Capitalism without capital

June 2020

The modern economy has seen a marked shift in the GDP and labour share involved in the production of manufactured goods, such as food, vehicles, and electronics, towards labour-intensive service sectors like healthcare, education, and professional services. Baumol famously identified the cause as the higher productivity growth of goods-production relative to services: companies can invent machines to decrease the amount of people needed to produce the same number of mobile phones, whereas hospitals and schools may still require a similar number of doctors or teachers to achieve the same quality of outcomes.

Accompanying this change has been a shift in the character of investment. Investment, like labour, provides a vital input to the economy, distributing resources to build up capital that will provide long-term value in future. Traditionally, businesses mainly invested in physical capital, or tangibles, like buildings, land, machines, or computers. However, over the past few decades, businesses have steadily invested more into intangible capital such as software, product development, branding, or supply chain management.

This trend was the focus of Haskel and Westlake (2018), which followed Corrado et al. (2005) in describing three classes of intangibles: computerized information such as software and databases; innovative property like R&D, mineral exploration, and artistic originals; and economic competencies including training, branding, and business processes. Notably, these categories vary in their legal protection and their inclusion in national accounts as investments. Haskel and Westlake show that the gap between tangible and intangible investment has been narrowing since the mid-1990s in major advanced economies, with the GDP share of intangibles rising, and falling for tangibles. In the United States, UK, Finland, and Sweden, the average share of investment between 1999 and 2013 was greater for intangibles. The rise, particularly prominent in the most developed countries, may be linked to the reallocation from goods to services, globalization, market liberalization, and other factors.

The rest of this essay will explore a framework which differentiates the behaviour of economies and businesses with tangible versus intangible assets, before considering how the ascent of intangibles may help to explain problems in innovation, finance, and inequality.


Haskel and Westlake (2018) summarize the distinct economic properties of intangibles with “4 S’s: scalability, sunkenness, spillovers, and synergies.”

  • Scalability refers to the ability to repeatedly use an asset with a low marginal cost. In the past, a DVD rental shop could expand its business to another town by investing in a new store at a similar cost to its original store, whereas Netflix today can extend its own product to additional living rooms at almost zero cost. This may lead industries to become increasingly dominated by fewer firms.
  • Sunkenness is the idea that intangible assets are sunk costs: unlike material assets like buildings which are easily traded between owners and repurposed, and are convenient collateral, intangibles tend to be relatively specific to a firm and less obviously useful to others. They are difficult to value, particularly as a market may not exist for them, such as for investments in branding.
  • Spillovers occur when ideas generated by one firm are used by others, due to their non-rivalry: the iPhone, announced in 2007, inspired competitors to develop their own much improved smartphones. Firms may invest fewer resources in innovation if others can easily copy their ideas, highlighting the need for intellectual property rights, and for public R&D investment. Geography interacts with spillovers, as the clustering of people facilitates the exchange of ideas.
  • Synergy relates to the complementarity of ideas: the iPhone itself is more valuable when combined with the App Store and Apple’s brand reputation, and an online grocery store is improved by a supply chain with a greater variety of goods.

Tangible investments exhibit some of these behaviours too, but not to the same economic extent. For instance, the specificity and uncertainty of intangibles makes them harder to finance, the owner of a physical asset is usually clearer than who may own the rights to some intellectual property, and synergies between intangibles are less spatially localized.


The growth rate in the United States fell from an average of around 2.25% in the twentieth century to 1% in the twenty-first, and the story is similar in the UK, France, Germany, Japan, and other advanced economies, which have struggled to restore rates seen before the Great Recession (Vollrath, 2020). Larry Summers termed this era of low growth secular stagnation, with economies beset by low interest rates, low investment, but high returns on investment and profits. For economists, this is puzzling. By lowering the interest rates, central banks expected to raise the level of investment as money would be cheaper to borrow, and the opportunity for high returns should excite investors. Vollrath argued that the causes of low growth were primarily an ageing population, the goods-to-services reallocation, and a decline in geographic mobility, while others cite factors such as declining research productivity and a growing difficulty in discovering new ideas (Bloom et al., 2020), or increasing market power. Remarkably, these economies also share in the gradual but dramatic increase in intangible investment, which has many effects, including perhaps on growth.


A widening inequality between firms has coincided with their rise, illustrated by a higher concentration of firms within industries, and greater market power — the ability to charge more for a good or service than it cost to produce — possibly due to the scalability of intangibles. The trend is most visible in ICT and data services firms, which are highly scalable, and in industries with regulations that make it harder to compete (Criscuolo et al., 2019). Digital businesses at the frontier have claimed some overwhelming market shares, with high fixed but low or zero marginal costs, and often reinforcing network efforts, where each user gains non-linearly increasing benefit the greater number there are. Near the end of 2017, 88% of web searches used Google, while 85% of all desktops were running Microsoft operating systems, and 2.2 billion people actively used Facebook (Coyle, 2020). One measure of market power is the average markup, or selling price of a good or service above its cost, which stands at 67% today versus 18% in 1980 (De Loecker et al., 2020), although it may be difficult to discern the optimal percentage within an industry that rewards innovators without letting firms become too complacent (Aghion et al., 2005). Another indicator is the drop in R&D investment levels by top industry firms, which would usually be expected to keep them ahead of their competition; this does not seem to be driven by low predictions of future growth — instead, profits have increasingly been used to payout shareholders (Gutiérrez and Philippon, 2017). Finally, inequality between firms could also explain around two-thirds of the rise in income inequality between 1981 and 2013: for the most part, the wage gap between occupations within firms is increasing more slowly than between firms, driven by the selection of higher-earners into the top firms (Song et al. 2019).

Underinvestment in private R&D is expected due to spillovers, as firms have less incentive to invest if other firms can copy their ideas and reap some portion of the total benefits: using US firm panel data between 1980 and 2001, Bloom et al. (2013) estimated that the returns to all firms exceeded the private at 55% to 21%. There is a range of evidence that the leading firms are best placed to take advantage of spillovers, such as a greater spread in firm productivity in countries which invest heavily in intangibles and services, compared to a smaller spread within those dominated by manufacturing (Haskel and Wesklake, 2018). Hall et al. (2005) saw that a firm’s R&D investment and number of citations of their patents were highly correlated with their stock market value, suggesting that those that already invest substantially in intangibles are able to perform best. Conversely, firms which do not currently engage in R&D may not gain by stepping up, as they may lack the effective management for turning new ideas into products (Coad et al., 2020). If innovation is “ideas having sex” (Ridley, 2010), the most intangible-heavy firms may be best-placed to exploit spillovers and synergies with other ideas.


The sunkenness of intangibles — where they are trickier to value and have less well-developed markets — makes them harder to finance. Some are too firm-specific or entangled to sell separately, and even intellectual property like patents and copyrights are relatively specialized. As a result, intangible-heavy firms are more often financed by equity — ownership of some fraction of the business — than debt (Haskel and Westlake, 2018). Banking has adapted slowly, with vast institutions based on lending rather than equity, which would require forecasting the prospects of a firm. Venture capital has used equity to greater effect, particularly in Silicon Valley, perhaps due to deep networks and the synergistic nature of intangibles. However, startups are unlikely to have the capital or incentive to perform large-scale R&D or basic research.

Governments therefore have strong reasons to fund R&D, including through direct grants, tax credits, and increasing the long-run supply of human capital through universities or immigration (Bloom et al., 2019). Public R&D investment can crowd-in privately funded R&D, increasing the private investment that would otherwise have occurred by supplying large upfront costs, making technologies cheaper and more feasible for private firms, and producing spillovers (Moretti et al., 2019). This may be particularly important for basic research, and developing emerging sectors like low-carbon technologies. Greater interdisciplinarity and the integration of research and development, often separated into universities and firms, might also contribute positively to innovation (Arora et al., 2019).


Lastly, the growth in intangibles plays a major role in where people live, as the concentration in cities of people in knowledge-intensive jobs works to increase the number of valuable connections or serendipitous moments between firms and people that result in spillovers and synergies between their ideas: there are increasing returns to scale, so that if a city doubles its population, it may more than double its wages, income, GDP, and the number of patents it generates (Bettencourt et al., 2007). In the United States, Moretti (2019) found that ten cities accounted for 70%, 79%, and 59% of inventors in computing, semiconductors, and the combination of biology, chemistry, and medicine, as these fields have become increasingly geographically concentrated. Urban agglomeration also increases the supply of skilled labour within commuting distance, and the rate of assortative matching between firms and workers, also a driver of wage inequality across regions (Dauth et al., 2018). While this may have led to greater efficiency and overall prosperity, many of the most productive cities such as New York and the San Francisco Bay Area are becoming more unaffordable, as restrictions on the housing supply inhibit further growth since workers find it harder to relocate or stay there: labour misallocation due to these restrictions had reduced overall growth in the United States by over 50% from 1964 to 2009 (Hsieh and Moretti, 2019).

In the UK, London is experiencing similar issues, but may have fared better due to its vast network of transport links both across the city and with other towns and cities, which has increased its labour pool. On the other hand, infrastructure spending has been biased towards London and South East because of their prosperity, which has only reinforced geographic inequality (Coyle and Sensier, 2020): besides London, other UK cities do not seem to be seeing the effects of agglomeration. In addition, 46% of public and charitable investment in R&D is concentrated within London, Oxford, and Cambridge, significantly higher than the proportions of business spending at 31% and population at 21% (Forth and Jones, 2020). Reappraising such imbalances may be key to greater and more equitable growth in the future, as may changing remote working practices (Clancy, 2020).


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