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6
IMPACTS OF RESEARCH ON THE LABOR
MARKET AND CAREER DEVELOPMENT
Several speakers during the workshop contended that the most
important influence of research is the training it provides for
undergraduates, graduate students, and postdoctoral fellows, who then
bring those experiences and skills into the workplace. Three speakers at
the workshop looked specifically at that assertion. Economic analyses
can reveal the value of these workers to the economy, while survey
results can uncover the preferences and goals of workers and employers.
However, many questions still surround the processes through which
supply and demand interact.
R AND D SPENDING AND THE R AND D WORKFORCE
In the short term, the relationship between R and D and the
workforce is relatively weak, said Anthony Carnevale, Director of the
Georgetown University Center on Education and the Workforce. But in
the longer term, the relationship can be much stronger.
Explaining the Residual
Economists explain economic growth and productivity increases in
part by citing the development of human capital and investments in
physical infrastructure. But those two factors explain only part of the
growth of the economy. The residual— “between 65 and 40 percent,
depending on who you read,” Carnevale said— comes from advances in
knowledge.
Many economists think of these advances in knowledge as being
embodied in technologies, but in fact the residual consists of everything
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50 MEASURING THE IMPACTS OF FEDERAL INVESTMENTS IN RESEARCH
that cannot be measured as a direct investment in the economy.
Carnevale said that he preferred to think of advances in knowledge as the
way people combine and use resources, whether human, technological,
or otherwise. So advances in knowledge include the development of
Walmart as opposed to mom and pop hardware stores, not just the direct
effects of technology.
R and D Spending and Economic Growth
Connecting federal spending on R and D to these advances in
knowledge is a difficult problem. For example, R and D directly involves
a fairly limited number of people. About 1.4 million U.S. workers spend
at least 10 percent of their time doing R and D, out of a total workforce
of about 150 million people. (The former number includes social
scientists, although the Center on Education and the Workforce typically
does not include social scientists among workers in science, technology,
engineering, and mathematics, or STEM.) The relatively small size of the
STEM workforce explains why federal investments in research have
relatively small short-term impacts on employment.
The STEM workforce engages in both research, which Carnevale
identified as scientific investigations— and development — or the
application of scientific knowledge. While research has sometimes led
directly to technologies that are economically important, development is
a much more important source of innovations, according to Carnevale.
“Historically, science owes a whole lot more to the invention of the
steam engine than the steam engine ever owed to science. That is, most
of the development of economies occurs in application, not in labs.” A
strong argument also can be made, he said, that the economic value from
development has been growing more rapidly than the economic
development from research. “A lot of wealth creation in the world now
has to do with process improvements, not so much invention.” Even in
industries such as pharmaceuticals, where discoveries lead to new
products, the commercialization and distribution networks bring in much
of the new revenue.
The Growth of the STEM Workforce
The STEM workforce, which is larger than the number of people
doing R and D, is growing, said Carnevale. Today, people who work in
science, technology, engineering, or mathematics— not counting social
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IMPACTS OF RESEARCH ON THE LABOR MARKET AND CAREER DEVELOPMENT 51
scientists—represent 5 percent of the workforce, and this percentage is
increasing.
The STEM workforce represents the endpoint of a long process of
attrition, Carnevale pointed out. Many people with high mathematics
scores in grade school and high school do not want to be STEM workers
and do not pursue those subjects when they go to college. Among those
who enter college declaring an interest in STEM subjects, many switch
to other majors before they graduate. Even among STEM majors, many
go into other careers. And among those who begin in STEM careers,
many move out of the STEM workforce, especially after the age of 35.
In part, this attrition results from opportunities in other fields.
Wages for STEM workers are relatively high, but the wages in other
fields associated with high test scores in areas such as mathematics are
even higher. Competencies developed in STEM fields are in demand in a
large and growing share of occupations that pay well, which translates
into many opportunities for people who have those competencies.
Also, workers who switch out of STEM fields tend to have values
and interests that are different than those associated with STEM
occupations, Carnevale said. Among STEM workers, the values and
interests recorded by industrial psychologists are relatively narrow,
whereas the values and interests in the general workforce are relatively
broad, especially for high-achieving students who have many choices.
Given these observations, said Carnevale, the United States is going
to have to rely more and more on foreign-born STEM workers.
International diversity is now greater than the domestic diversity in the
STEM workforce, and a healthy and productive STEM workforce will
require focusing on both sources of diversity.
SURVEYS OF GRADUATE STUDENTS AND POSTDOCTORAL
FELLOWS
Existing surveys reveal valuable information about the career
trajectories of graduate students, postdoctoral fellows, and early career
scientists and engineers, but they also have many limitations. Henry
Sauermann, Assistant Professor of Strategic Management at the Georgia
Institute of Technology, profiled existing surveys and described a new
survey that he and a colleague conducted that has provided valuable
additional information.
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52 MEASURING THE IMPACTS OF FEDERAL INVESTMENTS IN RESEARCH
Existing Sources of Data
Several different data sources provide information on the aggregate
flows and stock of scientists and engineers. The National Science
Foundation’s Survey of Earned Doctorates, which Ph.D. recipients fill
out when they graduate, provides much valuable data and now includes
financial information such as salaries, at least for the people who have
job offers. In addition, the Survey of Doctorate Recipients (SDR), the
National Survey of Recent College Graduates (NSRCG), and the
National Survey of College Graduates (NSCG) – NSF’s other personnel
surveys— all provide important data on the stock of intellectual capital
available to the economy. In addition, some information on postdoctoral
fellows is available through the Sigma Xi survey and through the SDR.
Once students become active scientists, they begin to produce
publications and patents, which can be used to track where people go,
what they do, and the extent of their collaborations. Finally, a new
federal data collection program, STAR Metrics (discussed in detail in
Chapter 8) collects information on funding for public research and the
extent to which that funding is used to support postdocs, Ph.D.’s, or other
students.
Sauermann described what he called his “wish list” of data that
would be very useful to have. For example, when a student reports
moving from Stanford University to a company, the move reflects a labor
market transaction. But the data do not reveal what the student or the
company wants. More information is needed on both sides to know how
well the job market is operating. On the supply side, the data might
include aspirations, intentions, and skill sets. On the demand side, what
kinds of jobs are open and what kinds of skills do firms need? For
example, an ongoing argument, said Sauermann, is over whether the
United States has too few scientists who know something about business
and who can work in larger teams and companies. “It’s a question about
the match between the training that individuals receive and what is
required on the demand side.”
It is also important to understand more about how the labor market
works, Sauermann observed. Supply and demand might match in the
aggregate, but there may be great inefficiency in that process. Not every
job seeker knows all the potential employers, and not all the potential
employers know about all the people they might hire. How do students
collect information? Who tells them about different careers? To what
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IMPACTS OF RESEARCH ON THE LABOR MARKET AND CAREER DEVELOPMENT 53
extent do advisors know what an industry or government job entails? All
of these questions are important.
It also would be interesting in know more about the training
experience itself and how training translates into future career outcomes,
Sauermann said. An ideal data set would track individuals when they
enter a Ph.D. program, ask them why they are seeking a doctorate, track
their learning experiences, and determine how their experiences changed
their intentions. “This is really important if you think of graduate school
as the place that trains people and socializes people into becoming
scientists.”
Current data reveal very little about people who do not graduate. Do
they consider their time in graduate school to have been wasted? Was it
good for them to realize that graduate school might not have been a good
fit? How do institutions make selection decisions?
Finally, current data provide little information on people who earn
doctoral degrees outside the United States, though some efforts are under
way to get more data about these individuals.
A Science and Engineering Ph.D. and Postdoctoral Fellow Survey
To learn more about the attitudes and actions of graduate students
and postdocs, Roach and Sauermann (2010) conducted the Science and
Engineering Ph.D. and Postdoc Survey (SEPPS) at 39 leading research
universities in the United States. They collected contact information for
30,000 individuals, conducted the survey in the spring of 2010, and had
about a 30 percent response rate. The survey focused on advanced Ph.D.
students who had passed any necessary exams and postdocs in the life
sciences, chemistry, physics, engineering, and computer science.
One question they asked was, “Thinking back to when you began
your Ph.D. program, how important were the following factors in your
decision to pursue a Ph.D.?” Respondents agreed more strongly with the
statements that they were always interested in research, were curious to
learn about a specific field, or needed a Ph.D. for a desired career. They
agreed less strongly with the statement that they admired the status of
people holding Ph.D.’s, and they agreed least with the statement that they
had difficulty finding another job. Research “is a career that people
consciously choose as opposed to being forced into it because there’s
nothing else to do,” Sauermann concluded. Also, although some foreign
graduate students and postdocs agreed that getting a Ph.D. offers
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54 MEASURING THE IMPACTS OF FEDERAL INVESTMENTS IN RESEARCH
opportunities to secure a visa, on average this motivation did not rank
highly.
When postdocs were asked the same question about their
fellowships, they agreed most strongly with the statements that a postdoc
would increase their chance to get a desired job and deepen their skills in
a particular area. They agreed moderately with the idea that a postdoc
gave them more time before deciding on a career and agreed less
strongly with the statement that they had difficulty finding another job.
When asked about their current funding sources, between 70 and 80
percent responded that they were funded by federal sources. About 60
percent got university fellowship and assistantship funding. Private
foundations were quite active, especially in some of the fields, while
very few respondents received industry funding. Postdocs in the
biological and life sciences got fewer university fellowships and
assistantships but more industry funding.
When postdocs were asked, “How involved were you in securing
your most important source of funding?” respondents in the biological
sciences averaged 50 points on a scale from 0 to 100, while people from
physics averaged 38, people from computer science 29, people from
chemistry 38, and people from engineering 39.
The survey asked whether their research contributes fundamental
insights or theories, or whether it creates knowledge to solve practical
problems, with people being allowed to respond affirmatively to both
questions. They were also asked whether they were interested in doing
basic research or applied research later in their careers. Among the life
scientists, people who got federal funding were much more likely to be
engaged in basic research than people who did not get federal funding.
Similarly, those getting industry funding were much less likely to be
engaged in basic research than those who did not. People receiving
funding from foundations were also more likely to be engaged in applied
research.
Interestingly, there was not much relationship between funding
source and career aspiration or what people wanted to do later. The only
exception is that people who got industry funding tended not to be
interested in working in basic research later.
Two other question asked, “How much freedom do you have in
choosing your research topics?” and “How much freedom do you
actually have in influencing the direction of your research projects?”
People with multiple funding sources reported an increased level of
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IMPACTS OF RESEARCH ON THE LABOR MARKET AND CAREER DEVELOPMENT 55
choice in terms of what they wanted to work on as well as in terms of
deciding how they want to work on these things. The only individual
funding source that made a big difference was foundation funding, where
people felt much more freedom in their choice of research topics.
“Presumably, that’s not because the funding makes them free, but
because they have a pet project, or they’re enthusiastic about something,
and they go apply to different foundations. . . . In that sense, foundations
seem to provide a lot of freedom— not because people get their money
first and then choose but because they choose first.” In contrast, industry
funding tends to have a slightly negative impact on freedom, but only for
postdocs.
Finally, the survey asked about the types of jobs respondents found
most appealing, whether teaching at a college or university or doing
research at a college or university, a government research institution, an
established firm, or a startup (Figure 6-1). Most of the respondents in the
life sciences wanted to have a faculty R and D job, with 50 percent
finding that the most interesting career. Physicists and computer
scientists rated that option even higher, but chemists and engineers had
less interest in a faculty R and D position and more interest in R and D
jobs at established firms. People who received industry funding were less
interested in a faculty research career and more interested in working
either for a start-up or for an established firm.
The experiences people have during their education shape their
involvement in the labor market, Sauermann concluded. “We need to
understand more of what these labor market processes look like to see
how we can direct or change, if we want to, these labor market
outcomes.”
THE COMPLEX NETWORK OF SKILLS AND INVESTMENTS
Recent discussions of U.S. science and technology policy have
emphasized the concept of global competitiveness. As James Evans,
Assistant Professor of Sociology at the University of Chicago, pointed
out, this concept inevitably poses the question: What is a globally
competitive STEM workforce, and how does the government best invest
in developing this kind of workforce?
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56 MEASURING THE IMPACTS OF FEDERAL INVESTMENTS IN RESEARCH
0.45
0.40
0.35
0.30
0.25
0.20
0.15
0.10
0.05
0.00
Biological/Life Chemistry Physics Engineering Computer Total
Science
Faculty-Teaching Faculty-Research Government Established Firm Startup Other
FIGURE 6-1 When postdoctoral fellows were asked “Please rank the following
careers from most likely to pursue to least likely to pursue,” Ph.D.’s in the
biological and life sciences, physics, and computer science were more likely to
favor faculty teaching jobs, while chemistry and engineering students were more
likely to opt for jobs with established firms.
SOURCE: Sauerman, 2010
Competitiveness as Size
One framing emphasizes the much repeated concerns about the
supply or size of the STEM workforce. For example, in a 2007 op-ed
article in the Washington Post, Bill Gates wrote, “Demand for
specialized technical skills has long exceeded the supply of native-born
workers with advanced degrees, and scientists and engineers from other
countries fill this gap. This issue has reached a crisis point.” This framing
produces a one-dimensional indicator of competitiveness that is fairly
easy to measure, said Evans. However, with only 5 percent of the world
population, the United States inevitably will drop below the 35 to 45
percent of global science and engineering activity that it retained through
the end of the twentieth century. As the world continues to develop, more
countries will be producing more scientific activity, and these scientists
will receive more publications, more citations, and more attention.
Existing measurements of the STEM workforce are closely cued to
size, Evans observed. Inputs to the workforce include the gross amounts
spent on training grants and an unknown proportion of research grants
spent on personnel in training. Outputs in surveys such as the SED, SDR,
and STAR Metrics are the numbers of doctorates, the sectors of their
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IMPACTS OF RESEARCH ON THE LABOR MARKET AND CAREER DEVELOPMENT 57
jobs, their incomes, and self-reports of activities and outcomes (such as
articles and patents). Given these measures, it is impossible to assess the
efficiency with which the system matches inputs with outputs.
Competitiveness as Efficiency
Another framing is to think of competitiveness in the STEM
workforce as efficiency in producing a sufficient supply of the skills in
demand. From this perspective, the United States can be seen as the most
efficient investor in science and engineering skill. Wages for STEM
workers have been largely flat, said Evans. Reports of low supplies of
scientists and engineers typically come from hot industries and from
potentially self-interested parties, suggesting that there is no undersupply
of skill. In fact, there may be an oversupply of skill or an oversupply of
the wrong types of skill.
This framing leads to a more nuanced concern about the efficiency
or the relevance of training investments in the STEM workforce. From
this perspective, the relevant inputs are the size of the training
investments and the relevant outcomes are the incomes of STEM
workers, assuming that the market is clearing. But to make such an
assessment, improved measurements would be needed. The first such
improvement would be the educational components of research grants.
The second would be improved information about STEM workers, such
as some of the information described in the previous presentation.
Measurements of efficiency also would require a better sense of
preferences to judge the elasticity of individual human capital
investments. For example, how much is it worth for students to have
control over the subject of their research? Some natural experiments have
yielded information on this issue. For example, when the size of a
research grant goes up, the student response goes up in an approximately
linear fashion. But real experiments should be organized, Evans said,
because the presence of confounders can make natural experiments hard
to interpret.
The problem with this framing is that it typically responds to past
rather than future labor needs, Evans noted. For example, this
perspective has motivated initiatives such as the Alfred P. Sloan
Foundation’s advocacy of programs that award the professional science
master’s as a terminal degree. But this effort may undervalue the
doctorate, even if society or U.S. companies benefit more from a
doctorate than does the recipient of that degree.
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58 MEASURING THE IMPACTS OF FEDERAL INVESTMENTS IN RESEARCH
Competitiveness as Quality
A third framing equates competitiveness with quality. From this
perspective, the United States can be seen as the elite global supplier of
science and engineering skill, Evans observed. This indicator of
competitiveness is very difficult to measure because it has such a high
dimension. It also renders obsolete the idea of thinking about
competitiveness in terms of a labor market. Instead, actual skills and
their actual and potential value must be considered within the broader
system of innovation. Researchers and their contributions can no longer
be treated as independently and identically distributed. Even bibliometric
methods are inadequate, because particular articles and patents fit within
the system in certain places, and understanding those places is the key to
the allocation problem. “When we open the box of content, instead of
just measuring the numbers of papers, we have to look at the papers, we
have to look at the content, and it’s a daunting exercise.”
Coauthorship and citation networks are one way to measure the
contributions of individuals, though “it’s not clear how much insight”
they can produce, said Evans. Authors and papers can be identified as
more central or more peripheral. Visualization techniques also make it
possible to determine how clusters are linked together to form modules
in a network. In addition, natural language processing and machine
learning can increasingly discern the landscape in millions of papers to
identify features of those landscapes. Together, these techniques “can
give us a much richer and more powerful view of the value of
investments,” said Evans.
Doctoral STEM Education
Students who undergo a doctoral education emerge with a
specialized set of skills and techniques, including meta-techniques, such
as being able to design a research project. This observation raises several
linked questions: What is the role of deep, specialized knowledge in
exploring new knowledge or skills? What is the role of social networks
developed or entered into through education in spreading knowledge or
skills? And what is the role of interdisciplinary laboratories in managing
novel combinations of knowledge or skills?
Evans studied these questions through an investigation of almost
20,000 publications involving Arabidopsis thaliana (a small flowering
plant used as a model organism) in which he identified principal
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IMPACTS OF RESEARCH ON THE LABOR MARKET AND CAREER DEVELOPMENT 59
investigators, organizations, subfields, countries, genes, gene products,
methods, and metabolites used. He found that the more persistent
researchers were within these identified terms, the more central they
were within the coauthorship network. At the same time, with these
researchers it was more likely that industry collaboration and funding
would influence their work to become more theoretically unexpected. In
essence, government sponsorship encouraged validation and moved work
toward the center of the network. Industry sponsorship encouraged
novelty and pushed work toward the periphery of the network.
“This suggests an interesting and important complementarity
between government and industrial efforts,” Evans concluded.
Governments sponsor hubs of knowledge, while industry involvement
encourages the exploration of high-value novel combinations.
Network analysis of geographic localization also has shown that
knowledge flows within communities and within firms. Furthermore,
many ties in the biosciences are formed through doctoral committees and
communities.
The important point, concluded Evans, is that analysts need to look
beyond labor markets to the relative values of skilled people.
Investigating this issue will require linking individuals and their
preferences with the papers and patents they produce. “Labor market
issues cannot be separated from the content of science.”
DISCUSSION
In response to a question from a workshop participant about the
importance of the arts and humanities in generating economic value,
Evans noted that he was very interested in the complex combinations of
STEM knowledge and the arts and humanities in such areas as design.
“It’s silly to cordon those things off in the context, especially, of industry
and productivity.”
Sauermann added that many people do not work in the field in
which they studied, and these numbers are especially low for the social
sciences. “Many people are studying stuff they don’t use. Maybe that’s
by choice. Maybe not. Again, I think it would be interesting to know.”
A workshop participant asked about the tendency of professors to
train students for positions in academia rather than industry, to which
Sauermann replied that some faculty members are very active in industry
and have their students work on industry grants. However, in a separate
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60 MEASURING THE IMPACTS OF FEDERAL INVESTMENTS IN RESEARCH
survey, he asked students what level of money, freedom, equipment, and
so on they expected to have in different kinds of careers, and many more
students marked “Don’t know” when asked about start-ups and
established firms than when asked about academia. “It could be that they
don’t search it out because they don’t want to be in industry. [But] there
is probably less information out there.”
Carnevale added that the U.S. Department of Education is
supporting the development of an online system that will collect
information on all transcripts of students, including those in college and
graduate school, and connect that information to wage records supplied
by every employer in America. Currently, in 26 states, a student in a
Ph.D. program in physics can find out how many of last year’s graduates
got a job, whether it was in physics, what their wages were, and the
duration of their employment.
