The Dynamic Analysis Of Carbon Emissions In China: Based On The Method Of A Structural Decomposition

The environmental kuznets curve (EKC) provides a fundamental framework for studying the relationship between economic variables and environmental variables, and at the same time, provides the theoretical foundation for the development of energy economics. Based on the theory of "coupling", China's economic growth and energy consumptions are now positively correlated, and greenhouse gases, as a byproduct, vastly affect the global atmosphere.This paper is about to find carbon emissions'affecting factors and abating policies based on carbon emissions'decomposing methods by sorting out references at home and broad. In order to avoid the sample selection bias and accurately analyze the historical condition of China's carbon emissions, this paper uses the method of structual vector autoregression (SVAR), and sets long-term constraints to identify unknown paramenters. In order to guarantee the robustness of the model, this paper proposes the method of Bayesian Vector Autoregression, sets hyperparameters of the model through the specification of informative and noninformative priors, and presents that the SVAR model is robust by making a comparision of paramenters in the two models.Based on above paramenter estimations and robust tests of the model, it is concluded as below:1) Relying on the method of counterfactual analyses, it is not until year1995that the economic growth rate of our country is positively correlated with the growth rate of carbon dioxide in statistics, and it has not yet reached the inflexion point about our contry's carbon emissions.2) The data generating process can be derived by the robust test of the model, thus the simulated mean of the growth rate of carbon emissions is approximately7%under the sample size of50000, which shows that the amount of carbon emissions of our country will still be in the high level in the relative long time period unless the abating technique of carbon emissions has a significant change.3) If GDP data is calculated by incorporating the factor of pice, the simulated economic growth rate will be distributed between10%and15%in a ralatively high probability, thus the goal, which says that carbon emissions per GDP in2020will be decreased by40%-45%compared to the2005level, will be realised in a high probability under the condition that the average of carbon emissions is7%. Although the decomposing method of the SVAR model and the robust test of the BVAR model can be better to depict the dynamic effect of carbon emissions of our country, the mediun and long term development goal of our country is still in an uncertain condition especially in the scenario that the global systematic risk has already gradually increased.