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.

TBA

TBA