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Social interaction, herd behaviour and the formation of agent expectations


Author Info

  • Mark Bowden

    (School of Economics, University of Queensland)

  • Stuart McDonald

    (School of Economics, University of Queensland)


Survey data on agent expectations appear to experience inertia, remaining relatively stable for protracted periods punctuated with the occasional structural shift initiated by exogenous changes. The data is also characterised with an underlying level of volatility which varies over time. This paper examines if social interaction and herd behaviour, based on the social learning literature, can explain the characteristics of this dynamic process. The social learning takes place in a network with small world characteristics. Moving from an ordered to a small world network dramatically increases the level of volatility and it quickly reaches a higher state (at which point increasing the randomness of the network has little effect). Assuming that all social networks have small world characteristics then there is an inherent level of volatility in expectations formation. Increasing the influence of experts, by increasing the number of connections from these agents, also increases volatility. This may explain the variability in volatility over time. Finally, it is found that under certain network structures, where the number of connections between agents is increased, herd behaviour leads to information cascades potentially leading to the formation of speculative bubbles

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Bibliographic Info

Paper provided by Society for Computational Economics in its series Computing in Economics and Finance 2006 with number 178.

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Date of creation: 04 Jul 2006
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Handle: RePEc:sce:scecfa:178

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Related research

Keywords: Social Learning; Expectations Formation; Social Networks; Herd Behaviour; Information Contagion; volatility; structural shifts; Agent Based Models.;


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Cited by:
  1. Bell, William Paul, 2009. "Network Averaging: a technique for determining a proxy for the dynamics of networks," MPRA Paper 38026, University Library of Munich, Germany.
  2. Bell, William Paul, 2008. "Adaptive interactive profit expectations using small world networks and runtime weighted model averaging," MPRA Paper 38027, University Library of Munich, Germany.
  3. repec:pra:mprapa:37920 is not listed on IDEAS
  4. Bell, William Paul, 2008. "Adaptive Interactive Profit Expectations and Small World Networks," MPRA Paper 37924, University Library of Munich, Germany.


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