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Technological innovation is the key to develop wind power and photovoltaic power industries. The feed-in tariff (FIT) policy, as a demand-pull policy, is important to support renewable energy technological innovation. Using the "difference-in-differences" method, this paper investigates the impact of FIT policy of wind power and the impact of the FIT policy designed according to differences in the distribution of resources on wind power technological innovation. The findings show that the FIT policy can drive patenting in wind power technologies during the implementation period, but may play a relatively weak promoting role in technological innovation in the latter term, and the FIT policy designed according to differences in the distribution of resources also stimulates more patent counts. Finally, based on the fixed effect negative binomial regression model, this paper finds that the higher feed-in tariffs can increase the patent counts in photovoltaic power technologies. [ABSTRACT FROM AUTHOR]

Expanding the supplies of new energy can not only reduce CO2 emissions, but also alleviate energy shortage. This paper applies the quantile regression to investigate the new energy industry in China. The results show that economic growth exerts the greatest effect on the new energy industry in the lower 10th quantile province. This is because these provinces have the developed economies, demand for a higher ecological environment and new energy resources. Foreign energy dependence has a minimal impact on the new energy industry in the 25th-50th quantile province, due to their minimal oil importation. The contribution of technological progress to the upper 90th quantile province is the lowest, because their R&D capabilities are the weakest. The impact of energy consumption structure decreases in steps from the lower 10th quantile provinces to the upper 90th quantile provinces. The agricultural sector promotes the new energy industry in most provinces. [ABSTRACT FROM AUTHOR]

Existing studies have focused on the negative impact of inefficient resource allocation on energy performance in China, but neglected to explore the underlying reason for this phenomenon from the perspective of market segmentation. To fill this research gap, the epsilon-based measure model is used to estimate energy efficiency, and the measurement method of market segmentation is improved in this paper. On the basis of a theoretical hypothesis, we use fractional regression models to conduct empirical research. The results show that market segmentation has a significant negative effect on China’s energy efficiency. Additionally, this inhibitory effect is robust but heterogeneous. The impact mechanism test indicates that energy price distortion, enterprise technology innovation, and industrial ag)glomeration are three intermediate influence channels. Based on these analyses, we suggest that China should accelerate market-oriented reform and eliminate market segmentation in pursuit of energy-saving and emission-abating goals. [ABSTRACT FROM AUTHOR]