The aim of the course is to introduce the students to concepts and ideas of causal identification in the evaluation of public policy. In all areas of policy making - be it economic policy, structural design of institutions or reforms in public management - researchers and policy makers are interested in "identifying" cause and effect. The course will deal both with the statistical foundations and the application of the most standard methods for causal identification. In two lectures each, we will learn about the counterfactual model, the regression control framework, matching techniques, the difference-in-difference model, the instrumental variable approach and regression discontinuity design. Special emphasis will be given to the intuitive aspects of those models, the applicability to various topics in public policy as well as hands-on statistical programming and data processing.