Modelling complex systems of heterogeneous agents to better design sustainability transitions policy
Modelling complex systems of heterogeneous agents to better design sustainability transitions policy
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DOI：
10.1016/j.gloenvcha.2016.02.003
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发表时间：
2015-06
影响因子：
8.9
通讯作者：
J. Mercure;J. Mercure;H. Pollitt;A. Bassi;J. Viñuales;N. Edwards
中科院分区：
文献类型：
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作者：
J. Mercure;J. Mercure;H. Pollitt;A. Bassi;J. Viñuales;N. Edwards
本文提出了可持续性转型政策干预建模方法的根本转变，以考虑复杂性（例如，自我强化机制，如多主体相互作用产生的技术锁定）和主体异质性（例如，收入分层引起的消费者和投资行为差异）。我们首先分析了气候政策制定者面临的不确定性及其对投资决策者的影响。然后，我们确定了最常用于为可持续发展政策提供信息的基于平衡和优化的方法中的五个缺点：（i）他们的规范性，基于优化的性质，（ii）他们对代理人的完全理性的不切实际的依赖，（iii）他们无法解释代理人之间的相互影响（多智能体相互作用）和捕获相关的自我强化（正反馈）过程，（iv）它们不能代表多个解决方案和路径依赖，以及（v）它们不能正确地解释试剂的异质性。本文的目的是介绍一种基于复杂性动力学和主体异质性的替代建模方法，并探讨其在可持续发展政策的四个关键领域的应用，即（1）技术采用和扩散，（2）低碳政策的宏观经济影响，（3）社会经济系统与自然环境之间的相互作用，以及（4）政策结果的预期。随后讨论了拟议方法的实际意义，参考与上述每个领域有关的四个具体应用：运输技术的传播，低碳投资对收入和就业的影响，级联不确定性的管理，以及生物燃料政策的跨部门影响。最后，文章呼吁从根本上改变方法论，将社会经济系统的建模与气候系统的建模相结合，以综合和现实地理解可持续发展政策的影响。
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 mechanisms, such as technology lock-ins, arising from multi-agent interactions) and agent heterogeneity (e.g. differences in consumer and investment behaviour arising from income stratification). 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 (multi-agent interactions) 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 subsequently discussed by reference to four specific applications relating to each of the above areas: 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. In conclusion, 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.