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Environmental Regulation, Factor Marketisation Allocation and Carbon Emissions Performance: Empirical Evidence from Resource-Based Cities in China

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  • Jiaming Wang

    (School of Economics and Management, Chinese and Law, Shandong Institute of Petroleum and Chemical Technology, Dongying 257061, China)

  • Chengyao Lin

    (School of Economics and Management, Chinese and Law, Shandong Institute of Petroleum and Chemical Technology, Dongying 257061, China)

  • Xiangyun Wang

    (School of Economics and Management, Chinese and Law, Shandong Institute of Petroleum and Chemical Technology, Dongying 257061, China)

  • Shuwen Wang

    (School of Economics and Management, Chinese and Law, Shandong Institute of Petroleum and Chemical Technology, Dongying 257061, China)

Abstract

Resource-based cities had an irreplaceable role in the process of the economic miracle in China. Advancing such cities’ carbon emissions reduction is a crucial aspect of the country’s steady realisation of the dual carbon peak and neutrality strategy. The reasonable implementation of environmental regulation and the efficiency of factor marketisation allocation are the key links for resource-based cities to improve carbon emissions performance, break the resource curse and reduce carbon emissions. Based on this, this study centres on the driving relationship between environmental regulation, the efficiency of factor marketisation allocation and carbon emissions performance as the core research problem. This study takes the panel data of 116 resource-based cities in China from 2006 to 2020 as the research sample; the non-radial meta-frontier total factor carbon emissions performance index is selected as the measurement index of carbon emission performance of resource-based cities based on the applicability analysis of the model. This study explores the characteristics of regional heterogeneity and type heterogeneity of carbon emissions performance driven by environmental regulation under the moderating effect of the efficiency of factor marketisation allocation and further explores the threshold effect, aiming to clarify the driving relationship between the three. The findings reveal that the driving effect of environmental regulation intensity on carbon emissions performance exhibits a fluctuating upward trend, the effect transformed by compliance cost and innovation compensation. The efficiency of factor marketisation allocation has a double threshold superposition effect on carbon emissions performance fluctuation that is driven by environmental regulation, indicating that market and government effectiveness can operate together to improve the carbon emissions performance. Based on these results, this study proposes countermeasures and suggestions for improving carbon emissions performance using environmental regulation and the efficiency of factor marketisation allocation.

Suggested Citation

  • Jiaming Wang & Chengyao Lin & Xiangyun Wang & Shuwen Wang, 2024. "Environmental Regulation, Factor Marketisation Allocation and Carbon Emissions Performance: Empirical Evidence from Resource-Based Cities in China," Sustainability, MDPI, vol. 16(17), pages 1-24, August.
    • Handle: RePEc:gam:jsusta:v:16:y:2024:i:17:p:7265-:d:1462815
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    1. Jagdish N. Bhagwati & Richard A. Brecher & Tatsuo Hatta, 1985. "The Generalized Theory of Transfers and Welfare: Exogenous (policy-Imposed) and Endogenous (Transfer-Induced) Distortion," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 100(3), pages 697-714.
    2. Eibinger, Tobias & Deixelberger, Beate & Manner, Hans, 2024. "Panel data in environmental economics: Econometric issues and applications to IPAT models," Journal of Environmental Economics and Management, Elsevier, vol. 125(C).
    3. Färe, Rolf & Grosskopf, Shawna, 2010. "Directional distance functions and slacks-based measures of efficiency: Some clarifications," European Journal of Operational Research, Elsevier, vol. 206(3), pages 702-702, November.
    4. Daniel L. Millimet & Jayjit Roy, 2016. "Empirical Tests of the Pollution Haven Hypothesis When Environmental Regulation is Endogenous," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 31(4), pages 652-677, June.
    5. Wu, Haitao & Hao, Yu & Ren, Siyu, 2020. "How do environmental regulation and environmental decentralization affect green total factor energy efficiency: Evidence from China," Energy Economics, Elsevier, vol. 91(C).
    6. Zhang, Ning & Wei, Xiao, 2015. "Dynamic total factor carbon emissions performance changes in the Chinese transportation industry," Applied Energy, Elsevier, vol. 146(C), pages 409-420.
    7. Badunenko, Oleg & Galeotti, Marzio & Hunt, Lester C., 2023. "Better to grow or better to improve? Measuring environmental efficiency in OECD countries with a stochastic environmental Kuznets frontier (SEKF)," Energy Economics, Elsevier, vol. 121(C).
    8. Siami, Navid & Winter, Ralph A., 2021. "Jevons’ paradox revisited: Implications for climate change," Economics Letters, Elsevier, vol. 206(C).
    9. Tombe, Trevor & Winter, Jennifer, 2015. "Environmental policy and misallocation: The productivity effect of intensity standards," Journal of Environmental Economics and Management, Elsevier, vol. 72(C), pages 137-163.
    10. Jiang, Tangyang & Cao, Chi & Lei, Leyuan & Hou, Jie & Yu, Yang & Jahanger, Atif, 2023. "Temporal and spatial patterns, efficiency losses and impact factors of energy mismatch in China under environmental constraints," Energy, Elsevier, vol. 282(C).
    11. Färe, Rolf & Grosskopf, Shawna, 2010. "Directional distance functions and slacks-based measures of efficiency," European Journal of Operational Research, Elsevier, vol. 200(1), pages 320-322, January.
    12. 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.
    13. Yang, Qiuyue & Song, Deyong, 2019. "How does environmental regulation break the resource curse: Theoretical and empirical study on China," Resources Policy, Elsevier, vol. 64(C).
    14. Hamaguchi, Yoshihiro, 2023. "Environmental tax evasion as a determinant of the Porter and pollution haven hypotheses in a corrupt political system," Economic Analysis and Policy, Elsevier, vol. 79(C), pages 610-633.
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