Intermediaries may not be the consumer welfare hero we want, but more often than not, they are one that we need.
In policy discussions about the digital economy, a background assumption that frequently underlies the discourse is that intermediaries and centralization always and only serve as a cost to consumers, and to society more generally. Thus, one commonly sees arguments that consumers would be better off if they could freely combine products from different trading partners. According to this logic, bundled goods, walled gardens, and other intermediaries are always to be regarded with suspicion, while interoperability, open source, and decentralization are laudable features of any market.
However, as with all economic goods, intermediation offers both costs and benefits. The challenge for market players is to assess these tradeoffs and, ultimately, to produce the optimal level of intermediation.
As one example, some observers assume that purchasing food directly from a producer benefits consumers because intermediaries no longer take a cut of the final purchase price. But this overlooks the tremendous efficiencies supermarkets can achieve in terms of cost savings, reduced carbon emissions (because consumers make fewer store trips), and other benefits that often outweigh the costs of intermediation.
The same anti-intermediary fallacy is plain to see in countless other markets. For instance, critics readily assume that insurance, mortgage, and travel brokers are just costly middlemen.
This unduly negative perception is perhaps even more salient in the digital world. Policymakers are quick to conclude that consumers are always better off when provided with “more choice.” Draft regulations of digital platforms have been introduced on both sides of the Atlantic that repeat this faulty argument ad nauseam, as do some antitrust decisions.
Even the venerable Tyler Cowen recently appeared to sing the praises of decentralization, when discussing the future of Web 3.0:
One person may think “I like the DeFi options at Uniswap,” while another may say, “I am going to use the prediction markets over at Hedgehog.” In this scenario there is relatively little intermediation and heavy competition for consumer attention. Thus most of the gains from competition accrue to the users. …
… I don’t know if people are up to all this work (or is it fun?). But in my view this is the best-case scenario — and the most technologically ambitious. Interestingly, crypto’s radical ability to disintermediate, if extended to its logical conclusion, could bring about a radical equalization of power that would lower the prices and values of the currently well-established crypto assets, companies and platforms.
While disintermediation certainly has its benefits, critics often gloss over its costs. For example, scams are practically nonexistent on Apple’s “centralized” App Store but are far more prevalent with Web3 services. Apple’s “power” to weed out nefarious actors certainly contributes to this difference. Similarly, there is a reason that “middlemen” like supermarkets and travel agents exist in the first place. They notably perform several complex tasks (e.g., searching for products, negotiating prices, and controlling quality) that leave consumers with a manageable selection of goods.
Returning to the crypto example, besides being a renowned scholar, Tyler Cowen is also an extremely savvy investor. What he sees as fun investment choices may be nightmarish (and potentially dangerous) decisions for less sophisticated consumers. The upshot is that intermediaries are far more valuable than they are usually given credit for.
Bringing People Together
The reason intermediaries (including online platforms) exist is to reduce transaction costs that suppliers and customers would face if they tried to do business directly. As Daniel F. Spulber argues convincingly:
Markets have two main modes of organization: decentralized and centralized. In a decentralized market, buyers and sellers match with each other and determine transaction prices. In a centralized market, firms act as intermediaries between buyers and sellers.
[W]hen there are many buyers and sellers, there can be substantial transaction costs associated with communication, search, bargaining, and contracting. Such transaction costs can make it more difficult to achieve cross-market coordination through direct communication. Intermediary firms have various means of reducing transaction costs of decentralized coordination when there are many buyers and sellers.
This echoes the findings of Nobel laureate Ronald Coase, who observed that firms emerge when they offer a cheaper alternative to multiple bilateral transactions:
The main reason why it is profitable to establish a firm would seem to be that there is a cost of using the price mechanism. The most obvious cost of “organising ” production through the price mechanism is that of discovering what the relevant prices are. […] The costs of negotiating and concluding a separate contract for each exchange transaction which takes place on a market must also be taken into account.
Economists generally agree that online platforms also serve this cost-reduction function. For instance, David Evans and Richard Schmalensee observe that:
Multi-sided platforms create value by bringing two or more different types of economic agents together and facilitating interactions between them that make all agents better off.
It’s easy to see the implications for today’s competition-policy debates, and for the online intermediaries that many critics would like to see decentralized. Particularly salient examples include app store platforms (such as the Apple App Store and the Google Play Store); online retail platforms (such as Amazon Marketplace); and online travel agents (like Booking.com and Expedia). Competition policymakers have embarked on countless ventures to “open up” these platforms to competition, essentially moving them further toward disintermediation. In most of these cases, however, policymakers appear to be fighting these businesses’ very raison d’être.
For example, the purpose of an app store is to curate the software that users can install and to offer payment solutions; in exchange, the store receives a cut of the proceeds. If performing these tasks created no value, then to a first approximation, these services would not exist. Users would simply download apps via their web browsers, and the most successful smartphones would be those that allowed users to directly install apps (“sideloading,” to use the more technical terms). Forcing these platforms to “open up” and become neutral is antithetical to the value proposition they offer.
Calls for retail and travel platforms to stop offering house brands or displaying certain products more favorably are equally paradoxical. Consumers turn to these platforms because they want a selection of goods. If that was not the case, users could simply bypass the platforms and purchase directly from independent retailers or hotels.Critics sometimes retort that some commercial arrangements, such as “most favored nation” clauses, discourage consumers from doing exactly this. But that claim only reinforces the point that online platforms must create significant value, or they would not be able to obtain such arrangements in the first place.
All of this explains why characterizing these firms as imposing a “tax” on their respective ecosystems is so deeply misleading. The implication is that platforms are merely passive rent extractors that create no value. Yet, barring the existence of market failures, both their existence and success is proof to the contrary. To argue otherwise places no faith in the ability of firms and consumers to act in their own self-interest.
A Little Evolution
This last point is even more salient when seen from an evolutionary standpoint. Today’s most successful intermediaries—be they online platforms or more traditional brick-and-mortar firms like supermarkets—mostly had to outcompete the alternative represented by disintermediated bilateral contracts.
Critics of intermediaries rarely contemplate why the app-store model outpaced the more heavily disintermediated software distribution of the desktop era. Or why hotel-booking sites exist, despite consumers’ ability to use search engines, hotel websites, and other product-search methods that offer unadulterated product selections. Or why mortgage brokers are so common when borrowers can call local banks directly. The list is endless.
Digital markets could have taken a vast number of shapes, so why have they systematically gravitated towards those very characteristics that authorities condemn? For instance, if market tipping and consumer lock-in are so problematic, why is it that new corners of the digital economy continue to emerge via closed platforms, as opposed to collaborative ones? Indeed, if recent commentary is to be believed, it is the latter that should succeed because they purportedly produce greater gains from trade. And if consumers and platforms cannot realize these gains by themselves, then we should see [other] intermediaries step into the breach – i.e. arbitrage. This does not seem to be happening in the digital economy. The naïve answer is to say that this is precisely the problem, the harder one is to actually understand why.
Fiat Versus Emergent Disintermediation
All of this is not to say that intermediaries are perfect, or that centralization always beats decentralization. Instead, the critical point is about the competitive process. There are vast differences between centralization that stems from government fiat and that which emerges organically.
(Dis)intermediation is an economic good. Markets thus play a critical role in deciding how much or little of it is provided. Intermediaries must charge fees that cover their costs, while bilateral contracts entail transaction costs. In typically Hayekian fashion, suppliers and buyers will weigh the costs and benefits of these options.
Intermediaries are most likely to emerge in markets prone to excessive transaction costs and competitive processes ensure that only valuable intermediaries survive. Accordingly, there is no guarantee that government-mandated disintermediation would generate net benefits in any given case.
Of course, the market does not always work perfectly. Sometimes, market failures give rise to excessive (or insufficient) centralization. And policymakers should certainly be attentive to these potential problems and address them on a case-by-case basis. But there is little reason to believe that today’s most successful intermediaries are the result of market failures, and it is thus critical that policymakers do not undermine the valuable role they perform.
For example, few believe that supermarkets exist merely because government failures (such as excessive regulation) or market failures (such as monopolization) prevent the emergence of smaller rivals. Likewise, the app-store model is widely perceived as an improvement over previous software platforms; few consumers appear favorably disposed toward its replacement with sideloading of apps (for example, few Android users choose to sideload apps rather than purchase them via the Google Play Store). In fact, markets appear to be moving in the opposite direction: even traditional software platforms such as Windows OS increasingly rely on closed stores to distribute software on their platforms.
More broadly, this same reasoning can (and has) been applied to other social institutions, such as the modern family. For example, the late Steven Horwitz observed that family structures have evolved in order to adapt to changing economic circumstances. Crucially, this process is driven by the same cost-benefit tradeoff that we see in markets. In both cases, agents effectively decide which functions are better performed within a given social structure, and which ones are more efficiently completed outside of it.
Returning to Tyler Cowen’s point about the future of Web3, the case can be made that whatever level of centralization ultimately emerges is most likely the best case scenario. Sure, there may be some market failures and suboptimal outcomes along the way, but they ultimately pale in comparison to the most pervasive force: namely, economic agents’ ability to act in what they perceive to be their best interest. To put it differently, if Web3 spontaneously becomes as centralized as Web 2.0 has been, that would be testament to the tremendous role that intermediaries play throughout the economy.
The American Choice and Innovation Online Act (previously called the Platform Anti-Monopoly Act), introduced earlier this summer by U.S. Rep. David Cicilline (D-R.I.), would significantly change the nature of digital platforms and, with them, the internet itself. Taken together, the bill’s provisions would turn platforms into passive intermediaries, undermining many of the features that make them valuable to consumers. This seems likely to remain the case even after potential revisions intended to minimize the bill’s unintended consequences.
In its current form, the bill is split into two parts that each is dangerous in its own right. The first, Section 2(a), would prohibit almost any kind of “discrimination” by platforms. Because it is so open-ended, lawmakers might end up removing it in favor of the nominally more focused provisions of Section 2(b), which prohibit certain named conduct. But despite being more specific, this section of the bill is incredibly far-reaching and would effectively ban swaths of essential services.
Section 2(a) essentially prohibits any behavior by a covered platform that would advantage that platform’s services over any others that also uses that platform; it characterizes this preferencing as “discrimination.”
As we wrote when the House Judiciary Committee’s antitrust bills were first announced, this prohibition on “discrimination” is so broad that, if it made it into law, it would prevent platforms from excluding or disadvantaging any product of another business that uses the platform or advantaging their own products over those of their competitors.
The underlying assumption here is that platforms should be like telephone networks: providing a way for different sides of a market to communicate with each other, but doing little more than that. When platforms do do more—for example, manipulating search results to favor certain businesses or to give their own products prominence —it is seen as exploitative “leveraging.”
But consumers often want platforms to be more than just a telephone network or directory, because digital markets would be very difficult to navigate without some degree of “discrimination” between sellers. The Internet is so vast and sellers are often so anonymous that any assistance which helps you choose among options can serve to make it more navigable. As John Gruber put it:
From what I’ve seen over the last few decades, the quality of the user experience of every computing platform is directly correlated to the amount of control exerted by its platform owner. The current state of the ownerless world wide web speaks for itself.
Sometimes, this manifests itself as “self-preferencing” of another service, to reduce additional time spent searching for the information you want. When you search for a restaurant on Google, it can be very useful to get information like user reviews, the restaurant’s phone number, a button on mobile to phone them directly, estimates of how busy it is, and a link to a Maps page to see how to actually get there.
This is, undoubtedly, frustrating for competitors like Yelp, who would like this information not to be there and for users to have to click on either a link to Yelp or a link to Google Maps. But whether it is good or bad for Yelp isn’t relevant to whether it is good for users—and it is at least arguable that it is, which makes a blanket prohibition on this kind of behavior almost inevitably harmful.
If it isn’t obvious why removing this kind of feature would be harmful for users, ask yourself why some users search in Yelp’s app directly for this kind of result. The answer, I think, is that Yelp gives you all the information above that Google does (and sometimes is better, although I tend to trust Google Maps’ reviews over Yelp’s), and it’s really convenient to have all that on the same page. If Google could not provide this kind of “rich” result, many users would probably stop using Google Search to look for restaurant information in the first place, because a new friction would have been added that made the experience meaningfully worse. Removing that option would be good for Yelp, but mainly because it removes a competitor.
If all this feels like stating the obvious, then it should highlight a significant problem with Section 2(a) in the Cicilline bill: it prohibits conduct that is directly value-adding for consumers, and that creates competition for dedicated services like Yelp that object to having to compete with this kind of conduct.
Some or all of this behavior would be prohibited under Section 2(a) of the Cicilline bill. Combined with the bill’s presumption that conduct must be defended affirmatively—that is, the platform is presumed guilty unless it can prove that the challenged conduct is pro-competitive, which may be very difficult to do—and the bill could prospectively eliminate a huge range of socially valuable behavior.
Supporters of the bill have already been left arguing that the law simply wouldn’t be enforced in these cases of benign discrimination. But this would hardly be an improvement. It would mean the Federal Trade Commission (FTC) and U.S. Justice Department (DOJ) have tremendous control over how these platforms are built, since they could challenge conduct in virtually any case. The regulatory uncertainty alone would complicate the calculus for these firms as they refine, develop, and deploy new products and capabilities.
So one potential compromise might be to do away with this broad-based rule and proscribe specific kinds of “discriminatory” conduct instead. This approach would involve removing Section 2(a) from the bill but retaining Section 2(b), which enumerates 10 practices it deems to be “other discriminatory conduct.” This may seem appealing, as it would potentially avoid the worst abuses of the broad-based prohibition. In practice, however, it would carry many of the same problems. In fact, many of 2(b)’s provisions appear to go even further than 2(a), and would proscribe even more procompetitive conduct that consumers want.
Sections 2(b)(1) and 2(b)(9)
The wording of these provisions is extremely broad and, as drafted, would seem to challenge even the existence of vertically integrated products. As such, these prohibitions are potentially even more extensive and invasive than Section 2(a) would have been. Even a narrower reading here would seem to preclude safety and privacy features that are valuable to many users. iOS’s sandboxing of apps, for example, serves to limit the damage that a malware app can do on a user’s device precisely because of the limitations it imposes on what other features and hardware the app can access.
Section 2(b)(2)
This provision would preclude a firm from conditioning preferred status on use of another service from that firm. This would likely undermine the purpose of platforms, which is to absorb and counter some of the risks involved in doing business online. An example of this is Amazon’s tying eligibility for its Prime program to sellers that use Amazon’s delivery service (FBA – Fulfilled By Amazon). The bill seems to presume in an example like this that Amazon is leveraging its power in the market—in the form of the value of the Prime label—to profit from delivery. But Amazon could, and already does, charge directly for listing positions; it’s unclear why it would benefit from charging via FBA when it could just charge for the Prime label.
An alternate, simpler explanation is that FBA improves the quality of the service, by granting customers greater assurance that a Prime product will arrive when Amazon says it will. Platforms add value by setting out rules and providing services that reduce the uncertainties between buyers and sellers they’d otherwise experience if they transacted directly with each other. This section’s prohibition—which, as written, would seem to prevent any kind of quality assurance—likely would bar labelling by a platform, even where customers explicitly want it.
Section 2(b)(3)
As written, this would prohibit platforms from using aggregated data to improve their services at all. If Apple found that 99% of its users uninstalled an app immediately after it was installed, it would be reasonable to conclude that the app may be harmful or broken in some way, and that Apple should investigate. This provision would ban that.
Sections 2(b)(4) and 2(b)(6)
These two provisions effectively prohibit a platform from using information it does not also provide to sellers. Such prohibitions ignore the fact that it is often good for sellers to lack certain information, since withholding information can prevent abuse by malicious users. For example, a seller may sometimes try to bribe their customers to post positive reviews of their products, or even threaten customers who have posted negative ones. Part of the role of a platform is to combat that kind of behavior by acting as a middleman and forcing both consumer users and business users to comply with the platform’s own mechanisms to control that kind of behavior.
If this seems overly generous to platforms—since, obviously, it gives them a lot of leverage over business users—ask yourself why people use platforms at all. It is not a coincidence that people often prefer Amazon to dealing with third-party merchants and having to navigate those merchants’ sites themselves. The assurance that Amazon provides is extremely valuable for users. Much of it comes from the company’s ability to act as a middleman in this way, lowering the transaction costs between buyers and sellers.
Section 2(b)(5)
This provision restricts the treatment of defaults. It is, however, relatively restrained when compared to, for example, the DOJ’s lawsuit against Google, which treats as anticompetitive even payment for defaults that can be changed. Still, many of the arguments that apply in that case also apply here: default status for apps can be a way to recoup income foregone elsewhere (e.g., a browser provided for free that makes its money by selling the right to be the default search engine).
Section 2(b)(7)
This section gets to the heart of why “discrimination” can often be procompetitive: that it facilitates competition between platforms. The kind of self-preferencing that this provision would prohibit can allow firms that have a presence in one market to extend that position into another, increasing competition in the process. Both Apple and Amazon have used their customer bases in smartphones and e-commerce, respectively, to grow their customer bases for video streaming, in competition with Netflix, Google’s YouTube, cable television, and each other. If Apple designed a search engine to compete with Google, it would do exactly the same thing, and we would be better off because of it. Restricting this kind of behavior is, perversely, exactly what you would do if you wanted to shield these incumbents from competition.
Section 2(b)(8)
As with other provisions, this one would preclude one of the mechanisms by which platforms add value: creating assurance for customers about the products they can expect if they visit the platform. Some of this relates to child protection; some of the most frustrating stories involve children being overcharged when they use an iPhone or Android app, and effectively being ripped off because of poor policing of the app (or insufficiently strict pricing rules by Apple or Google). This may also relate to rules that state that the seller cannot offer a cheaper product elsewhere (Amazon’s “General Pricing Rule” does this, for example). Prohibiting this would simply impose a tax on customers who cannot shop around and would prefer to use a platform that they trust has the lowest prices for the item they want.
Section 2(b)(10)
Ostensibly a “whistleblower” provision, this section could leave platforms with no recourse, not even removing a user from its platform, in response to spurious complaints intended purely to extract value for the complaining business rather than to promote competition. On its own, this sort of provision may be fairly harmless, but combined with the provisions above, it allows the bill to add up to a rent-seekers’ charter.
Conclusion
In each case above, it’s vital to remember that a reversed burden of proof applies. So, there is a high chance that the law will side against the defendant business, and a large downside for conduct that ends up being found to violate these provisions. That means that platforms will likely err on the side of caution in many cases, avoiding conduct that is ambiguous, and society will probably lose a lot of beneficial behavior in the process.
Put together, the provisions undermine much of what has become an Internet platform’s role: to act as an intermediary, de-risk transactions between customers and merchants who don’t know each other, and tweak the rules of the market to maximize its attractiveness as a place to do business. The “discrimination” that the bill would outlaw is, in practice, behavior that makes it easier for consumers to navigate marketplaces of extreme complexity and uncertainty, in which they often know little or nothing about the firms with whom they are trying to transact business.
Customers do not want platforms to be neutral, open utilities. They can choose platforms that are like that already, such as eBay. They generally tend to prefer ones like Amazon, which are not neutral and which carefully cultivate their service to be as streamlined, managed, and “discriminatory” as possible. Indeed, many of people’s biggest complaints with digital platforms relate to their openness: the fake reviews, counterfeit products, malware, and spam that come with letting more unknown businesses use your service. While these may be unavoidable by-products of running a platform, platforms compete on their ability to ferret them out. Customers are unlikely to thank legislators for regulating Amazon into being another eBay.
Interrogations concerning the role that economic theory should play in policy decisions are nothing new. Milton Friedman famously drew a distinction between “positive” and “normative” economics, notably arguing that theoretical models were valuable, despite their unrealistic assumptions. Kenneth Arrow and Gerard Debreu’s highly theoretical work on General Equilibrium Theory is widely acknowledged as one of the most important achievements of modern economics.
But for all their intellectual value and academic merit, the use of models to inform policy decisions is not uncontroversial. There is indeed a long and unfortunate history of influential economic models turning out to be poor depictions (and predictors) of real-world outcomes.
This raises a key question: should policymakers use economic models to inform their decisions and, if so, how? This post uses the economics of externalities to illustrate both the virtues and pitfalls of economic modeling. Throughout economic history, externalities have routinely been cited to support claims of market failure and calls for government intervention. However, as explained below, these fears have frequently failed to withstand empirical scrutiny.
Today, similar models are touted to support government intervention in digital industries. Externalities are notably said to prevent consumers from switching between platforms, allegedly leading to unassailable barriers to entry and deficient venture-capital investment. Unfortunately, as explained below, the models that underpin these fears are highly abstracted and far removed from underlying market realities.
Ultimately, this post argues that, while models provide a powerful way of thinking about the world, naïvely transposing them to real-world settings is misguided. This is not to say that models are useless—quite the contrary. Indeed, “falsified” models can shed powerful light on economic behavior that would otherwise prove hard to understand.
Bees
Fears surrounding economic externalities are as old as modern economics. For example, in the 1950s, economists routinely cited bee pollination as a source of externalities and, ultimately, market failure.
The basic argument was straightforward: Bees and orchards provide each other with positive externalities. Bees cross-pollinate flowers and orchards contain vast amounts of nectar upon which bees feed, thus improving honey yields. Accordingly, several famous economists argued that there was a market failure; bees fly where they please and farmers cannot prevent bees from feeding on their blossoming flowers—allegedly causing underinvestment in both. This led James Meade to conclude:
[T]he apple-farmer provides to the beekeeper some of his factors free of charge. The apple-farmer is paid less than the value of his marginal social net product, and the beekeeper receives more than the value of his marginal social net product.
If, then, apple producers are unable to protect their equity in apple-nectar and markets do not impute to apple blossoms their correct shadow value, profit-maximizing decisions will fail correctly to allocate resources at the margin. There will be failure “by enforcement.” This is what I would call an ownership externality. It is essentially Meade’s “unpaid factor” case.
It took more than 20 years and painstaking research by Steven Cheung to conclusively debunk these assertions. So how did economic agents overcome this “insurmountable” market failure?
The answer, it turns out, was extremely simple. While bees do fly where they please, the relative placement of beehives and orchards has a tremendous impact on both fruit and honey yields. This is partly because bees have a very limited mean foraging range (roughly 2-3km). This left economic agents with ample scope to prevent free-riding.
Using these natural sources of excludability, they built a web of complex agreements that internalize the symbiotic virtues of beehives and fruit orchards. To cite Steven Cheung’s research:
Pollination contracts usually include stipulations regarding the number and strength of the colonies, the rental fee per hive, the time of delivery and removal of hives, the protection of bees from pesticide sprays, and the strategic placing of hives. Apiary lease contracts differ from pollination contracts in two essential aspects. One is, predictably, that the amount of apiary rent seldom depends on the number of colonies, since the farmer is interested only in obtaining the rent per apiary offered by the highest bidder. Second, the amount of apiary rent is not necessarily fixed. Paid mostly in honey, it may vary according to either the current honey yield or the honey yield of the preceding year.
But what of neighboring orchards? Wouldn’t these entail a more complex externality (i.e., could one orchard free-ride on agreements concluded between other orchards and neighboring apiaries)? Apparently not:
Acknowledging the complication, beekeepers and farmers are quick to point out that a social rule, or custom of the orchards, takes the place of explicit contracting: during the pollination period the owner of an orchard either keeps bees himself or hires as many hives per area as are employed in neighboring orchards of the same type. One failing to comply would be rated as a “bad neighbor,” it is said, and could expect a number of inconveniences imposed on him by other orchard owners. This customary matching of hive densities involves the exchange of gifts of the same kind, which apparently entails lower transaction costs than would be incurred under explicit contracting, where farmers would have to negotiate and make money payments to one another for the bee spillover.
In short, not only did the bee/orchard externality model fail, but it failed to account for extremely obvious counter-evidence. Even a rapid flip through the Yellow Pages (or, today, a search on Google) would have revealed a vibrant market for bee pollination. In short, the bee externalities, at least as presented in economic textbooks, were merely an economic “fable.” Unfortunately, they would not be the last.
The Lighthouse
Lighthouses provide another cautionary tale. Indeed, Henry Sidgwick, A.C. Pigou, John Stuart Mill, and Paul Samuelson all cited the externalities involved in the provision of lighthouse services as a source of market failure.
Here, too, the problem was allegedly straightforward. A lighthouse cannot prevent ships from free-riding on its services when they sail by it (i.e., it is mostly impossible to determine whether a ship has paid fees and to turn off the lighthouse if that is not the case). Hence there can be no efficient market for light dues (lighthouses were seen as a “public good”). As Paul Samuelson famously put it:
Take our earlier case of a lighthouse to warn against rocks. Its beam helps everyone in sight. A businessman could not build it for a profit, since he cannot claim a price from each user. This certainly is the kind of activity that governments would naturally undertake.
He added that:
[E]ven if the operators were able—say, by radar reconnaissance—to claim a toll from every nearby user, that fact would not necessarily make it socially optimal for this service to be provided like a private good at a market-determined individual price. Why not? Because it costs society zero extra cost to let one extra ship use the service; hence any ships discouraged from those waters by the requirement to pay a positive price will represent a social economic loss—even if the price charged to all is no more than enough to pay the long-run expenses of the lighthouse.
More than a century after it was first mentioned in economics textbooks, Ronald Coase finally laid the lighthouse myth to rest—rebutting Samuelson’s second claim in the process.
What piece of evidence had eluded economists for all those years? As Coase observed, contemporary economists had somehow overlooked the fact that large parts of the British lighthouse system were privately operated, and had been for centuries:
[T]he right to operate a lighthouse and to levy tolls was granted to individuals by Acts of Parliament. The tolls were collected at the ports by agents (who might act for several lighthouses), who might be private individuals but were commonly customs officials. The toll varied with the lighthouse and ships paid a toll, varying with the size of the vessel, for each lighthouse passed. It was normally a rate per ton (say 1/4d or 1/2d) for each voyage. Later, books were published setting out the lighthouses passed on different voyages and the charges that would be made.
In other words, lighthouses used a simple physical feature to create “excludability” and prevent free-riding. The main reason ships require lighthouses is to avoid hitting rocks when they make their way to a port. By tying port fees and light dues, lighthouse owners—aided by mild government-enforced property rights—could easily earn a return on their investments, thus disproving the lighthouse free-riding myth.
Ultimately, this meant that a large share of the British lighthouse system was privately operated throughout the 19th century, and this share would presumably have been more pronounced if government-run “Trinity House” lighthouses had not crowded out private investment:
The position in 1820 was that there were 24 lighthouses operated by Trinity House and 22 by private individuals or organizations. But many of the Trinity House lighthouses had not been built originally by them but had been acquired by purchase or as the result of the expiration of a lease.
Of course, this system was not perfect. Some ships (notably foreign ones that did not dock in the United Kingdom) might free-ride on this arrangement. It also entailed some level of market power. The ability to charge light dues meant that prices were higher than the “socially optimal” baseline of zero (the marginal cost of providing light is close to zero). Though it is worth noting that tying port fees and light dues might also have decreased double marginalization, to the benefit of sailors.
Samuelson was particularly weary of this market power that went hand in hand with the private provision of public goods, including lighthouses:
Being able to limit a public good’s consumption does not make it a true-blue private good. For what, after all, are the true marginal costs of having one extra family tune in on the program? They are literally zero. Why then prevent any family which would receive positive pleasure from tuning in on the program from doing so?
However, as Coase explained, light fees represented only a tiny fraction of a ship’s costs. In practice, they were thus unlikely to affect market output meaningfully:
[W]hat is the gain which Samuelson sees as coming from this change in the way in which the lighthouse service is financed? It is that some ships which are now discouraged from making a voyage to Britain because of the light dues would in future do so. As it happens, the form of the toll and the exemptions mean that for most ships the number of voyages will not be affected by the fact that light dues are paid. There may be some ships somewhere which are laid up or broken up because of the light dues, but the number cannot be great, if indeed there are any ships in this category.
Samuelson’s critique also falls prey to the Nirvana Fallacy pointed out by Harold Demsetz: markets might not be perfect, but neither is government intervention. Market power and imperfect appropriability are the two (paradoxical) pitfalls of the first; “white elephants,” underinvestment, and lack of competition (and the information it generates) tend to stem from the latter.
Which of these solutions is superior, in each case, is an empirical question that early economists had simply failed to consider—assuming instead that market failure was systematic in markets that present prima facie externalities. In other words, models were taken as gospel without any circumspection about their relevance to real-world settings.
The Tragedy of the Commons
Externalities were also said to undermine the efficient use of “common pool resources,” such grazing lands, common irrigation systems, and fisheries—resources where one agent’s use diminishes that of others, and where exclusion is either difficult or impossible.
The most famous formulation of this problem is Garret Hardin’s highly influential (over 47,000 cites) “tragedy of the commons.” Hardin cited the example of multiple herdsmen occupying the same grazing ground:
The rational herdsman concludes that the only sensible course for him to pursue is to add another animal to his herd. And another; and another … But this is the conclusion reached by each and every rational herdsman sharing a commons. Therein is the tragedy. Each man is locked into a system that compels him to increase his herd without limit—in a world that is limited. Ruin is the destination toward which all men rush, each pursuing his own best interest in a society that believes in the freedom of the commons.
In more technical terms, each economic agent purportedly exerts an unpriced negative externality on the others, thus leading to the premature depletion of common pool resources. Hardin extended this reasoning to other problems, such as pollution and allegations of global overpopulation.
Although Hardin hardly documented any real-world occurrences of this so-called tragedy, his policy prescriptions were unequivocal:
The most important aspect of necessity that we must now recognize, is the necessity of abandoning the commons in breeding. No technical solution can rescue us from the misery of overpopulation. Freedom to breed will bring ruin to all.
As with many other theoretical externalities, empirical scrutiny revealed that these fears were greatly overblown. In her Nobel-winning work, Elinor Ostrom showed that economic agents often found ways to mitigate these potential externalities markedly. For example, mountain villages often implement rules and norms that limit the use of grazing grounds and wooded areas. Likewise, landowners across the world often set up “irrigation communities” that prevent agents from overusing water.
Along similar lines, Julian Morris and I conjecture that informal arrangements and reputational effects might mitigate opportunistic behavior in the standard essential patent industry.
These bottom-up solutions are certainly not perfect. Many common institutions fail—for example, Elinor Ostrom documents several problematic fisheries, groundwater basins and forests, although it is worth noting that government intervention was sometimes behind these failures. To cite but one example:
Several scholars have documented what occurred when the Government of Nepal passed the “Private Forest Nationalization Act” […]. Whereas the law was officially proclaimed to “protect, manage and conserve the forest for the benefit of the entire country”, it actually disrupted previously established communal control over the local forests. Messerschmidt (1986, p.458) reports what happened immediately after the law came into effect:
Nepalese villagers began freeriding — systematically overexploiting their forest resources on a large scale.
In any case, the question is not so much whether private institutions fail, but whether they do so more often than government intervention. be it regulation or property rights. In short, the “tragedy of the commons” is ultimately an empirical question: what works better in each case, government intervention, propertization, or emergent rules and norms?
More broadly, the key lesson is that it is wrong to blindly apply models while ignoring real-world outcomes. As Elinor Ostrom herself put it:
The intellectual trap in relying entirely on models to provide the foundation for policy analysis is that scholars then presume that they are omniscient observers able to comprehend the essentials of how complex, dynamic systems work by creating stylized descriptions of some aspects of those systems.
Dvorak Keyboards
In 1985, Paul David published an influential paper arguing that market failures undermined competition between the QWERTY and Dvorak keyboard layouts. This version of history then became a dominant narrative in the field of network economics, including works by Joseph Farrell & Garth Saloner, and Jean Tirole.
The basic claim was that QWERTY users’ reluctance to switch toward the putatively superior Dvorak layout exerted a negative externality on the rest of the ecosystem (and a positive externality on other QWERTY users), thus preventing the adoption of a more efficient standard. As Paul David put it:
Although the initial lead acquired by QWERTY through its association with the Remington was quantitatively very slender, when magnified by expectations it may well have been quite sufficient to guarantee that the industry eventually would lock in to a de facto QWERTY standard. […]
Competition in the absence of perfect futures markets drove the industry prematurely into standardization on the wrong system — where decentralized decision making subsequently has sufficed to hold it.
Unfortunately, many of the above papers paid little to no attention to actual market conditions in the typewriter and keyboard layout industries. Years later, Stan Liebowitz and Stephen Margolis undertook a detailed analysis of the keyboard layout market. They almost entirely rejected any notion that QWERTY prevailed despite it being the inferior standard:
Yet there are many aspects of the QWERTY-versus-Dvorak fable that do not survive scrutiny. First, the claim that Dvorak is a better keyboard is supported only by evidence that is both scant and suspect. Second, studies in the ergonomics literature find no significant advantage for Dvorak that can be deemed scientifically reliable. Third, the competition among producers of typewriters, out of which the standard emerged, was far more vigorous than is commonly reported. Fourth, there were far more typing contests than just the single Cincinnati contest. These contests provided ample opportunity to demonstrate the superiority of alternative keyboard arrangements. That QWERTY survived significant challenges early in the history of typewriting demonstrates that it is at least among the reasonably fit, even if not the fittest that can be imagined.
In short, there was little to no evidence supporting the view that QWERTY inefficiently prevailed because of network effects. The falsification of this narrative also weakens broader claims that network effects systematically lead to either excess momentum or excess inertia in standardization. Indeed, it is tempting to characterize all network industries with heavily skewed market shares as resulting from market failure. Yet the QWERTY/Dvorak story suggests that such a conclusion would be premature.
Killzones, Zoom, and TikTok
If you are still reading at this point, you might think that contemporary scholars would know better than to base calls for policy intervention on theoretical externalities. Alas, nothing could be further from the truth.
For instance, a recent paper by Sai Kamepalli, Raghuram Rajan and Luigi Zingales conjectures that the interplay between mergers and network externalities discourages the adoption of superior independent platforms:
If techies expect two platforms to merge, they will be reluctant to pay the switching costs and adopt the new platform early on, unless the new platform significantly outperforms the incumbent one. After all, they know that if the entering platform’s technology is a net improvement over the existing technology, it will be adopted by the incumbent after merger, with new features melded with old features so that the techies’ adjustment costs are minimized. Thus, the prospect of a merger will dissuade many techies from trying the new technology.
Although this key behavioral assumption drives the results of the theoretical model, the paper presents no evidence to support the contention that it occurs in real-world settings. Admittedly, the paper does present evidence of reduced venture capital investments after mergers involving large tech firms. But even on their own terms, this data simply does not support the authors’ behavioral assumption.
And this is no isolated example. Over the past couple of years, several scholars have called for more muscular antitrust intervention in networked industries. A common theme is that network externalities, switching costs, and data-related increasing returns to scale lead to inefficient consumer lock-in, thus raising barriers to entry for potential rivals (here, here, here).
But there are also countless counterexamples, where firms have easily overcome potential barriers to entry and network externalities, ultimately disrupting incumbents.
Zoom is one of the most salient instances. As I have written previously:
To get to where it is today, Zoom had to compete against long-established firms with vast client bases and far deeper pockets. These include the likes of Microsoft, Cisco, and Google. Further complicating matters, the video communications market exhibits some prima facie traits that are typically associated with the existence of network effects.
Along similar lines, Geoffrey Manne and Alec Stapp have put forward a multitude of other examples. These include: The demise of Yahoo; the disruption of early instant-messaging applications and websites; MySpace’s rapid decline; etc. In all these cases, outcomes do not match the predictions of theoretical models.
More recently, TikTok’s rapid rise offers perhaps the greatest example of a potentially superior social-networking platform taking significant market share away from incumbents. According to the Financial Times, TikTok’s video-sharing capabilities and its powerful algorithm are the most likely explanations for its success.
While these developments certainly do not disprove network effects theory, they eviscerate the common belief in antitrust circles that superior rivals are unable to overthrow incumbents in digital markets. Of course, this will not always be the case. As in the previous examples, the question is ultimately one of comparing institutions—i.e., do markets lead to more or fewer error costs than government intervention? Yet this question is systematically omitted from most policy discussions.
In Conclusion
My argument is not that models are without value. To the contrary, framing problems in economic terms—and simplifying them in ways that make them cognizable—enables scholars and policymakers to better understand where market failures might arise, and how these problems can be anticipated and solved by private actors. In other words, models alone cannot tell us that markets will fail, but they can direct inquiries and help us to understand why firms behave the way they do, and why markets (including digital ones) are organized in a given way.
In that respect, both the theoretical and empirical research cited throughout this post offer valuable insights for today’s policymakers.
For a start, as Ronald Coase famously argued in what is perhaps his most famous work, externalities (and market failure more generally) are a function of transaction costs. When these are low (relative to the value of a good), market failures are unlikely. This is perhaps clearest in the “Fable of the Bees” example. Given bees’ short foraging range, there were ultimately few real-world obstacles to writing contracts that internalized the mutual benefits of bees and orchards.
Perhaps more importantly, economic research sheds light on behavior that might otherwise be seen as anticompetitive. The rules and norms that bind farming/beekeeping communities, as well as users of common pool resources, could easily be analyzed as a cartel by naïve antitrust authorities. Yet externality theory suggests they play a key role in preventing market failure.
Along similar lines, mergers and acquisitions (as well as vertical integration, more generally) can reduce opportunism and other externalities that might otherwise undermine collaboration between firms (here, here and here). And much of the same is true for certain types of unilateral behavior. Tying video games to consoles (and pricing the console below cost) can help entrants overcome network externalities that might otherwise shield incumbents. Likewise, Google tying its proprietary apps to the open source Android operating system arguably enabled it to earn a return on its investments, thus overcoming the externality problem that plagues open source software.
All of this raises a tantalizing prospect that deserves far more attention than it is currently given in policy circles: authorities around the world are seeking to regulate the tech space. Draft legislation has notably been tabled in the United States, European Union and the United Kingdom. These draft bills would all make it harder for large tech firms to implement various economic hierarchies, including mergers and certain contractual arrangements.
This is highly paradoxical. If digital markets are indeed plagued by network externalities and high transaction costs, as critics allege, then preventing firms from adopting complex hierarchies—which have traditionally been seen as a way to solve externalities—is just as likely to exacerbate problems. In other words, like the economists of old cited above, today’s policymakers appear to be focusing too heavily on simple models that predict market failure, and far too little on the mechanisms that firms have put in place to thrive within this complex environment.
The bigger picture is that far more circumspection is required when using theoretical models in real-world policy settings. Indeed, as Harold Demsetz famously put it, the purpose of normative economics is not so much to identify market failures, but to help policymakers determine which of several alternative institutions will deliver the best outcomes for consumers:
This nirvana approach differs considerably from a comparative institution approach in which the relevant choice is between alternative real institutional arrangements. In practice, those who adopt the nirvana viewpoint seek to discover discrepancies between the ideal and the real and if discrepancies are found, they deduce that the real is inefficient. Users of the comparative institution approach attempt to assess which alternative real institutional arrangement seems best able to cope with the economic problem […].
In current discussions of technology markets, few words are heard more often than “platform.” Initial public offering (IPO) prospectuses use “platform” to describe a service that is bound to dominate a digital market. Antitrust regulators use “platform” to describe a service that dominates a digital market or threatens to do so. In either case, “platform” denotes power over price. For investors, that implies exceptional profits; for regulators, that implies competitive harm.
Conventional wisdom holds that platforms enjoy high market shares, protected by high barriers to entry, which yield high returns. This simple logic drives the market’s attribution of dramatically high valuations to dramatically unprofitable businesses and regulators’ eagerness to intervene in digital platform markets characterized by declining prices, increased convenience, and expanded variety, often at zero out-of-pocket cost. In both cases, “burning cash” today is understood as the path to market dominance and the ability to extract a premium from consumers in the future.
This logic is usually wrong.
The Overlooked Basics of Platform Economics
To appreciate this perhaps surprising point, it is necessary to go back to the increasingly overlooked basics of platform economics. A platform can refer to any service that matches two complementary populations. A search engine matches advertisers with consumers, an online music service matches performers and labels with listeners, and a food-delivery service matches restaurants with home diners. A platform benefits everyone by facilitating transactions that otherwise might never have occurred.
A platform’s economic value derives from its ability to lower transaction costs by funneling a multitude of individual transactions into a single convenient hub. In pursuit of minimum costs and maximum gains, users on one side of the platform will tend to favor the most popular platforms that offer the largest number of users on the other side of the platform. (There are partial exceptions to this rule when users value being matched with certain typesof other users, rather than just with more users.) These “network effects” mean that any successful platform market will always converge toward a handful of winners. This positive feedback effect drives investors’ exuberance and regulators’ concerns.
There is a critical point, however, that often seems to be overlooked.
Market share only translates into market power to the extent the incumbent is protected against entry within some reasonable time horizon. If Warren Buffett’s moat requirement is not met, market share is immaterial. If XYZ.com owns 100% of the online pet food delivery market but entry costs are asymptotic, then market power is negligible. There is another important limiting principle. In platform markets, the depth of the moat depends not only on competitors’ costs to enter the market, but users’ costs in switching from one platform to another or alternating between multiple platforms. If users can easily hop across platforms, then market share cannot confer market power given the continuous threat of user defection. Put differently: churn limits power over price.
Contrary to natural intuitions, this is why a platform market consisting of only a few leaders can still be intensely competitive, keeping prices low (down to and including $0) even if the number of competitors is low. It is often asserted, however, that users are typically locked into the dominant platform and therefore face high switching costs, which therefore implicitly satisfies the moat requirement. If that is true, then the “high churn” scenario is a theoretical curiosity and a leading platform’s high market share would be a reliable signal of market power. In fact, this common assumption likely describes the atypical case.
AWS and the Cloud Data-Storage Market
This point can be illustrated by considering the cloud data-storage market. This would appear to be an easy case where high switching costs (due to the difficulty in shifting data among storage providers) insulate the market leader against entry threats. Yet the real world does not conform to these expectations.
While Amazon Web Services pioneered the $100 billion-plus market and is still the clear market leader, it now faces vigorous competition from Microsoft Azure, Google Cloud, and other data-storage or other cloud-related services. This may reflect the fact that the data storage market is far from saturated, so new users are up for grabs and existing customers can mitigate lock-in by diversifying across multiple storage providers. Or it may reflect the fact that the market’s structure is fluid as a function of technological changes, enabling entry at formerly bundled portions of the cloud data-services package. While it is not always technologically feasible, the cloud storage market suggests that users’ resistance to platform capture can represent a competitive opportunity for entrants to challenge dominant vendors on price, quality, and innovation parameters.
The Surprising Instability of Platform Dominance
The instability of leadership positions in the cloud storage market is not exceptional.
Consider a handful of once-powerful platforms that were rapidly dethroned once challenged by a more efficient or innovative rival: Yahoo and Alta Vista in the search-engine market (displaced by Google); Netscape in the browser market (displaced by Microsoft’s Internet Explorer, then displaced by Google Chrome); Nokia and then BlackBerry in the mobile wireless-device market (displaced by Apple and Samsung); and Friendster in the social-networking market (displaced by Myspace, then displaced by Facebook). AOL was once thought to be indomitable; now it is mostly referenced as a vintage email address. The list could go on.
Overestimating platform dominance—or more precisely, assuming platform dominance without close factual inquiry—matters because it promotes overestimates of market power. That, in turn, cultivates both market and regulatory bubbles: investors inflate stock valuations while regulators inflate the risk of competitive harm.
DoorDash and the Food-Delivery Services Market
Consider the DoorDash IPO that launched in early December 2020. The market’s current approximately $50 billion valuation of a business that has been almost consistently unprofitable implicitly assumes that DoorDash will maintain and expand its position as the largest U.S. food-delivery platform, which will then yield power over price and exceptional returns for investors.
There are reasons to be skeptical. Even where DoorDash captures and holds a dominant market share in certain metropolitan areas, it still faces actual and potential competition from other food-delivery services, in-house delivery services (especially by well-resourced national chains), and grocery and other delivery services already offered by regional and national providers. There is already evidence of these expected responses to DoorDash’s perceived high delivery fees, a classic illustration of the disciplinary effect of competitive forces on the pricing choices of an apparently dominant market leader. These “supply-side” constraints imposed by competitors are compounded by “demand-side” constraints imposed by customers. Home diners incur no more than minimal costs when swiping across food-delivery icons on a smartphone interface, casting doubt that high market share is likely to translate in this context into market power.
Deliveroo and the Costs of Regulatory Autopilot
Just as the stock market can suffer from delusions of platform grandeur, so too some competition regulators appear to have fallen prey to the same malady.
A vivid illustration is provided by the 2019 decision by the Competition Markets Authority (CMA), the British competition regulator, to challenge Amazon’s purchase of a 16% stake in Deliveroo, one of three major competitors in the British food-delivery services market. This intervention provides perhaps the clearest illustration of policy action based on a reflexive assumption of market power, even in the face of little to no indication that the predicate conditions for that assumption could plausibly be satisfied.
Far from being a dominant platform, Deliveroo was (and is) a money-losing venture lagging behind money-losing Just Eat (now Just Eat Takeaway) and Uber Eats in the U.K. food-delivery services market. Even Amazon had previously closed its own food-delivery service in the U.K. due to lack of profitability. Despite Deliveroo’s distressed economic circumstances and the implausibility of any market power arising from Amazon’s investment, the CMA nonetheless elected to pursue the fullest level of investigation. While the transaction was ultimately approved in August 2020, this intervention imposed a 15-month delay and associated costs in connection with an investment that almost certainly bolstered competition in a concentrated market by funding a firm reportedly at risk of insolvency. This is the equivalent of a competition regulator driving in reverse.
Concluding Thoughts
There seems to be an increasingly common assumption in commentary by the press, policymakers, and even some scholars that apparently dominant platforms usually face little competition and can set, at will, the terms of exchange. For investors, this is a reason to buy; for regulators, this is a reason to intervene. This assumption is sometimes realized, and, in that case, antitrust intervention is appropriate whenever there is reasonable evidence that market power is being secured through something other than “competition on the merits.” However, several conditions must be met to support the market power assumption without which any such inquiry would be imprudent. Contrary to conventional wisdom, the economics and history of platform markets suggest that those conditions are infrequently satisfied.
Without closer scrutiny, reflexively equating market share with market power is prone to lead both investors and regulators astray.
Not surprisingly, we’ve discussed Coase quite a bit here at Truth on the Market. Follow this link to see our collected thoughts on Coase over the years.
Probably my favorite, and certainly most frequently quoted, of Coase’s many wise words is this:
One important result of this preoccupation with the monopoly problem is that if an economist finds something—a business practice of one sort or other—that he does not understand, he looks for a monopoly explanation. And as in this field we are very ignorant, the number of ununderstandable practices tends to be rather large, and the reliance on a monopoly explanation, frequent.
Of course this, a more generalized statement of the above from The Problem of Social Cost, is the essence of his work:
All solutions have costs, and there is no reason to suppose that governmental regulation is called for simply because the problem is not well handled by the market or the firm. Satisfactory views on policy can only come from a patient study of how, in practice, the market, firms and governments handle the problem of harmful effects…. It is my belief that economists, and policy-makers generally, have tended to over-estimate the advantages which come from governmental regulation. But this belief, even if justified, does not do more than suggest that government regulation should be curtailed. It does not tell us where the boundary line should be drawn. This, it seems to me, has to come from a detailed investigation of the actual results of handling the problem in different ways.
RSS - Posts