IRIS researchers will post working papers to repositories such as the NBER (www.nber.org/papers.html) and the Entrepreneurship Research & Policy Network (EPRN) (http://www.ssrn.com/en/index.cfm/erpn/). Research using UMETRICS and IRIS data has resulted in the following papers authored by IRIS PIs:
Why the US science and engineering workforce is aging rapidly
David Blau and Bruce A. Weinberg
Proceedings of the National Academy of Sciences
Early Edition: approved February 14, 2017
The science and engineering workforce has aged rapidly in recent years, both in absolute terms and relative to the workforce as a whole. This is a potential concern if the large number of older scientists crowds out younger scientists, making it difficult for them to establish independent careers. In addition, scientists are believed to be most creative earlier in their careers, so the aging of the workforce may slow the pace of scientific progress. We develop and simulate a demographic model, which shows that a substantial majority of recent aging is a result of the aging of the large baby boom cohort of scientists. However, changes in behavior have also played a significant role, in particular, a decline in the retirement rate of older scientists, induced in part by the elimination of mandatory retirement in universities in 1994. Furthermore, the age distribution of the scientific workforce is still adjusting. Current retirement rates and other determinants of employment in science imply a steady- state mean age 2.3 y higher than the 2008 level of 48.6.
STEM Training and Early Career Outcomes of Female and Male Graduate Students: Evidence from UMETRICS Data Linked to the 2010 Census
Catherine Buffington, Benjamin Cerf, Christina Jones, and Bruce A. Weinberg
American Economic Review May 2016
Women are underrepresented in science and engineering, with the underrepresentation increasing in career stage. We analyze gender differences at critical junctures in the STEM pathway–graduate training and the early career–using UMETRICS administrative data matched to the 2010 Census and W-2s. We find strong gender separation in teams, although the effects of this are ambiguous. While no clear disadvantages exist in training environments, women earn 10% less than men once we include a wide range of controls, most notably field of study. This gap disappears once we control for women’s marital status and presence of children.
Wrapping it up in a person: Examining employment and earnings outcomes for Ph.D. recipients
Nikolas Zolas, Nathan Goldschlag, Ron Jarmin, Paula Stephan, Jason Owen- Smith, Rebecca F. Rosen, Barbara McFadden Allen, Bruce A. Weinberg, Julia I. Lane
Science 11 December 2015
Vol. 350 no. 6266 pp. 1367-1371
Science link: http://www.sciencemag.org/content/350/6266/1367.full
full text pdf: http://econ.ohio-state.edu/weinberg/Science-2015-Zolas-1367-71-PUBLISHED.pdf
supplementary material pdf: http://econ.ohio-state.edu/weinberg/Science-aac5949_Zolas-SM-PUBLISHED.pdf
In evaluating research investments, it is important to establish whether the expertise gained by researchers in conducting their projects propagates into the broader economy. For eight universities, it was possible to combine data from the UMETRICS project, which provided administrative records on graduate students supported by funded research, with data from the U.S. Census Bureau. The analysis covers 2010–2012 earnings and placement outcomes of people receiving doctorates in 2009–2011. Almost 40% of supported doctorate recipients, both federally and nonfederally funded, entered industry and, when they did, they disproportionately got jobs at large and high-wage establishments in high-tech and professional service industries. Although Ph.D. recipients spread nationally, there was also geographic clustering in employment near the universities that trained and employed the researchers. We also show large differences across fields in placement outcomes.
New linked data on research investments: Scientific workforce, productivity, and public value
Julia I. Lane, Jason Owen-Smith, Rebecca F. Rosen, and Bruce A. Weinberg
Research Policy Volume 44, Issue 9
December 2014, Pages 1659–1671
The New Data Frontier
Longitudinal micro-data derived from transaction level information about wage and vendor payments made by Federal grants on multiple US campuses are being developed in a partnership involving researchers, university administrators, representatives of Federal agencies, and others. This paper describes the UMETRICS data initiative that has been implemented under the auspices of the Committee on Institutional Cooperation. The resulting data set reflects an emerging conceptual framework for analyzing the process, products, and impact of research. It grows from and engages the work of a diverse and vibrant community. This paper situates the UMETRICS effort in the context of research evaluation and ongoing data infrastructure efforts in order to highlight its novel and valuable features. Refocusing data construction in this field around individuals, networks, and teams offers dramatic possibilities for data linkage, the evaluation of research investments, and the development of rigorous conceptual and empirical models. Two preliminary analyses of the scientific workforce and network approaches to characterizing scientific teams ground a discussion of future directions and a call for increased community engagement.
Science Funding and Short-Term Economic Activity
Bruce A. Weinberg, Jason Owen-Smith, Rebecca F. Rosen, Lou Schwarz, Barbara McFadden Allen, Roy E. Weiss, Julia Lane
Science 4 April 2014
There is considerable interest among policy-makers in documenting short-term effects of science funding. A multiyear scientific journey that leads to long-term fruits of research, such as a moon landing, is more tangible if there is visible nearer-term activity, such as the presence of astronauts. Yet systematic data on such activities have not heretofore existed. The only source of information for describing the production of most science is surveys that have been called “a rough estimate, frequently based on unexamined assumptions that originated years earlier.