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Effect of population migration on spatial carbon emission transfers in China

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  • Gao, Cuixia
  • Tao, Simin
  • He, Yuyang
  • Su, Bin
  • Sun, Mei
  • Mensah, Isaac Adjei

Abstract

Large-scale population migration entails changes in productive and consumptive activities, which has enormous implications on the spatial relocation of carbon emissions. This study uses multiple methods to empirically assess the impact of interprovincial population migration of China on its trade-induced carbon transfers from a spatial view over 2002–2012. We constructed two networks of migration and carbon transfers, and based on the analysis of their topological structure, we inferred that carbon flows and migration are complements–larger migration flows typically correlate with larger trade-related carbon flows. Furthermore, we analyzed how migration affects interprovincial carbon transfers; in addition, we explored the geographical factor by dividing Chinese provinces into five subregions. The results illustrated that trade-induced carbon emissions situation in China was shaped partly by interprovincial migration at the national level. While the contribution of migration varies markedly across subregions owing to the unbalanced regional economic development and carbon intensity, migration-focused emission control strategy should be enhanced discriminatively to better understand China's inter-provincial joint energy conservation and emission reduction policy.

Suggested Citation

  • Gao, Cuixia & Tao, Simin & He, Yuyang & Su, Bin & Sun, Mei & Mensah, Isaac Adjei, 2021. "Effect of population migration on spatial carbon emission transfers in China," Energy Policy, Elsevier, vol. 156(C).
  • Handle: RePEc:eee:enepol:v:156:y:2021:i:c:s0301421521003207
    DOI: 10.1016/j.enpol.2021.112450
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    as
    1. Sgrignoli, Paolo & Metulini, Rodolfo & Schiavo, Stefano & Riccaboni, Massimo, 2015. "The relation between global migration and trade networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 417(C), pages 245-260.
    2. Francesc Ortega & Giovanni Peri, 2012. "The Effect of Trade and Migration on Income," NBER Working Papers 18193, National Bureau of Economic Research, Inc.
    3. Zhibo Zhao & Tian Yuan & Xunpeng Shi & Lingdi Zhao, 2020. "Heterogeneity in the relationship between carbon emission performance and urbanization: evidence from China," Mitigation and Adaptation Strategies for Global Change, Springer, vol. 25(7), pages 1363-1380, October.
    4. Zhifu Mi & Jing Meng & Dabo Guan & Yuli Shan & Malin Song & Yi-Ming Wei & Zhu Liu & Klaus Hubacek, 2017. "Chinese CO2 emission flows have reversed since the global financial crisis," Nature Communications, Nature, vol. 8(1), pages 1-10, December.
    5. Fang, Delin & Chen, Bin, 2019. "Information-based ecological network analysis for carbon emissions," Applied Energy, Elsevier, vol. 238(C), pages 45-53.
    6. Wei, Yi-Ming & Liu, Lan-Cui & Fan, Ying & Wu, Gang, 2007. "The impact of lifestyle on energy use and CO2 emission: An empirical analysis of China's residents," Energy Policy, Elsevier, vol. 35(1), pages 247-257, January.
    7. Francesc Ortega & Giovanni Peri, 2012. "The Effect of Trade and Migration on Income," NBER Working Papers 18193, National Bureau of Economic Research, Inc.
    8. Zhang, Hongwu & Shi, Xunpeng & Wang, Keying & Xue, Jinjun & Song, Ligang & Sun, Yongping, 2020. "Intertemporal lifestyle changes and carbon emissions: Evidence from a China household survey," Energy Economics, Elsevier, vol. 86(C).
    9. Li, Baibing & Martin, Elaine B. & Morris, A. Julian, 2002. "On principal component analysis in L1," Computational Statistics & Data Analysis, Elsevier, vol. 40(3), pages 471-474, September.
    10. Qi, Wei & Li, Guangdong, 2020. "Residential carbon emission embedded in China's inter-provincial population migration," Energy Policy, Elsevier, vol. 136(C).
    11. Su, Bin & Ang, B.W., 2014. "Input–output analysis of CO2 emissions embodied in trade: A multi-region model for China," Applied Energy, Elsevier, vol. 114(C), pages 377-384.
    12. Ma, Lin & Tang, Yang, 2020. "Geography, trade, and internal migration in China," Journal of Urban Economics, Elsevier, vol. 115(C).
    13. Zhang, Hongwu & Shi, Xunpeng & Cheong, Tsun Se & Wang, Keying, 2020. "Convergence of carbon emissions at the household level in China: A distribution dynamics approach," Energy Economics, Elsevier, vol. 92(C).
    14. PU, Zhengning & YUE, Shujing & GAO, Peng, 2020. "The driving factors of China's embodied carbon emissions," Technological Forecasting and Social Change, Elsevier, vol. 153(C).
    15. Peter H. Egger & Maximilian von Ehrlich & Douglas R. Nelson, 2012. "Migration and Trade," The World Economy, Wiley Blackwell, vol. 35(2), pages 216-241, February.
    16. Spiros Bougheas & Douglas R. Nelson, 2012. "Skilled Worker Migration and Trade: Inequality and Welfare," The World Economy, Wiley Blackwell, vol. 35(2), pages 197-215, February.
    17. Wang, Ying & Chen, Xiangyuan, 2020. "Natural resource endowment and ecological efficiency in China: Revisiting resource curse in the context of ecological efficiency," Resources Policy, Elsevier, vol. 66(C).
    18. Gao, Cuixia & Sun, Mei & Shen, Bo, 2015. "Features and evolution of international fossil energy trade relationships: A weighted multilayer network analysis," Applied Energy, Elsevier, vol. 156(C), pages 542-554.
    19. Dabo Guan & Stephan Klasen & Klaus Hubacek & Kuishuang Feng & Zhu Liu & Kebin He & Yong Geng & Qiang Zhang, 2014. "Determinants of stagnating carbon intensity in China," Nature Climate Change, Nature, vol. 4(11), pages 1017-1023, November.
    20. Gao, Cuixia & Su, Bin & Sun, Mei & Zhang, Xiaoling & Zhang, Zhonghua, 2018. "Interprovincial transfer of embodied primary energy in China: A complex network approach," Applied Energy, Elsevier, vol. 215(C), pages 792-807.
    21. Li, Jun & Zhang, Dayong & Su, Bin, 2019. "The Impact of Social Awareness and Lifestyles on Household Carbon Emissions in China," Ecological Economics, Elsevier, vol. 160(C), pages 145-155.
    22. Rodolfo Metulini & Massimo Riccaboni & Paolo Sgrignoli & Zhen Zhu, 2017. "The indirect effects of foreign direct investment on trade: A network perspective," The World Economy, Wiley Blackwell, vol. 40(10), pages 2193-2225, October.
    23. Giorgio Fagiolo & Marina Mastrorillo, 2014. "Does Human Migration Affect International Trade? A Complex-Network Perspective," PLOS ONE, Public Library of Science, vol. 9(5), pages 1-20, May.
    24. Su, Bin & Ang, B.W., 2011. "Multi-region input–output analysis of CO2 emissions embodied in trade: The feedback effects," Ecological Economics, Elsevier, vol. 71(C), pages 42-53.
    25. Rafiq, Shuddhasattwa & Nielsen, Ingrid & Smyth, Russell, 2017. "Effect of internal migration on the environment in China," Energy Economics, Elsevier, vol. 64(C), pages 31-44.
    26. Jing-Li Fan & Hua Liao & Bao-Jun Tang & Su-Yan Pan & Hao Yu & Yi-Ming Wei, 2016. "The impacts of migrant workers consumption on energy use and CO 2 emissions in China," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 81(2), pages 725-743, March.
    27. Chang, Chun-Ping & Dong, Minyi & Sui, Bo & Chu, Yin, 2019. "Driving forces of global carbon emissions: From time- and spatial-dynamic perspectives," Economic Modelling, Elsevier, vol. 77(C), pages 70-80.
    28. Luo, Xiaohu & Caron, Justin & Karplus, Valerie J. & Zhang, Da & Zhang, Xiliang, 2016. "Interprovincial migration and the stringency of energy policy in China," Energy Economics, Elsevier, vol. 58(C), pages 164-173.
    29. Zhu, Qin & Peng, Xizhe & Wu, Kaiya, 2012. "Calculation and decomposition of indirect carbon emissions from residential consumption in China based on the input–output model," Energy Policy, Elsevier, vol. 48(C), pages 618-626.
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