Complexity economics
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Complexity economics is the application of complexity science to the problems of economics. It is one of the four C's of a new paradigm surfacing in the field of economics. The four C's are complexity, chaos, catastrophe and cybernetics. This new mode of economic thought rejects traditional assumptions that imply that the economy is a closed system that eventually reaches an equilibrium. Instead, it views economies as open complex adaptive systems with endogenous evolution. Complex systems do not necessarily settle to equilibrium — even ideal deterministic models may exhibit chaos, which is distinct from both random (nondeterministic) and analytic behavior.
Complexity economics rejects many aspects of traditional economic theory. The mathematic models used by traditional economics were copied from early models of thermodynamics. These mathematic models of economics were solely based on the first law of thermodynamics, equilibrium. Later, the second law of thermodynamics, entropy, was discovered. Proponents of complexity economics claim that traditional economic models never adapted to the latter discovery and thus remain incomplete models of reality. However, the concept of "entropy" introduced by Boltzmann's statistical thermodynamics, and developed in 1949 by C. Shannon & W. Weaver as "information uncertainty" associated with any probability distribution, has been used at least since 1988 to formulate the important concepts of organization and disorder, viewed as basic state parameters, in describing/simulating the evolution of complex systems (including economic systems). As to the practicability of theoretical instruments, there is also a crucial difference to allow for: traditional economics was conceived before computers had been invented. Computational simulations have made it possible to demonstrate macro-level rules using only micro-level behaviors without assuming idealized market actors. For example, Pareto's law can be demonstrated to arise spontaneously.
Complexity economics is built on foundations which draw inspiration from areas such as behavioral economics, institutional economics, Austrian economics, and evolutionary economics. Complexity incorporates components from each of these areas of economic thought, though the complex perspective includes many more characteristics to describe a dynamic system such as emergence, sensitive dependence on initial conditions, red queen behavior, and complex systems usually incorporate a selection mechanism as described by most general evolutionary models. There is no widely accepted specific definition for complexity as it pertains to economic systems. This is largely due to the fact that the field as a whole is still under construction.
[edit] Behavior of complex systems
Brian Arthur, Steven N. Durlauf, and David A. Lane, of the Santa Fe Institute in their introduction to The Economy as an Evolving Complex System II define six features of complex systems that have presented significant trouble for traditional mathematics.
- Dispersed Interaction — What happens in the economy is determined by the interaction of many dispersed, possibly heterogeneous, agents acting in parallel. The action of any given agent depends upon the anticipated actions of a limited number of other agents and on the aggregate state these agents co-create.
- No Global Controller — No global entity controls interactions. Instead, controls are provided by mechanisms of competition and coordination between agents. Economic actions are mediated by legal institutions, assigned roles, and shifting associations. Nor is there a universal competitor—a single agent that can exploit all opportunities in the economy.
- Cross-cutting Hierarchical Organization — The economy has many levels of organization and interaction. Units at any given level behaviors, actions, strategies, products typically serve as "building blocks" for constructing units at the next higher level. The overall organization is more than hierarchical, with many sorts of tangling interactions (associations, channels of communication) across levels.
- Continual Adaptation — Behaviors, actions, strategies, and products are revised continually as the individual agents accumulate experience—the system constantly adapts.
- Perpetual Novelty Niches — These are continually created by new markets, new technologies, new behaviors, new institutions. The very act of filling a niche may provide new niches. The result is ongoing, perpetual novelty.
- Out-of-Equilibrium Dynamics — Because new niches, new potentials, new possibilities, are continually created, the economy operates far from any optimum or global equilibrium. Improvements are always possible and indeed occur regularly.
[edit] Comparison with classical economics
The table below illustrates the differences between the complexity perspective and classical economics. Eric Beinhocker proposes five concepts that distinguish complexity economics from traditional economics. The first five categories are Beinhocker's synthesis, the last four are from W. Brian Arthur as reprinted in David Colander's The Complexity Vision.
| Complexity Economics | Traditional Economics | |
|---|---|---|
| Dynamic | Open, dynamic, non-linear systems, far from equilibrium | Closed, static, linear systems in equilibrium |
| Agents | Modelled individually; use inductive rules of thumb to make decisions; have incomplete information; are subject to errors and biases; learn to adapt over time; heterogeneous agents | Modelled collectively; use complex deductive calculations to make decisions; have complete information; make no errors and have no biases; have no need for learning or adaptation (are already perfect), mostly homogeneous agents |
| Networks | Explicitly model bi-lateral interactions between individual agents; networks of relationships change over time | Assume agents only interact indirectly through market mechanisms (e.g. auctions) |
| Emergence | No distinction between micro/macro economics; macro patterns are emergent result of micro level behaviours and interactions. | Micro-and macroeconomics remain separate disciplines |
| Evolution | The evolutionary process of differentiation, selection and amplification provides the system with novelty and is responsible for its growth in order and complexity | No mechanism for endogenously creating novelty, or growth in order and complexity |
| Technology | Technology fluid, endogenous to the system | Technology as given or selected on economic basis |
| Preferences | Formulation of preferences becomes central; individuals not necessarily selfish | Preferences given; Individuals selfish |
| Origins from Physical Sciences | Based on Biology (structure, pattern, self-organized, life cycle) | Based on 19th-century physics (equilibrium, stability, deterministic dynamics) |
| Elements | Patterns and Possibilities | Price and Quantity |
[edit] References
- Santa Fe Institute Birthplace of complexity science
- Beinhocker, Eric D. The Origin of Wealth: Evolution, Complexity, and the Radical Remaking of Economics. Boston, Massachusetts: Harvard Business School Press, 2006.[1]
- What Should Policymakers Know About Economic Complexity (PDF) Summary of key ideas in complexity economics
- Colander, David. The Complexity Vision; The Teaching of Economics. ISBN:1-84064-252-1
- Brian Arthur, Steven Durlauf, David A. Lane. Introduction: Process and Emergence in the Economy. The Economy as an Evolving Complex System II. Addison-Wesley, Reading, Mass., 1997.
http://www.santafe.edu/~wbarthur/Papers/ADLIntro.html
- Ludovico, Mario, L'evoluzione sintropica dei sistemi urbani, (Syntropy in the Evolution of Urban Systems), Bulzoni, Roma (Italy) 1988 & 1991 - English summary in:
http://www.mario-ludovico.com/pdf/syntropy.pdf
