natural experiment, the analysis of the quantum mechanics revolution further substantiates the
link between the current depth of knowledge in a field, its training requirements, and the ensuing
innovative output of young scholars.
Table 2: Age at Ph.D. Trends
Dependent Variable: Age at Highest Degree | ||
_______________(1)___________________ |
______________(2) | |
Year of Highest |
4.11*** |
4.39*** |
Degree (in 100’s) |
(0.61) |
(0.65) |
Data |
Nobel Prize Winners |
Nobel Prize Winners |
Field Fixed Effects |
No |
Yes |
Country of Degree |
No |
Yes |
Number of |
505 |
505 |
Time span |
1858-1990 |
1858-1990 |
Average age |
26.5 |
26.5 |
R2 |
0.084 |
0.283 |
Notes: Both specifications consider trends in the age at highest degree among
Nobel Prize winners. The coefficient gives the age trend in years per century.
Robust standard errors are given in parentheses. Field fixed effects for Nobel Prizes
comprise four categories: Physics, Chemistry, Medicine, and Economics. Source:
Jones (2010). *** Indicates significance at a 99% confidence level.
Collectively, we see a tendency toward broad and dramatic declines in early life-cycle
productivity among great minds and ordinary inventors, and we see close relationships with
increased training duration. Policymakers in some fields - especially in life sciences and at the
NIH - have noticed related increases in training duration and a decline in grant awards to
younger scholars, and are substantially concerned by these shifts within their field. As has been
summarized here, the aging patterns are a much more general phenomenon. Policy implications
will be discussed below.
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