Geography Reference
In-Depth Information
a sort of unii ed theory of complexity. This has been the central thinking behind the
Santa Fe Institute programme of research on the 'science of complexity'. The aim of the
Santa Fe studies has been to explore the possibility of a formal theory of complexity - or
more precisely, a theory of 'self-organisation' - that applies equally to both natural and
social systems. Notable examples have included the work of Allen (1982, 1985, 1992) and
Arthur (1988, 1989, 1994; and Arthur et al., 1997) on social and economic-technological
systems.
Interestingly, Arthur's work in particular contained a number of applications to geo-
graphic phenomena, such as the development of urban and industrial location patterns.
Subsequent to, and somewhat similarly to Arthur's work, Krugman has used complex-
ity theory as one of the conceptual strands of his so-called 'new economic geography'
(Krugman, 1994, 1996, 1997). Following the Santa Fe
Zeitgeist
, Krugman
has
sought
to show how:
Models of self-organisation can be applied to many economic phenomena - how the princi-
ple of 'order from instability' which explains the growth of hurricanes and embryos, can also
explain the formation of cities and business cycles; how the principles of 'order from random
growth' can explain the rules that describe the sizes of earthquakes, meteorites and metropoli-
tan areas. (1996, p. vi)
The main argument underpinning Krugman's thesis is that common principles of self-
organisation can be shown to operate across all sorts of systems - physical, biological
and socio-economic - and that these principles provide a new view of how the economy
structures itself in space and time.
6
We should emphasise immediately where we agree and where we disagree with
Krugman. A survey of the literature on complexity thinking does indeed suggest that
natural, physical and social systems display certain similarities in 'complex behav-
iour', that is the emergence, under certain conditions, of self-organised complexity at a
macroscopic scale in the form of spatial patterns or temporal rhythms. But the actual
processes involved in the emergence of self-organised complexity obviously dif er as
between, say, cellular biology, the human brain, societal organisation and economic
systems. This implies that distinct limits are likely to exist to the construction of a single,
unii ed 'meta-theory' of complexity that is equally applicable to such diverse phenom-
ena. Such a theory would perhaps only be possible at a very high level of abstraction
and generalisation, which presumably is why some adherents of complexity thinking
- including the Santa Fe school, and many others (such as Krugman, 1996) - seek to
establish formal mathematical principles of complex behaviour.
7
However, it is our view
that a formal (mathematical) modelling methodology is neither necessary nor of itself
sui cient for understanding the complex behaviour of the economic landscape; evolu-
tionary processes in the social-economic sphere are not easily reduced to, nor rarely can
be adequately represented by, formal models.
8
Thus while we might share Krugman's
view that the economic landscape can be viewed as a complex evolving system, we do
not subscribe to the argument that this automatically requires the adoption of a model-
based methodological strategy. Our task here, instead, is more ontological in purpose,
namely to explore how far and in what ways some of the 'generic' aspects of evolutionary
behaviour that are held to characterise complex systems can inform how we think about
and conceptualise the economic landscape and its evolution. As in the case of borrowing
