Syllabus

Title
6319 Economic Modeling
Instructors
Univ.Prof. Dr.Dr. Ulrich Berger, Ass.Prof. PD Michael Pfarrhofer, Ph.D.
Type
PI
Weekly hours
2
Language of instruction
Englisch
Registration
02/13/25 to 02/19/25
Registration via LPIS
Notes to the course
Subject(s) Bachelor Programs
Dates
Day Date Time Room
Wednesday 03/12/25 10:15 AM - 12:00 PM TC.3.10
Wednesday 03/19/25 10:15 AM - 12:00 PM TC.3.10
Wednesday 03/26/25 10:15 AM - 12:00 PM TC.3.10
Wednesday 04/02/25 10:15 AM - 12:00 PM TC.3.10
Wednesday 04/09/25 10:15 AM - 12:00 PM TC.3.10
Wednesday 04/30/25 10:00 AM - 12:00 PM TC.3.03
Wednesday 05/07/25 10:15 AM - 12:00 PM TC.3.10
Wednesday 05/14/25 10:15 AM - 12:00 PM TC.3.10
Wednesday 05/21/25 10:15 AM - 12:00 PM TC.3.10
Wednesday 05/28/25 10:15 AM - 12:00 PM TC.3.10
Wednesday 06/04/25 10:15 AM - 12:00 PM TC.3.10
Wednesday 06/18/25 10:00 AM - 12:00 PM TC.4.03
Contents

The first part of the course introduces the concept of models in economic research and examines the central idea of homo oeconomicus. Based on these foundations we introduce and discuss several fundamental models of microeconomics and game theory, including preference relations, choice under certainty and under risk, and two-person games.

The second part of the course introduces students to stochastic processes and explores their applications in dynamic models of the macroeconomy. We characterize and analyze the role of policy and non-policy shocks (and their propagation) in shaping business cycles.

Learning outcomes

Students recognize the fundamental place of formal models in economic research. They understand the central role played by homo oeconomicus and are able to counter naive criticism of this model. Students know the most important models in microeconomics and game theory and can explain how they work and how to interpret their results. Students understand key topics in time series analysis and can apply related concepts both theoretically and empirically to assess the dynamic causal effects of macroeconomic shocks.

Attendance requirements

The attendance requirement is met, if a student is present at least 80%. Therefore, students are allowed to be absent for at most two teaching units.

Teaching/learning method(s)

Lectures and interactive solving of exercises in class.

Assessment

A midterm exam (40%) covers the first part and a final exam (40%) the second part. The remaining 10% in each part can be earned by solving homework exercises, by active participation, or by submitting a modelling group-project. (Detailed information on this will be provided in the first unit of each part.)

Readings

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Recommended previous knowledge and skills

Knowledge of basic mathematics and quantitative methods is necessary.

Availability of lecturer(s)

The lecturers can be contacted by email.

Last edited: 2024-11-14



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