Given the pace of technological change, we tend to think of our age as the most innovative ever. But over the past several years, a number of economists have argued that increasing R&D efforts are yielding decreasing returns.
Are Ideas Getting Harder to Find?, a recent paper by economists Nicholas Bloom, Charles Jones and Michael Webb from Stanford and John Van Reenen from MIT, shows that, across a wide range of industries, research efforts are rising substantially while research productivity is declining sharply.
Moore’s Law, the empirical observation that the number of transistors in a computer chip doubles approximately every two years, illustrates these trends. The paper points out that the number of researchers required to double chip density today is 18 times larger than those required in the early 1970s. In the case of Moore’s Law, research productivity has been declining at a rate of about 6.8% per year.
The authors conducted a similar in-depth analysis in the agricultural and pharmaceutical industries. For agricultural yields, research effort went up by a factor of two between 1970 and 2007, while research productivity declined by a factor of 4 over the same period, at an annual rate of 3.7 %. For pharmaceuticals, research efforts went up by a factor of 9 between 1970 and 2014 while research productivity declined by a factor of 5, an annual rate of 3.5%.
“Taking the U.S. aggregate number as representative, research productivity falls in half every 13 years – ideas are getting harder and harder to find,” they write. “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.”
Why is research productivity declining, despite our increasingly advanced technologies? Let me briefly discuss two intriguing, potential answers to this important question.
In a 2009 paper, The Burden of Knowledge and the ‘Death of the Renaissance Man’: Is Innovation Getting Harder?, Northwestern economist Benjamin Jones argued that “If innovation increases the stock of knowledge, then the educational burden on successive cohorts of innovators may increase.” His theory is based on two simple observations.
First, “innovators are not born at the frontier of knowledge.” They must undertake considerable education to reach the frontiers of knowledge where the majority of innovation takes place. Individuals can only absorb knowledge at a limited rate, so their education occupies considerable time and a significant portion of their lives.
Second, the stock of knowledge has been rapidly expanding across most disciplines, over the past 150 years, and particularly over the past several decades. If reaching the frontiers of knowledge requires standing on the shoulders of giants, “one must first climb up their backs, and the greater the body of knowledge, the harder this climb becomes.”
Innovators can compensate for this increasing knowledge burden in two key ways. They can choose to learn more, thus continuing to lengthen their education. Or they can become more specialized, narrowing their area of expertise and forcing them to work in teams of innovators with complementary specialized expertise.
Mr. Jones presented evidence that both, longer educational periods and greater specialization, are actually happening. PhD’s have been taking longer in most fields, and additional postdoctoral training is often required for leading-edge academic and research positions. Analysis of a rich patent data set shows that the age of first patent has been increasing over time at a substantial rate. A similar analysis also shows that more and more research is being conducted by teams, and the size of the teams has been going up over the years. He further shows that teamwork and specialization are greater in fields with deeper knowledge.
Such a knowledge burden mechanism helps explain why productivity rates have not grown over the past several decades despite the large expansion of the overall research effort, with potentially negative implications for long-run economic growth. It further suggests that the very nature of innovation is changing.
Read the full post at The Wall Street Journal.
Irving Wladawsky-Berger is a Visiting Lecturer in Information Technology at the MIT Sloan School of Management.