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Copyright of China Population Resources & Environment is the property of Shandong Normal University and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The report to the 20th National Congress of the Communist Party of China mentioned that China is facing tightening resource and environmental constraints, environmental pollution, and other issues, and the energy-consuming right trading policy is a key measure to promote green, circular, and low-carbon development in China. Under the dual consideration of ecological benefits and economic benefits, this paper took the pilot launch of energy-consuming trading as a quasi-natural experiment and used panel data from 31 provinces in China from 2009 to 2020 and the different-in-differences method to explore the impact of this policy on the optimization and upgrading of China's industrial structure. The study showed that: (J) The energy-consuming right trading policy could promote the optimization and upgrading of the industrial structure, and the promotion effect on the upgrading of the industrial structure outweighed its adverse impact on the rationalization of the industrial structure, as evidenced by a series of robustness tests. © The mechanism analysis showed that the realization paths of industrial structure upgrading were the upgrading of technological innovation and that of energy consumption structure, and the policy suppressed the adverse impact on the rationalization of industrial structure by improving the input structure and output structure of some industrial sectors. © In addition, the pilot policy of energy-consuming rights had obvious regional heterogeneity for the optimization and upgrading of industrial structure, which significantly promoted the upgrading of industrial structure in the central and western regions and the rationalization of industrial structure in the eastern regions. This study provides some policy references for the optimization and upgrading of industrial structure from the perspective of improving the energy-consuming right trading market. [ABSTRACT FROM AUTHOR]

Copyright of Geography & Geographic Information Science is the property of Geography & Geo-Information Science Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Existing studies mainly focus on exploring the ‘inclusive effect’ of digital finance in the process of technological innovation, but generally ignore the ‘network effect’ of digital finance empowerment. Based on China’s inter-provincial panel data and threshold regression technology, this paper empirically examined the nonlinear empowerment mechanism of digital finance to promote the development of green innovation. The results of this study showed that: during the study period, digital finance significantly drove China ’s green innovation and the empowerment effect of the eastern and central regions was much higher than that of the western regions, indicating that the ‘inclusive effect’ of digital finance was significant; the empowerment effect of digital finance on green innovation had a positive dynamic evolution process from weak to strong, but this kind of ‘network effect’ characteristic mainly appeared in the eastern and western regions, while the central region showed a positive ‘U’-shape nonlinear pattern; and the nonlinear empowerment effect of digital finance on green innovation had a heterogeneous and strengthened adjustment mechanism. It had positive and increasing marginal efficiency characteristics under the adjustment of urbanization, fiscal transparency, and residents’ income level. It was manifested under the constraints of urban-rural income gap and economic growth targets. Under the influence of technology introduction, it presented a positive inverted a ‘U’-shaped characteristic. At present, only by continuously improving fiscal transparency, residents’ income, and urbanization level, continuously narrowing the urban-rural income gap, and keeping the economic growth target and technology introduction at a reasonable level, can we maximize the green innovation effect empowered by digital finance. This article has discovered the coexistence of the ‘inclusive effect’ and ‘network effect’ of digital finance empowerment in the process of green innovation. The relevant conclusions may provide local governments with a ‘Digital Finance Express’ during the 14th Five-Year Plan period to accelerate the development of green innovation. [ABSTRACT FROM AUTHOR]

⑴ Background——Green credit is the main part of China’s green finance system. The interaction between green credit and technology innovation is an important driving force for the transformation and upgrading of the forestry industry structure, and also an important means to realize the high-quality development of modern forestry. To discuss the specific effects of green credit and technology innovation on China’s forestry industry structure can provide a theoretical basis for the high-quality development of modern forestry. ⑵ Methods——This paper proposes the research hypotheses by analyzing the potential impact mechanism of green credit (hpc) and forestry technology innovation (tepscore) on the forestry industry structure (nfishc）. Based on the panel data of 28 provinces (municipalities and autonomous regions) from 2008 to 2019,the static FGLS fixed effects model of C-D production function is used to explore the interaction effects of green credit and technology innovation on the forestry industry structure. Meanwhile, in order to solve the possible endogeneity problem of the model and analyze the influence of interaction terms on the interrelation between green credit and technology innovation, the lagged terms of the explained variables are added and the dynamic system GMM model is used to estimate the interaction of green credit and technology innovation on the forestry industry structure. ⑶ Results——Firstly, green credit and forestry technology innovation both play a significant role in promoting the forestry industry structure. Among them, every 1% increase in the level of green credit will increase the forestry industry structure by 0. 126%,every 1% increase in the level of forestry technology innovation will increase the forestry industry structure by 0. 114%. Secondly, the interaction between green credit and forestry technology innovation can indeed enhance their effects of promoting the optimization of forestry industry structure, what’s more, green credit and forestry technology innovation are threshold variables to each other and both of them have a single threshold effect on forestry industry structure. In particular, when the proportion of high energy-consuming interest expenditure is less than 3. 914,there will be a certain scale effect and agglomeration effect. Every 1% increase in the level of forestry technology innovation, the forestry industry structure will significantly increase by 0. 249%. However, when the effect of interaction terms on green credit and forestry technology innovation is further examined, it is found that the development of green credit is not conducive to forestry technology innovation and forestry technology innovation also has a significant negative impact on green credit. Finally, the analysis of the effect of control variables on the forestry industry structure shows that in the process of forestry production, only increasing labor input (fen) has a little effect on the forestry industry, and the effect is not significant. Excessive financial intervention (finf) is not conducive to the transformation of forestry structure. Urbanization level (urban), opening degree (op) and forest coverage rate (fcr) may not only promote the consumption and trade of the forest products, but also adversely affect the forestry industry economy. ⑷ Conclusions and Discussions——First, constantly optimize the investment environment of green credit and give full play to the role of financial regulatory departments in guiding and encouraging banks to develop green credit. Banks should actively implement green credit policies, taking credit scale, structures and efficiency into accounts to lead the development of forestry green enterprises. Second, based on the development status of forestry enterprises, continue to increase the cultivation of the innovative subjects, improve the level of human capital in forestry, promote the upgrading of forestry industry structure. Third, increase the investment in forestry research and development and education of forestry talents, improve the conversion rate of forestry technology patents, and pay attention to the deep integration of forestry technology innovation and forestry green credit to realize the high-quality development of forestry economy. [ABSTRACT FROM AUTHOR]