Race to achieving sustainable environment in China: Can financial globalization and renewable energy consumption help meet this stride?

Investigating the drivers of CO emissions is essential for limiting global warming, which has sparked widespread concern. This study evaluates the association between economic complexity and CO emissions in China, considering the effect of disintegrated energy and financial globalization on the environmental function between 1970 and 2018. This dataset was analyzed using the autoregressive lag model (ARDL) and frequency-domain causality approaches. The ARDL unveiled that urbanization, economic complexity, financial globalization, and economic growth deteriorate the environment while environmental sustainability is achieved through renewable energy utilization. The study also validates the Environmental Kuznets Curve hypothesis. Also, the frequency-domain causality disclosed that all regressors (economic growth, financial globalization, economic complexity, and urbanization) could forecast CO emissions in China at different frequencies. Based on these outcomes, policy recommendations are formulated.