Economy-wide impacts of behavioral climate change mitigation: Linking agent-based and computable general equilibrium models

Leila Niamir*, Olga Ivanova, Tatiana Filatova

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

19 Citations (Scopus)
79 Downloads (Pure)


Households are responsible for a significant share of global greenhouse emissions. Hence, academic and policy discourses highlight behavioral changes among households as an essential strategy for combating climate change. However, formal models used to assess economic impacts of energy policies face limitations in tracing cumulative impacts of adaptive behavior of diverse households. The past decade has witnessed a proliferation of agent-based simulation models that quantify behavioral climate change mitigation relying on social science theories and micro-level survey data. Yet, these behaviorally-rich models usually operate on a small scale of neighborhoods, towns, and small regions, ignoring macro-scale social institutions such as international markets and rarely covering large areas relevant for climate change mitigation policy. This paper presents a methodology to scale up behavioral changes among heterogeneous individuals regarding energy choices while tracing their macroeconomic and cross-sectoral impacts. To achieve this goal, we combine the strengths of top-down computable general equilibrium models and bottom-up agent-based models. We illustrate the integration process of these two alien modeling approaches by linking data-rich macroeconomic with micro-behavioral models. Following a three-step approach, we investigate the dynamics of cumulative impacts of changes in individual energy use under three behavioral scenarios. Our findings demonstrate that the regional dimension is important in a low-carbon economy transition. Heterogeneity in individual socio-demographics (e.g. education and age), structural characteristics (e.g. type and size of dwellings), behavioral and social traits (e.g. awareness and personal norms), and social interactions amplify these differences, causing nonlinearities in diffusion of green investments among households and macro-economic dynamics.

Original languageEnglish
Article number104839
JournalEnvironmental Modelling and Software
Early online date31 Aug 2020
Publication statusPublished - 1 Dec 2020


  • UT-Hybrid-D
  • Computational economics
  • Environmental modeling
  • Grassroots dynamics
  • Soft linking
  • Upscaling
  • Behavior change


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