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The impact of natural resource dependence and green finance on green economic growth in the context of COP26

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  • Tan, Junlan
  • Su, Xiang
  • Wang, Rong

Abstract

The cop26 conference proposed that in order to cope with climate change, global countries need to focus on green economic growth (GEG) and accelerate green transformation. This paper adopts panel data of 30 provinces in China from 2008 to 2021 to measure the level of regional GEG, incorporating natural resource dependence, green finance and regional GEG into an overall research framework, and using a systematic GMM model to explore the relationship of them, and concludes as follows: (1) In the temporal dimension, GEG in China has increased, and each province generally shows a “U" shape development trend. From the spatial dimension, the overall change trend of each region shows that the GEG of each region in China shows an upward trend, with the western region increasing more and the eastern region increasing the least. (2) The phenomenon of “resource curse” exists in the eastern, western regions and the whole country, while insignificant in the central region, which does not reflect the “resource curse effect”. Green finance has a significant positive effect on the GEG of all the regions, with the most significant effect value in west, followed by Central and the weakest in East. (3) The per capita GDP of all regions can improve GEG. Environmental regulation promotes GEG at the national level and in the east, with a non-significant effect test in central and a negative in western region. Human capital level promotes GEG in all regions; foreign direct investment promotes GEG in all regions. The work can provide reference for achieving regional green economic transformation.

Suggested Citation

  • Tan, Junlan & Su, Xiang & Wang, Rong, 2023. "The impact of natural resource dependence and green finance on green economic growth in the context of COP26," Resources Policy, Elsevier, vol. 81(C).
    • Handle: RePEc:eee:jrpoli:v:81:y:2023:i:c:s0301420723000594
    DOI: 10.1016/j.resourpol.2023.103351
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    1. Christopher F Baum & Mark E. Schaffer & Steven Stillman, 2003. "Instrumental variables and GMM: Estimation and testing," Stata Journal, StataCorp LP, vol. 3(1), pages 1-31, March.
    2. Zhang, Dongyang & Mohsin, Muhammad & Rasheed, Abdul Khaliq & Chang, Youngho & Taghizadeh-Hesary, Farhad, 2021. "Public spending and green economic growth in BRI region: Mediating role of green finance," Energy Policy, Elsevier, vol. 153(C).
    3. Montfort Mlachila & René Tapsoba & Sampawende J. A. Tapsoba, 2017. "A Quality of Growth Index for Developing Countries: A Proposal," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 134(2), pages 675-710, November.
    4. Umar, Muhammad & Ji, Xiangfeng & Mirza, Nawazish & Rahat, Birjees, 2021. "The impact of resource curse on banking efficiency: Evidence from twelve oil producing countries," Resources Policy, Elsevier, vol. 72(C).
    5. Per Andersen & Niels Christian Petersen, 1993. "A Procedure for Ranking Efficient Units in Data Envelopment Analysis," Management Science, INFORMS, vol. 39(10), pages 1261-1264, October.
    6. Hallegatte, Stephane & Heal, Geoffrey & Fay, Marianne & Treguer, David, 2011. "From growth to green growth -- a framework," Policy Research Working Paper Series 5872, The World Bank.
    7. Richard Blundell & Stephen Bond, 2000. "GMM Estimation with persistent panel data: an application to production functions," Econometric Reviews, Taylor & Francis Journals, vol. 19(3), pages 321-340.
    8. Charnes, A. & Cooper, W. W. & Rhodes, E., 1978. "Measuring the efficiency of decision making units," European Journal of Operational Research, Elsevier, vol. 2(6), pages 429-444, November.
    9. Belaid, Fateh & Dagher, Leila & Filis, George, 2021. "Revisiting the resource curse in the MENA region," Resources Policy, Elsevier, vol. 73(C).
    10. Lee, Chi-Chuan & Lee, Chien-Chiang, 2022. "How does green finance affect green total factor productivity? Evidence from China," Energy Economics, Elsevier, vol. 107(C).
    11. Anne D. Boschini & Jan Pettersson & Jesper Roine, 2007. "Resource Curse or Not: A Question of Appropriability," Scandinavian Journal of Economics, Wiley Blackwell, vol. 109(3), pages 593-617, September.
    12. Inesa Mikhno & Viktor Koval & Galyna Shvets & Oksana Garmatiuk & Rima Tamošiūnienė, 2021. "Green Economy in Sustainable Development and Improvement of Resource Efficiency," Central European Business Review, Prague University of Economics and Business, vol. 2021(1), pages 99-113.
    13. Martin F. Quaas & Sjak Smulders, 2018. "Brown Growth, Green Growth, and the Efficiency of Urbanization," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 71(2), pages 529-549, October.
    14. Taghizadeh-Hesary, Farhad & Yoshino, Naoyuki, 2019. "The way to induce private participation in green finance and investment," Finance Research Letters, Elsevier, vol. 31(C), pages 98-103.
    15. Alwyn Young, 2003. "Gold into Base Metals: Productivity Growth in the People's Republic of China during the Reform Period," Journal of Political Economy, University of Chicago Press, vol. 111(6), pages 1220-1261, December.
    16. Mealy, Penny & Teytelboym, Alexander, 2022. "Economic complexity and the green economy," Research Policy, Elsevier, vol. 51(8).
    17. Addisu A Lashitew & Michael L Ross & Eric Werker, 2021. "What Drives Successful Economic Diversification in Resource-Rich Countries? [“Blocking the Pathway out of the Resource Curse: What Hinders Diversification in Resource-rich Developing Countries?”]," The World Bank Research Observer, World Bank, vol. 36(2), pages 164-196.
    18. Hua Tao & Min Tao & Rong Wang, 2022. "Do Education Human Capital and Environmental Regulation Drive the Growth Efficiency of the Green Economy in China?," Sustainability, MDPI, vol. 14(24), pages 1-20, December.
    19. Ben Lahouel, Béchir & Taleb, Lotfi & Ben Zaied, Younes & Managi, Shunsuke, 2021. "Does ICT change the relationship between total factor productivity and CO2 emissions? Evidence based on a nonlinear model," Energy Economics, Elsevier, vol. 101(C).
    20. Olsen, Karen Holm & Fenhann, Jørgen, 2008. "Sustainable development benefits of clean development mechanism projects: A new methodology for sustainability assessment based on text analysis of the project design documents submitted for validatio," Energy Policy, Elsevier, vol. 36(8), pages 2773-2784, August.
    21. R. D. Banker & A. Charnes & W. W. Cooper, 1984. "Some Models for Estimating Technical and Scale Inefficiencies in Data Envelopment Analysis," Management Science, INFORMS, vol. 30(9), pages 1078-1092, September.
    22. D'Amato, D. & Korhonen, J., 2021. "Integrating the green economy, circular economy and bioeconomy in a strategic sustainability framework," Ecological Economics, Elsevier, vol. 188(C).
    23. Michael Wara, 2007. "Is the global carbon market working?," Nature, Nature, vol. 445(7128), pages 595-596, February.
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    Cited by:

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    3. Minye Rao & László Vasa & Yudan Xu & Pinghua Chen, 2023. "Spatial and Heterogeneity Analysis of Environmental Taxes’ Impact on China’s Green Economy Development: A Sustainable Development Perspective," Sustainability, MDPI, vol. 15(12), pages 1-16, June.
    4. Henryk Dzwigol & Aleksy Kwilinski & Oleksii Lyulyov & Tetyana Pimonenko, 2023. "The Role of Environmental Regulations, Renewable Energy, and Energy Efficiency in Finding the Path to Green Economic Growth," Energies, MDPI, vol. 16(7), pages 1-18, March.
    5. Wanzhe Chen & Jiaqi Liu & Xuanwei Ning & Lei Du & Yang Zhang & Chengliang Wu, 2023. "Low-Carbon City Building and Green Development: New Evidence from Quasi Natural Experiments from 277 Cities in China," Sustainability, MDPI, vol. 15(15), pages 1-28, July.
    6. Kong, Yan & Dong, Chuntong & Zhang, Yingyu, 2023. "Quantile on Quantile Analysis of Natural resources-growth and geopolitical risk trilemma," Resources Policy, Elsevier, vol. 85(PA).

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