Causal Inference in the Social Sciences

About

This course will introduce you to the concepts and methods of causal inference and causal modeling in the social sciences. It will highlight the relevance of research design, analytical methods, and their systematic combination to optimize the validity of causal inferences drawn from empirical studies. Building on existing knowledge concerning linear regression modelling and research design, the course will then cover key methods to estimate causal effects, including fixed effects estimations with various addons, event study analyses, matching, difference-in-differences, regression discontinuity, and instrumental variables. Throughout the course, you will apply these concepts and methods in hands-on sessions to real-world examples in the social sciences. The application will be conducted with the statistical software package Stata. A solid background in Stata is expected. By the end of the course, you will have the skills and knowledge to design, conduct, and interpret causal inference studies in the social sciences. You will be able to engage with the contemporary literature of causal inference and identify state-of-the-art methods which might be most relevant to your specific research question

Course leader

Matthias Collischon and Florian Zimmermann, Institute for Employment Research (IAB), Nuremberg

Target group

You will find the course useful if you:
- have a background in the social, behavioral or economic sciences (economists, political scientists, sociologists, criminologists, psychologists, etc.),
- are interested in methods for causal inference based on observational data, especially panel data,
- have a firm knowledge in linear regression modelling,
- are motivated to apply the concepts and statistical approaches in hands-on sessions

Course aim

By the end of the course, you will:
- have acquired an understanding of up-to-date causal estimation approaches to understand and critically reflect on current studies,
- be able to conceptually design your own studies to identify causal effects,
- bring the conceptual considerations into practice and conduct the relevant estimations

Fee info

The rates include the tuition fee, course materials, the academic program, social and plenary program, and coffee/tea breaks.