Government corruption, market segmentation and renewable energy technology innovation: Evidence from China

2021 ◽  
Vol 300 ◽  
pp. 113686
Author(s):  
Siyu Ren ◽  
Yu Hao ◽  
Haitao Wu
2020 ◽  
pp. 0958305X2092893
Author(s):  
Bai Liu ◽  
Yutian Liu ◽  
Ailian Zhang

With the depletion of fossil energy and the rise of global temperature, it is urgent to use renewable energy to solve environmental problems. By studying the heterogeneous relationship between CO2 emissions and renewable energy technology innovation in different countries, we can find out the gap and something helpful to energy development. In the empirical test, we use the negative binomial regression model with fixed effects to study the impact of CO2 emissions on renewable energy technology innovation from 1997 to 2016. The research shows that impact is positive in oil-importing countries, but this relationship is not established in oil-exporting countries. In both oil importers and oil exporters, CO2 emissions have a positive effect on the solar energy technological innovation, however, the influence on the technology innovation of solar energy in oil exporters is more significant than that of renewable energy. Whether for oil importers or oil exporters, it can be more reasonable and effective to develop renewable energy by clarifying the impact of CO2 emissions on domestic renewable energy technology innovation.


2021 ◽  
Vol 9 ◽  
Author(s):  
Chen Feng ◽  
Yuansheng Wang ◽  
Rong Kang ◽  
Lei Zhou ◽  
Caiquan Bai ◽  
...  

Based on the provincial panel data of China from 2001 to 2016, this study uses the social network analysis approach to empirically investigate the characteristics and driving factors of the spatial association network of China’s interprovincial renewable energy technology innovation. The findings are as following. 1) The spatial association of China’s interprovincial renewable energy technology innovation exhibits a typical network structure. Moreover, its network density, network hierarchy and network efficiency are 0.3696, 0.6667 and 0.7833 in 2001 and 0.4084, 0.4764 and 0.7044 in 2016, respectively, implying the spatial association network became more and more complex and the interprovincial association strengthened during the sample period. 2) This spatial association network presents a “core-edge” distribution pattern. The positions and roles of various provinces vary greatly in the spatial association network. Specifically, the developed coastal regions such as Shanghai, Beijing and Tianjin have a degree centrality, closeness centrality and betweenness centrality of above 75, 80 and 10, respectively, indicating that they always play a central role in the network. However, the northeastern regions and the relatively backward central and western regions such as Heilongjiang, Jilin, Xinjiang, Hainan and Hebei only have a degree centrality, closeness centrality and betweenness centrality of below 20, 55 and 0.1, respectively, indicating that they are at a relatively marginal position. 3) The geographical proximity and the expansion of the differences in economic development level and R&D inputs are conducive to the enhancement of the spatial association of China’s renewable energy technology innovation.


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