Empirical analysis on China’s carbon emission reduction and GDP growth(PDF)
《长安大学学报（社科版）》[ISSN:1671-6248/CN:61-1391/C]
- Issue:
- 2020年03期
- Page:
- 55-67
- Research Field:
- 经济与管理
- Publishing date:
Info
- Title:
- Empirical analysis on China’s carbon emission reduction and GDP growth
- Author(s):
- WANG Baozhong1; HE Liancheng2
- 1. School of Management，Xi’an Polytechnic University，Xi’an 710048，Shaanxi，China；2. School of Economics and Management，Northwestern University，Xi’an 710062，Shaanxi，China
- Keywords:
- GDP; carbon emission intensity; Shaanxi province; discrete difference equation prediction; coal consumption proportion ratio; vector autoregression model; impulse response function
- PACS:
- X321；F224
- DOI:
- -
- Abstract:
- Based on the annual amount of carbon emissions and actual GDP data of Shaanxi province in 1980~2018, this paper uses the Discrete Difference Equation Prediction Model (DDEPM) to forecast Shaanxi’s carbon emission and GDP in order to study China’s economic development speed and the patterns in carbon emission increase, and then obtains the predicted carbon emission intensity of the province in 2020. By constructing a vector autoregression model (VAR), this paper conducts a correlation analysis comparing the amount of carbon emissions of Shaanxi province in 1980~2018 with the actual and predicted data sequences of GDP, and examines the accuracy of the DDEPM forecast method. Research shows that the 2020 carbon emission reduction targets of Shaanxi province put forward by the central government can be achieved.The denominator driving effect resulted from the rapid growth of GDP is the main factor contributing to the achievement of targets, but in the long term this effect is not sustainable to a certain extent. All provinces and regions should look for path of breakthrough in terms of reducing the absolute amount of carbon emissions, increase the input and R&D of lowcarbon technology and highly efficient utilization technology of coal, enhance the utilization efficiency of coal consumption per unit, improve the R&D level of clean energy technology, amplify the utilization rate of existing new energy resources and efficiency, and aim to achieve targets both in reducing carbon emissions and the social and economic sustainable development of China.
Last Update: 2020-07-02