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externalities and spillovers that inl uence, shape and regulate the behaviour of individual
agents located within them (and indeed beyond). In this sense, such spatial-economic struc-
tures are not only examples of 'i rst-order' emergence (unintended spatial outcomes of
myriads of micro-actions) but also of 'second-order' emergence (whereby these same meso-
level spatial structures and arrangements - in conjunction with macro-level processes - feed
back to inl uence micro-level behaviours and actions). Explicating these spatially emergent
and spatially embedded systems of 'upward and downward causation' (Hodgson, 2004),
and their multi-scalar operation and manifestation, would seem to us to be a critical task
for a complexity-based evolutionary economic geography research agenda.
Likewise, how geographic-economic space both shapes and is shaped by the growth
and transformation of knowledge are key ingredients of any complexity-based evolu-
tionary economic geography. As we have seen, the most inl uential complexity econo-
mists argue that it is knowledge and its adaptation that makes the economy a complex
system. But we know that the spatial localisation and agglomeration of economic agents
is itself a major stimulus to the creation and circulation of knowledge: clusters, industrial
districts and cities are quintessentially 'knowledge communities' (Loasby, 1998; Maskell,
2001; Pinch et al., 2003). In this sense, the creation of new knowledge - the engine of eco-
nomic growth - is a spatially emergent ef ect, which then becomes part of the properties
of economic agents (see Plummer and Sheppard, 2006). New knowledge (and innova-
tion) typically emerges on a small scale in local contexts. But some of this new knowledge
has the capacity to stimulate widespread adoption and large-scale transformations of
the economic landscape. Conceptualising the role of geographic space in stimulating
and conditioning the emergence, dif usion and adoption of economic novelty is to our
mind a fundamental research task confronting evolutionary economic geographers. A
complexity approach necessarily focuses attention on the co-evolution of knowledge and
the economic landscape.
These are but some of the fragments of what is obviously a much larger research
agenda. Whether and how far complexity thinking can help inform the construction of
an evolutionary economic geography is as yet an open question. And as we have argued,
complexity economics is itself underdeveloped. Yet, a complexity approach does seem
to resonate with some of the central concerns of evolutionary economic geography. We
know that the economic landscape is a highly complicated system, but it is also complex,
in the specii c sense of the term developed in this chapter: it is an open, highly intercon-
nected, self-organising, emergent and adaptive system. The task is to construct an onto-
logically defensible framework based on this conception.
Notes
1.
The original Nelson-Winter draws on Lamarckian rather than Darwinian evolutionary ideas. Although
the processes of selection, mutation and inheritance are invoked not as biological metaphors but as real
economic processes, they nevertheless explicitly acknowledge that there is an analogy between bio-genetic
process and i rm dynamics.
2.
Note that we are not arguing against the use of analogies and metaphors per se. In fact, virtually all
explanatory accounts make use of both. What matters of course is the relevance and appropriateness of
the analogies or metaphors that are used. In this context, it is curious that Newtonian mechanistic analo-
gies and metaphors should have dominated mainstream neoclassical economics for so long when they are
clearly at odds with how actual socio-economic systems are constituted and develop.
3.
Elsewhere in the
Principles of Economics
,
Marshall acknowledges his debt to the writings of Herbert
Spencer, and goes on to emphasise that 'biological conceptions are more complex than those of mechan-
ics' (1930, p. xiv).
