865-0008-00L Policy Evaluation and Applied Statistics
|Semester||Autumn Semester 2022|
|Lecturers||I. Günther, K. Harttgen, K. Schneider|
|Periodicity||two-yearly recurring course|
|Language of instruction||English|
|Comment||MAS ETH in Development and Cooperation students have priority for admission. Interested students can apply to be placed on the waiting list and will be informed about a possible admission by the program coordinators within the first week after the start of lectures.|
|Abstract||This 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.|
- 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.
|Content||Policy 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.