Journal of Northeastern University Natural Science ›› 2015, Vol. 36 ›› Issue (2): 297-300.DOI: 10.12068/j.issn.1005-3026.2015.02.031

• Management Science • Previous Articles     Next Articles

Influencing Factors Analysis and Trend Forecasting of China’s Carbon Emissions——Empirical Study Based on STIRPAT and GM(1,1) Models

TONG Xin1, CHEN Kai1, LI Gang1,2   

  1. 1. School of Business Administration, Northeastern University, Shenyang 110819, China; 2. Northeastern University at Qinhuangdao, Qinhuangdao 066004, China.
  • Received:2014-05-12 Revised:2014-05-12 Online:2015-02-15 Published:2014-11-07
  • Contact: TONG Xin
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Abstract: STIRPAT (stochastic impacts by regression on population, affluence, and technology) model is used to analyze the influencing factors of China’s carbon emissions, and gray model GM(1, 1)is applied to the prediction of emissions from 2012 to 2020. The analysis shows that urbanization,economy growth, industrial structure, energy prices, population, energy structure and foreign trade are the main factors to aggravate the emissions, while technology progress plays an important role in the inhibition of emissions. Among the factors mentioned, population and industrial structures are the two dominant factors. Based on the GM(1, 1), China’ carbon emission is predicted, showing the pressure of reducing carbon emissions is great. Therefore, the governance of carbon emission should synthetically consider the factors mentioned above.

Key words: carbon emission, influencing factor, partial least squares regression, STIRPAT model, GM(1, 1)model

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