Patrick Michael Kuhn: Catalogue data in Spring Semester 2019 |
| Name | Dr. Patrick Michael Kuhn |
| URL | https://sites.google.com/site/pmkuhndr/home |
| Department | Humanities, Social and Political Sciences |
| Relationship | Lecturer |
| Number | Title | ECTS | Hours | Lecturers | |
|---|---|---|---|---|---|
| 869-0107-00L | Policy Impact Evaluation  Number of participants limited to11. Only for MAS in Science, Technology and Policy and Science, Technology and Policy MSc. | 2 credits | 1G | P. M. Kuhn | |
| Abstract | This seminar will look at a variety of evaluation designs, from randomized program evaluations through experimental evaluation methods to observational analysis, using a variety of research designs. Evaluating the effectiveness of public programs is important, since it can help to decide which program should be expanded and which ones should be scaled down or discontinued. | ||||
| Learning objective | Program evaluation comprises a set of (statistical) tools designed to assess the causal impact of interventions to social systems, such as job training programs, on outcomes of interest, such as earnings or length of unemployment. We will look at a variety of evaluation designs, from randomized program evaluations through experimental evaluation methods to observational analysis, using a variety of research designs. Evaluating the effectiveness of public programs is important, since it can help us decide which program we should expand and which ones we should scale down or discontinue. The goal of this seminar is to introduce students to the fi of program evaluation and its statistical tools, and enable them to think about how programs should be developed, and become critical consumers of empirical evaluations of public programs. The two-day seminar consists of two parts: a series of lectures and exercises on randomized program evaluation on day 1 and a lecture and exercises on ex-post program evaluation on day 2. The are three lectures introducing students to the topic, key challenges (e.g., the fundamental problem of causal inference), and the various evaluation designs. For each of these lectures students are assigned introductory readings, which should be completed prior to attending the relevant lectures. The readings are very basic and introduce students to key concepts and challenges in a non-technical way to build intuition. The lectures will expand on those readings and move beyond the readings pretty quickly, introducing the key concepts in a more technical and rigorous manner. The lectures will also provide examples to illustrate the use of the various concepts. The exercises serve as practice, requiring students to apply the concepts of the lecture in developing evaluation designs for real-world policy programs from a variety of policy areas. The seminar targets 'mathematically inclined' master and doctoral students. Basic knowledge of statistical inference and regression analysis at the introductory level is required. The assigned readings and lectures will make use of some elementary calculus and statistical notation. The seminar will focus on evaluation design rather than analytical techniques, we will therefore not be performing any data analysis or use any specific statistical software. For students with limited past exposure to statistical inference and regression analysis, I recommend reading the following prior to attending the seminar: - Achen, Christopher J. (1982) Interpreting and Using Regression. The Little Green Books Series. London: Sage Publications Inc. - Stock, James and Mark Watson (2011) Introduction to Econometrics, Third Edition. London: Pearson Education, Part II. | ||||
| Content | Lectures: The Fundamental Problem of Causal Inference Randomized Program Evaluations Ex-post Evaluations Student Exercises | ||||