Economics, Complexity and Development
Inclusive and sustainable economic development constitutes difficult challenges for all countries. It is a complex phenomenon, involving heterogeneous agents, continuous innovations, and structural change. Understanding the unbalances and discontinuities in the process of economic development requires tools and thinking suited to deal with complex systems and evolving dynamics.

Research on economic complexity (Arthur-2013, Beinhocker-2006) provides a promising way to study the relationship between economic growth, structural change and SDGs.

In recent years, with the advances in computer science, several macro models representing the economy as a complex system have emerged. Such models are significantly contributing to understand the economy as the result of interactions between heterogeneous agents.

Empirical work investigating changes in the composition of export structures describes the space of goods and sectors using tools from network and complexity theory. Similarly, technological change has been described as a complex adaptive system.

Aims and Objectives
Agent-based simulation models are increasingly adopted as research tool in economics and other social sciences. Along with the several avenues that these models open for research,
are the difficulties related to programming, following a robust methodological protocol and properly communicate the model and results.
The course will provide students with the necessary skills to design, implement, and analyse robust agent based models.
This is a week-long full-time intensive course to teach PhD and young scholars how implement and best exploit agent-based simulation models in Economics for research purposes. It will
provide students with both the technical and methodological skills required to successfully develop and analyse simulation models in a research project, such as a PhD or a paper.