GRA 4144 Applying Economic Analysis
GRA 4144 Applying Economic Analysis
In this course, you will learn to understand markets and strategies and how economic analysis supports business decisions. The course will emphasize both theoretical understanding and practical applications, with data analysis and real-world case studies. The skills and knowledge acquired in this course will enable you to use analytics in business strategy applications.
After completing the course, the students should know the main microeconomic theories and models relevant to understanding markets and strategic dynamics. They should also understand how these insights can be used to support strategic decisions.
After completing the course, students should be able to:
- Mathematically formulate and solve economic models of relevance to the firm.
- Analyze and understand the strategic dynamic of a market.
- Use a combination of economic analysis, computational tools and available data in support of actual firm decisions.
Students will learn how to apply practical economic analysis in situations commonly faced by firms.
The course will cover the following main topics:
- Strategic interactions
- Market structures
- Game theory
- Pricing schemes
- Network externalities
- Auctions
The teaching will mainly consist of lectures and working with practical cases. Case solutions will be given in R or Excel, but students are free to use Python or Matlab if they prefer.
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.
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 specific prerequisites and will assume that students have followed normal study progression. For double degree and exchange students, please note that equivalent courses are accepted.
Disclaimer
Deviations in teaching and exams may occur if external conditions or unforeseen events call for this.
Students are expected to be familiar with constrained optimization in one or two variables. No prior knowledge of Economics is required.
| Assessments |
|---|
Exam category: Submission Form of assessment: Submission PDF Exam/hand-in semester: First Semester Weight: 100 Grouping: Individual Duration: 48 Hour(s) Comment: Home exam Exam code: GRA 41441 Grading scale: ECTS Resit: Examination when next scheduled course |
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.