The data seem to speak for themselves regarding ageing. To ensure population stability (immigration is a separate and often contentious matter), the so-called fertility (or replacement) rate, being the number of children a woman is likely to have during her child-bearing years, has famously been marked as 2.1, whereby two workers will replace their parents as they drop out of the labour force. A fertility rate of above 2.1 (but not too much above) will add additional young workers to support their retired parents and grandparents, while a fertility rate below that number will put increasing pressure on national economies seeking to support their senior citizens. As has been well publicized, many countries especially in Europe and Asia are well below the replacement rate. Thus, for Europe taken as a whole, the replacement rate is 1.6 (being significantly below that in certain Mediterranean and East European countries as well as dropping in Germany); it is around 1.6 in China (largely the result of the one-child policy); it is 1.4 in Japan and 1.3 in South Korea. To the contrary, the numbers in France, Nordic countries and the United States show a replacement rate around 2.1, while Israel, almost alone in the Western world, is at 2.9. Taken as a whole, nearly half of the world’s population may soon not be replacing itself.
All of this is well and good, but what about IP? Let’s start with the basic question: how, if at all, does age affect inventive activity? It seems to this Kat that one proxy for gauging this metric is the distribution of inventors by age. Using five to ten-year age cohorts, is inventive activity, as measured by the number of patents, independent of the age of the inventor, or is there a greater likelihood that a certain age cohort(s) will be engaged in inventions? This Kat is not aware of any of empirical studies on this point (but he would be delighted if any Kat readers could direct him to such research). Indeed, this Kat wonders whether, even in this age of big data in the service of IP (see for example the piece by Kat riend Nigel Swycher in the latest issue of IAM magazine, “Big data solutions to determining IP risk and value”), it is even possible to extract such information.
Let’s assume that such data, at least in some form, can be assembled. What they might be their implications? An insight to this question was suggested in a contrarian piece that appeared on May 31st in The Economist, here. Entitled “Quality time”, with the byline (“Why shrinking populations may no bad thing”), the article (from which some of the data mentioned above was extracted) argued that when education of senior citizens is taken account, the fertility rates need only be between 1.5-1.8 to achieve stability. This is because, as the piece went to conclude:
Better-educated people are more productive and healthier, retire later and live longer. Education levels in most places have been rising and are likely to continue to do so…..Educating more people to a high level will be expensive, both because of the direct costs and because the better-educated start work later. But they will contribute more to the economy throughout their working lives and retire later, so the investment will pay off.
Let’s assume for purposes of argument that there is merit to this conclusion. If so, the ”contribution” to the economy in the form of putting downward pressure on the younger generations of workers to support senior citizens is understandable. But does this “contribution” also mean increased inventive activity? Perhaps extending the working careers of the well-educated will increase the number (and even the so-called “quality”) of patents. If that is a likely outcome, then the observation made in the article should be brought to bear on the analysis of the effects of ageing on inventive activity. But assume, to the contrary, that inventive activity is skewed to young age cohorts. In that case, the presumed benefits from increasing education on altering the dependency ratio between the young and the elderly might actually be offset to some extent by the extended presence of less inventive senior citizens in the productive workplace (who might even block the market entry of potentially inventive younger employees). Given the potential import of which outcome is more likely, obtaining good data to reach informed decisions seems to this Kat to be a matter of particular importance.
I am fairly confident you would find that the number of patents issued to inventors varies significantly with age, and that a more well educated and intellectual population would be anticipated to continue to be innovate as the population ages.
ReplyDelete(These could be measured by random sampling of ages of published inventors, and by comparisons between countries with different demographics, ex. Japan vs Israel).
One complication in investigating innovation relative to age might be the existence of senior management who are listed on every or nearly every patent application produced by a company. In some cases, this is the result of a truly innovative mind who has experience and vision and is far more productive than any of their younger employees could hope to be due to greater understanding of the technical field. In other cases, it is more a question of being the boss and it being a carer ending move not to list the boss on the application.
Another question that comes to mind: what is the relationship between productivity and density? Will a lower replacement rate result in perhaps more innovations per capita, but at a greatly reduced total volume of innovations?