Applied longitudinal data analysis: Diversity across the life course

This course teaches empirical methods that enable students to study diversity across the life course. How long does it take to leave poverty or unemployment? What determines upward mobility in the labor market? When do individuals leave education, the parental home, get divorced or have a child? How do patterns vary by gender, education, family context, ethnicity, migration background and country? In order to answer questions of this kind, we use micro-level data from various sources. Moreover, students will get familiar with classical methods for longitudinal data. These include, in particular: Event history modeling, sequence analysis and fixed-effects regression. Some R-skills (usually obtained in STAT I) are useful. The course is designed for students who have taken Statistics I, and who are following the policy analysis track.

Moreover, MIA Students and MPP students with a specialisation in management and organisation are also very welcome. The course is particularly relevant for students who are searching for data for their master's projects. The course leaves room for exploring the potential of different data sets and for employing the data to answer substantial policy-relevant research questions.