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Identifying the determinants and spatial nexus of provincial carbon intensity in China: a dynamic spatial panel approach

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Abstract

Is emission intensity of carbon dioxide (CO2) spatially correlated? What determines the CO2 intensity at a provincial level? More importantly, what climate and economic policy decisions should the China’s central and local governments make to reduce the CO2 intensity and prevent the environmental pollution given that China has been the largest emitter of CO2? We aim to address these questions in this study by applying a dynamic spatial system generalized method of moment technique. Our analysis suggests that provinces are influenced by their neighbours. In addition, CO2 intensities are relatively higher in the western and middle areas, and that the spatial agglomeration effect of the provincial CO2 intensity is obvious. Our analysis also shows that CO2 intensity is nonlinearly related to gross domestic product, positively associated with secondary-sector share and foreign direct investment, and negatively associated with population size. Important policy implications are drawn on reducing carbon intensity.

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Acknowledgments

This study was supported by the Program for New Century Excellent Talents in University (NCET-13-0583). We are grateful to Wolfgang Cramer, Jintao Xu and two anonymous reviewers for their useful comments and suggestions on the early version of this paper.

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Authors and Affiliations

  1. Department of Energy Economics, Renmin University of China, Beijing, 100872, China

    Xinye Zheng & Yihua Yu

  2. School of Economics, Chongqing Technology and Business University, Chongqing, 400067, China

    Jing Wang

  3. Institute of International Economy, University of International Business and Economics, Beijing, 100029, China

    Huihui Deng

Authors
  1. Xinye Zheng
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  2. Yihua Yu
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  3. Jing Wang
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  4. Huihui Deng
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Correspondence to Yihua Yu.

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Editor: Jintao Xu.

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Zheng, X., Yu, Y., Wang, J. et al. Identifying the determinants and spatial nexus of provincial carbon intensity in China: a dynamic spatial panel approach. Reg Environ Change 14, 1651–1661 (2014). https://doi.org/10.1007/s10113-014-0611-2

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  • DOI: https://doi.org/10.1007/s10113-014-0611-2

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