ABM4ECO - Agent based models in Economics: theory, toolkit, and policy laboratories

VI EDITION | ON SITE | APPLICATION

Deadline for Registration 
10th May, 2027

Period
5th - 9th July, 2027

Learning objectives 

The Seasonal School is intended to achieve the following objectives: 

• Learning of agent-based modelling techniques (ABMs) as a tool of analysis and interpretation of economic and social processes. 

• Development and design of agent-based models through software laboratories (Laboratory for Simulation Development platform, LSD). 

• Introduction to statistical and econometric techniques for the analysis of macro- evolutionary agent-based models (R software). 

Competencies provided include: 

• Theories and applications of agent-based models in micro and macroeconomics uncovering diverse thematic areas such as technical progress, business cycles, labour markets, economic growth, climate change. 

• Empirical validation and analysis of models' parametric space. 

• Scenarios-based analysis and policy experiments. 

Teaching methodologies

Students will find an interactive and cross-disciplinary learning environment that will mix frontal lectures, laboratories, group works and presentations with critical discussion.

Target participants

Master and PhD students in economics, finance, public policy, statistics, physics, data science, and engineering.

Coordinator and key teaching staff

Coordinator: Prof. Francesco Lamperti 

Key teaching staff: Prof. Giovanni Dosi; Prof. Giorgio Fagiolo; Prof. Alessio Moneta; Prof. Mauro Napoletano (Université Côte d’Azur); Prof. Andrea Roventini; Prof. Marcelo Pereira (UNICAMP); Dr. Lilit Popoyan (Università di Napoli Parthenope); Prof. Maria Enrica Virgillito (Catholic University of Milan)

SDGs (https://sdgs.un.org/goals)

(8) Decent work and Econmic growth

(10) Reduced Inequalities

(13) Climate Action