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Electricity demand in the iron ore industry: Evidence from Brazil

Author

Listed:
  • Max Resende

    (Federal University of Santa Catarina)

  • Juliano Leal

    (Institute of Technological Education)

  • João Simoni

    (Federal University of Minas Gerais)

Abstract

Electricity planning is a key strategic business in the mining industry. Thus, this paper assesses the electricity demand in the Brazilian iron ore industry with an emphasis on electricity prices and the production value chain to address the sector-specific behavioral patterns, using daily data from December 2018 to April 2020. By employing impulse response functions and variance decomposition analysis, the paper shows that electricity demand is primarily determined by internal factors of the ore production rather than exogenous variables, such as the electricity price and weather conditions. Moreover, short and long-run electricity price elasticities are computed, providing further insights into the dynamics of the sector, and indicating that price is inelastic with similar values for both time frames. This suggests from an energy policy perspective that any price movements (taxes) are bound to have a fairly limited effect as they may cause financial turmoil given the long-term characteristic of delivery contracts in the sector.

Suggested Citation

  • Max Resende & Juliano Leal & João Simoni, 2021. "Electricity demand in the iron ore industry: Evidence from Brazil," Economics Bulletin, AccessEcon, vol. 41(3), pages 929-937.
    • Handle: RePEc:ebl:ecbull:eb-20-00483
    as

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    References listed on IDEAS

    as
    1. Cialani, Catia & Mortazavi, Reza, 2018. "Household and industrial electricity demand in Europe," Energy Policy, Elsevier, vol. 122(C), pages 592-600.
    2. Bernstein, Ronald & Madlener, Reinhard, 2015. "Short- and long-run electricity demand elasticities at the subsectoral level: A cointegration analysis for German manufacturing industries," Energy Economics, Elsevier, vol. 48(C), pages 178-187.
    3. Akihiro Otsuka, 2015. "Demand for industrial and commercial electricity: evidence from Japan," Journal of Economic Structures, Springer;Pan-Pacific Association of Input-Output Studies (PAPAIOS), vol. 4(1), pages 1-11, December.
    4. Labandeira, Xavier & Labeaga, José M. & López-Otero, Xiral, 2017. "A meta-analysis on the price elasticity of energy demand," Energy Policy, Elsevier, vol. 102(C), pages 549-568.
    5. M. Hashem Pesaran & Yongcheol Shin & Richard J. Smith, 2001. "Bounds testing approaches to the analysis of level relationships," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 16(3), pages 289-326.
    6. Sebastian Kripfganz & Daniel C. Schneider, 2023. "ardl: Estimating autoregressive distributed lag and equilibrium correction models," Stata Journal, StataCorp LLC, vol. 23(4), pages 983-1019, December.
    7. Arisoy, Ibrahim & Ozturk, Ilhan, 2014. "Estimating industrial and residential electricity demand in Turkey: A time varying parameter approach," Energy, Elsevier, vol. 66(C), pages 959-964.
    8. Roula Inglesi-Lotz, James Blignaut, 2011. "Estimating the price elasticity for demand for electricity by sector in South Africa," South African Journal of Economic and Management Sciences, University of Pretoria, Faculty of Economic and Management Sciences, vol. 14(4), pages 449-465, December.
    9. Lin, Boqiang & Ouyang, Xiaoling, 2014. "Electricity demand and conservation potential in the Chinese nonmetallic mineral products industry," Energy Policy, Elsevier, vol. 68(C), pages 243-253.
    10. Sharimakin, Akinsehinwa & Glass, Anthony J. & Saal, David S. & Glass, Karligash, 2018. "Dynamic multilevel modelling of industrial energy demand in Europe," Energy Economics, Elsevier, vol. 74(C), pages 120-130.
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    Keywords

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    JEL classification:

    • L7 - Industrial Organization - - Industry Studies: Primary Products and Construction
    • Q4 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy

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