Green technology innovation and CO2 emission in China: Evidence from a spatial-temporal analysis and a nonlinear spatial durbin model
Based on the panel data of 30 provinces in China from 2007 to 2019, this paper investigates the impact of green technology innovation on carbon intensity. Firstly, this paper studies the dynamic evolution and temporal and spatial pattern of China's provincial green technology innovation and car...
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Veröffentlicht in: | Energy policy 2023-01, Vol.172, p.113338, Article 113338 |
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Sprache: | eng |
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Zusammenfassung: | Based on the panel data of 30 provinces in China from 2007 to 2019, this paper investigates the impact of green technology innovation on carbon intensity. Firstly, this paper studies the dynamic evolution and temporal and spatial pattern of China's provincial green technology innovation and carbon intensity. On this basis, the nonlinear spatial Durbin model (SDM) is used to explore the impact of green technology innovation on carbon intensity, and the relevant variables are controlled. The results show that there is a significant spatial agglomeration phenomenon in China's provincial green technology innovation level and carbon intensity. The direct impact of green technological innovation on carbon intensity in local region shows a significant "inverted-U" relationship, that is, when the level of green technological innovation is relatively low, green technological innovation will promote carbon emissions, while when the level of green technological innovation reaches a certain level, this promotion relationship will change into inhibition relationship. From the perspective of interregional spillover effect, green technological innovation also has an “inverted-U″ nonlinear impact on carbon emissions in adjacent regions, that is, the impact of green technological innovation on carbon emissions in adjacent regions is also promoted first and then restrained.
•The influence of green technology innovation on carbon emission is analyzed.•Spatial spillover effect is considered in the analysis.•The inverse U-shaped relationship between them was found.•Some policy recommendations on CO2 emission reduction are put forward. |
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ISSN: | 0301-4215 1873-6777 |
DOI: | 10.1016/j.enpol.2022.113338 |