Human capital is the ability, knowledge and skill base that is typically acquired or enhanced by an individual through education and training. The National Center for Science and Engineering Statistics (NCSES) at the National Science Foundation (NSF) has a rich set of human capital indicators. NCSES’s academic surveys provide information on sources of academic funding for science and engineering research, and those data give snapshots of the balance of investments among various fields of study and the infrastructure that is supported by federal dollars at academic institutions.1
NCSES’s Science and Engineering Statistical Data System (SESTAT) is a comprehensive database on education, employment, work activities, and demographic characteristics. SESTAT collects information from three biennial sample surveys of individuals: the National Survey of College Graduates; the National Survey of Recent College Graduates, and the Survey of Doctorate Recipients. At the Census Bureau, a 2009 change to the American Community Survey added a “field of bachelor’s degree” question, which had been recommended by the National Research Council (2008).2 NCSES plans to draw and refresh the entire National Survey of College Graduates from the American Community Survey. We note that NCSES is the international leader on science and engineering education statistics.
The National Science Board’s Science and Engineering Indicators (SEI) biennial report contains data on enrollments and degrees by demographic classification, including data by citizenship, place of birth, and postdoctoral fellowship. It has information on students by type of financial support in graduate school, including support from the federal government, by field of study. The data include “stay rates” and intent to stay in the United States. Data are also available on tertiary degrees conferred in other countries.
NCSES currently publishes a range of statistics on published papers, including country, countries’ shares of cited papers, and international collaboration. NCSES also uses its Business Research and Development and Innovation Survey (BRDIS) for employment statistics, publishing an InfoBrief on research and development (R&D) employment intensity, domestic and foreign R&D employment, and company-performed R&D expenditures per R&D employee.3 The National Center for Education Statistics provides NCSES with elementary, secondary and tertiary education statistics for publication.
1It should be noted that NSF includes social sciences and psychology in its definition of science and engineering: see http://www.nsf.gov/statistics/infbrief/nsf10315/nsf10315.pdf [December 2011].
2The Panel to Assess the Benefits of the American Community Survey for the NSF Science Resources Statistics Division recommended: “The National Science Foundation should use current data from the American Community Survey to evaluate the degree to which the American Community Survey with the field-of-degree question would allow for the production of mandated indicator reports in the future” (National Research Council, 2008, p. 7).
There is a persistent problem of underutilization of existing data on science, technology, engineering, and mathematics (STEM) workers. Although worker mobility is undermeasured in traditional STI employment statistics, there are longitudinal studies that capture data on movement of workers with STEM degrees within and outside traditional science and engineering jobs. Staff from a range of agencies emphasized to the panel that they have much underutilized data, particularly regarding human capital. For example, at the panel’s workshop Erika McEntarfer of the Census Bureau described a potential use of data from the Longitudinal Employer-Household Dynamics Survey that could link workers longitudinally across jobs. Her division is currently working on this project. Integrating these data (along with similar data on firm dynamics) into the statistics offered by NCSES would create a useful set of indicators. Trends on how macroeconomic fluctuations affect workers and knowledge flows in science and engineering occupations would be just one output from these data. More descriptive data on innovators would also broaden understanding of the skill sets that lead to advances in science and technological innovation. Getting this information would require case studies, which could enhance understanding of the statistics based on counting stocks and flows of individuals and knowledge capital.
There are also data from BRDIS that have not been fully used. Headcounts and related statistics are available for the United States and worldwide for employment, R&D employment, R&D employment by occupation and gender, and highest degree earned. For the United States, there are also counts of H-1B and L-1 visa holders.4 Full-time-equivalent (FTE) counts are available for science and engineering workers, as are the number of these FTEs that are funded by the federal government in the United States. Thus, NCSES could publish statistics other than those released in the 2010 InfoBrief on employment statistics. In particular, NCSES could use BRDIS alone to show the number of non-U.S. citizens who have H-1B or L-1 visas and are employed in the United States as R&D scientists and engineers. NCSES has also published an InfoBrief on foreign science and engineering students who are enrolled in schools in the United States.5 Currently, NCSES publications do not include statistics on how many U.S. employees in science and engineering occupations were trained in a specific foreign country. Continued collaborative effort between NCSES and the Department of Homeland Security are expected to yield better STEM education and workforce indicators.
Based on a crude measure of interest to users of the SEI online statistics, education and workforce measures are the most viewed (unadjusted for length of views), with statistics on states a distant second. NCSES’s bedrock statistics on human capital, therefore, are one of the agency’s most important products. However, more extensive analytically based measures of
4The H-1B and L-1 visas are for foreign workers in specialty occupations in fields that require highly specialized knowledge and intra-country transferees, respectively. For the fields covered, see http://www.uscis.gov/portal/site/uscis/menuitem.eb1d4c2a3e5b9ac89243c6a7543f6d1a/?vgnextoid=73566811264a3210VgnVCM100000b92ca60aRCRD&vgnextchannel=73566811264a3210VgnVCM100000b92ca60aRCRD [January 2012].
5See InfoBrief NSF 10-324, July 2010: available http://www.nsf.gov/statistics/infbrief/nsf10324/nsf10324.pdf [December 2011]. All of the statistics reported in this brief are special tabulations from the Student and Exchange Visitor Information System database, maintained by Immigration and Customs Enforcement of the U.S. Department of Homeland Security.
human capital, particularly related to inputs to innovation, would be valuable to policy makers and others.
Policy makers, university administrators, and business strategists are all interested in an evidence-based answer to the following questions: How much knowledge capital does the United States have? How many people, possessing what kind of skills, are needed to achieve a robust STI system? How mobile are science and engineering workers between public and private sector jobs? Is the population of science and engineering researchers aging, and if so, at what rate? There is also a keen interest in internationally comparative data: Where does the United States rank among nations on elements of advancement of scientific knowledge? In which fields is the United States a net exporter of knowledge? The America COMPETES Reauthorization Act of 2010 calls for NCSES to provide information on STEM education. NCSES has many elements already in its datasets to satisfy this requirement.
At the panel’s workshop, several presenters described measures of STI talent that go beyond the counts of science and engineering undergraduates, graduate students, doctoral recipients, and postdoctorate workers. For example, Howard Alper (University of Ottawa), listed items that would be useful in a suite of “talent” measures, including: data from the Programme for International Student Assessment (PISA) for 15-year-olds; percentage of population with tertiary education; numbers of bachelor-degree graduates in science and engineering-related disciplines; number of Ph.D.s in science, math, and engineering; and R&D personnel in business. We note that NCSES currently publishes statistics on each of these measures.
Other suggested measures of STI talent included the pool of students who are initially trained in community colleges, as a pathway to a bachelor’s degree and higher degrees.6 It is often noted by engineers that many high-skilled jobs in certain engineering fields require a master’s-level degree and not a doctorate. Therefore, NCSES has an opportunity to expand its human capital indicators by providing measures on master’s-level STI talent. With such data, one could answer several related questions: Where is there excess demand for STI talent and what type of talent is in high demand? What additional sources of “talent” can best be tapped to supply these workers?
More detailed data on immigrants, women, minorities, and people with disabilities in the science and engineering workforce would provide information to answer such questions about talent. Without good counts of these individuals, the full STI workforce capacity of the nation cannot be known. It is also important to consider what fields other than physical and biological sciences, technology, engineering, and mathematics are important for advances in STI. A careful assessment of network sciences, as well as behavioral and social sciences, would be valuable because they are in part responsible for acceleration of innovation. For example, social networks are used in “collaboratories” to further scientific inquiry without the need for brick-and-mortar facilities. These contributions to the scientific enterprise come from behavioral and social sciences. For advances in basic science, it is arguably true that the physical and biological science disciplines are the primary reservoir of talent. However, the broader scope of innovation, including managerial and organizational elements, includes the social, behavioral and managerial sciences as critical contributors to outputs and outcomes. Christopher Hill (2007) argues that the skill set is changing for advancing innovation:
6In July 2011 NCSES published an InfoBrief, “Community Colleges: Playing an Important Role in the Education of Science, Engineering, and Health Graduates.” Available: http://www.nsf.gov/statistics/infbrief/nsf11317/nsf11317.pdf [December 2011]. The data for that report were taken from NCSES’s National Survey of Recent College Graduates.
In the post-scientific society, the creation of wealth and jobs based on innovation and new ideas will tend to draw less on the natural sciences and engineering and more on the organizational and social sciences, on the arts, on new business processes, and on meeting consumer needs based on niche production of specialized products and services in which interesting design and appeal to individual tastes matter more than low cost or radical new technologies.7
CONCLUSIONS AND RECOMMENDATION
Since there is a rich set of topics on human capital that NCSES’s indicators inform, the panel chose only a few items to focus on in this report. The panel’s final report will address other, no less important, items.
First, it is important to obtain better measures of rapid changes in the STI workforce, including job mobility. Worker mobility between jobs, occupations, and nations is important to measure since it is an indicator of how knowledge flows and spillovers occur and how knowledge markets operate. For instance, it is important to know in what industries people with degrees in science—in both STEM fields and social and behavioral sciences—work in throughout their lifetimes. It is also of national interest to have information on the flows of undergraduate and graduate students, postdoctoral fellows, and workers between states and between countries.
Second, it is important to determine where there are overlapping datasets among the federal statistical agencies on STEM education and workforce statistics. NCSES has long-term relationships with several statistical agencies that provide education data for science and engineering indicators. Some education indicators are collected through NCSES surveys, while others are reported by NCSES on the basis of statistics generated at other agencies and organizations. In particular, NCSES and the National Center for Education Statistics (NCES) both collect data on higher education degree holders. Very recently, NCSES and NCES staff agreed to undertake a joint gap analysis to examine education data-gathering activities. This analysis will enable both agencies, and others, to determine where there is useful overlap, where there are voids, and where efficiencies can be achieved by streamlining efforts. A series of workshops on potential linkages, interoperability and rationalization of datasets on human capital will further improve efficiencies among the agencies. This will enable NCSES to plan for a greater role of data clearinghouse specifically on STI education and workforce data.
Third, there are clear near-term opportunities for NCSES to mine BRDIS for indicators related to the STEM labor force. NCSES already has several activities under way or planned to update its portfolio on education and workforce statistics. For instance, NCSES is rethinking the collection of data on the science and engineering workforce as the National Survey of College Graduates transitions to a sampling frame completely built from the American Community Survey; it is also implementing the International Survey of Doctoral Recipients and integrating it into the Survey of Doctoral Recipients; and it is developing an Early Career Doctorate Project and considering new statistics on earnings of STI workers as a potential new indicator. All of these efforts can provide new indicators that address user needs. For example, a science and engineering wage index could facilitate international comparisons and become another explanatory variable for international flows of science and engineering students and workers. The panel’s final report will offer recommendations on how these efforts should be prioritized.
RECOMMENDATION 1: The National Center for Science and Engineering Statistics should explore methods of using existing longitudinal data on labor force mobility related to science, technology, and innovation activities in the United States and abroad. This work should include gap analyses and workshops with statistical agencies to determine how to achieve efficient management of datasets and statistics for human capital indicators. The agency should also use its own data resources, especially the Business Research and Development and Innovation Survey, for new employment measures.