been widely reported that 60% of online shoppers start their search on Amazon, while only 26% opt for Google Search. In other words, Amazon’s ability to rapidly show users the product they are looking for somewhat alleviates the need for a general search engine. In turn, this certainly constrains Google’s behavior to some extent. And much of the same applies to other websites that provide a specific type of content (think of Twitter, LinkedIn, Tripadvisor, Booking.com, etc.)

Finally, it is also revealing that the most common searches on Google are, in all likelihood, made to reach other websites — a function for which competition is literally endless:

The upshot is that Google Search and other search engines perform a bundle of functions. Most of these can be done via alternative means, and this will increasingly be the case as technology continues to advance. 

This is all the more important given that the vast majority of search engine revenue derives from roughly 30 percent of search terms (notably those that are linked to product searches). The remaining search terms are effectively a loss leader. And these profitable searches also happen to be those where competition from alternative means is, in all likelihood, the strongest (this includes competition from online retail platforms, and online travel agents like Booking.com or Kayak, but also from referral sites, direct marketing, and offline sources). In turn, this undermines US plaintiffs’ claims that Google faces little competition from rivals like Amazon, because they don’t compete for the entirety of Google’s search results (in other words, Google might face strong competition for the most valuable ads):

108. […] This market share understates Google’s market power in search advertising because many search-advertising competitors offer only specialized search ads and thus compete with Google only in a limited portion of the market. 

Critics might mistakenly take the above for an argument that Google has no market power because competition is “just a click away”. But the point is more subtle, and has important implications as far as market definition is concerned.

Authorities should not define the search market by arguing that no other rival is quite like Google (or one if its rivals) — as the DOJ and state AGs did in their complaint:

90. Other search tools, platforms, and sources of information are not reasonable substitutes for general search services. Offline and online resources, such as books, publisher websites, social media platforms, and specialized search providers such as Amazon, Expedia, or Yelp, do not offer consumers the same breadth of information or convenience. These resources are not “one-stop shops” and cannot respond to all types of consumer queries, particularly navigational queries. Few consumers would find alternative sources a suitable substitute for general search services. Thus, there are no reasonable substitutes for general search services, and a general search service monopolist would be able to maintain quality below the level that would prevail in a competitive market. 

And as the EU Commission did in the Google Search decision:

(162) For the reasons set out below, there is, however, limited demand side substitutability between general search services and other online services. […]

(163) There is limited substitutability between general search services and content sites. […]

(166) There is also limited substitutability between general search services and specialised search services. […]

(178) There is also limited substitutability between general search services and social networking sites.

Ad absurdum, if consumers suddenly decided to access information via other means, Google could be the only firm to provide general search results and yet have absolutely no market power. 

Take the example of Yahoo: Despite arguably remaining the most successful “web directory”, it likely lost any market power that it had when Google launched a superior — and significantly more successful — type of search engine. Google Search may not have provided a complete, literal directory of the web (as did Yahoo), but it offered users faster access to the information they wanted. In short, the Yahoo example shows that being unique is not equivalent to having market power. Accordingly, any market definition exercise that merely focuses on the idiosyncrasies of firms is likely to overstate their actual market power. 

Given what precedes, the question that authorities should ask is thus whether Google Search (or another search engine) performs so many unique functions that it may be in a position to restrict output. So far, no one appears to have convincingly answered this question.

Similar uncertainties surround the question of how a search engine might restrict output, especially on the user side of the search market. Accordingly, authorities will struggle to produce evidence (i) the Google has market power, especially on the user side of the market, and (ii) that its behavior has anticompetitive effects.

Consider the following:

The SSNIP test (which is the standard method of defining markets in antitrust proceedings) is inapplicable to the consumer side of search platforms. Indeed, it is simply impossible to apply a hypothetical 10% price increase to goods that are given away for free.

This raises a deeper question: how would a search engine exercise its market power? 

For a start, it seems unlikely that it would start charging fees to its users. For instance, empirical research pertaining to the magazine industry (also an ad-based two-sided market) suggests that increased concentration does not lead to higher magazine prices. Minjae Song notably finds that:

Taking the advantage of having structural models for both sides, I calculate equilibrium outcomes for hypothetical ownership structures. Results show that when the market becomes more concentrated, copy prices do not necessarily increase as magazines try to attract more readers.

It is also far from certain that a dominant search engine would necessarily increase the amount of adverts it displays. To the contrary, market power on the advertising side of the platform might lead search engines to decrease the number of advertising slots that are available (i.e. reducing advertising output), thus showing less adverts to users. 

Finally, it is not obvious that market power would lead search engines to significantly degrade their product (as this could ultimately hurt ad revenue). For example, empirical research by Avi Goldfarb and Catherine Tucker suggests that there is some limit to the type of adverts that search engines could profitably impose upon consumers. They notably find that ads that are both obtrusive and targeted decrease subsequent purchases:

Ads that match both website content and are obtrusive do worse at increasing purchase intent than ads that do only one or the other. This failure appears to be related to privacy concerns: the negative effect of combining targeting with obtrusiveness is strongest for people who refuse to give their income and for categories where privacy matters most.

The preceding paragraphs find some support in the theoretical literature on two-sided markets literature, which suggests that competition on the user side of search engines is likely to be particularly intense and beneficial to consumers (because they are more likely to single-home than advertisers, and because each additional user creates a positive externality on the advertising side of the market). For instance, Jean Charles Rochet and Jean Tirole find that:

The single-homing side receives a large share of the joint surplus, while the multi-homing one receives a small share.

This is just a restatement of Mark Armstrong’s “competitive bottlenecks” theory:

Here, if it wishes to interact with an agent on the single-homing side, the multi-homing side has no choice but to deal with that agent’s chosen platform. Thus, platforms have monopoly power over providing access to their single-homing customers for the multi-homing side. This monopoly power naturally leads to high prices being charged to the multi-homing side, and there will be too few agents on this side being served from a social point of view (Proposition 4). By contrast, platforms do have to compete for the single-homing agents, and high profits generated from the multi-homing side are to a large extent passed on to the single-homing side in the form of low prices (or even zero prices).

All of this is not to suggest that Google Search has no market power, or that monopoly is necessarily less problematic in the search engine industry than in other markets. 

Instead, the argument is that analyzing competition on the user side of search platforms is unlikely to yield dispositive evidence of market power or anticompetitive effects. This is because market power is hard to measure on this side of the market, and because even a monopoly platform might not significantly restrict user output. 

That might explain why the DOJ and state AGs analysis of anticompetitive effects is so limited. Take the following paragraph (provided without further supporting evidence):

167. By restricting competition in general search services, Google’s conduct has harmed consumers by reducing the quality of general search services (including dimensions such as privacy, data protection, and use of consumer data), lessening choice in general search services, and impeding innovation. 

Given these inherent difficulties, antitrust investigators would do better to focus on the side of those platforms where mainstream IO tools are much easier to apply and where a dominant search engine would likely restrict output: the advertising market. Not only is it the market where search engines are most likely to exert their market power (thus creating a deadweight loss), but — because it involves monetary transactions — this side of the market lends itself to the application of traditional antitrust tools.  

Looking at the right side of the market

Finally, and unfortunately for Google’s critics, available evidence suggests that its position on the (online) advertising market might not meet the requirements necessary to bring a monopolization case (at least in the US).

For a start, online advertising appears to exhibit the prima facie signs of a competitive market. As Geoffrey Manne, Sam Bowman and Eric Fruits have argued:

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.

Second, empirical research suggests that the market might need to be widened to include offline advertising. For instance, Avi Goldfarb and Catherine Tucker show that there can be important substitution effects between online and offline advertising channels:

Using data on the advertising prices paid by lawyers for 139 Google search terms in 195 locations, we exploit a natural experiment in “ambulance-chaser” regulations across states. When lawyers cannot contact clients by mail, advertising prices per click for search engine advertisements are 5%–7% higher. Therefore, online advertising substitutes for offline advertising.

Of course, a careful examination of the advertising industry could also lead authorities to define a narrower relevant market. For example, the DOJ and state AG complaint argued that Google dominated the “search advertising” market:

97. Search advertising in the United States is a relevant antitrust market. The search advertising market consists of all types of ads generated in response to online search queries, including general search text ads (offered by general search engines such as Google and Bing) […] and other, specialized search ads (offered by general search engines and specialized search providers such as Amazon, Expedia, or Yelp). 

Likewise, the European Commission concluded that Google dominated the market for “online search advertising” in the AdSense case (though the full decision has not yet been made public). Finally, the CMA’s online platforms report found that display and search advertising belonged to separate markets. 

But these are empirical questions that could dispositively be answered by applying traditional antitrust tools, such as the SSNIP test. And yet, there is no indication that the authorities behind the US complaint undertook this type of empirical analysis (and until its AdSense decision is made public, it is not clear that the EU Commission did so either). Accordingly, there is no guarantee that US courts will go along with the DOJ and state AGs’ findings.

In short, it is far from certain that Google currently enjoys an advertising monopoly, especially if the market is defined more broadly than that for “search advertising” (or the even narrower market for “General Search Text Advertising”). 

Concluding remarks

The preceding paragraphs have argued that a successful antitrust case against Google is anything but a foregone conclusion. In order to successfully bring a suit, authorities would notably need to figure out just what market it is that Google is monopolizing. In turn, that would require a finer understanding of what competition, and monopoly, look like in the search and advertising industries.

In the latest congressional hearing, purportedly analyzing Google’s “stacking the deck” in the online advertising marketplace, much of the opening statement and questioning by Senator Mike Lee and later questioning by Senator Josh Hawley focused on an episode of alleged anti-conservative bias by Google in threatening to demonetize The Federalist, a conservative publisher, unless they exercised a greater degree of control over its comments section. The senators connected this to Google’s “dominance,” arguing that it is only because Google’s ad services are essential that Google can dictate terms to a conservative website. A similar impulse motivates Section 230 reform efforts as well: allegedly anti-conservative online platforms wield their dominance to censor conservative speech, either through deplatforming or demonetization.

Before even getting into the analysis of how to incorporate political bias into antitrust analysis, though, it should be noted that there likely is no viable antitrust remedy. Even aside from the Section 230 debate, online platforms like Google are First Amendment speakers who have editorial discretion over their sites and apps, much like newspapers. An antitrust remedy compelling these companies to carry speech they disagree with would almost certainly violate the First Amendment.

But even aside from the First Amendment aspect of this debate, there is no easy way to incorporate concerns about political bias into antitrust. Perhaps the best way to understand this argument in the antitrust sense is as a non-price effects analysis. 

Political bias could be seen by end consumers as an important aspect of product quality. Conservatives have made the case that not only Google, but also Facebook and Twitter, have discriminated against conservative voices. The argument would then follow that consumer welfare is harmed when these dominant platforms leverage their control of the social media marketplace into the marketplace of ideas by censoring voices with whom they disagree. 

While this has theoretical plausibility, there are real practical difficulties. As Geoffrey Manne and I have written previously, in the context of incorporating privacy into antitrust analysis:

The Horizontal Merger Guidelines have long recognized that anticompetitive effects may “be manifested in non-price terms and conditions that adversely affect customers.” But this notion, while largely unobjectionable in the abstract, still presents significant problems in actual application. 

First, product quality effects can be extremely difficult to distinguish from price effects. Quality-adjusted price is usually the touchstone by which antitrust regulators assess prices for competitive effects analysis. Disentangling (allegedly) anticompetitive quality effects from simultaneous (neutral or pro-competitive) price effects is an imprecise exercise, at best. For this reason, proving a product-quality case alone is very difficult and requires connecting the degradation of a particular element of product quality to a net gain in advantage for the monopolist. 

Second, invariably product quality can be measured on more than one dimension. For instance, product quality could include both function and aesthetics: A watch’s quality lies in both its ability to tell time as well as how nice it looks on your wrist. A non-price effects analysis involving product quality across multiple dimensions becomes exceedingly difficult if there is a tradeoff in consumer welfare between the dimensions. Thus, for example, a smaller watch battery may improve its aesthetics, but also reduce its reliability. Any such analysis would necessarily involve a complex and imprecise comparison of the relative magnitudes of harm/benefit to consumers who prefer one type of quality to another.

Just as with privacy and other product qualities, the analysis becomes increasingly complex first when tradeoffs between price and quality are introduced, and then even more so when tradeoffs between what different consumer groups perceive as quality is added. In fact, it is more complex than privacy. All but the most exhibitionistic would prefer more to less privacy, all other things being equal. But with political media consumption, most would prefer to have more of what they want to read available, even if it comes at the expense of what others may want. There is no easy way to understand what consumer welfare means in a situation where one group’s preferences need to come at the expense of another’s in moderation decisions.

Consider the case of The Federalist again. The allegation is that Google is imposing their anticonservative bias by “forcing” the website to clean up its comments section. The argument is that since The Federalist needs Google’s advertising money, it must play by Google’s rules. And since it did so, there is now one less avenue for conservative speech.

What this argument misses is the balance Google and other online services must strike as multi-sided platforms. The goal is to connect advertisers on one side of the platform, to the users on the other. If a site wants to take advantage of the ad network, it seems inevitable that intermediaries like Google will need to create rules about what can and can’t be shown or they run the risk of losing advertisers who don’t want to be associated with certain speech or conduct. For instance, most companies don’t want to be associated with racist commentary. Thus, they will take great pains to make sure they don’t sponsor or place ads in venues associated with racism. Online platforms connecting advertisers to potential consumers must take that into consideration.

Users, like those who frequent The Federalist, have unpriced access to content across those sites and apps which are part of ad networks like Google’s. Other models, like paid subscriptions (which The Federalist also has available), are also possible. But it isn’t clear that conservative voices or conservative consumers have been harmed overall by the option of unpriced access on one side of the platform, with advertisers paying on the other side. If anything, it seems the opposite is the case since conservatives long complained about legacy media having a bias and lauded the Internet as an opportunity to gain a foothold in the marketplace of ideas.

Online platforms like Google must balance the interests of users from across the political spectrum. If their moderation practices are too politically biased in one direction or another, users could switch to another online platform with one click or swipe. Assuming online platforms wish to maximize revenue, they will have a strong incentive to limit political bias from its moderation practices. The ease of switching to another platform which markets itself as more free speech-friendly, like Parler, shows entrepreneurs can take advantage of market opportunities if Google and other online platforms go too far with political bias. 

While one could perhaps argue that the major online platforms are colluding to keep out conservative voices, this is difficult to square with the different moderation practices each employs, as well as the data that suggests conservative voices are consistently among the most shared on Facebook

Antitrust is not a cure-all law. Conservatives who normally understand this need to reconsider whether antitrust is really well-suited for litigating concerns about anti-conservative bias online. 

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 against Google—the CMA concluded, in other words, that Google had not broken UK competition law—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.

[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 Dirk Auer, (Senior Researcher, Liege Competition & Innovation Institute; Senior Fellow, ICLE).]

Privacy absolutism is the misguided belief that protecting citizens’ privacy supersedes all other policy goals, especially economic ones. This is a mistake. Privacy is one value among many, not an end in itself. Unfortunately, the absolutist worldview has filtered into policymaking and is beginning to have very real consequences. Readers need look no further than contact tracing applications and the fight against Covid-19.

Covid-19 has presented the world with a privacy conundrum worthy of the big screen. In fact, it’s a plotline we’ve seen before. Moviegoers will recall that, in the wildly popular film “The Dark Knight”, Batman has to decide between preserving the privacy of Gotham’s citizens or resorting to mass surveillance in order to defeat the Joker. Ultimately, the caped crusader begrudgingly chooses the latter. Before the Covid-19 outbreak, this might have seemed like an unrealistic plot twist. Fast forward a couple of months, and it neatly illustrates the difficult decision that most western societies urgently need to make as they consider the use of contract tracing apps to fight Covid-19.

Contact tracing is often cited as one of the most promising tools to safely reopen Covid-19-hit economies. Unfortunately, its adoption has been severely undermined by a barrage of overblown privacy fears.

Take the contact tracing API and App co-developed by Apple and Google. While these firms’ efforts to rapidly introduce contact tracing tools are laudable, it is hard to shake the feeling that they have been holding back slightly. 

In an overt attempt to protect users’ privacy, Apple and Google’s joint offering does not collect any location data (a move that has irked some states). Similarly, both firms have repeatedly stressed that users will have to opt-in to their contact tracing solution (as opposed to the API functioning by default). And, of course, all the data will be anonymous – even for healthcare authorities. 

This is a missed opportunity. Google and Apple’s networks include billions of devices. That puts them in a unique position to rapidly achieve the scale required to successfully enable the tracing of Covid-19 infections. Contact tracing applications need to reach a critical mass of users to be effective. For instance, some experts have argued that an adoption rate of at least 60% is necessary. Unfortunately, existing apps – notably in Singapore, Australia, Norway and Iceland – have struggled to get anywhere near this number. Forcing users to opt-out of Google and Apple’s services could go a long way towards inverting this trend. Businesses could also boost these numbers by making them mandatory for their employees and consumers.

However, it is hard to blame Google or Apple for not pushing the envelope a little bit further. For the best part of a decade, they and other firms have repeatedly faced specious accusations of “surveillance capitalism”. This has notably resulted in heavy-handed regulation (including the GDPR, in the EU, and the CCPA, in California), as well as significant fines and settlements

Those chickens have now come home to roost. The firms that are probably best-placed to implement an effective contact tracing solution simply cannot afford the privacy-related risks. This includes the risk associated with violating existing privacy law, but also potential reputational consequences. 

Matters have also been exacerbated by the overly cautious stance of many western governments, as well as their citizens: 

  • The European Data Protection Board cautioned governments and private sector actors to anonymize location data collected via contact tracing apps. The European Parliament made similar pronouncements.
  • A group of Democratic Senators pushed back against Apple and Google’s contact tracing solution, notably due to privacy considerations.
  • And public support for contact tracing is also critically low. Surveys in the US show that contact tracing is significantly less popular than more restrictive policies, such as business and school closures. Similarly, polls in the UK suggest that between 52% and 62% of Britons would consider using contact tracing applications.
  • Belgium’s initial plans for a contact tracing application were struck down by its data protection authority on account that they did not comply with the GDPR.
  • Finally, across the globe, there has been pushback against so-called “centralized” tracing apps, notably due to privacy fears.

In short, the West’s insistence on maximizing privacy protection is holding back its efforts to combat the joint threats posed by Covid-19 and the unfolding economic recession. 

But contrary to the mass surveillance portrayed in the Dark Knight, the privacy risks entailed by contact tracing are for the most part negligible. State surveillance is hardly a prospect in western democracies. And the risk of data breaches is no greater here than with many other apps and services that we all use daily. To wit, password, email, and identity theft are still, by far, the most common targets for cyber attackers. Put differently, cyber criminals appear to be more interested in stealing assets that can be readily monetized, rather than location data that is almost worthless. This suggests that contact tracing applications, whether centralized or not, are unlikely to be an important target for cyberattackers.

The meagre risks entailed by contact tracing – regardless of how it is ultimately implemented – are thus a tiny price to pay if they enable some return to normalcy. At the time of writing, at least 5,8 million human beings have been infected with Covid-19, causing an estimated 358,000 deaths worldwide. Both Covid-19 and the measures destined to combat it have resulted in a collapse of the global economy – what the IMF has called “the worst economic downturn since the great depression”. Freedoms that the west had taken for granted have suddenly evaporated: the freedom to work, to travel, to see loved ones, etc. Can anyone honestly claim that is not worth temporarily sacrificing some privacy to partially regain these liberties?

More generally, it is not just contact tracing applications and the fight against Covid-19 that have suffered because of excessive privacy fears. The European GDPR offers another salient example. Whatever one thinks about the merits of privacy regulation, it is becoming increasingly clear that the EU overstepped the mark. For instance, an early empirical study found that the entry into force of the GDPR markedly decreased venture capital investments in Europe. Michal Gal aptly summarizes the implications of this emerging body of literature:

The price of data protection through the GDPR is much higher than previously recognized. The GDPR creates two main harmful effects on competition and innovation: it limits competition in data markets, creating more concentrated market structures and entrenching the market power of those who are already strong; and it limits data sharing between different data collectors, thereby preventing the realization of some data synergies which may lead to better data-based knowledge. […] The effects on competition and innovation identified may justify a reevaluation of the balance reached to ensure that overall welfare is increased. 

In short, just like the Dark Knight, policymakers, firms and citizens around the world need to think carefully about the tradeoff that exists between protecting privacy and other objectives, such as saving lives, promoting competition, and increasing innovation. As things stand, however, it seems that many have veered too far on the privacy end of the scale.

The goal of US antitrust law is to ensure that competition continues to produce positive results for consumers and the economy in general. We published a letter co-signed by twenty three of the U.S.’s leading economists, legal scholars and practitioners, including one winner of the Nobel Prize in economics (full list of signatories here), to exactly that effect urging the House Judiciary Committee on the State of Antitrust Law to reject calls for radical upheaval of antitrust law that would, among other things, undermine the independence and neutrality of US antitrust law. 

A critical part of maintaining independence and neutrality in the administration of antitrust is ensuring that it is insulated from politics. Unfortunately, this view is under attack from all sides. The President sees widespread misconduct among US tech firms that he believes are controlled by the “radical left” and is, apparently, happy to use whatever tools are at hand to chasten them. 

Meanwhile, Senator Klobuchar has claimed, without any real evidence, that the mooted Uber/Grubhub merger is simply about monopolisation of the market, and not, for example, related to the huge changes that businesses like this are facing because of the Covid shutdown.

Both of these statements challenge the principle that the rule of law depends on being politically neutral, including in antitrust. 

Our letter, contrary to the claims made by President Trump, Sen. Klobuchar and some of the claims made to the Committee, asserts that the evidence and economic theory is clear: existing antitrust law is doing a good job of promoting competition and consumer welfare in digital markets and the economy more broadly, and concludes that the Committee should focus on reforms that improve antitrust at the margin, not changes that throw out decades of practice and precedent.

The letter argues that:

  1. The American economy—including the digital sector—is competitive, innovative, and serves consumers well, contrary to how it is sometimes portrayed in the public debate. 
  2. Structural changes in the economy have resulted from increased competition, and increases in national concentration have generally happened because competition at the local level has intensified and local concentration has fallen.
  3. Lax antitrust enforcement has not allowed systematic increases in market power, and the evidence simply does not support out the idea that antitrust enforcement has weakened in recent decades.
  4. Existing antitrust law is adequate for protecting competition in the modern economy, and built up through years of careful case-by-case scrutiny. Calls to throw out decades of precedent to achieve an antitrust “Year Zero” would throw away a huge body of learning and deliberation.
  5. History teaches that discarding the modern approach to antitrust would harm consumers, and return to a situation where per se rules prohibited the use of economic analysis and fact-based defences of business practices.
  6. Common sense reforms should be pursued to improve antitrust enforcement, and the reforms proposed in the letter could help to improve competition and consumer outcomes in the United States without overturning the whole system.

The reforms suggested include measures to increase transparency of the DoJ and FTC, greater scope for antitrust challenges against state-sponsored monopolies, stronger penalties for criminal cartel conduct, and more agency resources being made available to protect workers from anti-competitive wage-fixing agreements between businesses. These are suggestions for the House Committee to consider and are not supported by all the letter’s signatories.

Some of the arguments in the letter are set out in greater detail in the ICLE’s own submission to the Committee, which goes into detail about the nature of competition in modern digital markets and in traditional markets that have been changed because of the adoption of digital technologies. 

The full letter is here.

[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 Kristian Stout, (Associate Director, International Center for Law & Economics]

The public policy community’s infatuation with digital privacy has grown by leaps and bounds since the enactment of GDPR and the CCPA, but COVID-19 may leave the most enduring mark on the actual direction that privacy policy takes. As the pandemic and associated lockdowns first began, there were interesting discussions cropping up about the inevitable conflict between strong privacy fundamentalism and the pragmatic steps necessary to adequately trace the spread of infection. 

Axiomatic of this controversy is the Apple/Google contact tracing system, software developed for smartphones to assist with the identification of individuals and populations that have likely been in contact with the virus. The debate sparked by the Apple/Google proposal highlights what we miss when we treat “privacy” (however defined) as an end in itself, an end that must necessarily  trump other concerns. 

The Apple/Google contact tracing efforts

Apple/Google are doing yeoman’s work attempting to produce a useful contact tracing API given the headwinds of privacy advocacy they face. Apple’s webpage describing its new contact tracing system is a testament to the extent to which strong privacy protections are central to its efforts. Indeed, those privacy protections are in the very name of the service: “Privacy-Preserving Contact Tracing” program. But, vitally, the utility of the Apple/Google API is ultimately a function of its efficacy as a tracing tool, not in how well it protects privacy.

Apple/Google — despite the complaints of some states — are rolling out their Covid-19-tracking services with notable limitations. Most prominently, the APIs will not allow collection of location data, and will only function when users explicitly opt-in. This last point is important because there is evidence that opt-in requirements, by their nature, tend to reduce the flow of information in a system, and when we are considering tracing solutions to an ongoing pandemic surely less information is not optimal. Further, all of the data collected through the API will be anonymized, preventing even healthcare authorities from identifying particular infected individuals.

These restrictions prevent the tool from being as effective as it could be, but it’s not clear how Apple/Google could do any better given the political climate. For years, the Big Tech firms have been villainized by privacy advocates that accuse them of spying on kids and cavalierly disregarding consumer privacy as they treat individuals’ data as just another business input. The problem with this approach is that, in the midst of a generational crisis, our best tools are being excluded from the fight. Which begs the question: perhaps we have privacy all wrong? 

Privacy is one value among many

The U.S. constitutional order explicitly protects our privacy as against state intrusion in order to guarantee, among other things, fair process and equal access to justice. But this strong presumption against state intrusion—far from establishing a fundamental or absolute right to privacy—only accounts for part of the privacy story. 

The Constitution’s limit is a recognition of the fact that we humans are highly social creatures and that privacy is one value among many. Properly conceived, privacy protections are themselves valuable only insofar as they protect other things we value. Jane Bambauer explored some of this in an earlier post where she characterized privacy as, at best, an “instrumental right” — that is a tool used to promote other desirable social goals such as “fairness, safety, and autonomy.”

Following from Jane’s insight, privacy — as an instrumental good — is something that can have both positive and negative externalities, and needs to be enlarged or attenuated as its ability to serve instrumental ends changes in different contexts. 

According to Jane:

There is a moral imperative to ignore even express lack of consent when withholding important information that puts others in danger. Just as many states affirmatively require doctors, therapists, teachers, and other fiduciaries to report certain risks even at the expense of their client’s and ward’s privacy …  this same logic applies at scale to the collection and analysis of data during a pandemic.

Indeed, dealing with externalities is one of the most common and powerful justifications for regulation, and an extreme form of “privacy libertarianism” —in the context of a pandemic — is likely to be, on net, harmful to society.

Which brings us back to efforts of Apple/Google. Even if those firms wanted to risk the ire of  privacy absolutists, it’s not clear that they could do so without incurring tremendous regulatory risk, uncertainty and a popular backlash. As statutory matters, the CCPA and the GDPR chill experimentation in the face of potentially crippling fines. While the FTC Act’s Section 5 prohibition on “unfair or deceptive” practices is open to interpretation in manners which could result in existentially damaging outcomes. Further, some polling suggests that the public appetite for contact tracing is not particularly high – though, as is often the case, such pro-privacy poll outcomes rarely give appropriate shrift to the tradeoff required.

As a general matter, it’s important to think about the value of individual privacy, and how best to optimally protect it. But privacy does not stand above all other values in all contexts. It is entirely reasonable to conclude that, in a time of emergency, if private firms can devise more effective solutions for mitigating the crisis, they should have more latitude to experiment. Knee-jerk preferences for an amorphous “right of privacy” should not be used to block those experiments.

Much as with the Cosmic Turtle, its tradeoffs all the way down. Most of the U.S. is in lockdown, and while we vigorously protect our privacy, we risk frustrating the creation of tools that could put a light at the end of the tunnel. We are, in effect, trading liberty and economic self-determination for privacy.

Once the worst of the Covid-19 crisis has passed — hastened possibly by the use of contact tracing programs — we can debate the proper use of private data in exigent circumstances. For the immediate future, we should instead be encouraging firms like Apple/Google to experiment with better ways to control the pandemic. 

[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 Dirk Auer, (Senior Researcher, Liege Competition & Innovation Institute; Senior Fellow, ICLE).]

Across the globe, millions of people are rapidly coming to terms with the harsh realities of life under lockdown. As governments impose ever-greater social distancing measures, many of the daily comforts we took for granted are no longer available to us. 

And yet, we can all take solace in the knowledge that our current predicament would have been far less tolerable if the COVID-19 outbreak had hit us twenty years ago. Among others, we have Big Tech firms to thank for this silver lining. 

Contrary to the claims of critics, such as Senator Josh Hawley, Big Tech has produced game-changing innovations that dramatically improve our ability to fight COVID-19. 

The previous post in this series showed that innovations produced by Big Tech provide us with critical information, allow us to maintain some level of social interactions (despite living under lockdown), and have enabled companies, universities and schools to continue functioning (albeit at a severely reduced pace).

But apart from information, social interactions, and online working (and learning); what has Big Tech ever done for us?

One of the most underappreciated ways in which technology (mostly pioneered by Big Tech firms) is helping the world deal with COVID-19 has been a rapid shift towards contactless economic transactions. Not only are consumers turning towards digital goods to fill their spare time, but physical goods (most notably food) are increasingly being exchanged without any direct contact.

These ongoing changes would be impossible without the innovations and infrastructure that have emerged from tech and telecommunications companies over the last couple of decades. 

Of course, the overall picture is still bleak. The shift to contactless transactions has only slightly softened the tremendous blow suffered by the retail and restaurant industries – some predictions suggest their overall revenue could fall by at least 50% in the second quarter of 2020. Nevertheless, as explained below, this situation would likely be significantly worse without the many innovations produced by Big Tech companies. For that we would be thankful.

1. Food and other goods

For a start, the COVID-19 outbreak (and government measures to combat it) has caused many brick & mortar stores and restaurants to shut down. These closures would have been far harder to implement before the advent of online retail and food delivery platforms.

At the time of writing, e-commerce websites already appear to have witnessed a 20-30% increase in sales (other sources report 52% increase, compared to the same time last year). This increase will likely continue in the coming months.

The Amazon Retail platform has been at the forefront of this online shift.

  • Having witnessed a surge in online shopping, Amazon announced that it would be hiring 100.000 distribution workers to cope with the increased demand. Amazon’s staff have also been asked to work overtime in order to meet increased demand (in exchange, Amazon has doubled their pay for overtime hours).
  • To attract these new hires and ensure that existing ones continue working, Amazon simultaneously announced that it would be increasing wages in virus-hit countries (from $15 to $17, in the US) .
  • Amazon also stopped accepting “non-essential” goods in its warehouses, in order to prioritize the sale of household essentials and medical goods that are in high demand.
  • Finally, in Italy, Amazon decided not to stop its operations, despite some employees testing positive for COVID-19. Controversial as this move may be, Amazon’s private interests are aligned with those of society – maintaining the supply of essential goods is now more important than ever. 

And it is not just Amazon that is seeking to fill the breach left temporarily by brick & mortar retail. Other retailers are also stepping up efforts to distribute their goods online.

  • The apps of traditional retail chains have witnessed record daily downloads (thus relying on the smartphone platforms pioneered by Google and Apple).
  •  Walmart has become the go-to choice for online food purchases:

(Source: Bloomberg)

The shift to online shopping mimics what occurred in China, during its own COVID-19 lockdown. 

  • According to an article published in HBR, e-commerce penetration reached 36.6% of retail sales in China (compared to 29.7% in 2019). The same article explains how Alibaba’s technology is enabling traditional retailers to better manage their supply chains, ultimately helping them to sell their goods online.
  • A study by Nielsen ratings found that 67% of retailers would expand online channels. 
  • One large retailer shut many of its physical stores and redeployed many of its employees to serve as online influencers on WeChat, thus attempting to boost online sales.
  • Spurred by compassion and/or a desire to boost its brand abroad, Alibaba and its founder, Jack Ma, have made large efforts to provide critical medical supplies (notably tests kits and surgical masks) to COVID-hit countries such as the US and Belgium.

And it is not just retail that is adapting to the outbreak. Many restaurants are trying to stay afloat by shifting from in-house dining to deliveries. These attempts have been made possible by the emergence of food delivery platforms, such as UberEats and Deliveroo. 

These platforms have taken several steps to facilitate food deliveries during the outbreak.

  • UberEats announced that it would be waiving delivery fees for independent restaurants.
  • Both UberEats and Deliveroo have put in place systems for deliveries to take place without direct physical contact. While not entirely risk-free, meal delivery can provide welcome relief to people experiencing stressful lockdown conditions.

Similarly, the shares of Blue Apron – an online meal-kit delivery service – have surged more than 600% since the start of the outbreak.

In short, COVID-19 has caused a drastic shift towards contactless retail and food delivery services. It is an open question how much of this shift would have been possible without the pioneering business model innovations brought about by Amazon and its online retail platform, as well as modern food delivery platforms, such as UberEats and Deliveroo. At the very least, it seems unlikely that it would have happened as fast.

The entertainment industry is another area where increasing digitization has made lockdowns more bearable. The reason is obvious: locked-down consumers still require some form of amusement. With physical supply chains under tremendous strain, and social gatherings no longer an option, digital media has thus become the default choice for many.

Data published by Verizon shows a sharp increase (in the week running from March 9 to March 16) in the consumption of digital entertainment, especially gaming:

This echoes other sources, which also report that the use of traditional streaming platforms has surged in areas hit by COVID-19.

  • Netflix subscriptions are said to be spiking in locked-down communities. During the first week of March, Netflix installations increased by 77% in Italy and 33% in Spain, compared to the February average. Netflix app downloads increased by 33% in Hong kong and South Korea. The Amazon Prime app saw a similar increase.
  • YouTube has also witnessed a surge in usage. 
  • Live streaming (on platforms such as Periscope, Twitch, YouTube, Facebook, Instagram, etc) has also increased in popularity. It is notably being used for everything from concerts and comedy clubs to religious services, and even zoo visits.
  • Disney Plus has also been highly popular. According to one source, half of US homes with children under the age of 10 purchased a Disney Plus subscription. This trend is expected to continue during the COVID-19 outbreak. Disney even released Frozen II three months ahead of schedule in order to boost new subscriptions.
  • Hollywood studios have started releasing some of their lower-profile titles directly on streaming services.

Traffic has also increased significantly on popular gaming platforms.

These are just a tiny sample of the many ways in which digital entertainment is filling the void left by social gatherings. It is thus central to the lives of people under lockdown.

2. Cashless payments

But all of the services that are listed above rely on cashless payments – be it to limit the risk or contagion or because these transactions take place remotely. Fintech innovations have thus turned out to be one of the foundations that make social distancing policies viable. 

This is particularly evident in the food industry. 

  • Food delivery platforms, like UberEats and Deliveroo, already relied on mobile payments.
  • Costa coffee (a UK equivalent to starbucks) went cashless in an attempt to limit the spread of COVID-19.
  • Domino’s Pizza, among other franchises, announced that it would move to contactless deliveries.
  • President Donald Trump is said to have discussed plans to keep drive-thru restaurants open during the outbreak. This would also certainly imply exclusively digital payments.
  • And although doubts remain concerning the extent to which the SARS-CoV-2 virus may, or may not, be transmitted via banknotes and coins, many other businesses have preemptively ceased to accept cash payments

As the Jodie Kelley – the CEO of the Electronic Transactions Association – put it, in a CNBC interview:

Contactless payments have come up as a new option for consumers who are much more conscious of what they touch. 

This increased demand for cashless payments has been a blessing for Fintech firms. 

  • Though it is too early to gage the magnitude of this shift, early signs – notably from China – suggest that mobile payments have become more common during the outbreak.
  • In China, Alipay announced that it expected to radically expand its services to new sectors – restaurants, cinema bookings, real estate purchases – in an attempt to compete with WeChat.
  • PayPal has also witnessed an uptick in transactions, though this growth might ultimately be weighed-down by declining economic activity.
  • In the past, Facebook had revealed plans to offer mobile payments across its platforms – Facebook, WhatsApp, Instagram & Libra. Those plans may not have been politically viable at the time. The COVID-19 could conceivably change this.

In short, the COVID-19 outbreak has increased our reliance on digital payments, as these can both take place remotely and, potentially, limit contamination via banknotes. None of this would have been possible twenty years ago when industry pioneers, such as PayPal, were in their infancy. 

3. High speed internet access

Similarly, it goes without saying that none of the above would be possible without the tremendous investments that have been made in broadband infrastructure, most notably by internet service providers. Though these companies have often faced strong criticism from the public, they provide the backbone upon which outbreak-stricken economies can function.

By causing so many activities to move online, the COVID-19 outbreak has put broadband networks to the test. So for, broadband infrastructure around the world has been up to the task. This is partly because the spike in usage has occurred in daytime hours (where network’s capacity is less straine), but also because ISPs traditionally rely on a number of tools to limit peak-time usage.

The biggest increases in usage seem to have occurred in daytime hours. As data from OpenVault illustrates:

According to BT, one of the UK’s largest telecoms operators, daytime internet usage is up by 50%, but peaks are still well within record levels (and other UK operators have made similar claims):

Anecdotal data also suggests that, so far, fixed internet providers have not significantly struggled to handle this increased traffic (the same goes for Content Delivery Networks). Not only were these networks already designed to withstand high peaks in demand, but ISPs have, such as Verizon, increased their  capacity to avoid potential issues.

For instance, internet speed tests performed using Ookla suggest that average download speeds only marginally decreased, it at all, in locked-down regions, compared to previous levels:

However, the same data suggests that mobile networks have faced slightly larger decreases in performance, though these do not appear to be severe. For instance, contrary to contemporaneous reports, a mobile network outage that occurred in the UK is unlikely to have been caused by a COVID-related surge. 

The robustness exhibited by broadband networks is notably due to long-running efforts by ISPs (spurred by competition) to improve download speeds and latency. As one article put it:

For now, cable operators’ and telco providers’ networks are seemingly withstanding the increased demands, which is largely due to the upgrades that they’ve done over the past 10 or so years using technologies such as DOCSIS 3.1 or PON.

Pushed in part by Google Fiber’s launch back in 2012, the large cable operators and telcos, such as AT&T, Verizon, Comcast and Charter Communications, have spent years upgrading their networks to 1-Gig speeds. Prior to those upgrades, cable operators in particular struggled with faster upload speeds, and the slowdown of broadband services during peak usage times, such as after school and in the evenings, as neighborhood nodes became overwhelmed.

This is not without policy ramifications.

For a start, these developments might vindicate antitrust enforcers that allowed mergers that led to higher investments, sometimes at the expense of slight reductions in price competition. This is notably the case for so-called 4 to 3 mergers in the wireless telecommunications industry. As an in-depth literature review by ICLE scholars concludes:

Studies of investment also found that markets with three facilities-based operators had significantly higher levels of investment by individual firms.

Similarly, the COVID-19 outbreak has also cast further doubts over the appropriateness of net neutrality regulations. Indeed, an important criticism of such regulations is that they prevent ISPs from using the price mechanism to manage congestion

It is these fears of congestion, likely unfounded (see above), that led the European Union to urge streaming companies to voluntarily reduce the quality of their products. To date, Netflix, Youtube, Amazon Prime, Apple, Facebook and Disney have complied with the EU’s request. 

This may seem like a trivial problem, but it was totally avoidable. As a result of net neutrality regulation, European authorities and content providers have been forced into an awkward position (likely unfounded) that unnecessarily penalizes those consumers and ISPs who do not face congestion issues (conversely, it lets failing ISPs off the hook and disincentivizes further investments on their part). This is all the more unfortunate that, as argued above, streaming services are essential to locked-down consumers. 

Critics may retort that small quality decreases hardly have any impact on consumers. But, if this is indeed the case, then content providers were using up unnecessary amounts of bandwidth before the COVID-19 outbreak (something that is less likely to occur without net neutrality obligations). And if not, then European consumers have indeed been deprived of something they valued. The shoe is thus on the other foot.

These normative considerations aside, the big point is that we can all be thankful to live in an era of high-speed internet.

 4. Concluding remarks 

Big Tech is rapidly emerging as one of the heroes of the COVID-19 crisis. Companies that were once on the receiving end of daily reproaches – by the press, enforcers, and scholars alike – are gaining renewed appreciation from the public. Times have changed since the early days of these companies – where consumers marvelled at the endless possibilities that their technologies offered. Today we are coming to realize how essential tech companies have become to our daily lives, and how they make society more resilient in the face of fat-tailed events, like pandemics.

The move to a contactless, digital, economy is a critical part of what makes contemporary societies better-equipped to deal with COVID-19. As this post has argued, online delivery, digital entertainment, contactless payments and high speed internet all play a critical role. 

To think that we receive some of these services for free…

Last year, Erik Brynjolfsson, Avinash Collins and Felix Eggers published a paper in PNAS, showing that consumers were willing to pay significant sums for online goods they currently receive free of charge. One can only imagine how much larger those sums would be if that same experiment were repeated today.

Even Big Tech’s critics are willing to recognize the huge debt we owe to these companies. As Stephen Levy wrote, in an article titled “Has the Coronavirus Killed the Techlash?”:

Who knew the techlash was susceptible to a virus?

The pandemic does not make any of the complaints about the tech giants less valid. They are still drivers of surveillance capitalism who duck their fair share of taxes and abuse their power in the marketplace. We in the press must still cover them aggressively and skeptically. And we still need a reckoning that protects the privacy of citizens, levels the competitive playing field, and holds these giants to account. But the momentum for that reckoning doesn’t seem sustainable at a moment when, to prop up our diminished lives, we are desperately dependent on what they’ve built. And glad that they built it.

While it is still early to draw policy lessons from the outbreak, one thing seems clear: the COVID-19 pandemic provides yet further evidence that tech policymakers should be extremely careful not to kill the goose that laid the golden egg, by promoting regulations that may thwart innovation (or the opposite).

[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 Dirk Auer, (Senior Fellow of Law & Economics, International Center for Law & Economics).]

Republican Senator Josh Hawley infamously argued that Big Tech is overrated. In his words:

My biggest critique of big tech is: what big innovation have they really given us? What is it now that in the last 15, 20 years that people who say they are the brightest minds in the country have given this country? What are their great innovations?

To Senator Hawley these questions seemed rhetorical. Big Tech’s innovations were trivial gadgets: “autoplay” and “snap streaks”, to quote him once more.

But, as any Monty Python connoisseur will tell you, rhetorical questions have a way of being … not so rhetorical. In one of Python’s most famous jokes, members of the “People’s Front of Judea” ask “what have the Romans ever done for us”? To their own surprise, the answer turns out to be a great deal:

This post is the first in a series examining some of the many ways in which Big Tech is making Coronavirus-related lockdowns and social distancing more bearable, and how Big Tech is enabling our economies to continue functioning (albeit at a severely reduced pace) throughout the outbreak. 

Although Big Tech’s contributions are just a small part of a much wider battle, they suggest that the world is drastically better situated to deal with COVID-19 than it would have been twenty years ago – and this is in no small part thanks to Big Tech’s numerous innovations.

Of course, some will say that the world would be even better equipped to handle COVID-19, if Big Tech had only been subject to more (or less) regulation. Whether these critiques are correct, or not, they are not the point of this post. For many, like Senator Hawley, it is apparently undeniable that tech does more harm than good. But, as this post suggests, that is surely not the case. And before we do decide whether and how we want to regulate it in the future, we should be particularly mindful of what aspects of “Big Tech” seem particularly suited to dealing with the current crisis, and ensure that we don’t adopt regulations that thoughtlessly undermine these.

1. Priceless information 

One of the most important ways in which Big Tech firms have supported international attempts to COVID-19 has been their role as  information intermediaries. 

As the title of a New York Times article put it:

When Facebook Is More Trustworthy Than the President: Social media companies are delivering reliable information in the coronavirus crisis. Why can’t they do that all the time?

The author is at least correct on the first part. Big Tech has become a cornucopia of reliable information about the virus:

  • Big Tech firms are partnering with the White House and other agencies to analyze massive COVID-19 datasets in order to help discover novel answers to questions about transmission, medical care, and other interventions. This partnership is possible thanks to the massive investments in AI infrastructure that the leading tech firms have made. 
  • Google Scholar has partnered with renowned medical journals (as well as public authorities) to guide citizens towards cutting edge scholarship relating to COVID-19. This a transformative ressource in a world of lockdows and overburdened healthcare providers.
  • Google has added a number of features to its main search engine – such as a “Coronavirus Knowledge Panel” and SOS alerts – in order to help users deal with the spread of the virus.
  • On Twitter, information and insights about COVID-19 compete in the market for ideas. Numerous news outlets have published lists of recommended people to follow (Fortune, Forbes). 

    Furthermore – to curb some of the unwanted effects of an unrestrained market for ideas – Twitter (and most other digital platforms) links to the websites of public authorities when users search for COVID-related hashtags.
  • This flow of information is a two-way street: Twitter, Facebook and Reddit, among others, enable citizens and experts to weigh in on the right policy approach to COVID-19. 

    Though the results are sometimes far from perfect, these exchanges may prove invaluable in critical times where usual methods of policy-making (such as hearings and conferences) are mostly off the table.
  • Perhaps most importantly, the Internet is a precious source of knowledge about how to deal with an emerging virus, as well as life under lockdown. We often take for granted how much of our lives benefit from extreme specialization. These exchanges are severely restricted under lockdown conditions. Luckily, with the internet and modern search engines (pioneered by Google), most of the world’s information is but a click away.

    For example, Facebook Groups have been employed by users of the social media platform in order to better coordinate necessary activity among community members — like giving blood — while still engaging in social distancing.

In short, search engines and social networks have been beacons of information regarding COVID-19. Their mostly bottom-up approach to knowledge generation (i.e. popular topics emerge organically) is essential in a world of extreme uncertainty. This has ultimately enabled these players to stay ahead of the curve in bringing valuable information to citizens around the world.

2. Social interactions

This is probably the most obvious way in which Big Tech is making life under lockdown more bearable for everyone. 

  • In Italy, Whatsapp messages and calls jumped by 20% following the outbreak of COVID-19. And Microsoft claims that the use of Skype jumped by 100%.
  • Younger users are turning to social networks, like TikTok, to deal with the harsh realities of the pandemic.
  • Strangers are using Facebook groups to support each other through difficult times.
  • And institutions, like the WHO, are piggybacking on this popularity to further raise awareness about COVID-19 via social media. 
  • In South Africa, health authorities even created a whatsapp contact to answer users questions about the virus.
  • Most importantly, social media is a godsend for senior citizens and anyone else who may have to live in almost total isolation for the foreseeable future. For instance, nursing homes are putting communications apps, like Skype and WhatsApp, in the hands of their patients, to keep up their morale (here and here).

And with the economic effects of COVID-19 starting to gather speed, users will more than ever be grateful to receive these services free of charge. Sharing data – often very limited amounts – with a platform is an insignificant price to pay in times of economic hardship. 

3. Working & Learning

It will also be impossible to effectively fight COVID-19 if we cannot maintain the economy afloat. Stock markets have already plunged by record amounts. Surely, these losses would be unfathomably worse if many of us were not lucky enough to be able to work, and from the safety of our own homes. And for those individuals who are unable to work from home, their own exposure is dramatically reduced thanks to a significant proportion of the population that can stay out of public.

Once again, we largely have Big Tech to thank for this. 

  • Downloads of Microsoft Teams and Zoom are surging on both Google and Apple’s app stores. This is hardly surprising. With much of the workforce staying at home, these video-conference applications have become essential. The increased load generated by people working online might even have caused Microsoft Teams to crash in Europe.
  • According to Microsoft, the number of Microsoft Teams meetings increased by 500 percent in China.
  • Sensing that the current crisis may last for a while, some firms have also started to conduct job interviews online; populars apps for doing so include Skype, Zoom and Whatsapp. 
  • Slack has also seen a surge in usage, as firms set themselves up to work remotely. It has started offering free training, to help firms move online.
  • Along similar lines, Google recently announced that its G suite of office applications – which enables users to share and work on documents online – had recently passed 2 Billion users.
  • Some tech firms (including Google, Microsoft and Zoom) have gone a step further and started giving away some of their enterprise productivity software, in order to help businesses move their workflows online.

And Big Tech is also helping universities, schools and parents to continue providing coursework and lectures to their students/children.

  • Zoom and Microsoft Teams have been popular choices for online learning. To facilitate the transition to online learning, Zoom has notably lifted time limits relating to the free version of its app (for schools in the most affected areas).
  • Even in the US, where the virus outbreak is currently smaller than in Europe, thousands of students are already being taught online.
  • Much of the online learning being conducted for primary school children is being done with affordable Chromebooks. And some of these Chromebooks are distributed to underserved schools through grant programs administered by Google.
  • Moreover, at the time of writing, most of the best selling books on Amazon.com are pre-school learning books:

Finally, the advent of online storage services, such as Dropbox and Google Drive, has largely alleviated the need for physical copies of files. In turn, this enables employees to remotely access all the files they need to stay productive. While this may be convenient under normal circumstances, it becomes critical when retrieving a binder in the office is no longer an option.

4. So what has Big Tech ever done for us?

With millions of families around the world currently under forced lockdown, it is becoming increasingly evident that Big Tech’s innovations are anything but trivial. Innovations that seemed like convenient tools only a couple of days ago, are now becoming essential parts of our daily lives (or, at least, we are finally realizing how powerful they truly are). 

The fight against COVID-19 will be hard. We can at least be thankful that we have Big Tech by our side. Paraphrasing the Monty Python crew: 

Q: What has Big Tech ever done for us? 

A: Abundant, free, and easily accessible information. Precious social interactions. Online working and learning.

Q: But apart from information, social interactions, and online working (and learning); what has Big Tech ever done for us?

For the answer to this question, I invite you to stay tuned for the next post in this series.

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

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

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

The wrong economic models

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

An incorrect view of innovation

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

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

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

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

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

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

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

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

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

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

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

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

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

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

Conclusion

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

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

In mid-November, the 50 state attorneys general (AGs) investigating Google’s advertising practices expanded their antitrust probe to include the company’s search and Android businesses. Texas Attorney General Ken Paxton, the lead on the case, was supportive of the development, but made clear that other states would manage the investigations of search and Android separately. While attorneys might see the benefit in splitting up search and advertising investigations, platforms like Google need to be understood as a coherent whole. If the state AGs case is truly concerned with the overall impact on the welfare of consumers, it will need to be firmly grounded in the unique economics of this platform.

Back in September, 50 state AGs, including those in Washington, DC and Puerto Rico, announced an investigation into Google. In opening the case, Paxton said that, “There is nothing wrong with a business becoming the biggest game in town if it does so through free market competition, but we have seen evidence that Google’s business practices may have undermined consumer choice, stifled innovation, violated users’ privacy, and put Google in control of the flow and dissemination of online information.” While the original document demands focused on Google’s “overarching control of online advertising markets and search traffic,” reports since then suggest that the primary investigation centers on online advertising.

Defining the market

Since the market definition is the first and arguably the most important step in an antitrust case, Paxton has tipped his hand and shown that the investigation is converging on the online ad market. Yet, he faltered when he wrote in The Wall Street Journal that, “Each year more than 90% of Google’s $117 billion in revenue comes from online advertising. For reference, the entire market for online advertising is around $130 billion annually.” As Patrick Hedger of the Competitive Enterprise Institute was quick to note, Paxton cited global revenue numbers and domestic advertising statistics. In reality, Google’s share of the online advertising market in the United States is 37 percent and is widely expected to fall.

When Google faced scrutiny by the Federal Trade Commission in 2013, the leaked staff report explained that “the Commission and the Department of Justice have previously found online ‘search advertising’ to be a distinct product market.” This finding, which dates from 2007, simply wouldn’t stand today. Facebook’s ad platform was launched in 2007 and has grown to become a major competitor to Google. Even more recently, Amazon has jumped into the space and independent platforms like Telaria, Rubicon Project, and The Trade Desk have all made inroads. In contrast to the late 2000s, advertisers now use about four different online ad platforms.

Moreover, the relationship between ad prices and industry concentration is complicated. In traditional economic analysis, fewer suppliers of a product generally translates into higher prices. In the online ad market, however, fewer advertisers means that ad buyers can efficiently target people through keywords. Because advertisers have access to superior information, research finds that more concentration tends to lead to lower search engine revenues. 

The addition of new fronts in the state AGs’ investigation could spell disaster for consumers. While search and advertising are distinct markets, it is the act of tying the two together that makes platforms like Google valuable to users and advertisers alike. Demand is tightly integrated between the two sides of the platform. Changes in user and advertiser preferences have far outsized effects on the overall platform value because each side responds to the other. If users experience an increase in price or a reduction in quality, then they will use the platform less or just log off completely. Advertisers see this change in users and react by reducing their demand for ad placements as well. When advertisers drop out, the total amount of content also recedes and users react once again. Economists call these relationships demand interdependencies. The demand on one side of the market is interdependent with demand on the other. Research on magazines, newspapers, and social media sites all support the existence of demand interdependencies. 

Economists David Evans and Richard Schmalensee, who were cited extensively in the Supreme Court case Ohio v. American Express, explained the importance of their integration into competition analysis, “The key point is that it is wrong as a matter of economics to ignore significant demand interdependencies among the multiple platform sides” when defining markets. If they are ignored, then the typical analytical tools will yield incorrect assessments. Understanding these relationships makes the investigation all that more difficult.

The limits of remedies

Most likely, this current investigation will follow the trajectory of Microsoft in the 1990s when states did the legwork for a larger case brought by the Department of Justice (DoJ). The DoJ already has its own investigation into Google and will probably pull together all of the parties for one large suit. Google is also subject to a probe by the House of Representatives Judiciary Committee as well. What is certain is that Google will be saddled with years of regulatory scrutiny, but what remains unclear is what kind of changes the AGs are after.

The investigation might aim to secure behavioral changes, but these often come with a cost in platform industries. The European Commission, for example, got Google to change its practices with its Android operating system for mobile phones. Much like search and advertising, the Android ecosystem is a platform with cross subsidization and demand interdependencies between the various sides of the market. Because the company was ordered to stop tying the Android operating system to apps, manufacturers of phones and tablets now have to pay a licensing fee in Europe if they want Google’s apps and the Play Store. Remedies meant to change one side of the platform resulted in those relationships being unbundled. When regulators force cross subsidization to become explicit prices, consumers are the one who pay.

The absolute worst case scenario would be a break up of Google, which has been a centerpiece of Senator Elizabeth Warren’s presidential platform. As I explained last year, that would be a death warrant for the company:

[T]he value of both Facebook and Google comes in creating the platform, which combines users with advertisers. Before the integration of ad networks, the search engine industry was struggling and it was simply not a major player in the Internet ecosystem. In short, the search engines, while convenient, had no economic value. As Michael Moritz, a major investor of Google, said of those early years, “We really couldn’t figure out the business model. There was a period where things were looking pretty bleak.” But Google didn’t pave the way. Rather, Bill Gross at GoTo.com succeeded in showing everyone how advertising could work to build a business. Google founders Larry Page and Sergey Brin merely adopted the model in 2002 and by the end of the year, the company was profitable for the first time. Marrying the two sides of the platform created value. Tearing them apart will also destroy value.

The state AGs need to resist making this investigation into a political showcase. As Pew noted in documenting the rise of North Carolina Attorney General Josh Stein to national prominence, “What used to be a relatively high-profile position within a state’s boundaries has become a springboard for publicity across the country.” While some might cheer the opening of this investigation, consumer welfare needs to be front and center. To properly understand how consumer welfare might be impacted by an investigation, the state AGs need to take seriously the path already laid out by platform economics. For the sake of consumers, let’s hope they are up to the task. 

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

(Comparison of Google and Apple’s smartphone business models. Red $ symbols represent money invested; Green $ symbols represent sources of revenue; Black lines show the extent of Google and Apple’s control over their respective platforms)

For the third in my series of posts about the Google Android decision, I will delve into the theories of harm identified by the Commission. 

The big picture is that the Commission’s analysis was particularly one-sided. The Commission failed to adequately account for the complex business challenges that Google faced – such as monetizing the Android platform and shielding it from fragmentation. To make matters worse, its decision rests on dubious factual conclusions and extrapolations. The result is a highly unbalanced assessment that could ultimately hamstring Google and prevent it from effectively competing with its smartphone rivals, Apple in particular.

1. Tying without foreclosure

The first theory of harm identified by the Commission concerned the tying of Google’s Search app with the Google Play app, and of Google’s Chrome app with both the Google Play and Google Search apps.

Oversimplifying, Google required its OEMs to choose between either pre-installing a bundle of Google applications, or forgoing some of the most important ones (notably Google Play). The Commission argued that this gave Google a competitive advantage that rivals could not emulate (even though Google’s terms did not preclude OEMs from simultaneously pre-installing rival web browsers and search apps). 

To support this conclusion, the Commission notably asserted that no alternative distribution channel would enable rivals to offset the competitive advantage that Google obtained from tying. This finding is, at best, dubious. 

For a start, the Commission claimed that user downloads were not a viable alternative distribution channel, even though roughly 250 million apps are downloaded on Google’s Play store every day.

The Commission sought to overcome this inconvenient statistic by arguing that Android users were unlikely to download apps that duplicated the functionalities of a pre-installed app – why download a new browser if there is already one on the user’s phone?

But this reasoning is far from watertight. For instance, the 17th most-downloaded Android app, the “Super-Bright Led Flashlight” (with more than 587million downloads), mostly replicates a feature that is pre-installed on all Android devices. Moreover, the five most downloaded Android apps (Facebook, Facebook Messenger, Whatsapp, Instagram and Skype) provide functionalities that are, to some extent at least, offered by apps that have, at some point or another, been preinstalled on many Android devices (notably Google Hangouts, Google Photos and Google+).

The Commission countered that communications apps were not appropriate counterexamples, because they benefit from network effects. But this overlooks the fact that the most successful communications and social media apps benefited from very limited network effects when they were launched, and that they succeeded despite the presence of competing pre-installed apps. Direct user downloads are thus a far more powerful vector of competition than the Commission cared to admit.

Similarly concerning is the Commission’s contention that paying OEMs or Mobile Network Operators (“MNOs”) to pre-install their search apps was not a viable alternative for Google’s rivals. Some of the reasons cited by the Commission to support this finding are particularly troubling.

For instance, the Commission claimed that high transaction costs prevented parties from concluding these pre installation deals. 

But pre-installation agreements are common in the smartphone industry. In recent years, Microsoft struck a deal with Samsung to pre-install some of its office apps on the Galaxy Note 10. It also paid Verizon to pre-install the Bing search app on a number of Samsung phones, in 2010. Likewise, a number of Russian internet companies have been in talks with Huawei to pre-install their apps on its devices. And Yahoo reached an agreement with Mozilla to make it the default search engine for its web browser. Transaction costs do not appear to  have been an obstacle in any of these cases.

The Commission also claimed that duplicating too many apps would cause storage space issues on devices. 

And yet, a back-of-the-envelope calculation suggests that storage space is unlikely to be a major issue. For instance, the Bing Search app has a download size of 24MB, whereas typical entry-level smartphones generally have an internal memory of at least 64GB (that can often be extended to more than 1TB with the addition of an SD card). The Bing Search app thus takes up less than one-thousandth of these devices’ internal storage. Granted, the Yahoo search app is slightly larger than Microsoft’s, weighing almost 100MB. But this is still insignificant compared to a modern device’s storage space.

Finally, the Commission claimed that rivals were contractually prevented from concluding exclusive pre-installation deals because Google’s own apps would also be pre-installed on devices.

However, while it is true that Google’s apps would still be present on a device, rivals could still pay for their applications to be set as default. Even Yandex – a plaintiff – recognized that this would be a valuable solution. In its own words (taken from the Commission’s decision):

Pre-installation alongside Google would be of some benefit to an alternative general search provider such as Yandex […] given the importance of default status and pre-installation on home screen, a level playing field will not be established unless there is a meaningful competition for default status instead of Google.

In short, the Commission failed to convincingly establish that Google’s contractual terms prevented as-efficient rivals from effectively distributing their applications on Android smartphones. The evidence it adduced was simply too thin to support anything close to that conclusion.

2. The threat of fragmentation

The Commission’s second theory of harm concerned the so-called “antifragmentation” agreements concluded between Google and OEMs. In a nutshell, Google only agreed to license the Google Search and Google Play apps to OEMs that sold “Android Compatible” devices (i.e. devices sold with a version of Android did not stray too far from Google’s most recent version).

According to Google, this requirement was necessary to limit the number of Android forks that were present on the market (as well as older versions of the standard Android). This, in turn, reduced development costs and prevented the Android platform from unraveling.

The Commission disagreed, arguing that Google’s anti-fragmentation provisions thwarted competition from potential Android forks (i.e. modified versions of the Android OS).

This conclusion raises at least two critical questions: The first is whether these agreements were necessary to ensure the survival and competitiveness of the Android platform, and the second is why “open” platforms should be precluded from partly replicating a feature that is essential to rival “closed” platforms, such as Apple’s iOS.

Let us start with the necessity, or not, of Google’s contractual terms. If fragmentation did indeed pose an existential threat to the Android ecosystem, and anti-fragmentation agreements averted this threat, then it is hard to make a case that they thwarted competition. The Android platform would simply not have been as viable without them.

The Commission dismissed this possibility, relying largely on statements made by Google’s rivals (many of whom likely stood to benefit from the suppression of these agreements). For instance, the Commission cited comments that it received from Yandex – one of the plaintiffs in the case:

(1166) The fact that fragmentation can bring significant benefits is also confirmed by third-party respondents to requests for information:

[…]

(2) Yandex, which stated: “Whilst the development of Android forks certainly has an impact on the fragmentation of the Android ecosystem in terms of additional development being required to adapt applications for various versions of the OS, the benefits of fragmentation outweigh the downsides…”

Ironically, the Commission relied on Yandex’s statements while, at the same time, it dismissed arguments made by Android app developers, on account that they were conflicted. In its own words:

Google attached to its Response to the Statement of Objections 36 letters from OEMs and app developers supporting Google’s views about the dangers of fragmentation […] It appears likely that the authors of the 36 letters were influenced by Google when drafting or signing those letters.

More fundamentally, the Commission’s claim that fragmentation was not a significant threat is at odds with an almost unanimous agreement among industry insiders.

For example, while it is not dispositive, a rapid search for the terms “Google Android fragmentation”, using the DuckDuckGo search engine, leads to results that cut strongly against the Commission’s conclusions. Of the ten first results, only one could remotely be construed as claiming that fragmentation was not an issue. The others paint a very different picture (below are some of the most salient excerpts):

“There’s a fairly universal perception that Android fragmentation is a barrier to a consistent user experience, a security risk, and a challenge for app developers.” (here)

“Android fragmentation, a problem with the operating system from its inception, has only become more acute an issue over time, as more users clamor for the latest and greatest software to arrive on their phones.” (here)

“Android Fragmentation a Huge Problem: Study.” (here)

“Google’s Android fragmentation fix still isn’t working at all.” (here)

“Does Google care about Android fragmentation? Not now—but it should.” (here).

“This is very frustrating to users and a major headache for Google… and a challenge for corporate IT,” Gold said, explaining that there are a large number of older, not fully compatible devices running various versions of Android.” (here)

Perhaps more importantly, one might question why Google should be treated differently than rivals that operate closed platforms, such as Apple, Microsoft and Blackberry (before the last two mostly exited the Mobile OS market). By definition, these platforms limit all potential forks (because they are based on proprietary software).

The Commission argued that Apple, Microsoft and Blackberry had opted to run “closed” platforms, which gave them the right to prevent rivals from copying their software.

While this answer has some superficial appeal, it is incomplete. Android may be an open source project, but this is not true of Google’s proprietary apps. Why should it be forced to offer them to rivals who would use them to undermine its platform? The Commission did not meaningfully consider this question.

And yet, industry insiders routinely compare the fragmentation of Apple’s iOS and Google’s Android OS, in order to gage the state of competition between both firms. For instance, one commentator noted:

[T]he gap between iOS and Android users running the latest major versions of their operating systems has never looked worse for Google.

Likewise, an article published in Forbes concluded that Google’s OEMs were slow at providing users with updates, and that this might drive users and developers away from the Android platform:

For many users the Android experience isn’t as up-to-date as Apple’s iOS. Users could buy the latest Android phone now and they may see one major OS update and nothing else. […] Apple users can be pretty sure that they’ll get at least two years of updates, although the company never states how long it intends to support devices.

However this problem, in general, makes it harder for developers and will almost certainly have some inherent security problems. Developers, for example, will need to keep pushing updates – particularly for security issues – to many different versions. This is likely a time-consuming and expensive process.

To recap, the Commission’s decision paints a world that is either black or white: either firms operate closed platforms, and they are then free to limit fragmentation as they see fit, or they create open platforms, in which case they are deemed to have accepted much higher levels of fragmentation.

This stands in stark contrast to industry coverage, which suggests that users and developers of both closed and open platforms care a great deal about fragmentation, and demand that measures be put in place to address it. If this is true, then the relative fragmentation of open and closed platforms has an important impact on their competitive performance, and the Commission was wrong to reject comparisons between Google and its closed ecosystem rivals. 

3. Google’s revenue sharing agreements

The last part of the Commission’s case centered on revenue sharing agreements between Google and its OEMs/MNOs. Google paid these parties to exclusively place its search app on the homescreen of their devices. According to the Commission, these payments reduced OEMs and MNOs’ incentives to pre-install competing general search apps.

However, to reach this conclusion, the Commission had to make the critical (and highly dubious) assumption that rivals could not match Google’s payments.

To get to that point, it notably assumed that rival search engines would be unable to increase their share of mobile search results beyond their share of desktop search results. The underlying intuition appears to be that users who freely chose Google Search on desktop (Google Search & Chrome are not set as default on desktop PCs) could not be convinced to opt for a rival search engine on mobile.

But this ignores the possibility that rivals might offer an innovative app that swayed users away from their preferred desktop search engine. 

More importantly, this reasoning cuts against the Commission’s own claim that pre-installation and default placement were critical. If most users, dismiss their device’s default search app and search engine in favor of their preferred ones, then pre-installation and default placement are largely immaterial, and Google’s revenue sharing agreements could not possibly have thwarted competition (because they did not prevent users from independently installing their preferred search app). On the other hand, if users are easily swayed by default placement, then there is no reason to believe that rivals could not exceed their desktop market share on mobile phones.

The Commission was also wrong when it claimed that rival search engines were at a disadvantage because of the structure of Google’s revenue sharing payments. OEMs and MNOs allegedly lost all of their payments from Google if they exclusively placed a rival’s search app on the home screen of a single line of handsets.

The key question is the following: could Google automatically tilt the scales to its advantage by structuring the revenue sharing payments in this way? The answer appears to be no. 

For instance, it has been argued that exclusivity may intensify competition for distribution. Conversely, other scholars have claimed that exclusivity may deter entry in network industries. Unfortunately, the Commission did not examine whether Google’s revenue sharing agreements fell within this category. 

It thus provided insufficient evidence to support its conclusion that the revenue sharing agreements reduced OEMs’ (and MNOs’) incentives to pre-install competing general search apps, rather than merely increasing competition “for the market”.

4. Conclusion

To summarize, the Commission overestimated the effect that Google’s behavior might have on its rivals. It almost entirely ignored the justifications that Google put forward and relied heavily on statements made by its rivals. The result is a one-sided decision that puts undue strain on the Android Business model, while providing few, if any, benefits in return.

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

(Left, Android 10 Website; Right, iOS 13 Website)

In a previous post, I argued that the Commission failed to adequately define the relevant market in its recently published Google Android decision

This improper market definition might not be so problematic if the Commission had then proceeded to undertake a detailed (and balanced) assessment of the competitive conditions that existed in the markets where Google operates (including the competitive constraints imposed by Apple). 

Unfortunately, this was not the case. The following paragraphs respond to some of the Commission’s most problematic arguments regarding the existence of barriers to entry, and the absence of competitive constraints on Google’s behavior.

The overarching theme is that the Commission failed to quantify its findings and repeatedly drew conclusions that did not follow from the facts cited. As a result, it was wrong to conclude that Google faced little competitive pressure from Apple and other rivals.

1. Significant investments and network effects ≠ barriers to entry

In its decision, the Commission notably argued that significant investments (millions of euros) are required to set up a mobile OS and App store. It also argued that market for licensable mobile operating systems gave rise to network effects. 

But contrary to the Commission’s claims, neither of these two factors is, in and of itself, sufficient to establish the existence of barriers to entry (even under EU competition law’s loose definition of the term, rather than Stigler’s more technical definition)

Take the argument that significant investments are required to enter the mobile OS market.

The main problem is that virtually every market requires significant investments on the part of firms that seek to enter. Not all of these costs can be seen as barriers to entry, or the concept would lose all practical relevance. 

For example, purchasing a Boeing 737 Max airplane reportedly costs at least $74 million. Does this mean that incumbents in the airline industry are necessarily shielded from competition? Of course not. 

Instead, the relevant question is whether an entrant with a superior business model could access the capital required to purchase an airplane and challenge the industry’s incumbents.

Returning to the market for mobile OSs, the Commission should thus have questioned whether as-efficient rivals could find the funds required to produce a mobile OS. If the answer was yes, then the investments highlighted by the Commission were largely immaterial. As it happens, several firms have indeed produced competing OSs, including CyanogenMod, LineageOS and Tizen.

The same is true of Commission’s conclusion that network effects shielded Google from competitors. While network effects almost certainly play some role in the mobile OS and app store markets, it does not follow that they act as barriers to entry in competition law terms. 

As Paul Belleflamme recently argued, it is a myth that network effects can never be overcome. And as I have written elsewhere, the most important question is whether users could effectively coordinate their behavior and switch towards a superior platform, if one arose (See also Dan Spulber’s excellent article on this point).

The Commission completely ignored this critical interrogation during its discussion of network effects.

2. The failure of competitors is not proof of barriers to entry

Just as problematically, the Commission wrongly concluded that the failure of previous attempts to enter the market was proof of barriers to entry. 

This is the epitome of the Black Swan fallacy (i.e. inferring that all swans are white because you have never seen a relatively rare, but not irrelevant, black swan).

The failure of rivals is equally consistent with any number of propositions: 

  • There were indeed barriers to entry; 
  • Google’s products were extremely good (in ways that rivals and the Commission failed to grasp); 
  • Google responded to intense competitive pressure by continuously improving its product (and rivals thus chose to stay out of the market); 
  • Previous rivals were persistently inept (to take the words of Oliver Williamson); etc. 

The Commission did not demonstrate that its own inference was the right one, nor did it even demonstrate any awareness that other explanations were at least equally plausible.

3. First mover advantage?

Much of the same can be said about the Commission’s observation that Google enjoyed a first mover advantage

The elephant in the room is that Google was not the first mover in the smartphone market (and even less so in the mobile phone industry). The Commission attempted to sidestep this uncomfortable truth by arguing that Google was the first mover in the Android app store market. It then concluded that Google had an advantage because users were familiar with Android’s app store.

To call this reasoning “naive” would be too kind. Maybe consumers are familiar with Google’s products today, but they certainly weren’t when Google entered the market. 

Why would something that did not hinder Google (i.e. users’ lack of familiarity with its products, as opposed to those of incumbents such as Nokia or Blackberry) have the opposite effect on its future rivals? 

Moreover, even if rivals had to replicate Android’s user experience (and that of its app store) to prove successful, the Commission did not show that there was anything that prevented them from doing so — a particularly glaring omission given the open-source nature of the Android OS.

The result is that, at best, the Commission identified a correlation but not causality. Google may arguably have been the first, and users might have been more familiar with its offerings, but this still does not prove that Android flourished (and rivals failed) because of this.

4. It does not matter that users “do not take the OS into account” when they purchase a device

The Commission also concluded that alternatives to Android (notably Apple’s iOS and App Store) exercised insufficient competitive constraints on Google. Among other things, it argued that this was because users do not take the OS into account when they purchase a smartphone (so Google could allegedly degrade Android without fear of losing users to Apple)..

In doing so, the Commission failed to grasp that buyers might base their purchases on a devices’ OS without knowing it.

Some consumers will simply follow the advice of a friend, family member or buyer’s guide. Acutely aware of their own shortcomings, they thus rely on someone else who does take the phone’s OS into account. 

But even when they are acting independently, unsavvy consumers may still be driven by technical considerations. They might rely on a brand’s reputation for providing cutting edge devices (which, per the Commission, is the most important driver of purchase decisions), or on a device’s “feel” when they try it in a showroom. In both cases, consumers’ choices could indirectly be influenced by a phone’s OS.

In more technical terms, a phone’s hardware and software are complementary goods. In these settings, it is extremely difficult to attribute overall improvements to just one of the two complements. For instance, a powerful OS and chipset are both equally necessary to deliver a responsive phone. The fact that consumers may misattribute a device’s performance to one of these two complements says nothing about their underlying contribution to a strong end-product (which, in turn, drives purchase decisions). Likewise, battery life is reportedly one of the most important features for users, yet few realize that a phone’s OS has a large impact on it.

Finally, if consumers were really indifferent to the phone’s operating system, then the Commission should have dropped at least part of its case against Google. The Commission’s claim that Google’s anti-fragmentation agreements harmed consumers (by reducing OS competition) has no purchase if Android is provided free of charge and consumers are indifferent to non-price parameters, such as the quality of a phone’s OS. 

5. Google’s users were not “captured”

Finally, the Commission claimed that consumers are loyal to their smartphone brand and that competition for first time buyers was insufficient to constrain Google’s behavior against its “captured” installed base.

It notably found that 82% of Android users stick with Android when they change phones (compared to 78% for Apple), and that 75% of new smartphones are sold to existing users. 

The Commission asserted, without further evidence, that these numbers proved there was little competition between Android and iOS.

But is this really so? In almost all markets consumers likely exhibit at least some loyalty to their preferred brand. At what point does this become an obstacle to interbrand competition? The Commission offered no benchmark mark against which to assess its claims.

And although inter-industry comparisons of churn rates should be taken with a pinch of salt, it is worth noting that the Commission’s implied 18% churn rate for Android is nothing out of the ordinary (see, e.g., here, here, and here), including for industries that could not remotely be called anticompetitive.

To make matters worse, the Commission’s own claimed figures suggest that a large share of sales remained contestable (roughly 39%).

Imagine that, every year, 100 devices are sold in Europe (75 to existing users and 25 to new users, according to the Commission’s figures). Imagine further that the installed base of users is split 76–24 in favor of Android. Under the figures cited by the Commission, it follows that at least 39% of these sales are contestable.

According to the Commission’s figures, there would be 57 existing Android users (76% of 75) and 18 Apple users (24% of 75), of which roughly 10 (18%) and 4 (22%), respectively, switch brands in any given year. There would also be 25 new users who, even according to the Commission, do not display brand loyalty. The result is that out of 100 purchasers, 25 show no brand loyalty and 14 switch brands. And even this completely ignores the number of consumers who consider switching but choose not to after assessing the competitive options.

Conclusion

In short, the preceding paragraphs argue that the Commission did not meet the requisite burden of proof to establish Google’s dominance. Of course, it is one thing to show that the Commission’s reasoning was unsound (it is) and another to establish that its overall conclusion was wrong.

At the very least, I hope these paragraphs will convey a sense that the Commission loaded the dice, so to speak. Throughout the first half of its lengthy decision, it interpreted every piece of evidence against Google, drew significant inferences from benign pieces of information, and often resorted to circular reasoning.

The following post in this blog series argues that these errors also permeate the Commission’s analysis of Google’s allegedly anticompetitive behavior.