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Regional Differences, Distribution Dynamics, and Convergence of the Green Total Factor Productivity of China’s Cities under the Dual Carbon Targets

Author

Listed:
  • Long Qian

    (School of Economics and Management, Anhui Polytechnic University, Wuhu 241000, China)

  • Yunjie Zhou

    (School of Economics and Management, Anhui Polytechnic University, Wuhu 241000, China)

  • Ying Sun

    (School of Economics and Management, Anhui Polytechnic University, Wuhu 241000, China)

Abstract
Economic development in China has been severely restricted by environmental problems such as carbon emissions. Improving green total factor productivity (GTFP) is an extremely important pathway to realizing carbon peak and carbon neutrality. Nevertheless, existing studies on China’s urban GTFP under the carbon emissions constraint are still insufficient. In this context, this study adopts the directional distance function (DDF), includes carbon emissions in the undesirable output, combines the global Malmquist–Luenberger (GML) productivity index, and calculates the GTFP of China’s cities. On this basis, the Dagum Gini coefficient, kernel density estimation, and convergence model are employed to explore the regional differences, distribution dynamics, and convergence in China and in three subdivision regions of east, center, and west. The core conclusions are as follows: (1) the average annual growth rate of GTFP in China’s cities is about 0.7064%, which is relatively low, but there is great room for improvement. The growth trend of GTFP in the three subdivision regions of east, center and west is obvious, presenting a spatial distribution characteristic of “high in the east and low in the west”; (2) the regional differences in GTFP of these cities are enlarging, with the largest gap in the eastern region and the smallest in the western region. Intraregional difference is the primary source of regional differences; (3) the imbalance in urban GTFP in China is prominent, with noticeable gradient differences, making it difficult to achieve hierarchical crossing. The central and western regions even have multilevel differentiation problems; (4) there is an absolute β convergence and conditional β convergence of China’s GTFP, but no σ convergence. As a result, it is necessary to comprehensively consider and actively implement the concept of shared development, enhance technological progress, focus on narrowing the differences in GTFP, and facilitate coordinated green development within the regions.

Suggested Citation

  • Long Qian & Yunjie Zhou & Ying Sun, 2023. "Regional Differences, Distribution Dynamics, and Convergence of the Green Total Factor Productivity of China’s Cities under the Dual Carbon Targets," Sustainability, MDPI, vol. 15(17), pages 1-26, August.
    • Handle: RePEc:gam:jsusta:v:15:y:2023:i:17:p:12999-:d:1227808
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    1. Jeyhun I. Mikayilov & Marzio Galeotti & Fakhri J. Hasanov, 2018. "The Impact of Economic Growth on CO2 Emissions in Azerbaijan," IEFE Working Papers 102, IEFE, Center for Research on Energy and Environmental Economics and Policy, Universita' Bocconi, Milano, Italy.
    2. Suyang Xiao & Susu Wang & Fanhua Zeng & Wei-Chiao Huang, 2022. "Spatial Differences and Influencing Factors of Industrial Green Total Factor Productivity in Chinese Industries," Sustainability, MDPI, vol. 14(15), pages 1-24, July.
    3. Glaeser, Edward L. & Kahn, Matthew E., 2010. "The greenness of cities: Carbon dioxide emissions and urban development," Journal of Urban Economics, Elsevier, vol. 67(3), pages 404-418, May.
    4. Martina Halaskova & Beata Gavurova & Kristina Kocisova, 2020. "Research and Development Efficiency in Public and Private Sectors: An Empirical Analysis of EU Countries by Using DEA Methodology," Sustainability, MDPI, vol. 12(17), pages 1-22, August.
    5. Dagum, Camilo, 1997. "A New Approach to the Decomposition of the Gini Income Inequality Ratio," Empirical Economics, Springer, vol. 22(4), pages 515-531.
    6. Junwei Zhao & Yuxiang Zhang & Anhang Chen & Huiqin Zhang, 2022. "Analysis on the Spatio-Temporal Evolution Characteristics of the Impact of China’s Digitalization Process on Green Total Factor Productivity," IJERPH, MDPI, vol. 19(22), pages 1-21, November.
    7. Vivek Ghosal & Andreas Stephan & Jan F. Weiss, 2019. "Decentralized environmental regulations and plant‐level productivity," Business Strategy and the Environment, Wiley Blackwell, vol. 28(6), pages 998-1011, September.
    8. Florian Dorn & Stefanie Gaebler & Felix Roesel, 2021. "Ineffective fiscal rules? The effect of public sector accounting standards on budgets, efficiency, and accountability," Public Choice, Springer, vol. 186(3), pages 387-412, March.
    9. Guo, Qingbin & Wang, Yong & Dong, Xiaobin, 2022. "Effects of smart city construction on energy saving and CO2 emission reduction: Evidence from China," Applied Energy, Elsevier, vol. 313(C).
    10. Habtamu Alem, 2023. "The role of green total factor productivity to farm-level performance: evidence from Norwegian dairy farms," Agricultural and Food Economics, Springer;Italian Society of Agricultural Economics (SIDEA), vol. 11(1), pages 1-16, December.
    11. Ewa Cichowicz & Ewa Rollnik-Sadowska & Monika Dędys & Maria Ekes, 2021. "The DEA Method and Its Application Possibilities for Measuring Efficiency in the Public Sector—The Case of Local Public Employment Services," Economies, MDPI, vol. 9(2), pages 1-13, May.
    12. Dong-hyun Oh, 2010. "A global Malmquist-Luenberger productivity index," Journal of Productivity Analysis, Springer, vol. 34(3), pages 183-197, December.
    13. Liping Zhu & Rui Shi & Lincheng Mi & Pu Liu & Guofeng Wang, 2022. "Spatial Distribution and Convergence of Agricultural Green Total Factor Productivity in China," IJERPH, MDPI, vol. 19(14), pages 1-16, July.
    14. Chaofan Chen & Qingxin Lan & Ming Gao & Yawen Sun, 2018. "Green Total Factor Productivity Growth and Its Determinants in China’s Industrial Economy," Sustainability, MDPI, vol. 10(4), pages 1-25, April.
    15. K. J. Arrow, 1971. "The Economic Implications of Learning by Doing," Palgrave Macmillan Books, in: F. H. Hahn (ed.), Readings in the Theory of Growth, chapter 11, pages 131-149, Palgrave Macmillan.
    16. Chen, Xiang & Chen, Yong & Huang, Wenli & Zhang, Xuping, 2023. "A new Malmquist-type green total factor productivity measure: An application to China," Energy Economics, Elsevier, vol. 117(C).
    17. Fukuyama, Hirofumi & Weber, William L., 2009. "A directional slacks-based measure of technical inefficiency," Socio-Economic Planning Sciences, Elsevier, vol. 43(4), pages 274-287, December.
    18. Talwar, Shalini & Talwar, Manish & Kaur, Puneet & Dhir, Amandeep, 2020. "Consumers’ resistance to digital innovations: A systematic review and framework development," Australasian marketing journal, Elsevier, vol. 28(4), pages 286-299.
    19. Nihal Ahmed & Zeeshan Hamid & Farhan Mahboob & Khalil Ur Rehman & Muhammad Sibt e Ali & Piotr Senkus & Aneta Wysokińska-Senkus & Paweł Siemiński & Adam Skrzypek, 2022. "Causal Linkage among Agricultural Insurance, Air Pollution, and Agricultural Green Total Factor Productivity in United States: Pairwise Granger Causality Approach," Agriculture, MDPI, vol. 12(9), pages 1-17, August.
    20. Aigner, D J & Amemiya, Takeshi & Poirier, Dale J, 1976. "On the Estimation of Production Frontiers: Maximum Likelihood Estimation of the Parameters of a Discontinuous Density Function," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 17(2), pages 377-396, June.
    21. António Afonso & Ludger Schuknecht & Vito Tanzi, 2005. "Public sector efficiency: An international comparison," Public Choice, Springer, vol. 123(3), pages 321-347, June.
    22. Lindikaya W. Myeki & Nicolette Matthews & Yonas T. Bahta, 2023. "Decomposition of Green Agriculture Productivity for Policy in Africa: An Application of Global Malmquist–Luenberger Index," Sustainability, MDPI, vol. 15(2), pages 1-17, January.
    23. Jesús A. Tapia & Bonifacio Salvador, 2022. "Data envelopment analysis efficiency in the public sector using provider and customer opinion: An application to the Spanish health system," Health Care Management Science, Springer, vol. 25(2), pages 333-346, June.
    24. Liyuan Zhang & Xiang Ma & Young-Seok Ock & Lingli Qing, 2022. "Research on Regional Differences and Influencing Factors of Chinese Industrial Green Technology Innovation Efficiency Based on Dagum Gini Coefficient Decomposition," Land, MDPI, vol. 11(1), pages 1-20, January.
    25. Ivan Muñiz & Andrés Dominguez, 2020. "The Impact of Urban Form and Spatial Structure on per Capita Carbon Footprint in U.S. Larger Metropolitan Areas," Sustainability, MDPI, vol. 12(1), pages 1-19, January.
    26. 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.
    27. Wei Qian & Yongsheng Wang, 2022. "How Do Rising Labor Costs Affect Green Total Factor Productivity? Based on the Industrial Intelligence Perspective," Sustainability, MDPI, vol. 14(20), pages 1-19, October.
    28. Konstantinos Angelopoulos & Apostolis Philippopoulos & Efthymios Tsionas, 2008. "Does public sector efficiency matter? Revisiting the relation between fiscal size and economic growth in a world sample," Public Choice, Springer, vol. 137(1), pages 245-278, October.
    29. Bingfei Bao & Shengtian Jin & Lilian Li & Kaifeng Duan & Xiaomei Gong, 2021. "Analysis of Green Total Factor Productivity of Grain and Its Dynamic Distribution: Evidence from Poyang Lake Basin, China," Agriculture, MDPI, vol. 12(1), pages 1-16, December.
    30. Carlos Barros & Fernando Alves, 2004. "Productivity in the tourism industry," International Advances in Economic Research, Springer;International Atlantic Economic Society, vol. 10(3), pages 215-225, October.
    31. Chong Huang & Kedong Yin & Hongbo Guo & Benshuo Yang, 2022. "Regional Differences and Convergence of Inter-Provincial Green Total Factor Productivity in China under Technological Heterogeneity," IJERPH, MDPI, vol. 19(9), pages 1-20, May.
    32. Juan Tang & Fangming Qin, 2022. "Analyzing the impact of local government competition on green total factor productivity from the factor market distortion perspective: based on the three stage DEA model," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 24(12), pages 14298-14326, December.
    33. R. G. Chambers & Y. Chung & R. Färe, 1998. "Profit, Directional Distance Functions, and Nerlovian Efficiency," Journal of Optimization Theory and Applications, Springer, vol. 98(2), pages 351-364, August.
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