Apprenticeships play a key role in enabling successful school-to-work transitions in many countries but, in the presence of imperfect information, the specificity of this type of training may entail important costs for those working outside their training fields. I study this issue in one of the most prominent training settings, the German apprenticeship system. Using administrative data and a broad occupational classification, I find that 40% of individuals work in occupations different from their training. I estimate the cost of mismatch using vacancy instruments and extend methodological approaches in high-dimensional selection settings. Lacking training in one’s occupation entails an average wage penalty of 14%, the equivalent of two years of work experience. The penalty increases with the task distance between training and occupation. My findings suggest that retraining is crucial to mitigate the adverse consequences from imperfect information in specialized training settings.

While previous research has shown that disadvantaged young people are less likely to work in professional occupations than their advantaged peers, even conditional on their education, until now little has been known about the reasons for this - are they applying for professional entry-level roles and not being hired, or are they not applying in the first place? Using unique recruitment data from 17 large employers' graduate programmes, we are able to answer this question for the first time. We find that applicants from lower SEB groups and ethnic minority groups are well represented among the applicant pool, but disproportionately do not receive job offers, even when considering applicants with similar prior attainment and other demographic characteristics applying to similar roles. Around half of the gap in job offers between working class and professional background applicants appears during the application sift and online test phase of the process. The other half of the gap in offers emerges at the face-to-face stages. For ethnic minority groups, the majority of the gap in offer rates emerges at the application sift and online test phase, rather than at the face-to-face stage. Women are typically underrepresented in the applicant pool across entry routes but are more likely to achieve a job offer than otherwise similar men, among those who do apply.

Genetic endowments are fixed at conception, and they remain constant over the life course of individuals. Therefore, genetic inequality contradicts the widespread goal of providing equal educational opportunities to all members of society. In line with this policy goal, there is a long-standing literature in economics, sociology, and psychology that poses “the question of how well schools reduce the inequity of birth” (Coleman et al., 1966, p.36). In this paper, we investigate the question of how well schools address inequalities based on genetic disadvantages by providing the first causal study to estimate the interaction between genetic endowments and school quality. To this end, we combine Norwegian data on genetic trios (mothers, fathers, fathers) with validated measures of school value-added. Our (preliminary) findings suggest that schools equalize opportunities by reducing genetic gradients in reading (but not numeracy).

Co-Authors: Rinni Norlinder, J. Lucas Tilley, and Emma von Essen

Until 2013, Sweden required transgender people to undergo sterilizing surgery before changing their legal gender. We analyze whether the removal of this requirement led to an increase in the number of people changing legal gender, and if dropping the requirement had an impact on health and earnings among those who did so. Our analysis uses population-wide administrative data from 2006 to 2020, including information on legal gender changes, medical records, and socioeconomic traits. We find that 3-4 times as many people changed legal gender, and 30% of trans women and 55% of trans men chose not to have surgery within 5 years when it was no longer mandated. We also find positive effects on earnings growth and a lower rate of sick leave.

Effect heterogeneity is central for social mobility research, focusing on whether subgroups have converging or differential mobility rates. Still, standardized approaches are lacking, and conventional methods suffer from drawbacks – e.g., covariate imbalance and overfitting. I propose a three-stage evaluation process that uses prediction methods, complementing conventional examinations of group mean and effect differences, that allows for gauging subgroup-specific changes in explanatory power. The analytical framework additionally focuses on identifying what heterogeneity components (parental SES, gender, or migration background) drive any differences produced. While drawing on traditional subgroup analysis and intersectionality theory, the empirical focus is on universality vs. interactive models of social mobility using detailed Swedish register and census data. Although the conventional interpretation of interactive models shows strong support for subgroup heterogeneity and varying social mobility rates, predictive results indicate minimal improvements in fit and little support for an effect heterogeneity by parental SES. In sum, the interpretation of coefficients and graphical analysis of interactions can be contextualized by expanding the criteria for assessing subgroup heterogeneity. Ultimately, this leads to a better understanding of subgroup particularities, guiding future research toward richer answers with a focus on both effect estimates and how well competing models fit the data.