Excerpt

In 1987, ten economists and ten natural scientists gathered at the Santa Fe Institute (SFI) for a ten-day workshop to explore a provocative idea: Could the global economy be understood as an evolving complex system? Few could have anticipated the significance of this meeting in igniting the development of a brand-new research field, now known as complexity economics. In reaching beyond equilibrium formulations to instead analyze the economy as an evolutionary system shaped by the interactions of diverse, adaptive and boundedly rational agents, the field sought to offer a more dynamic, realistic, and empirically grounded approach for understanding economic behavior. This shift in perspective would prove transformative, opening new ways to understand everything from financial crises to technological change, to inequality and economic development.

What is Complexity Economics?

Complexity economics draws from the science of complex systems to understand the economy as an adaptive system where macro-level patterns emerge from the interaction of many diverse agents, rather than being imposed from above or derived from representative agents. The field shares with modern economics an increasingly empirical orientation but draws on interdisciplinary tools from physics, biology, computer science, and network theory to study economic phenomena across multiple scales and time scales simultaneously. For instance, complexity economists pioneered the use of network analysis to map financial contagion, trace supply chain vulnerabilities, and understand how countries’ productive capabilities shape their development paths. This empirical focus extends to uncovering universal patterns like power-law distributions in firm sizes, growth rates, and wealth: regularities that emerge across diverse economic contexts and can be explained through bottom-up mechanisms rather than top-down assumptions.

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