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Carbon dioxide (CO 2 ) emission is a major contributor to global climate change and needs an instant reduction to preserve the environmental quality of the planet. To ensure this, our study examines the role of green factors in terms of finance, technology, and energy in reducing CO 2  emissions in China using quarterly data spanning 2001Q1-2020Q4. A recently developed frequency- and time-varying technique named “Wavelet Local Multiple Correlation” is applied to examine the impact of considered factors on CO 2  emission dynamics in short-, medium-, and long-term. Thus, our study is the first to provide detailed insights into the role of green factors in reducing CO 2  emission in China in a multivariate context. The outcomes confirm the long-term positive connectedness among green finance, green technology, and green energy consumption. Secondly, all these factors are asymmetrically and negatively correlated to CO 2  emissions in long-term frequencies. However, green energy and green finance are highly affecting the CO 2  in long-term, while green technology in medium-term. Finally, the multivariate analysis confirms that all the explanatory variables follow a similar trend in affecting CO 2  emission; though, green finance is the dominant factor in the correlation. Based on the findings, the study recommends promoting green innovations, financial measures, and renewable energy that help China to limit CO 2  emissions and promote environmental quality.

energy sources, part b: economics, planning, and policy

Green perspectives of finance, technology innovations, and energy consumption in restraining carbon emissions in China: Fresh insights from Wavelet approach