Course Goals This course covers core micro-econometric methods and the principles of causal inference to evaluate policy measures. The course builds upon and extends the material covered in Empirical Economics. Building on the basics of econometric modelling, we will discuss the interpretation of causal estimation models and the implications for policy evaluation. We will cover matching methods, fixed-effects estimation, difference-in-difference estimators, instrumental-variables approach, and regression discontinuity design. Both experimental and quasi-experimental approaches to causal inference and program evaluation will be covered.

The emphasis will be on developing a solid understanding of the underlying econometric principles of the methods taught, as well as on their empirical application for the evaluation of policy and programs. Theory, background and examples will be covered in lectures, while the exercises given in intensifying courses will allow students to apply the theory to practical examples using STATA.

• apply core methods of causal inference taught in the course on relevant research topics.
• interpret results obtained from various econometric approaches.
• read and understand studies that apply causal methods to investigate actual economic issues relevant for economic or social policy.

• the formal and practical aspects of important microeconometric methods for causal inference.
• when and how to apply core methods of causal inference and these methods’ limitations.
• how to interpret result and distinguish between causal inference and correlation analyses