This module presents, compares and contrasts different macroeconomic modeling paradigms. Students will get to know several advanced ways in which economic growth can be modeled and what assumptions and fundamental views on economic dynamics underlie each strategy.
This module presents, compares and contrasts different macroeconomic modeling paradigms.
Students will get to know several advanced ways in which economic growth can be modeled
and what assumptions and fundamental views on economic dynamics underlie each strategy.
In particular, the mainstream Dynamic Stochastic General Equilibrium (DSGE) approach is
compared to alternative approaches such as the System Dynamics (SD) approach. The goal is
to highlight the basic features, strengths and weaknesses of the models discussed and the
different views they reflect on the nature of economic processes. Students will also learn how
a complexity view on the economy differs from the neoclassical view and how it can be
represented through alternative modeling strategies.
Students will also get the opportunity to apply their newly attained knowledge in some
applied modeling tasks.
- You get an overview of different macroeconomic modeling paradigms.
- You learn about the major class of mainstream macroeconomic models, the Dynamic
Stochastic General Equilibrium (DSGE) approach with both its features and drawbacks.
- You learn how economic dynamics can be represented using systems of differential
equations and System Dynamics (SD) models.
- You acquire methodological knowledge about creating and solving macroeconomic models
such as continuous dynamic systems, DSGE- and SD-models.
Students will need excellent English skills and the willingness to deal different types of
economic models, some mathematical and some computational. Students should also be
willing to deal with some macroeconomic models in a hands-on fashion.
This module consists of lectures and some tutorials. There will also be a Moodle course that
will likely go online the week starting on October 10th.
Participants: no restriction
Lectures/tutorials: In the tutorial sessions, students can work on their homework tasks and
ask questions. Students are expected to bring their own laptops and pre-install some Open Source
software to make this feasible.
Assessment: A final exam that will take place in Feburary 2023. The date will be announced shortly in the Moodle course.
In order to qualify for the final exam, you will need to submit six ungraded homework assignments (Studienleistung) that can be worked on in the tutorial sessions. The topics of the final exam will mirror those of the homework assignments very closely.
Time and place: Friday,10:00 to12:00(HGB50),Friday12:00 to 14:00(GD02/236)
(in person, except where noted differently in the lesson plan and below)
The first two sessions will take place ondifferent days and times, they
will be streamed live on Zoom and available as recordings on Moodle.
Start: October, 11th 2022, 12:30 – 14:00 – Zoom live & recorded:
introduction to the course.
Second session: October, 20st 2022, 16:15 – 17:45 – Zoom live &
(The links to the zoom sessions will be provided in due time on Moodle
Resit exam: date and further details will be announced in due time.
This module contains 120 hours of self-study and applied homework.
Relevant material will be provided on Moodle.
The preliminary course schedule will be available on Moodle before the introductory session.
Any change will be announced on Moodle in due course.
Infomaterial (PDF Download):
Exam Registration: Will be announced in the Moodle course.
Exam De-Registration: Will be announced in the Moodle course.
Both via FlexNow
Vorlesung / Tutorium
HGB 50, GD02/236, online