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We show evidence of localized knowledge spillovers using a new database of US patent interferences terminated between 1998 and 2014. Interferences resulted when two or more independent parties submitted identical claims of invention nearly simultaneously. Following the idea that inventors of identical inventions share common knowledge inputs, interferences provide a new method for measuring knowledge spillovers. Interfering inventors are 1.4 to 4.0 times more likely to live in the same local area than matched control pairs of inventors. They are also more geographically concentrated than citation-linked inventors. Our results emphasize geographic distance as a barrier to tacit knowledge flows.

This paper examines how high-skilled immigrants contribute to knowledge diffusion using a rich data set of Russian scientists and US citations to Soviet-era publications. Analysis of a panel of US cities and scientific fields shows that citations to Soviet-era work increased significantly with the arrival of immigrants. A difference-in-differences analysis with matched paper pairs also shows that after Russian scientists moved to the United States, citations to their Soviet-era papers increased relative to control papers. Both strategies reveal scientific field–specific effects. Ideas in high-impact papers and papers previously accessible to US scientists were the most likely to “spill over” to natives.

When choices are made from ordered lists, individuals can exhibit biases toward selecting certain options as a result of the ordering. We examine this phenomenon in the context of consumer response to the ordering of economics papers in an e-mail announcement issued by the NBER. We show that despite the effectively random list placement, papers listed first each week are about 30% more likely to be viewed, downloaded, and subsequently cited. We suggest that a model of “skimming” behavior, where individuals focus on the first few papers in the list due to time constraints, would be most consistent with our findings.

I estimate the impact of a historic grant program, funded by George Soros, that provided grants to over 28,000 Soviet scientists shortly after the end of the USSR. Exploiting a discontinuity in the grant eligibility formula, I show that the grants more than doubled publications on the margin, significantly induced scientists to remain in the science sector, and had long-lasting impacts. While existing evidence shows negligible impacts of scientific grants, I show that funding for science can have high marginal returns when funding levels are low relative to the stock of human capital.

By examining the ethnic identity of authors in over 2.5 million scientific papers written by US-based authors from 1985 to 2008, we find that persons of similar ethnicity coauthor together more frequently than predicted by their proportion among authors. The greater homophily is associated with publication in lower-impact journals and with fewer citations. Meanwhile, papers with authors in more locations and with longer reference lists get published in higher-impact journals and receive more citations. These findings suggest that diversity in inputs by author ethnicity, location, and references leads to greater contributions to science as measured by impact factors and citations. Reprinted by permission of the University of Chicago Press. © All rights reserved

We present the results of a field experiment conducted at Harvard Medical School to understand the extent to which search costs affect matching among scientific collaborators. We generated exogenous variation in search costs for pairs of potential collaborators by randomly assigning individuals to 90-minute structured information-sharing sessions as part of a grant funding opportunity. We estimate that the treatment increases the probability of grant co-application of a given pair of researchers by 75%. The findings suggest that matching between scientists is subject to considerable friction, even in the case of geographically proximate scientists working in the same institutional context.

The educational gender gap has closed or reversed in many countries. But what of gendered labour market inequalities? Using micro‐level census data for some 40 countries, the authors examine the labour force participation gap between men and women, the “marriage gap” between married and single women's participation, and the “motherhood gap” between mothers' and non‐mothers' participation. They find significant heterogeneity among countries in terms of the size of these gaps, the speed at which they are changing, and the relationships between them and the educational gap. But counterfactual regression analysis shows that the labour force participation gap remains largely unexplained by the other gaps.

We present novel evidence from over 2,000 student inventors from colleges and universities across the United States who applied to a prestigious national prize. These unique data provide us with self-reported information about gender, race, and ethnicity for students earlier on the \"pathway to invention\" - young people who have already shown evidence of their inventiveness and are among those likely to be future patent holders. First, we show that 14% of prize applicants are from under-represented minority (URM) groups, which is a smaller gap than estimates of the racial/ethnic gap in patenting. We find striking differences in the focus of the inventions being created by URM inventors, particularly at the intersection of gender and race: URM men are much more likely than all other groups to work on consumer-oriented inventions and less likely to work on health care inventions. URM women are similar to non-URM students in being most likely to work on health care inventions. Differences by field of study show that URM men are more likely than other groups to come from business, and URM women are more likely to come from biological sciences. Finally, we show that slightly more URM applicants come from public research universities. A fruitful area for future research is examining the ways different types of universities support the development of URM students as inventors and contribute to URM students' continuation on the pathway to invention.

We present novel evidence from over 2,000 student inventors from colleges and universities across the United States who applied to a prestigious national prize. These unique data provide us with self-reported information about gender, race, and ethnicity for students earlier on the “pathway to invention” — young people who have already shown evidence of their inventiveness and are among those likely to be future patent holders. First, we show that 14% of prize applicants are from under-represented minority (URM) groups, which is a smaller gap than estimates of the racial/ethnic gap in patenting. We find striking differences in the focus of the inventions being created by URM inventors, particularly at the intersection of gender and race: URM men are much more likely than all other groups to work on consumer-oriented inventions and less likely to work on health care inventions. URM women are similar to non-URM students in being most likely to work on health care inventions. Differences by field of study show that URM men are more likely than other groups to come from business, and URM women are more likely to come from biological sciences. Finally, we show that slightly more URM applicants come from public research universities. A fruitful area for future research is examining the ways different types of universities support the development of URM students as inventors and contribute to URM students’ continuation on the pathway to invention.

This paper measures aggregate changes in job characteristics in the United States from 2005 to 2015 and decomposes those changes into components representing shifts within occupations and changes in occupational employment shares. Per our title, within-occupation changes dominate, raising doubts about the ability of projections based on expected changes in the occupational composition of employment to capture the likely future of work. Indeed, our data show only weak relationships between automatability, repetitiveness, and other job attributes and changes in occupational employment. The results suggest that analysts give greater attention to within-occupation impacts of technology in assessing the future of work.