Conventional marxist theory used to argue that capitalism was doomed to regular and deepening crisis due to the impact of a phenomen known as ‘the falling rate of profit’. Basically the idea runs as follows: since on the marxist view labour is the only source of genuine wealth creation, and capital accumulation means that the proportion of active labour to ‘dead labour’ (capital investment) tends to decline, then the ‘rate of profit’ will diminish accordingly. Now I certainly have no intention of going into all this rigmorole, but I do remember some wit back in the seventies suggesting that if this was the case, then, for example, we could argue that intelligence must be falling, since the quantity of active human brainpower as a proportion of accumulated knowledge (living to dead ‘mental labour’) was constantly diminishing.
Well, low and behold, a paper out this week at the NBER argues just this case.
The paper in question is: The Burden of Knowledge and the ‘Death of the Renaissance Man’: Is Innovation Getting Harder? Benjamin F Jones. Here’s the abstract.
This paper investigates, theoretically and empirically, a possibly fundamental aspect of technological progress. If knowledge accumulates as technology progresses, then successive generations of innovators may face an increasing educational burden. Innovators can compensate in their education by seeking narrower expertise, but narrowing expertise will reduce their individual capacities, with implications for the organization of innovative activity – a greater reliance on teamwork – and negative implications for growth. I develop a formal model of this “knowledge burden mechanism” and derive six testable predictions for innovators. Over time, educational attainment will rise while increased specialization and teamwork follow from a sufficiently rapid increase in the burden of knowledge. In cross-section, the model predicts that specialization and teamwork will be greater in deeper areas of knowledge while, surprisingly, educational attainment will not vary across fields. I test these six predictions using a micro-data set of individual inventors and find evidence consistent with each prediction. The model thus provides a parsimonious explanation for a range of empirical patterns of inventive activity. Upward trends in academic collaboration and lengthening doctorates, which have been noted in other research, can also be explained by the model, as can much-debated trends relating productivity growth and patent output to aggregate inventive effort. The knowledge burden mechanism suggests that the nature of innovation is changing, with negative implications for long-run economic growth.
The implications of this: well the most obvious is that more years of study are required (the lengthening doctorates bit). This may not be as detrimental from an economic point of view the author suggests, since really it is possible to work and study at the same time, and what we may be moving to is a society where the concept of lifelong education is the important one.
An issue our author doesn’t seem to consider: networking externalities. The technology is changing. The arrival of the internet means that any individual can process far more information far more rapidly today (oh those lazy, sleepy afternoons in the library stacks, how I miss them, yawn). So this is going to offset the accumulation of ‘dead’ information problem.
Also, of course, there are more people alive today, and a higher proportion of them are engaged in some sort of research or other. The first century Greek philosopher Plutarch famously speculated that there might be more alive in his generation than the sum total of all those who had lived in previous generations. This may well have been true of the 20th century also, and will possibly be true of the first half of this one.
One other paper the same author published this week seems to offer some sort of hope for us ‘grey hairs’:
Age and Great Invention
Benjamin F Jones.
Great achievements in knowledge are produced by older innovators today than they were a century ago. Using data on Nobel Prize winners and great inventors, I find that the age at which noted innovations are produced has increased by approximately 6 years over the 20th Century. This trend is consistent with a shift in the life-cycle productivity of great minds. It is also consistent with an aging workforce. The paper employs a semi-parametric maximum likelihood model to (1) test between these competing explanations and (2) locate any specific shifts in life-cycle productivity. The productivity explanation receives considerable support. I find that innovators are much less productive at younger ages, beginning to produce major ideas 8 years later at the end of the 20th Century than they did at the beginning. Furthermore, the later start to the career is not compensated for by increasing productivity beyond early middle age. I show that these distinct shifts for knowledge-based careers are consistent with a knowledge-based theory, where the accumulation of knowledge across generations leads innovators to seek more education over time. More generally, the results show that individual innovators are productive over a narrowing span of their life cycle, a trend that reduces — other things equal — the aggregate output of innovators. This drop in productivity is particularly acute if innovators’ raw ability is greatest when young.