Syllabus
Registration via LPIS
Day | Date | Time | Room |
---|---|---|---|
Tuesday | 03/03/20 | 09:00 AM - 12:00 PM | D4.0.144 |
Tuesday | 03/10/20 | 09:00 AM - 12:00 PM | D4.0.144 |
Tuesday | 03/17/20 | 09:00 AM - 12:00 PM | D4.0.144 |
Tuesday | 03/24/20 | 09:00 AM - 12:00 PM | D4.0.144 |
Tuesday | 03/31/20 | 09:00 AM - 12:00 PM | D4.0.144 |
Tuesday | 04/21/20 | 09:00 AM - 12:00 PM | D4.0.144 |
Tuesday | 04/28/20 | 09:00 AM - 12:00 PM | D4.0.144 |
Tuesday | 05/05/20 | 09:00 AM - 12:00 PM | Online-Einheit |
Tuesday | 06/16/20 | 09:00 AM - 12:00 PM | Online-Einheit |
Tuesday | 06/23/20 | 09:00 AM - 12:00 PM | Online-Einheit |
Tuesday | 06/30/20 | 09:00 AM - 12:00 PM | Online-Einheit |
This class deals with methods and theory of program evaluation in health economics and selected social policy fields. It comprises three main parts:
- Module 1:
Paradigms and typologies of program evaluation, big picture on evidence-based policy-making
Social context of program evaluation: different types of stakeholders, dissemination of results, stakeholder analysis
- Module 2: Methods for impact evaluation
RCT, Matching, Regression Discontinuity, Diff-in-Diff
- Module 3: Methods for economic evaluation
Cost-benefit, cost-effectiveness, cost-utility analysis
***** Please note that the instructor will be on parental leave in May 2020 (expected). No class-session during parental leave. Maximum number of class sessions will be 12. *****
After this course students ...
-
aware of the importance of the social context of program evaluation,
-
familiar with the causality concept in impact evaluation and its prerequisites,
-
familiar with different econometric approaches to identify program effects,
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familiar with different approaches how to relate program benefits to its costs and draw conclusions about efficiency,
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generally able to critically reflect on different methods of impact and economic evaluation in terms of their limitations and benefits.
This being a ‘Course with continuous Assessment (PI)’, the university requires students to attend at least 80% of all classes for completing the course successfully.
- Lectures
- Examples
- Group discussions
- Discussion of distributed papers and examples
- Application in statistical software (e.g. R/Stata), exercises & examples
- 40% (Individual) Written exam, open questions
- 20% (Group) Completion of small exercises/assignments
- 30% (Group) Preparation & moderation of hands-on tutorial (Stat. Software, Excel)
- 10% (Individual) Active participation in class
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