The effect of the digital economy on carbon emissions: an empirical study in China

Wang, C.B.; Qi, Fang; Liu, Pengzhen; Ibrahim, Haslindar; Wang, Xiaoran

doi:10.1007/s11356-023-27742-3

Cited by 15 publications

(5 citation statements)

References 60 publications

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“…The equation is shown below: (6) Based on this theory, the STIRPAT model, introduced by York et al, further incorporates the concept of differential elasticity coefficients and random errors [36], which is widely used to analyze the relationship between human activities and environmental changes: (7) In this study, we consider several social and economic variables as predictive factors to ensure that the synthetic control group and the treatment group have similar carbon emission characteristics before the construction of NSC. These variables include annual average population (ten thousand people) and per capita GDP (ten thousand yuan) to represent urban population and economic scale respectively [3,10,16,22]. Additionally, green patent grants and the ratio of fiscal technology investment to GDP is used as a proxy for urban technology level [3,6,27].…”

Section: Predictive Variablementioning

confidence: 99%

“…The digital industry itself is energyintensive [15]. While digital technology enhances productivity, it can lead to lower product/service prices, potentially increasing energy use through higher demand [5,16,17]. In summary, digitization's impact on the environment follows diverse pathways, resulting in a complex, nonlinear, inverted U-shaped relationship, as seen in the literature [12,16,18,20].…”

Section: Introductionmentioning

confidence: 99%

“…Regarding the assessment about the environmental effect of digitization, existing research covers specific technological [8,12,14,18], as well as the implementation of national-level digital infrastructure policies [3,4,10,11,13,[21][22][23][24]. Some studies have conducted comprehensive evaluations about the environmental effect of digitization using digital economy indices [6,9,16,19]. However, there is still a need for further literature on the environmental impact assessment of large-scale computational (research) infrastructure project.…”

Section: Introductionmentioning

confidence: 99%

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High Energy Consumption or Dirty Energy Using? The Driving Factors Behind Carbon Emission in National Supercomputing Centers

Haodong,

Gaofeng

2024

Pol. J. Environ. Stud.

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Regarding the impact of digitization on the environment, a definitive consensus remains elusive in the scholarly discourse. This article evaluates the carbon emissions impact of China's National Supercomputing Centers (NSCs) in terms of computational power, aiming to determine whether NSCs exhibit significant carbon emissions effects and to identify the underlying factors driving them. Theoretically, we integrate both direct and indirect effect into a comprehensive research framework, comprising the dimensions of energy consumption and energy structure. Empirically, the synthetic control method (SCM) is employed, constructing a group of synthetic control cities that closely resemble the NSC cities. The research findings show that NSC cities exhibit statistically significant differences in carbon emissions compared to synthetically non-NSC cities, yet this phenomenon manifests with intercity heterogeneity. Upon scrutinizing the driving factors, it becomes apparent that NSCs primarily elevate urban energy consumption scale through increased industrial electricity usage, thus fostering the escalation of local carbon emissions. Interestingly, in certain cities, despite witnessing a surge in energy consumption scale attributable to NSC, carbon emissions effects were not observed, which could be predominantly ascribed to a higher proportion of clean energy within the energy structure. The above results unveil the existence of NSC carbon emissions effect as well as its driving factors (high energy consumption and dirty energy using), providing policy guidance for public sectors aiming to enhance NSC operational efficiency, optimize energy structure, and broaden the spillover effect.

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Section: Predictive Variablementioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

High Energy Consumption or Dirty Energy Using? The Driving Factors Behind Carbon Emission in National Supercomputing Centers

Haodong,

Gaofeng

2024

Pol. J. Environ. Stud.

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“…From the industrial level, first, as an emerging service sector, digital inclusive finance possesses attributes of minimal energy consumption, reduced pollution, and heightened efficiency. Consequently, its progression proves more favorable for advancing the reduction of carbon emissions in comparison to conventional industries (Qin et al, 2022;Wang et al, 2023b). Second, Through the availability of alternative funding routes, digital inclusive finance broadens the purview of financial services, shattering the financing barriers encountered by small and medium-sized firms.…”

Section: Theoretical Analysis and Research Hypotheses 21 Carbon Emiss...mentioning

confidence: 99%

Digital inclusive finance, consumption structure upgrading and carbon emissions

Ye,

Xu,

2023

Front. Environ. Sci.

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The “14th Five-Year Plan” represents a crucial phase in enhancing financial inclusivity in China and addressing the challenge of “peak carbon emissions.” Given the digital economy’s rapid growth, China must urgently devise a model for high-quality development that combines digital finance with eco-friendly and low-carbon strategies. Uniquely focusing on the intersection of digital finance and sustainable growth, this paper fills a critical gap in the existing literature. To examine the impact of digital inclusive financing on carbon emissions from the vantage point of enhancing consumption structures, this study uses panel data covering the years 2014–2020 from 30 Chinese provinces. This research underscores the novel finding that digital inclusive finance can play a significant role in lowering carbon emissions by encouraging individuals to alter their consumption patterns. Variations across regions are evident in the impact, with the central and western areas experiencing a more pronounced decline in carbon emissions in comparison to the eastern region. Moreover, the influence of consumption structure upgrading varies across regions. Additionally, the study identifies a positive spatial spillover relationship between digital inclusive finance and carbon emissions. Through its pioneering exploration, this study offers fresh insights for boosting digital finance’s carbon-reduction impacts through consumption structure upgrades, strengthening the spatial interconnectedness of digital finance and consumption trends, and eventually supporting a path toward low-carbon, high-quality development.

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“…It has been shown that the growth of national carbon emissions can be curbed to a considerable extent by the development of the digital economy and that reductions in emissions are positively correlated with each country's level of economic development [13]. The impact of the digital economy on carbon emissions is a non-linear inverted "U"-type relationship, and in China, for example, its impact on carbon emissions is mainly in the eastern region, while the impact on the central and western regions is weaker [14]. The digital economy can promote green total factor productivity (GTFP) through green technological innovation, industrial structure upgrading, energy saving, and emission reduction and has a positive spatial spillover effect, which can significantly promote the green development of cities.…”

Section: Introductionmentioning

confidence: 99%

Digital Economy, Clean Energy Consumption, and High-Quality Economic Development: The Case of China

Ren,

Zhang

2023

Sustainability

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The digital economy has become an important force driving China’s socio-economic development. From the perspective of sustainable energy development and based on China’s provincial panel data from 2011 to 2020, this paper probes into the relationship and transmission mechanism of digital economy, clean energy consumption, and high-quality economic development and utilizes the spatial Durbin model and intermediary effect model to carry out empirical tests on the paths of their influence. The results indicate that (1) the digital economy has a significant promoting effect and a positive spatial spillover effect on high-quality economic development, and its influence has obvious spatial heterogeneity; (2) the intermediary effect model validates that clean energy consumption is a mediating variable of digital economy and high-quality economy development, and its conduction effect also has obvious spatial heterogeneity. The research conclusions provide a new perspective and empirical evidence for understanding the relationship between digital economy and high-quality economic development as well as policy implications for the realization of digital transformation and low-carbon development goals.

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The effect of the digital economy on carbon emissions: an empirical study in China

Cited by 15 publications

References 60 publications

High Energy Consumption or Dirty Energy Using? The Driving Factors Behind Carbon Emission in National Supercomputing Centers

High Energy Consumption or Dirty Energy Using? The Driving Factors Behind Carbon Emission in National Supercomputing Centers

Digital inclusive finance, consumption structure upgrading and carbon emissions

Digital Economy, Clean Energy Consumption, and High-Quality Economic Development: The Case of China

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