869-0107-00L  Policy Impact Evaluation

SemesterSpring Semester 2019
LecturersP. M. Kuhn
Periodicityyearly recurring course
Language of instructionEnglish
CommentNumber of participants limited to11.

Only for MAS in Science, Technology and Policy and Science, Technology and Policy MSc.



Courses

NumberTitleHoursLecturers
869-0107-00 GPolicy Impact Evaluation
Block Course 22. - 24.03. 2019
16s hrs
22.03.09:15-17:00UNO B 11 »
23.03.09:15-17:00UNO B 11 »
24.03.09:15-17:00UNO B 11 »
P. M. Kuhn

Catalogue data

AbstractThis 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 objectiveProgram 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.
ContentLectures:
The Fundamental Problem of Causal Inference
Randomized Program Evaluations
Ex-post Evaluations

Student Exercises

Performance assessment

Performance assessment information (valid until the course unit is held again)
Performance assessment as a semester course
ECTS credits2 credits
ExaminersP. M. Kuhn
Typeungraded semester performance
Language of examinationEnglish
RepetitionRepetition only possible after re-enrolling for the course unit.

Learning materials

No public learning materials available.
Only public learning materials are listed.

Groups

No information on groups available.

Restrictions

Places11 at the most
PriorityRegistration for the course unit is only possible for the primary target group
Primary target groupScience, Technology and Policy MSc (860000)
MAS ETH in Science, Technology and Policy (869000)
Waiting listuntil 18.02.2019

Offered in

ProgrammeSectionType
MAS in Science, Technology and PolicyMAS-specific Core CoursesWInformation
Science, Technology, and Policy MasterElectivesWInformation