Excerpt from Deterministic Chaos in Models of Human Behavior: Methodological Issues and Experimental Results

Recent work has shown that several well-known models in the system dynamics literature contain previously unsuspected regimes of deterministic chaos. The work of Day (l982a, l982b) provides an early example of chaotic behavior in economic models, while Mosekilde and others (1987) have developed corporate models which exhibit chaos. Two of the most extensively analyzed such models are Sterman's model of the economic long wave (sterman 1985, 1986, Rasmussen, Mosekilde, and Sterman 1985) and the production distribution system or Beer Distribution Game (forrester 1961, Jarmain 1963, Sterman 1984, Mosekilde and Larsen, this issue). While the demonstration that chaos can be endogenously produced in these systems is an important theoretical development, the significance of the results hinges in large measure on whether the chaotic regimes lie in the realistic region of parameter space or whether they are mathematical curiosities never observed in the real system. Further there are major questions regarding the descriptive accuracy of the decision rules postulated in the models of human systems developed to date which contain strange attractors. The practical significance of chaos and other phenomena such as self-organization in policy-oriented modeling remains unclear until it can be determined that these phenomena can occur in models whose decision rules are grounded in empirical study of the actual decision processes of the agents. It is difficult if not impossible to resolve such issues by appeal to the aggregate empirical data. In the case of the long wave, for example, there have been at most five long-wave cycles since the industrial revolution, too few for statistically reliable results. Worse, the data required are simply unavailable, and much of it is corrupted by measurement error (chen, this issue).

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