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...

Funding of research is critically important because it affects the flow of new, doctorally qualified scientists into the workforce. This paper provides new insights into how survey data can be combined with administrative records to examine the ways in which funding affects workforce decisions....

This paper using transaction based data to provide new insights into the link between the geographic proximity of businesses and associated economic activity. It contributes to the literature by developing both two new measures of distance and a set of stylized facts on the distances between...

This paper investigates the local impact of biomedical research on mortality in the USA. Causally estimating the marginal value of biomedical research is challenging due to a lack of micro data linking health outcomes to plausibly exogenous variation in research. We create a new linkage between...

The rapid diffusion and use of new ideas are critical for advancing and realizing the value of innovation. This paper explores the impact of demographic characteristics of innovators and potential adopters on the adoption of important new scientific ideas through networks. Using rich,...

In the early phases of the COVID-19 epidemic labor markets exhibited considerable churn, which we relate to three primary findings. First, reopening policies generated asymmetrically large increases in reemployment of those out of work, compared to modest decreases in job loss among those...

This paper uses newly available data from Web of Science on publications matched to researchers in Survey of Doctorate Recipients to compare scientific publications collected by surveys and algorithmic approaches. We aim to illustrate the different types of measurement errors in self-reported...

Using dissertation research topics found in the EconLit database and large-scale algorithmic methods that identify author demographics based on names, we explore the link between race and ethnicity and fields of economic research. We find that underrepresented racial and ethnic minority (URM)...

Using the EconLit dissertation database and large-scale algorithmic methods that identify author demographics from names, we investigate the connection between the gender of economics dissertators and dissertation topics. Despite stagnation in the share of women among economics Ph.D.s in recent...

Marketing and strategy researchers have often studied how organizations navigate multiple identities in relation to category spanning but extant literature pays less attention to understanding how individuals do so. Moreover, current econometric approaches only scratch the surface with respect...