IDEAS home Printed from https://ideas.repec.org/a/eee/energy/v151y2018icp455-466.html
   My bibliography  Save this article

Long-term modelling and assessment of the energy-economy decoupling in Spain

Author

Listed:
  • García-Gusano, Diego
  • Suárez-Botero, Jasson
  • Dufour, Javier

Abstract

Over the past few years, a decoupling effect between economic growth and energy consumption has been detected in many countries. Albeit this fact may be understood as positive, it supposes a concern for energy systems modellers since assumption-making process, especially concerning the linkage of the socio-economic drivers with energy demand, cannot be founded on simplistic relationships any longer. Accordingly, this article develops a double assessment to solve that problem. It proposes the use of econometric models as suitable tools to project the electricity demand in Spain, and besides, it introduces those refined energy demand projections as input for the Spanish energy system model, created using the LEAP framework. The results show substantial deviations (up to 18% by 2050) in the electricity production required and, to some extent, such divergences involve changes in the electricity production technology mix. Besides, from the electricity demand side, the use of refined demand projections has a significant effect on the sectoral behaviour, proving that –with respect to a simplistic set of projections– industry demand is overestimated, whereas residential demand is undervalued. In summary, due to the existence of a decoupling effect, energy systems modellers should avoid making simplistic assumptions when taking exogenous demand projections.

Suggested Citation

  • García-Gusano, Diego & Suárez-Botero, Jasson & Dufour, Javier, 2018. "Long-term modelling and assessment of the energy-economy decoupling in Spain," Energy, Elsevier, vol. 151(C), pages 455-466.
    • Handle: RePEc:eee:energy:v:151:y:2018:i:c:p:455-466
    DOI: 10.1016/j.energy.2018.03.102
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0360544218305115
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.energy.2018.03.102?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
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Valentina Bosetti & Carlo Carraro & Marzio Galeotti & Emanuele Massetti & Massimo Tavoni, 2006. "WITCH. A World Induced Technical Change Hybrid Model," Working Papers 2006_46, Department of Economics, University of Venice "Ca' Foscari".
    2. Wang, Wenwen & Li, Man & Zhang, Ming, 2017. "Study on the changes of the decoupling indicator between energy-related CO2 emission and GDP in China," Energy, Elsevier, vol. 128(C), pages 11-18.
    3. Pérez-García, Julián & Moral-Carcedo, Julián, 2016. "Analysis and long term forecasting of electricity demand trough a decomposition model: A case study for Spain," Energy, Elsevier, vol. 97(C), pages 127-143.
    4. Raquel Carrasco & José M. Labeaga & J. David López-Salido, 2005. "Consumption and Habits: Evidence from Panel Data," Economic Journal, Royal Economic Society, vol. 115(500), pages 144-165, January.
    5. Lim, Kyoung-Min & Lim, Seul-Ye & Yoo, Seung-Hoon, 2014. "Short- and long-run elasticities of electricity demand in the Korean service sector," Energy Policy, Elsevier, vol. 67(C), pages 517-521.
    6. Wadud, Zia & Dey, Himadri S. & Kabir, Md. Ashfanoor & Khan, Shahidul I., 2011. "Modeling and forecasting natural gas demand in Bangladesh," Energy Policy, Elsevier, vol. 39(11), pages 7372-7380.
    7. He, Yongxiu & Jiao, Jie & Chen, Qian & Ge, Sifan & Chang, Yan & Xu, Yang, 2017. "Urban long term electricity demand forecast method based on system dynamics of the new economic normal: The case of Tianjin," Energy, Elsevier, vol. 133(C), pages 9-22.
    8. Burke, Paul J. & Csereklyei, Zsuzsanna, 2016. "Understanding the energy-GDP elasticity: A sectoral approach," Energy Economics, Elsevier, vol. 58(C), pages 199-210.
    9. Benjamin Sexauer, 1977. "The Role of Habits and Stocks in Consumer Expenditure," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 91(1), pages 127-142.
    10. Suganthi, L. & Samuel, Anand A., 2012. "Energy models for demand forecasting—A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 16(2), pages 1223-1240.
    11. Ekonomou, L., 2010. "Greek long-term energy consumption prediction using artificial neural networks," Energy, Elsevier, vol. 35(2), pages 512-517.
    12. Bithas, K. & Kalimeris, P., 2013. "Re-estimating the decoupling effect: Is there an actual transition towards a less energy-intensive economy?," Energy, Elsevier, vol. 51(C), pages 78-84.
    13. Nakajima, Tadahiro & Hamori, Shigeyuki, 2010. "Change in consumer sensitivity to electricity prices in response to retail deregulation: A panel empirical analysis of the residential demand for electricity in the United States," Energy Policy, Elsevier, vol. 38(5), pages 2470-2476, May.
    14. Howells, Mark & Rogner, Holger & Strachan, Neil & Heaps, Charles & Huntington, Hillard & Kypreos, Socrates & Hughes, Alison & Silveira, Semida & DeCarolis, Joe & Bazillian, Morgan & Roehrl, Alexander, 2011. "OSeMOSYS: The Open Source Energy Modeling System: An introduction to its ethos, structure and development," Energy Policy, Elsevier, vol. 39(10), pages 5850-5870, October.
    15. Valentina Bosetti, Carlo Carraro, Marzio Galeotti, Emanuele Massetti, Massimo Tavoni, 2006. "A World induced Technical Change Hybrid Model," The Energy Journal, International Association for Energy Economics, vol. 0(Special I), pages 13-38.
    16. Hajko, Vladimír, 2017. "The failure of Energy-Economy Nexus: A meta-analysis of 104 studies," Energy, Elsevier, vol. 125(C), pages 771-787.
    17. Blázquez, Leticia & Boogen, Nina & Filippini, Massimo, 2013. "Residential electricity demand in Spain: New empirical evidence using aggregate data," Energy Economics, Elsevier, vol. 36(C), pages 648-657.
    18. George P. Papaioannou & Christos Dikaiakos & Anargyros Dramountanis & Panagiotis G. Papaioannou, 2016. "Analysis and Modeling for Short- to Medium-Term Load Forecasting Using a Hybrid Manifold Learning Principal Component Model and Comparison with Classical Statistical Models (SARIMAX, Exponential Smoot," Energies, MDPI, vol. 9(8), pages 1-40, August.
    19. Hamid R. Khosravani & María Del Mar Castilla & Manuel Berenguel & Antonio E. Ruano & Pedro M. Ferreira, 2016. "A Comparison of Energy Consumption Prediction Models Based on Neural Networks of a Bioclimatic Building," Energies, MDPI, vol. 9(1), pages 1-24, January.
    20. Bullard, Clark W. & Foster, Craig Z., 1976. "On decoupling energy and GNP growth," Energy, Elsevier, vol. 1(3), pages 291-300.
    21. Kesicki, Fabian & Anandarajah, Gabrial, 2011. "The role of energy-service demand reduction in global climate change mitigation: Combining energy modelling and decomposition analysis," Energy Policy, Elsevier, vol. 39(11), pages 7224-7233.
    22. Csereklyei, Zsuzsanna & Stern, David I., 2015. "Global energy use: Decoupling or convergence?," Energy Economics, Elsevier, vol. 51(C), pages 633-641.
    23. Adom, Philip Kofi, 2017. "The long-run price sensitivity dynamics of industrial and residential electricity demand: The impact of deregulating electricity prices," Energy Economics, Elsevier, vol. 62(C), pages 43-60.
    24. Parikh, Jyoti & Purohit, Pallav & Maitra, Pallavi, 2007. "Demand projections of petroleum products and natural gas in India," Energy, Elsevier, vol. 32(10), pages 1825-1837.
    25. Dahl, Carol & Sterner, Thomas, 1991. "Analysing gasoline demand elasticities: a survey," Energy Economics, Elsevier, vol. 13(3), pages 203-210, July.
    26. Gambhir, Ajay & Napp, Tamaryn A. & Emmott, Christopher J.M. & Anandarajah, Gabrial, 2014. "India's CO2 emissions pathways to 2050: Energy system, economic and fossil fuel impacts with and without carbon permit trading," Energy, Elsevier, vol. 77(C), pages 791-801.
    27. Brown, Alan & Deaton, Angus S, 1972. "Surveys in Applied Economics: Models of Consumer Behaviour," Economic Journal, Royal Economic Society, vol. 82(328), pages 1145-1236, December.
    28. P. Capros & Denise Van Regemorter & Leonidas Paroussos & P. Karkatsoulis & C. Fragkiadakis & S. Tsani & I. Charalampidis & Tamas Revesz, 2013. "GEM-E3 Model Documentation," JRC Research Reports JRC83177, Joint Research Centre.
    29. Chen, B. & Yang, Q. & Li, J.S. & Chen, G.Q., 2017. "Decoupling analysis on energy consumption, embodied GHG emissions and economic growth — The case study of Macao," Renewable and Sustainable Energy Reviews, Elsevier, vol. 67(C), pages 662-672.
    30. Alessandro Danesin & Pedro Linares, 2015. "An Estimation of Fuel Demand Elasticities for Spain An Aggregated Panel Approach Accounting for Diesel Share," Journal of Transport Economics and Policy, University of Bath, vol. 49(1), pages 1-16, January.
    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. Chang, Miguel & Lund, Henrik & Thellufsen, Jakob Zinck & Østergaard, Poul Alberg, 2023. "Perspectives on purpose-driven coupling of energy system models," Energy, Elsevier, vol. 265(C).
    2. Hussain, Arif & Perwez, Usama & Ullah, Kafait & Kim, Chul-Hwan & Asghar, Nosheen, 2021. "Long-term scenario pathways to assess the potential of best available technologies and cost reduction of avoided carbon emissions in an existing 100% renewable regional power system: A case study of G," Energy, Elsevier, vol. 221(C).
    3. Rafael Sánchez-Durán & Joaquín Luque & Julio Barbancho, 2019. "Long-Term Demand Forecasting in a Scenario of Energy Transition," Energies, MDPI, vol. 12(16), pages 1-23, August.
    4. Parrado-Hernando, Gonzalo & Pfeifer, Antun & Frechoso, Fernando & Miguel González, Luis Javier & Duić, Neven, 2022. "A novel approach to represent the energy system in integrated assessment models," Energy, Elsevier, vol. 258(C).
    5. Torres-Brito, David Israel & Cruz-Aké, Salvador & Venegas-Martínez, Francisco, 2023. "Impacto de los contaminantes por gases de efecto invernadero en el crecimiento económico en 86 países (1990-2019): Sobre la curva inversa de Kuznets [Impact of the Effect of Greenhouse Gas Pollutan," MPRA Paper 119031, University Library of Munich, Germany.
    6. Alfredo Cabezas-Ares & María Jesús Delgado-Rodríguez & Sonia de Lucas-Santos, 2020. "The Dynamics of Cyclical Convergence and Decoupling in the Environmental Performance of Spanish Regions," Sustainability, MDPI, vol. 12(20), pages 1-14, October.
    7. Liu, Tie-Ying & Lee, Chien-Chiang, 2020. "Convergence of the world’s energy use," Resource and Energy Economics, Elsevier, vol. 62(C).
    8. Martín-Gamboa, Mario & Iribarren, Diego & García-Gusano, Diego & Dufour, Javier, 2019. "Enhanced prioritisation of prospective scenarios for power generation in Spain: How and which one?," Energy, Elsevier, vol. 169(C), pages 369-379.

    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. Debnath, Kumar Biswajit & Mourshed, Monjur, 2018. "Forecasting methods in energy planning models," Renewable and Sustainable Energy Reviews, Elsevier, vol. 88(C), pages 297-325.
    2. Atul Anand & L Suganthi, 2018. "Hybrid GA-PSO Optimization of Artificial Neural Network for Forecasting Electricity Demand," Energies, MDPI, vol. 11(4), pages 1-15, March.
    3. Ciola, Emanuele & Turco, Enrico & Gurgone, Andrea & Bazzana, Davide & Vergalli, Sergio & Menoncin, Francesco, 2023. "Enter the MATRIX model:a Multi-Agent model for Transition Risks with application to energy shocks," Journal of Economic Dynamics and Control, Elsevier, vol. 146(C).
    4. Kan, Siyi & Chen, Bin & Chen, Guoqian, 2019. "Worldwide energy use across global supply chains: Decoupled from economic growth?," Applied Energy, Elsevier, vol. 250(C), pages 1235-1245.
    5. Zheng, Jiali & Duan, Hongbo & Zhou, Sheng & Wang, Shouyang & Gao, Ji & Jiang, Kejun & Gao, Shuo, 2021. "Limiting global warming to below 1.5 °C from 2 °C: An energy-system-based multi-model analysis for China," Energy Economics, Elsevier, vol. 100(C).
    6. John Hassler & Per Krusell & Conny Olovsson, 2021. "Directed Technical Change as a Response to Natural Resource Scarcity," Journal of Political Economy, University of Chicago Press, vol. 129(11), pages 3039-3072.
    7. Miller, Mark & Alberini, Anna, 2016. "Sensitivity of price elasticity of demand to aggregation, unobserved heterogeneity, price trends, and price endogeneity: Evidence from U.S. Data," Energy Policy, Elsevier, vol. 97(C), pages 235-249.
    8. Gjorgiev, Blazhe & Garrison, Jared B. & Han, Xuejiao & Landis, Florian & van Nieuwkoop, Renger & Raycheva, Elena & Schwarz, Marius & Yan, Xuqian & Demiray, Turhan & Hug, Gabriela & Sansavini, Giovanni, 2022. "Nexus-e: A platform of interfaced high-resolution models for energy-economic assessments of future electricity systems," Applied Energy, Elsevier, vol. 307(C).
    9. Angelopoulos, Dimitrios & Siskos, Yannis & Psarras, John, 2019. "Disaggregating time series on multiple criteria for robust forecasting: The case of long-term electricity demand in Greece," European Journal of Operational Research, Elsevier, vol. 275(1), pages 252-265.
    10. Yu, Miao & Zhao, Xintong & Gao, Yuning, 2019. "Factor decomposition of China’s industrial electricity consumption using structural decomposition analysis," Structural Change and Economic Dynamics, Elsevier, vol. 51(C), pages 67-76.
    11. Shao, Zhen & Chao, Fu & Yang, Shan-Lin & Zhou, Kai-Le, 2017. "A review of the decomposition methodology for extracting and identifying the fluctuation characteristics in electricity demand forecasting," Renewable and Sustainable Energy Reviews, Elsevier, vol. 75(C), pages 123-136.
    12. Shumilov, Andrei, 2021. "Анализ Неопределенности В Интегрированных Моделях Климата И Экономики: Обзор Литературы [Uncertainty analysis in integrated assessment models of the economics of climate change: a literature survey," MPRA Paper 110171, University Library of Munich, Germany.
    13. Zhao, Xu & Dahl, Carol A. & Luo, Dongkun, 2019. "How OECD countries subsidize oil and natural gas producers and modeling the consequences: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 104(C), pages 111-126.
    14. DeCarolis, Joseph F. & Hunter, Kevin & Sreepathi, Sarat, 2012. "The case for repeatable analysis with energy economy optimization models," Energy Economics, Elsevier, vol. 34(6), pages 1845-1853.
    15. Hafezi, Reza & Akhavan, AmirNaser & Pakseresht, Saeed & A. Wood, David, 2021. "Global natural gas demand to 2025: A learning scenario development model," Energy, Elsevier, vol. 224(C).
    16. Laha, Priyanka & Chakraborty, Basab, 2017. "Energy model – A tool for preventing energy dysfunction," Renewable and Sustainable Energy Reviews, Elsevier, vol. 73(C), pages 95-114.
    17. Desiderio Romero-Jordán & Pablo del Río & Cristina Peñasco, 2014. "Household electricity demand in Spanish regions. Public policy implications," Working Papers 2014/24, Institut d'Economia de Barcelona (IEB).
    18. Martins, Luís Oscar Silva & Amorim, Inara Rosa & Mendes, Vinícius de Araújo & Silva, Marcelo Santana & Freires, Francisco Gaudêncio Mendonça & Teles, Eduardo Oliveira & Torres, Ednildo Andrade, 2021. "Price and income elasticities of residential electricity demand in Brazil and policy implications," Utilities Policy, Elsevier, vol. 71(C).
    19. Ciola, Emanuele & Turco, Enrico & Gurgone, Andrea & Bazzana, Davide & Vergalli, Sergio & Menoncin, Francesco, 2022. "Charging the macroeconomy with an energy sector: an agent-based model," FEEM Working Papers 319877, Fondazione Eni Enrico Mattei (FEEM).
    20. Thakur, Jagruti & Rauner, Sebastian & Darghouth, Naïm R. & Chakraborty, Basab, 2018. "Exploring the impact of increased solar deployment levels on residential electricity bills in India," Renewable Energy, Elsevier, vol. 120(C), pages 512-523.

    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:energy:v:151:y:2018:i:c:p:455-466. 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.journals.elsevier.com/energy .

    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.