IDEAS home Printed from https://ideas.repec.org/p/unu/wpaper/wp-2020-157.html
   My bibliography  Save this paper

Pandemics and their impact on oil and metal prices

Author

Listed:
  • Tony Addison
  • Atanu Ghoshray

Abstract

We examine the effect of pandemics on selected commodity prices—in particular, those of zinc, copper, lead, and oil. We set up a vector autoregressive model and analyse data since the mid-nineteenth century to determine how prices reacted to pandemics such as the 1918 Spanish Flu, 1957 Asian Flu, and 1968 Hong Kong Flu. We control for demand and supply fundamentals to generate forecasts from the point of outbreak, and we consider whether any pattern can be deduced in reactions to adverse global shocks.

Suggested Citation

  • Tony Addison & Atanu Ghoshray, 2020. "Pandemics and their impact on oil and metal prices," WIDER Working Paper Series wp-2020-157, World Institute for Development Economic Research (UNU-WIDER).
    • Handle: RePEc:unu:wpaper:wp-2020-157
    as

    Download full text from publisher

    File URL: https://www.wider.unu.edu/sites/default/files/Publications/Working-paper/PDF/wp2020-157.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Stuermer, Martin, 2018. "150 Years Of Boom And Bust: What Drives Mineral Commodity Prices?," Macroeconomic Dynamics, Cambridge University Press, vol. 22(3), pages 702-717, April.
    2. Christiane Baumeister & Gert Peersman, 2013. "The Role Of Time‐Varying Price Elasticities In Accounting For Volatility Changes In The Crude Oil Market," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 28(7), pages 1087-1109, November.
    3. Nick Bloom & Stephen Bond & John Van Reenen, 2007. "Uncertainty and Investment Dynamics," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 74(2), pages 391-415.
    4. Angus Deaton & Guy Laroque, 1992. "On the Behaviour of Commodity Prices," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 59(1), pages 1-23.
    5. Serena Ng & Pierre Perron, 2001. "LAG Length Selection and the Construction of Unit Root Tests with Good Size and Power," Econometrica, Econometric Society, vol. 69(6), pages 1519-1554, November.
    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. Caldara, Dario & Cavallo, Michele & Iacoviello, Matteo, 2019. "Oil price elasticities and oil price fluctuations," Journal of Monetary Economics, Elsevier, vol. 103(C), pages 1-20.
    2. Winkelried, Diego, 2021. "Unit roots in real primary commodity prices? A meta-analysis of the Grilli and Yang data set," Journal of Commodity Markets, Elsevier, vol. 23(C).
    3. Gauvin, Ludovic & Rebillard, Cyril, 2013. "Towards Recoupling? Assessing the Impact of a Chinese Hard Landing on Commodity Exporters: Results from Conditional Forecast in a GVAR Model," MPRA Paper 65457, University Library of Munich, Germany.
    4. John Cuddington & Zhongmin Wang, 2006. "Assessing the Degree of Spot Market Integration for U.S. Natural Gas: Evidence from Daily Price Data," Journal of Regulatory Economics, Springer, vol. 29(2), pages 195-210, March.
    5. Amélie Charles & Chew Lian Chua & Olivier Darné & Sandy Suardi, 2021. "Oil price shocks, real economic activity and uncertainty," Bulletin of Economic Research, Wiley Blackwell, vol. 73(3), pages 364-392, July.
    6. Joëts, Marc & Mignon, Valérie & Razafindrabe, Tovonony, 2017. "Does the volatility of commodity prices reflect macroeconomic uncertainty?," Energy Economics, Elsevier, vol. 68(C), pages 313-326.
    7. Mignon, Valérie & Saadaoui, Jamel, 2025. "Asymmetries in the oil market: accounting for the growing role of China through quantile regressions," Macroeconomic Dynamics, Cambridge University Press, vol. 29, pages 1-1, January.
    8. Goodness C. Aye & Rangan Gupta & Mampho P. Modise, 2015. "Do Stock Prices Impact Consumption and Interest Rate in South Africa? Evidence from a Time-varying Vector Autoregressive Model," Journal of Emerging Market Finance, Institute for Financial Management and Research, vol. 14(2), pages 176-196, August.
    9. Ludovic Gauvin & Cyril C. Rebillard, 2018. "Towards recoupling? Assessing the global impact of a Chinese hard landing through trade and commodity price channels," The World Economy, Wiley Blackwell, vol. 41(12), pages 3379-3415, December.
    10. Gil-Alana, Luis A. & Chang, Shinhye & Balcilar, Mehmet & Aye, Goodness C. & Gupta, Rangan, 2015. "Persistence of precious metal prices: A fractional integration approach with structural breaks," Resources Policy, Elsevier, vol. 44(C), pages 57-64.
    11. Kang, Wensheng & Ratti, Ronald A. & Vespignani, Joaquin L., 2017. "Oil price shocks and policy uncertainty: New evidence on the effects of US and non-US oil production," Energy Economics, Elsevier, vol. 66(C), pages 536-546.
    12. Refk Selmi & Jamal Bouoiyour & Shawkat Hammoudeh, 2020. "Common and country-specific uncertainty fluctuations in oil-producing countries : Measures, macroeconomic effects and policy challenges," Post-Print hal-02929898, HAL.
    13. Peter Broer & Jürgen Antony, 2013. "Financial Shocks and Economic Activity in the Netherlands," CPB Discussion Paper 260, CPB Netherlands Bureau for Economic Policy Analysis.
    14. Van Robays, Ine, 2012. "Macroeconomic uncertainty and the impact of oil shocks," Working Paper Series 1479, European Central Bank.
    15. Balcilar, Mehmet & Gupta, Rangan & Wohar, Mark E., 2017. "Common cycles and common trends in the stock and oil markets: Evidence from more than 150years of data," Energy Economics, Elsevier, vol. 61(C), pages 72-86.
    16. Jin, Xin, 2019. "The role of market expectations in commodity price dynamics: Evidence from oil data," Journal of International Money and Finance, Elsevier, vol. 90(C), pages 1-18.
    17. Martin Stuermer, 2022. "Non-renewable resource extraction over the long term: empirical evidence from global copper production," Mineral Economics, Springer;Raw Materials Group (RMG);Luleå University of Technology, vol. 35(3), pages 617-625, December.
    18. Xiao-lin Li & Mehmet Balcilar & Rangan Gupta & Tsangyao Chang, 2016. "The Causal Relationship Between Economic Policy Uncertainty and Stock Returns in China and India: Evidence from a Bootstrap Rolling Window Approach," Emerging Markets Finance and Trade, Taylor & Francis Journals, vol. 52(3), pages 674-689, March.
    19. Bataa, Erdenebat & Izzeldin, Marwan & Osborn, Denise R., 2016. "Changes in the global oil market," Energy Economics, Elsevier, vol. 56(C), pages 161-176.
    20. van de Ven, Dirk Jan & Fouquet, Roger, 2017. "Historical energy price shocks and their changing effects on the economy," Energy Economics, Elsevier, vol. 62(C), pages 204-216.

    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:unu:wpaper:wp-2020-157. 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: Siméon Rapin (email available below). General contact details of provider: https://edirc.repec.org/data/widerfi.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.