Relationships among the Groups
Broadly speaking, the first group will discuss the theoretical foundations of an improved synthesis of evolutionary and complex systems theory. The other groups will explore implications of the improved synthesis to socioeconomic systems at three levels: micro (individual agent behavior), meso (institutions), and macro (economies). A sampling of societal issues that can be addressed include:
- Design features that improve the efficacy of single groups.
- How single groups combine to create larger-scale socioeconomic units (e.g., cities, corporations, nations, global systems)
- Valid and invalid formulations of the invisible hand concept.
- How can societies acquire and develop “good institutions” (and “good” cultures within institutions) that promote political stability and economic growth?
- Quality of Life from an evolutionary and complex systems perspective.
- Human attentional processes and the influence of media on the economy.
- How do human nature and cultural evolution interact in shaping individual preferences?
- Under what conditions are regulatory systems within and across levels of a multi-tier social organization functional or dysfunctional?
- What incentives are motivating, beyond monetary incentives, and when are monetary incentives counterproductive?
Group 1: Challenges in Integrating Complexity and Evolution
The physicist and Nobel laureate Murray Gell-Mann is reputed to have said “Can you imagine how difficult physics would be if atoms could think?” This statement captures the nature of complex economic systems. The lower-level units of the system—individuals and organizations—are complex in their own right, even before the complexity that results from their interactions at the level of the economic system (Beinhocker 2006). Agents that are products of genetic or cultural selection possess a very special kind of complexity that is fitness-enhancing based on the selection criteria. Systems of adaptive agents are unlikely to be adaptive at the systemic level unless they are the product of system-level selection. Somehow, models of complex economic systems must capture the essential details while remaining tractable. To understand the challenges of integrating complexity and evolution, case studies of some of the most advanced current research programs will be presented in the background papers to this group: (a) models of economic growth and innovation; (b) models of segregation in viscous and multi-group populations; (c) evolutionary modeling in biological and social systems; and (d) complex dynamics of financial markets. These case studies will help us derive generalities about the challenges of integrating complexity and evolution.
Group 2: Evolutionary Behavioral Economics
A currently vibrant area of economics is behavioral economics, which departs significantly from orthodox theory: It grounds economic theory on more realistic assumptions on human preferences and cognitive abilities as revealed by the choices they actually make, or “Homo sapiens, not Homo economicus,” as Thaler and Sunstein (2008) put it; it also conducts empirical research and experiments to better understand human preferences and abilities in order to inform theory. A long list of “anomalies” and “paradoxes” have been found in this research that are, however, only anomalous and paradoxical against the background of orthodox theory, which is basically restricted to axioms of consistency of choices. Evolutionary theory has more to say on human behavior. It can help to identify sources of “mismatch” between human genetic dispositions and behavior that is adequate in the sense of social rationality. Likewise, the complex social dynamics of preference and opinion formation that sometimes haunt collective human behavior into misconduct (e.g. under forms of “herd behavior”) need to be understood with their roots in evolved dispositions at the level of information processing and preference formation.
This group will attempt to provide a foundation for understanding such features of human behavior in the domain of economics by adopting an evolutionary and complex systems perspective. It will also interface with the Group 1 by clarifying the properties of the lowest-level agents (individuals) of multi-tier human socioeconomic systems, but will also emphasize the idea that aggregate behavior, which bears little relation to the behavior of any individual, may emerge from the interaction between these individuals. An especially important task for this group is to clarify the role that cultural evolution plays in shaping the preferences, abilities and norms of individual agents, which limits the set that can be called culturally universal. Special attention will be given to: (a) proximate mechanisms of individual behavior (neurological, endocrinological, and physiological); (b) human nature at the individual level with a focus on preferences; and (c) how preferences and norms contribute to the functioning of small groups.
Group 3: Evolution of Institutions
Human social institutions are intermediate levels of functional organization in large-scale human socioeconomic systems. They are composed of individual agents and social groups, and in turn become lower-level units of large-scale societies comprising multiple institutions. Social institutions are products of cultural evolution and their histories cannot be ignored. For example, why are some nations rich and others poor? Research suggests that economic development today has deep historical roots. Rival hypotheses focus on the role of geography, institutions, and technology in explaining the variation in the ability of different human societies to nurture productive economies. Because institutions and technologies are cultural elements, we can profitably study them from the point of view of cultural evolution. This means not only formulating theories in evolutionary terms, but also using historical data to test theories in the same way that evolutionary biologists use the paleontological record.
Another puzzle is: Why have complex societies, with elaborate governance structures and extensive division of labor, taken over Earth? What is it about complexity that makes it adaptive?
This group is charged with developing a clear set of rival theories, delineating predictions that theories make, and specifying what sort of historical data can be used to test these predictions empirically. It will interface with the other two groups by addressing intermediate levels of functional organization in large-scale socioeconomic systems. Special attention will be given to: (a) the long-term evolution of economic and social institutions; (b) what makes some institutions more adaptable and resilient to change than others; (c) the cultural evolution of markets; and (d) the cultural evolution of private property norms.
Group 4: The Adaptive Management of Complex Systems
Complex systems are inherently difficult to predict. Weather provides a classic example: it is a complex physical system that can only be forecasted with the help of enormous inputs of real-time data and an array of computer simulation models that are tested against each other. Complex human socioeconomic systems are no different, calling for an experimental and forecasting approach to policy formulation. As Bernanke, the chairman of the Federal Reserve Board, stated: “I just think tht it is not realistic to think that human beings can fully anticipate all possible interactions and complex developments. The best approach for dealing with this uncertainty is to make sure that the system is fundamentally resilient and that we have as many fail-safes and back-up arrangements as possible” (Intl. Herald Tribune, May 17, 2010).
The best that theory can do is outline plausible alternatives, which must be tested in real-world systems. This approach is already being developed in a number of contexts, such as the management of ecological systems, where it is referred to as “adaptive management” (e.g., Allan and Stankey 2009; Swenson 2010). This group will formulate the concept of “adaptive management” in general terms and expand the number of contexts for its application. It will interface with the other three groups by creating a framework for theory development and empirical research on a diversity of real-world complex systems. Special attention will be given to: (a) case studies of adaptation and maladaptation from the past; (b) shaping innovation ecosystems; (c) incorporating complexity into policy-making; and (d) adaptive management of disasters.
Top of page
No comments:
Post a Comment