Discrimination through Biased Memory [PDF] 

Best Paper Award in Gender Economics by Unicredit Foundation (2023)

Abstract: This paper shows that decision-makers make more stereotypical decisions when they struggle to recall individual-level information, penalizing women in male-dominated fields. Analyzing administrative data from Italian public schools, I find that when teachers need to assess a larger number of students, girls are less likely to be recommended for top-tier scientific high school tracks compared to boys with the same math standardized scores. Notably, this bias vanishes for teachers who report checking student data in class registers, relying less on memory alone. To directly assess the extent to which limitations and biases in recall generate more stereotypical decisions, I conducted two experiments. In the first, teachers provided track recommendations for a series of student profiles. When teachers cannot check individual data and must rely on memory, they recall a limited set of individual signals and disproportionately retrieve stereotype-consistent information. As a consequence, large gender-based disparities in track recommendations emerge, with girls 39% less likely to be recommended to STEM tracks than identical boys. Eliminating memory constraints by allowing teachers to check individual-level information reduces the gender gap by 80%, potentially mitigating the misallocation of talent. A second large-scale online experiment generalizes this mechanism. Taken together, the results highlight how memory limitations and biases amplify discriminatory behaviors and suggest that simple, cost-effective interventions facilitating access to individual-level information can mitigate such biases.

Childhood Environment and Motherhood Penalties (with Antonio Coran and Malene Laczek) [PDF]

Abstract: We explore the impact of childhood environment on the earnings penalties that mothers face at the birth of their first child. Using administrative data from Denmark, we classify municipalities based on the motherhood penalties experienced by permanent residents. High-penalty places offer fewer human capital development opportunities and have a lower labor supply of women in the previous generation. We use a movers’ design to distinguish the causal effect of childhood environment from the sorting of families. Our findings indicate that women who spent a longer period of their childhood in a high-penalty area experience lower earnings after childbirth, even though they have similar earnings the years before the birth of their first child. Next, we find that policies that impact the childhood environment can influence motherhood penalties; increases in childcare availability during childhood lower motherhood penalties decades later. We show suggestive evidence that higher childhood exposure to working women can act as a mechanism.

Unveiling Discrimination in Teachers' Expectations (with Michela Carlana and Eleonora Patacchini) 

Abstract: Using a unique combination of administrative data, surveys, and incentivized experiments, we provide evidence of discrimination in teachers' advice for students' career trajectories based on family background. Keeping students' capabilities and interests constant, teachers generalize low expectations on future educational achievement and labor market prospects for students from economically disadvantaged families. These expectations occur without information about parental involvement and financial constraints for each student.

Addressing Inequalities in High School Track Choice (with Michela Carlana and Eleonora Patacchini) 

AEA RCT R-0010758 

Abstract: Using rich administrative data on the population of Italian students, we document stark socioeconomic (SES) gaps in high-school track choices that align with the track recommendations made by teachers. To address this issue, we are implementing a large-scale intervention in schools that provides teachers with personalized reports detailing their former students' post-middle school outcomes and including information on the SES disparities in their previous recommendations. Our objective is to assess the impact of this intervention on teachers' track recommendations and students' choices.