Geography Reference
In-Depth Information
odological; that is to say, it has been based on the use of formal models of complex
systems drawn from the natural sciences to make claims about the nature and dynamics
of (abstract) economic landscapes, as exemplii ed by the work of Arthur, Krugman and
others. The problem with this approach is that the initiating premises, assumptions and
processes are restricted to the content of the specii c scientii c models used, and these
may not be adequate or realistic in relation to actually occurring, as opposed to hypo-
thetical abstract and model-generated, economic landscapes. In such approaches, the
characteristics of the economic landscape are thus those of the model, rather than those
that actually exist.
Our argument here is that we need to look beyond the increasingly dominant model-
ling paradigms associated with complexity, including the functional development of
appropriate computational architectures (such as multi-agent models and dynamical
systems models), to a more philosophically inclined social-ontological approach. What
precisely does it mean to talk of the economic landscape as a complex system? In what
sense is the economic landscape a meaningful complex system to which the concepts of
complexity thinking can be meaningfully applied? What does connectivity mean and
how do we distinguish partial from strong connections? These are dii cult questions. To
be analytically useful, complexity is not something that just bolts on to or can be blended
with an existing conceptual/theoretical framework to add a 'complexity perspective' or
'evolutionary perspective'. Nor is it sui cient to invoke the terminology and concepts of
complexity science without thinking through what these concepts are being applied to,
and what they mean in an economic-geographical context.
We take the view that if 'the economy' is indeed a complex system, its complexity
arises in large part precisely because it is spatially distributed and spatially embedded.
But this then behoves us to specify how this spatiality relates to complexity, both theo-
retically and empirically. We might adopt the terminology of Dopfer and Potts (2004b)
and say that geography contributes to complexity because it increases the modularity,
hierarchic depth and openness of the economy. The economy is modular because it is
made up of a very large number of functional (sub)systems that are connected to (and
interact with) one another (households, i rms, institutions, states, and so on). The com-
plexity of the economy is also a result of its hierarchic depth. That is, each (sub)system
is itself complex in its own way, and simultaneously both made up of, and a component
of, other systems: every part is a whole and every whole is a part. The economy is open
in the sense that these systems interact via innumerable networks of connections and
associations, and these connections can change. But exactly how does geographic space
inl uence the modularity, hierarchic depth and openness of the economy?
From a complexity perspective, the spatial structure and organisation of the economy
- the presence of features such as industrial districts, business clusters, cities, regional
agglomerations, networks and the like - are to be understood as emergent properties of
an economy, the unplanned meso-outcomes of the individual actions and behaviours of
numerous individual economic agents (households, i rms, institutions of various kinds,
governments). Are such emergent spatial structures and features merely outcomes? Or
are they themselves complex (sub)systems? Or are they just part of the 'environment'
within which households, i rms and other economic agents exist and function? Economic
geographers have spent considerable ef ort demonstrating that spatial structures such as
clusters, regional high-tech agglomerations, cities and the like are the source of a host of
