How can computable general equilibrium models serve low-carbon policy? A systematic review

• Published in: Environmental research letters Vol. 18; no. 3; pp. 33002 - 33017
• Main Authors: An, Kangxin, Zhang, Shihui, Zhou, Jiaxin, Wang, Can
• Format: Journal Article
• Language: English
• Published: Bristol IOP Publishing 01.03.2023
• Subjects: Carbon; computable general equilibrium; Demand analysis; Economic analysis; Economic impact; Economic models; Economics; Energy policy; Environmental impact; Environmental impact assessment; Environmental policy; impact; Impact analysis; low-carbon policy; Optimization; Policy analysis; Policy research; Systematic review
• ISSN: 1748-9326; 1748-9326
• DOI: 10.1088/1748-9326/acbbe2

Computable general equilibrium (CGE) models have been widely employed in economic, social, and environmental impact assessments for low-carbon policies. As net-zero transition has become a global trend, it is crucial to conduct a systematic review of how CGE models serve low-carbon policies. This review examined 1002 studies published between 2001 and 2021, revealing the application of CGE models in low-carbon policy analysis by researchers in 51 countries, including the United States, China, Western Europe, Japan, and Australia, while studies in Latin America, Central Asia and Eastern Europe are limited. Climate targets, carbon pricing, and energy policy are the main policy focuses of CGE analysis, while land policy, demand-side actions, and several other policies are less studied. In addition, CGE analysis generally focuses on the economic impacts of carbon reduction, with a growing amount of attention on social and environmental consequences. The structure, database, and model coupling techniques of CGE models are becoming more complex in order to serve the increasingly multifaceted and diverse policy study purposes. This study provides a comprehensive overview of the research trends of CGE studies on low-carbon policies, thus improving our understanding on low-carbon policies, multiple impacts, and CGE models. We also identify the gaps and potential cutting-edge techniques of current low-carbon policy research. Future work should improve the capacity of CGE models to simulate actual ‘second-best’ policies, provide feedback of complex impacts on policy optimization, and enhance dynamic mechanisms on structural change.