IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v13y2021i8p4588-d539840.html
   My bibliography  Save this article

Dynamic Electricity Intensity Trends in 91 Countries

Author

Listed:
  • Hann-Earl Kim

    (Department of Global Business, Gachon University, 1342 Seongnam-daero, Sujung-gu, Gyeonggi-do 13120, Korea)

  • Yu-Sang Chang

    (Gachon Center for Convergence Research, Gachon University, 1342 Seongnam-daero, Sujung-gu, Gyeonggi-do 13120, Korea)

  • Hee-Jin Kim

    (Department of Global Business, Gachon University, 1342 Seongnam-daero, Sujung-gu, Gyeonggi-do 13120, Korea)

Abstract

Despite numerous studies on energy productivity and efficiency, only a few focus on the electricity intensity (EI) of economic output. As these studies largely examine the declining trend in EI, the increasing and/or fluctuating trends in EI have not been studied. We analyze EI trends by estimating the progress ratios from experience curves of 91 countries from 1991 to 2011. The results reveal wide variation in progress ratios, ranging from 53% to 135%, with an average of 101.5%. Furthermore, more than half of the 91 countries displayed a kinked slope, indicating the fluctuating rate of change in EI. The rate of population growth seems to be related to the increasing EI trends. A clear understanding of the relative performance of each country in terms of the progress ratio and the pattern of EI trends would be useful for the country’s policymakers to develop strategic options for the future.

Suggested Citation

  • Hann-Earl Kim & Yu-Sang Chang & Hee-Jin Kim, 2021. "Dynamic Electricity Intensity Trends in 91 Countries," Sustainability, MDPI, vol. 13(8), pages 1-26, April.
  • Handle: RePEc:gam:jsusta:v:13:y:2021:i:8:p:4588-:d:539840
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/13/8/4588/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2071-1050/13/8/4588/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Ang, James B., 2007. "CO2 emissions, energy consumption, and output in France," Energy Policy, Elsevier, vol. 35(10), pages 4772-4778, October.
    2. Kim, Dong Wook & Chang, Hyun Joon, 2012. "Experience curve analysis on South Korean nuclear technology and comparative analysis with South Korean renewable technologies," Energy Policy, Elsevier, vol. 40(C), pages 361-373.
    3. Lafond, François & Bailey, Aimee Gotway & Bakker, Jan David & Rebois, Dylan & Zadourian, Rubina & McSharry, Patrick & Farmer, J. Doyne, 2018. "How well do experience curves predict technological progress? A method for making distributional forecasts," Technological Forecasting and Social Change, Elsevier, vol. 128(C), pages 104-117.
    4. Witajewski-Baltvilks, Jan & Verdolini, Elena & Tavoni, Massimo, 2015. "Bending the learning curve," Energy Economics, Elsevier, vol. 52(S1), pages 86-99.
    5. Lean, Hooi Hooi & Smyth, Russell, 2010. "CO2 emissions, electricity consumption and output in ASEAN," Applied Energy, Elsevier, vol. 87(6), pages 1858-1864, June.
    6. Farmer, J. Doyne & Lafond, François, 2016. "How predictable is technological progress?," Research Policy, Elsevier, vol. 45(3), pages 647-665.
    7. Apergis, Nicholas & Payne, James E., 2009. "CO2 emissions, energy usage, and output in Central America," Energy Policy, Elsevier, vol. 37(8), pages 3282-3286, August.
    8. Stern, David I., 2004. "The Rise and Fall of the Environmental Kuznets Curve," World Development, Elsevier, vol. 32(8), pages 1419-1439, August.
    9. Grubler, Arnulf, 2010. "The costs of the French nuclear scale-up: A case of negative learning by doing," Energy Policy, Elsevier, vol. 38(9), pages 5174-5188, September.
    10. Kim, Young Se, 2015. "Electricity consumption and economic development: Are countries converging to a common trend?," Energy Economics, Elsevier, vol. 49(C), pages 192-202.
    11. Béla Nagy & J Doyne Farmer & Quan M Bui & Jessika E Trancik, 2013. "Statistical Basis for Predicting Technological Progress," PLOS ONE, Public Library of Science, vol. 8(2), pages 1-7, February.
    12. Sagar, Ambuj D. & van der Zwaan, Bob, 2006. "Technological innovation in the energy sector: R&D, deployment, and learning-by-doing," Energy Policy, Elsevier, vol. 34(17), pages 2601-2608, November.
    13. Vaona, Andrea, 2013. "The sclerosis of regional electricity intensities in Italy: An aggregate and sectoral analysis," Applied Energy, Elsevier, vol. 104(C), pages 880-889.
    14. Liddle, Brantley, 2009. "Electricity intensity convergence in IEA/OECD countries: Aggregate and sectoral analysis," Energy Policy, Elsevier, vol. 37(4), pages 1470-1478, April.
    15. Inglesi-Lotz, R. & Blignaut, J.N., 2012. "Electricity intensities of the OECD and South Africa: A comparison," Renewable and Sustainable Energy Reviews, Elsevier, vol. 16(7), pages 4491-4499.
    16. McDonald, Alan & Schrattenholzer, Leo, 2001. "Learning rates for energy technologies," Energy Policy, Elsevier, vol. 29(4), pages 255-261, March.
    17. Trappey, Amy J.C. & Trappey, Charles V. & Liu, Penny H.Y. & Lin, Lee-Cheng & Ou, Jerry J.R., 2013. "A hierarchical cost learning model for developing wind energy infrastructures," International Journal of Production Economics, Elsevier, vol. 146(2), pages 386-391.
    18. Neij, Lena, 2008. "Cost development of future technologies for power generation--A study based on experience curves and complementary bottom-up assessments," Energy Policy, Elsevier, vol. 36(6), pages 2200-2211, June.
    19. Lars Wenzel & Andr Wolf, 2014. "Changing Patterns of Electricity Usage in European Manufacturing: A Decomposition Analysis," International Journal of Energy Economics and Policy, Econjournals, vol. 4(4), pages 516-530.
    20. Rout, Ullash K. & Blesl, Markus & Fahl, Ulrich & Remme, Uwe & Voß, Alfred, 2009. "Uncertainty in the learning rates of energy technologies: An experiment in a global multi-regional energy system model," Energy Policy, Elsevier, vol. 37(11), pages 4927-4942, November.
    21. Wei, Max & Smith, Sarah Josephine & Sohn, Michael D., 2017. "Non-constant learning rates in retrospective experience curve analyses and their correlation to deployment programs," Energy Policy, Elsevier, vol. 107(C), pages 356-369.
    22. Apergis, Nicholas & Payne, James E., 2010. "The emissions, energy consumption, and growth nexus: Evidence from the commonwealth of independent states," Energy Policy, Elsevier, vol. 38(1), pages 650-655, January.
    23. Verbruggen, Aviel, 2006. "Electricity intensity backstop level to meet sustainable backstop supply technologies," Energy Policy, Elsevier, vol. 34(11), pages 1310-1317, July.
    24. Nikolaos Kouvaritakis & Antonio Soria & Stephane Isoard, 2000. "Modelling energy technology dynamics: methodology for adaptive expectations models with learning by doing and learning by searching," International Journal of Global Energy Issues, Inderscience Enterprises Ltd, vol. 14(1/2/3/4), pages 104-115.
    25. Kwon, Sanguk & Cho, Seong-Hoon & Roberts, Roland K. & Kim, Hyun Jae & Park, KiHyun & Edward Yu, Tun-Hsiang, 2016. "Short-run and the long-run effects of electricity price on electricity intensity across regions," Applied Energy, Elsevier, vol. 172(C), pages 372-382.
    26. Chang, Yusang & Lee, Jinsoo & Yoon, Hyerim, 2012. "Alternative projection of the world energy consumption-in comparison with the 2010 international energy outlook," Energy Policy, Elsevier, vol. 50(C), pages 154-160.
    27. Dinda, Soumyananda, 2004. "Environmental Kuznets Curve Hypothesis: A Survey," Ecological Economics, Elsevier, vol. 49(4), pages 431-455, August.
    28. Herrerias, M.J., 2013. "Seasonal anomalies in electricity intensity across Chinese regions," Applied Energy, Elsevier, vol. 112(C), pages 1548-1557.
    29. Wei, Max & Smith, Sarah J. & Sohn, Michael D., 2017. "Experience curve development and cost reduction disaggregation for fuel cell markets in Japan and the US," Applied Energy, Elsevier, vol. 191(C), pages 346-357.
    30. Yu Sang Chang & Byong-Jin You & Hann Earl Kim, 2020. "Dynamic Trends of Fine Particulate Matter Exposure across 190 Countries: Analysis and Key Insights," Sustainability, MDPI, vol. 12(7), pages 1-34, April.
    31. Hien, P.D., 2019. "Excessive electricity intensity of Vietnam: Evidence from a comparative study of Asia-Pacific countries," Energy Policy, Elsevier, vol. 130(C), pages 409-417.
    32. Herrerias, M.J. & Liu, G., 2013. "Electricity intensity across Chinese provinces: New evidence on convergence and threshold effects," Energy Economics, Elsevier, vol. 36(C), pages 268-276.
    33. Marvin J. Horowitz, 2004. "Electricity Intensity in the Commercial Sector: Market and Public Program Effects," The Energy Journal, International Association for Energy Economics, vol. 0(Number 2), pages 115-138.
    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. Yu Sang Chang & Dosoung Choi & Hann Earl Kim, 2017. "Dynamic Trends of Carbon Intensities among 127 Countries," Sustainability, MDPI, vol. 9(12), pages 1-21, December.
    2. Gutiérrez-Pedrero, María Jesús & Tarancón, Miguel Ángel & del Río, Pablo & Alcántara, Vicent, 2018. "Analysing the drivers of the intensity of electricity consumption of non-residential sectors in Europe," Applied Energy, Elsevier, vol. 211(C), pages 743-754.
    3. Yu Sang Chang & Byong-Jin You & Hann Earl Kim, 2020. "Dynamic Trends of Fine Particulate Matter Exposure across 190 Countries: Analysis and Key Insights," Sustainability, MDPI, vol. 12(7), pages 1-34, April.
    4. Bella, Giovanni & Massidda, Carla & Mattana, Paolo, 2014. "The relationship among CO2 emissions, electricity power consumption and GDP in OECD countries," Journal of Policy Modeling, Elsevier, vol. 36(6), pages 970-985.
    5. Muhammad Shahbaz & Avik Sinha, 2019. "Environmental Kuznets curve for CO2emissions: a literature survey," Journal of Economic Studies, Emerald Group Publishing Limited, vol. 46(1), pages 106-168, January.
    6. Kais, Saidi & Sami, Hammami, 2016. "An econometric study of the impact of economic growth and energy use on carbon emissions: Panel data evidence from fifty eight countries," Renewable and Sustainable Energy Reviews, Elsevier, vol. 59(C), pages 1101-1110.
    7. Thomassen, Gwenny & Van Passel, Steven & Dewulf, Jo, 2020. "A review on learning effects in prospective technology assessment," Renewable and Sustainable Energy Reviews, Elsevier, vol. 130(C).
    8. Saboori, Behnaz & Sulaiman, Jamalludin, 2013. "CO2 emissions, energy consumption and economic growth in Association of Southeast Asian Nations (ASEAN) countries: A cointegration approach," Energy, Elsevier, vol. 55(C), pages 813-822.
    9. Ozcan, Burcu, 2013. "The nexus between carbon emissions, energy consumption and economic growth in Middle East countries: A panel data analysis," Energy Policy, Elsevier, vol. 62(C), pages 1138-1147.
    10. Elia, A. & Kamidelivand, M. & Rogan, F. & Ó Gallachóir, B., 2021. "Impacts of innovation on renewable energy technology cost reductions," Renewable and Sustainable Energy Reviews, Elsevier, vol. 138(C).
    11. Shahbaz, Muhammad & Sinha, Avik, 2019. "Environmental Kuznets Curve for CO2 emission: A survey of empirical literature," MPRA Paper 100257, University Library of Munich, Germany, revised 2019.
    12. Hamit-Haggar, Mahamat, 2012. "Greenhouse gas emissions, energy consumption and economic growth: A panel cointegration analysis from Canadian industrial sector perspective," Energy Economics, Elsevier, vol. 34(1), pages 358-364.
    13. Samadi, Sascha, 2018. "The experience curve theory and its application in the field of electricity generation technologies – A literature review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 82(P3), pages 2346-2364.
    14. Mansor H. Ibrahim & Siong Hook Law, 2016. "Institutional Quality and CO 2 Emission–Trade Relations: Evidence from Sub-Saharan Africa," South African Journal of Economics, Economic Society of South Africa, vol. 84(2), pages 323-340, June.
    15. Balsalobre-Lorente, Daniel & Shahbaz, Muhammad & Roubaud, David & Farhani, Sahbi, 2018. "How economic growth, renewable electricity and natural resources contribute to CO2 emissions?," Energy Policy, Elsevier, vol. 113(C), pages 356-367.
    16. Muhammad, Shahbaz & Lean, Hooi Hooi & Muhammad, Shahbaz Shabbir, 2011. "Environmental Kuznets Curve and the role of energy consumption in Pakistan," MPRA Paper 34929, University Library of Munich, Germany, revised 22 Nov 2011.
    17. Ibrahim, Mansor H. & Law, Siong Hook, 2014. "Social capital and CO2 emission—output relations: A panel analysis," Renewable and Sustainable Energy Reviews, Elsevier, vol. 29(C), pages 528-534.
    18. Mansoor Ahmed KOONDHAR & Lingling QIU & Houjian LI & Weiwei LIU & Ge HE, 2018. "A nexus between air pollution, energy consumption and growth of economy: A comparative study between the USA and China-based on the ARDL bound testing approach," Agricultural Economics, Czech Academy of Agricultural Sciences, vol. 64(6), pages 265-276.
    19. Bölük, Gülden & Mert, Mehmet, 2014. "Fossil & renewable energy consumption, GHGs (greenhouse gases) and economic growth: Evidence from a panel of EU (European Union) countries," Energy, Elsevier, vol. 74(C), pages 439-446.
    20. Nicholas M Odhiambo, 2017. "CO2 emissions and economic growth in sub-Saharan African countries: A panel data analysis," International Area Studies Review, Center for International Area Studies, Hankuk University of Foreign Studies, vol. 20(3), pages 264-272, September.

    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:gam:jsusta:v:13:y:2021:i:8:p:4588-:d:539840. 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: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    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.