This post emerges from my puzzling over the overlap between Hayek’s neoliberal critique of attempts to model complexity well enough to make predictions and economic policy and my view that “knowledge, plans, and action [have to] be continually reassessed in response to developments — predicted and surprising alike” (as described in a 2011 post).
The now-widespread invocation of resilience in policy arenas is traced by Walker and Cooper (2011) to the perspectives on Adaptive Environmental Management of ecologist C.S. Holling (Gunderson et al. 1995). Holling was an early skeptic of the value of models that make confident predictions about human-environmental-resources systems, such as those of The Limits to Growth (Meadows and Meadows 1972). Walker and Cooper (2011, 144) draw attention to the uncanny similarities of the perspectives of Holling and followers of the neo-liberal economist Friedrich Hayek, especially in “their pessimism about the management of complex systems according to predictive models.” Given the differences in the social implications they and I draw from a view that ecological and social complexity is not amenable to predictive modeling, the puzzle is how to justify one view over another?
As Mirowski (2009) explains, although the “neo-liberal thought collective” that has built on Hayek continues to evolve and tussle over tensions or contradictions, there is a common thread: the unfettered market knows best. This conviction does not translate to anti-government libertarianism. Instead, neo-liberalism requires involvement in politics or even control of the State in order to prevent or undo interference in markets by governments that want to operate as if policy makers and their economic models could process information better than the market.
Natural selection lies at the center of Hayek’s thinking: “We understand now that all enduring structures above the level of the simplest atoms, and up to the brain and society, are the results of, and can be explained only in terms of, processes of selective evolution…” Hayek (2011, 158). This is a progressive process; moreover, whatever it is that selective evolution increases, it does it blindly, without supervision. In such a Lagrangian (or Euler-Lagrangian) process, the action of a system moves it inexorably towards some optimum value. Three shortcomings strike me here. First, in an adaptive landscape as depicted in evolutionary theory, a biological population can find itself, so to speak, on the top of a hill looking up at a mountain. Disruptions have to occur if a population is not to get stuck at such a merely local optimum. Extending this picture to economics and society, there then has to be group deciding that it knows when to disrupt and how.
A second, more fundamental problem is that complex systems elude predictive models precisely because they are unlike classical mechanics. They exhibit characteristics such as small changes in initial conditions leading to qualitative differences in outcome, new structures emerging from the interaction of previous elements or structures, and hysteresis, which means that the pathway to a given state cannot be rewound in the other direction (Waldrop 1992). Complex systems cannot be managed following some predictive models, but neither can they be guaranteed to achieve some optimal, even locally optimal, state just because they are products of processes of selective evolution.
The third shortcoming of Hayek’s reliance on selective evolution is evident once it is acknowledged that all evolution occurs in some ecological context. Traditionally, the focus of evolutionary theory rests on genetics, differential representation of characters, and individual populations, often with the assumption that the ecological context is static or, if transient, regularly reoccurs (Taylor 2001). The structure and dynamics of evolution’s ecological context have not been well integrated into evolutionary theory (but see Darwin 1859, 60-79). It may well be hard to conceptualize and theorize adaptation to some environment that is not static or regular. Yet, to the extent that ecological context in which evolution occurs is the kind that researchers find hard to manage according to predictive models, evolutionary theory needs to explain how organisms make their living and reproduce in it—indeed, how they have done so for almost four billion years. In short, Hayekians, if they are to be consistent, cannot rely on selective evolution as an optimizing, progressive process to justify their neo-liberal rejection of government involvement in shaping the economy.
Darwin, C. (1859 ). On the Origin of Species. Cambridge, MA: Harvard University Press.
Gunderson, L. H., C. S. Holling, et al. (1995). “Barriers broken and bridges built: A synthesis”. Pp. 489-532 in Barriers and Bridges to the Renewal of Ecosystems and Institutions. L. H. Gunderson, C. S. Holling and S. S. Light (Eds.) New York: Columbia University Press
Hayek, F. (2011). Law, Legislation and Liberty, Volume 3: The Political Order of a Free People. Chicago: University of Chicago Press.
Meadows, D., D. Meadows, et al. (1972). The Limits to Growth. New York: Universe Books.
Mirowski, P. (2009). “Postface: defining neoliberalism”. Pp. 414-455 in The road from Mont Pelerin: The making of the neoliberal thought collective. P. Mirowski and D. Plehwe (Eds.) Cambridge, MA: Harvard University Press
Taylor, P. J. (2001). “From natural selection to natural construction to disciplining unruly complexity: The challenge of integrating ecological dynamics into evolutionary theory”. Pp. 377-393 in Thinking About Evolution: Historical, Philosophical and Political Perspectives. R. Singh, K. Krimbas, D. Paul and J. Beatty (Eds.) Cambridge: Cambridge University Press
Waldrop, M. M. (1992). Complexity: The Emerging Science at the Edge of Order and Chaos. New York: Simon and Schuster.
Walker, J. and M. Cooper (2011). “Genealogies of resilience: From systems ecology to the political economy of crisis adaptation.” Security Dialogue 42: 143-160.