Agent-based models in Economics: theory, toolkit and policy laboratories
I EDITION | ON SITE | APPLICATION
Deadline for Registration
April 30th, 2022
Maria Enrica Virgillito
July 11th -15th, 2022
The study of economies seen as complex evolving systems has proven to be an appropriate lens of analysis to interpret and provide diagnoses of the many instances of the structure of capitalism. Heterogeneity, non-linearity, interdependent and cumulative processes, structural crises, regime changes, path-dependence and inequalities are among the key properties of both micro and macroeconomic phenomena.
Agent-based models are a powerful and growing tool to develop theoretical models disciplined by empirical evidence, able to address the complex and evolving nature of economies; additionally they constitute a natural policy laboratory enabling the possibility to perform scenarios analysis useful to inform policy choices.
The Institute of Economics of Sant'Anna School of Advanced Studies launches the first Seasonal School in "Agent based models in Economics: theory, toolkit and policy laboratories".
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).
- 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, economic cycles, labour markets, economic growth, climate change.
- Empirical validation and analysis of models' parametric space.
- Scenarios-based analysis and policy experiments.
Frontal lectures, laboratories and seminars.
Who should attend this Seasonal School?
Master and PhD students enrolled in Economics curricula. Applicants from other disciplines are welcomed.
Key teaching staff
Giovanni Dosi, Francesco Lamperti, Andrea Roventini, Giorgio Fagiolo, Francesco Lamperti, Alessio Moneta, Lilit Popoyan, Emanuele Russo, Marcelo C. Pereira