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Edited by J. Barkley Rosser Jr.
Chapter 5: Bounded Rationality and Learning in Complex Markets
5. Bounded rationality and learning in complex markets* Cars H. Hommes 5.1 Introduction There are two opposing views concerning the expectations hypothesis in economics and finance. According to the traditional, neoclassical view, propagated by Muth (1961) and Lucas (1972), agents form rational expectations (RE) without any systematic forecasting mistakes. In the rational framework it is often assumed that agents have full knowledge of their economic environment, and use all available information from economic theory to compute rational forecast. Moreover, typically it is assumed that all agents are fully rational, leading to the representative rational agent benchmark. Friedman (1953) provided an early argument in support of the representative rational agent framework, namely that irrational agents would be driven out of the market, since rational agents earn higher profits or utility. Stated differently, evolutionary selection prevents irrational behavior and the economy may be described as if all agents are perfectly rational. Simon (1957) already criticized this view, arguing that deliberation and information gathering costs should be taken into account. More recently, work on bounded rationality in the 1990s, surveyed, for example, in Sargent (1993) and Conlisk (1996), has challenged the traditional view, emphasizing that the extreme assumptions concerning perfect knowledge of the economy and infinite computing capacities are highly unrealistic and in sharp contrast with observed behavior in laboratory experiments with human subjects (for example, Tversky and Kahnemann, 1974). In macroeconomics, much work has been done on adaptive learning, as surveyed, for example, in Evans and Honkapohja (2001). A key underlying assumption...
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