Nonlinear Economics
Leading economists in the 1940s and 1950s were determined to turn economics into a precise science (Waldrop1994: 24). Their main aim was to use science, perceived within a strictly linear framework, to bring order, predictability and control into the study and practice of economics. The principle of diminishing returns was the cornerstone of their rationale. They implicitly believed that economic events create their own negative feedback, which stablises the economy at or near equilibrium. In short, the economic system is assumed to be linear.
Several economists, notably Georescu-Roegen of Vanderbilt University and Brian Arthur from Stanford University, advocated a shift to a nonlinear framework during the 1970s, 1980s and 1990s. Arthur argued that increasing returns described actual economic events more accurately than diminishing returns. In that nonlinear view of economics, positive feedback is seen as the mechanism that could magnify minor fluctuations into major upheavals.
Spreading Ripples
These initial concerns spread to a wider circle of social science disciplines. Byrne maintained that societies behave as nonlinear complex systems. He envisioned a strong link between realism and complexity, and went on to suggest that this combination was fatal to positivism, which assumes total mastery over nature is possible, and to postmodernism, which rejects grand narratives and advocates in essence social inaction.
The above shift in viewpoint is also evident in international politics, as argued by Jervis for instance, and business organisation, as advocated by Stacey. Similarly, research by Rihani in the study and practice development led him to conclude that nations behave, and therefore develop, as Complex Adaptive Systems.
Moreover, it is interesting to note that social scientists now regularly speak of interactions, emergent properties and evolutionary change, expressions that are common in the language of complex systems theory, even when they are not aware of the theoretical roots of these terms. In short, the shift to nonlinearity is underway. The need now is to consider the shift in more explicit terms and to analyse the practical implications of of adopting a nonlinear paradigm that treats socio-economic processes as evolving complex systems.
Complexity and Healthcare
Healthcare is the latest field in which complexity has emerged as a useful analytical tool. Because of its late arrival in this instance, complexity is being applied in a sensible manner. Authors regularly point out that within the healthcare arena there are sectors where linear methods are appropriate and sectors where a shift to complexity might be more effective. The British Medical Journal (BMJ) published a series of introductory articles on this topic in the early-2000s. This was followed by a number of excellent books (published by Radcliffe, see below) that dealt with different aspects of the issue. Similar trends are evident in other countries.
Further Reading
Arthur, W. B. (1990) ‘Positive Feedback in the Economy’, Scientific American, February: 80-85.
Arthur, W. B. (1994) Increasing Returns and Path Dependence in the Economy, Ann Arbor: University of Michigan Press.
Byrne, D. (1998) Complexity Theory and the Social Sciences, London: Routledge.
Day, R. H. (1994) Complex Economic Dynamics: An Introduction to Dynamical Systems and Market Mechanisms, Massachusetts: MIT Press.
Holt, T. A. (ed.) (2004) Complexity for Clinicians, Oxford: Radcliffe.
Jervis, R. (1999) Systems Effects: Complexity in Political and Social Life, Princeton: Princeton University Press.
Kernick, D. (ed.) (2004) Complexity and Healthcare Organisation, Oxford: Radcliffe.
Ormerod, P. (1994) The Death of Economics, London: Faber and Faber.
Ormerod, P. (1998) Butterfly Economics, London: Faber and Faber.
Rihani, S. (2002) Complex Systems Theory and Development Practice: Understanding Non-linear Realities, London: Zed Books.
Sweeney, K. and F. Griffiths (eds.) (2002) Complexity and Healthcare, Oxford: Radcliffe.