Acceptance of computer modeling and experimentation has spread slowly at best in economics in large part because agent-based models often seem foreign to the neoclassical core of economics, as that core is understood today. But in its beginnings neoclassical economics was not built from choice theory, did not represent decisions as solutions to constrained optimization problems, made no strong assumptions about the rationality of agents, and did not view the world as always in equilibrium. Agent-based economics can tap into this older neoclassical economics of adaptive behavior and ongoing market processes while circumventing the technical obstacles which forced the forerunners to adopt the "static" method.Agent-based process analysis will finally make it possible to tackle the central problem of macroeconomics, namely, the self-regulating capabilities of a capitalistic economy. Keynes challenged the presumption that flexibility of all prices guaranteed the stability of general equilibrium, arguing that effective demand failures meant that Say's Law did not hold. When supply did not create its own demand, stabilization policy in the form of aggregate demand management was required to restore full employment. In modern general equilibrium based macroeconomics, in contrast, Say's Law always holds, only "frictions" stand in the way of full employment, and stabilization policy lacks any tenable rationalization.Agent-based computational methods provide the only way in which the self-regulatory capabilities of complex dynamic models can be explored so as to advance our understanding of the adaptive dynamics of actual economies.
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ReDIF This chapter was published in: Leigh Tesfatsion & Kenneth L. Judd (ed.) Handbook of Computational Economics, , chapter 36, pages 1625-1637, 2006.