This course introduces and discusses the tools to answer causal questions across all not only in economics (from labor and health to development and finance) but also in the social sciences more broadly. Students will gain hands-on experience with key causal inference concepts and tools

• Intro: Causality and correlation -- reatment effects, selection bias, and regression
• Randomized control trials
• Regression discontinuity designs
• Difference-in-differences estimation
• Instrumental variables
• Extra: Power analysis and estimation uncertainty: bootstrap and randomization inference

By the end of this course, students will be equipped to apply key causal inference methods for their research interests.

They will gain familiarity with the most important microeconometric evaluation techniques used in academic literature, with a particular emphasis on recent advancements. Students will develop the ability to understand contemporary research papers employing these methods and critically assess their strengths and limitations across diverse evaluation contexts.

Classroom attendance is mandatory, as active participation is essential for mastering the material and engaging with the course content.

Up to three absences will be tolerated, but students are expected to independently review and catch up on any material covered during missed sessions. 

The course combines lectures and tutorials into a unified format. Key microeconometric evaluation techniques will be presented and practiced. Students will apply these methods through coding exercises and group assignments to reinforce their understanding and develop practical skills.

The course assessment is based on three components:

• Midterm Exam: 35%
• Homework (4 Assignments): 25%
• Final Exam: 40%

Each component must be passed independently. The final grade will be determined by the weighted average of the three scores, based on the following grade scale:

Please log in with your WU account to use all functionalities of read!t. For off-campus access to our licensed electronic resources, remember to activate your VPN connection connection. In case you encounter any technical problems or have questions regarding read!t, please feel free to contact the library at readinglists@wu.ac.at.