Keywords
behavioral changes; energy; ABM; CGE; upscaling; empirical
Start Date
17-9-2020 2:40 PM
End Date
17-9-2020 3:00 PM
Abstract
Agent-based models (ABMs) are the key method to formalize adaptive human behavior in computational models of human-environment systems. It allows for a detailed representation of diverse behavioral strategies of actors grounded in different theories and data, explicit modeling of their learning and adaptation behavior and their social interactions driving information and innovation diffusion. However, ABMs are originally designed to be small scale. As computer science literature highlights, ABMs are difficult to scale up. While the technical part of the challenge could be resolved by more (distributed) computational power, the architectural solutions regarding heterogeneity, interactions, coordination and synchronization of actions of a much larger population are also in demand. Importantly, as ABMs scale up, it becomes insufficient to just multiply agents (e.g. households) in numbers. It implies that new institutional decisions and processes relevant at larger scales have to be modelled endogenously. This paper proposes an innovative methodological approach for scaling up behavioral changes among heterogeneous individuals regarding energy choices while tracing macroeconomic and cross-sectoral impacts of these changes. To achieve this goal, we combine the strengths of top-down computable general equilibrium (CGE) models and bottom-up ABMs. Our ABM simulates behavioral changes among households with respect to energy use and climate mitigation actions, which are grounded in theories from psychology and survey data. CGE estimates economy-wide impacts of behavioural changes through a step-wise aggregation procedure going from regional to national and EU scales. Following this approach, we investigate the dynamics of cumulative impacts of changes in individual energy use under three behavioral scenarios. We find that differences in education and age among different EU regions lead to an uneven distribution of benefits of a green economy transition. Heterogeneity among household agents and presence of social interactions amplify these differences, causing nonlinearities in diffusion of green investments among households and macro-economic dynamics
Macro scale impacts of behavioral climate change mitigation: linking agent-based and computable general equilibrium models
Agent-based models (ABMs) are the key method to formalize adaptive human behavior in computational models of human-environment systems. It allows for a detailed representation of diverse behavioral strategies of actors grounded in different theories and data, explicit modeling of their learning and adaptation behavior and their social interactions driving information and innovation diffusion. However, ABMs are originally designed to be small scale. As computer science literature highlights, ABMs are difficult to scale up. While the technical part of the challenge could be resolved by more (distributed) computational power, the architectural solutions regarding heterogeneity, interactions, coordination and synchronization of actions of a much larger population are also in demand. Importantly, as ABMs scale up, it becomes insufficient to just multiply agents (e.g. households) in numbers. It implies that new institutional decisions and processes relevant at larger scales have to be modelled endogenously. This paper proposes an innovative methodological approach for scaling up behavioral changes among heterogeneous individuals regarding energy choices while tracing macroeconomic and cross-sectoral impacts of these changes. To achieve this goal, we combine the strengths of top-down computable general equilibrium (CGE) models and bottom-up ABMs. Our ABM simulates behavioral changes among households with respect to energy use and climate mitigation actions, which are grounded in theories from psychology and survey data. CGE estimates economy-wide impacts of behavioural changes through a step-wise aggregation procedure going from regional to national and EU scales. Following this approach, we investigate the dynamics of cumulative impacts of changes in individual energy use under three behavioral scenarios. We find that differences in education and age among different EU regions lead to an uneven distribution of benefits of a green economy transition. Heterogeneity among household agents and presence of social interactions amplify these differences, causing nonlinearities in diffusion of green investments among households and macro-economic dynamics
Stream and Session
false