Advanced Econometrics: Causal Analysis PHD401
In most of economics, marketing and business management, we are interested in causal relations between variables, rather than mere correlations. For example, it is not the correlation between marketing expenses and sales that is of interest, but the effect of increasing marketing expenses for a product on the sale volume of the same product.
Course description for study year 2020-2021. Please note that changes may occur.
PHD401
5
1
Spring
English
UiS Business School
Knowledge
Students should be conversant about methods for estimating and identifying causal effects, and have the intuition and skills necessary to design and implement empirical strategies for causal analysis.
Skills
Students should be able to
- Understand causal modeling
- Gain the statistical tools for causal analysis
- Design and implement empirical strategies for causal analysis
- Become aware of underlying assumptions, strengths, and weaknesses of different experimental and quasi experimental approaches
- Become acquainted with key players in the development and implementation of strategies for causal analysis
General competence
The student should be conversant in the world of causal analyses, using instrumental variables, difference-in-difference, regression discontinuity design, synthetic control methods, and randomized controlled trials. They should be able to be consumers and producers of causal analyses. They should have the background to develop and implement ethically sound and scientifically valid empirical strategies. They should also have proficiency in software designed to implement causal analysis.
Vurderingsform | Vekting | Varighet | Karakter | Hjelpemiddel |
---|---|---|---|---|
Individual essay | 1/1 | Pass - Fail |
Student evaluation will be conducted according to the regulations set forth by the Faculty of Social sciences.
- Full participation during the whole course is required. (One week on intensive lectures and PC-lab exercises).
- Active participation in discussions in general.
- In addition, there is a term paper requirement ( 8-10 pages, demonstrating knowledge and application skills).
The course will be taught through a combination of lectures, seminars and exercises. The seminars will include student presentations and discussions. Each student will be required to give one seminar presentation. All students are expected to read required literature ahead of the seminars and to participate actively in the discussions. Exercises will be undertaken on empirical cases (firms, sectors, markets) using appropriate data and software tools. Students will also have a written assignment in addition to the final essay.
Estimated student workload in hours:
1. Lecture 28
2. Seminar/lab exercise 8
3. Specific supervision 20
4. Student's self studies 50
5. Written assignment 40
TOTAL 146