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Carbon Dioxide Emissions, Economic Growth, and Selected Types of Fossil Energy Consumption in China: Empirical Evidence from 1965 to 2015

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  • Hongze Li

    (School of Economy and Management, North China Electric Power University, Beijing 102206, China)

  • Bingkang Li

    (School of Economy and Management, North China Electric Power University, Beijing 102206, China)

  • Hao Lu

    (School of Economy and Management, North China Electric Power University, Beijing 102206, China)

Abstract

This paper empirically investigates the interactions among CO 2 emissions, economic growth, and three selected types of fossil energy consumption (coal, gas, and oil) using time series data from China over the period 1965–2015. Classic econometric analysis technologies including the Johansen cointegration test, the vector error correction model (VECM), and the Granger causality test based on VECM are employed to meet our objectives, and the presence of breaks in the data is also considered. Cointegration test result supports the existence of a long-run equilibrium relationship among the five variables, and the error correction mechanisms of the system involving the five variables are proven to be effective by VECM. Additionally, the Granger causality test based on VECM reveals that the bidirectional causalities between GDP and coal consumption, between GDP and gas consumption, and between coal consumption and CO 2 emissions and unidirectional causalities running from GDP and oil consumption to CO 2 emissions, from GDP to oil consumption, and from coal consumption to oil and gas consumption are found. Furthermore, several policy implications are proposed in the final section of this paper based on the empirical results.

Suggested Citation

  • Hongze Li & Bingkang Li & Hao Lu, 2017. "Carbon Dioxide Emissions, Economic Growth, and Selected Types of Fossil Energy Consumption in China: Empirical Evidence from 1965 to 2015," Sustainability, MDPI, vol. 9(5), pages 1-14, April.
  • Handle: RePEc:gam:jsusta:v:9:y:2017:i:5:p:697-:d:97051
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