Assuming prior knowledge in simple and multiple linear regression modelling, this course introduces students to a new perspective on studying causes and effects in social science research. Based on a framework of causality, the course agenda covers various strategies to uncover causal relationships using statistical tools. We start with reflecting about causality, the ideal research design, and then learn to use a framework to study causal effects. Then, we revisit common regression estimators of causal effects and learn about their limits. Next, we will focus on matching and weighting, instrumental variables, panel and difference-in-difference estimators. Das Seminar ist für fortgeschrittene Masterstudierende geeignet. close