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For Potts, the ontology of methodological individualism, social atomism and equi-
librium of traditional economics is replaced in complexity economics by an ontology of
'connectivity':
Generally connections are specii c direct relationships between elements and are ubiquitous in
the economic system. They exist in the structure of interdependencies and interactions between
agents. They exist in the modalities of technology and the forms of organisation and compe-
tence. They exist as contracts. They exist in the structure of decision rules and the way that
information is processed, In all such events, the dynamics of economic systems can be seen to
occur most in the space of connections. (Potts, 2000, p. 3)
Potts goes further and suggests that knowledge in all of its multifarious forms is in fact
about connection. For Potts, as for many evolutionary economists, it is the growth of
knowledge that drives the process of economic evolution (Foster, 1993, 1994, 1997;
Metcalfe, 1997, 1998; Metcalfe and Foster, 2004). Similarly, Foster pieces together a
vision of evolutionary economics based not on biological analogy, but on principles of
complex self-organisation in which knowledge plays a formative role: 'economic self-
organisation involves acquired energy and acquired knowledge, which in combination,
yield creativity in economic evolution' (Foster, 1997, p. 444). According to such authors,
the structure of knowledge is a structure of connections, and the various instances
of knowledge - such as technology, routines, habits, competences and the like - are
instances of specii c connections, that is of networks, that seem to work in a particular
environment. Thus, from this perspective, economic evolution - and hence complexity
economics - is about the emergence and evolution of multiple connections in the form
of networks.
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However, notwithstanding the ef orts of Potts, Foster and others to forge a 'hetero-
dox' complexity economics, for the most part much of complexity thinking in economics
commits the conl ation referred to by Lawson, that is it reduces the ontological to the
epistemological. The economy is taken as constituted by scale-invariant laws or dynam-
ics that apply not just to the economy but to all sorts of complex systems: self-organising
systems reach a state of spontaneous order and then 'follow a dynamic pattern that is
lawful in its own right' (Batten, 2001, p. 94). Typically these laws and dynamics are
identii ed by the presence of behavioural and statistical signatures or hallmarks such as
power laws, punctuated equilibria, and phase transitions, and attractors (see Krugman,
1994).
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In many cases, it is the belief in these universal complex dynamics that is used to
justify both mathematical formalism and, in an economic context, agent-based computer
simulations.
The belief that dif erent types of complex system all show signature behaviours
and common emergent patterns runs through all versions of complexity economics to
some degree. Yet, such a conceptualisation overlooks the obvious but important fact
that social and economic systems show dif erent and distinctive forms of complexity:
social, spatial and historical context shape the nature of the economy and its behaviour.
According to Foster (2005), all economic systems are 'third-' or 'fourth-order' complex.
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In 'third-order' systems individual agents modify their environments to increase access
to energy and resources, reduce their ef ort costs, or seek out free information to increase
their knowledge. In 'fourth-order' complex systems individual agents form beliefs
about the beliefs of others (collective understandings) that are critical for their survival.
