Analysis of the impact path on factors of China's energy-related CO2 emissions: a path analysis with latent variables

Abstract

Identifying the impact path on factors of CO₂ emissions is crucial for the government to take effective measures to reduce carbon emissions. The most existing research focuses on the total influence of factors on CO₂ emissions without differentiating between the direct and indirect influence. Moreover, scholars have addressed the relationships among energy consumption, economic growth, and CO₂ emissions rather than estimating all the causal relationships simultaneously. To fill this research gaps and explore overall driving factors' influence mechanism on CO₂ emissions, this paper utilizes a path analysis model with latent variables (PA-LV) to estimate the direct and indirect effect of factors on China's energy-related carbon emissions and to investigate the causal relationships among variables. Three key findings emanate from the analysis: (1) The change in the economic growth pattern inhibits the growth rate of CO₂ emissions by reducing the energy intensity; (2) adjustment of industrial structure contributes to energy conservation and CO₂ emission reduction by raising the proportion of the tertiary industry; and (3) the growth of CO₂ emissions impacts energy consumption and energy intensity negatively, which results in a negative impact indirectly on itself. To further control CO₂ emissions, the Chinese government should (1) adjust the industrial structure and actively develop its tertiary industry to improve energy efficiency and develop low-carbon economy, (2) optimize population shifts to avoid excessive population growth and reduce energy consumption, and (3) promote urbanization steadily to avoid high energy consumption and low energy efficiency.

Keywords: Causality relationships; Direct and indirect influence; Energy-related carbon emissions; Influencing mechanism; Path analysis with latent variables model; Policy implications.