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Complexity economics
Complexity economics is the application of complexity science to the problems of economics. It studies computer simulations to gain insight into economic dynamics, and avoids the assumption that the economy is a system in equilibrium.〔Beinhocker, Eric D. The Origin of Wealth: Evolution, Complexity, and the Radical Remaking of Economics. Boston, Massachusetts: Harvard Business School Press, 2006.〕
== Models ==
The "nearly archetypal example" is an artificial stock market model created by the Santa Fe Institute in 1989.〔 The model shows two different outcomes, one where "agents do not search much for predictors and there is convergence on a homogeneous rational expectations outcome" and another where "all kinds of technical trading strategies appearing and remaining and periods of bubbles and crashes occurring".〔
Another area has studied the prisoner's dilemma, such as in a network where agents play amongst their nearest neighbors or a network where the agents can make mistakes from time to time and "evolve strategies".〔 In these models, the results show a system which displays "a pattern of constantly changing distributions of the strategies".〔
More generally, complexity economics models are often used to study how non-intuitive results at the macro-level of a system can emerge from simple interactions at the micro level. This avoids assumptions of the representative agent method, which attributes outcomes in collective systems as the simple sum of the rational actions of the individuals.
抄文引用元・出典: フリー百科事典『 ウィキペディア（Wikipedia）』
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