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Determinants of Carbon Emission in China: How Good is Green Investment?

Abstract The rapid industrialization and modernization of the People's Republic of China's economy have significantly aggravated the nation's carbon emission-induced climate change adversities. Under this premise, this study attempts to analyze the roles of green investments and other key macroeconomic aggregates in reducing carbon emissions in 30 provinces in China from 1995 to 2017. The robust econometric tools efficient in handling cross-sectional dependency and slope heterogeneity issues were utilized. The Westerlund cointegration analysis confirms the long-term association between the variables of concern. Moreover, the elasticity estimates from the cross-section augmented autoregressive distributed a lag approach indicate that investments in green projects are seen to reduce short- and long-term carbon emission levels. In contrast, the extraction of natural resources, the development of the financial sector, and energy investments increase carbon emissions, both in the short and long term. Furthermore, the Dumitrescu and Hurlin causality analysis indicate bidirectional causation amongst carbon emissions and the other macroeconomic aggregates considered in this study.
- Tsinghua University China (People's Republic of)
- Qingdao University China (People's Republic of)
- Peking University China (People's Republic of)
- Peking University China (People's Republic of)
- North South University Bangladesh
citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).301 popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.Top 0.1% influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).Top 1% impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.Top 0.1%
