The impact of digital finance on pollutants emission: evidence from Chinese cities
Abstract
This paper investigates whether emerging digital finance can reduce environmental pollution in China based on data from 273 of China's prefecture-level cities spanning the period from 2010 to 2017. The dynamic spatial econometric models (DSDM) find a significant negative association between digital finance and pollutants emissions, and the impacts vary among regions and urban development stages. The impact mechanism test proves that digital finance reduces pollutants emissions through technological innovation, structural adjustment, and capital allocation effects. In addition, we explore the different dimensions of digital finance and find that the depth of use has a more practical effect on reducing emissions. Further analyses based on the threshold model show an inverted N-shaped nexus between digital finance and emissions. The threshold effect also exists in terms of the traditional financial level. Our study proves that emerging digital finance crucially affects its potential benefits to environment and provides an empirical basis for policy-makers to accelerate the digitalization of financial markets, particularly paying attention to its emission-reduction effects.
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Evidence of inverted N-shaped relationships was found for a total of two associations in the cases of Turkey [102] and China [89].
“Evidence of other forms of nonlinear relationships (inverted N-shaped relationships in particular) were found for a total of two associations in the cases of Turkey [102] and China [89].”
From ICT sector, digitization and environmental sustainability: A systematic review of the literature from 2000 to 2022 (2023) · cites this paper as [89]
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- Authors
- Wan, J., Pu, Z., & Tavera, C.
- Affiliations
- Southeast University (CN)
- Corresponding author
- Pu, Zhengning
- ORCID
- Pu, Zhengning
- Venue
- Environmental Science and Pollution Research
- Published
- 2022-01-21
- Volume
- 30
- Issue
- 15
- Pages
- 42923-42942
- ISSN
- 0944-1344 (ISSN-L)
- 1614-7499
- OpenAlex
- W4206997570
- Cited by
- 75
- References
- 44
- Citations by year
- 2026: 1 · 2025: 11 · 2024: 19 · 2023: 29 · 2022: 15
- FWCI
- 14.88
- Type
- journal article
- Language
- en
- Open access
- closed
- Licence
- Locations
- Environmental Science and Pollution Research (publishedVersion)
- PubMed (publishedVersion)
- HAL (submittedVersion)
- Topics
- Social Sciences › Economics, Econometrics and Finance › Economics and Econometrics › Energy, Environment, Economic Growth
- Social Sciences › Business, Management and Accounting › Management Information Systems › FinTech, Crowdfunding, Digital Finance
- Social Sciences › Economics, Econometrics and Finance › General Economics, Econometrics and Finance › Digital Transformation in Financial Services
- Keywords
- digital finance, pollutant emissions, environmental pollution, technological innovation, structural adjustment, capital allocation, financial depth, threshold effects, financial development, urban development stages, Chinese cities
- MeSH terms
- China, Cities, Environmental Pollutants, Environmental Pollution, Models, Econometric, Economic Development
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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