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The relationship between urbanization, income growth and carbon dioxide emissions and the policy implications for China: a cointegrated vector error correction (VEC) analysis

Author

Listed:
  • Xiangrong Ma

    (China University of Geosciences (Beijing))

  • Jianping Ge

    (China University of Geosciences (Beijing)
    Ministry of Land and Resources)

  • Wei Wang

    (China University of Geosciences (Beijing)
    Ministry of Land and Resources)

Abstract

China is in a phase of rapid urbanization and economic development; in addition, the country’s carbon dioxide (CO2) emissions are increasing. Using a multivariate vector error correction model, this paper investigates the relationship between urbanization, income growth and CO2 emissions in China. The empirical evidence shows that the three variables are cointegrated, indicating a long-term relationship among urbanization, income growth and CO2 emissions. Moreover, a Granger causality test reveals that urbanization is the reason for income growth in China. There is also evidence that both urbanization and income growth lead to CO2 emissions. Hence, authorities should pay more attention to mitigating the negative effects on the environment when developing and implementing policies that promote urbanization and income growth. However, CO2 emissions do not cause changes in income and urbanization in China. Therefore, China should enforce stricter policies for reducing CO2 emissions.

Suggested Citation

  • Xiangrong Ma & Jianping Ge & Wei Wang, 2017. "The relationship between urbanization, income growth and carbon dioxide emissions and the policy implications for China: a cointegrated vector error correction (VEC) analysis," 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. 87(2), pages 1017-1033, June.
    • Handle: RePEc:spr:nathaz:v:87:y:2017:i:2:d:10.1007_s11069-017-2807-5
    DOI: 10.1007/s11069-017-2807-5
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