Exploring the Effective Way of Reducing Carbon Intensity in the Heavy Industry: A Semiparametric Econometric Approach

Abstract

China has promised that by 2030, its carbon intensity will be cut down by about 60%. Unlike existing related research, this article employs a novel semiparametric regression model to explore the carbon intensity of the heavy industry. The main results are as follows: (1) the relationship between spatial agglomeration and carbon intensity shows a non-linear pattern, mainly caused by the cross-regional flow of production factors. (2) The impact of technological progress on carbon intensity also displays significant non-linear characteristics, mainly due to the staged differences in R&D investment. The following three factors are linearly related to carbon intensity. (1) Energy consumption structure has a more significant linear impact on the carbon intensity in the central and eastern regions, due to the heavy coal consumption of the heavy industry in these two regions. (2) The linear impact of environmental regulations on the carbon intensity in the eastern region is more significant, owing to the region’s considerable investments in environmental governance. (3) The industrial structure has the most significant linear impact on the carbon intensity in the eastern region, since the scale of the tertiary industry in this region is larger.

Keywords: Driving factors; Carbon intensity; The heavy industry; Semi-parametric regression model