The reason why the complexity approach is taking hold now in economics is because the computing technology has advanced. This advance allows consideration of analytical systems that could not previously be considered by economists. Consideration of these systems suggested that the results of the "control-based" models might not extend easily to more complicated systems, and that we now have a method-piggybacking computer assisted analysis onto analytic methods-to start generating patterns that might provide a supplement to the standard approach. It is that approach that we consider the complexity approach.
The papers in this volume develop these ideas. In terms of policy the papers suggest that economists should become a bit less certain in their policy conclusions, and that they expand their bag of tools supplementing their standard model with some additional models including (1) agent based models, in which one does not use analytics to develop the pattern, but instead one uses computational power to deal with specification of models that are far beyond analytic solution; and (2) non-linear dynamic stochastic models many of which are beyond analytic solution, but whose nature can be discovered by a combination of analytics and computer simulations.
The volume is divided into four sections: general issues, modeling issues, applications, and policy issues. Each struggles with complicated ideas relatedto our general theme, and a number of them try out new techniques.
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