TOPICS IN ECONOMICS I
- Overview
- Assessment methods
- Learning objectives
- Contents
- Bibliography
- Delivery method
- Teaching methods
- Contacts/Info
None.
Students will be evaluated on the basis of an essay discussing a topic relevant to the course. A written exam will be introduced if necessary.
Agent-based modelling (ABM) has been acknowledged by many scholars and various scientific disciplines as a promising tool to investigate the dynamics of complex systems, such as economic systems. In particular in economics, ABM increasingly gains momentum and is considered as an approach with the potential to overcome the shortcomings of the mainstream approach with its optimization- and equilibrium-oriented framework which requires substantial simplifications of the phenomena under investigation.
By the end of the course, students will
- understand the basics of the ABM approach, including the main benefits and pitfalls,
- be able to assess when an agent-based approach should be used and why,
- have learned basic programming skills in NetLogo allowing them to independently work with existing models and to create new models.
This course is subdivided into 4 interrelated parts:
(1) Introduction to agent-based modelling in economics (5 hours): The introduction aims at giving some more general thoughts on what agent-based modelling is, what we can do with it and how it relates to other modelling approaches. Through various sample models, this part with also introduce the students to NetLogo a free software environment that can be used to program simple agent-based models.
(2) Current challenges of economics (5 hours): The second part aims at explaining in more detail the advantages of an agent-based modelling approach, focusing on the current challenges in economics. The main benefits and pitfalls of ABM will be elaborated on by using sample models in NetLogo. For this, the students will work in groups using and analysing the sample models.
(3) Modelling knowledge as a key for innovation (5 hours): During the third part of this course, students will develop a simple model of knowledge creation and diffusion. For this, different knowledge representations will be introduced and the consequences of each representation will be discussed in detail.
(4) Future challenges (5 hours): The last part of this course will critically reassess the content of the course and will give a broad overview on future challenges and possible research avenues in this field.
The course will be based on a set of slides written by the lecturer, covering both theory and specialized paper-length examples. A list of academic papers addressing more advanced topics will be provided to the students as additional readings.
The course will combine traditional lecturing and self determined learning in groups. Particular focus will be on the practical application of the theory by working with NetLogo.
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