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Technology or Institutions: Which Is the Source of Green Economic Growth in Chinese Cities?

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  • Jing Han

    (School of Economics and Resource Management, Beijing Normal University, Beijing 100875, China)

  • Xi Chen

    (School of Economics and Resource Management, Beijing Normal University, Beijing 100875, China)

  • Yawen Sun

    (Institute of European Studies of Chinese Academy of Social Sciences, Beijing 100732, China)

Abstract

To relax the increasingly tight resource and environmental constraints on development, China needs to follow a pattern of growth that comprehensively encompasses economic growth, environmental protection, and resource conservation, namely, green economic growth. The key to achieving green economic growth is to improve green total factor productivity, of which technological innovation and institutional innovation are the primary driving forces. Based on the panel data of 266 cities in China from 2004 to 2018, this paper first uses the Directional Distance Function and Global Malmquist–Luenberger productivity index to measure the urban green total factor productivity to represent urban green economic growth; then, the impact of technological innovation and institutional innovation on urban green economic growth is studied by using the panel Granger causality test and SYS-GMM dynamic panel model. The results are described as follows: China’s urban green total factor productivity shows an increasing trend from 2004 to 2018, and the average growth rate of green total factor productivity is 3.27%, which is far lower than the average GDP growth rate of 9.14%; both technological innovation and institutional innovation can significantly promote the growth of the urban green economy, but institutional innovation has a greater role in promoting the growth of the urban green economy than technological innovation. In addition, the relationship between institutional innovation and urban green economic growth is more stable.

Suggested Citation

  • Jing Han & Xi Chen & Yawen Sun, 2021. "Technology or Institutions: Which Is the Source of Green Economic Growth in Chinese Cities?," Sustainability, MDPI, vol. 13(19), pages 1-20, October.
  • Handle: RePEc:gam:jsusta:v:13:y:2021:i:19:p:10934-:d:648191
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    as
    1. Liu, Yunqiang & Zhu, Jialing & Li, Eldon Y. & Meng, Zhiyi & Song, Yan, 2020. "Environmental regulation, green technological innovation, and eco-efficiency: The case of Yangtze river economic belt in China," Technological Forecasting and Social Change, Elsevier, vol. 155(C).
    2. Li, Bo & Dewan, Hasnat, 2017. "Efficiency differences among China's resource-based cities and their determinants," Resources Policy, Elsevier, vol. 51(C), pages 31-38.
    3. Lin, Boqiang & Zhu, Junpeng, 2019. "Fiscal spending and green economic growth: Evidence from China," Energy Economics, Elsevier, vol. 83(C), pages 264-271.
    4. Du, Juan & Chen, Yao & Huang, Ying, 2018. "A Modified Malmquist-Luenberger Productivity Index: Assessing Environmental Productivity Performance in China," European Journal of Operational Research, Elsevier, vol. 269(1), pages 171-187.
    5. Jia, Junxue & Guo, Qingwang & Zhang, Jing, 2014. "Fiscal decentralization and local expenditure policy in China," China Economic Review, Elsevier, vol. 28(C), pages 107-122.
    6. Pang, Rui-Zhi & Deng, Zhong-Qi & Hu, Jin-li, 2015. "Clean energy use and total-factor efficiencies: An international comparison," Renewable and Sustainable Energy Reviews, Elsevier, vol. 52(C), pages 1158-1171.
    7. Yujiao Xian & Ke Wang & Xunpeng Shi & Chi Zhang & Yi-Ming Wei & Zhimin Huang, 2018. "Carbon emissions intensity reduction target for China¡¯s power industry: An efficiency and productivity perspective," CEEP-BIT Working Papers 117, Center for Energy and Environmental Policy Research (CEEP), Beijing Institute of Technology.
    8. Wang, Yun & Sun, Xiaohua & Guo, Xu, 2019. "Environmental regulation and green productivity growth: Empirical evidence on the Porter Hypothesis from OECD industrial sectors," Energy Policy, Elsevier, vol. 132(C), pages 611-619.
    9. Cheng, Zhonghua & Li, Xiang & Wang, Meixiao, 2021. "Resource curse and green economic growth," Resources Policy, Elsevier, vol. 74(C).
    10. Glass, Anthony & Kenjegalieva, Karligash & Paez-Farrell, Juan, 2013. "Productivity growth decomposition using a spatial autoregressive frontier model," Economics Letters, Elsevier, vol. 119(3), pages 291-295.
    11. Arellano, Manuel & Bover, Olympia, 1995. "Another look at the instrumental variable estimation of error-components models," Journal of Econometrics, Elsevier, vol. 68(1), pages 29-51, July.
    12. Helvoigt, Ted L. & Adams, Darius M., 2009. "A stochastic frontier analysis of technical progress, efficiency change and productivity growth in the Pacific Northwest sawmill industry," Forest Policy and Economics, Elsevier, vol. 11(4), pages 280-287, July.
    13. Liu, Zuankuo & Xin, Li, 2019. "Has China's Belt and Road Initiative promoted its green total factor productivity?——Evidence from primary provinces along the route," Energy Policy, Elsevier, vol. 129(C), pages 360-369.
    14. Pastor, Jesus T. & Lovell, C.A. Knox, 2005. "A global Malmquist productivity index," Economics Letters, Elsevier, vol. 88(2), pages 266-271, August.
    15. Reilly, John M., 2012. "Green growth and the efficient use of natural resources," Energy Economics, Elsevier, vol. 34(S1), pages 85-93.
    16. Blundell, Richard & Bond, Stephen, 1998. "Initial conditions and moment restrictions in dynamic panel data models," Journal of Econometrics, Elsevier, vol. 87(1), pages 115-143, August.
    17. Sohag, Kazi & Taşkın, F. Dilvin & Malik, Muhammad Nasir, 2019. "Green economic growth, cleaner energy and militarization: Evidence from Turkey," Resources Policy, Elsevier, vol. 63(C), pages 1-1.
    18. Hartwig, Jochen, 2010. "Is health capital formation good for long-term economic growth? - Panel Granger-causality evidence for OECD countries," Journal of Macroeconomics, Elsevier, vol. 32(1), pages 314-325, March.
    19. Granger, C. W. J. & Newbold, P., 1974. "Spurious regressions in econometrics," Journal of Econometrics, Elsevier, vol. 2(2), pages 111-120, July.
    20. Smulders, Sjak & Withagen, Cees, 2012. "Green growth -- lessons from growth theory," Policy Research Working Paper Series 6230, The World Bank.
    21. Albrizio, Silvia & Kozluk, Tomasz & Zipperer, Vera, 2017. "Environmental policies and productivity growth: Evidence across industries and firms," Journal of Environmental Economics and Management, Elsevier, vol. 81(C), pages 209-226.
    22. 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).
    23. Davis, Lance & North, Douglass, 1970. "Institutional Change and American Economic Growth: A First Step Towards a Theory of Institutional Innovation," The Journal of Economic History, Cambridge University Press, vol. 30(1), pages 131-149, March.
    24. World Bank, 2012. "Inclusive Green Growth : The Pathway to Sustainable Development," World Bank Publications - Books, The World Bank Group, number 6058, December.
    25. Manuel Arellano & Stephen Bond, 1991. "Some Tests of Specification for Panel Data: Monte Carlo Evidence and an Application to Employment Equations," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 58(2), pages 277-297.
    26. Manello, Alessandro, 2017. "Productivity growth, environmental regulation and win–win opportunities: The case of chemical industry in Italy and Germany," European Journal of Operational Research, Elsevier, vol. 262(2), pages 733-743.
    27. Zhang, Cheng & Guo, Bingnan & Wang, Jianke, 2014. "The different impacts of home countries characteristics in FDI on Chinese spillover effects: Based on one-stage SFA," Economic Modelling, Elsevier, vol. 38(C), pages 572-580.
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    Cited by:

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    2. Hisham Alidrisi, 2021. "The Development of an Efficiency-Based Global Green Manufacturing Innovation Index: An Input-Oriented DEA Approach," Sustainability, MDPI, vol. 13(22), pages 1-11, November.
    3. Kai Chen & Feng Guo & Shuang Xu, 2022. "The Impact of Digital Economy Agglomeration on Regional Green Total Factor Productivity Disparity: Evidence from 285 Cities in China," Sustainability, MDPI, vol. 14(22), pages 1-16, November.

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