The age distribution and retirement patterns of the S&E labor force affect its size, productivity, and the opportunities it offers for new S&E workers. For many decades, rapid increases in new entries into the workforce created a relatively young pool of workers, with only a small percentage near traditional retirement age. Now, individuals who earned S&E degrees in the late 1960s and early 1970s are moving into the later part of their careers.
The increasing average age of S&E workers may mean increased experience and greater productivity among them. However, it could also reduce opportunities for younger researchers to make productive contributions by working independently. In many scientific fields, folklore and empirical evidence indicate that the most creative research comes from younger people (Stephan and Levin 1992).
Aside from the possible effects on productivity, early career opportunities, and, perhaps, the culture within some scientific fields, the age structure of the S&E labor force has important implications for its growth rate. This section does not attempt to project future S&E labor market trends; however, it posits some general conclusions. Absent changes in degree production, retirement patterns, or immigration, the number of S&E-trained workers in the labor force will continue to grow for some time, but the growth rate may slow considerably as an increasing proportion of the S&E labor force reaches traditional retirement age. With slowing growth, the average age of the S&E labor force will increase.
Age Distribution of the S&E Workforce
Net immigration, morbidity, mortality, and, most of all, historical S&E degree production patterns affect the age distribution of scientists and engineers in the workforce. With the exception of new fields such as computer sciences (in which 56% of degree holders are younger than age 40), the greatest population density of individuals with S&E degrees occurs between the ages of 40 and 49. Figure
This general pattern also holds for individuals with S&E
doctorates. Because of the length of time needed to obtain a
doctorate, those who hold these degrees are somewhat older
than individuals who have less advanced S&E degrees. The
greatest population density of S&E doctorate holders occurs between the ages of 40 and 54. This can be seen most easily
Across all degree levels and fields, 26.4% of the labor
force with S&E degrees is older than age 50. The proportion
ranges from 15% of individuals with their highest degree in
computer sciences to 41% of individuals with their highest
degree in geosciences (figure
Altogether, the age distribution of S&E-educated individuals suggests the following likely effects on the future of the S&E labor force:
Taken together, these factors suggest a slower growing and older S&E labor force. Both trends would be accentuated if either new degree production were to drop or immigration were to slow, both concerns raised by a 2003 report of the Committee on Education and Human Resources Task Force on National Workforce Policies for Science and Engineering of the National Science Board (NSB 2003).
S&E Workforce Retirement Patterns
The retirement behavior of individuals can differ in complex ways. Some individuals retire from one job and continue to work part time or even full time at another position, sometimes even for the same employer. Others leave the workforce without a retired designation from a formal pension plan. Table
By age 61, slightly more than 50% of those with an S&E bachelor's degree as their highest degree are no longer working full time. The age at which at least half of S&E degree holders no longer work full time increases by degree level—to age 62 at the master's level and age 66 at the doctoral level. Longevity also differs by degree level when measuring the number of individuals who leave the workforce entirely: half of all S&E bachelor's degree holders left the workforce entirely by age 65, compared with S&E master's degree and doctorate holders who left the workforce at ages 66 and 69, respectively. Although many S&E degree holders who formally retire from one job continue to work full time or part time, formal retirement occurs at similar ages for all levels of degree holders: more than 50% of bachelor's, master's, and doctoral degree holders have formally retired from jobs by age 65, 66, and 67, respectively.
An important part of the growth of the S&E labor force comes from the increased presence of women and ethnic minorities. In 2006, white males constituted 58% of those in the labor force over age 50 whose highest degree was in S&E. Among those under age 30, only 35% were white males (NSF/SRS 2006). This represents both a change in the composition of the total U.S. labor force and a growth in the participation of women and minorities in S&E.
Both women and underrepresented ethnic minorities
have shown steady growth in their proportion of the S&E
labor force (see figures
Representation of Women in S&E
Women constituted more than one-fourth (26%) of the college-educated workforce in S&E occupations and two-fifths (40%) of those with S&E degrees in 2006, according to NSF's SESTAT data.
Census data on S&E occupations from 1980 to 2007 show
the number of women in S&E occupations rising from 12%
to 27% over those 27 years (figure 3-27). Figures
Age Distribution and Experience. On average, women
in the S&E workforce are younger than men (figures
Unemployment. Unemployment rates in 2006 were
somewhat higher for women in S&E occupations than for
men: 2.2% of men and 2.9% of women were unemployed. In
contrast, the unemployment rate in 1993 was 2.7% for men
and 2.1% for women (table
Representation of Racial and Ethnic Minorities in S&E
With the exception of Asians/Pacific Islanders, racial and ethnic minorities represent only a small proportion of those employed in S&E occupations in the United States. Collectively, blacks, Hispanics, and other ethnic groups (the latter category includes American Indians/Alaska Natives) constitute 24% of the total U.S. population, 13% of college graduates, and 10% of college-educated individuals employed in S&E occupations.
Conversely, Asians/Pacific Islanders, despite constituting only 5% of the U.S. population, accounted for 7% of college graduates and 14% of those employed in S&E occupations in 2003. Although most (82%) Asians/Pacific Islanders in S&E occupations were foreign born, those born in the United States were also more highly represented in S&E than in the total workforce.
Age Distribution. As is the case for women, underrepresented
racial and ethnic minorities in the S&E workforce
are much younger than non-Hispanic whites in the same
S&E jobs (figure
Salary Differentials for Women and Minorities
Trends in Median Salaries. Women and members of underrepresented minority groups have generally lower earnings than their male and nonminority counterparts. However, differences in average age, work experience, fields of degree, sector of employment, and other characteristics can make direct comparison of salary and earnings statistics misleading. This section discusses these income gaps and explores some of the underlying factors that may affect them.
Factors Influencing Salary Differentials. Regression analysis is a statistical method that can be used to examine salary and other differences simultaneously. Although this type of analysis can provide insight, it cannot give definitive answers to questions about the openness of S&E to women and minorities. The most basic reason is that no labor force survey ever captures information on all characteristics that may affect compensation.
In 2006, women with S&E bachelor's degrees working full time had mean salaries that were 36.2% less than those of their male counterparts. Likewise, full-time salaries of blacks, Hispanics, and individuals in other underrepresented ethnic groups with S&E bachelor's degrees were 25.8% less than those of non-Hispanic whites and Asians/Pacific Islanders with S&E bachelor's degrees. While still substantial, these salary differentials decrease as level of degree increases for both women and ethnic minorities, reaching 21.1% and 15.0% respectively.
Effects of Age and Years Since Degree. On average, women and members of underrepresented minority groups are younger than their counterparts in most S&E fields. Controlling for differences in both age and years since receipt of degree reduces the estimated salary differential for both women and minorities at every degree level.
For women, it reduces salary differentials by about one-third at the bachelor's and master's degree levels, and by about half at the doctorate level. Statistical controls may make less difference at lower degree levels because similar proportions of men and women with S&E degrees are in mid-career, but a larger proportion of men are at older ages, where salaries begin to decline.
For underrepresented ethnic minorities, controlling for age and years since degree produces proportionally larger reductions in salary differentials than is the case for women. Introducing these controls reduces salary differentials between underrepresented minorities and both non-Hispanic whites and Asians/Pacific Islanders by more than half at all degree levels.
Effects of Field of Degree on Salary Differentials. Controlling for field of degree in addition to age and years since degree reduces the estimated salary differentials for women with S&E degrees to –12.0% at the bachelor's degree level and to –7.6% at the doctorate level. These reductions generally reflect the greater concentration of women in the lower-paying social and life sciences as opposed to engineering and computer sciences.
Field of degree is also associated with reduction of estimated salary differentials for underrepresented ethnic groups. Controlling for field of degree further reduces salary differentials to –9.1% for individuals with S&E bachelor's degrees and to –5.5% for individuals with S&E doctorates. At the doctoral level, field of degree, age, and years since degree together account for two-thirds of salary differentials for underrepresented ethnic groups.
Effects of Occupation and Employer Characteristics on Salary Differentials. Occupation and employer characteristics affect compensation. Academic and nonprofit employers typically pay less for the same skills than employers pay in the private sector, and government compensation falls somewhere between the two groups. Other factors affecting salary are the sector of the economy, the U.S. region where a person works, and whether the person is working in S&E or in R&D. However, occupation and employer characteristics may not be determined solely by individual choice; they may also in part reflect an individual's career success.
When comparing women with men and underrepresented ethnic groups with non-Hispanic whites and Asians/Pacific Islanders, controlling for occupation and employer further reduces salary differentials. At the doctoral level, controlling for occupation leaves no statistically significant difference between the salaries of underrepresented ethnic groups compared with non-Hispanic whites and Asians/Pacific Islanders.
Effects of Family and Personal Characteristics on Salary Differentials. Marital status, the presence of children, parental education, and other personal characteristics are often associated with differences in compensation. Although these differences may involve discrimination, they may also reflect many subtle individual differences that can affect work productivity. For example, having highly educated parents is associated with higher salaries for individuals of all ethnicities and both sexes. It may well be associated with greater academic achievement not directly measured in these data; alternatively, it may be associated with family and personal networks that are conducive to career success. In any event, for many individuals in many ethnic groups, historical discrimination probably affected parents' educational opportunities and achievement.
Controlling for these additional characteristics changes salary differentials only slightly for each group and degree level. An additional issue for the wage differentials of women, however, is that family and child variables often have different effects for men and women. In these estimates, both marriage and children are associated with higher salaries for men with S&E degrees at all levels, but have a negligible association with women's earnings. Allowing for these differences in sex effects reduces the salary differential at the bachelor's degree level to 4.7% and leaves no statistically significant difference in salary at the master's degree and doctorate levels.