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Vassilis Koulovassilopoulos and Giulia Iori ()
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Vassilis Koulovassilopoulos: South Bank University

No 84, Computing in Economics and Finance 2000 from Society for Computational Economics

Abstract: A common feature of many aggregate variables in economics and finance is that they exhibit oscillatory behaviour, showing boom-and-bust patterns. Examples are fad and bandwagon behaviour in sociology, business cycles in economics, bubbles in stock market prices, wave behaviour in the adoption of innovation technology.We study consumption behaviour in systems with heterogeneous interacting agents. Two different models are introduced, respectively with long and short range interactions among agents. At any time step an agent decides whether or not to consume a good, doing so if this provides positive utility. Utility is affected by idiosyncratic preferences (noise) and costs as well as externalities from other agents. Agents are ranked in classes, with interactions among agents depending on the agents' ``distance'' (such as, for example, differences in wealth), and they recognize peer, distinction and aspiration groups. We simulate the system numerically for different choices of the parameters as well as for different class (wealth) distributions and identify different complex patterns: a steady state regime with a variety of consumption modes of behaviour, and a wave/cycle regime. The cases of fashion (fad) and value goods are both analyzed.The crucial point in this model is not the exact description of individual behaviour but the interrelation between individuals and the statistical properties of consumers' characteristics. We want to identify which are the relevant mechanisms that determine the large scale behaviour of aggregate consumption. In our model the macro-level organization, manifests in complex consumption patterns, which emerge purely from the micro-level interactions among agents, without the coordinating effect of any aggregate signal.Particular emphasis is given to the dynamical properties of the model, and we provide examples of complex patterns, such as non-periodic consumption cycles and turbulent behaviour with boom and busts in consumption activity. Our model bears resemblance with models of statistical mechanics of disordered systems and provides an example of how the development of appropriate numerical approaches may provide fundamental advances in the understanding of the complex behaviour that arise from the nonlinear spatio-temporal interactions among a large number of units.

Date: 2000-07-05
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More papers in Computing in Economics and Finance 2000 from Society for Computational Economics CEF 2000, Departament d'Economia i Empresa, Universitat Pompeu Fabra, Ramon Trias Fargas, 25,27, 08005, Barcelona, Spain. Contact information at EDIRC.
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