The Family Origin of the Math Gender Gap is a White Affluent Phenomenon (with David Figlio, Paola Giuliano, and Paola Sapienza), American Economic Association Papers & Proceedings 111 (2021): 179-183 [Final draft] [Journal article] [NBER wp] [Slides] Summary: NBER Reporter, UCLA Anderson Review
Previous research has shown that norms around the role of women in society could help explain the gender gap in mathematics and that these norms could be transmitted within the family. Using data from the Florida Department of Education combined with birth certificates, we uncover important heterogeneity in the transmission of gender biases within the family. We find that gender role norms can explain the lower performance of girls in mathematics only in relatively affluent White families, whereas they do not apparently matter for the performance of Black girls.
Born in the Family: Preferences For Boys and the Gender Gap in Math (with David Figlio, Paola Giuliano, and Paola Sapienza), Journal of Economic Behavior & Organization 183 (2021): 175-188 [Final draft] [Journal article] [NBER wp] Summary: Corriere della Sera, Kellogg Insights, NBER Reporter, Quartz, UCLA Daily Bruin, University of California, UCLA Anderson Review, VoxEU (podcast)
We study the effect of preferences for boys on the performance in mathematics of girls, using evidence from two different data sources. In our first set of results, we identify families with a preference for boys by using fertility stopping rules in a large population of households whose children attend public schools in Florida. Girls growing up in a boy-biased family score on average 3 percentage points lower on math tests when compared to girls raised in other types of families. In our second set of results, we find similar effects when we study the correlations between girls’ performance in mathematics and maternal gender role attitudes, using evidence from the National Longitudinal Survey of Youth. We conclude that socialization at home can explain a non-trivial part of the observed gender disparities in mathematics performance and document that maternal gender attitudes correlate with those of their children, supporting the hypothesis that preferences transmitted through the family impact children behavior.
Dealing With Adversity: Religiosity or Science? Evidence From the Great Influenza Pandemic (with Enrico Berkes, Davide M Coluccia, and Mara Squicciarini) [Draft] [CEPR wp] Summary: LSE Blogs
How do societies respond to adversity? After a negative shock, separate strands of research document either an increase in religiosity or a boost in innovation efforts. In this paper, we show that both reactions can occur at the same time, driven by different individuals within society. The setting of our study is the 1918–1919 influenza pandemic in the United States. To measure religiosity, we construct a novel indicator based on naming patterns of newborns. We measure innovation through the universe of granted patents. Exploiting plausibly exogenous county-level variation in exposure to the pandemic, we provide evidence that more-affected counties become both more religious and more innovative. Looking within counties, we uncover heterogeneous responses: individuals from more religious backgrounds further embrace religion, while those from less religious backgrounds become more likely to choose a scientific occupation. Facing adversity widens the distance in religiosity between science-oriented individuals and the rest of the population, and it increases the polarization of religious beliefs.
Racial Discrimination and Lost Innovation (with Davide M Coluccia and Sebastian Ottinger) (updated draft to follow)
Works in progress
Political Ideology and Innovation (with Marta Morando) [Abstract] [Slides]
We study the role of political ideology for a critical group of economic agents: inventors. We document that, in “politically polarizing” fields, inventors patent innovations that align with their political beliefs. We construct a novel dataset matching data from the US Patent Office (USPTO) with individual Voter Register data for two large US states, and with the universe of US campaign contributions data. We proxy political ideology with individual party affiliation, and we focus on fields where the ideological distance between Republicans and Democrats is especially large in the general population. We find that, compared to Republicans, Democrats are: i) more likely to file green patents; ii) more likely to file female-health patents, an effect that persists in the subset of male inventors; and iii) less likely to file weapon-related patents. The magnitudes are large, and range from one fourth to one third of total patent production in these technologies. This pattern is not explained by differential monetary incentives, suggesting that inventors may derive intrinsic utility from producing innovation aligned with their beliefs.
Indirect Experience (with Livia Alfonsi) [Abstract] [Slides]
How do events occurred within an individual’s network affect individual behavior? In this paper we study how the staggered arrival of the COVID–19 pandemic across countries of the world affected the behavior of migrants living in the US. We combine evidence from a survey we designed and administered to international students in June 2020, administrative data on death rates, Google Mobility trends, and Google Search trends. We document four facts. First, migrants from a country hit early on in the pandemic are more likely to modify their behavior before official shelter-in-place orders in the US. Second, this change in behavior persists after four months. Third, they are more likely to report modifying their behavior because of events in their home country. Finally, we present suggestive evidence they have higher risk perception. To interpret our results, we develop an experience-based learning model where experience is indirect (occurs through the network) rather than direct (occurs though the individual).
Return Innovation: The Knowledge Spillovers of the British Migration to the United States, 1870-1940 (with Davide M Coluccia)
What drives the diffusion of knowledge across countries? In this paper, we provide new evidence that out-migration generates a flow of knowledge from the country of destination to the country of origin of migrants. During the Age of Mass Migration, nearly four million British migrated to the US. We construct a novel individual-level dataset linking British immigrants in the US to the UK census, and we complement it with the newly digitized universe of UK patents. Using a new shift-share instrument for bilateral migration flows and a triple-differences design, we document a positive, significant, and persistent effect of exposure to US technology through migrant ties on the direction of innovation in Britain in 1870–1940. The individual-level analysis indicates that this “return innovation” effect does not require the physical return of emigrants. Instead, we find that migration linkages generate information flows that facilitate the cross-border diffusion of novel knowledge. Furthermore, our findings suggest that the market integration fostered by migration ties is an additional driver of these knowledge flows.
America's Missing Entrepreneurs (with Raj Chetty, Matthew Smith, John Van Reenen, Owen Zidar, and Erik Zwick)