Is the carbon emissions trading system conducive to the urban green technology innovation level? Evidence from China

Han, Yaling; Zhe, Caihong; Liu, Xuemei

doi:10.1016/j.egyr.2023.02.023

Cited by 31 publications

(3 citation statements)

References 29 publications

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“…It will also promote investment in green innovation projects by enhancing liquidity. For example, the carbon finance system uses digital finance to participate in carbon trading activities, which enhances carbon trading liquidity, reduces investment costs, allows more capital to flow to low-carbon projects [37], and enhances green innovation.…”

Section: Innovation Effectmentioning

confidence: 99%

Non-Linear Impacts and Spatial Spillover of Digital Finance on Green Total Factor Productivity: An Empirical Study of Smart Cities in China

Zhang

Fan

2023

Sustainability

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Smart cities are important digital economy vehicles that can fully exploit the green attributes and spatial penetration of digital finance. Using panel data for 100 cities selected as pilot smart cities in China from 2011 to 2019, this paper applies a spatial econometric model to analyze the non-linear impacts of digital finance on GTFP and its spatial spillovers. Furthermore, it utilizes mediation models to study their transmission mechanisms. The results show that digital finance first inhibits and then promotes GTFP, with spatial spillovers in four dimensions: geography, information, technology, and human capital. Its mediating mechanisms are innovation effects, structural effects, and scale effects. The statistical significance of the U-shaped relationship is regionally heterogeneous, according to different levels of human capital, informatization, urbanization, and financial marketization. Based on digital finance’s U-shaped and heterogeneous impacts on GTFP, policy recommendations are to adopt differentiated development strategies according to specific levels of digital finance and underlying conditions in smart cities. Stimulating the innovation and structural effects and suppressing the scale effects will help digital finance breakthrough inflection points, and will positively promote GTFP. It is also necessary to encourage inter-regional cooperation among smart cities to fully release spatial spillover dividends through technology sharing, information transfer, and talent exchange to promote the linked improvement of GTFP.

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Section: Innovation Effectmentioning

confidence: 99%

Non-Linear Impacts and Spatial Spillover of Digital Finance on Green Total Factor Productivity: An Empirical Study of Smart Cities in China

Zhang

Fan

2023

Sustainability

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“…Furthermore, to mitigate bias arising from population differences among cities, the level of technological innovation in cities is measured by the number of patent applications per 10,000 people. (Han et al 2023) (2) Functional division(fd). Referring to the methodology employed by Chen et al (2022), the ratio of "the proportion of employees in productive service industries to employees in manufacturing industries" in the center city group of the urban cluster is used to compare with the corresponding ratio in the peripheral city group.…”

Section: Intermediary Variablementioning

confidence: 99%

Has the construction of national central cities improved the carbon productivity of urban cluster? Empirical evidence from China

Li,

Wang,

Cao

2023

Preprint

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The national central city is the highest level within China's urban system, bearing the significant responsibility of leading national and regional coordinated development. Based on panel data from 19 city clusters and 207 cities in China spanning the years 2003 to 2019, we treat China's national central city construction policy as a quasi-natural experiment. It employs a difference-in-differences model and a mediation effects model to evaluate the impact mechanism of national central city construction on urban cluster carbon productivity. The result shows that, firstly, the national central city construction significantly enhances urban cluster carbon productivity, a result robustly validated through various sensitivity tests. Secondly, heterogeneity analysis demonstrates that national central city construction exerts a positive influence on the carbon productivity of city clusters in the eastern and central regions. Notably, the effect is more pronounced in the eastern region, whereas it exhibits a distinct inhibitory effect on city clusters in the western region. Overall, the policy effect follows a "U"-shaped trend from west to east. Moreover, a positive correlation emerges between policy effects and city scale, implying that larger cities within city clusters manifest more prominent policy effects stemming from national central city construction. Thirdly, the mechanism of action suggests that national central city construction primarily enhances carbon productivity by augmenting technological innovation capabilities and expediting functional division within urban clusters. Based on the aforementioned findings, it is recommended to actively advance national central city construction, further elevate the technological level of national central cities, and sustain the role of national central cities in driving functional specialization within urban clusters.

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“…Chen et al [28] confirmed that the digital transformation of the national economy had a significant positive impact on the efficiency of green technology innovation in Chinese energy-saving and environmental protection firms. In addition, scholars have also studied the effects of central environmental protection inspectors [29], carbon emissions trading [30], and smart cities [31] on the efficiency of green technology innovation. Due to the different research subjects and methods, the conclusions reached also differ.…”

Section: Measurements Of Green Technology Innovation Efficiencymentioning

confidence: 99%

Spatial Correlation Network Analysis of Industrial Green Technology Innovation Efficiency in China

Fan

2023

Systems

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Exploring the spatial correlation network and its structural characteristics of China’s industrial green technology innovation efficiency is significant for promoting the coordinated development of inter-regional industrial green transformation. Based on the innovation value chain, this paper divides China’s industrial green technology innovation system into three interrelated sub-stages: technology research and development, achievement transformation, and commercialization. The NSBM model is used to measure the efficiency of industrial green technology innovation in 30 provinces and cities in mainland China from 2011 to 2020. The modified gravity model and social network analysis method are introduced to explore its spatial correlation network’s structural characteristics and evolution rules. The results show that the spatial network correlation intensity of the three stages of green technology innovation efficiency in regional industry has gradually strengthened. There is no strict hierarchical structure, and the spatial network tends to be stable. The network shows an apparent “core–edge” distribution in all three stages, with the eastern coastal and central more developed regions at the network’s core. Meanwhile, the northeastern and western remote areas are at the network’s edge and less connected with other regions’ provinces and cities. The distribution of network blocks in the three stages of green technology innovation efficiency is similar. The net benefit block mainly includes the eastern coastal and surrounding developed areas. The net spillover block mainly consists of the economically backward northwest region. The broker block is primarily distributed in the surrounding provinces and cities of the Bohai Rim. The bidirectional spillover block is mainly located in the southwest region. Finally, some suggestions are put forward to promote the coordinated improvement of regional industrial green technology innovation efficiency from the perspective of integrity, individuality, and agglomeration.

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Is the carbon emissions trading system conducive to the urban green technology innovation level? Evidence from China

Cited by 31 publications

References 29 publications

Non-Linear Impacts and Spatial Spillover of Digital Finance on Green Total Factor Productivity: An Empirical Study of Smart Cities in China

Non-Linear Impacts and Spatial Spillover of Digital Finance on Green Total Factor Productivity: An Empirical Study of Smart Cities in China

Has the construction of national central cities improved the carbon productivity of urban cluster? Empirical evidence from China

Spatial Correlation Network Analysis of Industrial Green Technology Innovation Efficiency in China

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