This track explores the application of complex systems theory to economic phenomena, emphasizing the interdependencies and interactions within economic agents. Contributions may include theoretical frameworks and empirical studies that illustrate the dynamics of economic systems.

Focusing on agent-based computational economics, this track invites papers that utilize agent-based models to analyze economic behavior and market dynamics. Submissions should demonstrate how these models can enhance our understanding of economic complexity.

This track seeks contributions that apply Bayesian methods to non-linear time series and econometric models. Papers should discuss the advantages of Bayesian approaches in capturing uncertainty and improving predictive accuracy in economic contexts.

Contributions to this track should focus on econometric techniques that address regime changes, non-linear cointegration, and panel data methods within complex systems. The aim is to enhance the understanding of economic relationships through advanced econometric modeling.

This track examines the diffusion of innovations through system dynamics analysis, highlighting the factors that influence the adoption of new technologies in economic systems. Papers should provide insights into the mechanisms driving innovation and its impact on economic growth.

This track invites research that applies principles from physics to understand financial markets and economic systems. Contributions should explore the implications of extreme events and market behavior through the lens of econophysics.