4.7 Article

Examining the effects of socioeconomic development on China's carbon productivity: A panel data analysis

期刊

SCIENCE OF THE TOTAL ENVIRONMENT
卷 659, 期 -, 页码 681-690

出版社

ELSEVIER SCIENCE BV
DOI: 10.1016/j.scitotenv.2018.12.409

关键词

Carbon productivity; Spatiotemporal patterns; Socioeconomic determinants; Low-carbon economy; Panel data analysis; China

资金

  1. National Natural Science Foundation of China [41601151]
  2. Natural Science Foundation of Guangdong Province [2016A030310149]
  3. Pearl River S&T Nova Program of Guangzhou [201806010187]
  4. China Scholarship Council [201806385014]

向作者/读者索取更多资源

China, which is the largest carbon emitter and the largest developing country in the world, faces the challenge of achieving energy conservation and emission reduction without sacrificing economic development. Improving carbon productivity consists a possible way to seek a coordination between economic development and carbon emission reduction. Therefore, it is of great significance to examine the effects of socioeconomic development on China's carbon productivity and accordingly provide policy suggestions for China's low-carbon economic development. However, this topic has not been adequately addressed in previous studies. In order to fill this gap, this study detailed an empirical investigation into the impacts of socioeconomic development on China's carbon productivity. First, aided by spatial analysis methods, a detailed analysis of the spatiotemporal patterns and dynamics of China's province-level carbon productivity was conducted. Moreover, using an extended STIRPAT model and panel data modeling technique, the effects of a range of socioeconomic factors on China's carbon productivity were quantitatively examined. The results indicated that China's carbon productivity increased gradually between 1997 and 2016, and carbon productivity in East China was much higher than that of their counterparts in Central China and West China. Provincial administrative units with highly developed economies witnessed spectacular increases in carbon productivity. Panel data analysis demonstrated that GDP per capita, technology level, trade openness, and foreign direct investment exerted positive effects, while energy consumption structure, industrial proportion, and urbanization level exerted negative effects, on China's carbon productivity. Based on the findings of this study, a series of policy suggestions with respect to improving China's carbon productivity were proposed. (c) 2018 Elsevier B.V. All rights reserved.

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