Study on regional carbon emission efficiency based on SE-SBM and geographic detector models

Yuan Zhang and Xiangyang Xu ()
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Yuan Zhang: Qingdao Technical College
Xiangyang Xu: Qingdao Technical College

Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, 2025, vol. 27, issue 5, No 31, 10569-10591

Abstract: Abstract With the rapid development of information technology, achieving a low-carbon economy through digital analysis has become a top priority. The achievement of this goal is crucial for effective and targeted improvement of carbon emission efficiency. Based on statistical data from Chinese provinces, this paper constructs a super-efficiency SBM (SE-SBM) model for 30 provinces and eight economic regions, respectively. Secondly, combined with the Malmquist (ML) and Theil index, this paper discusses the dynamic evolution and regional carbon. Finally, use a geographic detector model to identify the main driving factors affecting regional carbon emission efficiency. The increase in the technical progress index (TPC) brings about an enhancement in the ML index. The inter-regional difference contributes most principal. The top three driving factors are energy consumption, electricity consumption, and per capita GDP, and the impact of green development level shows a gradually increasing trend. This article analyzes the differences and causes of carbon emission efficiency in different aspects from multiple perspectives by optimizing the model. It not only decomposes the dynamic evolution trend of the differences but also accurately identifies the different components of the differences, which helps to propose targeted measures to achieve effective carbon emission reduction in different regions, thereby helping to achieve China’s overall development goals.

Keywords: Carbon emissions efficiency; Driving factors; SE-SBM model; ML index; Geographic detector (search for similar items in EconPapers)
Date: 2025
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DOI: 10.1007/s10668-023-04323-5

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