Examining the asymmetric role of economic complexity, resource efficiency, and renewable energy on consumption-based CO2 emissions in China

Although several empirical studies have extensively examined the role of knowledge accumulation, resource efficiency, and renewable energy in environmental challenges facing the world over the last three decades, little is known about the possible their asymmetric roles. Thus, this study examines the asymmetric roles of economic complexity, resource efficiency, and renewable energy utilization on consumption-based CO2 emissions (CBCO2) in China from 1995 to 2019. Using wavelet correlation, wavelet quantile correlation, and cross-quantilogram methods, along with a series of robustness checks based on quantile-on-quantile regression and nonparametric Granger causality-in-quantiles, our empirical results indicate that, while economic complexity and economic growth are positively associated with CBCO2, the strength of the association varies across quantiles. Our results also indicate that resource efficiency and renewable energy are negatively associated with CBCO2 with evidence of variation across quantiles. Furthermore, economic complexity, resource efficiency, renewable energy, and economic growth have stronger predictive power across quantiles-in-variance than quantiles-in-mean, with weaker predictive power in the higher quantiles of CBCO2. This implies that the predictability over the distribution of CBCO2 and its volatility is asymmetric. Finally, policy recommendations are offered to help China achieve its long-term environmental sustainability goals.