New Books in Economics J. Doyne Farmer, "Making Sense of Chaos" (Yale UP, 2024)
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Sep 25, 2025 
J. Doyne Farmer, Director of the Complexity Economics Program at the Institute for New Economic Thinking, discusses his book, Making Sense of Chaos. He explores the shortcomings of traditional economic models and advocates for complexity economics, utilizing agent-based simulations. Farmer explains key concepts like bounded rationality and emergence, and how they can lead to more accurate predictions. He emphasizes the importance of data-first approaches and how these insights can help policymakers address pressing challenges like climate change and economic stability.
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Distinguish Risk From True Uncertainty
- Mainstream macro often treats unknowns as quantifiable 'risk' while real decisions face Knightian uncertainty.
- Models must handle unknown probabilities and unforeseen outcomes to reflect real-world decision-making.
Embed Heuristics Directly In Models
- Use heuristics explicitly in economic models rather than treating them as anomalies.
- Integrate behavioral findings into simulation rules to improve realism and predictive power.
Let Data Guide Model Building
- Physicists often start with data and build models to match patterns, contrasting economics' theory-first pedagogy.
- Exploratory data analysis complements theory and helps reveal empirical regularities worth modeling.
