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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: Dr. Luca Verginer
VVZ CR n/a

Last Updated: 2026-06-01 11:30:27

Abstract

What drives systemic risk in financial markets? How do global supply networks shape trade?We address these questions through the lens of complex networks, examining how interactions among firms, institutions, and countries create emergent macroeconomic behavior. We analyze how network topology shapes diffusion, resilience, and growth—and how network models inform policy and decision-making.

Objective

By completing this course, participants will be able to: - Understand the basic concepts of complex networks and their relevance in economics - Use network analysis to characterize resilience, power, and vulnerability - Simulate and interpret dynamic processes on networks (e.g., contagion, diffusion, growth) - Evaluate policy implications and systemic risks using a network-based perspective

Content

In this course, we explore the following themes: - Foundations of Network Theory - Basics of graph theory. - Network topology and their meaning and application in economic models. - Network Metrics and Their Economic Interpretation - Measuring centrality, clustering, and community structures, and exploring their impact on market power, collusion, or information flow. - Models of network evolution and growth, focusing on how economic incentives shape network structure. - Modeling Economic Systems as Networks - Input-Output Networks: Production and consumption interdependencies. - Financial Networks: Contagion and systemic risk from interconnected balance sheets. - Trade and Production Networks: Exploring global value chains and regional trade blocs as network structures. - Game Theory and Strategic Interactions on Networks: Games on networks, diffusion of behaviors, bargaining, and coalition formation. - Dynamic Processes and Resilience - Contagion and Diffusion: Spread of financial shocks, adoption of new technologies, or shifts in consumer behavior. - Systemic Risk and Resilience: Identifying structural weaknesses, analyzing feedback loops, and measuring robustness to shocks. Students will complete coding and data analysis assignments to build, analyze, and simulate networks using Python. Applications are drawn from real-world economic datasets covering trade, production, and financial systems.

Resources

Lecture Notes

Lecture slides and materials will be provided to registered students via Moodle. Details will be explained in 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.Weekly self-studies, the continuous performance assessment (obligatorisches Leistungselement), accounts for 30% to the final grade.

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 H 44)
  • Tue 12:15-13:00 (ML H 44)
3 h weekly

Offered In