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Causality between Energy Consumption and Economic Growth in Beijing: Evidence from Cross-Industry Panel Data

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Advances in Computer Science, Environment, Ecoinformatics, and Education (CSEE 2011)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 217))

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Abstract

This paper applies the most recently developed panel unit root, heterogeneous panel cointegration and panel-based error correction models to investigate the causal relationship between energy consumption and economic growth for three industries in Beijing during the period of 1980-2008. The empirical results indicate that there is bidirectional Granger causality in the short run, but unidirectional Granger causality running from energy consumption to economic growth in the long run.

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References

  1. Wu, Q., Chen, L., Zhang, Y., et al.: Retesting the Granger Causality between Energy Consumption and GDP in China: Based on the Provincial Panel Data Analysis. The Journal of Quantitative and Technical Economics (6), 27–40 (2008)

    Google Scholar 

  2. Yuan, J., Kang, J., Zhao, C., et al.: Energy consumption and economic growth: evidence from China at both aggregated and disaggregated levels. Energy Economics (30), 3077–3094 (2008)

    Article  Google Scholar 

  3. Ma, C., Chu, H., Li, k., et al.: Co-integration Analysis and an Error Correction Model of China’s Energy Consumption and Economy Growth. Systems Engineering 22(10), 47–50 (2004)

    Google Scholar 

  4. He, Y., Li, Y., Li, D., et al.: The cointegration test between energy consumption and economic growth in Beijing. Statistics and Decision (8), 90–92 (2008)

    Google Scholar 

  5. Levine, A., Lin, C.F., Chu, C.S.: Unit root tests in panel data: asymptotic and finite-sample properties. Journal of Econometrics (108), 1–24 (2002)

    Article  MathSciNet  MATH  Google Scholar 

  6. Pedroni, P.: Panel cointegration: asymptotic and finite sample properties of pooled time series tests with an application to the PPP hypothesis. Econometric Theory 20(3), 597–625

    Google Scholar 

  7. Pedroni, P.: Critical values for cointegration tests in heterogeneous panels with multiple regressors. Oxford Bulletin of Economics and Statistics (61), 653–670 (1999)

    Article  Google Scholar 

  8. Zhang, L., Huang, Y.: Potential Analysis on Structural Energy-saving in China. Potential Analysis on Structural Energy-saving in China (05), 27–34 (2008)

    Google Scholar 

  9. Oh, W., Lee, K.: Causal relationship between energy consumption and GDP revisited: the case of Korea 1970-1999. Energy Economics (26), 5–51 (2004)

    Article  Google Scholar 

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© 2011 Springer-Verlag Berlin Heidelberg

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Zhang, X., Wang, C., Tan, Y., Zhang, F. (2011). Causality between Energy Consumption and Economic Growth in Beijing: Evidence from Cross-Industry Panel Data. In: Lin, S., Huang, X. (eds) Advances in Computer Science, Environment, Ecoinformatics, and Education. CSEE 2011. Communications in Computer and Information Science, vol 217. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-23339-5_42

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  • DOI: https://doi.org/10.1007/978-3-642-23339-5_42

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-23338-8

  • Online ISBN: 978-3-642-23339-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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