We are living, we are told, in an age of monopolies. The days when Standard Oil or U.S. Steel commanded the economy and ran it to their liking may be long gone. But unlock your smartphone and, critics argue, the glowing icons you see represent a group of monopolists every bit as powerful and entrenched. And the problem is not just with trillion-dollar technology platforms. A growing gap between the most profitable and productive firms and the laggards can be seen in most countries and sectors.

For the past decade, there has been a groundswell of opinion about the institutional fix needed to deal with decreasing competition among firms. At its heart are two ideas. The first is that competition policy has been heading in the wrong direction for four decades, and the problems are now coming home to roost. The second is that tech companies present a new and especially dangerous threat to competitive markets.

The most frequently proposed remedy is a return to the antitrust principles of the 1960s and 1970s — in particular to a greater willingness to intervene when firms enjoy very large market shares. Proponents sometimes describe themselves as neo-Brandeisians, after Louis Brandeis, a trust-busting Supreme Court justice of the early 20th century. Their critics refer to their movement, with its backto- the-future vibe, as “hipster antitrust.”

The view that antitrust is failing us, especially in the digital arena, enjoys broad support. The 2019 investigation of the U.S. House Judiciary Committee into digital markets is a prominent example. It called for more vigorous antitrust enforcement that includes breakups of dominant platforms, data portability requirements, and prohibitions on the abuse of bargaining power. The UK conducted its own special review of digital competition in 2019, led by U.S. economist Jason Furman. The EU shares this special concern. Speaking in October 2020, the EU commissioner Margrethe Vestager described digital platforms as “gatekeepers, with enormous power over our lives.” She continued:

They can influence our safety — whether dangerous products and harmful content can spread widely, or whether they’re quickly removed. They can affect our opportunities — whether markets respond to our needs, or whether they just work in the interests of the platforms themselves. They even have the power to guide our political debates, and to protect — or undermine — our democracy.

Here, we argue that a different type of institutional reform is needed in a world where intangibles — everything from protected intellectual property like patents to brand recognition and databases — drive economic performance. Our argument has several parts. First, the apparent decline of competition cannot be properly understood without taking into account the growing importance of intangibles. When their effects are considered, some symptoms of growing market power, such as rising markups and greater concentration at a national level in some markets, turn out to be illusory. Others are real, but they owe as much to the changing nature of capital as they do to changes in the philosophical basis of regulation.

Second, intangibles-rich businesses create different challenges for regulators, requiring them to be more expert. Finally, while antitrust has typically concentrated on falling competition between firms, we think it’s important to consider rising competition among workers — competition for schools, jobs and status. We argue that this competition owes much to the growing importance of intangibles. In particular, it increases the risk of zerosum competition among workers, escalating the risk of investment in unnecessary degrees and meaningless credentials.

The Received Wisdom on Declining Competition

Let’s first review the standard argument regarding the problem of interfirm competition, which is most clearly set out in the important research of the economist Thomas Philippon. If there are a small number of competing firms in a market, most economists start to worry. This situation is often associated with less competition over prices and variety of goods, and weaker incentives to innovate.

A related phenomenon is the rise in what economists call the “markup,” the difference between the marginal cost of producing a product and how much that product sells for. Influential research by Jan De Loecker and Jan Eeckhout suggests that markups have been steadily rising since 1980 in the U.S. and Europe. This is another red flag for economists: in competitive markets, we would not expect markups to keep rising because consumers would shift to buying from competitors with lower prices.

What are the other symptoms of a lack of competition? To many economists, enduring leader/laggard gaps look like another sign of competition gone wrong. After all, the genius of competition is that only firms with the best products will do well in the marketplace. But the best product is subject to continual change — what the economist Joseph Schumpeter called creative destruction. In a well functioning market, we would expect to see laggard firms either exiting the market or replacing the leading firms as their products get better.

For some, another troubling aspect of competition in the modern economy is the conglomerate nature of some of our new firms. Amazon started as a bookseller. It now produces movies and sells web hosting; Google has moved from a search engine to online advertising to an email service to driverless cars. This reminds many of the industrial structure of the 1960s, when large conglomerates dominated many industries. That story did not end well: conglomerates were sluggish and unproductive, and most ended broken up by market forces.

In sum, many people see increased concentration, increased insulation of the leaders from the laggards and the trend toward conglomerates as indications of a lack of competition. And, they argue, lack of competition takes the economy to many bad places: low innovation, poor management and employment practices, rent-seeking, and dissatisfied consumers with nowhere else to go.

The Effect of Intangibles on Competition Among Firms

We believe the rise in intangibles offers an alternative explanation for what has happened to competition. Consider market concentration first.

Here, it is important to note the difference between concentration in national markets and concentration in local markets. For many goods, national concentration matters a lot less to competition than local concentration. Imagine two different countries. In the first, there are no supermarket chains, and every town has a single, independent supermarket. In the second, there are two supermarket chains, and every town has one store owned by each chain. In the first country, each independent supermarket can act like a monopolist because few people will travel to the next town for their weekly shopping. Measured national concentration would be massively higher in the second country. But consumers might prefer it because every consumer has two stores to choose from, and there is likely to be more competition in terms of price and variety.

Research by Chang-Tai Hsieh and Esteban Rossi-Hansberg examined the difference between local and national concentration in the United States since 1977. They concluded that national concentration has risen and local concentration has fallen. The reason is a profoundly intangible one: “ICT-based technologies and adoption of new management practices have finally made it possible for firms outside of manufacturing to scale production over a large number of locations.”

To put it another way, because intangibles are scalable, service businesses with valuable intangibles (such as popular brands, strong management practices or distinctive product offerings) can spread across many local markets. If that sounds abstract, think of national and international retail chains, which invest heavily in branding, software (for stock control, customer loyalty programs and e-commerce), relationships with suppliers (the secret sauce of “fast fashion”) and new product development — all intangible investments. Think of mid-market chains that rapidly grow from successful independent restaurants. A world with lots of these chains, whose business models rely on intangibles in a way most independent stores do not, is likely to have more intense local competition that does not show up in the national concentration figures.

This idea is also borne out in work by Matej Bajgar, Chiara Criscuolo and Jonathan Timmis at the OECD, who studied the correlation between changes in concentration and intangible intensity. Rises in concentration, they confirmed, have occurred in the most intangible- intensive industries. But the markups of American firms and the total rate of return are more or less unchanged when one accounts for increases in intangibles in firms’ capital. The runaway profitability of businesses is at least partly an artifact of omitting an increasingly important part of the capital stock.

We see something similar when we look at economy-wide profits. It seems natural to turn to national accounts for the share of GDP accounted for by profits. And in the United States and elsewhere, the share of profits has risen.

But measurement here is fraught with difficulty. Germán Gutiérrez and Sophie Piton have dug into these data and found a different picture. National accounts break GDP into wages, profits and payments to the selfemployed (which are in practice a mixture of wages and profits). Profits are measured by tax returns from corporations. Profits therefore will change for at least two reasons. First, if the numbers or treatment of the selfemployed as corporations changes. Second, if national accounts treat buildings as capital, as would be expected because buildings are durable sources of capital services.

It turns out, however, that in Europe nearly 20 percent of non-financial corporations’ capital stock is actually housing. When we talk about “profits” as a measure of competition among businesses, we surely want to strip this out. Housing makes little difference in the measured capital of U.S. businesses, so profits have, indeed, been rising. But outside the United States, the share of profits has been stable.

Finally, could the ability of large firms to scale up and exploit synergies explain the growing gap between the leaders and the laggards? Controlling for a large number of other factors, industries that are more intangiblesintensive have a growing productivity dispersion, which suggests that intangibles are the main driver of productivity dispersion.

The implication of all these findings is that intangibles help make sense of the perceived crisis of interfirm competition in three ways. First, including intangibles such as markups reduces or eliminates the apparent increases in market power we would otherwise see in the data. Second, the growing importance of intangibles has underpinned the phenomenon of increasing local competition and falling national competition as intangibles-rich national chains open new local establishments. Third, to the extent that concentration has increased, it seems that it has done so in the most intangibles-intensive sectors, suggesting that the winner-takes-all characteristics of intangible capital may be to blame rather than deterioration of policy vigilance.

Not Quite So Fast

So far, our arguments suggest that, when it comes to interfirm competition, intangibles provide reasons for optimism and for rejecting the concerns of hipster antitrust. Unfortunately, things are not quite so simple. An intangible economy is harder to regulate, requiring changes to the institutions that enforce competition policy.

How does competition affect prices in an intangibles-rich economy? There is a lingering suspicion that competition might work differently online. After all, doesn’t the information that the internet now gives consumers benefit only the smart and savvy? Those who seek the variety of supply that competition brings will be the winners. Those without the ability or means to seek such bargains will surely lose out.

In fact, the basic textbook economics model suggests the complete opposite. In that world, savvy consumers spread the benefits of their bargain-hunting to everybody. To understand how that happens, start by thinking about the price of milk at your local supermarket. If you ask people what the price of milk is, most of them are rather hazy about it. Indeed, many politicians get a briefing on the price of milk before they go before the media, as it’s a standard question that an interviewer might ask in an attempt to embarrass them.

Does a general lack of awareness regarding milk prices mean that supermarkets can simply raise the price of milk, safe in the knowledge that uninformed consumers will not notice? Not necessarily. Suppose there are some consumers who do know the difference. If the supermarket raises the price those consumers will simply go elsewhere, either by physically walking elsewhere or by clicking a button. And if there are enough of them, the supermarket knows that it’s going to lose out if it raises its milk price.

Just how much it loses out depends on the responsiveness of demand to price. And it turns out that supermarkets don’t need that many “marginal consumers” to make such a price increase unprofitable. When only 15 percent of consumers are responsive, milk prices stay low. Thus, the 85 percent of consumers who have little idea of milk prices get the benefit from those active 15 percent. The actions of just a few hold the price low for everyone.

Another example is hotel minibars. These minibars, with their very high prices, seem to be a prime example of preying on thirsty and hungry consumers (or perhaps those with less self-control). But it’s worth remembering that hotels offer minibars to everybody. If the hotel believes that at least some fraction of its guests are going to purchase high-markup items from the minibar, it will reduce the base price of its hotel rooms to attract more minibar users. The hotel therefore ends up reducing prices for everyone, and the nonminibar drinkers get the advantage of those who yield to such temptation.

Matters are different, however, if everybody pays a different price. If the supermarket could engineer price changes in such a way that prices stayed low for the pricesensitive customers but got raised for the price-insensitive ones, it might be able to successfully raise prices even in the face of competition.

Such a strategy is difficult to pull off. First, the supermarket must know who is pricesensitive. And it would have to know not only for milk but for thousands of other products supermarkets usually stock. Second, the supermarket would have to find a way to segment the market and hold prices low just for the more responsive customers.

In pre-internet days, coupons were used for exactly this purpose. Sensitive customers snipped coupons and got price reductions for which insensitive customers were indifferent, allowing supermarkets to segment the market. But coupons were an inaccurate method of segmentation, and while the customers bearing coupons revealed themselves to be the sensitive customers, coupons didn’t typically use customers’ purchasing histories.

Today, segmentation can be accomplished much more easily. Shops, especially those online, have detailed information about individuals — their shopping habits, their responsiveness to prices, and other contractual details from online accounts or from loyalty cards for in-store purchases. So the cost of information, which the market segmentation strategy crucially requires, seems to have come down.

Which raises an interesting hypothesis. Perhaps in earlier years we were really all in it together as far as prices were concerned. With the move to the internet and increased information in the economy, perhaps the situation has completely changed.

Finding widespread evidence of “personalized” pricing is harder than you might think. One standout area is internet dating. Parship, a large German provider of online dating services that boasts of setting up 55,000 relationships since 2001, uses its detailed sign-up questionnaire to determine the client’s monthly membership fee. These fees differed by salary, among other characteristics. A female tester with a fictional annual income of €100,000 [approximately $113,000] was asked to pay a €44.93 monthly fee, while another tester with a fictional annual income of €15,000 was offered the membership for just €30.02 per month. A male user with an equally low income was offered a lower fee than the female user — only €26.45 per month.

While Parship extensively uses personal information to calculate personal prices, less sophisticated efforts are more common. The economist Aniko Hannak documented several cases where companies inferred higher ability to pay from the type of computer that the buyer used. For example, researchers found that Mac users will spend up to 30 percent more than PC users for the same room on the U.S. online booking portal Orbitz. Staples, a large office supply chain in the United States, charged different prices based on the location of its online shoppers. Search effort can also make a difference: for example, users searching for flights more intensively, by using Google Flights, always paid less.

Price steering, a close cousin of individualized pricing, changes the order of search results, presenting those results based on what the retailer already knows about the customer from previous visits to its site. A good analogy is the way that Netflix presents content to its users. Over the course of time, Netflix learns about its users’ preferences, allowing it to tailor suggested content better and better from visit to visit.

The rationale and effectiveness of regulatory intervention in these sorts of cases is very complicated. Taking steps to raise competition typically helps all customers. But many suggested interventions — regulating minibar prices, for example — are steps to change not all prices but rather the structure of prices. Capping minibar prices might help those customers who want a drink or a snack, but it might harm other customers if the general level of prices at the hotel rises to recover the loss in profits from the minibar.

Michael Grubb and Matthew Osborne examined the FCC’s 2013 introduction of “billshock” regulation. In response to complaints from mobile phone users who went over their allotted lower-cost minutes and received enormous bills, a law was passed requiring mobile operators to send text alerts to consumers who are about to go over their text/ call limit and so incur “overage” charges. And indeed, this law did reduce the number of consumers who incurred overages. But simulations suggested that the operators regained the lost profits by increasing their standard charges for everyone.

What should we conclude? Interventions that end up changing the structure of prices are fraught with problems and need to be considered very carefully. Furthermore, there are situations in which differential pricing improves things for both firms and consumers — particularly when it comes to some intangibles-intensive businesses whose products have high fixed costs but near-zero marginal costs, such as software, data, music and video games. Setting prices for these businesses is tricky since they need to find a way of covering their fixed costs. One way to do this is to allow businesses to charge different prices to different consumers (often for different versions: free and paid Zoom, for example).

Consider the market for video games, where sales, deals and bundles help companies set different prices for many different types of customers (most notably, those willing to wait versus those unwilling to wait). Charging different prices probably increases the volume of games sold compared with what would happen if firms had to set a single price high enough to cover their fixed costs, and it means that more consumers get a game at a price they are willing to pay.

Another issue relates to how we encourage business dynamism. There has been a welcome trend in competition policy away from monitoring simple concentration toward ensuring that it remains possible for new firms to enter a market. But ensuring that market entry is easy becomes harder in a world of intangibles-intensive businesses.

Intangible capital tends to be heterogeneous: one idea, one brand, one operating process is usually not like any others. One consequence is that the tactics intangiblesrich businesses use to maintain competitive advantage — what Warren Buffett would call the “moats” around their businesses — are also highly varied and tend to require bespoke analysis.

When one of the authors worked on intellectual property policy for the UK government, a controversial issue was the rivalry between online platforms and the owners of content such as music videos and sporting rights. The issue was in a broad sense one of competition and market dominance. But the specifics were very specific indeed.

For example, how quickly should content platforms such as YouTube be required to take down pirated content? The answer matters because the faster a platform is required to remove the offending content, the less likely it is to have a permanent “reserve army” of illegal content available to users, which in turn weakens its bargaining position in negotiations with rights holders over how much money the rights holders receive each time their content is viewed. It may come as no surprise that this issue was dealt with not by the normal regulatory processes but rather with a high-touch negotiation across government departments.

Another issue is mergers. Critics decry Facebook’s purchase of WhatsApp on the grounds that the purchase may have stopped future competition. But the prospect of being bought out by another company may be the only way that new intangibles-intensive businesses can get started in the first place, especially if they have trouble raising finance through conventional channels.

These examples are just some of the almost infinite variety of market-dominance questions that regulators may be called on to resolve for intangibles-intensive businesses. Each presents its own technical challenges, and it is hard to resolve them using the kind of rules-based procedures that work for assessing market dominance in discrete industries dominated by brick-and-mortar assets. A host of regulatory questions affect business dynamism, so if dynamism becomes a more important lever of competition policy, it will require a wider range of government competencies to make it work.

Bolstering Competition in an Intangible Economy

Both the many different types of the marketdominance problem in an intangible economy and the way online platforms change the marginal consumer’s effect on pricing decisions have implications for the way we regulate competition. Our guiding priority should remain increasing consumer welfare, and ensuring that markets are contestable should remain an important means of protecting consumers. However, understanding a wide variety of new business models, marketaccess dynamics, and the impact of digital technologies on pricing requires significant knowledge on the part of regulators.

The economist John Fingleton has made two interesting suggestions. First, an “n + 1” regulator might sit across all sectors of the economy and aim to support new companies with innovative ideas that existing laws or regulations cannot accommodate. The “n + 1” moniker signifies that the regulator would be responsible for radically new business models that do not sit well in the established market framework of the industry. Recent examples that an n + 1 regulator may have usefully looked at include peer-to-peer finance businesses and telematic (usage-based) car insurance, both of which faced regulatory challenges. This approach already exists in health care, where treatments that haven’t received regulatory approval are allowed to be used under certain circumstances. It also exists to some extent in fintech (innovations in the financial and technology crossover space).

In addition, Fingleton suggests that we might reform sectoral regulation so that regulators deal with activity rather than industry — for example, on access charges for all utilities rather than access charges on a utility-byutility basis. This approach might also help avoid worries that industry-specialist regulators might be captured by the industries they regulate. It would also provide a forum for thinking about how to regulate intangiblesintensive platform businesses, such as food delivery firms.

Turning to broad competition questions in the intangible economy, we are cautious. Sometimes regulators encourage rivalry by intervening in a market, thereby improving its general functioning. On other occasions they intervene in only part of the market (often following lobbying). Interventions around the structure of prices, rather than general market functioning, can have unforeseen consequences. As we saw in the billshock case, these efforts may backfire.

Further, we think the intangibles lens helps to better evaluate some policy questions. Large companies might very well be a good thing if their scale and synergies benefit consumers — providing, for example, a wide network or indirectly encouraging entrants by the prospect of mergers. Breaking up a company like Amazon might dissolve synergies and scale, which could end up being a net loss for consumers.

Does this possible outcome mean that we should do nothing in the digital space? Not necessarily.

First, there might be some harm if large search engines dominate the digital advertising market. Second, rather than treating intangibles as a bug, competition authorities should treat them as a feature. The obvious example is the widespread utilization of online price comparison websites, used by 85 percent of UK consumers with internet access and accounting for 40 - 60 percent of home and car insurance sales, respectively. Making sure competition between these sites is strong would be a good use of limited regulatory time. Finally, competition regulators need to keep an eye out for unintended consequences, such as threats to privacy.

These institutional changes are less dramatic than the aggressive upgrading of antitrust that many are advocating. Indeed, some might call them downright boring. But the key point is that in a world of intangibles-intensive businesses that have strong economies of scale and that may often obtain temporary dominance over markets, the best weapon is new firms. Making sure businesses have a fair chance to enter markets and dethrone today’s monopolists is more effective than the traditional metrics and tools of antitrust.

Intangibles and the Rat Race

Let’s turn now to the other dysfunctional aspect of competition in today’s economy: the intensification of competition among workers. This trend has been accelerated by the growing importance of intangibles in the economy, and it presents its own institutional challenges. But unlike the question of interfirm competition, it has received relatively little political consideration.

In the words of legal scholar Daniel Markovits, “Today’s elite workplace fetishizes extreme skill and effort. Super-skills (and hence also the education and degrees that provide and mark skill) become increasingly important, not just to securing high incomes and high status but also to avoiding low incomes and low status.”

Anecdotes abound on how the rat race has become pervasive, especially in education. The 2019 FBI investigation “Operation Varsity Blues” revealed a network of Wall Street and Hollywood personalities paying to get their children into various universities via bribery of officials and inflation of exam results. More prosaic, but no less remarkable, academic research has documented the huge difference to life prospects from succeeding or failing at various academic hurdles, surely adding to the pressures on parents and children.

The economists Stephen Machin, Sandra McNally and Jenifer Ruiz-Valenzuela looked at the consequences of failing to obtain a C grade in English in the GCSE (General Certificate of Secondary Education) exam in the UK at age 16. The probability of dropping out of school at age 18 for the narrow-miss pupils rises by about four percentage points. This is a large number when compared with the national dropout average, which is 12 percent.

Such findings are backed by employers. Of those surveyed in 2013, 43 percent use GCSEs in English and math as a filter. Hiring managers did not see applicants with grades below level C regardless of the applicants’ other achievements.

Contrast this with blue-collar hiring practices at Ford in the 1960s reported by Daron Acemoglu of MIT. In the words of one of Ford’s managers:

If we had a vacancy, we would look outside in the plant waiting room to see if there were any warm bodies standing there. If someone was there and they looked physically OK and weren’t an obvious alcoholic, they were hired.

To some extent, the rat race is a first-order consequence of the growth of intangible capital. One subset of intangible capital is the software and management systems that enable businesses to track staff performance, reward the high performers and punish the low performers, whether the workplace is an Amazon warehouse or a corporate law firm. The other aspect of intangibles is that they allow the talented workers to create eye-watering amounts of value, increasing the returns to being the best footballer, quantitative trader or industrial designer. No wonder, then, that in an intangibles-intensive society, these aspects of the rat race are intensified.

The inequality caused by these first-order effects is significant, but it is familiar and can be addressed by familiar policies and institutions — redistributive taxation, minimum wage laws and employment rights. But the quotation above from Markovits reveals a less obvious, second-order effect of an intangibles- rich economy: education and degrees are valuable not just because they confer skills, but also because they “mark” them. In other words, an intangible economy is likely to reward what economists call human capital “signaling” — acquiring credentials not because they are inherently valuable but because they are a credible way to prove that a worker is skillful.

Signaling matters because it is hard for employers to distinguish skilled workers from less skilled. Gaining an elite qualification such as a university degree may be valuable not only because it indicates that an employee has learned valuable skills but also because it is a signal that a prospective employee is conscientious and intelligent.

To be credible, a signal must be costly, either in cash terms or in terms of the time and effort it takes to obtain; otherwise, anyone could get one. This requirement creates a problem. A dollar or hour of work spent gaining a useful qualification not only creates value for the person who earns it. By making that person more productive, it also creates value for the economy as a whole. It is a positive- sum proposition. In contrast, spending the same dollar or hour on a qualification whose only benefit is signaling creates a private return to the people who earn the qualification, but it does not give them skills. Instead, it merely allows them to get a job that someone else might have gotten.

Unfortunately, none of the participants in a typical educational transaction have a strong incentive to distinguish between real human capital formation and signaling. From an employer’s viewpoint, it does not matter why a degree and certificate are useful, so long as it is. When John Paul Getty was asked why he chose men with classics degrees to run his companies, he replied, “Because they sell more oil.”

Similarly, employees care only about their private return. Even schools, universities and training establishments have compromised motives. On the one hand, they may have strong intrinsic motivations to ensure that what they teach is rigorous and in good faith; on the other, they have little incentive to make themselves redundant by probing too deeply the nature of the benefit they provide.

What’s more, it may not be easy for educational establishments to provide real human capital formation even if they want to. The synergies between intangibles such as R&D and worker skills can often be difficult to realize, requiring close interaction between education providers and employers (or their integration, in the form of on-the-job training).

In a world where the returns to skills are high and rising but the ability to judge talent is imperfect, and where it is hard for universities to predict employer needs, we would expect to see a boom in signaling. It is widely observed that a college degree is becoming a prerequisite for many jobs that were once done by non-graduates. By the same token, prestigious employers that once recruited candidates with undergraduate degrees are now choosing between candidates with a master’s degree and those with doctorates.

One proposed approach is to make the education market work better. If students spent their own money, arguably providers would compete to offer courses that really do improve employability. This intuition has been the main thrust behind much of the past 30 years of higher education reform in the UK, in which university education has gone from entirely state-funded (with student numbers capped, and places limited to those with the best examination results) to a system of relatively high fees and subsidized loans provided by the government. The government has produced detailed data on the future salaries of graduates in different disciplines, along with frameworks and rankings that try to provide this evidence to prospective students in a salient way. The U.S. system has, of course, gone much further down this road, with most students incurring large amounts of debt.

Gallons of ink have been spilled over the merits and demerits of marketizing the university system. Critics argue that it increases inequality and ignores the value of education to the extent that schooling does not translate into salaries — and in any case, that many of the metrics used to assess courses and universities are statistically unsound. But neither side seems to have much of an answer to the question of how to discourage wasteful signaling.

Even if market reforms fully achieved their goal of giving prospective students strong incentives to choose only courses with high returns, there would still be the problem that individual students are indifferent as to whether that return comes from learning useful knowledge and skills or acts as a signal that they are more intelligent and conscientious than others.

Another marginal improvement is to expand subsidies to cover more than just a university education. The UK government announced in 2021 that it was extending its loan subsidies to non-university vocational education, a move that was widely welcomed by those worried about the dominance of universities in the British system. American critics of universities point to short, vocational coding schools like the Lambda School (Bloom Institute of Technology), as possible models, and imply that it would be better if more young people took this route for postsecondary education.

But this route also has risks. The UK’s historical experience of a freer education market in which students depend on cheap loans is not encouraging. In September 2000, the government introduced an Individual Learning Accounts scheme, a sum of money that adults aged 19 and older could spend on education. An education provider could enroll a student and then claim the student’s allowance from the government. To encourage new providers, the government allowed any institution to enroll students. But just 15 months later, after fears that bogus providers were walking away with the money, the scheme was scrapped. It was later found that lack of reporting meant that the government was unaware that just 13 providers had registered over 10,000 accounts.

The real problem here is that, for the most part, government policy assumes more education as better, and relatively little consideration is given to what to do about signaling. It is expected that education providers, employers and learners have a strong incentive to make sure that education is useful. But, as we have seen, there is no overriding incentive for any of these groups to choose real human capital formation over signaling alone.

In addition, making good policy on this subject is hard. Governments are not well placed to differentiate between degrees or qualifications that generate real skills and those that merely signal. At most, they make broad-brush attempts to promote science and math degrees — which could involve more human capital formation but could also involve signaling — or they focus on students’ prospective earnings, which could also be the result of signaling.

We believe policymakers need to invest time and money in data-gathering and in conducting more experiments to understand more about what types of licensing generate real value rather than signaling. Educational reform has strong parallels with the quantityversus- quality issue in public science funding. The idea that funneling ever-increasing numbers of students into higher education is sufficient to solve the skills problem is a “quantity” view, but the solution may be to provide more variety in truly useful skills.