Aggregation in agent-based models of economies

Agent based models are often described as bottom-up. Macro level phenomena emerge from the micro level interactions of agents. These macro level phenomena include fixed points, dynamic patterns, and long transients. In this paper, I explore the link between micro level characteristics – learning rules, diversity, network structure, and externalities – and the macro level patterns they produce. I focus on why we need agent level modeling, on how these models produce emergent phenomenon, and on how agent based models help understand outcomes of social systems in a way that differs from the analytic, equilibrium approach.