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Is China on Track to Comply with Its 2020 Copenhagen Carbon Intensity Commitment?

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  • Yang, Yuan
  • Zhang, Junjie
  • Wang, Can

Abstract

In the 2009 Copenhagen Accord, China agreed to slash its carbon intensity (carbon dioxide emissions/GDP) by 40% to 45% from the 2005 level by 2020. We assess whether China can achieve the target under the business-as-usual scenario by forecasting its emissions from energy consumption. Our preferred model shows that China's carbon intensity is projected to decline by only 33%. The results imply that China needs additional mitigation effort to comply with the Copenhagen commitment. In addition, China's baseline emissions are projected to increase by 56% in the next decade (2011-2020). The emission growth is more than triple the emission reductions that the European Union and the United States have committed to in the same period.

Suggested Citation

  • Yang, Yuan & Zhang, Junjie & Wang, Can, 2014. "Is China on Track to Comply with Its 2020 Copenhagen Carbon Intensity Commitment?," University of California at San Diego, Economics Working Paper Series qt1r5251g8, Department of Economics, UC San Diego.
    • Handle: RePEc:cdl:ucsdec:qt1r5251g8
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    1. Yu, Jihai & de Jong, Robert & Lee, Lung-fei, 2008. "Quasi-maximum likelihood estimators for spatial dynamic panel data with fixed effects when both n and T are large," Journal of Econometrics, Elsevier, vol. 146(1), pages 118-134, September.
    2. Zhang, Junjie & Wang, Can, 2011. "Co-benefits and additionality of the clean development mechanism: An empirical analysis," Journal of Environmental Economics and Management, Elsevier, vol. 62(2), pages 140-154, September.
    3. Marcellino, Massimiliano & Stock, James H. & Watson, Mark W., 2003. "Macroeconomic forecasting in the Euro area: Country specific versus area-wide information," European Economic Review, Elsevier, vol. 47(1), pages 1-18, February.
    4. William A. Pizer, 2005. "The case for intensity targets," Climate Policy, Taylor & Francis Journals, vol. 5(4), pages 455-462, July.
    5. Meng, Lei & Guo, Ju'e & Chai, Jian & Zhang, Zengkai, 2011. "China's regional CO2 emissions: Characteristics, inter-regional transfer and emission reduction policies," Energy Policy, Elsevier, vol. 39(10), pages 6136-6144, October.
    6. Simonetta Longhi & Peter Nijkamp, 2007. "Forecasting Regional Labor Market Developments under Spatial Autocorrelation," International Regional Science Review, , vol. 30(2), pages 100-119, April.
    7. Alan S. Manne & Richard G. Richels, 1994. "The Costs of Stabilizing Global CO2 Emissions: A Probabilistic Analysis Based on Expert Judgments," The Energy Journal, International Association for Energy Economics, vol. 0(Number 1), pages 31-56.
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    Keywords

    Social and Behavioral Sciences; climate change; carbon dioxide emissions; China; spatial econometrics.;
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