Spatial Spillover Effect of Heterogeneous Green Innovations on Carbon Emissions: Evidence from Yangtze River Delta Region of China
DOI:
https://doi.org/10.31181/ijes1612027295Keywords:
Heterogeneous green innovation, Carbon emissions, Spatial spillover effect, Spatial econometric model, Green technology, Environmental innovation, Public R&D investmentAbstract
Green innovation is widely recognized as an effective pathway for reconciling economic development with carbon emission reduction. However, there is still no consensus on the spatial relationship between green innovation (GI) and carbon emissions (CEs). To address this gap, this study uses panel data from China’s Yangtze River Delta region to examine the spatial spillover effects of GI and its subcomponents on CEs, as well as the role of public R&D investment in this relationship. The findings reveal a non-intuitive and spatially asymmetric effect of GI. Specifically, GI tends to increase CEs in the region where innovation occurs while reducing CEs in neighboring cities. Moreover, the impacts of green technologies (GTs) on CEs vary across regions and channels. Innovation in GTs, indirect CE reduction mechanisms, and direct CE reduction effects all exhibit significant regional spillover impacts on CEs. The results further show that public R&D investment, both locally and through spatial spillovers, weakens the relationship between GI and CEs. This study contributes to the literature by advancing the understanding of how different forms of green technological progress generate heterogeneous spatial spillover effects on CEs. It is among the first to systematically examine how public R&D investment moderates the relationship between GT and CEs. From a policy perspective, the findings provide practical insights into strengthening regional green innovation capacity while simultaneously reducing carbon emissions within an integrated development framework.
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Umar, M., Ji, X., Kirikkaleli, D., & Xu, Q. (2020). COP21 roadmap: Do innovation, financial development, and transportation infrastructure matter for environmental sustainability in China? Journal of Environmental Management, 271, 111026. https://doi.org/10.1016/j.jenvman.2020.111026
Ganda, F. (2019). The impact of innovation and technology investments on carbon emissions in selected organisation for economic co-operation and development countries. Journal of Cleaner Production, 217, 469–483. https://doi.org/10.1016/j.jclepro.2019.01.235
Chen, H., Yi, J., Chen, A., Peng, D., & Yang, J. (2023). Green technology innovation and CO₂ emission in China: Evidence from a spatial-temporal analysis and a nonlinear spatial Durbin model. Energy Policy, 172, 113338. https://doi.org/10.1016/j.enpol.2022.113338
Khattak, S. I., Ahmad, M., ul Haq, Z., Shaofu, G., & Hang, J. (2022). On the goals of sustainable production and the conditions of environmental sustainability: Does cyclical innovation in green and sustainable technologies determine carbon dioxide emissions in G-7 economies. Sustainable Production and Consumption, 29, 406–420. https://doi.org/10.1016/j.spc.2021.10.022
Xu, L., Fan, M., Yang, L., & Shao, S. (2021). Heterogeneous green innovations and carbon emission performance: Evidence at China's city level. Energy Economics, 99, 105269. https://doi.org/10.1016/j.eneco.2021.105269
Liu, J., & Kang, S. J. (2024). The impact of green innovation on CO₂ emissions in China: Evidence from spatial regression model. International Economic Journal, 38(3), 446–470. https://doi.org/10.1080/10168737.2024.2378460
Lu, X., & Lu, Z. (2024). How does green technology innovation affect urban carbon emissions? Evidence from Chinese cities. Energy and Buildings, 325, 115025. https://doi.org/10.1016/j.enbuild.2024.115025
Bai, Y., Song, S., Jiao, J., & Yang, R. (2019). The impacts of government R&D subsidies on green innovation: Evidence from Chinese energy-intensive firms. Journal of Cleaner Production, 233, 819–829. https://doi.org/10.1016/j.jclepro.2019.06.107
Fan, J., & Teo, T. (2022). Will China's R&D investment improve green innovation performance? An empirical study. Environmental Science and Pollution Research, 29(26), 39331–39344. https://doi.org/10.1007/s11356-021-18464-5
Wang, M., Li, Y., Li, J., & Wang, Z. (2021). Green process innovation, green product innovation and its economic performance improvement paths: A survey and structural model. Journal of Environmental Management, 297, 113282. https://doi.org/10.1016/j.jenvman.2021.113282
Zhao, Z., Zhao, Y., Shi, X., Zheng, L., Fan, S., & Zuo, S. (2024). Green innovation and carbon emission performance: The role of digital economy. Energy Policy, 195, 114344. https://doi.org/10.1016/j.enpol.2024.114344
Töbelmann, D., & Wendler, T. (2020). The impact of environmental innovation on carbon dioxide emissions. Journal of Cleaner Production, 244, 118787. https://doi.org/10.1016/j.jclepro.2019.118787
Wang, Z., & Zhu, Y. (2020). Do energy technology innovations contribute to CO₂ emissions abatement? A spatial perspective. Science of the Total Environment, 726, 138574. https://doi.org/10.1016/j.scitotenv.2020.138574
Xia, M., Dong, L., Zhao, X., & Jiang, L. (2024). Green technology innovation and regional carbon emissions: Analysis based on heterogeneous treatment effect modeling. Environmental Science and Pollution Research, 31(6), 9614–9629. https://doi.org/10.1007/s11356-023-31818-5
Hao, Z., Zhao, Z., Pan, Z., Tang, D., Zhao, M., & Zhang, H. (2025). Spatial effects of financial agglomeration and green technological innovation on carbon emissions. Sustainability, 17(6), 2746. https://doi.org/10.3390/su17062746
Shan, S., Genç, S. Y., Kamran, H. W., & Dinca, G. (2021). Role of green technology innovation and renewable energy in carbon neutrality: A sustainable investigation from Turkey. Journal of Environmental Management, 294, 113004. https://doi.org/10.1016/j.jenvman.2021.113004
Liu, T., & Wang, L. (2025). Green-process vs. green-product innovation: The diverse impact of the carbon emission trading system. Applied Economics, 1–16. https://doi.org/10.1080/00036846.2025.2488530
Chen, X., Pan, X., & Sinha, P. (2022). What to green: Family involvement and different types of eco-innovation. Business Strategy and the Environment, 31(5), 2588–2602. https://doi.org/10.1002/bse.3045
Zhao, N., Liu, X., Pan, C., & Wang, C. (2021). The performance of green innovation: From an efficiency perspective. Socio-Economic Planning Sciences, 78, 101062. https://doi.org/10.1016/j.seps.2021.101062
Gupta, H., & Barua, M. K. (2018). A framework to overcome barriers to green innovation in SMEs using BWM and fuzzy TOPSIS. Science of the Total Environment, 633, 122–139. https://doi.org/10.1016/j.scitotenv.2018.03.173
Miao, C., Fang, D., Sun, L., & Luo, Q. (2017). Natural resources utilization efficiency under the influence of green technological innovation. Resources, Conservation and Recycling, 126, 153–161. https://doi.org/10.1016/j.resconrec.2017.07.019
Andersén, J. (2021). A relational natural-resource-based view on product innovation: The influence of green product innovation and green suppliers on differentiation advantage in small manufacturing firms. Technovation, 104, 102254. https://doi.org/10.1016/j.technovation.2021.102254
Dugoua, E., & Dumas, M. (2021). Green product innovation in industrial networks: A theoretical model. Journal of Environmental Economics and Management, 107, 102420. https://doi.org/10.1016/j.jeem.2021.102420
Fang, G., Gao, Z., Wang, L., & Tian, L. (2022). How does green innovation drive urban carbon emission efficiency? Evidence from the Yangtze River Economic Belt. Journal of Cleaner Production, 375, 134196. https://doi.org/10.1016/j.jclepro.2022.134196
Bhowmik, C., Zindani, D., Chatterjee, P., Marinkovic, D., & Šliogerienė, J. (2025). Evaluation of green energy sources: An extended fuzzy-TODIM approach based on Schweizer-Sklar and power averaging operators. Facta Universitatis, Series: Mechanical Engineering, 23(3), 627–648. https://doi.org/10.22190/FUME240711042B
Sahoo, S. K., Goswami, S. S., Božanić, D., & Mitra, S. (2025). Evaluating green economy strategies through multi-criteria decision analysis: A systematic review. International Journal of Economic Sciences, 14(1), 385–407. https://doi.org/10.31181/ijes1412025245
Tu, C., Liang, Y., & Fu, Y. (2024). How does the environmental attention of local governments affect regional green development? Empirical evidence from local governments in China. Humanities and Social Sciences Communications, 11(1), 1–14. https://doi.org/10.1057/s41599-024-02887-9
Fischer, C. (2008). Emissions pricing, spillovers, and public investment in environmentally friendly technologies. Energy Economics, 30(2), 487–502. https://doi.org/10.1016/j.eneco.2007.06.001
Garrone, P., & Grilli, L. (2010). Is there a relationship between public expenditures in energy R&D and carbon emissions per GDP? An empirical investigation. Energy Policy, 38(10), 5600–5613. https://doi.org/10.1016/j.enpol.2010.04.057
Huang, J., Hao, Y., & Lei, H. (2018). Indigenous versus foreign innovation and energy intensity in China. Renewable and Sustainable Energy Reviews, 81, 1721–1729. https://doi.org/10.1016/j.rser.2017.05.266
Li, W., & Zheng, M. (2016). Substantive or strategic innovation? The impact of macro-industrial policy on micro-firm innovation. Economic Research, 51(04), 60–73.
Feichtinger, G., Lambertini, L., Leitmann, G., & Wrzaczek, S. (2016). R&D for green technologies in a dynamic oligopoly: Schumpeter, Arrow and inverted-U's. European Journal of Operational Research, 249(3), 1131–1138. https://doi.org/10.1016/j.ejor.2015.09.025
Fernández, Y. F., López, M. F., & Blanco, B. O. (2018). Innovation for sustainability: The impact of R&D spending on CO₂ emissions. Journal of Cleaner Production, 172, 3459–3467. https://doi.org/10.1016/j.jclepro.2017.11.001
Churchill, S. A., Inekwe, J., Smyth, R., & Zhang, X. (2019). R&D intensity and carbon emissions in the G7: 1870–2014. Energy Economics, 80, 30–37. https://doi.org/10.1016/j.eneco.2018.12.020
Liu, C. (2025). The impact of green technological innovation on carbon emissions: A perspective based on nonlinear effects, moderating effects and spatial spillover effects. Technology Analysis & Strategic Management, 1–18. https://doi.org/10.1080/09537325.2025.2506532
Tao, C., Ja'afar, R., & Wan Hussain, M. H. W. (2025). The implications of environmental uncertainty on enterprise operations, financing, and investments: A systematic literature review. International Review, 14(3-4), 108–117. https://doi.org/10.5937/intrev2504108T
Huang, Y., Zhang, Z., & Sun, S. (2026). The economic mechanisms of artificial intelligence resources affecting green risk management: Empirical evidence from Chinese listed firms. International Journal of Economic Sciences, 15(1), 303–323. https://doi.org/10.31181/ijes1512026277
Qi, S., Peng, H., & Tan, X. (2019). The moderating effect of R&D investment on income and carbon emissions in China: Direct and spatial spillover insights. Sustainability, 11(5), 1235. https://doi.org/10.3390/su11051235
Zhang, Q., Li, J., Kong, Q., & Huang, H. (2024). Spatial effects of green innovation and carbon emission reduction in China: Mediating role of infrastructure and informatization. Sustainable Cities and Society, 106, 105426. https://doi.org/10.1016/j.scs.2024.105426
Yang, X., Jia, Z., Yang, Z., & Yuan, X. (2021). The effects of technological factors on carbon emissions from various sectors in China: A spatial perspective. Journal of Cleaner Production, 301, 126949. https://doi.org/10.1016/j.jclepro.2021.126949
Li, M., & Wang, Q. (2017). Will technology advances alleviate climate change? Dual effects of technology change on aggregate carbon dioxide emissions. Energy for Sustainable Development, 41, 61–68. https://doi.org/10.1016/j.esd.2017.08.004
Weina, D., Gilli, M., Mazzanti, M., & Nicolli, F. (2016). Green inventions and greenhouse gas emission dynamics: A close examination of provincial Italian data. Environmental Economics and Policy Studies, 18(2), 247–263. https://doi.org/10.1007/s10018-015-0126-1
Peng, W., Yin, Y., Wen, Z., & Kuang, J. (2021). Spatial spillover effect of green innovation on economic development quality in China: Evidence from a panel data of 270 prefecture-level and above cities. Sustainable Cities and Society, 69, 102863. https://doi.org/10.1016/j.scs.2021.102863
Zhao, C., & Wang, B. (2022). How does new-type urbanization affect air pollution? Empirical evidence based on spatial spillover effect and spatial Durbin model. Environment International, 165, 107304. https://doi.org/10.1016/j.envint.2022.107304
Chen, Y., & Jin, S. (2023). Artificial intelligence and carbon emissions in manufacturing firms: The moderating role of green innovation. Processes, 11(9), 2705. https://doi.org/10.3390/pr11092705
Lien, D., & Balakrishnan, N. (2023). Some results on multiple regression analysis with data cleaned by trimming and winsorization. Communications in Statistics: Simulation and Computation, 52(10), 5082–5089. https://doi.org/10.1080/03610918.2021.1982974
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