Exploring the relationship between digital infrastructure and carbon emission efficiency: New insights from the resource curse and green technology innovation in China
Author
Abstract
Suggested Citation
DOI: 10.1016/j.resourpol.2024.105354
Download full text from publisher
As the access to this document is restricted, you may want to search for a different version of it.
References listed on IDEAS
- Emmanouil Tranos & Aura Reggiani & Peter Nijkamp, 2013. "Accessibility of Cities in the Digital Economy," Tinbergen Institute Discussion Papers 13-160/VIII, Tinbergen Institute.
- Bryan Kelly & Dimitris Papanikolaou & Amit Seru & Matt Taddy, 2021.
"Measuring Technological Innovation over the Long Run,"
American Economic Review: Insights, American Economic Association, vol. 3(3), pages 303-320, September.
- Bryan Kelly & Dimitris Papanikolaou & Amit Seru & Matt Taddy, 2018. "Measuring Technological Innovation over the Long Run," NBER Working Papers 25266, National Bureau of Economic Research, Inc.
- Liangen Zeng & Haiyan Lu & Yenping Liu & Yang Zhou & Haoyu Hu, 2019. "Analysis of Regional Differences and Influencing Factors on China’s Carbon Emission Efficiency in 2005–2015," Energies, MDPI, vol. 12(16), pages 1-21, August.
- Chai, Jian & Tian, Lingyue & Jia, Ruining, 2023. "New energy demonstration city, spatial spillover and carbon emission efficiency: Evidence from China's quasi-natural experiment," Energy Policy, Elsevier, vol. 173(C).
- David Tilson & Kalle Lyytinen & Carsten Sørensen, 2010. "Research Commentary ---Digital Infrastructures: The Missing IS Research Agenda," Information Systems Research, INFORMS, vol. 21(4), pages 748-759, December.
- Zhang, Junjie & Yu, Shiwei & Xiong, Xingyi & Hu, Xing, 2024. "Impacts of ICT penetration shaping nonworking time use on indirect carbon emissions: Evidence from Chinese households," Energy Economics, Elsevier, vol. 129(C).
- Fang, Guochang & Gao, Zhengye & Tian, Lixin & Fu, Min, 2022. "What drives urban carbon emission efficiency? – Spatial analysis based on nighttime light data," Applied Energy, Elsevier, vol. 312(C).
- Schade, Philipp & Schuhmacher, Monika C., 2022. "Digital infrastructure and entrepreneurial action-formation: A multilevel study," Journal of Business Venturing, Elsevier, vol. 37(5).
- Jia, Ruining & Shao, Shuai & Yang, Lili, 2021. "High-speed rail and CO2 emissions in urban China: A spatial difference-in-differences approach," Energy Economics, Elsevier, vol. 99(C).
- Zhang, Wei & Liu, Xuemeng & Wang, Die & Zhou, Jianping, 2022. "Digital economy and carbon emission performance: Evidence at China's city level," Energy Policy, Elsevier, vol. 165(C).
- Bai, Caiquan & Du, Kerui & Yu, Ying & Feng, Chen, 2019. "Understanding the trend of total factor carbon productivity in the world: Insights from convergence analysis," Energy Economics, Elsevier, vol. 81(C), pages 698-708.
- James P. Lesage, 2008. "An Introduction to Spatial Econometrics," Revue d'économie industrielle, De Boeck Université, vol. 0(3), pages 19-44.
- Kevin J. Stiroh & Dale W. Jorgenson, 1999. "Information Technology and Growth," American Economic Review, American Economic Association, vol. 89(2), pages 109-115, May.
- Du, Yanan & Zhou, Jianping & Bai, Jiancheng & Cao, Yujia, 2023. "Breaking the resource curse: The perspective of improving carbon emission efficiency based on digital infrastructure construction," Resources Policy, Elsevier, vol. 85(PB).
- Dongdong Lu & Zilong Wang, 2023. "Towards green economic recovery: how to improve green total factor productivity," Economic Change and Restructuring, Springer, vol. 56(5), pages 3163-3185, October.
- Auty, Richard M., 2007. "Natural resources, capital accumulation and the resource curse," Ecological Economics, Elsevier, vol. 61(4), pages 627-634, March.
- Jiang, Hong & Murmann, Johann Peter, 2022. "The Rise of China's Digital Economy: An Overview," Management and Organization Review, Cambridge University Press, vol. 18(4), pages 790-802, August.
- Wang, Keying & Wu, Meng & Sun, Yongping & Shi, Xunpeng & Sun, Ao & Zhang, Ping, 2019. "Resource abundance, industrial structure, and regional carbon emissions efficiency in China," Resources Policy, Elsevier, vol. 60(C), pages 203-214.
- Heleen L. Soest & Michel G. J. Elzen & Detlef P. Vuuren, 2021. "Net-zero emission targets for major emitting countries consistent with the Paris Agreement," Nature Communications, Nature, vol. 12(1), pages 1-9, December.
- Feng, Yidai & Liu, Yaobin & Yuan, Huaxi, 2022. "The spatial threshold effect and its regional boundary of new-type urbanization on energy efficiency," Energy Policy, Elsevier, vol. 164(C).
- Yiru Guo & Yan Hu & Ke Shi & Yuriy Bilan, 2020. "Valuation of Water Resource Green Efficiency Based on SBM–TOBIT Panel Model: Case Study from Henan Province, China," Sustainability, MDPI, vol. 12(17), pages 1-17, August.
- Song, Malin & Peng, Licheng & Shang, Yuping & Zhao, Xin, 2022. "Green technology progress and total factor productivity of resource-based enterprises: A perspective of technical compensation of environmental regulation," Technological Forecasting and Social Change, Elsevier, vol. 174(C).
- Apergis, Nicholas & Aye, Goodness C. & Barros, Carlos Pestana & Gupta, Rangan & Wanke, Peter, 2015.
"Energy efficiency of selected OECD countries: A slacks based model with undesirable outputs,"
Energy Economics, Elsevier, vol. 51(C), pages 45-53.
- Nicholas Apergis & Goodness C. Aye & Carlos P. Barros & Rangan Gupta & Peter Wanke, 2014. "Energy Efficiency of Selected OECD Countries: A Slacks Based Model with Undesirable Outputs," Working Papers 201477, University of Pretoria, Department of Economics.
- Cheng, Zhonghua & Li, Lianshui & Liu, Jun & Zhang, Huiming, 2018. "Total-factor carbon emission efficiency of China's provincial industrial sector and its dynamic evolution," Renewable and Sustainable Energy Reviews, Elsevier, vol. 94(C), pages 330-339.
- Sun, Jingjing & Zhai, Chenchen & Dong, Xiaoqi & Li, Chengming & Wang, Zeyu & Li, Dandan & Sun, Yongping, 2023. "How does digital infrastructure break the resource curse of cities? Evidence from a quasi-natural experiment in China," Resources Policy, Elsevier, vol. 86(PA).
- Chang, Lei & Shi, Fanglan & Taghizadeh-Hesary, Farhad & Saydaliev, Hayot Berk, 2023. "Information and communication technologies development and the resource curse," Resources Policy, Elsevier, vol. 80(C).
- Corinne Autant‐Bernard & James P. LeSage, 2011.
"Quantifying Knowledge Spillovers Using Spatial Econometric Models,"
Journal of Regional Science, Wiley Blackwell, vol. 51(3), pages 471-496, August.
- Corinne Autant-Bernard & James Lesage, 2009. "Quantifying knowledge spillovers using spatial econometric models," Post-Print hal-00430618, HAL.
- Corinne Autant-Bernard, 2009. "Quantifying knowledge spillovers using spatial econometric models," Post-Print hal-00430626, HAL.
- Yildizbasi, Abdullah, 2021. "Blockchain and renewable energy: Integration challenges in circular economy era," Renewable Energy, Elsevier, vol. 176(C), pages 183-197.
- Hong, Junjie & Shi, Fangyuan & Zheng, Yuhan, 2023. "Does network infrastructure construction reduce energy intensity? Based on the “Broadband China” strategy," Technological Forecasting and Social Change, Elsevier, vol. 190(C).
- Murmann, Johann Peter, 2022. "Forum on ‘The Rise of China's Digital Economy’," Management and Organization Review, Cambridge University Press, vol. 18(4), pages 788-789, August.
- Du, Kerui & Li, Jianglong, 2019. "Towards a green world: How do green technology innovations affect total-factor carbon productivity," Energy Policy, Elsevier, vol. 131(C), pages 240-250.
- Chen, Huanyu & Yi, Jizheng & Chen, Aibin & Peng, Duanxiang & Yang, Jieqiong, 2023. "Green technology innovation and CO2 emission in China: Evidence from a spatial-temporal analysis and a nonlinear spatial durbin model," Energy Policy, Elsevier, vol. 172(C).
- Zhang, Hongyan & Gao, Shuaizhi & Zhou, Peng, 2023. "Role of digitalization in energy storage technological innovation: Evidence from China," Renewable and Sustainable Energy Reviews, Elsevier, vol. 171(C).
- Tone, Kaoru, 2002. "A slacks-based measure of super-efficiency in data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 143(1), pages 32-41, November.
- Wang, Rong & Zameer, Hashim & Feng, Yue & Jiao, Zhilun & Xu, Li & Gedikli, Ayfer, 2019. "Revisiting Chinese resource curse hypothesis based on spatial spillover effect: A fresh evidence," Resources Policy, Elsevier, vol. 64(C).
- Yu, Yantuan & Zhang, Ning, 2021. "Low-carbon city pilot and carbon emission efficiency: Quasi-experimental evidence from China," Energy Economics, Elsevier, vol. 96(C).
- Yacov Y. Haimes & Stan Kaplan & James H. Lambert, 2002. "Risk Filtering, Ranking, and Management Framework Using Hierarchical Holographic Modeling," Risk Analysis, John Wiley & Sons, vol. 22(2), pages 383-397, April.
- Zekić-Sušac, Marijana & Mitrović, Saša & Has, Adela, 2021. "Machine learning based system for managing energy efficiency of public sector as an approach towards smart cities," International Journal of Information Management, Elsevier, vol. 58(C).
- Zhang, Ming & Du, Panpan & Jiang, Lixia, 2023. "Impact of endogenous power factors and price marketization on agricultural energy efficiency: Based on the use of coal and oil energy in China," Resources Policy, Elsevier, vol. 83(C).
- Chen, Yang & Cheng, Liang & Lee, Chien-Chiang, 2022. "How does the use of industrial robots affect the ecological footprint? International evidence," Ecological Economics, Elsevier, vol. 198(C).
- He, Jiankun & Deng, Jing & Su, Mingshan, 2010. "CO2 emission from China's energy sector and strategy for its control," Energy, Elsevier, vol. 35(11), pages 4494-4498.
- Li, Yumei & Naqvi, Bushra & Caglar, Ersin & Chu, Chien-Chi, 2020. "N-11 countries: Are the new victims of resource-curse?," Resources Policy, Elsevier, vol. 67(C).
- Qian, Xiangyan & Wang, Di & Wang, Jia & Chen, Sai, 2021. "Resource curse, environmental regulation and transformation of coal-mining cities in China," Resources Policy, Elsevier, vol. 74(C).
Most related items
These are the items that most often cite the same works as this one and are cited by the same works as this one.- Du, Xiaoyun & Meng, Conghui & Guo, Zhenhua & Yan, Hang, 2023. "An improved approach for measuring the efficiency of low carbon city practice in China," Energy, Elsevier, vol. 268(C).
- Du, Ruijin & Zhang, Nidan & Zhang, Mengxi & Kong, Ziyang & Jia, Qiang & Dong, Gaogao & Tian, Lixin & Ahsan, Muhammad, 2024. "Identifying the optimal node group of carbon emission efficiency correlation network in China based on pinning control theory," Applied Energy, Elsevier, vol. 368(C).
- Kong, Lingqian & Li, Zhaoyang & Liu, Biqian & Xu, Kai, 2024. "The impact of environmental protection tax reform on low-carbon total factor productivity: Evidence from China's fee-to-tax reform," Energy, Elsevier, vol. 290(C).
- Juanjuan Tian & Xiaoqian Song & Jinsuo Zhang, 2022. "Spatial-Temporal Pattern and Driving Factors of Carbon Efficiency in China: Evidence from Panel Data of Urban Governance," Energies, MDPI, vol. 15(7), pages 1-24, March.
- Ruijing Zheng & Yu Cheng & Haimeng Liu & Wei Chen & Xiaodong Chen & Yaping Wang, 2022. "The Spatiotemporal Distribution and Drivers of Urban Carbon Emission Efficiency: The Role of Technological Innovation," IJERPH, MDPI, vol. 19(15), pages 1-22, July.
- Liu, Yang & Wang, Jianda & Dong, Kangyin & Taghizadeh-Hesary, Farhad, 2023. "How does natural resource abundance affect green total factor productivity in the era of green finance? Global evidence," Resources Policy, Elsevier, vol. 81(C).
- Wang, Jianda & Dong, Kangyin & Sha, Yezhou & Yan, Cheng, 2022. "Envisaging the carbon emissions efficiency of digitalization: The case of the internet economy for China," Technological Forecasting and Social Change, Elsevier, vol. 184(C).
- Teng, Yin-Pei, 2023. "Natural resources extraction and sustainable development: Linear and non-linear resources curse hypothesis perspective for high income countries," Resources Policy, Elsevier, vol. 83(C).
- Wen, Yuyuan & Yu, Zilong & Xue, Jingjing & Liu, Yang, 2024. "How heterogeneous industrial agglomeration impacts energy efficiency subject to technological innovation:Evidence from the spatial threshold model," Energy Economics, Elsevier, vol. 136(C).
- Lee, Chien-Chiang & Xuan, Chengnan & Wang, Fuhao, 2024. "Natural resources and green economic growth: The role of artificial intelligence," Resources Policy, Elsevier, vol. 98(C).
- Nie, Song, 2024. "Does intellectual property rights protection matter for low-carbon transition? The role of institutional incentives," Economic Modelling, Elsevier, vol. 140(C).
- Zhuo, Chengfeng & Xie, Yuping & Mao, Yanhua & Chen, Pengqin & Li, Yiqiao, 2022. "Can cross-regional environmental protection promote urban green development: Zero-sum game or win-win choice?," Energy Economics, Elsevier, vol. 106(C).
- Lijie Wei & Zhibao Wang, 2022. "Differentiation Analysis on Carbon Emission Efficiency and Its Factors at Different Industrialization Stages: Evidence from Mainland China," IJERPH, MDPI, vol. 19(24), pages 1-14, December.
- Tang, Zhaopei & Wang, Liehui & Wu, Wei, 2023. "The impact of high-speed rail on urban carbon emissions: Evidence from the Yangtze River Delta," Journal of Transport Geography, Elsevier, vol. 110(C).
- Chai, Jian & Tian, Lingyue & Jia, Ruining, 2023. "New energy demonstration city, spatial spillover and carbon emission efficiency: Evidence from China's quasi-natural experiment," Energy Policy, Elsevier, vol. 173(C).
- Zhou, Tao & Huang, Xuhui & Zhang, Ning, 2023. "The effect of innovation pilot on carbon total factor productivity: Quasi-experimental evidence from China," Energy Economics, Elsevier, vol. 125(C).
- Du, Yanan & Zhou, Jianping & Bai, Jiancheng & Cao, Yujia, 2023. "Breaking the resource curse: The perspective of improving carbon emission efficiency based on digital infrastructure construction," Resources Policy, Elsevier, vol. 85(PB).
- Pan, Minjie & Zhao, Xin & lv, Kangjuan & Rosak-Szyrocka, Joanna & Mentel, Grzegorz & Truskolaski, Tadeusz, 2023. "Internet development and carbon emission-reduction in the era of digitalization: Where will resource-based cities go?," Resources Policy, Elsevier, vol. 81(C).
- Zhu, Chen & Lee, Chien-Chiang, 2022. "The effects of low-carbon pilot policy on technological innovation: Evidence from prefecture-level data in China," Technological Forecasting and Social Change, Elsevier, vol. 183(C).
- Feng Dong & Chang Qin & Xiaoyun Zhang & Xu Zhao & Yuling Pan & Yujin Gao & Jiao Zhu & Yangfan Li, 2021. "Towards Carbon Neutrality: The Impact of Renewable Energy Development on Carbon Emission Efficiency," IJERPH, MDPI, vol. 18(24), pages 1-23, December.
More about this item
Keywords
Digital infrastructure; Carbon emission efficiency; Resource curse; Lag and spillover effects; Threshold boundary;All these keywords.
Statistics
Access and download statisticsCorrections
All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:jrpoli:v:98:y:2024:i:c:s0301420724007219. See general information about how to correct material in RePEc.
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/inca/30467 .
Please note that corrections may take a couple of weeks to filter through the various RePEc services.