Development and International Cooperation Studies

For the first part of the course revolving, the following topics will be covered: - introduction to quantitative social science - introduction to causal inference in the social sciences - predictive policy problems - experimental vs. observational data - randomized experiments - linear regression - real-world data analysis with R - survey data analysis - internal vs. external validity

There are no formal pre-requisites. It is advisable that students are already in possession of basic economic and statistics knowledge as well as of basic skills in dealing with economic data analysis and visualization.

Llaudet, E., & Imai, K. (2022). Data Analysis for Social Science: A Friendly and Practical Introduction. Princeton University Press.

Attendance is not compulsory but is strongly encouraged.

Written exam (with open questions) and practical assignment involving empirical and data analysis.

In-person lectures