GRA 6612 Analysis of Experiments and Quasi-Experiments
GRA 6612 Analysis of Experiments and Quasi-Experiments
This course teaches modern design based approaches to empirical analysis that are prevalent in applied microeconomics. In particular, we focus on analysis techniques associated with credible empirical evidence - with a strong leaning towards experimental and quasi-experimental techniques. The course teaches both the actual implementation of the techniques using statistical software and relevant applications in the economics literature, with a particular emphasis on business relevant topics, such as personell economics and industrial organisation, in addition to classical applications in labor economics, health economics and development economics. We also explore to what extent the analysis techniques are used and can be used in business contexts.
After taking this course, students should
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know how to analyze empirical microeconomic problems using data from lab experiments or field experiments,
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know how to analyze data using regression techniques to generate comparable samples,
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know how to analyze data using instrumental variable techniques to overcome exogeneity problems,
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know how to exploit regression discontinuity designs,
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know how to analyze data using the difference-in-differences methodology.
After taking this course, students should
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be able to perform experimental and quasi-experimental analyses of economic data using statistical software
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be able to assess empirical analyses of economic problems, evaluating to what extent the analyses provide credible empirical evidence.
After taking this course, students should
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understand the selection problem and why correlation does not imply causality
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understand how and why randomized experiments enable researchers to answer causal questions empirically and why observational studies only rarely enable researchers to do provide such answers
- Empirical strategies in applied microeconomics
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Comparing experimental techniques and observational studies
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Implementation of empirical strategies in statistical software
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Key scientific studies in business relevant economics
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Applications of experimental techniques to business problems
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Please note that while attendance is not compulsory in all courses, it is the student’s own responsibility to obtain any information provided in class.
This is a course with continuous assessment (several exam components) and one final exam code. Each exam component is graded by using points on a scale from 0-100. The components will be weighted together according to the information in the course description in order to calculate the final letter grade for the examination code (course). Students who fail to participate in one/some/all exam elements will get a lower grade or may fail the course. You will find detailed information about the point system and the cut off points with reference to the letter grades when the course starts.
At resit, all exam components must, as a main rule, be retaken during next scheduled course.
All courses in the Masters programme will assume that students have fulfilled the admission requirements for the programme. In addition, courses in second, third and/or fourth semester can have spesific prerequisites and will assume that students have followed normal study progression. For double degree and exchange students, please note that equivalent courses are accepted.
Covid-19
Due to the Covid-19 pandemic, there may be deviations in teaching and learning activities as well as exams, compared with what is described in this course description.
Teaching
Information about what is taught on campus and other digital forms will be presented with the lecture plan before the start of the course each semester.
| Assessments |
|---|
Exam category: Activity Form of assessment: Presentation Weight: 20 Grouping: Group (2 - 3) Comment: Presentation Exam code: GRA66121 Grading scale: Point scale leading to ECTS letter grade Resit: All components must, as a main rule, be retaken during next scheduled course |
Exam category: Submission Form of assessment: Written submission Weight: 80 Grouping: Individual Duration: 5 Hour(s) Comment: Home exam Exam code: GRA66121 Grading scale: Point scale leading to ECTS letter grade Resit: All components must, as a main rule, be retaken during next scheduled course |
| Activity | Duration | Comment |
|---|---|---|
Teaching | 36 Hour(s) | |
Examination | 3 Hour(s) | |
Group work / Assignments | 8 Hour(s) | Preparations for student presentation |
Student's own work with learning resources | 113 Hour(s) |
A course of 1 ECTS credit corresponds to a workload of 26-30 hours. Therefore a course of 6 ECTS credits corresponds to a workload of at least 160 hours.