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Green technology innovations, urban innovation environment and CO2 emission reduction in China: Fresh evidence from a partially linear functional-coefficient panel model

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  • Lin, Boqiang
  • Ma, Ruiyang

Abstract

Green technology innovations are deemed as effective channels through which economic growth and environmental governance are balanced. However, empirical research on the nexus between green technology innovations and CO2 emissions, especially in developing countries, remains scant. Employing panel data on 264 prefecture-level cities from 2006 to 2017 in China, we explore the impact of the urban innovation environment on the effect of green technological innovations on CO2 emissions. The empirical results indicate that green technology innovations have a heterogeneous impact in different types of cities. Meanwhile, green technological innovations can contribute to CO2 emission mitigation after 2010, while the effect is not significant in Chinese cities before 2010. Secondly, green technology innovations can reduce CO2 emissions indirectly through industrial structure upgrading. Thirdly, when the urban innovation environment is considered, government fiscal expenditure cannot significantly impact the marginal effect of green technologies. Meanwhile, the marginal mitigation effect of green technology innovations on CO2 emissions is only significant when the human capital level of a city has reached a certain level. There is a better carbon emission reduction effect in cities with higher human capital levels. The results provide important enlightenment to realize the coordination and unity of economic transition to innovation-driven and green and low-carbon development.

Suggested Citation

  • Lin, Boqiang & Ma, Ruiyang, 2022. "Green technology innovations, urban innovation environment and CO2 emission reduction in China: Fresh evidence from a partially linear functional-coefficient panel model," Technological Forecasting and Social Change, Elsevier, vol. 176(C).
  • Handle: RePEc:eee:tefoso:v:176:y:2022:i:c:s0040162521008659
    DOI: 10.1016/j.techfore.2021.121434
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    as
    1. Daron Acemoglu & Philippe Aghion & Leonardo Bursztyn & David Hemous, 2012. "The Environment and Directed Technical Change," American Economic Review, American Economic Association, vol. 102(1), pages 131-166, February.
    2. Salim, Ruhul & Yao, Yao & Chen, George S., 2017. "Does human capital matter for energy consumption in China?," Energy Economics, Elsevier, vol. 67(C), pages 49-59.
    3. He, Gang & Kammen, Daniel M., 2016. "Where, when and how much solar is available? A provincial-scale solar resource assessment for China," Renewable Energy, Elsevier, vol. 85(C), pages 74-82.
    4. García-Quevedo, José & Segarra-Blasco, Agustí & Teruel, Mercedes, 2018. "Financial constraints and the failure of innovation projects," Technological Forecasting and Social Change, Elsevier, vol. 127(C), pages 127-140.
    5. Montmartin, Benjamin & Herrera, Marcos, 2015. "Internal and external effects of R&D subsidies and fiscal incentives: Empirical evidence using spatial dynamic panel models," Research Policy, Elsevier, vol. 44(5), pages 1065-1079.
    6. Mi, Zhifu & Zhang, Yunkun & Guan, Dabo & Shan, Yuli & Liu, Zhu & Cong, Ronggang & Yuan, Xiao-Chen & Wei, Yi-Ming, 2016. "Consumption-based emission accounting for Chinese cities," Applied Energy, Elsevier, vol. 184(C), pages 1073-1081.
    7. Wang, Shaojian & Liu, Xiaoping, 2017. "China’s city-level energy-related CO2 emissions: Spatiotemporal patterns and driving forces," Applied Energy, Elsevier, vol. 200(C), pages 204-214.
    8. Hu, Gang-Gao, 2021. "Is knowledge spillover from human capital investment a catalyst for technological innovation? The curious case of fourth industrial revolution in BRICS economies," Technological Forecasting and Social Change, Elsevier, vol. 162(C).
    9. Xu, Bin & Lin, Boqiang, 2016. "A quantile regression analysis of China's provincial CO2 emissions: Where does the difference lie?," Energy Policy, Elsevier, vol. 98(C), pages 328-342.
    10. Du, Kerui & Yu, Ying & Li, Jing, 2020. "Does international trade promote CO2 emission performance? An empirical analysis based on a partially linear functional-coefficient panel data model," Energy Economics, Elsevier, vol. 92(C).
    11. Wang, Shaojian & Liu, Xiaoping & Zhou, Chunshan & Hu, Jincan & Ou, Jinpei, 2017. "Examining the impacts of socioeconomic factors, urban form, and transportation networks on CO2 emissions in China’s megacities," Applied Energy, Elsevier, vol. 185(P1), pages 189-200.
    12. Gao, Kang & Yuan, Yijun, 2021. "The effect of innovation-driven development on pollution reduction: Empirical evidence from a quasi-natural experiment in China," Technological Forecasting and Social Change, Elsevier, vol. 172(C).
    13. Yu, Chin-Hsien & Wu, Xiuqin & Zhang, Dayong & Chen, Shi & Zhao, Jinsong, 2021. "Demand for green finance: Resolving financing constraints on green innovation in China," Energy Policy, Elsevier, vol. 153(C).
    14. Du, Kerui & Cheng, Yuanyuan & Yao, Xin, 2021. "Environmental regulation, green technology innovation, and industrial structure upgrading: The road to the green transformation of Chinese cities," Energy Economics, Elsevier, vol. 98(C).
    15. Chen, Zhongfei & Zhang, Xiao & Chen, Fanglin, 2021. "Do carbon emission trading schemes stimulate green innovation in enterprises? Evidence from China," Technological Forecasting and Social Change, Elsevier, vol. 168(C).
    16. Song, Yanwu & Zhang, Jinrui & Song, Yingkang & Fan, Xinran & Zhu, Yuqing & Zhang, Chen, 2020. "Can industry-university-research collaborative innovation efficiency reduce carbon emissions?," Technological Forecasting and Social Change, Elsevier, vol. 157(C).
    17. Tyler A. Jacobson & Jasdeep S. Kler & Michael T. Hernke & Rudolf K. Braun & Keith C. Meyer & William E. Funk, 2019. "Direct human health risks of increased atmospheric carbon dioxide," Nature Sustainability, Nature, vol. 2(8), pages 691-701, August.
    18. Sun, Bing & Yu, Yixin & Qin, Chao, 2017. "Should China focus on the distributed development of wind and solar photovoltaic power generation? A comparative study," Applied Energy, Elsevier, vol. 185(P1), pages 421-439.
    19. Kerui Du & Yonghui Zhang & Qiankun Zhou, 2020. "Fitting partially linear functional-coefficient panel-data models with Stata," Stata Journal, StataCorp LP, vol. 20(4), pages 976-998, December.
    20. Zhao, Jun & Shahbaz, Muhammad & Dong, Xiucheng & Dong, Kangyin, 2021. "How does financial risk affect global CO2 emissions? The role of technological innovation," Technological Forecasting and Social Change, Elsevier, vol. 168(C).
    21. Xu, Le & Fan, Meiting & Yang, Lili & Shao, Shuai, 2021. "Heterogeneous green innovations and carbon emission performance: Evidence at China's city level," Energy Economics, Elsevier, vol. 99(C).
    22. Nick Johnstone & Ivan Haščič & David Popp, 2017. "Erratum to: Renewable Energy Policies and Technological Innovation: Evidence Based on Patent Counts," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 68(2), pages 441-444, October.
    23. Xie, Rui & Wei, Dihan & Han, Feng & Lu, Yue & Fang, Jiayu & Liu, Yu & Wang, Junfeng, 2019. "The effect of traffic density on smog pollution: Evidence from Chinese cities," Technological Forecasting and Social Change, Elsevier, vol. 144(C), pages 421-427.
    24. 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.
    25. Wurlod, Jules-Daniel & Noailly, Joëlle, 2018. "The impact of green innovation on energy intensity: An empirical analysis for 14 industrial sectors in OECD countries," Energy Economics, Elsevier, vol. 71(C), pages 47-61.
    26. Hu, Feng & Xi, Xun & Zhang, Yueyue, 2021. "Influencing mechanism of reverse knowledge spillover on investment enterprises’ technological progress: An empirical examination of Chinese firms," Technological Forecasting and Social Change, Elsevier, vol. 169(C).
    27. 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).
    28. Du, Kerui & Li, Pengzhen & Yan, Zheming, 2019. "Do green technology innovations contribute to carbon dioxide emission reduction? Empirical evidence from patent data," Technological Forecasting and Social Change, Elsevier, vol. 146(C), pages 297-303.
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