by From Asad Zaman Classical Physics, the model for modern economics, was based on the ideas of stability and permanence of astronomical orbits; see Mirowski (1992). Deeper examination of astrophysics led to the replacement of this view by big bang which gave birth to the universe, and increasing entropy, which will lead to its heat death. “Equilibrium” just appears as a temporary and local phenomenon in an evolving and chaotic universe. Complexity economics takes non-equilibrium seriously. Constantly evolving systems may never be in equilibrium and may even lack a tendency towards equilibrium. The mode of analysis required for such systems cannot be based on the kind of mathematic currently dominant in the economics profession. Complex systems theory was pioneered in the 1980s and 1990s
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from Asad Zaman
Classical Physics, the model for modern economics, was based on the ideas of stability and permanence of astronomical orbits; see Mirowski (1992). Deeper examination of astrophysics led to the replacement of this view by big bang which gave birth to the universe, and increasing entropy, which will lead to its heat death. “Equilibrium” just appears as a temporary and local phenomenon in an evolving and chaotic universe.
Complexity economics takes non-equilibrium seriously. Constantly evolving systems may never be in equilibrium and may even lack a tendency towards equilibrium. The mode of analysis required for such systems cannot be based on the kind of mathematic currently dominant in the economics profession. Complex systems theory was pioneered in the 1980s and 1990s by a small team at the Santa Fe Institute led by W. Brian Arthur. Some of the key elements of this approach to economics can be described as follows:
- Computational Aspects: It is essential to understand how closely our analytical methods correlate with our computational abilities. Just as tensor calculus enabled the discovery of relativity by Einstein, the computer power today enables us to explore consequences of behavioral assumptions far beyond the capabilities of mathematical formulae. Even the mechanics of human motion cannot be captured in formulae, but can be expressed and represented as a linked network on computers. Similarly, computers today allow us to capture and analyze dynamics of extremely complex systems.
- Complex Features: Brian Arthur et al. (1997) describe several features of complex systems which create models of types not easily accessible by conventional analytical tools and techniques. These include: read more