Analysis of influencing factors of the CO₂ emissions in China: Nonparametric additive regression approach

As the maximal carbon dioxide (CO₂) contributor in world, China is embracing severe stress from emission reduction. It is increasingly important to study the factors affecting China's CO₂ emissions. Many researches had extensively researched the driving forces of CO₂ emissions of China. However, majority of the researches adopt a conventional linear method based on time-series or cross-section data for researching the CO₂ emissions as well as nearly neglect nonlinear relationships. To surmount the limitations of extant investigations, this research adopts a data-driven nonparametric additive regression approach to examine primary influencing factors of China's CO₂ emissions. The results manifest that the nonlinear influence of economy on CO₂ emissions is same as the Environmental Kuznets Curve hypothesis. The household consumption level embodies the inverted "U-type" pattern. The industrialization also embodies the overturned "U-type" relationship. Aggregate retail sales of consumer goods present a positive "U-type" effect upon CO₂ emissions. Similarly, the urbanization signifies a positive "U-type" nexus upon CO₂ emissions. Energy intensity indicates a positive "U-type" nexus. The paper ought to exert more attention to the dynamic effects of the driving forces above in order to abate the CO₂ emissions of China. This study will also propose corresponding policies and recommendations according to the dynamic effects.