AIER has a long history of fostering schools of economic thought that don’t adhere to the views that currently dominate mainstream academia. One paradigm that reflects recent advances in other scientific fields but also confirms views put forward by AIER for decades is the growing discipline called complexity economics.
As mathematical modeling came to dominate academic economics in the 20th century, there was an implicit assumption that the economy tended toward equilibrium—steady states that could be neatly captured by a few equations. As Brian Arthur, a complexity economics pioneer, writes, “Where equilibrium economics emphasizes order, determinacy, deduction, and stasis, this new framework emphasizes contingency, indeterminacy, sense-making, and openness to change.” (W. Brian Arthur, “Complexity and the Economy,” 2015.) Institutions, prices, and other outcomes arise from the behavior of a complex network of individual agents, who then react to those outcomes leading to constant dynamic change in the economy. This framework, unlike equilibrium economics, allows for general intuition and a holistic view of economic systems. It also allows for quantitative techniques, such as computer simulations, that don’t require reducing economies to a clean set of equations.
Complexity economics has many potential implications for the role of government in the economy. Viewing the economy as a vast, constantly evolving network of decision-making agents provides a cautionary note against top-down, centralized government action to correct what it views as flaws in the system. One common feature of complex systems is the inherent uncertainty in any intervention in the system. However, complexity economics does not preclude a constructive role for government policy, nor does it imply that the free market will lead to an ideal, optimal outcome. Government can set the rules of the game that are most likely to foster the best bottom-up solutions. For a far more complete treatment of these ideas, see David Colander and Roland Kupers’s 2014 book, “Complexity and the Art of Public Policy.”
This view of policy and the economy echoes Friedrich Hayek’s 1945 paper, “The Use of Knowledge in Society.” Hayek argues the futility of economic decisions being made by central planners using statistical information aggregated from throughout the economy. Instead, incentives stemming from the profit motive and prices are necessary to transmit information throughout the complex economy. Hayek’s work displays a remarkable intuitive understanding of networks and complexity theory that the field is still catching up to over 70 years later.
Complexity economics also echoes ideas that AIER has put forward for decades. Our founder, Edward C. Harwood, built on the ideas of the philosopher John Dewey, focusing on experimentation and actual observed economic outcomes over intuition and theory in drawing conclusions about the economy (Frank X. Ryan, “Seeing Together,” 2011). These ideas are related to the concept of unpredictability in complex systems. New science is going a long way to confirm old ideas put forward here at AIER.