We study how delays in NIH grant funding affect the career outcomes of research personnel. Using comprehensive earnings and tax records linked to university transaction data along with a difference-in-differences design, we find that a funding interruption of more than 30 days has a substantial effect on job placements for personnel who work in labs with a single NIH R01 research grant, including a 3 percentage point (40%) increase in the probability of not working in the US. Incorporating information from the full 2020 Decennial Census and data on publications, we find that about half of those induced into nonemployment appear to permanently leave the US and are 90% less likely to publish in a given year, with even larger impacts for trainees (postdocs and graduate students). Among personnel who continue to work in the US, we find that interrupted personnel earn 20% less than their continuously-funded peers, with the largest declines concentrated among trainees and other non-faculty personnel (such as staff and undergraduates). Overall, funding delays account for about 5% of US nonemployment in our data, indicating that they have a meaningful effect on the scientific labor force at the national level.
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The Color of Money: Federal vs. Industry Funding of University Research
September 2021
Working Paper Number:
CES-21-26
U.S. universities, which are important producers of new knowledge, have experienced a shift in research funding away from federal and towards private industry sources. This paper compares the effects of federal and private university research funding, using data from 22 universities that include individual-level payments for everyone employed on all grants for each university year and that are linked to patent and Census data, including IRS W-2 records. We instrument for an individual's source of funding with government-wide R&D expenditure shocks within a narrow field of study. We find that a higher share of federal funding causes fewer but more general patents, more high-tech entrepreneurship, a higher likelihood of remaining employed in academia, and a lower likelihood of joining an incumbent firm. Increasing the private share of funding has opposite effects for most outcomes. It appears that private funding leads to greater appropriation of intellectual property by incumbent firms.
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A Tale of Two Fields? STEM Career Outcomes
October 2023
Working Paper Number:
CES-23-53
Is the labor market for US researchers experiencing the best or worst of times? This paper analyzes the market for recently minted Ph.D. recipients using supply-and-demand logic and data linking graduate students to their dissertations and W2 tax records. We also construct a new dissertation-industry 'relevance' measure, comparing dissertation and patent text and linking patents to assignee firms and industries. We find large disparities across research fields in placement (faculty, postdoc, and industry positions), earnings, and the use of specialized human capital. Thus, it appears to simultaneously be a good time for some fields and a bad time for others.
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Military Service and Immigrants' Integration: Evidence From the Vietnam Draft Lotteries
June 2026
Working Paper Number:
CES-26-35
Seminal theories in political science argue that military service is a critical driver of minority integration. However, a major obstacle bedeviling the study of military service is self-selection: individuals who are better integrated may be more likely to join the military in the first place. We address the selection problem by examining the effects of military conscription during the Vietnam War using an instrumental variables approach. Conscription during 1970--72 was decided on the basis of national draft lotteries that assigned draft numbers based on an individual's date of birth. Using the draft lottery instrument, we find no evidence of a causal effect of military service on a range of integration outcomes from the 2000 decennial census. At least for the Vietnam era, the link between service and long-term integration is largely driven by self-selection, which points to important scope conditions for the integrationist view.
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Life-Cycle Effects of Women's Education on their Careers and Children
January 2026
Working Paper Number:
CES-26-09
We study the causal effect of women's education on their wages, non-wage job amenities, and spillovers to children. Using a regression discontinuity at the school entry birthdate cutoff, we find that women born just before the cutoff are more likely to complete some college, and experience multi-dimensional career gains that grow over the life cycle: greater employment and earnings, as well as more professional and higher-status jobs, more socially meaningful work, and better working conditions. Children's early-life health and prenatal inputs improve in tandem with career improvements, consistent with professional advances spurring'not hindering'infant investments. Career gains are concentrated in jobs that require exactly some college, the same schooling margin shifted by the cutoff, which indicates that increased post-secondary education is the primary channel for these effects. Together, the results show that women's college attendance generates large career returns'from both wages and amenities'that strengthen over time and produce meaningful benefits for children.
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College Majors and Earnings Growth
February 2026
Working Paper Number:
CES-26-14
We estimate major-specific earnings profiles using matched American Community Survey (ACS) and Longitudinal Employer-Household Dynamics (LEHD) data. Building on Deming and Noray (2020), we exploit a long earnings panel to overcome key limitations of cross-sectional approaches to lifecycle estimation. We find that engineering and computer science majors experience earnings growth that is comparable to or faster than that of other majors, a category including humanities, education, psychology, and similar fields. In contrast, Deming and Noray (2020) use a crosscohort approach and find that earnings for engineering and computer science majors decline relative to other fields over the lifecycle.
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Academic Science, Industrial R&D, and the Growth of Inputs
January 1993
Working Paper Number:
CES-93-01
This paper is a theoretical and empirical investigation of the connection between science, R&D, and the growth of capital. Studies of high technology industries and recent labor studies agree in assigning a large role to science and technology in the growth of human and physical capital, although direct tests of these relationships have not been carried out. This paper builds on the search approach to R&D of Evenson and Kislev (1976) to unravel the complex interactions between science, R&D, and factor markets suggested by these studies. In our theory lagged science increases the returns to R&D, so that scientific advance later feeds into growth of R&D. In turn, product quality improvements and price declines lead to the growth of industry by shifting out new product demand, perhaps at the expense of traditional industries. All this tends to be in favor of the human and physical capital used intensively by high technology industries. This is the source of the factor bias which is implicit in the growth of capital per head. Our empirical work overwhelmingly supports the contention that growth of labor skills and physical capital are linked to science and R&D. It also supports the strong sequencing of events that is a crucial feature of our model, first from science to R&D, and later to output and factor markets.
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Who Scars the Easiest? College Quality and the Effects of Graduating into a Recession
September 2024
Working Paper Number:
CES-24-47
Graduating from college into a recession is associated with earnings losses, but less is known about how these effects vary across colleges. Using restricted-use data from the National Survey of College Graduates, we study how the effects of graduating into worse economic conditions vary over college quality in the context of the Great Recession. We find that earnings losses are concentrated among graduates from relatively high-quality colleges. Key mechanisms include substitution out of the labor force and into graduate school, decreased graduate degree completion, and differences in the economic stability of fields of study between graduates of high- and low-quality colleges.
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Diversity and Labor Market Outcomes in the Economics Profession
July 2022
Working Paper Number:
CES-22-26
While the lack of gender and racial diversity in economics in academia (for students and professors) is well-established, less is known about the overall placement and earnings of economists by gender and race. Understanding demand-side factors is important, as improvements in the supply side by diversifying the pipeline alone may not be enough to improve equity in the profession. Using the Survey of Earned Doctorates (SED) linked to Longitudinal Employer-Household Dynamics (LEHD) jobs data, we examine placements and earnings for economists working in the U.S. after receiving a PhD by gender and race. We find enormous dispersion in pay for economists within and across sectors that grows over time. Female PhD economists earn about 12 percent less than their male colleagues on average; Black PhD economists earn about 15 percent less than their white counterparts on average; and overall underrepresented minority PhD economists earn about 8 percent less than their white counterparts. These pay disparities are attenuated in some sectors and when controlling for rank of PhD granting institution and employer.
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Occupational Classifications: A Machine Learning Approach
August 2018
Working Paper Number:
CES-18-37
Characterizing the work that people do on their jobs is a longstanding and core issue in labor economics. Traditionally, classification has been done manually. If it were possible to combine new computational tools and administrative wage records to generate an automated crosswalk between job titles and occupations, millions of dollars could be saved in labor costs, data processing could be sped up, data could become more consistent, and it might be possible to generate, without a lag, current information about the changing occupational composition of the labor market. This paper examines the potential to assign occupations to job titles contained in administrative data using automated, machine-learning approaches. We use a new extraordinarily rich and detailed set of data on transactional HR records of large firms (universities) in a relatively narrowly defined industry (public institutions of higher education) to identify the potential for machine-learning approaches to classify occupations.
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The Impact of Female Teachers on Female Students' Lifetime Well-Being
June 2026
Working Paper Number:
CES-26-39
We document an enduring influence of female primary school teachers on their female students in rural America circa 1940. Using historical US Census data linked to IRS records, later censuses, and death records, we find that exposure to female teachers significantly improved girls' educational attainment'particularly among those with poorly-educated parents and in areas with limited labor market opportunities for women. These educational gains translated into delayed marriage and childbearing, marriage matches to better-educated husbands and higher household income. We also find that exposure to female teachers increased longevity of women relative to men.
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