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Evaluation of long-term steel demand in developing countries- Case study: Iran

Author

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  • Kolagar, Mina
  • Saboohi, Yadollah
  • Fathi, Amirhossein

Abstract

The present study evaluates the application of top-down steel demand estimation in developing countries. The anticipated steel demand for the case of Iran is calculated by three methods, including the growth model (GM), the intensity of use hypothesis (IUH), and the fixed stock paradigm (FCP). GM shows a broad range of apparent steel demand based on the assumed growth factor. When the gross domestic product (GDP) per capita reaches 13,000 dollars per person (constant 2010 US$), the IUH method estimates the consumption peak consumption at around 500 kg steel per capita per year, which is being expected between 2040 and 2060 depending on the economic growth assumptions. Since fluctuations in the developing countries minimally affect the FCP, the steel demand based on this model is used to study the potential to satisfying the demand for steel in transportation sector from the scrap generated in the same sector. Iran faces a deficit of almost 8 million tons of steel scrap per year by 2025. Thus, the current examines the potentiality of supplying the required steel demand from the transport sector in two economic scenarios, including “regional rivalry” with restricted economic development and “fossil-fueled development’’ which focuses on the highest economic development using the temporal distribution matrix (TDM) method. Both scenarios demonstrate that the steel consumption peak appears from 2030 to 2040. The maximum steel demand in the transportation sector is 25% lower in the regional rivalry scenario than the fossil-fueled development. Moreover, while this scenario provides a steady trend in steel production and consumption by 2050, the scrap of the transport sector may fulfill the demand for steel in this sector; comparatively, this trend happens with 20 years delay in the fossil-fueled development scenario.

Suggested Citation

  • Kolagar, Mina & Saboohi, Yadollah & Fathi, Amirhossein, 2022. "Evaluation of long-term steel demand in developing countries- Case study: Iran," Resources Policy, Elsevier, vol. 77(C).
    • Handle: RePEc:eee:jrpoli:v:77:y:2022:i:c:s0301420722001234
    DOI: 10.1016/j.resourpol.2022.102675
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    References listed on IDEAS

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    1. Crompton, Paul, 2000. "Future trends in Japanese steel consumption," Resources Policy, Elsevier, vol. 26(2), pages 103-114, June.
    2. 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.
    3. Tilton, John E. & Lagos, Gustavo, 2007. "Assessing the long-run availability of copper," Resources Policy, Elsevier, vol. 32(1-2), pages 19-23.
    4. Cristina Besio & Andrea Pronzini, 2014. "Morality, Ethics, and Values Outside and Inside Organizations: An Example of the Discourse on Climate Change," Journal of Business Ethics, Springer, vol. 119(3), pages 287-300, February.
    5. Wang, Keying & Wu, Meng & Sun, Yongping & Shi, Xunpeng & Sun, Ao & Zhang, Ping, 2019. "Resource abundance, industrial structure, and regional carbon emissions efficiency in China," Resources Policy, Elsevier, vol. 60(C), pages 203-214.
    6. Johnson, Jeremiah & Reck, B.K. & Wang, T. & Graedel, T.E., 2008. "The energy benefit of stainless steel recycling," Energy Policy, Elsevier, vol. 36(1), pages 181-192, January.
    7. Gordon, R.B. & Bertram, M. & Graedel, T.E., 2007. "On the sustainability of metal supplies: A response to Tilton and Lagos," Resources Policy, Elsevier, vol. 32(1-2), pages 24-28.
    8. Cole, M.A. & Rayner, A.J. & Bates, J.M., 1997. "The environmental Kuznets curve: an empirical analysis," Environment and Development Economics, Cambridge University Press, vol. 2(4), pages 401-416, November.
    9. Crompton, Paul, 2015. "Explaining variation in steel consumption in the OECD," Resources Policy, Elsevier, vol. 45(C), pages 239-246.
    10. Goudarzi, Hossein, 2007. "Predicting Iran’s Raw Steel Demand in 2021 (in Persian)," The Journal of Planning and Budgeting (٠صلنامه برنامه ریزی Ùˆ بودجه), Institute for Management and Planning studies, vol. 12(4), pages 209-232, July.
    11. Ansari, Nastaran & Seifi, Abbas, 2012. "A system dynamics analysis of energy consumption and corrective policies in Iranian iron and steel industry," Energy, Elsevier, vol. 43(1), pages 334-343.
    12. J. R. Moroney & John M. Trapani, 1981. "Factor Demand and Substitution in Mineral-Intensive Industries," Bell Journal of Economics, The RAND Corporation, vol. 12(1), pages 272-284, Spring.
    Full references (including those not matched with items on IDEAS)

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    More about this item

    Keywords

    End-of-life recycling; Long term; Steel demand; Steel scrap; Top-down model;
    All these keywords.

    JEL classification:

    • J16 - Labor and Demographic Economics - - Demographic Economics - - - Economics of Gender; Non-labor Discrimination
    • B54 - Schools of Economic Thought and Methodology - - Current Heterodox Approaches - - - Feminist Economics
    • A14 - General Economics and Teaching - - General Economics - - - Sociology of Economics

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