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Complexity and Uncertainty in the Forecasting of Complex Social Systems

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  • Péter Alács

    (World in Figures)

Abstract

The better the model, the more features of the problem it explains. However, showing that the model has similarities to that of a phenomena is often less significant in applications due to lack of data. Forecasting, as special application of modelling, is neither an exception: besides statistical data one should use several types of subjective assumptions about the present and the future state of the model. In case of complex models, this fact is extremely important, because these models use often unobservable, hidden or - regarding its future evolution - uncertain variables. We developed a simple mathematical approach how these uncertainties can be managed in the model. We shall also show how these uncertainties can influence the behaviour of modelled variables, and how an approximate for time horizon of forecasts can be calculated. Classification-ACM-1998: J.4; Social and behavioral sciences

Suggested Citation

  • Péter Alács, 2004. "Complexity and Uncertainty in the Forecasting of Complex Social Systems," Interdisciplinary Description of Complex Systems - scientific journal, Croatian Interdisciplinary Society Provider Homepage: http://indecs.eu, vol. 2(1), pages 88-94.
    • Handle: RePEc:zna:indecs:v:2:y:2004:i:1:p:88-94
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    Cited by:

    1. Saqalli, M. & Gérard, B. & Bielders, C.L. & Defourny, P., 2011. "Targeting rural development interventions: Empirical agent-based modeling in Nigerien villages," Agricultural Systems, Elsevier, vol. 104(4), pages 354-364, April.

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