The Model Dimensionality and Its Impacts on the Strategic and Policy Outcomes in IAMs the Findings from the RICE2020 Model

• Published in: Computational economics Vol. 62; no. 3; pp. 1087 - 1106
• Main Author: Yang, Zili
• Format: Journal Article
• Language: English
• Published: New York Springer US 01.10.2023; Springer; Springer Nature B.V
• Subjects: Analysis; Behavioral/Experimental Economics; Breakdown; Climate change; Climatic changes; Computer Appl. in Social and Behavioral Sciences; Economic Theory/Quantitative Economics/Mathematical Methods; Economics; Economics and Finance; Energy modeling; Equilibrium; Experiments; Externality; Game theory; Greenhouse gases; Math Applications in Computer Science; Mitigation; Operations Research/Decision Theory; Regions; Research subjects; Simulation; Working groups; IAM for climate change; Model comparison; The Cournot-Nash equilibrium; The Lindahl equilibrium; Modeling methodologies
• ISSN: 0927-7099; 1572-9974; 1572-9974
• DOI: 10.1007/s10614-022-10292-0

This paper studies the impacts of regional breakdowns or model dimensionality on the model’s optimal solutions. Using the United States (USA) and China (CHN) as the experimental subject, we test the various solutions related to USA and CHN, such as the Cournot-Nash equilibrium and the Lindahl equilibrium, in the RICE2020 model under three regional breakdowns. Their solutions’ invariance and variances across different model dimensionalities indicate that modeling dimensionality may play a role in the strategic interactions among the regions in GHG mitigation. The simulation results also point out the pitfalls of the model comparisons across IAMs for climate change.