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Effects of Science and Technology Finance on Green Total Factor Productivity in China: Insights from an Empirical Spatial Durbin Model

Author

Listed:
  • Ying Lu

    (Shandong University of Technology)

  • Mahmood Ahmad

    (Shandong University of Technology)

  • Haotian Zhang

    (Shandong University of Technology)

  • Jingxian Guo

    (Shandong University of Technology)

Abstract

Undoubtedly, science and technology (sci-tech) finance plays a vital role in promoting innovation and industrial structure. Sci-tech finance may also affect green total factor productivity (GTFP). However, the research that integrates sci-tech finance and GTFP in the same environmental policy framework is still scant. In this context, the spatial spillover effect and mechanism of the impact of sci-tech finance on GTFP were empirically analyzed using the panel data of 30 provinces in China from 2010 to 2020. The slacks-based measure (SBM) model of non-expected output and the GML index were used to measure the GTFP, and the entropy weight method was used to measure the development level of sci-tech finance in each province. The results unveil that sci-tech finance and GTFP in China have significant spatial autocorrelation and spatial disequilibrium; the positive driving effect of sci-tech finance on GTFP has a significant spatial spillover effect. The mechanism test finds that sci-tech finance enhances local GTFP by expanding R&D expenditures and optimizing industrial structure, and the spatial spillover effect of sci-tech finance on GTFP in neighboring regions is realized by expanding R&D expenditures in neighboring regions. The heterogeneity test found that sci-tech finance has a significant positive effect on GTFP in the eastern region, an insignificant positive effect on the central regions, and a significant negative effect on the western and northeastern regions. Therefore, regional collaboration alliances should be established to fully play the spatial effect of sci-tech finance and enhance GTFP.

Suggested Citation

  • Ying Lu & Mahmood Ahmad & Haotian Zhang & Jingxian Guo, 2024. "Effects of Science and Technology Finance on Green Total Factor Productivity in China: Insights from an Empirical Spatial Durbin Model," Journal of the Knowledge Economy, Springer;Portland International Center for Management of Engineering and Technology (PICMET), vol. 15(2), pages 7280-7306, June.
    • Handle: RePEc:spr:jknowl:v:15:y:2024:i:2:d:10.1007_s13132-023-01306-9
    DOI: 10.1007/s13132-023-01306-9
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    1. Pagliacci, Carolina, 2020. "Financial constraints and inflation in Latin America: The impacts of bond financing and depreciations on supply inflation," Economic Analysis and Policy, Elsevier, vol. 68(C), pages 379-397.
    2. Feng, Chao & Huang, Jian-Bai & Wang, Miao, 2018. "Analysis of green total-factor productivity in China's regional metal industry: A meta-frontier approach," Resources Policy, Elsevier, vol. 58(C), pages 219-229.
    3. Choi, Changkyu & Rhee, Dong-Eun & Oh, Yonghyup, 2014. "Information and capital flows revisited: The Internet as a determinant of transactions in financial assets," Economic Modelling, Elsevier, vol. 40(C), pages 191-198.
    4. Lv, Chengchao & Shao, Changhua & Lee, Chien-Chiang, 2021. "Green technology innovation and financial development: Do environmental regulation and innovation output matter?," Energy Economics, Elsevier, vol. 98(C).
    5. Greenwood, Jeremy & Jovanovic, Boyan, 1990. "Financial Development, Growth, and the Distribution of Income," Journal of Political Economy, University of Chicago Press, vol. 98(5), pages 1076-1107, October.
    6. Liying Yu & Weishu Li & Zixuan Chen & Mingkang Shi & Hongda Liu, 2022. "Multi-stage collaborative efficiency measurement of sci-tech finance: network-DEA analysis and spatial impact research," Economic Research-Ekonomska Istraživanja, Taylor & Francis Journals, vol. 35(1), pages 300-324, December.
    7. Shi, Huiting & Chai, Jian & Lu, Quanying & Zheng, Jiali & Wang, Shouyang, 2022. "The impact of China's low-carbon transition on economy, society and energy in 2030 based on CO2 emissions drivers," Energy, Elsevier, vol. 239(PD).
    8. Sun, Yang & Tang, Xinwei, 2022. "The impact of digital inclusive finance on sustainable economic growth in China," Finance Research Letters, Elsevier, vol. 50(C).
    9. Xia, Fan & Xu, Jintao, 2020. "Green total factor productivity: A re-examination of quality of growth for provinces in China," China Economic Review, Elsevier, vol. 62(C).
    10. Li, Ke & Lin, Boqiang, 2017. "Economic growth model, structural transformation, and green productivity in China," Applied Energy, Elsevier, vol. 187(C), pages 489-500.
    11. Wübbeke, Jost & Heroth, Timo, 2014. "Challenges and political solutions for steel recycling in China," Resources, Conservation & Recycling, Elsevier, vol. 87(C), pages 1-7.
    12. Yuan, Huaxi & Feng, Yidai & Lee, Chien-Chiang & Cen, Yan, 2020. "How does manufacturing agglomeration affect green economic efficiency?," Energy Economics, Elsevier, vol. 92(C).
    13. Pittman, Russell W, 1983. "Multilateral Productivity Comparisons with Undesirable Outputs," Economic Journal, Royal Economic Society, vol. 93(372), pages 883-891, December.
    14. Min-Ren Yan & Kuo-Ming Chien, 2013. "Evaluating the Economic Performance of High-Technology Industry and Energy Efficiency: A Case Study of Science Parks in Taiwan," Energies, MDPI, vol. 6(2), pages 1-15, February.
    15. 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).
    16. Wang, Kai-Hua & Zhao, Yan-Xin & Jiang, Cui-Feng & Li, Zheng-Zheng, 2022. "Does green finance inspire sustainable development? Evidence from a global perspective," Economic Analysis and Policy, Elsevier, vol. 75(C), pages 412-426.
    17. Wang, Xinxin & Xu, Zeshui & Qin, Yong & Skare, Marinko, 2022. "Innovation, the knowledge economy, and green growth: Is knowledge-intensive growth really environmentally friendly?," Energy Economics, Elsevier, vol. 115(C).
    18. Alquist, Ron & Chabot, Benjamin R. & Yamarthy, Ram, 2022. "The price of property rights: Institutions, finance, and economic growth," Journal of International Economics, Elsevier, vol. 137(C).
    19. 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).
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