Innovation Policy and the Economy, Volume 11



to create quotas, forcing research grants to be given to younger scholars, even when their
proposals receive lower evaluation scores.

The smooth trends in NIH grantee age, however, can be understood through increased
training duration and demographic shifts. In fact, there is little that is unique about the recent
NIH grant age patterns. For example, Nobel Prize winning achievements in physics and
chemistry show similarly sized, smooth age dynamics over the late 20th century (Jones and
Weinberg 2010). With regard to the biosciences, many observers have noted that doctoral and
post-doctoral phases are extending. For example, the duration of the Ph.D. in biosciences rose
by 0.9 years per decade between 1970 and 1996.17 This rate is very similar to the broader delay
in innovative careers that was reviewed across many types of research in Section II. Thus part of
the decline in early life-cycle innovation can be seen not as an NIH phenomenon or biosciences
phenomenon, but as a much more general feature. As shown in Figure 5A, the declining
percentage of NIH grants given to scholars age 35 or below follows a broader decline in the
share of young medical school faculty members, so that a large part of the trend appears not to be
selection within academic scholars but rather the increasing absence of younger academic
scholars.18

These age shifts are also partly a function of demographics. As Jones (2010) emphasizes,
the 20th century aging phenomenon in Table 1 is due partly to a decline in early life-cycle
productivity (Figure 2) and partly to the increasing age of the background population.19 This
demographic effect is straightforward: when there are more older scholars around, more ideas
will tend to come from older scholars. The baby-boom generation in particular has created a
mass of aging scientists in recent decades. In fact, Figure 5B shows that while the percentage of
NIH grant recipients age 50 or above has increased dramatically, this trend closely tracks the
percentage of medical school faculty age 50 or above, so that we would expect the apparent

17 Author’s calculations, using data from Tilghman et al. (1998).

18 Figure 5 presents the author’s calculations using the NIH dataset, “Age Distribution of NIH RPG Principal
Investigators Compared to Medical School Faculty, 1980-2006”, which is available publicly from
http://report.nih.gov/investigators and trainees/index.aspx (Access date: 16 March 2010).

19 See also footnote 5.

23



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