IDEAS home Printed from https://ideas.repec.org/a/sae/enejou/v25y2004i1p87-101.html
   My bibliography  Save this article

A Note on the Fisher Ideal Index Decomposition for Structural Change in Energy Intensity

Author

Listed:
  • Gale A. Boyd
  • Joseph M. Roop

Abstract

Index numbers have been used to decompose aggregate trends in energy intensity, i.e., the ratio of energy use to activity. By making a direct appeal to the theory underlying price index numbers used by the energy decomposition literature, this note proposes the chain weighted Fisher Ideal Index as a formula that solves the 'residual problem.' The connection to index number theory also allows us to illustrate that the measures of activity used to define energy intensity need not be additive across the sectors that are involved in the decomposition. We give an empirical example using recent U.S. manufacturing data of the Fisher Ideal Index, compared to the Törnqvist Divisia index, a popular index in the energy literature.

Suggested Citation

  • Gale A. Boyd & Joseph M. Roop, 2004. "A Note on the Fisher Ideal Index Decomposition for Structural Change in Energy Intensity," The Energy Journal, , vol. 25(1), pages 87-101, January.
  • Handle: RePEc:sae:enejou:v:25:y:2004:i:1:p:87-101
    DOI: 10.5547/ISSN0195-6574-EJ-Vol25-No1-5
    as

    Download full text from publisher

    File URL: https://journals.sagepub.com/doi/10.5547/ISSN0195-6574-EJ-Vol25-No1-5
    Download Restriction: no

    File URL: https://libkey.io/10.5547/ISSN0195-6574-EJ-Vol25-No1-5?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. Ang, B.W. & Liu, F.L., 2001. "A new energy decomposition method: perfect in decomposition and consistent in aggregation," Energy, Elsevier, vol. 26(6), pages 537-548.
    2. 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. 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.
    2. 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.
    3. 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.
    4. 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.
    5. 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).
    6. 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.
    7. 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.
    8. 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.
    9. 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.
    10. 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.
    11. 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.
    12. 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.
    13. Inglesi-Lotz, R. & Pouris, A., 2012. "Energy efficiency in South Africa: A decomposition exercise," Energy, Elsevier, vol. 42(1), pages 113-120.
    14. Cansino, José M. & Román-Collado, Rocío & Merchán, José, 2019. "Do Spanish energy efficiency actions trigger JEVON’S paradox?," Energy, Elsevier, vol. 181(C), pages 760-770.
    15. Md. Afzal Hossain & Jean Engo & Songsheng Chen, 2021. "The main factors behind Cameroon’s CO2 emissions before, during and after the economic crisis of the 1980s," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 23(3), pages 4500-4520, March.
    16. Lin, Boqiang & Ouyang, Xiaoling, 2014. "Analysis of energy-related CO2 (carbon dioxide) emissions and reduction potential in the Chinese non-metallic mineral products industry," Energy, Elsevier, vol. 68(C), pages 688-697.
    17. Fernández González, P. & Landajo, M. & Presno, M.J., 2014. "Tracking European Union CO2 emissions through LMDI (logarithmic-mean Divisia index) decomposition. The activity revaluation approach," Energy, Elsevier, vol. 73(C), pages 741-750.
    18. Lin, Boqiang & Lei, Xiaojing, 2015. "Carbon emissions reduction in China's food industry," Energy Policy, Elsevier, vol. 86(C), pages 483-492.
    19. Jeong, Kyonghwa & Kim, Suyi, 2013. "LMDI decomposition analysis of greenhouse gas emissions in the Korean manufacturing sector," Energy Policy, Elsevier, vol. 62(C), pages 1245-1253.
    20. Wang, Wenchao & Mu, Hailin & Kang, Xudong & Song, Rongchen & Ning, Yadong, 2010. "Changes in industrial electricity consumption in china from 1998 to 2007," Energy Policy, Elsevier, vol. 38(7), pages 3684-3690, July.

    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:25:y:2004:i:1:p:87-101. 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.