The asymmetric influence of renewable energy and green innovation on carbon neutrality in China: Analysis from non-linear ARDL model

Abstract

Adopting green technology and renewable energy is imperative to address climate challenges and realize sustainable development goals. Therefore, this study examines the impact of green innovation and energy consumption on carbon emissions in China from Q1-1990 to Q4-2018. Due to several technological and economic shifts in recent eras, Chinese macro-economic data shows an abnormal distribution, and traditional linear estimators failed to integrate non-linearity. In response, this study employs a non-linear autoregressive distributed lag (NARDL) framework to address non-linearity arising from abnormal data distribution. The overall results reveal that positive shocks in green technology significantly mitigate carbon emissions by 0.262%, while negative shocks increase emissions by 0.104%. Similarly, positive shocks in renewable energy consumption caused a 0.360% reduction in carbon emissions, while negative shocks increased emissions by 0.424%. In contrast, a positive change in non-renewable energy consumption leads to 0.139% higher emissions. However, in a negative shock, this effect turns stronger and spurs carbon emissions by 0.246% in the long run. These findings confirm the asymmetricity because positive and negative shocks in regressors distinctly affect carbon emissions in China. Finally, population and economic growth contribute to higher emissions by 0.872% and 0.685% in the long run, respectively. Moreover, the error correction term confirms the long-run steady-state equilibrium convergence by 11.5% in the case of any shock in the short run. These results indicate that the Chinese government should promote green innovation and renewable energy policies based on their asymmetric emissions-reduction effects.