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A macroeconomic viewpoint using a structural VAR analysis of silver price behaviour

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  • Z. Robinson

    (University of South Africa)

Abstract

This article investigates silver price as a fluctuating commodity price since the financial crisis of 2007–2009. In this regard, a structural vector autoregression (VAR) was applied to observe the sensitivity of the silver price and future pricing due to changes in macroeconomic variables and to review changes in macroeconomic variables due to changes in the silver price. The main results show that the silver price is susceptible to changes in the gold price, increasing sideways. A shock to OECD GDP caused the silver price to increase which makes logical sense, thus showing a positive correlation between output and the silver price. A shock to the oil price caused the silver price to spike over the short term, then move sideways over the long term. A shock to the US Federal funds rate caused the silver price to dip over the short term, then increase slightly over the medium and move sideways over the long term, while a shock to the real effective exchange rate of the USA caused the silver price to increase sideways. The article sheds some light on the reactive status of the silver price to macroeconomic variables and its influence as a safe haven commodity.

Suggested Citation

  • Z. Robinson, 2024. "A macroeconomic viewpoint using a structural VAR analysis of silver price behaviour," Mineral Economics, Springer;Raw Materials Group (RMG);Luleå University of Technology, vol. 37(1), pages 15-23, March.
    • Handle: RePEc:spr:minecn:v:37:y:2024:i:1:d:10.1007_s13563-023-00386-y
    DOI: 10.1007/s13563-023-00386-y
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    1. 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.
    2. Apergis, Nicholas & Carmona-González, Nieves & Gil-Alana, Luis Alberiko, 2020. "Persistence in silver prices and the influence of solar energy," Resources Policy, Elsevier, vol. 69(C).
    3. Radetzki, Marian, 1989. "Precious metals : The fundamental determinants of their price behaviour," Resources Policy, Elsevier, vol. 15(3), pages 194-208, September.
    4. Woradee Jongadsayakul, 2015. "Determinants Of Silver Futures Price Volatility: Evidence From The Thailand Futures Exchange," The International Journal of Business and Finance Research, The Institute for Business and Finance Research, vol. 9(4), pages 81-87.
    5. Amare Wubishet Ayele & Emmanuel Gabreyohannes & Hayimro Edmealem, 2020. "Generalized Autoregressive Conditional Heteroskedastic Model to Examine Silver Price Volatility and Its Macroeconomic Determinant in Ethiopia Market," Journal of Probability and Statistics, Hindawi, vol. 2020, pages 1-10, May.
    6. Robinson, Zurika, 2017. "Sustainability of platinum production in South Africa and the dynamics of commodity pricing," Resources Policy, Elsevier, vol. 51(C), pages 107-114.
    7. Duncan Hodge, 2015. "Commodity prices, the exchange rate and manufacturing in South Africa: what do the data say?," African Journal of Economic and Management Studies, Emerald Group Publishing Limited, vol. 6(4), pages 356-379, December.
    8. Akram, Q. Farooq, 2009. "Commodity prices, interest rates and the dollar," Energy Economics, Elsevier, vol. 31(6), pages 838-851, November.
    9. Duncan Hodge, 2015. "Commodity prices, the exchange rate and manufacturing in South Africa: what do the data say?," African Journal of Economic and Management Studies, Emerald Group Publishing Limited, vol. 6(4), pages 356-379, December.
    10. Elie Bouri & Naji Jalkh, 2019. "Conditional quantiles and tail dependence in the volatilities of gold and silver," International Economics, CEPII research center, issue 157, pages 117-133.
    11. Pindyck, Robert S., 1981. "Models of resource markets and the explanation of resource price behaviour," Energy Economics, Elsevier, vol. 3(3), pages 130-139, July.
    12. Batten, Jonathan A. & Ciner, Cetin & Lucey, Brian M., 2010. "The macroeconomic determinants of volatility in precious metals markets," Resources Policy, Elsevier, vol. 35(2), pages 65-71, June.
    13. Issler, João Victor & Rodrigues, Claudia & Burjack, Rafael, 2014. "Using common features to understand the behavior of metal-commodity prices and forecast them at different horizons," Journal of International Money and Finance, Elsevier, vol. 42(C), pages 310-335.
    14. Zhu, Huiming & Peng, Cheng & You, Wanhai, 2016. "Quantile behaviour of cointegration between silver and gold prices," Finance Research Letters, Elsevier, vol. 19(C), pages 119-125.
    15. 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.
    16. Zurika Robinson, 2019. "Revisiting gold price behaviour: a structural VAR," Mineral Economics, Springer;Raw Materials Group (RMG);Luleå University of Technology, vol. 32(3), pages 365-372, November.
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    1. Chaya Bagrecha & Kuldeep Singh & Geeti Sharma & P. B. Saranya, 2025. "Forecasting silver prices: a univariate ARIMA approach and a proposed model for future direction," Mineral Economics, Springer;Raw Materials Group (RMG);Luleå University of Technology, vol. 38(1), pages 131-141, March.

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    Keywords

    Silver; Gold; Oil; Commodity prices;
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