4.4 Article

Trade-off between environmental sustainability and economic growth through coal consumption and natural resources exploitation in China: New policy insights from wavelet local multiple correlation

Journal

GEOLOGICAL JOURNAL
Volume 58, Issue 4, Pages 1384-1400

Publisher

WILEY
DOI: 10.1002/gj.4664

Keywords

coal consumption; environmental sustainability; natural resources; wavelet local multiple correlation

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Challenges brought on by rapid economic growth in China include the depletion of natural resources and environmental deterioration. This study evaluates the time-frequency nexus between CO2 emissions, natural resources, coal consumption, and economic growth using data from 1970 to 2020. The findings show that economic growth, coal consumption, and natural resources positively drive CO2 emissions at all frequencies, leading to environmental degradation. This study has significant implications for policy-making.
Challenges brought on by the rapid rate of economic growth include the depletion of natural resources (NAR) and environmental deterioration. Due to its abundant mineral resources and rapid economic growth, China has gained attention from both the developing and developed worlds. Using data from 1970/Q1 to 2020/Q4, this paper evaluates the time-frequency nexus between CO2 emissions and natural resources, coal consumption, and economic growth. The study employs the Wavelet Local Multiple Correlation (WLMC) to explore this nexus. This approach enhances the capacity to comprehend the fundamental relationships between these indicators at different frequencies. To the best of the investigator' knowledge, this is the first empirical investigation to explore the time-frequency nexus between natural resource, economic growth, coal use, and CO2 emissions in China, thus filling a gap in the literature. Furthermore, wavelet coherence is employed as a robustness check. The WLMC bivariate cases revealed that economic growth, coal consumption, and natural resources drive CO2 emissions positively at all frequencies, that is, in the short and long-term, thus leading to environmental degradation. Furthermore, the wavelet coherence results support the outcomes of the WLMC bivariate cases. This study offers significant implications for policy and insights that are supported by the findings.

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