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Impact of Green Innovation Efficiency on Carbon Emission Reduction in the Guangdong-Hong Kong-Macao GBA

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  • Lingming Chen

    (School of Business, Hunan University of Science and Technology (HNUST), Xiangtan 411201, China
    School of Economics and Management, Xinyu University (XYU), Xinyu 338004, China)

  • Congjia Huo

    (School of Business, Hunan University of Science and Technology (HNUST), Xiangtan 411201, China)

Abstract

Climate change has become a global issue of general concern to human society. It is not only an environmental issue, but also a development issue. As the second largest economy in the world, China has adhered to its commitments in the Paris Agreement and formulated a series of autonomous action targets. In this context, scholars have done a lot of research focusing on carbon emission reduction, but have neglected the spatial correlation of carbon emission, and lack of research on carbon emission reduction in urban agglomerations. The Guangdong-Hong Kong-Macao Greater Bay Area (GBA) has been at the forefront of China in terms of economy, politics, ecology, and civilization by taking advantage of the “one country, two systems” policy. This article innovatively proposes that there is a non-linear relationship between the efficiency of green innovation and the carbon emission intensity of the Guangdong-Hong Kong-Macao GBA, and has passed quantitative verification. Based on the panel data of the Guangdong-Hong Kong-Macao GBA from 2009 to 2019, we used the super-efficiency slacks-based measure (SBM) model to measure the efficiency of green innovation. We used the global Moran index and Theil index to discuss the spatial correlation of carbon emissions and regional differences in carbon emission intensity in the Guangdong-Hong Kong-Macao GBA, respectively. Then, we used the threshold model to verify the nonlinear relationship between the efficiency of green innovation and the intensity of carbon emissions in the Guangdong-Hong Kong-Macao GBA. The results of the study found that the green innovation efficiency of the Guangdong-Hong Kong-Macao GBA is increasing overall, carbon emissions have a certain spatial correlation, and the correlation is low overall. The impact of green innovation efficiency on carbon emission intensity has a non-linear relationship and there is an “inverted U” pattern between the two, and there is an inflection point in green innovation efficiency. Based on this, this article proposes carbon emission reduction measures within a reasonable range, and looks forward to future research directions and complement the research deficiencies.

Suggested Citation

  • Lingming Chen & Congjia Huo, 2021. "Impact of Green Innovation Efficiency on Carbon Emission Reduction in the Guangdong-Hong Kong-Macao GBA," Sustainability, MDPI, vol. 13(23), pages 1-22, December.
    • Handle: RePEc:gam:jsusta:v:13:y:2021:i:23:p:13450-:d:695434
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    1. Azomahou, Theophile & Laisney, Francois & Nguyen Van, Phu, 2006. "Economic development and CO2 emissions: A nonparametric panel approach," Journal of Public Economics, Elsevier, vol. 90(6-7), pages 1347-1363, August.
    2. van der Zwaan, B. C. C. & Gerlagh, R. & G. & Klaassen & Schrattenholzer, L., 2002. "Endogenous technological change in climate change modelling," Energy Economics, Elsevier, vol. 24(1), pages 1-19, January.
    3. Hansen, Bruce E., 1999. "Threshold effects in non-dynamic panels: Estimation, testing, and inference," Journal of Econometrics, Elsevier, vol. 93(2), pages 345-368, December.
    4. Ambec, Stefan & Barla, Philippe, 2002. "A theoretical foundation of the Porter hypothesis," Economics Letters, Elsevier, vol. 75(3), pages 355-360, May.
    5. Park, Se-Hark, 1992. "Decomposition of industrial energy consumption : An alternative method," Energy Economics, Elsevier, vol. 14(4), pages 265-270, October.
    6. 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.
    7. Ang, B.W & Zhang, F.Q & Choi, Ki-Hong, 1998. "Factorizing changes in energy and environmental indicators through decomposition," Energy, Elsevier, vol. 23(6), pages 489-495.
    8. 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).
    9. Musolesi Antonio & Mazzanti Massimiliano, 2014. "Nonlinearity, heterogeneity and unobserved effects in the carbon dioxide emissions-economic development relation for advanced countries," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 18(5), pages 521-541, December.
    10. He, Weijun & Wang, Bo & Danish, & Wang, Zhaohua, 2018. "Will regional economic integration influence carbon dioxide marginal abatement costs? Evidence from Chinese panel data," Energy Economics, Elsevier, vol. 74(C), pages 263-274.
    11. Yu-Shan Chen & Shyh-Bao Lai & Chao-Tung Wen, 2006. "The Influence of Green Innovation Performance on Corporate Advantage in Taiwan," Journal of Business Ethics, Springer, vol. 67(4), pages 331-339, September.
    12. Lingming Chen & Wenzhong Ye & Congjia Huo & Kieran James, 2020. "Environmental Regulations, the Industrial Structure, and High-Quality Regional Economic Development: Evidence from China," Land, MDPI, vol. 9(12), pages 1-22, December.
    13. Baoliu Liu & Zhenqing Sun & Huanhuan Li, 2021. "Can Carbon Trading Policies Promote Regional Green Innovation Efficiency? Empirical Data from Pilot Regions in China," Sustainability, MDPI, vol. 13(5), pages 1-15, March.
    14. 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.
    15. Jianchang Lu & Weiguo Fan & Ming Meng, 2015. "Empirical Research on China’s Carbon Productivity Decomposition Model Based on Multi-Dimensional Factors," Energies, MDPI, vol. 8(4), pages 1-25, April.
    16. Rajiv D. Banker & Richard C. Morey, 1986. "Efficiency Analysis for Exogenously Fixed Inputs and Outputs," Operations Research, INFORMS, vol. 34(4), pages 513-521, August.
    17. Tetsuya Tsurumi & Shunsuke Managi, 2010. "Decomposition of the environmental Kuznets curve: scale, technique, and composition effects," Environmental Economics and Policy Studies, Springer;Society for Environmental Economics and Policy Studies - SEEPS, vol. 11(1), pages 19-36, February.
    18. Boyd, Gale A. & Hanson, Donald A. & Sterner, Thomas, 1988. "Decomposition of changes in energy intensity : A comparison of the Divisia index and other methods," Energy Economics, Elsevier, vol. 10(4), pages 309-312, October.
    19. Vanessa Oltra & Maïder Saint Jean, 2009. "Sectoral systems of environmental innovation: an application to the French automotive industry," Post-Print hal-00274413, HAL.
    20. Apergis, Nicholas & Eleftheriou, Sofia & Payne, James E., 2013. "The relationship between international financial reporting standards, carbon emissions, and R&D expenditures: Evidence from European manufacturing firms," Ecological Economics, Elsevier, vol. 88(C), pages 57-66.
    21. Kumar, Surender & Managi, Shunsuke, 2009. "Energy price-induced and exogenous technological change: Assessing the economic and environmental outcomes," Resource and Energy Economics, Elsevier, vol. 31(4), pages 334-353, November.
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    Cited by:

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    3. Jing Liang & Lingying Pan, 2023. "Effect of Scale and Structure Changes of China’s High-Carbon Industries on Regional Carbon Emissions," Energies, MDPI, vol. 16(18), pages 1-17, September.
    4. Qingzhi Huan & Yiwen Chen & Xincong Huan, 2022. "A Frugal Eco-Innovation Policy? Ecological Poverty Alleviation in Contemporary China from a Perspective of Eco-Civilization Progress," Sustainability, MDPI, vol. 14(8), pages 1-16, April.
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    6. Weisong Mi & Kaixu Zhao & Pei Zhang, 2022. "Spatio-Temporal Evolution and Driving Mechanism of Green Innovation in China," Sustainability, MDPI, vol. 14(9), pages 1-27, April.

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