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How does artificial intelligence promote renewable energy development? The role of climate finance

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  • Zhao, Congyu
  • Dong, Kangyin
  • Wang, Kun
  • Nepal, Rabindra

Abstract

Scholars, stakeholders, and the government have given significant attention to the development of renewable energy in recent times. However, previous research has failed to acknowledge the potential impact of artificial intelligence on advancing renewable energy development. Drawing insights from a global dataset encompassing 63 countries over the period 2000–2019, this paper provides significant observations regarding the influence of artificial intelligence on the progress of renewable energy, by using the Instrumental Variable Generalized Method of Moments model. We also explore their asymmetric nexus, and the potential mediation effect. Moreover, this study explores the moderating role of climate finance and highlights the following interesting findings. First, artificial intelligence contributes significantly to the enhanced development of renewable energy, and this primary finding holds after two robustness tests of changing independent and dependent variables. Second, artificial intelligence has an asymmetric effect on renewable energy development, and their nexus is closer in countries with lower levels of renewable energy development. Thid, artificial intelligence works on renewable energy development through technology effect and innovation effect. Fourth, climate finance also presents direct benefits to renewable energy development; simultaneously, climate finance plays an effective moderating role in the relationship between artificial intelligence and renewable energy development. These findings inspire us to propose policy implications to promote the enhanced development of renewable energy.

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  • Zhao, Congyu & Dong, Kangyin & Wang, Kun & Nepal, Rabindra, 2024. "How does artificial intelligence promote renewable energy development? The role of climate finance," Energy Economics, Elsevier, vol. 133(C).
    • Handle: RePEc:eee:eneeco:v:133:y:2024:i:c:s0140988324002019
    DOI: 10.1016/j.eneco.2024.107493
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    as
    1. Khan, Zeeshan & Ali, Shahid & Dong, Kangyin & Li, Rita Yi Man, 2021. "How does fiscal decentralization affect CO2 emissions? The roles of institutions and human capital," Energy Economics, Elsevier, vol. 94(C).
    2. Wang, Jianlong & Wang, Weilong & Liu, Yong & Wu, Haitao, 2023. "Can industrial robots reduce carbon emissions? Based on the perspective of energy rebound effect and labor factor flow in China," Technology in Society, Elsevier, vol. 72(C).
    3. Sinha, Avik & Ghosh, Vinit & Hussain, Nazim & Nguyen, Duc Khuong & Das, Narasingha, 2023. "Green financing of renewable energy generation: Capturing the role of exogenous moderation for ensuring sustainable development," Energy Economics, Elsevier, vol. 126(C).
    4. Zhao, Jinsong & Zhou, Boxu & Li, Xinrui, 2022. "Do good intentions bring bad results? Climate finance and economic risks," Finance Research Letters, Elsevier, vol. 48(C).
    5. Alfonso Carfora & Monica Ronghi & Giuseppe Scandurra, 2017. "The effect of Climate Finance on Greenhouse Gas Emission: A Quantile Regression Approach," International Journal of Energy Economics and Policy, Econjournals, vol. 7(1), pages 185-199.
    6. Li, Juan & Ma, Shaoqi & Qu, Yi & Wang, Jiamin, 2023. "The impact of artificial intelligence on firms’ energy and resource efficiency: Empirical evidence from China," Resources Policy, Elsevier, vol. 82(C).
    7. Kafle, K. & Uprety, Labisha & Shrestha, Gitta & Pandey, V. & Mukherji, Aditi, 2022. "Are climate finance subsidies equitably distributed among farmers? Assessing socio-demographics of solar irrigation in Nepal," Papers published in Journals (Open Access), International Water Management Institute, pages 1-91:102756.
    8. Li, Chengming & Xu, Yang & Zheng, Hao & Wang, Zeyu & Han, Haiting & Zeng, Liangen, 2023. "Artificial intelligence, resource reallocation, and corporate innovation efficiency: Evidence from China's listed companies," Resources Policy, Elsevier, vol. 81(C).
    9. Zhao, Congyu & Wang, Kun & Dong, Xiucheng & Dong, Kangyin, 2022. "Is smart transportation associated with reduced carbon emissions? The case of China," Energy Economics, Elsevier, vol. 105(C).
    10. Ströbel, Johannes & Wurgler, Jeffrey, 2021. "What do you think about climate finance?," CEPR Discussion Papers 16622, C.E.P.R. Discussion Papers.
    11. Liu, Yang & Dong, Kangyin & Taghizadeh-Hesary, Farhad, 2023. "How does energy aid mitigate the recipient countries’ carbon emissions?," Economic Analysis and Policy, Elsevier, vol. 79(C), pages 359-375.
    12. Carè, R. & Weber, O., 2023. "How much finance is in climate finance? A bibliometric review, critiques, and future research directions," Research in International Business and Finance, Elsevier, vol. 64(C).
    13. Qi, Haozhi & Huang, Xucheng & Sheeraz, Muhammad, 2023. "Green financing for renewable energy development: Driving the attainment of zero-emission targets," Renewable Energy, Elsevier, vol. 213(C), pages 30-37.
    14. repec:ags:aaea22:335879 is not listed on IDEAS
    15. Acheampong, Alex O. & Dzator, Janet & Shahbaz, Muhammad, 2021. "Empowering the powerless: Does access to energy improve income inequality?," Energy Economics, Elsevier, vol. 99(C).
    16. Yaya Li & Yuru Zhang & An Pan & Minchun Han & Eleonora Veglianti, 2022. "Carbon emission reduction effects of industrial robot applications: Heterogeneity characteristics and influencing mechanisms," Post-Print hal-04522085, HAL.
    17. Umar, Muhammad & Safi, Adnan, 2023. "Do green finance and innovation matter for environmental protection? A case of OECD economies," Energy Economics, Elsevier, vol. 119(C).
    18. (Maggie) Fu, Xiaoqing & Bao, Qun & Xie, Hongjun & Fu, Xiaolan, 2021. "Diffusion of industrial robotics and inclusive growth: Labour market evidence from cross country data," Journal of Business Research, Elsevier, vol. 122(C), pages 670-684.
    19. Yu, Huaying & Wei, Wei & Li, Jinhe & Li, Ying, 2022. "The impact of green digital finance on energy resources and climate change mitigation in carbon neutrality: Case of 60 economies," Resources Policy, Elsevier, vol. 79(C).
    20. Khan, Ali Nawaz & Jabeen, Fauzia & Mehmood, Khalid & Ali Soomro, Mohsin & Bresciani, Stefano, 2023. "Paving the way for technological innovation through adoption of artificial intelligence in conservative industries," Journal of Business Research, Elsevier, vol. 165(C).
    21. Taghizadeh-Hesary, Farhad & Dong, Kangyin & Zhao, Congyu & Phoumin, Han, 2023. "Can financial and economic means accelerate renewable energy growth in the climate change era? The case of China," Economic Analysis and Policy, Elsevier, vol. 78(C), pages 730-743.
    22. Sean Goodwin & Marta Olazabal & Antonio J. Castro & Unai Pascual, 2023. "Global mapping of urban nature-based solutions for climate change adaptation," Nature Sustainability, Nature, vol. 6(4), pages 458-469, April.
    23. Zhao, Jun & Jiang, Qingzhe & Dong, Xiucheng & Dong, Kangyin & Jiang, Hongdian, 2022. "How does industrial structure adjustment reduce CO2 emissions? Spatial and mediation effects analysis for China," Energy Economics, Elsevier, vol. 105(C).
    24. Lin, Changqing & Xiao, Shengpeng & Yin, Zihui, 2022. "How do industrial robots applications affect the quality upgrade of Chinese export trade?," Telecommunications Policy, Elsevier, vol. 46(10).
    25. Acheampong, Alex O. & Amponsah, Mary & Boateng, Elliot, 2020. "Does financial development mitigate carbon emissions? Evidence from heterogeneous financial economies," Energy Economics, Elsevier, vol. 88(C).
    26. Xiao, Kun & Yu, Bolin & Cheng, Lei & Li, Fei & Fang, Debin, 2022. "The effects of CCUS combined with renewable energy penetration under the carbon peak by an SD-CGE model: Evidence from China," Applied Energy, Elsevier, vol. 321(C).
    27. Tang, Xinmeng & Zhou, Xiaoguang, 2023. "Impact of green finance on renewable energy development: A spatiotemporal consistency perspective," Renewable Energy, Elsevier, vol. 204(C), pages 320-337.
    28. Rishikesh Ram Bhandary & Kelly Sims Gallagher & Fang Zhang, 2021. "Climate finance policy in practice: a review of the evidence," Climate Policy, Taylor & Francis Journals, vol. 21(4), pages 529-545, April.
    29. Benjamin S. Halpern & Melanie Frazier & Juliette Verstaen & Paul-Eric Rayner & Gage Clawson & Julia L. Blanchard & Richard S. Cottrell & Halley E. Froehlich & Jessica A. Gephart & Nis S. Jacobsen & Ca, 2022. "The environmental footprint of global food production," Nature Sustainability, Nature, vol. 5(12), pages 1027-1039, December.
    30. Xu, Jialong & Moslehpour, Massoud & Tran, Trung Kien & Dinh, Khai Cong & Ngo, Thanh Quang & Huy, Pham Quang, 2023. "The role of institutional quality, renewable energy development and trade openness in green finance: Empirical evidence from South Asian countries," Renewable Energy, Elsevier, vol. 207(C), pages 687-692.
    31. Li, Yaya & Zhang, Yuru & Pan, An & Han, Minchun & Veglianti, Eleonora, 2022. "Carbon emission reduction effects of industrial robot applications: Heterogeneity characteristics and influencing mechanisms," Technology in Society, Elsevier, vol. 70(C).
    32. Bahoo, Salman & Cucculelli, Marco & Qamar, Dawood, 2023. "Artificial intelligence and corporate innovation: A review and research agenda," Technological Forecasting and Social Change, Elsevier, vol. 188(C).
    33. David Bidwell & Benjamin K. Sovacool, 2023. "Uneasy tensions in energy justice and systems transformation," Nature Energy, Nature, vol. 8(4), pages 317-320, April.
    34. Manuel Esperon-Rodriguez & Mark G. Tjoelker & Jonathan Lenoir & John B. Baumgartner & Linda J. Beaumont & David A. Nipperess & Sally A. Power & Benoît Richard & Paul D. Rymer & Rachael V. Gallagher, 2022. "Climate change increases global risk to urban forests," Nature Climate Change, Nature, vol. 12(10), pages 950-955, October.
    35. Jun Liu & Yu Qian & Yuanjun Yang & Zhidan Yang, 2022. "Can Artificial Intelligence Improve the Energy Efficiency of Manufacturing Companies? Evidence from China," IJERPH, MDPI, vol. 19(4), pages 1-18, February.
    36. Wang, Jianda & Wang, Kun & Dong, Kangyin & Zhang, Shiqiu, 2023. "Assessing the role of financial development in natural resource utilization efficiency: Does artificial intelligence technology matter?," Resources Policy, Elsevier, vol. 85(PA).
    37. Rabah Arezki, 2021. "Climate finance for Africa requires overcoming bottlenecks in domestic capacity," Nature Climate Change, Nature, vol. 11(11), pages 888-888, November.
    38. T. M. Logan & M. J. Anderson & A. C. Reilly, 2023. "Risk of isolation increases the expected burden from sea-level rise," Nature Climate Change, Nature, vol. 13(4), pages 397-402, April.
    39. Alharbi, Samar S. & Al Mamun, Md & Boubaker, Sabri & Rizvi, Syed Kumail Abbas, 2023. "Green finance and renewable energy: A worldwide evidence," Energy Economics, Elsevier, vol. 118(C).
    40. Lee, Chien-Chiang & Qin, Shuai & Li, Yaya, 2022. "Does industrial robot application promote green technology innovation in the manufacturing industry?," Technological Forecasting and Social Change, Elsevier, vol. 183(C).
    41. Zhao, Congyu & Dong, Kangyin & Jiang, Hong-Dian & Wang, Kun & Dong, Xiucheng, 2023. "How does energy poverty eradication realize the path to carbon unlocking? The case of China," Energy Economics, Elsevier, vol. 121(C).
    42. Ivanovski, Kris & Awaworyi Churchill, Sefa, 2020. "Convergence and determinants of greenhouse gas emissions in Australia: A regional analysis," Energy Economics, Elsevier, vol. 92(C).
    43. Wu, Linfei & Sun, Liwen & Qi, Peixiao & Ren, Xiangwei & Sun, Xiaoting, 2021. "Energy endowment, industrial structure upgrading, and CO2 emissions in China: Revisiting resource curse in the context of carbon emissions," Resources Policy, Elsevier, vol. 74(C).
    44. Zhang, Shaohui & Luo, Shunjun & Afshan, Sahar, 2022. "Role of climate technologies, financial development, and renewable energy in the facilitation of social, economic, and environmental goals," Renewable Energy, Elsevier, vol. 199(C), pages 169-178.
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    More about this item

    Keywords

    Artificial intelligence; Renewable energy development; Climate finance; Moderation effect; Global case;
    All these keywords.

    JEL classification:

    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models
    • F35 - International Economics - - International Finance - - - Foreign Aid
    • O13 - Economic Development, Innovation, Technological Change, and Growth - - Economic Development - - - Agriculture; Natural Resources; Environment; Other Primary Products
    • P28 - Political Economy and Comparative Economic Systems - - Socialist and Transition Economies - - - Natural Resources; Environment
    • Q55 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Environmental Economics: Technological Innovation

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