Geography Reference
In-Depth Information
Table 4
.
2 Beinhocker's i ve 'big ideas' that distinguish 'complexity economics' from
traditional economics
Complexity economics
Traditional economics
Dynamics
Open, dynamic, non-linear systems,
far from equilibrium
Closed, static linear systems in equilibrium
Agents
Modelled individually; agents
use inductive rules of thumb to
make decisions; have incomplete
information; are subject to errors
and biases; and learn and adapt
over time
Modelled collectively; agents use complex
deductive calculations to make decisions;
have complex information; make no errors
and have no biases; and have no need
for learning and adaptation (are already
perfect)
Networks
Explicitly models interactions
between individual agents; networks
of relationships change over time
Assumes agents only interact indirectly
though market mechanisms
Emergence
No distinction between micro- and
macro-economics; macro patterns
are emergent result of micro-level
behaviours and interactions
Micro- and macro-economics remain
separate disciplines
Evolution
The evolutionary process of
dif erentiation, selection and
amplii cation provides the system
with novelty and is responsible for
growth in order and complexity
No mechanism for endogenously creating
novelty or growth in order and complexity
Source:
Beinhocker (2006, p. 97).
The problem, however, is that dif erent economists approach the idea of 'complexity'
in quite dif erent ways. According to Perona (2004), two sharply divergent versions of
'complexity economics' can be distinguished: 'theoretic' and 'ontic'.
11
The term 'theo-
retic' refers to those versions of complexity economics that treat non-linearity, instabil-
ity, self-organisation, emergence, adaptive behaviour and the like, as features of the
mathematical
model
, the equation or system of equations, used to
represent
a particular
type of reality. Perona contrasts this to 'ontic' versions of complexity economics, that
is where complexity is seen as a property of real economic systems and phenomena.
Though we agree with the general thrust of Perona's argument, to our mind the label
'theoretic' in this context is not altogether helpful, since not all theories are cast in terms
of mathematical deductive models; and, some might argue, what is an ontology if not a
particular theory of how the world is structured? What Lawson (2003) elsewhere refers
to as a distinction between 'scientii c-ontological' and 'social-ontological' approaches to
complexity might be more appropriate, where the former is concerned with the nature
or structure of entities posited or presupposed by some scientii c model, and the latter
is concerned with the nature of socio-economic existence apart from any such model.
Arguably, the key distinction is between epistemological (methodological) and onto-
logical approaches to complexity. In complexity theory, epistemology has dominated
over ontology, with the latter often reduced to the former (in the manner discussed
by Lawson). The assumption has been that the same formal (thermodynamic and
