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363-0541-00L 3 Credits BSC , MSC , NDS D-USYS , D-MTEC , D-BAUG , D-MAVT , D-INFK , D-MATH , D-PHYS
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Economic Dynamics and Complexity

Lecturers & Examiners: Prof. em. Dr. Frank Schweitzer
VVZ CR n/a

Last Updated: 2026-02-05 16:16:53

Abstract

What causes economic business cycles? How are limited resources, competition, and cooperation reflected in growth dynamics? To answer such questions, we combine macroeconomic models and methods of nonlinear dynamics. We study the role of bifurcations and control parameters for dynamic stability. Feedback cycles and coupled dynamics are reasons for limited predictability, instability and chaos.

Objective

successful participant of the course is able to: - understand the importance of different modeling approaches - formalize and solve one- and two-dimensional nonlinear models - identify critical conditions for stability and dynamic transitions - analyze macroeconomic models of business cycles, supply and demand - apply formal concepts to model economic growth and competition

Content

System theory sees the economy as a complex adaptive system. What does this mean for economic modeling? We focus on two sources of complexity: (a) nonlinear dynamics, which is captured in this course, "Economic Dynamics and Complexity" and (b) collective interactions, which is captured in the course "Agent-Based Modeling of Economic Systems" (in Spring). Our approach to economic dynamics combines insights from different disciplines: macroeconomics studying business cycles and growth, system dynamics rooted general system theory and cybernetics, and nonlinear dynamics using applied mathematics. We start with a comparison of different modeling approaches, to highlight the problems and challenges of system modeling. The subsequent lectures then introduce different one- and two-dimensional nonlinear models with applications in economics, such as models of supply and demand, business cycles, growth and competition. Emphasis is on the formal analysis of these models using methods from applied mathematics and tools for solving coupled differential equations. Weekly self-study tasks are used to apply the concepts introduced in the lectures. We practice how to solve nonlinear models formally and numerically and how to interpret the results.

Resources

Lecture Notes

The lecture slides are provided as handouts - including notes and literature sources - to registered students only. All material is to be found on the Moodle platform. More details during the first lecture.

General Information

Language
English
Levels
BSC , MSC , NDS
Frequency
Yearly recurring

Examination

Type
end-of-semester examination
Mode
written 90 minutes
Aids
None
Digital
The exam takes place on devices provided by ETH Zurich.
The end-of-semester examination will account for 70% of the grade.The self-study tasks contribute to the compulsory continuous performance assessment (obligatorisches Leistungselement) and account for 30% to the final grade.The Leistungselement contains several modules: one obligatory self-study tasks (self-assessment, pass/fail), one group activity (one out of 3 group exercises, 15% of grade), and one individual submission (one out of 6 individual exercises, 15% of grade).Students will also be required to submit peer feedback about self-study solutions of other students (4 feedback submissions in total).The 30% Leistungselement is conditional on the pass/fail self-assessment exercise and the four feedback submissions.

Course Components

Type Title Time & Place Hours
lecture with exercise Economic Dynamics and Complexity
Lecture: Tuesday, 10-12 h Exercises: Tuesday, 12-13 h
  • Tue 10:15-12:00 (ML F 36)
  • Tue 12:15-13:00 (ML F 36)
3 h weekly

Offered In