E-print/Working paper (2021)
Luxembourg is known for its cultural and national diversity. Approximately 48 of the population is foreigners live in Luxembourg. For 15-29-year-olds, this share was approximately 42 in 2019 and 2020. Furthermore, approximately 185,000 foreign workers commute to Luxembourg daily. Considering this, Luxembourg is an interesting case for investigating national identity and political participation of a diverse society (STATEC 2020a, STATEC 2020b, STATEC 2021). Especially, as the biographies of young people in Luxembourg are becoming increasingly complex (e.g., mixed national parents; highly skilled expatriates), it is worth looking into different aspects and valuations of national identity and political participation of youth in Luxembourg (Amtépé and Hartmann-Hirsch, 2011). In this policy report, we look into the aspects of national identity and how young people living in Luxembourg define a ‘real Luxembourger’ using the Youth Survey Luxembourg (2019) data (Sozio et al., 2020). This will give us the opportunity to investigate what aspects of identity (e.g. Luxembourgish ancestry; the time spent living in Luxembourg) matter for young people to feel part of Luxembourgish society and how these change across different social backgrounds and demographics. The discourse about the interrelations of political participation and youth brings forward the dominant narrative of a disengaging and passive youth. Here, we also investigate these statements in the Luxembourgish context. We analyse the level of interest in politics across young people in Luxembourg and their means of political participation. Finally, we especially investigated the relationship between aspects of national identity, and political interest and engagement of young people in Luxembourg.
Presentation (2020, August 27)
Presentation (2019, July 17)
In our contribution, we assess the possibilities and limits of Cox regression models in social stratification research in the area of health. We are motivated by the need for a structured analytical strategy through which researchers can deal with health inequality. Previous findings suggest considering health as a relevant resource but also one, which is unequally distributed among the members of a population. Along these lines, we focus on the inequality of risks distribution and the social stratification of (non) access to health as a resource. Using the substantive example of health inequality, we perform five Monte Carlo simulations in constructed longitudinal data. Each setting simulates a different source of bias. Specifically: a) Measurement error (misspecification of time measurement); b) Linear dependency between class of origin, destination and mobility effects; c) Omitted variables bias; d) Disentangle of timing/probability effects, namely speed/overall occurrence likelihood of an event; and e) Unobserved heterogeneity among groups. The health-related risks approach in analysing health inequalities has a twofold advantage: a) it splits the health outcome in a true differential and in a stochastic component due to chance and b) it considers only the first – and in most cases more interesting part – as a source of inequality. Moreover, Cox regression models allow for a flexible parameterization conditional to the specific research settings. For instance, addition of frailty parameters to the regression equation can help social scientists to reduce unobserved heterogeneity. This problem is especially encountered in social stratification research when comparing logit transition probabilities. In summary, this study contributes to the current literature by demonstrating the flexibility of Cox regression models in social stratification research in the area of health. It further provides valuable analytic avenues for theory-driven empirical research in social scientific health research as it uncovers how various sources of bias affect estimates.