Microeconomics MSB107

Content

Microeconomic analysis provides critical tools for modern business leaders, public policymakers and resource managers, as well as researchers in both the private and public sector. This course introduces students to microeconomic theory and its real-world applications at the master-level. It comprises three separate modules: Module 1 presents core neoclassical theories of the consumer, firm, and market equilibrium outcomes, emphasizing training in abstract thinking and formal analysis (mathematical, graphical, and verbal). Module 2 covers a selection of extended microeconomic topics (e.g., game theory, multi-attribute discrete choice, behavioral economics, network economics, welfare economics). Module 3 trains students in applied microeconomic analysis (decoding scientific articles, conducting data analysis, and scientific writing).

Learning outcome

Knowledge

Upon completion of the course, students will have:

• An advanced understanding of key microeconomic concepts, theories and models that form the basis of the course and the science of economics
• The ability to see the complexity and scope of the determinants of economic behavior in consumers, producers and other types of microeconomic agents
• Developed extensive knowledge and economic intuition regarding the formalization of models of the decision-making processes of microeconomic agents

Skills

Upon completion of the course, students will:

• Have the ability to use different theories and models to analyze what drives economic actors in different situations
• Know how to read and comprehend published microeconomic research
• Be capable of implementing their own applied microeconomic research
• Be able to apply microeconomic tools as a basis for evaluating and developing economic decision-making strategies in both the private and public sectors of the economy

Required prerequisite knowledge

None

Exam

Course teacher(s)

Course coordinator: Gorm Kipperberg

Study Program Director: Yuko Onozaka

Method of work

Attend lectures, process course material (textbook chapters, scientific articles, etc.), solve practice problems (both graded and non-graded), work in learning teams. The expected distribution of effort is approximately as follows:

Attending lectures                       = 40 hours

Attending practice sessions        = 20 hours

Learning team work                     = 110 hours

Independent study                       = 110 hours

Open for

Course assessment

Students will have the opportunity to give feedback on the course first in an early dialogue, and then in a written course evaluation at the end of the course.

Literature