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Do Innovation and Entrepreneurship Support Policies Promote Urban Green Transformation?—The Mediating Role of Fiscal Technology Expenditure

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  • Junqi Wen

    (International Business School, Jinan University, Guangzhou 510632, China)

  • Yong Lan

    (International Business School, Jinan University, Guangzhou 510632, China)

  • Guoqin Bu

    (International Business School, Jinan University, Guangzhou 510632, China)

Abstract

This article takes the establishment of two batches of mass entrepreneurship and innovation demonstration bases in 2016 and 2017 as a quasi-natural experiment. It utilizes panel data from 284 cities in China from 2010 to 2021 to construct a multiple time point difference-in-difference (DID) model. This study finds that innovation and entrepreneurship support policies can effectively promote urban green transformation. The robustness of the model is ensured through parallel trend tests, placebo tests, difference-in-difference-in-difference models, PSM-DID, and other methods. A mechanism analysis reveals that fiscal technology expenditure partially mediates the process of innovation and entrepreneurship support policies affecting urban green transformation. A heterogeneity analysis indicates that innovation and entrepreneurship support policies have only a significant positive impact on the green transformation of eastern cities, (sub-)provincial cities, and cities with high green total factor productivity, suggesting that the effectiveness of innovation and entrepreneurship support policies may be influenced by the size of the urban economy. This article provides a theoretical basis and policy recommendations for better leveraging the effects of innovation and entrepreneurship support policies to address the dual challenges of economic and green transformation jointly.

Suggested Citation

  • Junqi Wen & Yong Lan & Guoqin Bu, 2024. "Do Innovation and Entrepreneurship Support Policies Promote Urban Green Transformation?—The Mediating Role of Fiscal Technology Expenditure," Sustainability, MDPI, vol. 16(7), pages 1-24, March.
    • Handle: RePEc:gam:jsusta:v:16:y:2024:i:7:p:2622-:d:1362048
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    1. López, Ramón & Galinato, Gregmar I. & Islam, Asif, 2011. "Fiscal spending and the environment: Theory and empirics," Journal of Environmental Economics and Management, Elsevier, vol. 62(2), pages 180-198, September.
    2. Rath, Badri Narayan & Akram, Vaseem & Bal, Debi Prasad & Mahalik, Mantu Kumar, 2019. "Do fossil fuel and renewable energy consumption affect total factor productivity growth? Evidence from cross-country data with policy insights," Energy Policy, Elsevier, vol. 127(C), pages 186-199.
    3. Florian Noseleit, 2013. "Entrepreneurship, structural change, and economic growth," Journal of Evolutionary Economics, Springer, vol. 23(4), pages 735-766, September.
    4. Festus Victor Bekun, 2022. "Mitigating Emissions in India: Accounting for the Role of Real Income, Renewable Energy Consumption and Investment in Energy," International Journal of Energy Economics and Policy, Econjournals, vol. 12(1), pages 188-192.
    5. 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.
    6. repec:diw:diwwpp:dp435 is not listed on IDEAS
    7. Hall, Bronwyn H. & Helmers, Christian, 2013. "Innovation and diffusion of clean/green technology: Can patent commons help?," Journal of Environmental Economics and Management, Elsevier, vol. 66(1), pages 33-51.
    8. Zhu, Joe, 1998. "Data envelopment analysis vs. principal component analysis: An illustrative study of economic performance of Chinese cities," European Journal of Operational Research, Elsevier, vol. 111(1), pages 50-61, November.
    9. Li, Ye & Chen, Yiyan, 2021. "Development of an SBM-ML model for the measurement of green total factor productivity: The case of pearl river delta urban agglomeration," Renewable and Sustainable Energy Reviews, Elsevier, vol. 145(C).
    10. Tong, Hefeng & Wang, Yan & Xu, Jiajun, 2020. "Green transformation in China: Structures of endowment, investment, and employment," Structural Change and Economic Dynamics, Elsevier, vol. 54(C), pages 173-185.
    11. W. Liu & W. Meng & X. Li & D. Zhang, 2010. "DEA models with undesirable inputs and outputs," Annals of Operations Research, Springer, vol. 173(1), pages 177-194, January.
    12. Mao, Wenxin & Wang, Wenping & Sun, Huifang & Yao, Peiyi & Wang, Xiaolei & Luo, Dang, 2021. "Urban industrial transformation patterns under natural resource dependence: A rule mining technique," Energy Policy, Elsevier, vol. 156(C).
    13. Xiaosheng Li & Yunxia Shu & Xin Jin, 2022. "Environmental regulation, carbon emissions and green total factor productivity: a case study of China," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 24(2), pages 2577-2597, February.
    14. Kemfert, Claudia, 2005. "Induced technological change in a multi-regional, multi-sectoral, integrated assessment model (WIAGEM): Impact assessment of climate policy strategies," Ecological Economics, Elsevier, vol. 54(2-3), pages 293-305, August.
    15. Zhou, P. & Ang, B.W. & Wang, H., 2012. "Energy and CO2 emission performance in electricity generation: A non-radial directional distance function approach," European Journal of Operational Research, Elsevier, vol. 221(3), pages 625-635.
    16. Raihan, Asif & Pavel, Monirul Islam & Muhtasim, Dewan Ahmed & Farhana, Sadia & Faruk, Omar & Paul, Arindrajit, 2023. "The role of renewable energy use, technological innovation, and forest cover toward green development: Evidence from Indonesia," Innovation and Green Development, Elsevier, vol. 2(1).
    17. Song, Malin & Du, Juntao & Tan, Kim Hua, 2018. "Impact of fiscal decentralization on green total factor productivity," International Journal of Production Economics, Elsevier, vol. 205(C), pages 359-367.
    18. Jaryn Bradford & Evan D. G. Fraser, 2008. "Local authorities, climate change and small and medium enterprises: identifying effective policy instruments to reduce energy use and carbon emissions," Corporate Social Responsibility and Environmental Management, John Wiley & Sons, vol. 15(3), pages 156-172, May.
    19. Tone, Kaoru, 2001. "A slacks-based measure of efficiency in data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 130(3), pages 498-509, May.
    20. Matthew Thompson, 2019. "Playing with the Rules of the Game: Social Innovation for Urban Transformation," International Journal of Urban and Regional Research, Wiley Blackwell, vol. 43(6), pages 1168-1192, November.
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