Thank you for your interest in the ABM Summer School

Agent-based models (ABM) are a powerful and increasingly essential tool in economics and across other social sciences for studying complex systems and social challenges. This summer school addresses the critical need for researchers to master not only the conceptual underpinnings of ABM but also the practical challenges of programming, adhering to robust protocols, and effectively communicating model design and results.

Building on past successful editions, this intensive, full-time summer school equips participants with the advanced theoretical understanding and skills to design, implement, validate, and analyse robust agent-based models, such as a PhD thesis, a high-quality academic paper, or a policy report.

In this edition we will also evaluate the power and limitations of Large Language Models (LLM) as co-pilots in designing and coding ABMs. In an era where researchers increasingly turn to LLM to generate code, this course emphasises the critical importance of understanding model mechanics. By comparing AI-generated models with manual coding, students will appreciate the need for bridging theory and implementation.

While the methodological skills acquired are applicable across all social sciences, the primary case studies will focus on economics, innovation, development, political economy, public policy and structural change.