Have we reached the end of the disruptive innovation era?
It may seem like there’s more technological innovation than ever today, but more innovation doesn’t necessarily mean more economic growth. Data shows that breaking new ground in technology requires ever-increasing investments in R&D, meaning that a dollar invested in R&D generates less and less bang for the buck in the exponential sense.
ABOUT THE AUTHORS
Eljas Aalto
Eljas works as an economist and data analyst at Futures Platform. He develops quantitative foresight analysis tools and participates in various customer projects to help them prepare for the future.
Henrik Södergrann
Henrik is a Foresight Analyst at Futures Platform and works with economics and finance-related research, foresight and the quantitative development of foresight analysis.
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“The pace of technological change is faster than ever”.
We’ve all heard the anecdotal statement. It’s no doubt that disruptive innovations are revolutionising production lines, work, and lifestyles. Progress in computing power, artificial intelligence and DNA sequencing might give the impression that the singularity – the point in time when technological change spirals irreversibly out of control – is fast approaching. But can we draw the same conclusion also from data?
HOW ARE TECHNOLOGICAL ADVANCES MEASURED?
Economists usually measure technological progress using national accounts and GDP. The most common way is to break economic growth into three components: growth in labour input, growth in capital input and growth in a residual component called total factor productivity (TFP).
The TFP component captures the share of growth which is not explained by changing quantities of production inputs, and this is often interpreted as technological change, although TFP also includes everything else that can’t be directly measured.
The main conclusion is simple: allocating resources to research and development leads to new ideas and increased productivity. The more resources are allocated to R&D, the faster the pace of technological change.
IS THIS THE END OF RAPID PRODUCTIVITY GROWTH?
What, then, do TFP growth trends look like? Well, it turns out that TFP growth rates have been on a downward trajectory in Western economies since the 1970s. In his 2016 book The Rise and Fall of American Growth, economist Robert Gordon argues that this trend signals the end of the era of great inventions.
Average annual growth rate of TFP. Source: StraightTalk
Economist Tyler Cowen makes the same argument in his 2011 book The Great Stagnation. Both scholars make their point by looking at the changes in daily life. Americans born in the late 19th century experienced massive changes in their daily lives during their lifetime: electricity, flush toilets, and commercial air traffic, just to name a few. Americans born in the 1970s haven’t experienced anything similar: almost all technological progress in their daily lives has been related to digital screens.
How is this secular decline in TFP growth rates compatible with the unprecedented progress in digital technologies we have experienced? Moore’s law (exponential growth in computing power), Haitz’s law (exponential improvement in LEDs), and Keck’s law (exponential growth in fibre-optic capacity), among other analogous rules of thumb, all show that exponential growth continues. But why is this not visible in productivity growth patterns?
A natural counterargument is the mismeasurement argument. Digital technologies might not show up in productivity statistics as other production technologies do. This productivity paradox was observed by economist Robert Solow already in 1987 when he famously stated that the computer age could be seen “everywhere but in the productivity statistics”.
The digital age has been marked by the emergence of non-market goods and services that don’t make us richer in the same monetary sense as previous technological improvements did. For example, Wikipedia and YouTube provide access to unlimited amounts of free content, which is not visible in national accounts. Similarly, smartphones have made the marginal costs of photography essentially zero, leading to a decline in the sales of cameras, films and photo development services. Hence, the contribution of photography to GDP has become weaker.
FUTURE TECHNOLOGY REQUIRES MORE AND MORE R&D EFFORTS
Beneath the exponential technological progress lies another trend – global investments in R&D. The enormous increase in R&D investments boosts the speed of technological progress. The exponential productivity growth, in turn, requires more and more R&D workers and scientists.
In other words, a dollar invested in R&D generates less and less bang for the buck in the exponential sense. This is also the argument laid out by Nicholas Bloom, Charles I. Jones, John van Reenen and Michael Webb in their article “Are Ideas Getting Harder to Find?”. The scholars present evidence from various industries, products, and firms showing that research effort is increasing substantially while their output – new ideas – stagnates. A good example is Moore’s Law. The number of researchers required today to achieve the famous doubling of computer chip density is more than 18 times larger than the number needed in the early 1970s.
At the same time, the age at which inventors first patent is rising, which economist Benjamin Jones explains by arguing that technology and knowledge have become more sophisticated. More learning is required to get to the point where technology can be pushed forward. This, in turn, leads to increasing specialisation and larger research teams.
These observations can easily be connected to the productivity slowdown hypothesis, but there are also other microeconomic factors that might explain the slowdown. It is possible, for instance, that as the number of patents grows, firms must increase their efforts in replicating and creating substitute technologies. It is also possible that strategic patenting has become a bigger problem, meaning that patents don’t reflect innovations in the traditional sense but are a means for firms to try to control competitors’ actions.
TOWARDS THE FUTURE OF TECHNOLOGY INNOVATION
In essence, technological change is positively correlated with population size – more people create more ideas. With the population growth rates stagnating in most Western countries, this means that economies will need to allocate an ever-increasing share of resources to R&D.
Although this might sound alarming, there is no need to become techno-pessimistic just yet: the share of R&D in the economy still has a lot of room to grow. Moreover, ideas spill over borders: there is a massive untapped potential of innovators and new ideas in the developing world, which will become increasingly more important in the decades ahead.
Going forward, artificial intelligence will also play a key role in shaping the future of technology innovation, especially considering the dwindling population. If AI can conduct some of the R&D activities, the population constraint on innovative activity can be avoided.
In conclusion, there’s no need to fear technological stagnation yet. As long as incentives, institutions and education levels continue to improve globally and there’s a favourable environment for ideas to spill over borders, we’ll keep pushing new frontiers in technological development.
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Literature
Bloom, N., Jones, C. I., Van Reenen, J. and Webb, M. (2020) “Are Ideas Getting Harder to Find?” American Economic Review, Vol. 110(4), 1104–44.
Cowen, T. (2011) The Great Stagnation: How America Ate All the Low-Hanging Fruit of Modern History, Got Sick, and Will (Eventually) Feel Better. New York: Dutton.
Gordon, R. J. (2016) The Rise and Fall of American Growth: The US Standard of Living Since the Civil War. Princeton University Press.
Jones, B. F. (2009) “The Burden of Knowledge and the ‘Death of the Renaissance Man’: Is Innovation Getting Harder?” Review of Economic Studies, Vol. 76(1), 283–317.
Jones, B. F. (2010) “Age and Great Invention”. Review of Economics and Statistics, Vol. 92(1), 1–14.
