865-0008-00L  Policy Evaluation and Applied Statistics

SemesterAutumn Semester 2021
LecturersI. Günther
Periodicitytwo-yearly recurring course
CourseDoes not take place this semester.
Language of instructionEnglish
CommentOnly for MAS in Development and Cooperation and Science, Technology, and Policy MSc.


AbstractThis course introduces students to key methods for quantitative policy impact evaluation and covers the different stages of the research process. Acquired skills are applied in a self-selected project applying experimental methods. Students also learn how to perform simple statistical analyses with the statistical Software R.
Learning objectiveStudents
- know strategies to test causal hypotheses using experimental methods and regression analysis.
- are able to formulate and implement a research design for a particular policy question and a particular type of data.
- are able to critically read and assess published studies on policy evaluation.
- are able to use the statistical software R for data analysis.
- can apply all the steps involved in a policy impact evaluation.
ContentPolicy impact evaluation employs a wide variety of research methods, such as statistical analysis of secondary data, surveys or laboratory and field experiments. The course will begin with an overview of the various methodological approaches, including their advantages and disadvantages and the conditions under which their use is appropriate. It will continue with a discussion of the different stages of a policy impact evaluation, including hypothesis generation, formulating a research design, measurement, sampling, data collection and data analysis. For data analysis, linear regression models will be revised, with a focus on difference-in-difference methods, regression discontinuity design and randomized controlled trials used for policy evaluation. Students, who already have a solid background in these methods can skip these sessions.

Throuhgout the course, students will work on a self-selected project on a suitable topic. In addition, students will have to solve bi-weekly assignments.