IDEAS home Printed from https://ideas.repec.org/a/ebl/ecbull/eb-13-00511.html
   My bibliography  Save this article

Comparisons of Chinese and Indian Energy Consumption Forecasting Models

Author

Listed:
  • Vipin Arora

    (U.S. Energy Information Administration)

Abstract

I evaluate the out-of-sample forecasting performance of five models of Chinese and Indian energy consumption. The results are mixed, but in general the auto-regressive distributed lag and unobserved components models perform the best over multiple evaluation criteria. I then use these two models and generate long-term forecasts [2010-2040] for comparison with the International Energy Outlook of the U.S. Energy Information Administration and other similar publications. For both countries the forecasting models predict higher levels and growth rates of energy consumption than the published estimates.

Suggested Citation

  • Vipin Arora, 2013. "Comparisons of Chinese and Indian Energy Consumption Forecasting Models," Economics Bulletin, AccessEcon, vol. 33(3), pages 2110-2121.
    • Handle: RePEc:ebl:ecbull:eb-13-00511
    as

    Download full text from publisher

    File URL: http://www.accessecon.com/Pubs/EB/2013/Volume33/EB-13-V33-I3-P197.pdf
    Download Restriction: no
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. Catherine Wolfram & Orie Shelef & Paul Gertler, 2012. "How Will Energy Demand Develop in the Developing World?," Journal of Economic Perspectives, American Economic Association, vol. 26(1), pages 119-138, Winter.
    2. Kwiatkowski, Denis & Phillips, Peter C. B. & Schmidt, Peter & Shin, Yongcheol, 1992. "Testing the null hypothesis of stationarity against the alternative of a unit root : How sure are we that economic time series have a unit root?," Journal of Econometrics, Elsevier, vol. 54(1-3), pages 159-178.
    3. Harvey, Andrew, 2006. "Forecasting with Unobserved Components Time Series Models," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 1, chapter 7, pages 327-412, Elsevier.
    4. Bhattacharyya, Subhes C. & Timilsina, Govinda R., 2009. "Energy demand models for policy formulation : a comparative study of energy demand models," Policy Research Working Paper Series 4866, The World Bank.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Aviral Kumar Tiwari & Claudiu T Albulescu & Phouphet Kyophilavong, 2014. "A comparison of different forecasting models of the international trade in India," Economics Bulletin, AccessEcon, vol. 34(1), pages 420-429.
    2. G P Girish & Aviral Kumar Tiwari, 2016. "A comparison of different univariate forecasting models forSpot Electricity Price in India," Economics Bulletin, AccessEcon, vol. 36(2), pages 1039-1057.

    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. Kuchler, Magdalena & Höök, Mikael, 2020. "Fractured visions: Anticipating (un)conventional natural gas in Poland," Resources Policy, Elsevier, vol. 68(C).
    2. Harvey,Andrew C., 2013. "Dynamic Models for Volatility and Heavy Tails," Cambridge Books, Cambridge University Press, number 9781107630024, January.
    3. Steinbuks, Jevgenijs, 2019. "Assessing the accuracy of electricity production forecasts in developing countries," International Journal of Forecasting, Elsevier, vol. 35(3), pages 1175-1185.
    4. DeRossi, G. & Harvey, A., 2006. "Time-Varying Quantiles," Cambridge Working Papers in Economics 0649, Faculty of Economics, University of Cambridge.
    5. Matteo Mogliani, 2010. "Residual-based tests for cointegration and multiple deterministic structural breaks: A Monte Carlo study," Working Papers halshs-00564897, HAL.
    6. Shahbaz, Muhammad & Hoang, Thi Hong Van & Mahalik, Mantu Kumar & Roubaud, David, 2017. "Energy consumption, financial development and economic growth in India: New evidence from a nonlinear and asymmetric analysis," Energy Economics, Elsevier, vol. 63(C), pages 199-212.
    7. Antonia López Villavicencio & Josep Lluís Raymond Bara, 2006. "The short and long-run determinants of the real exchange rate in Mexico," Working Papers wpdea0606, Department of Applied Economics at Universitat Autonoma of Barcelona.
    8. Saaed, A.A.J., 2007. "Inflation and Economic Growth in Kuwait: 1985-2005. Evidence from Co-Integration and Error Correction Model," Applied Econometrics and International Development, Euro-American Association of Economic Development, vol. 7(1).
    9. Demiralay, Sercan & Ulusoy, Veysel, 2014. "Value-at-risk Predictions of Precious Metals with Long Memory Volatility Models," MPRA Paper 53229, University Library of Munich, Germany.
    10. John Barkoulas & Christopher Baum & Mustafa Caglayan, 1999. "Fractional monetary dynamics," Applied Economics, Taylor & Francis Journals, vol. 31(11), pages 1393-1400.
    11. Azevedo, I. & Leal, V., 2021. "A new model for ex-post quantification of the effects of local actions for climate change mitigation," Renewable and Sustainable Energy Reviews, Elsevier, vol. 143(C).
    12. Löschel, Andreas & Pothen, Frank & Schymura, Michael, 2015. "Peeling the onion: Analyzing aggregate, national and sectoral energy intensity in the European Union," Energy Economics, Elsevier, vol. 52(S1), pages 63-75.
    13. Jan Babecký & Fabrizio Coricelli & Roman Horváth, 2009. "Assessing Inflation Persistence: Micro Evidence on an Inflation Targeting Economy," Czech Journal of Economics and Finance (Finance a uver), Charles University Prague, Faculty of Social Sciences, vol. 59(2), pages 102-127, June.
    14. Creel, Jerome & Bihan, Herve Le, 2006. "Using structural balance data to test the fiscal theory of the price level: Some international evidence," Journal of Macroeconomics, Elsevier, vol. 28(2), pages 338-360, June.
    15. Melissa Dell & Benjamin F. Jones & Benjamin A. Olken, 2014. "What Do We Learn from the Weather? The New Climate-Economy Literature," Journal of Economic Literature, American Economic Association, vol. 52(3), pages 740-798, September.
    16. Pulapre Balakrishnan & M Parameswaran, 2019. "Modeling the Dynamics of Inflation in India," Working Papers 16, Ashoka University, Department of Economics.
    17. Baum, Christopher F & Karasulu, Meral, 1998. "Modelling Federal Reserve Discount Policy," Computational Economics, Springer;Society for Computational Economics, vol. 11(1-2), pages 53-70, April.
    18. Chen, Pei-Fen & Chien, Mei-Se & Lee, Chien-Chiang, 2011. "Dynamic modeling of regional house price diffusion in Taiwan," Journal of Housing Economics, Elsevier, vol. 20(4), pages 315-332.
    19. Isaac Abunyuwah, 2020. "Modeling Market Integration and Asymmetric Price Transmission Dynamics of Yam Markets in Ghana," Journal of Economics and Behavioral Studies, AMH International, vol. 12(3), pages 23-31.
    20. Shahzad, Syed Jawad Hussain & Raza, Naveed & Balcilar, Mehmet & Ali, Sajid & Shahbaz, Muhammad, 2017. "Can economic policy uncertainty and investors sentiment predict commodities returns and volatility?," Resources Policy, Elsevier, vol. 53(C), pages 208-218.

    More about this item

    Keywords

    energy consumption; forecast; projection; China; India;
    All these keywords.

    JEL classification:

    • Q4 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy
    • C5 - Mathematical and Quantitative Methods - - Econometric Modeling

    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:ebl:ecbull:eb-13-00511. 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: John P. Conley (email available below). General contact details of provider: .

    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.