Deconstructing the Productivity Paradox

Researchers say that a shortage of exceptional talent is stalling productivity growth in the digital economy

By Irving Wladawsky-Berger

Despite the relentless advances of digital technologies, productivity growth has been declining over the past decade. Investment and interest rates have remained low, and income has continued to stagnate for the majority of workers in the US and other developed economies. The world seems to be stuck in a period of slow growth and no one is quite sure what’s causing this apparent contradiction.

Opinions abound. Harvard economist Larry Summers has argued that secular stagnation is the reason behind this unusual situation, caused primarily by a reluctance of companies to invest and of consumers to spend, with the ensuing excessive savings acting as a drag on economic growth.

Some contend — most prominently Northwestern University economist Robert Gordon,- that over the past few decades there’s been a fundamental decline in innovation and productivity. Perhaps our current technologies, advanced and exciting as they might be, aren’t as transformative as the technologies from the period between 1870 and 1970 when we experienced high productivity growth and a rising standard of living.

Demographic change, namely, the declining population and labor force growth around the world, is another potential cause for slow economic growth. The global labor force grew at an average of 1.8% per year between 1960 and 2005, but since then it’s been growing at just 1.1% annually, and it’s already shrinking in a number of countries, including Japan, Germany, and China.

Technology Outpaces Economy

Another possible explanation, advanced by Erik Brynjolfsson, Daniel Rock, and Chad Syverson in AI and the Modern Productivity Paradox, is that the paradox is primarily due to a time lag between technology advances and their impact on the economy. We’ve been living in a time of major transformative technologies — the Internet, smartphones, IoT, big data, AI — whose deployment and impact on productivity growth are still lagging.

While technologies may advance rapidly, humans and our institutions change slowly. Moreover, the more transformative the technologies, the longer it takes for them to be embraced by companies and industries across the economy. Leading edge firms are already benefiting from these advances, but most are still in the early learning stages. Translating technological advances into productivity gains requires major transformations in business processes, organization and culture, and these take time.

In a recent paper, Digital Abundance and Scarce Genius, Seth Benzell and Erik Brynjolfsson introduce a new, quite interesting argument: slow economic growth and stagnating wages are inexorably linked to the rise of our global superstar economy. A striking feature of digital technologies is their replicability at low or even zero cost, enabling digital innovations to spread almost instantly around the world.

As a result, digital labor and capital are becoming more abundant because they can be reproduced much more cheaply than their traditional, physical forms. Why then is productivity growth so lukewarm? What is constraining growth?

To address this paradox, Benzell and Brynjolfsson propose a novel production model. In addition to capital and labor, their model adds a third factor, a bottleneck which prevents economies from taking advantage of the abundance of digital capital and labor. They dub this third factor genius (G).

A Scarcity of Superstars

The G factor is primarily associated with exceptional talent, which — unlike labor and capital — isn’t subject to digitization. Its relative scarcity thus becomes a production bottleneck. “Many have the sense that intangible assets and superstar workers are more abundant than ever. Perhaps the most surprising thing then about our result is that these factors are increasingly scarce.”

The model helps explain “why ordinary labor and ordinary capital haven’t captured the gains from digitization, while a few superstars have earned immense fortunes. Their contributions, whether due to genius or luck, are both indispensable and impossible to digitize. This puts them in a position to capture the gains from digitization.”

The paper discusses three different manifestations of this scarce and growth-limiting genius factor: superstar individuals, organizational talent, and ‘virtual real estate’.

Superstar Individuals. Over the past few decades, labor markets in the U.S. and other advanced economies have experienced increased demand for highly skilled workers. While the demand for routine skills that can be replaced by technology has been declining, the demand for skills that are complemented and enhanced by technology keeps rising.

Jobs requiring expert problem solving and complex communication skills have significantly expanded with the earnings of the educated workers need to fill such jobs rising steadily.

“In 2008, the top 25% of U.S. workers earned more than half of all labor income, the top 2.5% of workers earned over 20% of labor income, the top .25% of workers earned over 7% of total labor earnings, and so on.”

The paper defines genius labor as comprising the top 3% of all workers. Their model predicts that in 2012, this 3% commanded 25% of labor income from U.S. non-financial corporations, a figure that was validated by empirical data. The income of the top 3% is likely higher now, given our continuing technology advances. This is evident in the large salaries and bonuses that AI experts are able to command.

Organizational Capital. In the 1990s, the Internet was supposed to usher a much more open, decentralized, democratic economy. Companies, from the largest to the smallest, could now transact with their customers anywhere anytime. Vertically integrated firms became virtual enterprises, increasingly relying on supply chain partners for many of the functions once done in-house. Experts noted that large firms were no longer necessary and would in fact be at a disadvantage when competing against digital savvy, agile startups.

As we well know, it hasn’t quite worked out as expected. Instead, we’ve seen the rise of the global superstar company, a second prominent G factor. Besides their ability to attract superstars individuals, such companies benefit from a number of intangible assets, including superior organizational capital mostly acquired through their considerable investments in leading-edge digital technologies and skills.

For example, McKinsey recently conducted a global online survey on the current state of AI adoption, garnering responses from over 2,000 participants across a range of business functions, industry sectors, geographical regions and company sizes. Overall, the survey found that the business world is beginning to adopt AI, but only 21% reported using AI throughout their companies. Many respondents said that their organizations lack the necessary talent and foundational practices to create value from AI at scale. Moreover, a critical success factor for AI is an organization’s progress in their company’s digital transformation. The same players who’ve been leaders in earlier waves of digitization are now leading the AI wave.

Virtual Real Estate. A third major G factor is a special type of intangible asset owned by superstars companies — virtual real estate,— which is sort of like land in a city: it’s roughly fixed in supply, prices can skyrocket as demand rises, and its development requires considerable capital and labor. Such assets include intellectual property— such as monopolies created by patents, copyrights, or trade secrets; control of de-facto standards — widely used operating systems or search algorithms; and the kind of brand reputation that makes their products highly desirable.

But no scarce asset is more valuable than a successful two-sided platform. The Internet’s universal reach and connectivity has led to increasingly powerful network effects. Scale increases a platform’s value. The more products or services a platform offers, the more consumers it will attract, helping it then attract more offerings, which then makes the platform even more valuable to consumers. Moreover, the larger the network, the more data is available to customize offerings and better match supply and demand, further increasing the platform’s value. The result is that a small number of companies have become category kings dominating the rest of their competitors in their particular markets.

Interrelated Factors

While distinct, these three different manifestations of the genius factor are closely interrelated. “Organizational capital may be hard to accumulate because it requires human geniuses to create it, nurture it, or sustain it. Similarly, huge profits gained by titans of digital industries may be attributed to their discovery of some new patch of virtual real estate. In a sense then, virtual real estate and organizational capital can be thought of as a type of crystallized human genius, perhaps reflecting the collective, if not necessarily consciously coordinated, efforts of many individuals. Conversely, the scarce asset owned by firms may include their attractiveness as a workplace for geniuses. Many have hypothesized that the comparative advantage of large digital platform companies is their special ability to recruit and motivate exceptional workers…”

“Idealists had imagined that digital abundance would be an inexorably egalitarian force. Reductions in the cost of information and communication capital, improvements in automation technologies, and the diffusion of AI were hoped to decentralize information and power, to the benefit of all. In contrast,… digital abundance can actually have highly non-egalitarian effect… increases in the productivity of unexceptional capital and labor have suppressed interest rates and median wages. Output has increased somewhat as a result of this abundance, but not anywhere near in proportion to the increased ubiquity of digital goods, services and processes. Furthermore, an increasing share of output has accumulated to a scarce complement, owned or provided by a lucky few…”

“Science fiction author William Gibson is quoted as saying ‘The future is already here — it’s just not very evenly distributed.’ It might be more accurate to say ‘the future is already here — but its rewards are not very evenly distributed.’ ”

Irving Wladawsky-Berger is a digital fellow of the MIT IDE.

This blog originally appeared on Wladawsky-Berger’s blog, here.

Find these and other IDE working papers and research reports on this Publications page.