IDEAS home Printed from https://ideas.repec.org/p/uza/wpaper/30192.html
   My bibliography  Save this paper

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

Author

Listed:
  • Zurika, Robinson

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 United States 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

  • Zurika, Robinson, 2023. "A macroeconomic viewpoint using a structural VAR analysis of silver price behaviour," Working Papers 30192, University of South Africa, Department of Economics.
    • Handle: RePEc:uza:wpaper:30192
    as

    Download full text from publisher

    File URL: http://uir.unisa.ac.za/bitstream/handle/10500/30192/11.%20A%20macroeconomic%20viewpoint%20using%20a%20structural%20VAR%20analysis%20of%20silver%20price%20behaviour.pdf
    Download Restriction: no
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. 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.
    2. 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.
    3. 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).
    4. 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.
    5. 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.
    6. Radetzki, Marian, 1989. "Precious metals : The fundamental determinants of their price behaviour," Resources Policy, Elsevier, vol. 15(3), pages 194-208, September.
    7. Akram, Q. Farooq, 2009. "Commodity prices, interest rates and the dollar," Energy Economics, Elsevier, vol. 31(6), pages 838-851, November.
    8. Bouri, Elie & Jalkh, Naji, 2019. "Conditional quantiles and tail dependence in the volatilities of gold and silver," International Economics, Elsevier, vol. 157(C), pages 117-133.
    9. 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.
    10. 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.
    11. 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.
    12. 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.
    13. 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.
    14. 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.
    15. 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.
    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.
    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. Antonakakis, Nikolaos & Kizys, Renatas, 2015. "Dynamic spillovers between commodity and currency markets," International Review of Financial Analysis, Elsevier, vol. 41(C), pages 303-319.
    2. Hu, Min & Zhang, Dayong & Ji, Qiang & Wei, Lijian, 2020. "Macro factors and the realized volatility of commodities: A dynamic network analysis," Resources Policy, Elsevier, vol. 68(C).
    3. Liu, Yang & Han, Liyan & Xu, Yang, 2021. "The impact of geopolitical uncertainty on energy volatility," International Review of Financial Analysis, Elsevier, vol. 75(C).
    4. Zuzanna Karolak, 2021. "Energy prices forecasting using nonlinear univariate models," Bank i Kredyt, Narodowy Bank Polski, vol. 52(6), pages 577-598.
    5. Rossen, Anja, 2015. "What are metal prices like? Co-movement, price cycles and long-run trends," Resources Policy, Elsevier, vol. 45(C), pages 255-276.
    6. Gong, Xu & Xu, Jun, 2022. "Geopolitical risk and dynamic connectedness between commodity markets," Energy Economics, Elsevier, vol. 110(C).
    7. Aikins Abakah, Emmanuel Joel & Gil-Alana, Luis A. & Tripathy, Trilochan, 2022. "Stochastic structure of metal prices: Evidence from fractional integration non-linearities and breaks," Resources Policy, Elsevier, vol. 78(C).
    8. 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.
    9. Rubaszek, Michał & Karolak, Zuzanna & Kwas, Marek, 2020. "Mean-reversion, non-linearities and the dynamics of industrial metal prices. A forecasting perspective," Resources Policy, Elsevier, vol. 65(C).
    10. Scarcioffolo, Alexandre R. & Etienne, Xiaoli L., 2021. "Regime-switching energy price volatility: The role of economic policy uncertainty," International Review of Economics & Finance, Elsevier, vol. 76(C), pages 336-356.
    11. Bayaa, Yasmeen & Qadan, Mahmoud, 2024. "The shape of the Treasury yield curve and commodity prices," International Review of Financial Analysis, Elsevier, vol. 94(C).
    12. 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.
    13. Sinem Guler Kangalli Uyar & Umut Uyar & Emrah Balkan, 2024. "Fundamental predictors of price bubbles in precious metals: a machine learning analysis," Mineral Economics, Springer;Raw Materials Group (RMG);Luleå University of Technology, vol. 37(1), pages 65-87, March.
    14. Vigne, Samuel A. & Lucey, Brian M. & O’Connor, Fergal A. & Yarovaya, Larisa, 2017. "The financial economics of white precious metals — A survey," International Review of Financial Analysis, Elsevier, vol. 52(C), pages 292-308.
    15. Arouri, Mohamed El Hedi & Hammoudeh, Shawkat & Lahiani, Amine & Nguyen, Duc Khuong, 2012. "Long memory and structural breaks in modeling the return and volatility dynamics of precious metals," The Quarterly Review of Economics and Finance, Elsevier, vol. 52(2), pages 207-218.
    16. Vasyl Golosnoy & Anja Rossen, 2018. "Modeling dynamics of metal price series via state space approach with two common factors," Empirical Economics, Springer, vol. 54(4), pages 1477-1501, June.
    17. Awasthi, Kritika & Ahmad, Wasim & Rahman, Abdul & Phani, B.V., 2020. "When US sneezes, clichés spread: How do the commodity index funds react then?," Resources Policy, Elsevier, vol. 69(C).
    18. Zhang, Yongmin & Ding, Shusheng & Scheffel, Eric M., 2019. "A key determinant of commodity price Co-movement: The role of daily market liquidity," Economic Modelling, Elsevier, vol. 81(C), pages 170-180.
    19. Cunado, Juncal & Gil-Alana, Luis A. & Gupta, Rangan, 2019. "Persistence in trends and cycles of gold and silver prices: Evidence from historical data," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 514(C), pages 345-354.
    20. Galán-Gutiérrez, Juan Antonio & Labeaga, José M. & Martín-García, Rodrigo, 2023. "Cointegration between high base metals prices and backwardation: Getting ready for the metals super-cycle," Resources Policy, Elsevier, vol. 81(C).

    More about this item

    Keywords

    Silver; Gold; Oil; Commodity prices;
    All these keywords.

    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:uza:wpaper:30192. 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: Shaun Donovan (email available below). General contact details of provider: https://edirc.repec.org/data/deusaza.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.