Construction of China’s low-carbon competitiveness evaluation system: A study based on provincial cross-section data

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Abstract

Purpose: As the contradiction between economic development, resource and environment has become increasingly prominent, low-carbon competitiveness has received worldwide focus. This study aims to examine low-carbon competitiveness in 31 provinces (cities and regions) of China. Design/methodology/approach: An evaluation index system for low-carbon competitiveness in China has been constructed, which is composed of 25 economic, social, environmental and policy indicators. To study the state of low-carbon competitiveness and resistance to China’ development of low-carbon competitiveness, this study uses a combination of the catastrophe progression model, the spatial autocorrelation model and the barrier method. Findings: China’ low-carbon competitiveness gradually decreases from coastal to inland areas: the Tibet and Ningxia Hui autonomous regions are the least competitive regions, while the Shandong and Jiangsu provinces are the most competitive areas. The spatial correlation of the 31 provinces’ low-carbon competitiveness is very low and lacks regional cooperation. This study finds that the proportion of a region’ wetland area, the proportion of tertiary industries represented in its GDP and afforestation areas are the main factors in the development of low-carbon competitiveness. China should become the leader of carbon competitiveness by playing the leading role in the Eastern Region, optimizing the industrial structure, improving government supervision and strengthening environmental protection. Originality/value: The paper provides a quantitative reference for evaluating China’ low-carbon competitiveness, which is beneficial for environmental policymaking. In addition, the evaluation and analysis methods offer relevant implications for developing countries.

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Wang, Y., Lan, Q., Jiang, F., & Chen, C. (2020). Construction of China’s low-carbon competitiveness evaluation system: A study based on provincial cross-section data. International Journal of Climate Change Strategies and Management, 12(1), 74–91. https://doi.org/10.1108/IJCCSM-11-2018-0076

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