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Can industrial agglomeration achieve the emission-reduction effect?

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  • Shen, Neng
  • Peng, Hui

Abstract

This paper adopted the Meta-constraints efficiency model to measure the environmental efficiency of the industry in China, and then used the spatial panel model to analyze the impact of industrial agglomeration externalities on environmental efficiency. The study found that industrial agglomeration exerted an apparent spatial spillover effect. Different agglomeration degrees and means may be matched with different environmental effects. With the evolution of agglomeration, the balanced effects among negative externality of scale (pollution effect). Marshallian and Jacobs positive externality (self-purification effect) lead to a U-curved tendency between industrial agglomeration and environmental efficiency. Therefore, with the increase of industrial agglomeration degree, the environmental efficiency first decreases and then increases. The effect of industrial agglomeration in the Midwest on the environment is mainly presented as a negative externality of scale, situated in the descending phase of the U curve. However, the effect of eastern industrial agglomeration on the environment mainly manifested as Marshallian and Jacobs positive externalities and was situated close to the ascending phase of the U curve. All regions should fully utilize the “self-purification” effect of the Marshallian externality and the Jacobs externality on emission-reduction according to the different phases of industrial development.

Suggested Citation

  • Shen, Neng & Peng, Hui, 2021. "Can industrial agglomeration achieve the emission-reduction effect?," Socio-Economic Planning Sciences, Elsevier, vol. 75(C).
  • Handle: RePEc:eee:soceps:v:75:y:2021:i:c:s0038012119305129
    DOI: 10.1016/j.seps.2020.100867
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    1. 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.
    2. Verhoef, Erik T. & Nijkamp, Peter, 2002. "Externalities in urban sustainability: Environmental versus localization-type agglomeration externalities in a general spatial equilibrium model of a single-sector monocentric industrial city," Ecological Economics, Elsevier, vol. 40(2), pages 157-179, February.
    3. Zeng, Dao-Zhi & Zhao, Laixun, 2009. "Pollution havens and industrial agglomeration," Journal of Environmental Economics and Management, Elsevier, vol. 58(2), pages 141-153, September.
    4. Grossman, G.M & Krueger, A.B., 1991. "Environmental Impacts of a North American Free Trade Agreement," Papers 158, Princeton, Woodrow Wilson School - Public and International Affairs.
    5. Ulrich Wagner & Christopher Timmins, 2009. "Agglomeration Effects in Foreign Direct Investment and the Pollution Haven Hypothesis," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 43(2), pages 231-256, June.
    6. Iwata, Hiroki & Okada, Keisuke & Samreth, Sovannroeun, 2010. "Empirical study on the environmental Kuznets curve for CO2 in France: The role of nuclear energy," Energy Policy, Elsevier, vol. 38(8), pages 4057-4063, August.
    7. QIN, Bo & WU, Jianfeng, 2015. "Does urban concentration mitigate CO2 emissions? Evidence from China 1998–2008," China Economic Review, Elsevier, vol. 35(C), pages 220-231.
    8. Zhang, Ning & Yu, Keren & Chen, Zhongfei, 2017. "How does urbanization affect carbon dioxide emissions? A cross-country panel data analysis," Energy Policy, Elsevier, vol. 107(C), pages 678-687.
    9. John Ehrenfeld, 2003. "Putting a Spotlight on Metaphors and Analogies in Industrial Ecology," Journal of Industrial Ecology, Yale University, vol. 7(1), pages 1-4, January.
    10. Christopher O’Donnell & D. Rao & George Battese, 2008. "Metafrontier frameworks for the study of firm-level efficiencies and technology ratios," Empirical Economics, Springer, vol. 34(2), pages 231-255, March.
    11. Ekpeno L. Effiong, 2018. "On the urbanization-pollution nexus in Africa: a semiparametric analysis," Quality & Quantity: International Journal of Methodology, Springer, vol. 52(1), pages 445-456, January.
    12. Hong, Jingke & Gu, Jianping & Liang, Xin & Liu, Guiwen & Shen, Geoffrey Qiping & Tang, Miaohan, 2019. "Spatiotemporal investigation of energy network patterns of agglomeration economies in China: Province-level evidence," Energy, Elsevier, vol. 187(C).
    13. Mi, Zhifu & Zhang, Yunkun & Guan, Dabo & Shan, Yuli & Liu, Zhu & Cong, Ronggang & Yuan, Xiao-Chen & Wei, Yi-Ming, 2016. "Consumption-based emission accounting for Chinese cities," Applied Energy, Elsevier, vol. 184(C), pages 1073-1081.
    14. Siqi Zheng & Matthew E. Kahn, 2013. "Understanding China's Urban Pollution Dynamics," Journal of Economic Literature, American Economic Association, vol. 51(3), pages 731-772, September.
    15. Holtedahl, Pernille & Joutz, Frederick L., 2004. "Residential electricity demand in Taiwan," Energy Economics, Elsevier, vol. 26(2), pages 201-224, March.
    16. Xu, Bin & Lin, Boqiang, 2015. "How industrialization and urbanization process impacts on CO2 emissions in China: Evidence from nonparametric additive regression models," Energy Economics, Elsevier, vol. 48(C), pages 188-202.
    17. George E. Battese & D. S. Prasada Rao, 2002. "Technology Gap, Efficiency, and a Stochastic Metafrontier Function," International Journal of Business and Economics, School of Management Development, Feng Chia University, Taichung, Taiwan, vol. 1(2), pages 87-93, August.
    18. Reinhard, Stijn & Knox Lovell, C. A. & Thijssen, Geert J., 2000. "Environmental efficiency with multiple environmentally detrimental variables; estimated with SFA and DEA," European Journal of Operational Research, Elsevier, vol. 121(2), pages 287-303, March.
    19. Akihiro Otsuka & Mika Goto & Toshiyuki Sueyoshi, 2014. "Energy efficiency and agglomeration economies: the case of Japanese manufacturing industries," Regional Science Policy & Practice, Wiley Blackwell, vol. 6(2), pages 195-212, June.
    20. Huang, Hai-Jun & Xia, Tian & Tian, Qiong & Liu, Tian-Liang & Wang, Chenlan & Li, Daqing, 2020. "Transportation issues in developing China's urban agglomerations," Transport Policy, Elsevier, vol. 85(C), pages 1-22.
    21. Cole, Matthew A. & Elliott, Robert J.R. & Wu, Shanshan, 2008. "Industrial activity and the environment in China: An industry-level analysis," China Economic Review, Elsevier, vol. 19(3), pages 393-408, September.
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