My research focuses on economic and social inequalities, and how early-life conditions, labor markets, and family policies shape long-term outcomes.
My first dissertation chapter examines why a small group of women reach the top 10% of the earnings distribution by their mid-30s. Using Norwegian register data, I compare top-earning women to closely matched peers to isolate the roles of family background, ability, education, fertility, and early-career job placement. I replicate the analysis for men to assess whether high-earning men and women follow similar paths.
My second project studies what drives fertility choices and caregiving behavior for men and women, using parental leave take-up as a key outcome. I begin by documenting fertility and parental leave patterns for both genders, and then analyze the role of gender norms and monetary incentives in shaping these behaviors. I examine how early-life exposure to working mothers influences men’s and women’s later labor supply, fertility decisions, and couples’ parental leave strategies. I also study how monetary incentives and firm environments affect parental leave take-up, particularly for men.
In the past, I explored the intersection of public economics and gender inequalities, conducting research on political representation and policy work on taxation.
Work in progress
Elite women: decomposing success (with Francesconi, M., Jensen, S. , Salvanes, K.)
Abstract: We study which characteristics differentiate the small group of women who reach the top of the earnings distribution by their mid-30s. Using Norwegian administrative registers for cohorts 1983–1988, we define “top-10” as women in the top decile of the annual earnings distribution at age 35. We construct sequential matched control samples (5-nearest neighbors) that cumulatively equalize: (i) family background (paternal income rank, parental education, birth region); (ii) high-school GPA; (iii) tertiary education (degree level and field); (iv) fertility (age at first birth and number of children); and (v) first-job characteristics (occupation, industry, firm size, sector, location, entry wage). We then estimate age-specific differences in earnings profiles from 20–40 for the different matched control groups. The sequence quantifies how much of the earnings gap between the top decile and the rest is associated with background and measured talent, how much is accounted for by education, and what remains after equalizing fertility and first-job placement. We replicate the decomposition for men and compare.
Peer reviewed publications
Brusini, I.M. (2022) Rethinking Political Representation: A new measurement of gender equality in political representation in the European Union. The Public Sphere: Journal of Public Policy, 10(1). https://psj.lse.ac.uk/articles/112