IDEAS home Printed from https://ideas.repec.org/a/eee/eneeco/v27y2005i1p195-208.html

Energy consumption in China: past trends and future directions

Author

Listed:
  • Crompton, Paul
  • Wu, Yanrui

Abstract

In 2003 China’s energy consumption amounted to 1678 million tonnes coal equivalent (MTCE), making China the world’s second largest consumer behind only the United States. China is now also one of the largest oil importers in the world. With an economy which is expected to maintain a rate of growth of 7 to 8 per cent for decades, China’s role in the world energy market becomes increasingly influential. This makes it important to predict China’s future demand for energy. The objective of this paper is to apply the Bayesian vector autoregressive methodology to forecast China’s energy consumption and to discuss potential implications. The results of this paper suggest that total energy consumption should increase to 2173 MtCE in 2010, an annual growth rate of 3.8 per cent which is slightly slower than the average rate in the past decade. The slower growth reflects an expected slower economic growth and the decline in energy consumption due to structural changes in the Chinese economy.
(This abstract was borrowed from another version of this item.)

Suggested Citation

  • Crompton, Paul & Wu, Yanrui, 2005. "Energy consumption in China: past trends and future directions," Energy Economics, Elsevier, vol. 27(1), pages 195-208, January.
    • Handle: RePEc:eee:eneeco:v:27:y:2005:i:1:p:195-208
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0140-9883(04)00094-5
    Download Restriction: Full text for ScienceDirect subscribers only
    ---><---

    As the access to this document is restricted, you may want to look for a different version below or

    for a different version of it.

    Other versions of this item:

    References listed on IDEAS

    as
    1. repec:aen:journl:1996v17-01-a02 is not listed on IDEAS
    2. Litterman, Robert B, 1986. "Forecasting with Bayesian Vector Autoregressions-Five Years of Experience," Journal of Business & Economic Statistics, American Statistical Association, vol. 4(1), pages 25-38, January.
    3. repec:aen:journl:1999v20-03-a03 is not listed on IDEAS
    4. John C. Robertson & Ellis W. Tallman, 1999. "Vector autoregressions: forecasting and reality," Economic Review, Federal Reserve Bank of Atlanta, vol. 84(Q1), pages 4-18.
    5. Tao Zha, 1998. "A dynamic multivariate model for use in formulating policy," Economic Review, Federal Reserve Bank of Atlanta, vol. 83(Q 1), pages 16-29.
    6. Fisher-Vanden, Karen & Jefferson, Gary H. & Liu, Hongmei & Tao, Quan, 2004. "What is driving China's decline in energy intensity?," Resource and Energy Economics, Elsevier, vol. 26(1), pages 77-97, March.
    7. von Hirschhausen, Christian & Andres, Michael, 2000. "Long-term electricity demand in China -- From quantitative to qualitative growth?," Energy Policy, Elsevier, vol. 28(4), pages 231-241, April.
    8. Summers, Peter M., 2001. "Forecasting Australia's economic performance during the Asian crisis," International Journal of Forecasting, Elsevier, vol. 17(3), pages 499-515.
    9. Thomas Doan & Robert B. Litterman & Christopher A. Sims, 1983. "Forecasting and Conditional Projection Using Realistic Prior Distributions," NBER Working Papers 1202, National Bureau of Economic Research, Inc.
    10. Christopher A. Sims, 1993. "A Nine-Variable Probabilistic Macroeconomic Forecasting Model," NBER Chapters, in: Business Cycles, Indicators, and Forecasting, pages 179-212, National Bureau of Economic Research, Inc.
    11. Sinton, Jonathan E. & Fridley, David G., 2000. "What goes up: recent trends in China's energy consumption," Energy Policy, Elsevier, vol. 28(10), pages 671-687, August.
    12. Sims, Christopher A & Zha, Tao, 1998. "Bayesian Methods for Dynamic Multivariate Models," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 39(4), pages 949-968, November.
    13. repec:aen:journl:1998v19-04-a04 is not listed on IDEAS
    14. Litterman, Robert, 1986. "Forecasting with Bayesian vector autoregressions -- Five years of experience : Robert B. Litterman, Journal of Business and Economic Statistics 4 (1986) 25-38," International Journal of Forecasting, Elsevier, vol. 2(4), pages 497-498.
    15. Huang, Jin-ping, 1993. "Industry energy use and structural change : A case study of The People's Republic of China," Energy Economics, Elsevier, vol. 15(2), pages 131-136, 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. John C. Robertson & Ellis W. Tallman, 1999. "Improving forecasts of the federal funds rate in a policy model," FRB Atlanta Working Paper 99-3, Federal Reserve Bank of Atlanta.
    2. Francis, Brian M. & Moseley, Leo & Iyare, Sunday Osaretin, 2007. "Energy consumption and projected growth in selected Caribbean countries," Energy Economics, Elsevier, vol. 29(6), pages 1224-1232, November.
    3. Francis Neville & Owyang Michael T. & Sekhposyan Tatevik, 2012. "The Local Effects of Monetary Policy," The B.E. Journal of Macroeconomics, De Gruyter, vol. 12(2), pages 1-38, March.
    4. John C. Robertson & Ellis W. Tallman, 1999. "Prior parameter uncertainty: Some implications for forecasting and policy analysis with VAR models," FRB Atlanta Working Paper 99-13, Federal Reserve Bank of Atlanta.
    5. Enrique M. Quilis(1), "undated". "Modelos Bvar: Especificación, Estimación E Inferencia," Working Papers 8-02 Classification-JEL :, Instituto de Estudios Fiscales.
    6. Boris Demeshev & Oxana Malakhovskaya, 2016. "BVAR mapping," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 43, pages 118-141.
    7. Hanck, Christoph & Prüser, Jan, 2016. "House prices and interest rates: Bayesian evidence from Germany," Ruhr Economic Papers 620, RWI - Leibniz-Institut für Wirtschaftsforschung, Ruhr-University Bochum, TU Dortmund University, University of Duisburg-Essen.
    8. Lutz Kilian & Tao Zha, 2002. "Quantifying the uncertainty about the half-life of deviations from PPP," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 17(2), pages 107-125.
    9. Silvia Miranda-Agrippino & Hélène Rey, 2020. "U.S. Monetary Policy and the Global Financial Cycle," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 87(6), pages 2754-2776.
    10. Kilian, L. & Zha, T., 1999. "Quantifying the Half-Life of Deviations from PPP: The Role of Economic Priors," Working Papers 450, Research Seminar in International Economics, University of Michigan.
    11. Eric M. Leeper & Tao Zha, 2002. "Empirical Analysis of Policy Interventions," NBER Working Papers 9063, National Bureau of Economic Research, Inc.
    12. Bekiros Stelios & Paccagnini Alessia, 2015. "Estimating point and density forecasts for the US economy with a factor-augmented vector autoregressive DSGE model," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 19(2), pages 107-136, April.
    13. Andrea Carriero & Todd E. Clark & Massimiliano Marcellino, 2021. "No‐arbitrage priors, drifting volatilities, and the term structure of interest rates," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 36(5), pages 495-516, August.
    14. Marta Banbura & Domenico Giannone & Lucrezia Reichlin, 2010. "Large Bayesian vector auto regressions," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 25(1), pages 71-92.
    15. Ghent, Andra, 2006. "Comparing Models of Macroeconomic Fluctuations: How Big Are the Differences?," MPRA Paper 180, University Library of Munich, Germany.
    16. Warne, Anders & Coenen, Günter & Christoffel, Kai, 2010. "Forecasting with DSGE models," Working Paper Series 1185, European Central Bank.
    17. Koop, Gary & Korobilis, Dimitris, 2010. "Bayesian Multivariate Time Series Methods for Empirical Macroeconomics," Foundations and Trends(R) in Econometrics, now publishers, vol. 3(4), pages 267-358, July.
    18. Carolyn Njenga & Michael Sherris, 2011. "Modeling Mortality with a Bayesian Vector Autoregression," Working Papers 201105, ARC Centre of Excellence in Population Ageing Research (CEPAR), Australian School of Business, University of New South Wales.
    19. Eric M. Leeper & Tao Zha, 2002. "Empirical analysis of policy interventions," Proceedings, Federal Reserve Bank of San Francisco, issue mar.
    20. Higgins, Patrick & Zha, Tao & Zhong, Wenna, 2016. "Forecasting China's economic growth and inflation," China Economic Review, Elsevier, vol. 41(C), pages 46-61.

    More about this item

    JEL classification:

    • Q41 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Demand and Supply; Prices
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods

    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:eee:eneeco:v:27:y:2005:i:1:p:195-208. 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/eneco .

    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.