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Green credit is an important financial tool to promote the transformation of the low-carbon economy. On the basis of clarifying the theoretical mechanism of the impact of green credit on carbon emission reduction, this paper used the fixed effect stochastic frontier model containing unexpected output to measure the total factor carbon productivity of 156 cities in China from 2000 to 2019 and empirically tested the carbon emission reduction effect of green credit and its mechanism from the three dimensions of productivity, intensity, and total amount. The research found that: ① Green credit development significantly improved total factor carbon productivity and reduced carbon emission intensity, but the average impact on total carbon emissions was not significant. The above conclusions were still valid after a series of robustness tests and treatments of endogeneity problems. ② The carbon emission reduction effect of green credit was heterogeneous due to differences in regional location, resource endowment, and financial efficiency. In the central region, non-resource-based cities, and cities with higher financial efficiency, green credit had significant carbon reduction effects in both carbon productivity and carbon intensity dimensions, while green credit in the eastern region, resource-based cities, and cities with lower financial efficiency only reduced carbon intensity. ③ The stimulation of green innovation and the reduction of energy intensity were the most effective channels for green credit to reduce carbon emissions, whereas the mediating effect of the structural transformation channel was not yet significant. Green credit was more effective in promoting green innovation and generating positive spillovers in the green innovation channel. However, green credits were more effective in improving carbon emission efficiency in the energy intensity channel, but the role of supporting low-carbon technologies must be enhanced. ④ Environmental regulations had two moderating mechanisms, 'positive compensation' and 'negative offset,' for the carbon reduction effect of green credit. When the demand and supply of financial resources were low, strengthening environmental regulations would weaken the incentive effect of green credit on low-carbon economic transformation. The above conclusion not only provides a new research perspective and supplementary empirical evidence for understanding the environmental effects of green credit, but also provides a useful reference for further improving green credit policies and promoting the development of a low-carbon economy. [ABSTRACT FROM AUTHOR]

Saving energy resources and reducing energy intensity are crucial to promoting China' s major strategic goals of reaching peak carbon emissions and achieving carbon neutrality, and are hence key to the promotion of green transformation and development in the new development stage. As an important practice, the policy of establishing pilot zones for green finance reform and innovations in China aims to promote green finance reform in depth, construct ecological civilization, and realize green economic transformation. Can the policy reduce energy intensity and contribute to energy conservation? What is its impact mechanism? There is a shortage of systematic analysis in academia on these issues. With panel data from Chinese cities from 2007 to 2020 and a generalized synthetic control method, this paper evaluated how the establishment of pilot zones for green finance reform and innovations affected energy intensity and analyzed its impact mechanisms. The results showed that: ① The implementation of the policy significantly reduced the energy intensity of the pilot zones, and the energy-saving effect exhibited 'policy first' and timeliness characteristics. ② The policy-induced energysaving effect was achieved by improving green innovation, easing financing constraints, optimizing industrial structure, and strengthening environmental governance. ③ The policy' s energy-saving effect was more remarkable in areas with better marketization and a higher education level. The findings suggest that the government should fully consider the differences in aspects such as institutional environment and resource endowment among varying regions, design distinct measures to attract more market players to participate in the green finance system oriented by energy efficiency improvement, energy structure transformation, and environmental governance, and create a much better market-oriented environment for green innovation and corporate financing. [ABSTRACT FROM AUTHOR]

Decomposing total factor productivity growth rate into internal growth effect that mainly considers industry internal technical advancement and the effect of factor reallocation formed by the flow of capital, labor and energy between sectors, this study took 23 subsectors as the research object and adopted the multi-sector growth accounting method to verify the 'structural dividend hypothesis' of capital, labor and energy from 2005 to 2017. The study drew the following conclusions: (1) Internal growth effect represented by sectoral technical advancement was still the main contributor to total factor productivity growth of the overall economy, but the contribution rate had decreased. (2) The reallocation effect of capital changed from 'structural negative benefit' to 'structural dividend'. (3) The reallocation effect of labor showed a trend of first rising and then falling, changing from 'structural dividend' to 'structural negative benefit'. (4) The effect of energy reallocation was gradually emerging, with a shift from 'negative structural benefit' to 'structural dividend'. Based on these research results, this paper argues that more attention should be paid to the efficiency of factor reallocation in addition to the technical advancement of all sectors. The inefficiency of factor reallocation caused by imperfect market and asymmetric information would partially offset the effect of technical advancement and hinder the high-quality economic development. In view of the reallocation of capital, labor and energy factors, this paper proposes the following suggestions: (1) In the reallocation of capital, consideration should be given to both the macroeconomic regulation and the role of market mechanism, and capital allocation should be carried out in accordance with the principle of profit maximization, so as to improve the elasticity of capital output and increase the allocation efficiency of capital. (2) The reallocation of labor force should not only be limited to the level of three industries; attention should also be paid to the marginal output differences within the secondary industry in this process. (3) Attention should be paid to the elasticity of energy output between sectors to avoid inefficient allocation during energy reallocation. It is also necessary to accelerate the phase-out of industries with high energy consumption and high pollution, promote the development of low energy industries to encourage 'energy conservation and emission reduction' as well as green development by increasing the effect of energy reallocation. [ABSTRACT FROM AUTHOR]

In the framework of DEA, based on the directional distance function considering the unexpected output, this paper used the Global-Malmquist-Luenberger productivity index to measure the green total factor productivity of 283 cities in China from 2003 to 2017. Then, we took innovative city construction as a quasi-natural experiment, and used the gradual DID ( difference-in-differences) model to estimate the impact of innovative city construction on green total factor productivity (GTFP). The study found that the construction of innovative cities was conducive to the green transformation of China's economic development. Compared with non-pilot cities, the GTFP of innovative pilot cities increased by 4.9% on average. Specifically, the construction of innovative cities could achieve innovation-driven urban green development in three ways: innovation effect, agglomeration effect and reverse force effect. Heterogeneity analysis found that the construction of innovative cities had a greater promoting effect on GTFP of cities in the eastern region, larger cities and cities with higher levels. Quantile estimation results showed that the effect of the construction of innovative cities on urban GTFP was increasing marginally. The conclusion of this study was robust, which still held after parallel trend test, PSM-DID method estimation, counterfactual test, placebo test, other robustness tests and instrumental variable estimation. This study has the following implications: In the process of building innovative cities, we should adhere to the principle of adjusting measures to local conditions, implement the 'one policy for one place' principle, give full play to the dominant position of local governments, and explore multi-dimensional ways to promote the level of GTFP of the city. [ABSTRACT FROM AUTHOR]