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This article proposes a fundamental methodological shift in the modelling ofpolicy interventions for sustainability transitions in order to account forcomplexity (e.g. self-reinforcing mechanism arising from multi-agentinteractions) and agent heterogeneity (e.g. differences in consumer andinvestment behaviour). We first characterise the uncertainty faced by climatepolicy-makers and its implications for investment decision-makers. We thenidentify five shortcomings in the equilibrium and optimisation-based approachesmost frequently used to inform sustainability policy: (i) their normative,optimisation-based nature, (ii) their unrealistic reliance on thefull-rationality of agents, (iii) their inability to account for mutualinfluences among agents and capture related self-reinforcing (positivefeedback) processes, (iv) their inability to represent multiple solutions andpath-dependency, and (v) their inability to properly account for agentheterogeneity. The aim of this article is to introduce an alternative modellingapproach based on complexity dynamics and agent heterogeneity, and explore itsuse in four key areas of sustainability policy, namely (1) technology adoptionand 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 theproposed methodology is discussed by reference to four applications: thediffusion of transport technology, the impact of low-carbon investment onincome and employment, the management of cascading uncertainties, and thecross-sectoral impact of biofuels policies. The article calls for a fundamentalmethodological shift aligning the modelling of the socio-economic system withthat of the climatic system, for a combined and realistic understanding of theimpact of sustainability policies.

Modelling complex systems of heterogeneous agents to better design sustainability transitions policy