This paper obtains comparable estimates of the effect of unemployment insurance (UI) benefits on labor supply throughout the unemployment spell and over the business cycle using a regression kink design and 20 years of administrative data from California. For a given unemployment duration, the behavioral effect of UI benefit levels on labor supply does not vary with the business cycle from 2002 to 2019. However, due to increased coverage from extensions in benefit durations, the duration elasticity of UI benefits rises during recessions. The behavioral effect during the start of the COVID-19 pandemic is substantially lower at all unemployment durations.

We establish the importance of team-specific capital in the typical inventor's career. Using administrative tax and patent data for the population of US patent inventors from 1996 to 2012, we find that an inventor's premature death causes a large and long-lasting decline in their co-inventor's earnings and citation-weighted patents (−4 percent and −15 percent after 8 years, respectively). After ruling out firm disruption, network effects, and top-down spillovers as main channels, we show that the effect is driven by close-knit teams and that team-specific capital largely results from an “experience” component increasing collaboration value over time. (JEL J24, J31, M54, O31, O34)

We characterize the factors that determine who becomes an inventor in the United States, focusing on the role of inventive ability (“nature”) versus environment (“nurture”). Using deidentified data on 1.2 million inventors from patent records linked to tax records, we first show that children's chances of becoming inventors vary sharply with characteristics at birth, such as their race, gender, and parents' socioeconomic class. For example, children from high-income (top 1%) families are 10 times as likely to become inventors as those from below-median income families. These gaps persist even among children with similar math test scores in early childhood-which are highly predictive of innovation rates-suggesting that the gaps may be driven by differences in environment rather than abilities to innovate. We directly establish the importance of environment by showing that exposure to innovation during childhood has significant causal effects on children's propensities to invent. Children whose families move to a high-innovation area when they are young are more likely to become inventors. These exposure effects are technology class and gender specific. Children who grow up in a neighborhood or family with a high innovation rate in a specific technology class are more likely to patent in exactly the same class. Girls are more likely to invent in a particular class if they grow up in an area with more women (but not men) who invent in that class. These gender- and technology class-specific exposure effects are more likely to be driven by narrow mechanisms, such as role-model or network effects, than factors that only affect general human capital accumulation, such as the quality of schools. Consistent with the importance of exposure effects in career selection, women and disadvantaged youth are as underrepresented among high-impact inventors as they are among inventors as a whole. These findings suggest that there are many “lost Einsteins”-individuals who would have had highly impactful inventions had they been exposed to innovation in childhood-especially among women, minorities, and children from low-income families.