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Chinese Journal of Management Science ›› 2018, Vol. 26 ›› Issue (7): 170-178.doi: 10.16381/j.cnki.issn1003-207x.2018.07.018

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The Drive Factor of Regional Carbon Productivity Disparities Based on Spatial Comparative Path Selection Model

YAO Ye1,2, XIA Yan1,2, FAN Ying3, JIANG Mao-rong1,2   

  1. 1. Institutes of Science and Development, Chinese Academy of Sciences, Beijing 100190, China;
    2. University of Chinese Academy of Sciences, Beijing, 100049, China;
    3. Beihang University, Beijing 100190, China
  • Received:2017-09-18 Revised:2018-01-19 Online:2018-07-20 Published:2018-09-20

Abstract: With the increasingly outstanding conflict between social progress and the climate change, how to develop low-carbon green economy has become a hot topic in academic circle and among governmental policy makers. As the core issue of developing carbon economy, increasing carbon productivity is already taken as the key strategy to cope with climate changes. At present, there is a great disparity between China and developed countries in terms of carbon productivity. At the same time, apparent disparities of regions have also severely hindered the growth of low carbon economy in our country. Therefore, to narrow the gaps of regions and enhancing the overall carbon productivity, the study of the disparities in regional carbon productivity and the influencing factors behind it is of great theoretical and practical significance to the formulation of proper energy and environmental policies and the development of low carbon economy.In this paper, the theory of minimum spanning tree (MST) is introduced into structural decomposition analysis and the spatial comparative path selection (SCPS) model is creatively constructed, which can help us to analysis the drive factor of regional disparities of carbon productivity disparities among 27 regions. For building the SCPS model, based on the method of structural decomposition analysis, each region is regarded as one vertex and the variation of bilateral comparison as side length (Paache-Laspeyres spread index is used, which is represented as PLS for direct comparison and CPLS for indirect comparison). In this way, the MST that has a minimum sum of side lengths in a forms spanning tree can be got. Based on SCPS model, the regional input-output tables of China in 2012 is used and five factors, which are GDP, value-added coefficients, production technology level, local and foreign final demand, are chosen to decompose the carbon productivity. The results show that the major driving factor for the regional disparities of carbon productivity is the sectors' carbon intensity. In accordance with the results, it is suggested that balancing the regional discordance, enhancing investments on low carbon industry and promoting development of low carbon technology can help us achieve the "overall increasing goal" for regional carbon productivity in China.

Key words: carbon productivity, structural decomposition analysis, spatial comparative path selection model, regional disparities, input-output technique

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