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- W4384008386 abstract "We propose a vector error correction model to explore the causal correlation between green finance, economic growth, and renewable energy consumption from both short- and long-run perspectives to empirically evaluate the efficacy of green finance policies. Based on time-series data from 2000 to 2020, we use the unit root test method to examine time-varying trends and cointegration for time-series data. We find that renewable energy consumption has a negative relationship with emissions but green finance is positively correlated with economic growth. Green finance is the driving factor behind the increasing utilization of renewable energy in China. CO 2 emissions per unit of GDP decreased by 1.077% for every 1% increase in green finance development. Although the share of renewable energy consumption increased by 1%, CO 2 emissions per unit of GDP decreased by 0.55%. Therefore, green finance is significant in decreasing CO 2 emissions; it has a negative impact on CO 2 emissions and the renewable energy sector and must be addressed by financial policy, stability, and long-run sustainability. We categorized green finance, which refers to carbon finance innovations such as trusteeship, to improve market demand and eventually develop industries to expand the number of emission-control industries." @default.
- W4384008386 created "2023-07-13" @default.
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- W4384008386 date "2023-07-12" @default.
- W4384008386 modified "2023-09-25" @default.
- W4384008386 title "The short- and long-run causal correlation between green finance, renewable energy consumption, and economic growth" @default.
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- W4384008386 doi "https://doi.org/10.1177/0958305x231187036" @default.
- W4384008386 hasPublicationYear "2023" @default.
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