In previous work, the analysis of the effects of aggregating simple dynamic systems has been studied by applying methods developed for thermodynamic systems in order to take account of stochastic effects. This approach is based on the Master Equation for the probability density of the contents of a vector of system levels. The goal of these studies is to determine the dynamic characteristics of systems composed of a population of sub-systems with the same dynamic structure while accounting for novel behavior that is introduced by the process of aggregating the sub-systems into the larger system.In this paper, the Master Equation analysis is applied to four versions of a Commodity Cycle model to determine the nature of modes of behavior that arise from the process of aggregating a population of entities whose dynamic structure is derived from the oscillatory structure of the commodity cycle model. The approach used here is novel in two respects. It contracts with the more recently developed analysis of chaotic systems in which non-linear, aggregate or lumped-parameter models generate behavior that is unpredictable while not being stochastic. In those models, no attempt is made to explain the large-scale or aggregate chaotic behavior in terms of the sub-systems. Compared to previous work in the same vein, this paper addresses itself to a slightly larger model as part of a natural progression in the analysis of ever-more complex systems by Master Equation methods.

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Date created

• 1987

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• Document

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• Creative Commons BY-NC-ND Attribution-NonCommercial-NoDerivs 4.0 International

  
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System Dynamic Society Records

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• This collection is part of the University Archives