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Can green technology innovation alleviate the regional energy dilemma? Evidence from 30 provinces in China

High energy intensity and energy consumption structure are the main contradictions restricting China’s green economic growth. Green technology innovation is an important factor to alleviate the energy dilemma. Referring to the IPC Green Inventory launched by the World Intellectual Property Organization, the green patents of 30 provinces in China from 2004 to 2019 are screened. Based on the panel data of 30 provinces in China, this study empirically tests the impact of green technology innovation on energy intensity and energy structure by employing fixed effect model and quantile regression model. The empirical results show that green technology innovation can significantly reduce energy intensity and energy structure, and the long-term effect is obviously higher than the short-term effect. Compared with the green utility model patent representing general innovation, the green invention patent representing disruptive innovation expresses more momentous long-term and short-term effect. The sustainable effect of green technology innovation will gradually weaken with the reduction of energy intensity and energy structure. For provinces with low energy structure, the impact of green technology innovation is no longer significant. Instrumental variable method and robustness test prove that the conclusion of this study is robust. This study provides support for the government and enterprises to promote technological innovation and play a part in alleviating the energy dilemma.
- Harbin University of Commerce China (People's Republic of)
- Harbin University of Commerce China (People's Republic of)
quantile regression model, energy intensity, energy structure, fixed effect model, Environmental sciences, green technology innovation, GE1-350
quantile regression model, energy intensity, energy structure, fixed effect model, Environmental sciences, green technology innovation, GE1-350
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).5 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 10% influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).Average impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.Top 10%
