Abstract
Digital infrastructure construction (DIC) and low-carbon transformation are important engines and objective functions of the superior economic development, and the synergistic drive between the two is essential to achieving lasting economic development. Based on the panel data of 279 cities in China between 2007 and 2019, the econometric model system is used to explore the impact mechanism of DIC on carbon total factor productivity (CTFP), and the impact of DIC on carbon rebound effect (CRE) is further studied. Research findings that, first, the expansion of DIC has a nonlinear effect on CTFP, with a U-shaped link between the two; multiple robustness tests confirm that this is still true. Second, DIC and optimization of the energy consumption structure in a “U” curve relationship, and the major strategy for increasing CTFP is to reduce energy consumption, while industrial structure optimization and technical innovation have less of a intermediary effect. Third, further analysis reveals that there is a “U” shaped nonlinear connection between the DIC and the CRE, and energy savings and emission reductions in the later stages of DIC fall short of expectations. The current DIC is still dominated by episodic expansion. The findings of the study can better enhance CTFP, curb the CRE, put a limit on total carbon emissions and accelerate the decoupling of economic growth from carbon emissions.
This is a preview of subscription content, log in via an institution to check access.
Similar content being viewed by others
Data availability
The data sets supporting the results of this article are included within the article and its additional files.
Notes
Data source: Digital China Development Report (2022) released at the opening ceremony of the 6th Digital China Construction Summit.
Abbreviations:
DICdigital infrastructure construction
CTFPcarbon total factor productivity
CREcarbon dioxide rebound effects
Data source: China Carbon Emissions Database (CEADs) and BP World Energy Statistics Yearbook 2021.
References
Ahmad M, Chandio AA, Solangi YA, Shah SAA, Shahzad F, Rehman A, Jabeen G (2021) Dynamic interactive links among sustainable energy investment, air pollution, and sustainable development in regional China. Environ Sci Pollut Res Int 28:1502–1518. https://doi.org/10.1007/s11356-020-10239-8
Arellano M, Bover O (1995) Another look at the instrumental variable estimation of error-components models. J Econ 68(1):29–51. https://doi.org/10.1016/0304-4076(94)01642
Armstrong K (2014) Big data: a revolution that will transform how we live, work, and think. Inf Commun Soc 17:1300–1302. https://doi.org/10.1080/1369118X.2014.923482
Aydin E, Brounen D, Kok N (2018) Information provision and energy consumption: evidence from a field experiment. En Econ 71:403–410. https://doi.org/10.1016/j.eneco.2018.03.008
Bao Z, Zhou X, Li G (2022) Does the internet promote green total factor productivity? Empirical evidence from China. Pol J Environ Stud 31:1037–1048. https://doi.org/10.15244/pjoes/141806
Berkhout F, Hertin J (2004) De-materialising and re-materialising: digital technologies and the environment. Futures 36:903–920. https://doi.org/10.1016/j.futures.2004.01.003
Bottazzi L, Peri G (2003) Innovation and spillovers in regions: evidence from European patent data. Eur Econ Rev 47:687–710. https://doi.org/10.2139/ssrn.318920
Chen C, Pinar M, Stengos T (2020) Renewable energy consumption and economic growth nexus: evidence from a threshold model. En Pol 139:111295. https://doi.org/10.1016/j.enpol.2020.111295
Chen Z, Song P, Wang B (2021) Carbon emissions trading scheme, energy efficiency and rebound effect - evidence from China’s provincial data. En Pol 157:1–11. https://doi.org/10.1016/j.enpol.2021.112507
Freund CL, Weinhold D (2004) The effect of the Internet on international trade. J Int Econ 62(1):171–189. https://doi.org/10.1080/09638199.2014.881906
Greening LA, Greene DL, Difiglio C (2000) Energy efficiency and consumption – the rebound effect – a survey. Energy Policy 28:389–401. https://doi.org/10.1016/S0301-4215(00)00021-5
Han D, Ding YY (2022) The impact of digital economy on total factor carbon productivity: the threshold effect of technology accumulation. Environ Sci Pollut Res 29:55691–55706. https://doi.org/10.1007/s11356-022-19721
Hong JP (2017) Causal relationship between ICT R&D investment and economic growth in Korea. Technol Forecast Soc Chang 116:70–75. https://doi.org/10.1016/j.techfore.2016.11.005
Johnson JS, Friend SB, Lee HS (2017) Big data facilitation, utilization, and monetization: exploring the 3Vs in a new product development process. J Prod Innov Manag 34:640–658. https://doi.org/10.1111/jpim.12397
Kais S, Hassen T, Saida Z (2017) Impact of information communication technology and economic growth on the electricity consumption: empirical evidence from 67 countries. J Knowl Econ 8:789–803. https://doi.org/10.1007/s13132-015-0276-1
Lyu K, Yang S (2023) How does the digital economy affect carbon emission efficiency? Evidence from energy consumption and industrial value chain. Energies 16(2):761. https://doi.org/10.3390/en16020761
Khazzoom JD (1980) Economic implications of mandated efficiency standards for household appliances. Energy 1:21–40. https://doi.org/10.5547/issn0195-6574-ej-vol1-no4-2
Koutroumpis P, Leiponen A, Thomas LDW (2020) Small is big in ICT: the impact of R&D on productivity. Telecommunication. Policy 44(1). https://doi.org/10.1016/j.telpol.2019.101833
Lange S, Pohl J, Santarius T (2020) Digitalization and energy consumption: does ICT reduce energy demand? Ecol Econ 176:106760. https://doi.org/10.1016/j.ecolecon.2020.106760
Li KJ, Dong DD, Han YF (2020) The analysis on the environmental performance of green innovation an examination based on spatial spillover effect and rebound effect. China Soft Science 7:112–121 (in Chinese)
Li Y, Yang X, Ran Q, Wu H, Irfan M, Ahmad M (2021) Energy structure, digital economy, and carbon emissions: evidence from China. Environ Sci Pollut Res 28:64606–64629. https://doi.org/10.1007/s11356-021-15304-4
Madden G, Savage SJ (2000) Telecommunications and economic growth. Int J Soc Econ 27:893–906. https://doi.org/10.1108/03068290010336397
Mitra A, Sharma C, Veganzones-varoudakis M (2016) Infrastructure, information & communication technology and firms’ productive performance of the Indian manufacturing. J Policy Model 38:353–371. https://doi.org/10.1016/j.jpolmod.2016.02.013
Moyer JD, Hughes BB (2012) ICTs: Do they contribute to increased carbon emissions. Technol Forecast Soc Chang 79(5):919–931
Nakatani R (2021) Total factor productivity enablers in the ICT industry: a cross-country firm-level analysis. Telecommunication. Policy 45(9). https://doi.org/10.1016/j.telpol.2021.102188
Ndubuisi G, Otioma C, Tetteh GK (2021) Digital infrastructure and employment in services: evidence form Sub-Saharan African countries. Telecoummuications Policy 45(8):1021153. https://doi.org/10.1016/j.telpol.2021.102153
Paunov C, Rollo V (2016) Has the Internet fostered inclusive innovation in the developing world? World Dev 78:587–609. https://doi.org/10.1016/j.worlddev.2015.10.029
Salahuddin M, Alam K (2015) Internet usage, electricity consumption and economic growth in Australia: a time series evidence. Telematics Inform 32:862–878. https://doi.org/10.1016/j.tele.2015.04.011
Shin DH, Choi MJ (2015) Ecological views of big data: perspectives and issues. Telematics Inform 32:311–320. https://doi.org/10.1016/j.tele.2014.09.006
Sun J (2020) From digital economy to digital trade: connotations, features, rule setting and impacts. Int Econ Trade Res 36(05):87–98
Wang HY, Wang JC, Jin ZD (2023) How ICT development affects manufacturing carbon emissions: theoretical and empirical evidence. Environ Sci Pollut Res 30(12):33674–33685. https://doi.org/10.1007/s11356-022-24581-6
Wu LP, Chen Y, Feylizadeh MR, Liu WJ (2018) Estimation of China’s macro-carbon rebound effect: method of integrating data envelopment analysis production model and sequential Malmquist-Luenberger index. J Clean Prod 198:1431–1442. https://doi.org/10.1016/j.jclepro.2018.07.034
Xu B, Chen Y, Shen X (2019) The clean energy development, carbon dioxide emission reduction and regional economic growth. Econ Res 54:188–202 (in Chinese)
Xue F, Liu JQ, Fu YM (2022) The effect of artificial intelligence technology on carbon emission. Sci Technol Stud 7:1–9 (in Chinese)
Yang L, Li Z (2017) Technology advance and the carbon dioxide emission in China-empirical research based on the rebound effect. En Pol 101:150–161. https://doi.org/10.1016/j.enpol.2016.11.020
Zhang X, Wan GH, Zhang JJ, He ZY (2019) Digital economy, financial inclusion, and inclusive growth. Econ Res 54:71–86 (in Chinese)
Zhang W, Zhao SQ, Wan XY, Yao Y (2021) Study on the effect of digital economy on high-quality economic development in China. PLoS One 16(9). https://doi.org/10.1371/journal.pone.0257365
Tao Z, Zhi Z, Shangkun L (2020) Digital economy, entrepreneurship, and high-quality economic development: empirical evidence from urban China. Manag World 36:65–76 (in Chinese)
Funding
This work was supported by the Major Project of Research on Philosophy and Social Science in Higher Education Institutions in Hubei Province [21ZD010], the Youth Project of Hunan Provincial Philosophy and Social Science Foundation [21YBQ079], the General Project of Hunan Provincial Philosophy and Social Science Foundation [19YBA333].
Author information
Authors and Affiliations
Contributions
All authors contributed the conception and design of this study. The empirical work and the manuscript’s first draft were performed by Mudan Lan and Yuke Zhu. The conceptualization and funding supporting were provided by Yuke Zhu. The methodology guidance and software supporting were provided by Mudan Lan and Yuke Zhu; the project administration and funding acquisition were provided by Yuke Zhu. All authors read and approved the final manuscript.
Corresponding author
Ethics declarations
Ethics approval
Not applicable.
Consent to participate
Not applicable.
Consent for publish
Not applicable.
Competing interests
The authors declare no competing interests.
Additional information
Responsible Editor: Ilhan Ozturk
Publisher’s note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
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
Lan, ., Zhu, Y. Digital infrastructure construction, carbon total factor productivity, and carbon rebound effect. Environ Sci Pollut Res 30, 88968–88985 (2023). https://doi.org/10.1007/s11356-023-28738-9
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s11356-023-28738-9