Nonlinear analysis of technological innovation and electricity generation on carbon dioxide emissions in China

Abstract

By using Stochastic Impacts by Regression on Population, Affluence, and Technology (STIRPAT) model, this paper explores the influence of electricity generation and technological innovation on CO2 emissions, as well as that of population and economic growth, in China during the period of 1985–2019. Econometric methods of smooth transition regression (STR) are used to calculate the threshold effects of the linkage among the selected variables. The conversion function of LSTR(1) (logistic STR with one regime switch) is selected by F-statistics based on third-order Taylor approximation. The results of the diagnostic test indicate that when the growth rate of electricity generation exceeds 8.914%, the relationships become nonlinear. Moreover, 1% increases of electricity generation and technological innovation may lead to increases of 2.91664% and 0.31016% in China's CO2 emissions, respectively, while a 1% increase in economic growth can decrease China's CO2 emissions by 1.16441%. Finally, some implications are suggested, such as strengthening the publicity surrounding environmental protection to reduce the footprint of CO2 emissions, extending the green GDP even further, and building a more diversified power supply structure.