IDEAS home Printed from https://ideas.repec.org/a/sae/enejou/v19y1998i4p85-105.html
   My bibliography  Save this article

The Relationship Between Energy Intensity and Income Levels: Forecasting Long Term Energy Demand in Asian Emerging Countries

Author

Listed:
  • Rossana Galli

Abstract

This paper analyses long-term trends in energy intensity for ten Asian emerging countries to test for a non-monotonic relationship between energy intensity and income in our sample. We estimate energy demand functions during 1973 1990 using a quadratic function of log income. We find that the long-run coefficient on squared income is negative and significant, indicating a change in trend of energy intensity. We then use our estimates to evaluate a medium-term forecast of energy demand in the Asian countries, using both a log-linear and a quadratic model. We find that in medium to high income countries the quadratic model performs better than the log-linear, with an average error of 9% against 43% in 1995. For the region as a whole, the quadratic model appears more adequate with a forecast error of 16% against 28% in 1995. These results are consistent with a process of dematerialization, which occurs as a result of a reduction of resource use per unit of GDP once an economy passes some threshold level of GDP per capita.

Suggested Citation

  • Rossana Galli, 1998. "The Relationship Between Energy Intensity and Income Levels: Forecasting Long Term Energy Demand in Asian Emerging Countries," The Energy Journal, , vol. 19(4), pages 85-105, October.
    • Handle: RePEc:sae:enejou:v:19:y:1998:i:4:p:85-105
    DOI: 10.5547/ISSN0195-6574-EJ-Vol19-No4-4
    as

    Download full text from publisher

    File URL: https://journals.sagepub.com/doi/10.5547/ISSN0195-6574-EJ-Vol19-No4-4
    Download Restriction: no
    File URL: https://libkey.io/10.5547/ISSN0195-6574-EJ-Vol19-No4-4?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. B. W. Ang & Ki-Hong Choi, 1997. "Decomposition of Aggregate Energy and Gas Emission Intensities for Industry: A Refined Divisia Index Method," The Energy Journal, International Association for Energy Economics, vol. 0(Number 3), pages 59-73.
    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. Jena, Pradyot, 2009. "A study of changing patterns of energy consumption and energy efficiency in the Indian manufacturing sector," MPRA Paper 31195, University Library of Munich, Germany.
    2. 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.
    3. de Freitas, Luciano Charlita & Kaneko, Shinji, 2011. "Decomposition of CO2 emissions change from energy consumption in Brazil: Challenges and policy implications," Energy Policy, Elsevier, vol. 39(3), pages 1495-1504, March.
    4. Arik Levinson, 2017. "Energy Intensity: Prices, Policy, or Composition in US States," Working Papers gueconwpa~17-17-04, Georgetown University, Department of Economics.
    5. Wang, Miao & Feng, Chao, 2017. "Analysis of energy-related CO2 emissions in China’s mining industry: Evidence and policy implications," Resources Policy, Elsevier, vol. 53(C), pages 77-87.
    6. Román-Collado, Rocío & Colinet, María José, 2018. "Are labour productivity and residential living standards drivers of the energy consumption changes?," Energy Economics, Elsevier, vol. 74(C), pages 746-756.
    7. Daniel Croner & Ivan Frankovic, 2018. "A Structural Decomposition Analysis of Global and NationalEnergy Intensity Trends," The Energy Journal, , vol. 39(2), pages 103-122, March.
    8. Fernández-Amador, Octavio & Francois, Joseph F. & Oberdabernig, Doris A. & Tomberger, Patrick, 2023. "Energy footprints and the international trade network: A new dataset. Is the European Union doing it better?," Ecological Economics, Elsevier, vol. 204(PA).
    9. Lizhan Cao & Hui Wang, 2022. "The Slowdown in China’s Energy Consumption Growth in the “New Normal” Stage: From Both National and Regional Perspectives," Sustainability, MDPI, vol. 14(7), pages 1-21, April.
    10. Voigt, Sebastian & De Cian, Enrica & Schymura, Michael & Verdolini, Elena, 2014. "Energy intensity developments in 40 major economies: Structural change or technology improvement?," Energy Economics, Elsevier, vol. 41(C), pages 47-62.
    11. Fernández, Esteban & Fernández, Paula, 2008. "An extension to Sun's decomposition methodology: The Path Based approach," Energy Economics, Elsevier, vol. 30(3), pages 1020-1036, May.
    12. Andreoni, V. & Galmarini, S., 2012. "European CO2 emission trends: A decomposition analysis for water and aviation transport sectors," Energy, Elsevier, vol. 45(1), pages 595-602.
    13. Shrestha, Ram M. & Anandarajah, Gabrial & Liyanage, Migara H., 2009. "Factors affecting CO2 emission from the power sector of selected countries in Asia and the Pacific," Energy Policy, Elsevier, vol. 37(6), pages 2375-2384, June.
    14. van Megen, Bram & Bürer, Meinrad & Patel, Martin K., 2019. "Comparing electricity consumption trends: A multilevel index decomposition analysis of the Genevan and Swiss economy," Energy Economics, Elsevier, vol. 83(C), pages 1-25.
    15. Wang, W.W. & Zhang, M. & Zhou, M., 2011. "Using LMDI method to analyze transport sector CO2 emissions in China," Energy, Elsevier, vol. 36(10), pages 5909-5915.
    16. Chen, Jiandong & Cheng, Shulei & Song, Malin, 2018. "Changes in energy-related carbon dioxide emissions of the agricultural sector in China from 2005 to 2013," Renewable and Sustainable Energy Reviews, Elsevier, vol. 94(C), pages 748-761.
    17. P. Fernández-González & M. Landajo & M.J. Presno, 2013. "Factors Influencing Changes In Aggregate Energy Consumption. An European Cross-Country Analysis," Regional and Sectoral Economic Studies, Euro-American Association of Economic Development, vol. 13(2), pages 18-30.
    18. Jin, Taeyoung, 2022. "Impact of heat and electricity consumption on energy intensity: A panel data analysis," Energy, Elsevier, vol. 239(PA).
    19. Xiao, Hao & Sun, Ke-Juan & Bi, Hui-Min & Xue, Jin-Jun, 2019. "Changes in carbon intensity globally and in countries: Attribution and decomposition analysis," Applied Energy, Elsevier, vol. 235(C), pages 1492-1504.
    20. Lin, Boqiang & Tan, Ruipeng, 2017. "Sustainable development of China's energy intensive industries: From the aspect of carbon dioxide emissions reduction," Renewable and Sustainable Energy Reviews, Elsevier, vol. 77(C), pages 386-394.

    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:sae:enejou:v:19:y:1998:i:4:p:85-105. 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: SAGE Publications (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.