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Related Experiment Videos

Policy analysis from first principles.

Scott Moss1

  • 1Centre for Policy Modelling, Business School, Manchester Metropolitan University, Manchester M1 3GH, United Kingdom. scott@cfpm.org

Proceedings of the National Academy of Sciences of the United States of America
|May 16, 2002
PubMed
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Social science research should begin with observation and problem definition. Adaptive agent models reveal markets share statistical signatures with real-world data, offering new policy analysis avenues.

Area of Science:

  • Social Sciences
  • Computational Social Science
  • Agent-Based Modeling

Background:

  • Traditional social science often lacks empirical grounding.
  • Statistical properties of market data, such as fat tails, are not well explained by conventional models.

Purpose of the Study:

  • To propose a social science methodology starting with observation and problem specification.
  • To demonstrate that adaptive agent models can replicate empirical market data characteristics.
  • To explore the implications of these findings for policy analysis.

Main Methods:

  • Analysis of sales volume and value data for various goods.
  • Development and simulation of an agent-based model with reasoning and socially embedded agents.
  • Comparison of statistical signatures (fat-tailed distributions) between simulated and real-world market data.

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Main Results:

  • Empirical data for sales distributions are commonly fat-tailed, implying infinite variance and potentially undefined means.
  • Agent-based models with reasoning and social embeddedness generate fat-tailed time series and cross-sectional data.
  • The simulated market data exhibit statistical signatures consistent with real-world fast-moving consumer goods and retail outlet data.

Conclusions:

  • Adaptive agent models with reasoning and social embeddedness possess the same statistical signatures as real markets.
  • The identified statistical signatures preclude conventional hypothesis testing and forecasting but allow for validation via domain expertise and qualitative data.
  • Adaptive agent modeling, integrated into broader procedures, offers an effective alternative for policy analysis where traditional social theory falls short.