Advancing Sustainable Development in OECD Countries: Carbon Emission Efficiency, Growth–Emission Decoupling, and Digital–Structural Transformation

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Abstract
Advancing sustainable development requires reconciling economic growth with carbon reduction. This study investigates carbon emission efficiency (CEE), growth–emission decoupling, and digital–structural transformation in 35 early OECD member countries from 1995 to 2023. It combines the IGT decoupling model, a three‐stage DEA framework using the Super‐EBM model, the GML index, and truncated regression to evaluate decoupling patterns, static and dynamic CEE, and the drivers of low‐carbon transition. The results show that OECD countries have generally shifted from relative toward absolute decoupling, indicating progress in separating economic expansion from carbon emissions. After controlling for external environmental factors and random noise, third‐stage CEE values are consistently higher than first‐stage estimates. Income‐based heterogeneity is evident: very high‐income and high‐income OECD countries generally perform better, while several lower‐income members also show strong managerial efficiency after adjustment. Dynamic GML results confirm that most OECD countries have improved their low‐carbon transition performance over time. The truncated analysis indicates that demographic scale negatively affects CEE, whereas artificial intelligence and service‐sector expansion significantly enhance efficiency. These findings highlight the importance of AI‐enabled innovation and service‐oriented industrial upgrading for sustainable low‐carbon development in OECD countries. The study offers evidence‐based guidance for economies seeking to align digital transformation, structural change, and climate objectives effectively.
Funding Information
  • National Natural Science Foundation of China (72574236)

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