A traditional measure of global trade is GDP, which looks at the value of imports and exports of goods and services. What if we consider the global trade in ideas? Using the trade in ideas as a measure of innovation and creativity can point us to future sources of value creation
Bloomberg Radio runs a series called “Master’s in Business.” Last month, host Barry Ritholtz interviewed Joseph Davis, Ph.D., global chief economist and head of investment strategy for Vanguard Group which manages US$ 5 trillion in assets. It’s an interesting interview about a new measure of innovation and creativity which I want to share. (1, 2)
To summarize, Davis posits that there were two periods over the last 200 years when growth in productivity was as low as it is today. Both then went on to lead a period of profound technological disruption.
Ironically, both those periods also featured a financial crisis before an industrial revolution or technological revolution kicked in.
The first period was the stock market panic of 1857, before the second industrial revolution accelerated economic growth.
The second was the bursting of the dotcom bubble in 2000, before we saw the acceleration of e-commerce, social media, and cloud services that are driving the current technological revolution.
His thesis is that the irrational exuberance of stock markets prior to these stock market crashes were largely driven by the euphoria of the promising technologies of the time. These were the steam engines and electricity in the former case, and routers and desk top computers in the latter case.
However, these are general purpose technologies which do not justify the valuations assigned to them during the euphoric phase. Hence, the stock market crashes.
It is not until the second phase kicks in, when business investment in the development of these general purpose technologies happens that applications are developed that change the world.
It is in this second phase that new business models are created and companies disrupt traditional industries in ways that are different from the form of the original technologies. For example, the computer software of the 90’s evolved to the present day applications of cloud computing and artificial intelligence.
So Davis asked, what are the general purpose technologies of today that will lead to the accelerated economic growth and industry disruptions of the future?
His team looked at the flow of ideas across countries. From this, they developed a metric: the ideas multiplier.
They claimed to have traced the development of over two million ideas.
Their research was not published. I can imagine that their sources were databases such as those of research publications and patents. I can imagine that they identified the ideas through meta tags, and that the tracking was through citation numbers and patent references.
The ideas multiplier is how many ideas are generated from one idea.
In 1980, the average ratio across all types of technologies was 40:1. One idea led to forty more ideas.
In 1992, the ratio in computing technology plateaued at 200:1. Davis claims this to be the leading signal that forecast the coming Internet revolution.
Davis interprets an increase in the ideas multiplier number to be a leading economic indicator of activity that appears four to five years into the future.
Today his team found certain technological fields where this idea multiplier has jumped dramatically like it did for computing technology in 1992.
In order of increasing leading signal strength, they are as follows:
1) Materials science
3) Agricultural and plant sciences
Of all of these, genetics “jumps off the charts” at 400:1. Its signal strength is twice the amount observed in computing technology that led to the Internet in 1992.
Davis notes that artificial intelligence (AI) is not on this list. His view is that AI is a general purpose technology, and that its impact will be through its application in one of the above fields.
It is encouraging to see that there are fields with leading economic indicators showing a signal even stronger than that of computing technology.
Also, my first career was in materials science. I was surprised to see it here, but I am also hopeful.
Is this to be believed?
First, his team used a method called network analysis, which is a trendy way of doing analysis these days. The methods are not far-fetched, but it also over-emphasizes features that rely on networks. Certainly, the proliferation of new research journals and open source journals will probably increase the ideas multiplier number over time for all fields.
Second, they cannot tell us what sub-field in any of these areas are responsible for the multiplier effect. That is because they are just looking at meta tags.
Third, can another period of profound and revolutionary disruption happen so soon after the last one?
However, at a general level, these fields do resonate with what we are seeing in new commercial technologies today.
I am also glad to see that AI was not on this list, even though it seems to be the trendy (euphoric?) technology of the moment. My interpretation of AI is different from Davis’ conclusion. I think AI has yet to hit the tipping point that we see in the above list of four fields.
Profound revolutionary change or not, the promise of any of these new fields giving rise to economic growth would be enough.
I will give example case studies of each of these fields in future posts.
This method of network analysis is also an interesting one, because of the implications given by those analyzing the results. Again, these will be discussed in future posts.
1) How to Measure the Economic Value of Ideas, Barry Ritholtz, Bloomberg, February 19, 2019
2) Masters in Business: Joe Davis, Vanguard’s Chief Economist, by Barry Ritholtz, February 16, 2019