Abstract
Achieving the synergistic reduction of CO2 and air pollution emissions (SRCAPEs) holds great significance in promoting the green transformation. However, limited research has been conducted on the spatio-temporal impact of digital inclusive finance (DIF) on the synergy between CO2 and air pollution emissions (SCAPEs). To address this gap, we comprehensively employ the linear regression model, geographically and the temporally weighted regression (GTWR) model, and the ordered probit model to empirically analyze the influence of DIF on SCAPE. Our research reveals the following: (1) The linear regression model demonstrates that, on average, DIF can achieve a weak synergistic emission reduction effect. This result remains robust after a battery of robustness tests. (2) The GTWR model reveals that the impact of DIF on both emissions exhibits evident spatio-temporal characteristics. Its emission reduction effect gradually increases, especially after 2014. (3) On the basis of the estimates from the GTWR model, we can identify four distinct synergy types driven by DIF. The number of cities with the preferred type (i.e., achieving SRCAPE) increases the most, from 59 in 2011 to 233 in 2019. (4) On the basis of the built ordered probit models, green technology innovation is an important path for DIF to achieve synergistic emission reduction. The synergistic emission reduction effect is also significantly moderated by the regional economic level and environmental regulation intensity. Our findings have policy implications for central and local governments in achieving SRCAPE and support efforts to achieve sustainable development.
Similar content being viewed by others
Data Availability
The data can be requested from the authors.
References
Abbasi F, Riaz K (2016) CO2 emissions and financial development in an emerging economy: an augmented VAR approach. Energy Policy 90:102–114. https://doi.org/10.1016/j.enpol.2015.12.017
Acemoglu D (2002) Directed technical change. Rev Econ Stud 69:781–809. https://doi.org/10.1111/1467-937X.00226
Acemoglu D, Aghion P, Bursztyn L, Hemous D (2012) The environment and directed technical change. Am Econ Rev 102:131–166. https://doi.org/10.1257/aer.102.1.131
Brunsdon C, Fotheringham AS, Charlton ME (1996) Geographically weighted regression: a method for exploring spatial nonstationarity. Geogr Anal 28:281–298. https://doi.org/10.1111/j.1538-4632.1996.tb00936.x
Cao S, Nie L, Sun H et al (2021) Digital finance, green technological innovation and energy-environmental performance: Evidence from China’s regional economies. J Clean Prod 327:129458. https://doi.org/10.1016/j.jclepro.2021.129458
Charfeddine L, Ben Khediri K (2016) Financial development and environmental quality in UAE: cointegration with structural breaks. Renew Sustain Energy Rev 55:1322–1335. https://doi.org/10.1016/j.rser.2015.07.059
Chen Z, Kahn ME, Liu Y, Wang Z (2018) The consequences of spatially differentiated water pollution regulation in China. J Environ Econ Manag 88:468–485. https://doi.org/10.1016/j.jeem.2018.01.010
Chen J, Gao M, Cheng S et al (2021) China’s city-level carbon emissions during 1992–2017 based on the inter-calibration of nighttime light data. Sci Rep 11:3323. https://doi.org/10.1038/s41598-021-81754-y
Chen J, Abbas J, Najam H et al (2023) Green technological innovation, green finance, and financial development and their role in green total factor productivity: empirical insights from China. J Clean Prod 382:135131. https://doi.org/10.1016/j.jclepro.2022.135131
Chen Z, Yu B, Yang C et al (2021) An extended time series (2000–2018) of global NPP-VIIRS-like nighttime light data from a cross-sensor calibration. Earth Syst Sci Data 13(3):889–906
Chu H, Yu H, Chong Y, Li L (2023) Does the development of digital finance curb carbon emissions? Evidence from county data in China. Environ Sci Pollut Res 30:49237–49254. https://doi.org/10.1007/s11356-023-25659-5
De Haas R, Popov A (2023) Finance and green growth. Econ J 133:637–668
Dong F, Yu B, Pan Y (2019) Examining the synergistic effect of CO2 emissions on PM2.5 emissions reduction: evidence from China. J Clean Prod 223:759–771. https://doi.org/10.1016/j.jclepro.2019.03.152
Dong Z, Xia C, Fang K, Zhang W (2022) Effect of the carbon emissions trading policy on the co-benefits of carbon emissions reduction and air pollution control. Energy Policy 165:112998. https://doi.org/10.1016/j.enpol.2022.112998
Du K, Li J (2019) Towards a green world: How do green technology innovations affect total-factor carbon productivity. Energy Policy 131:240–250. https://doi.org/10.1016/j.enpol.2019.04.033
Du M, Hou Y, Zhou Q, Ren S (2022) Going green in China: how does digital finance affect environmental pollution? Mechanism discussion and empirical test. Environ Sci Pollut Res 29:89996–90010. https://doi.org/10.1007/s11356-022-21909-0
Feng Y, Ning M, Lei Y et al (2019) Defending blue sky in China: effectiveness of the “air pollution prevention and control action plan” on air quality improvements from 2013 to 2017. J Environ Manage 252:109603. https://doi.org/10.1016/j.jenvman.2019.109603
Feng S, Zhang R, Li G (2022) Environmental decentralization, digital finance and green technology innovation. Struct Chang Econ Dyn 61:70–83
Friedlingstein P, Jones MW, O’Sullivan M (2022) Global Carbon Budget 2022. Earth Syst Sci Data 14:1917–2005
Geng G, Zheng Y, Zhang Q et al (2021) Drivers of PM2. 5 air pollution deaths in China 2002–2017. Nat Geosci 14:645–650
Greenstone M, He G, Li S, Zou EY (2021) China’s war on pollution: evidence from the first 5 years. Rev Environ Econ Policy 15:281–299
Gu A, Teng F, Feng X (2018) Effects of pollution control measures on carbon emission reduction in China: evidence from the 11th and 12th Five-Year Plans. Climate Policy 18:198–209. https://doi.org/10.1080/14693062.2016.1258629
Guan D, Meng J, Reiner DM et al (2018) Structural decline in China’s CO2 emissions through transitions in industry and energy systems. Nat Geosci 11:551–555
Guo F, Wang J, Wang F et al (2020) Measuring China’s digital financial inclusion: index compilation and spatial characteristics. China Econ Q 19:1401–1418
Hammer MS, van Donkelaar A, Li C et al (2020) Global estimates and long-term trends of fine particulate matter concentrations (1998–2018). Environ Sci Technol 54:7879–7890. https://doi.org/10.1021/acs.est.0c01764
Hao Y, Wang C, Yan G et al (2023) Identifying the nexus among environmental performance, digital finance, and green innovation: New evidence from prefecture-level cities in China. J Environ Manage 335:117554. https://doi.org/10.1016/j.jenvman.2023.117554
He J, Gong S, Yu Y et al (2017) Air pollution characteristics and their relation to meteorological conditions during 2014–2015 in major Chinese cities. Environ Pollut 223:484–496. https://doi.org/10.1016/j.envpol.2017.01.050
He N, Zeng S, Jin G (2023) Achieving synergy between carbon mitigation and pollution reduction: does green finance matter? J Environ Manage 342:118356. https://doi.org/10.1016/j.jenvman.2023.118356
Hottenrott H, Peters B (2012) Innovative capability and financing constraints for innovation: more money, more innovation? Rev Econ Stat 94:1126–1142
Huang B, Wu B, Barry M (2010) Geographically and temporally weighted regression for modeling spatio-temporal variation in house prices. Int J Geogr Inf Sci 24:383–401. https://doi.org/10.1080/13658810802672469
Ji W, Zhao K, Zhao B (2022) The trend of natural ventilation potential in 74 Chinese cities from 2014 to 2019: Impact of air pollution and climate change. Build Environ 218:109146. https://doi.org/10.1016/j.buildenv.2022.109146
Jia W, Li L, Lei Y et al (2023) Synergistic effect of CO2 and PM2 5. emissions from coal consumption and the impacts on health effects. J Environ Manage 325:116535
Le T-H, Le H-C, Taghizadeh-Hesary F (2020) Does financial inclusion impact CO2 emissions? Evid Asia Financ Res Lett 34:101451. https://doi.org/10.1016/j.frl.2020.101451
Lee C-C, Wang F (2022) How does digital inclusive finance affect carbon intensity? Econ Anal Policy 75:174–190. https://doi.org/10.1016/j.eap.2022.05.010
Lee C-C, Wang F, Lou R (2022) Digital financial inclusion and carbon neutrality: evidence from non-linear analysis. Resour Policy 79:102974. https://doi.org/10.1016/j.resourpol.2022.102974
Levine O, Warusawitharana M (2021) Finance and productivity growth: firm-level evidence. J Monet Econ 117:91–107. https://doi.org/10.1016/j.jmoneco.2019.11.009
Li P, Guo T (2022) Is digital finance a powerful means for Chinese cities to reduce environmental pollution in the fourth industrial revolution? Technol Anal Strateg Manage. https://doi.org/10.1080/09537325.2022.2137398
Li J, Wu Y, Xiao JJ (2020a) The impact of digital finance on household consumption: evidence from China. Econ Model 86:317–326. https://doi.org/10.1016/j.econmod.2019.09.027
Li Y, Cui Y, Cai B et al (2020) Spatial characteristics of CO2 emissions and PM2.5 concentrations in China based on gridded data. Appl Energy 266:114852. https://doi.org/10.1016/j.apenergy.2020.114852
Li L, Mi Y, Lei Y et al (2022) The spatial differences of the synergy between CO2 and air pollutant emissions in China’s 296 cities. Sci Total Environ 846:157323. https://doi.org/10.1016/j.scitotenv.2022.157323
Lin B, Ma R (2022a) How does digital finance influence green technology innovation in China? Evidence from the financing constraints perspective. J Environ Manage 320:115833. https://doi.org/10.1016/j.jenvman.2022.115833
Lin B, Ma R (2022b) Green technology innovations, urban innovation environment and CO2 emission reduction in China: Fresh evidence from a partially linear functional-coefficient panel model. Technol Forecast Soc 176:121434. https://doi.org/10.1016/j.techfore.2021.121434
Liu J-Y, Woodward RT, Zhang Y-J (2021a) Has carbon emissions trading reduced PM 2.5 in China? Environ Sci Technol 55:6631–6643. https://doi.org/10.1021/acs.est.1c00248
Liu Y, Luan L, Wu W et al (2021b) Can digital financial inclusion promote China’s economic growth? Int Rev Financ Anal 78:101889. https://doi.org/10.1016/j.irfa.2021.101889
Liu X, Chong Y, Di D, Li G (2023) Digital financial development, synergistic reduction of pollution, and carbon emissions: evidence from biased technical change. Environ Sci Pollut Res 30:109671–109690. https://doi.org/10.1007/s11356-023-29961-0
Nasreen S, Anwar S (2015) The impact of economic and financial development on environmental degradation: an empirical assessment of EKC hypothesis. Stud Econ Financ 32:485–502. https://doi.org/10.1108/SEF-07-2013-0105
Nunn N, Qian N (2014) US food aid and civil conflict. Am Econ Rev 104:1630–1666
Ozili PK (2018) Impact of digital finance on financial inclusion and stability. Borsa Istanbul Rev 18:329–340. https://doi.org/10.1016/j.bir.2017.12.003
Pu Z, Fei J (2022) The impact of digital finance on residential carbon emissions: Evidence from China. Struct Chang Econ Dyn 63:515–527
Renzhi N, Baek YJ (2020) Can financial inclusion be an effective mitigation measure? evidence from panel data analysis of the environmental Kuznets curve. Financ Res Lett 37:101725. https://doi.org/10.1016/j.frl.2020.101725
Sarma M, Pais J (2011) Financial Inclusion and Development. J Int Dev 23:613–628
Shahbaz M, Li J, Dong X, Dong K (2022) How financial inclusion affects the collaborative reduction of pollutant and carbon emissions: the case of China. Energ Econ 107:105847. https://doi.org/10.1016/j.eneco.2022.105847
Shan Y, Guan Y, Hang Y et al (2022) City-level emission peak and drivers in China. Sci Bull 67:1910–1920. https://doi.org/10.1016/j.scib.2022.08.024
Shi F, Ding R, Li H, Hao S (2022a) Environmental regulation, digital financial inclusion, and environmental pollution: an empirical study based on the spatial spillover effect and panel threshold effect. Sustainability 14(11):6869
Shi Q, Zheng B, Zheng Y et al (2022b) Co-benefits of CO2 emission reduction from China’s clean air actions between 2013–2020. Nat Commun 13:5061. https://doi.org/10.1038/s41467-022-32656-8
Sun Y, Tang X (2022) The impact of digital inclusive finance on sustainable economic growth in China. Financ Res Lett 50:103234. https://doi.org/10.1016/j.frl.2022.103234
Wan J, Pu Z, Tavera C (2022) The impact of digital finance on pollutants emission: evidence from chinese cities. Environ Sci Pollut Res. https://doi.org/10.1007/s11356-021-18465-4
Wang H, Guo J (2022) Impacts of digital inclusive finance on CO2 emissions from a spatial perspective: evidence from 272 cities in China. J Clean Prod 355:131618. https://doi.org/10.1016/j.jclepro.2022.131618
Wang L, Niu D, Fan H (2022) Urban configuration and PM2.5 concentrations: evidence from 330 Chinese cities. Environ Int 161:107129
Wang X, Wang X, Ren X, Wen F (2022b) Can digital financial inclusion affect CO2 emissions of China at the prefecture level? Evidence from a spatial econometric approach. Energ Econ 109:105966. https://doi.org/10.1016/j.eneco.2022.105966
Wang H, Gu K, Sun H, Xiao H (2023) Reconfirmation of the symbiosis on carbon emissions and air pollution: a spatial spillover perspective. Sci Total Environ 858:159906. https://doi.org/10.1016/j.scitotenv.2022.159906
Yan B, Wang F, Chen T et al (2023) Digital finance, environmental regulation and emission reduction in manufacturing industry: new evidence incorporating dynamic spatial-temporal correlation and competition. Int Rev Econ Financ 83:750–763. https://doi.org/10.1016/j.iref.2022.10.025
Yang L, Wang L, Ren X (2022) Assessing the impact of digital financial inclusion on PM2.5 concentration: evidence from China. Environ Sci Pollut R 29:22547–22554. https://doi.org/10.1007/s11356-021-17030-3
Yao S, Dong Z, Zhang Z (2023) How digital finance affects environmental pollution management: evidence from China. Environ Sci Pollut Res 30:105231–105246. https://doi.org/10.1007/s11356-023-29787-w
Yi M, Wang Y, Sheng M et al (2020) Effects of heterogeneous technological progress on haze pollution: evidence from China. Ecol Econ 169:106533. https://doi.org/10.1016/j.ecolecon.2019.106533
Yi H, Zhao L, Qian Y et al (2022) How to achieve synergy between carbon dioxide mitigation and air pollution control? Evidence from China. Sustain Cities Soc 78:103609. https://doi.org/10.1016/j.scs.2021.103609
Yuan S, Musibau HO, Genç SY et al (2021) Digitalization of economy is the key factor behind fourth industrial revolution: How G7 countries are overcoming with the financing issues? Technol Forecast Soc Chang 165:120533. https://doi.org/10.1016/j.techfore.2020.120533
Zhang M, Liu Y (2022) Influence of digital finance and green technology innovation on China’s carbon emission efficiency: empirical analysis based on spatial metrology. Sci Total Environ 838:156463. https://doi.org/10.1016/j.scitotenv.2022.156463
Zhang F, Deng X, Phillips F et al (2020) Impacts of industrial structure and technical progress on carbon emission intensity: evidence from 281 cities in China. Technol Forecast Soc Chang 154:119949. https://doi.org/10.1016/j.techfore.2020.119949
Zhang R, Wu K, Cao Y, Sun H (2023) Digital inclusive finance and consumption-based embodied carbon emissions: a dual perspective of consumption and industry upgrading. J Environ Manage 325:116632. https://doi.org/10.1016/j.jenvman.2022.116632
Zhang L, Ren Z, Chen B et al (2021) A prolonged artificial nighttime-light dataset of China (1984–2020). National Tibetan Plateau Data Center: Beijing, China
Zheng H, Li X (2022) The impact of digital financial inclusion on carbon dioxide emissions: empirical evidence from Chinese provinces data. Energy Rep 8:9431–9440. https://doi.org/10.1016/j.egyr.2022.07.050
Zhou Y, Zhang C, Li Z (2023) The impact of digital financial inclusion on household carbon emissions: evidence from China. J Econ Struct 12:2. https://doi.org/10.1186/s40008-023-00296-w
Zhu J, Wu S, Xu J (2023) Synergy between pollution control and carbon reduction: China’s evidence. Energy Econ 119:106541. https://doi.org/10.1016/j.eneco.2023.106541
Funding
This study received the financial support from the Natural Science Foundation of China (Grant number [72004093]).
Author information
Authors and Affiliations
Contributions
LX: Conceptualization, methodology, writing (review and editing), and funding acquisition.
ZC: Data Curation, methodology, visualization, and writing—original draft.
Corresponding author
Ethics declarations
Ethical approval
Not applicable.
Consent to participate
Not applicable.
Consent to publish
All the authors are in agreement with the publisher.
Competing interests
The authors declare no competing interests.
Additional information
Responsible Editor: Nicholas Apergis
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Supplementary Information
Below is the link to the electronic supplementary material.
Rights and permissions
Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.
About this article
Cite this article
Xing, L., Chen, Z. Spatio-temporal effects of digital inclusive finance on the synergy between CO2 and air pollution emissions in 251 Chinese cities. Environ Sci Pollut Res 31, 12301–12320 (2024). https://doi.org/10.1007/s11356-024-31988-w
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s11356-024-31988-w