Using the extended STIRPAT model, this research examines the influence of various factors on China carbon emission from 1971 to 2014, including total nuclear and alternative energy, total fossil energy, GDP per capita, total population, total urban population, merchandise trade of GDP, and services value added of GDP. Ridge regression was employed to perform the study. The research results show the positivity and significance of all factors on carbon emission. The estimated elastic coefficients reveal the most important factor influencing carbon emission is GDP per capita. Total fossil energy, total urban population, and nuclear energy of total energy use are also prominent influencing factors, while other factors such as value-added services of GDP and merchandise trade of GDP have less significant impacts on carbon emission in China. These findings of the research will be of great significance for China to control its carbon emission in the future and to mitigate global warming to some extent.
Keywords: CO2 emissions; China; Ridge regression; STIRPAT model.