Conventional financial and macroeconomic models have been demonstrated to be of limited utility in either forecasting, limiting, or remedying the current financial downturn. This workshop will focus on complexity-theoretic alternatives to traditional DSGE macroeconomic models. Specifically, agent-based approaches for building large-scale, distributed models of economic phenomena at the country-level will be highlighted. Attendees will discuss priorities for basic research to make progress toward useful models most expeditiously and explore plans for coordinating to develop next-generation modeling of economies. Participants will come from economics and finance, computer science and multi-agent systems, and physics, as well as public and private sector model users.
Even a slight improvement in our ability to model the economy would have valuable implications for better policy making and mroe robust economies. Also: methodological advances in complexity modeling that apply to economies will also be useful for modeling other important complex entities, like political systems, organizational systems, and systems.
