Agent-Based Economic Modeling Using Python
Course objective:
By the end of the course the participants will have acquired detailed knowledge of and hands-on experience in:
- Python
- How to formulate research questions for agent-based models
- How to write agent-based models
- How to create firm agents
- How to create household agents
- Different behavioral approaches to agents' behavior such as
- Maximizing agents
- Agents acting according to behavioral heuristics
- Machine learning and other behavioral approaches
- How to structure them for extensionality
Methodology:
The course will be hands-on and structured around the creation of models. On day one, we will implement the simplest possible economic model where agents only trade. From day 2 to day 4 we will progressively build an economy with:
- Production firms
- Consumers
- Workers
- Firm to firm trade
- A circular economy
The students will have created a model economy that can be extended to their research and analyzed to answer questions they are interested in.