IDEAS home Printed from https://ideas.repec.org/p/cdl/ucsdec/qt1r5251g8.html
   My bibliography  Save this paper

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

Author

Listed:
  • 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
    as

    Download full text from publisher

    File URL: https://www.escholarship.org/uc/item/1r5251g8.pdf;origin=repeccitec
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    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. William A. Pizer, 2005. "The case for intensity targets," Climate Policy, Taylor & Francis Journals, vol. 5(4), pages 455-462, July.
    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. 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.
    5. Alan S. Manne & Richard G. Richels, 1994. "The Costs of Stabilizing Global C02 Emissions: A Probabilistic Analysis Based on Expert Judgments," The Energy Journal, , vol. 15(1), pages 31-56, January.
    6. 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.
    7. Simonetta Longhi & Peter Nijkamp, 2007. "Forecasting Regional Labor Market Developments under Spatial Autocorrelation," International Regional Science Review, , vol. 30(2), pages 100-119, April.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Lehmann Robert & Wohlrabe Klaus, 2015. "Forecasting GDP at the Regional Level with Many Predictors," German Economic Review, De Gruyter, vol. 16(2), pages 226-254, May.
    2. Baltagi, Badi H. & Fingleton, Bernard & Pirotte, Alain, 2019. "A time-space dynamic panel data model with spatial moving average errors," Regional Science and Urban Economics, Elsevier, vol. 76(C), pages 13-31.
    3. Badi H. Baltagi & Bernard Fingleton & Alain Pirotte, 2014. "Estimating and Forecasting with a Dynamic Spatial Panel Data Model," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 76(1), pages 112-138, February.
    4. Lee, Lung-fei & Yu, Jihai, 2015. "Estimation of fixed effects panel regression models with separable and nonseparable space–time filters," Journal of Econometrics, Elsevier, vol. 184(1), pages 174-192.
    5. Anna Gloria Billé & Alessio Tomelleri & Francesco Ravazzolo, 2023. "Forecasting regional GDPs: a comparison with spatial dynamic panel data models," Spatial Economic Analysis, Taylor & Francis Journals, vol. 18(4), pages 530-551, October.
    6. Giuseppe Arbia, 2011. "A Lustrum of SEA: Recent Research Trends Following the Creation of the Spatial Econometrics Association (2007--2011)," Spatial Economic Analysis, Taylor & Francis Journals, vol. 6(4), pages 377-395, July.
    7. Robert Lehmann, 2016. "Economic Growth and Business Cycle Forecasting at the Regional Level," ifo Beiträge zur Wirtschaftsforschung, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, number 65, September.
    8. Baltagi, Badi H., 2013. "Panel Data Forecasting," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 2, chapter 0, pages 995-1024, Elsevier.
    9. A. M. Angulo & J. Mur & F. J. Trívez, 2018. "Measuring resilience to economic shocks: an application to Spain," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 60(2), pages 349-373, March.
    10. Lippi, Marco & Reichlin, Lucrezia & Hallin, Marc & Forni, Mario & Altissimo, Filippo & Cristadoro, Riccardo & Veronese, Giovanni & Bassanetti, Antonio, 2001. "EuroCOIN: A Real Time Coincident Indicator of the Euro Area Business Cycle," CEPR Discussion Papers 3108, C.E.P.R. Discussion Papers.
    11. repec:rri:wpaper:201303 is not listed on IDEAS
    12. Du, Yimeng & Takeuchi, Kenji, 2019. "Can climate mitigation help the poor? Measuring impacts of the CDM in rural China," Journal of Environmental Economics and Management, Elsevier, vol. 95(C), pages 178-197.
    13. repec:zbw:bofitp:2008_015 is not listed on IDEAS
    14. Ard H.J. den Reijer, 2005. "Forecasting Dutch GDP using Large Scale Factor Models," DNB Working Papers 028, Netherlands Central Bank, Research Department.
    15. Ivan Kitov & Oleg Kitov, 2013. "Does Banque de France control inflation and unemployment?," Papers 1311.1097, arXiv.org.
    16. Atems, Bebonchu, 2013. "The spatial dynamics of growth and inequality: Evidence using U.S. county-level data," Economics Letters, Elsevier, vol. 118(1), pages 19-22.
    17. Sun, Yong & Liu, Baoyin & Sun, Zhongrui & Yang, Ruijia, 2023. "Inter-regional cooperation in the transfers of energy-intensive industry: An evolutionary game approach," Energy, Elsevier, vol. 282(C).
    18. Casari, Marco & Tavoni, Alessandro, 2024. "Climate clubs in the laboratory," Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics), Elsevier, vol. 110(C).
    19. Li, Kunpeng & Lin, Wei, 2024. "Threshold spatial autoregressive model," Journal of Econometrics, Elsevier, vol. 244(1).
    20. Parent, Olivier & LeSage, James P., 2011. "A space-time filter for panel data models containing random effects," Computational Statistics & Data Analysis, Elsevier, vol. 55(1), pages 475-490, January.
    21. Brüggemann, Ralf & Lütkepohl, Helmut, 2013. "Forecasting contemporaneous aggregates with stochastic aggregation weights," International Journal of Forecasting, Elsevier, vol. 29(1), pages 60-68.
    22. repec:zbw:bofitp:2010_015 is not listed on IDEAS
    23. Michele Aquaro & Natalia Bailey & M. Hashem Pesaran, 2015. "Quasi Maximum Likelihood Estimation of Spatial Models with Heterogeneous Coefficients," CESifo Working Paper Series 5428, CESifo.

    More about this item

    Keywords

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

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:cdl:ucsdec:qt1r5251g8. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Lisa Schiff (email available below). General contact details of provider: https://edirc.repec.org/data/deucsus.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.