The Hidden Economics of Ideas

Ideas are getting harder and harder to find

There is a widely held view in Silicon Valley and within the zeitgeist of entrepreneurialism that good ideas are commonplace, and that execution of ideas is what matters for business success. However, there is compelling evidence that knocks that conventional wisdom off its pedestal.

A group of economists, Nicholas Bloom, Charles Jones, John Van Reenen, and Michael Webb, have released a working paper — Are Ideas Getting Harder To Find? — that argues the opposite:

Across a broad range of case studies at various levels of (dis)aggregation, we find that ideas — and in particular the exponential growth they imply — are getting harder and harder to find.

The authors use Moore’s Law as the pivotal example of the increasing numbers of researchers needed for continuation of historic rates of productivity increase. Moore’s Law is named for Intel cofounder Gordon Moore, who mentioned in 1965 that the number of transistors on integrated circuits had doubled every year. It has been somewhat rejiggered to focus on computer processing speeds, which double every two years.

Such doubling corresponds to a constant exponential growth rate of around 35% per year, a rate that has been remarkably steady for nearly half a century. As we show, this growth has been achieved by putting an ever growing number of researchers to work on pushing Moore’s Law forward. In particular, the number of researchers required to achieve the doubling of chip density today is more than 75 times larger than the number required in the early 1970s. At least as far as semiconductors are concerned, ideas are getting harder and harder to find. Idea TFP in this case is declining sharply, at a rate that averages about 10% per year.

Image for post

Moore’s Law 1971–2011

They offer a simple equation to concisely get this general case across (but note for Moore’s Law, the growth rate isn’t 2%, it’s something like 63% annually, to get the doubling every two years).

Image for post

TFP is total factor productivity, the ‘portion of output not explained by the amount of inputs used in production’, which equates to how efficiently resources are used. So, idea TFP is a measure of how efficiently ideas are being applied, and that factor is falling.

The authors also looked at agricultural productivity, cancer mortality rates, and elsewhere. To summarize, they write:

We find substantial heterogeneity across firms, but idea TFP is declining in more than 85% of the firms in our sample. Averaging across firms, idea TFP declines at a rate of 12% per year.


We find that idea TFP for the aggregate U.S. economy has declined by a factor of 48 since the 1930s, an average decrease of more than 5% per year.

These are staggering observations, and are corroborated by other researchers:

Griliches (1994) provides a summary of the earlier literature exploring the decline in patents per dollar of research spending. Gordon (2016) reports extensive new historical evidence from throughout the 19th and 20th centuries. Cowen (2011) synthesizes earlier work to explicitly make the case. Ben Jones (2009) documents a rise in the age at which inventors first patent and a general increase in the size of research teams, arguing that over time more and more learning is required just to get to the point where researchers are capable of pushing the frontier forward.

Image for post

US TFP Growth v Researchers

The researchers believe they have answered the question: can a constant level of research effort generate constant exponential growth in the entire economy or in specific economic niches? The answer seems to be ‘no’. Turned around, constant exponential growth requires a growing number of researchers.

One of the seemingly paradoxical outcomes of this economic understanding¹ is that idea TFP is declining most quickly in those sectors with the fastest growth rates, like semiconductors. The paradox is explained by the general purpose value of faster semiconductors. As the authors put it:

Demand for better computer chips is growing so fast that it is worth suffering the declines in idea TFP there in order to achieve the gains associated with Moore’s Law.

The lasting takeaway from this research on the growing investments needed in research is this: idea TFP is falling fast everywhere, across the economy.

Taking the U.S. aggregate number as representative, idea TFP falls in half every 13 years — ideas are getting harder and harder to find. Put differently, just to sustain constant growth in GDP per person, the U.S. must double the amount of research effort searching for new ideas every 13 years to offset the increased difficulty of finding new ideas.

One simplistic way of looking at those stats: we will have to employ at least twice as many researchers 13 years from now just for the economy to keep growing at the current rate, or make a lesser number of researchers significantly more productive.

A final observation: when people wonder why productivity growth has slowed, there is a simple reason. We aren’t investing enough in research.

  1. Known as a a semi-endogenous growth model.

Written by

Founder, Work Futures. Editor, GigaOm. My obsession is the ecology of work, and the anthropology of the future.

Get the Medium app

A button that says 'Download on the App Store', and if clicked it will lead you to the iOS App store
A button that says 'Get it on, Google Play', and if clicked it will lead you to the Google Play store