IDEAS home Printed from https://ideas.repec.org/p/mos/moswps/2024-08.html
   My bibliography  Save this paper

Artificial intelligence investments reduce risks to critical mineral supply

Author

Listed:
  • Joaquin Vespignani

    (Tasmanian School of Business and Economics, University of Tasmania, Australia)

  • Russell Smyth

    (Department of Economics, Monash University, Clayton, Australia)

Abstract

This paper employs insights from earth science on the financial risk of project developments to present an economic theory of critical minerals. Our theory posits that back-ended critical mineral projects that have unaddressed technical and nontechnical barriers, such as those involving lithium and cobalt, exhibit an additional risk for investors which we term the “back-ended risk premium”. We show that the back-ended risk premium increases the cost of capital and, therefore, has the potential to reduce investment in the sector. We posit that the back-ended risk premium may also reduce the gains in productivity expected from artificial intelligence (AI) technologies in the mining sector. Progress in AI may, however, lessen the back-ended risk premium itself through shortening the duration of mining projects and the required rate of investment through reducing the associated risk. We conclude that the best way to reduce the costs associated with energy transition is for governments to invest heavily in AI mining technologies and research.

Suggested Citation

  • Joaquin Vespignani & Russell Smyth, 2024. "Artificial intelligence investments reduce risks to critical mineral supply," Monash Economics Working Papers 2024-08, Monash University, Department of Economics.
    • Handle: RePEc:mos:moswps:2024-08
    as

    Download full text from publisher

    File URL: http://monash-econ-wps.s3-ap-southeast-2.amazonaws.com/RePEc/mos/moswps/2024-08.pdf
    Download Restriction: no
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. Speirs, Jamie & McGlade, Christophe & Slade, Raphael, 2015. "Uncertainty in the availability of natural resources: Fossil fuels, critical metals and biomass," Energy Policy, Elsevier, vol. 87(C), pages 654-664.
    2. Alan Carruth & Andy Dickerson & Andrew Henley, 2000. "What do We Know About Investment Under Uncertainty?," Journal of Economic Surveys, Wiley Blackwell, vol. 14(2), pages 119-154, April.
    3. Nwaila, Glen T. & Frimmel, Hartwig E. & Zhang, Steven E. & Bourdeau, Julie E. & Tolmay, Leon C.K. & Durrheim, Raymond J. & Ghorbani, Yousef, 2022. "The minerals industry in the era of digital transition: An energy-efficient and environmentally conscious approach," Resources Policy, Elsevier, vol. 78(C).
    4. Matthew Rosenblatt & Link Tejavibulya & Rongtao Jiang & Stephanie Noble & Dustin Scheinost, 2024. "Data leakage inflates prediction performance in connectome-based machine learning models," Nature Communications, Nature, vol. 15(1), pages 1-15, December.
    5. Vincent Moreau & Piero Carlo Dos Reis & François Vuille, 2019. "Enough Metals? Resource Constraints to Supply a Fully Renewable Energy System," Resources, MDPI, vol. 8(1), pages 1-18, January.
    6. Onifade, Moshood & Adebisi, John Adetunji & Shivute, Amtenge Penda & Genc, Bekir, 2023. "Challenges and applications of digital technology in the mineral industry," Resources Policy, Elsevier, vol. 85(PB).
    7. repec:bla:jecsur:v:14:y:2000:i:2:p:119-53 is not listed on IDEAS
    8. Noriega, Roberto & Pourrahimian, Yashar, 2022. "A systematic review of artificial intelligence and data-driven approaches in strategic open-pit mine planning," Resources Policy, Elsevier, vol. 77(C).
    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. Jamel Saadaoui & Russell Smyth & Joaquin Vespignani, 2024. "Ensuring the security of the clean energy transition: Examining the impact of geopolitical risk on the price of critical minerals," Monash Economics Working Papers 2024-19, Monash University, Department of Economics.

    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. Yi, Chongyan & Ma, Hong chao & Zhao, Kexu, 2024. "Impacts of digital economic transformation and green growth on trade flows of mineral resources," Resources Policy, Elsevier, vol. 90(C).
    2. Li, Dan, 2013. "Multilateral R&D alliances by new ventures," Journal of Business Venturing, Elsevier, vol. 28(2), pages 241-260.
    3. Ray Barrell & Sylvia Gottschalk & Dawn Holland & Ehsan Khoman & Iana Liadze & Olga Pomerantz, 2008. "The impact of EMU on growth and employment," European Economy - Economic Papers 2008 - 2015 318, Directorate General Economic and Financial Affairs (DG ECFIN), European Commission.
    4. Farida M. Issatayeva & Gulnara M. Aubakirova & Aliya D. Maussymbayeva & Lyussiya I. Togaibayeva & Valery V. Biryukov & Elena Vechkinzova, 2023. "Fuel and Energy Complex of Kazakhstan: Geological and Economic Assessment of Enterprises in the Context of Digital Transformation," Energies, MDPI, vol. 16(16), pages 1-23, August.
    5. Henley, Andrew, 2009. "Switching Costs and Occupational Transition into Self-Employment," IZA Discussion Papers 3969, Institute of Labor Economics (IZA).
    6. Klaus Mohn & Petter Osmundsen, 2011. "Asymmetry and uncertainty in capital formation: an application to oil investment," Applied Economics, Taylor & Francis Journals, vol. 43(28), pages 4387-4401.
    7. Panagiotidis, Theodore & Printzis, Panagiotis, 2020. "What is the investment loss due to uncertainty?," Global Finance Journal, Elsevier, vol. 45(C).
    8. Henriques, Irene & Sadorsky, Perry, 2011. "The effect of oil price volatility on strategic investment," Energy Economics, Elsevier, vol. 33(1), pages 79-87, January.
    9. Veronika Varvařovská & Michaela Staňková, 2021. "Does the Involvement of "Green Energy" Increase the Productivity of Companies in the Production of the Electricity Sector?," European Journal of Business Science and Technology, Mendel University in Brno, Faculty of Business and Economics, vol. 7(2), pages 152-164.
    10. Jia, Shaoqing & Yang, Liuyong & Zhou, Fangzhao, 2022. "Geopolitical risk and corporate innovation: Evidence from China," Journal of Multinational Financial Management, Elsevier, vol. 66(C).
    11. Augusto Cerqua & Marco Letta & Gabriele Pinto, 2024. "On the (Mis)Use of Machine Learning with Panel Data," Papers 2411.09218, arXiv.org.
    12. Driver, Ciaran & Temple, Paul & Urga, Giovanni, 2008. "Real options -- delay vs. pre-emption: Do industrial characteristics matter?," International Journal of Industrial Organization, Elsevier, vol. 26(2), pages 532-545, March.
    13. Gianluca Femminis, 2019. "Risk aversion heterogeneity and the investment–uncertainty relationship," Journal of Economics, Springer, vol. 127(3), pages 223-264, August.
    14. Mustafa Caglayan & Rebeca Muñoz Torres, 2011. "The Effect of the Exchange Rates on Investment in Mexican Manufacturing Industry," Open Economies Review, Springer, vol. 22(4), pages 669-683, September.
    15. Catherine Fuss & Philip Vermeulen, 2008. "Firms' investment decisions in response to demand and price uncertainty," Applied Economics, Taylor & Francis Journals, vol. 40(18), pages 2337-2351.
    16. H. Dharma Kwon & Wenxin Xu & Anupam Agrawal & Suresh Muthulingam, 2016. "Impact of Bayesian Learning and Externalities on Strategic Investment," Management Science, INFORMS, vol. 62(2), pages 550-570, February.
    17. Giovannoni, Francesco & de Dios Tena, Juan, 2008. "Market concentration, macroeconomic uncertainty and monetary policy," European Economic Review, Elsevier, vol. 52(6), pages 1097-1123, August.
    18. Keiichi Hori & Hiroshi Osano, 2017. "Agency Contracts, Noncommitment Timing Strategies and Real Options," The Japanese Economic Review, Springer, vol. 68(4), pages 521-554, December.
    19. Song, Jeongseop & Zhang, Fan, 2024. "Regional market uncertainty and corporate investment," The North American Journal of Economics and Finance, Elsevier, vol. 69(PB).
    20. Aytekin GÜVEN & Arzu AKKOYUNLU-WIGLEY, 2018. "The Effects of Market Structure on Uncertainty-Investment Relationship: Evidence from Turkish Manufacturing Industry," Sosyoekonomi Journal, Sosyoekonomi Society, issue 26(37).

    More about this item

    Keywords

    Critical Minerals; Artificial Intelligence; Risk Premium;
    All these keywords.

    JEL classification:

    • Q02 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - General - - - Commodity Market
    • Q40 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - General
    • Q50 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - General

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    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:mos:moswps:2024-08. 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: Simon Angus (email available below). General contact details of provider: https://edirc.repec.org/data/dxmonau.html .

    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.