Macroeconomics from the Bottom Up via Very Large Scale Multi-Agent Systems

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This research concerns the creation of a new kind of macroeconomic model. Conventional macroeconomics uses mathematics to represent how aggregate economic variables, like overall savings and investment, jointly determine one another. Such models are highly aggregate, as if the overall economy consisted of one large firm selling to a single consumer who is also an employee. Due to recent advances in computer technology, the macroeconomy can be represented much more realistically, with all the heterogeneity that is present in the real world also present in models of it.In the proposed research, computational models will be built consisting of large numbers (millions) of software objects known as agents, with each object representing a person. Over time these agents will interact economically, buying and selling artificial goods, consuming and saving, investing and trading. Using such models, aggregate economic relationships will emerge in cross-section as well as over time. The overall goal is to end up with a behaviorally rich model of an economy 'under glass,' so to speak-an artificial economy-that can be calibrated to real economies of today. If successful, this research will move macroeconomics away from highly stylized models and empirically unrealistic behavioral specifications, to models that are more believable. Ultimately, the goal of such efforts is to produce macroeconomic models that have high performance at predicting the near term unfolding of an economy, thus providing more accurate forecasts of economic evolution. These models could aid policy-makers in their decision-making, which in turn could translate into potentially very large increases in the performance of the economy.