The impact of digital economy on total factor carbon productivity: the threshold effect of technology accumulation

Han, Dongri; Ding, Yingying; Shi, Ziyi; He, Yao

doi:10.1007/s11356-022-19721-x

Cited by 83 publications

(41 citation statements)

References 30 publications

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“…3. friendliness, thus the rise of digital industries has contributed to carbon emission efficiency (Han et al, 2022). Moreover, the development of the digital industry is the basis for the digitization of traditional industries.…”

Section: Control Variablesmentioning

confidence: 99%

Exploring the Impact of the Digital Economy on Carbon Emission Efficiency Under Factor Misallocation Constraints: New Insights From China

Liu

et al. 2022

Front. Environ. Sci.

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The digital economy has introduced far-reaching innovations in the fields of government governance, enterprise production, and social operation. How to motivate the economic development mode towards a low-carbon and greenway transformation through the digital economy is a major issue concerning the Chinese government. However, there is scarce evidence to interpret the role mechanism of the digital economy on carbon emission efficiency from the factor misallocation scenario. Taking a database from 30 provincial-level administrative regions for the period from 2011 to 2019 in China as an example, the paper examines the effect of the digital economy on carbon emission efficiency, as well as explores its role mechanism deeply in terms of factor misallocation (capital misallocation and labor misallocation). The results suggest that there is a significant potential for the digital economy to contribute to carbon emission efficiency, as well as this finding, is valid when considering both the endogeneity issue and a series of robustness checks. Also, the digital economy can significantly contribute to carbon efficiency in both southern and northern regions, but more strongly in the northern region. Besides, the digital economy can inhibit the factor misallocation (labor misallocation and capital misallocation) level which ultimately improves carbon emission efficiency. Finally, as a digital economy, it can positively impact carbon efficiency in the long run by mitigating factor misallocation (labor misallocation and capital misallocation).

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Section: Control Variablesmentioning

confidence: 99%

Exploring the Impact of the Digital Economy on Carbon Emission Efficiency Under Factor Misallocation Constraints: New Insights From China

Liu

et al. 2022

Front. Environ. Sci.

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“…As a converging economy, the digital economy has become a driving force for highquality development and a new engine to promote industrial structure upgrading [48]. Beijing-Tianjin-Hebei and the Yangtze River Delta are currently the fastest growing digital economy regions in China, where the digital economy has an important impact on promoting industrial upgrading, technological innovation, and improved resource allocation efficiency [72], thus making an important contribution to improving air quality.…”

Section: The Differential Impacts Of Industrial Upgrading On Air Poll...mentioning

confidence: 99%

“…By transforming the economic growth mode and increasing the proportion of the digital industry in GDP, the regional industrial structure can be optimized [45]. Industrial digitalization realizes low consumption and low emissions mainly through the digitalization, intelligence, and clean transformation of the original traditional industry, which directly reduces the emission of air pollution and realizes the synergistic control of multiple pollutants in all aspects [48]. Therefore, it is necessary to improve air quality by accelerating industrial upgrading and promoting the digital economy.…”

Section: Introductionmentioning

confidence: 99%

Has Industrial Upgrading Improved Air Pollution?—Evidence from China’s Digital Economy

Wang

et al. 2022

Sustainability

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Air pollution has seriously hindered China’s sustainable development. The impact mechanism of industrial upgrading on air pollution is still unclear, given the rapid digital economy. It is necessary to analyze the impact of industrial structure upgrading on air pollution through the digital economy. To investigate the impact of industrial upgrading and the digital economy on air pollution, this paper selected the industrial advanced index and the digital economy index to construct a panel regression model to explore the improvement effect of industrial upgrading on air pollution and selected China’s three typical areas to construct a zonal regression model. The concentrations of air pollutants showed a downward trend during 2013–2020. Among them, the SO2 concentration decreased by 63%, which is lower than the PM2.5 and NO2 concentrations. The spatial pattern of air pollutants is heavier in the north than in the south and heavier in the east than in the west, with the North China Plain being the center of gravity. These air pollutants have significant spatial spillover effects, while local spatial correlation is dominated by high-high and low-low clustering. Industrial upgrading has a stronger suppressive effect on the PM2.5 concentration than the suppressive effect on the SO2 and NO2 concentrations, while the digital economy has a stronger improvement effect on the SO2 concentration than its improvement effect on the PM2.5 and NO2 concentrations. Industrial upgrading has a stronger improvement effect on air pollution in the Yangtze River Delta urban agglomeration than in Beijing–Tianjin–Hebei and its surrounding areas, while the improvement in air pollution attributable to the digital economy in Beijing–Tianjin–Hebei and its surrounding areas is stronger than in the Yangtze River Delta urban agglomeration. There are significant differences in the effects of industrial upgrading and the digital economy on the various types of air pollutants.

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“…Many scholars have conducted research on the digital economy. Han and Ding studied the impact of the digital economy on total factor carbon productivity [1]. In the context of COVID-19, Li and Liang examined the impact of the digital economy on the integration of China's cultural tourism industry [2].…”

Section: Introductionmentioning

confidence: 99%

Evaluation of High-quality Development of Shaanxi’s Economy Based on Digital Economy Based on Machine Learning Algorithm

Wang

2022

International Transactions on Electrical Energy Systems

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With the strong development of industrial transformation, the digital economy, as the most dynamic, innovative, and widely radiated economic form at present, has become an important force driving the development of the global economy. Shaanxi Province has accelerated the development of the digital economy, and the development of the province’s digital economy has shown a good trend. However, the current digital economy development measurement is still unable to accurately observe the development law of the digital economy industry, which makes it difficult to measure the control standards for the digital economy industry. Therefore, this study has evaluated the development of digital economy in Shaanxi Province based on machine learning algorithms. This study first puts forward the dimensions of digital economy monitoring and evaluation and then combines the characteristics of digital economy development in Shaanxi Province to determine the quality evaluation indicators of digital economy development. Finally, according to the machine learning algorithm, a quality evaluation model of digital economy development was established, and through the evaluation results, suggestions were put forward for the development plan of digital economy in Shaanxi Province. The experimental results showed that, after re-planning the digital economy in Shaanxi Province according to the evaluation results, the development of the digital economy in Shaanxi Province has increased by 9.82%, indicating that the evaluation model plays a good reference role in the formulation of the digital economy development plan.

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The impact of digital economy on total factor carbon productivity: the threshold effect of technology accumulation

Cited by 83 publications

References 30 publications

Exploring the Impact of the Digital Economy on Carbon Emission Efficiency Under Factor Misallocation Constraints: New Insights From China

Exploring the Impact of the Digital Economy on Carbon Emission Efficiency Under Factor Misallocation Constraints: New Insights From China

Has Industrial Upgrading Improved Air Pollution?—Evidence from China’s Digital Economy

Evaluation of High-quality Development of Shaanxi’s Economy Based on Digital Economy Based on Machine Learning Algorithm

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