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EconTalk

Chaos and Complexity Economics (with J. Doyne Farmer)

Aug 26, 2024
01:05:15
Snipd AI
J. Doyne Farmer, a physicist advocating for new economic models, discusses chaos theory's role in reshaping economics. He argues that complexity economics provides better predictions than traditional theories, especially in understanding human behavior and market dynamics. Farmer emphasizes the need for agent-based modeling to improve forecasts, particularly in volatile areas like the housing market. The conversation also touches on parallels between economic predictions and weather forecasting, highlighting the unpredictable nature of human decisions.
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Quick takeaways

  • Complexity economics provides a dynamic framework for understanding human behavior in economic systems, challenging traditional utility-maximization models.
  • Agent-based modeling in complexity economics captures individual motivations and interactions, offering richer insights into market phenomena than standard theories.

Deep dives

Understanding Complexity Economics

Complexity economics applies methods from complex systems science to the field of economics, diverging from traditional models that rely on utility maximization. This approach emphasizes creating simulations to better understand economic behaviors rather than just formulating mathematical equations. A significant aspect of complexity economics is its focus on quantitative models that provide realistic predictions and detailed insights about institutions, making them applicable for policy analysis. By considering a multitude of factors influencing human behavior in real-world scenarios, like climate change and macroeconomic fluctuations, this model aims to address the complications that standard economic theories often overlook.

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