The power of bridging decision scales
Model coupling for advanced climate policy analysis
Tatiana Filatova (TU Delft - Policy Analysis, TU Delft - Multi Actor Systems)
Joos Akkerman (TU Delft - Multi Actor Systems, TU Delft - Policy Analysis)
Francesco Bosello (Fondazione Centro Euro-Mediterraneo sui Cambiamenti Climatici, Ca' Foscari University Venice)
Theodoros Chatzivasileiadis (TU Delft - Multi Actor Systems, TU Delft - Policy Analysis)
Ignasi Cortés Arbués
Amineh Ghorbani (TU Delft - System Engineering, TU Delft - Multi Actor Systems)
Olga Ivanova (Planbureau voor de Leefomgeving)
Nina Knittel (Karl-Franzens-Universitat Graz)
Jan Kwakkel (TU Delft - Multi Actor Systems, TU Delft - Policy Analysis)
Francesco Lamperti (Scuola Superiore Sant’Anna, Fondazione Centro Euro-Mediterraneo sui Cambiamenti Climatici)
Nicholas R. Magliocca (TU Delft - Policy Analysis)
Giacomo Marangoni (TU Delft - Multi Actor Systems, TU Delft - Policy Analysis, Fondazione Centro Euro-Mediterraneo sui Cambiamenti Climatici)
Stefan Nabernegg (Karl-Franzens-Universitat Graz)
Anton Pichler (WU Wien)
Adrian Poujon
Karolina Safarzynska (University of Warsaw)
Alessandro Taberna (TU Delft - Multi Actor Systems, Fondazione Centro Euro-Mediterraneo sui Cambiamenti Climatici, TU Delft - Policy Analysis)
Mariësse A.E. van Sluisveld (Planbureau voor de Leefomgeving)
Liz Verbeek (TU Delft - Multi Actor Systems, TU Delft - Policy Analysis)
Taoyuan Wei (Center for International Climate and Environmental Research - Oslo (CICERO))
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Abstract
Climate policy faces increasingly complex challenges that span multiple human decision scales in nature-society systems. Contemporary climate policy models, while valuable and increasingly versatile in handling spatial and temporal scales, struggle to capture interacting multiscale decisions on the socioeconomic side. This perspective draws attention to the power of coupling among different modeling families, taking integrated assessment models (IAM), computable general equilibrium models (CGE), and agent-based models (ABM) as examples. Recent computational advances, maturity of models, availability of data, and interdisciplinary expertise make model coupling an increasingly feasible, effective, and useful tool for climate policy analysis. We examine the unique contributions of each modeling approach, highlight synergies from uniting their strengths, and discuss alternatives to and conditions for coupling. In addressing methodological challenges, we present examples of effective coupling of IAM-ABM-CGE, emphasizing the importance of maintaining model integrity while enhancing policy relevance. By bridging human decision scales and leveraging complementary strengths, coupled models can provide nuanced insights into climate-economy interactions, ultimately supporting effective and equitable-not just efficient and optimal-climate policies.
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