  This article proposes a fundamental methodological shift in the modelling of
policy interventions for sustainability transitions in order to account for
complexity (e.g. self-reinforcing mechanism arising from multi-agent
interactions) and agent heterogeneity (e.g. differences in consumer and
investment behaviour). We first characterise the uncertainty faced by climate
policy-makers and its implications for investment decision-makers. We then
identify five shortcomings in the equilibrium and optimisation-based approaches
most frequently used to inform sustainability policy: (i) their normative,
optimisation-based nature, (ii) their unrealistic reliance on the
full-rationality of agents, (iii) their inability to account for mutual
influences among agents and capture related self-reinforcing (positive
feedback) processes, (iv) their inability to represent multiple solutions and
path-dependency, and (v) their inability to properly account for agent
heterogeneity. The aim of this article is to introduce an alternative modelling
approach based on complexity dynamics and agent heterogeneity, and explore its
use in four key areas of sustainability policy, namely (1) technology adoption
and diffusion, (2) macroeconomic impacts of low-carbon policies, (3)
interactions between the socio-economic system and the natural environment, and
(4) the anticipation of policy outcomes. The practical relevance of the
proposed methodology is discussed by reference to four applications: the
diffusion of transport technology, the impact of low-carbon investment on
income and employment, the management of cascading uncertainties, and the
cross-sectoral impact of biofuels policies. The article calls for a fundamental
methodological shift aligning the modelling of the socio-economic system with
that of the climatic system, for a combined and realistic understanding of the
impact of sustainability policies.
