IDEAS home Printed from https://ideas.repec.org/a/eee/eneeco/v71y2018icp273-281.html
   My bibliography  Save this article

Gold and crude oil prices after the great moderation

Author

Listed:
  • Sephton, Peter
  • Mann, Janelle

Abstract

Previous studies have reported that gold prices and crude oil prices seem to be related, with causality generally running from oil prices to gold prices. This paper revisits the question using non-linear threshold cointegration methods. It examines how a shock to oil prices affects gold prices, with the impacts shown to depend on both the size of the shock and the region within which the system lies when the shock occurs. This simple, yet novel result helps to explain why earlier studies found conflicting evidence on whether gold and crude prices share a long-run relationship. The empirical findings also suggest that energy policies should not be designed without consideration for their interaction with financial policies.

Suggested Citation

  • Sephton, Peter & Mann, Janelle, 2018. "Gold and crude oil prices after the great moderation," Energy Economics, Elsevier, vol. 71(C), pages 273-281.
    • Handle: RePEc:eee:eneeco:v:71:y:2018:i:c:p:273-281
    DOI: 10.1016/j.eneco.2018.02.022
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0140988318300859
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.eneco.2018.02.022?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Balke, Nathan S & Fomby, Thomas B, 1997. "Threshold Cointegration," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 38(3), pages 627-645, August.
    2. Hansen, Bruce E. & Seo, Byeongseon, 2002. "Testing for two-regime threshold cointegration in vector error-correction models," Journal of Econometrics, Elsevier, vol. 110(2), pages 293-318, October.
    3. Keating, John W. & Valcarcel, Victor J., 2017. "What's so great about the Great Moderation?," Journal of Macroeconomics, Elsevier, vol. 51(C), pages 115-142.
    4. Lindé, Jesper & Smets, Frank & Wouters, Rafael, 2016. "Challenges for Central Banks´ Macro Models," Working Paper Series 323, Sveriges Riksbank (Central Bank of Sweden).
    5. Davidson, Russell & MacKinnon, James G, 1981. "Several Tests for Model Specification in the Presence of Alternative Hypotheses," Econometrica, Econometric Society, vol. 49(3), pages 781-793, May.
    6. MacKinnon, James G. & White, Halbert & Davidson, Russell, 1983. "Tests for model specification in the presence of alternative hypotheses : Some further results," Journal of Econometrics, Elsevier, vol. 21(1), pages 53-70, January.
    7. Sephton, Peter & Mann, Janelle, 2013. "Further evidence of an Environmental Kuznets Curve in Spain," Energy Economics, Elsevier, vol. 36(C), pages 177-181.
    8. Jesper Lindé, 2018. "DSGE models: still useful in policy analysis?," Oxford Review of Economic Policy, Oxford University Press and Oxford Review of Economic Policy Limited, vol. 34(1-2), pages 269-286.
    9. Enders, Walter & Siklos, Pierre L, 2001. "Cointegration and Threshold Adjustment," Journal of Business & Economic Statistics, American Statistical Association, vol. 19(2), pages 166-176, April.
    10. Nikolay Gospodinov, 2005. "Testing For Threshold Nonlinearity in Short-Term Interest Rates," Journal of Financial Econometrics, Oxford University Press, vol. 3(3), pages 344-371.
    11. Peter Sephton & Janelle Mann, 2013. "Threshold Cointegration: Model Selection with an Application," Journal of Economics and Econometrics, Economics and Econometrics Society, vol. 56(2), pages 54-77.
    12. Peter Sephton & Janelle Mann, 2016. "Compelling Evidence of an Environmental Kuznets Curve in the United Kingdom," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 64(2), pages 301-315, June.
    13. Ramey, V.A., 2016. "Macroeconomic Shocks and Their Propagation," Handbook of Macroeconomics, in: J. B. Taylor & Harald Uhlig (ed.), Handbook of Macroeconomics, edition 1, volume 2, chapter 0, pages 71-162, Elsevier.
    14. Peter Sephton, 2001. "Forecasting recessions: can we do better on MARS?," Review, Federal Reserve Bank of St. Louis, vol. 83(Mar), pages 39-49.
    15. Seo, Myung Hwan, 2008. "Unit Root Test In A Threshold Autoregression: Asymptotic Theory And Residual-Based Block Bootstrap," Econometric Theory, Cambridge University Press, vol. 24(6), pages 1699-1716, December.
    16. Richard Damania & Bill Z. Yang, 1998. "Price Rigidity and Asymmetric Price Adjustment in a Repeated Oligopoly," Journal of Institutional and Theoretical Economics (JITE), Mohr Siebeck, Tübingen, vol. 154(4), pages 659-659, December.
    17. Peter Sephton, 2008. "Critical values of the augmented fractional Dickey–Fuller test," Empirical Economics, Springer, vol. 35(3), pages 437-450, November.
    18. Kanjilal, Kakali & Ghosh, Sajal, 2017. "Dynamics of crude oil and gold price post 2008 global financial crisis – New evidence from threshold vector error-correction model," Resources Policy, Elsevier, vol. 52(C), pages 358-365.
    19. Elliott, Graham & Rothenberg, Thomas J & Stock, James H, 1996. "Efficient Tests for an Autoregressive Unit Root," Econometrica, Econometric Society, vol. 64(4), pages 813-836, July.
    20. Olivier Blanchard, 2016. "Do DSGE Models Have a Future?," Policy Briefs PB16-11, Peterson Institute for International Economics.
    21. Lucia Alessi & Eric Ghysels & Luca Onorante & Richard Peach & Simon Potter, 2014. "Central Bank Macroeconomic Forecasting During the Global Financial Crisis: The European Central Bank and Federal Reserve Bank of New York Experiences," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 32(4), pages 483-500, October.
    22. Ignacio N Lobato & Carlos Velasco, 2007. "Efficient Wald Tests for Fractional Unit Roots," Econometrica, Econometric Society, vol. 75(2), pages 575-589, March.
    23. Peter Sephton & Janelle Mann, 2015. "Nonlinear attractors and asymmetries between non-life insurance premiums and financial markets," Empirical Economics, Springer, vol. 49(3), pages 783-799, November.
    24. Chang, Hsiao-Fen & Huang, Liang-Chou & Chin, Ming-Chin, 2013. "Interactive relationships between crude oil prices, gold prices, and the NT–US dollar exchange rate—A Taiwan study," Energy Policy, Elsevier, vol. 63(C), pages 441-448.
    25. Sjaastad, Larry A., 2008. "The price of gold and the exchange rates: Once again," Resources Policy, Elsevier, vol. 33(2), pages 118-124, June.
    26. Gonzalo, Jesus & Pitarakis, Jean-Yves, 2002. "Estimation and model selection based inference in single and multiple threshold models," Journal of Econometrics, Elsevier, vol. 110(2), pages 319-352, October.
    27. Chen, Hao & Liao, Hua & Tang, Bao-Jun & Wei, Yi-Ming, 2016. "Impacts of OPEC's political risk on the international crude oil prices: An empirical analysis based on the SVAR models," Energy Economics, Elsevier, vol. 57(C), pages 42-49.
    28. David Bolder & Tiago Rubin, 2007. "Optimization in a Simulation Setting: Use of Function Approximation in Debt Strategy Analysis," Staff Working Papers 07-13, Bank of Canada.
    29. Engle, Robert & Granger, Clive, 2015. "Co-integration and error correction: Representation, estimation, and testing," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 39(3), pages 106-135.
    30. Bampinas Georgios & Panagiotidis Theodore, 2015. "On the relationship between oil and gold before and after financial crisis: linear, nonlinear and time-varying causality testing," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 19(5), pages 657-668, December.
    31. Sephton, Peter S, 1994. "Cointegration Tests on MARS," Computational Economics, Springer;Society for Computational Economics, vol. 7(1), pages 23-35, February.
    32. Lindé, J. & Smets, F. & Wouters, R., 2016. "Challenges for Central Banks’ Macro Models," Handbook of Macroeconomics, in: J. B. Taylor & Harald Uhlig (ed.), Handbook of Macroeconomics, edition 1, volume 2, chapter 0, pages 2185-2262, Elsevier.
    33. Peter Sephton, 2005. "Forecasting inflation using the term structure and MARS," Applied Economics Letters, Taylor & Francis Journals, vol. 12(4), pages 199-202.
    34. Burak Gürış & Burcu Kiran, 2014. "The price of gold and the exchange rate: Evidence from threshold cointegration and threshold granger causality analyses for Turkey," Acta Oeconomica, Akadémiai Kiadó, Hungary, vol. 64(1), pages 91-101, March.
    35. Seyyedsajjad Seyyedi, 2017. "Analysis of the Interactive Linkages Between Gold Prices, Oil Prices, and Exchange Rate in India," Global Economic Review, Taylor & Francis Journals, vol. 46(1), pages 65-79, January.
    36. Steve Ambler, 2016. "Ripple Effects: Oil Price Shocks and Monetary Policy," e-briefs 245, C.D. Howe Institute.
    37. Mann, Janelle & Sephton, Peter, 2016. "Global relationships across crude oil benchmarks," Journal of Commodity Markets, Elsevier, vol. 2(1), pages 1-5.
    38. Peter Sephton, 2017. "Finite Sample Critical Values of the Generalized KPSS Stationarity Test," Computational Economics, Springer;Society for Computational Economics, vol. 50(1), pages 161-172, June.
    39. Reboredo, Juan C., 2013. "Is gold a hedge or safe haven against oil price movements?," Resources Policy, Elsevier, vol. 38(2), pages 130-137.
    40. Aguilera, Roberto F. & Radetzki, Marian, 2017. "The synchronized and exceptional price performance of oil and gold: Explanations and prospects," Resources Policy, Elsevier, vol. 54(C), pages 81-87.
    41. Bart Hobijn & Philip Hans Franses & Marius Ooms, 2004. "Generalizations of the KPSS‐test for stationarity," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 58(4), pages 483-502, November.
    42. Jing Li & Junsoo Lee, 2010. "ADL tests for threshold cointegration," Journal of Time Series Analysis, Wiley Blackwell, vol. 31(4), pages 241-254, July.
    43. Zhang, Yue-Jun & Wei, Yi-Ming, 2010. "The crude oil market and the gold market: Evidence for cointegration, causality and price discovery," Resources Policy, Elsevier, vol. 35(3), pages 168-177, September.
    44. Shafiee, Shahriar & Topal, Erkan, 2010. "An overview of global gold market and gold price forecasting," Resources Policy, Elsevier, vol. 35(3), pages 178-189, September.
    45. Peter Sephton, 2009. "Critical values for the augmented efficient Wald test for fractional unit roots," Empirical Economics, Springer, vol. 37(3), pages 615-626, December.
    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. Zhu, Xuehong & Niu, Zibo & Zhang, Hongwei & Huang, Jiaxin & Zuo, Xuguang, 2022. "Can gold and bitcoin hedge against the COVID-19 related news sentiment risk? New evidence from a NARDL approach," Resources Policy, Elsevier, vol. 79(C).
    2. Youssef, Manel & Mokni, Khaled, 2021. "Oil-gold nexus: Evidence from regime switching-quantile regression approach," Resources Policy, Elsevier, vol. 73(C).
    3. Adekoya, Oluwasegun B. & Oliyide, Johnson A. & Oduyemi, Gabriel O., 2021. "How COVID-19 upturns the hedging potentials of gold against oil and stock markets risks: Nonlinear evidences through threshold regression and markov-regime switching models," Resources Policy, Elsevier, vol. 70(C).
    4. Ding, Qian & Huang, Jianbai & Chen, Jinyu, 2021. "Dynamic and frequency-domain risk spillovers among oil, gold, and foreign exchange markets: Evidence from implied volatility," Energy Economics, Elsevier, vol. 102(C).
    5. Zhang, Pinyi & Ci, Bicong, 2020. "Deep belief network for gold price forecasting," Resources Policy, Elsevier, vol. 69(C).
    6. Fijorek, Kamil & Jurkowska, Aleksandra & Jonek-Kowalska, Izabela, 2021. "Financial contagion between the financial and the mining industries – Empirical evidence based on the symmetric and asymmetric CoVaR approach," Resources Policy, Elsevier, vol. 70(C).
    7. Salisu, Afees A. & Adediran, Idris, 2020. "Gold as a hedge against oil shocks: Evidence from new datasets for oil shocks," Resources Policy, Elsevier, vol. 66(C).
    8. Alameer, Zakaria & Elaziz, Mohamed Abd & Ewees, Ahmed A. & Ye, Haiwang & Jianhua, Zhang, 2019. "Forecasting gold price fluctuations using improved multilayer perceptron neural network and whale optimization algorithm," Resources Policy, Elsevier, vol. 61(C), pages 250-260.
    9. Tanin, Tauhidul Islam & Sarker, Ashutosh & Brooks, Robert & Do, Hung Xuan, 2022. "Does oil impact gold during COVID-19 and three other recent crises?," Energy Economics, Elsevier, vol. 108(C).
    10. Johnson A. Oliyide & Oluwasegun B. Adekoya & Muhammad A. Khan, 2021. "Economic policy uncertainty and the volatility connectedness between oil shocks and metal market: An extension," International Economics, CEPII research center, issue 167, pages 136-150.
    11. Taner Akan & Halil İbrahim Gündüz & Tara Vanlı & Ahmet Baran Zeren & Ali Haydar Işık & Tamerlan Mashadihasanli, 2023. "Why are some countries cleaner than others? New evidence from macroeconomic governance," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 25(7), pages 6167-6223, July.
    12. Wang, Xinya & Lucey, Brian & Huang, Shupei, 2022. "Can gold hedge against oil price movements: Evidence from GARCH-EVT wavelet modeling," Journal of Commodity Markets, Elsevier, vol. 27(C).
    13. Sirine Toumi, 2019. "Co-movements amongst Gold and Oil: A Multivariate Time-Varying Asymmetric Approach," International Journal of Finance, Insurance and Risk Management, International Journal of Finance, Insurance and Risk Management, vol. 9(3-4), pages 52-68.
    14. Zhang, Guangyong & Jiang, Le & Tian, Lixin & Fu, Min, 2021. "Analysis of the gold fixing price fluctuation in different times based on the directed weighted networks," The North American Journal of Economics and Finance, Elsevier, vol. 57(C).
    15. Mohamed Arbi Madani & Zied Ftiti, 2022. "Is gold a hedge or safe haven against oil and currency market movements? A revisit using multifractal approach," Annals of Operations Research, Springer, vol. 313(1), pages 367-400, June.
    16. Sephton, Peter S., 2019. "El Niño, La Niña, and a cup of Joe," Energy Economics, Elsevier, vol. 84(C).
    17. Sephton, Peter, 2023. "Threshold cointegration and asymmetries between dividends and earnings news," Finance Research Letters, Elsevier, vol. 58(PB).
    18. Cheng, Sheng & Han, Lingyu & Cao, Yan & Jiang, Qisheng & Liang, Ruibin, 2022. "Gold-oil dynamic relationship and the asymmetric role of geopolitical risks: Evidence from Bayesian pdBEKK-GARCH with regime switching," Resources Policy, Elsevier, vol. 78(C).
    19. Salisu, Afees A. & Vo, Xuan Vinh & Lawal, Adedoyin, 2021. "Hedging oil price risk with gold during COVID-19 pandemic," Resources Policy, Elsevier, vol. 70(C).
    20. Maciej Mróz, 2022. "The Impact of Energy Commodity Prices on Selected Clean Energy Metal Prices," Energies, MDPI, vol. 15(9), pages 1-15, April.
    21. Sephton, Peter S., 2022. "Revisiting the inflation-hedging properties of precious metals in Africa," Resources Policy, Elsevier, vol. 77(C).
    22. Adekoya, Oluwasegun B. & Oliyide, Johnson A., 2020. "The hedging effectiveness of industrial metals against different oil shocks: Evidence from the four newly developed oil shocks datasets," Resources Policy, Elsevier, vol. 69(C).

    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. Sephton, Peter S., 2019. "El Niño, La Niña, and a cup of Joe," Energy Economics, Elsevier, vol. 84(C).
    2. Kanjilal, Kakali & Ghosh, Sajal, 2017. "Dynamics of crude oil and gold price post 2008 global financial crisis – New evidence from threshold vector error-correction model," Resources Policy, Elsevier, vol. 52(C), pages 358-365.
    3. Peter Sephton & Janelle Mann, 2013. "Threshold Cointegration: Model Selection with an Application," Journal of Economics and Econometrics, Economics and Econometrics Society, vol. 56(2), pages 54-77.
    4. Peter Sephton & Janelle Mann, 2016. "Compelling Evidence of an Environmental Kuznets Curve in the United Kingdom," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 64(2), pages 301-315, June.
    5. Sephton, Peter, 2023. "Threshold cointegration and asymmetries between dividends and earnings news," Finance Research Letters, Elsevier, vol. 58(PB).
    6. Muhammad Shahbaz & Naceur Khraief & Mantu Kumar Mahalik, 2020. "Investigating the environmental Kuznets’s curve for Sweden: evidence from multivariate adaptive regression splines (MARS)," Empirical Economics, Springer, vol. 59(4), pages 1883-1902, October.
    7. Peter Sephton & Janelle Mann, 2015. "Nonlinear attractors and asymmetries between non-life insurance premiums and financial markets," Empirical Economics, Springer, vol. 49(3), pages 783-799, November.
    8. Mann, Janelle M., 2013. "Is there a Global Relationship Across Crude Oil Benchmarks?," 2013 Annual Meeting, August 4-6, 2013, Washington, D.C. 150368, Agricultural and Applied Economics Association.
    9. Cui, Moyang & Wong, Wing-Keung & Wisetsri, Worakamol & Mabrouk, Fatma & Muda, Iskandar & Li, Zeyun & Hassan, Marria, 2023. "Do oil, gold and metallic price volatilities prove gold as a safe haven during COVID-19 pandemic? Novel evidence from COVID-19 data," Resources Policy, Elsevier, vol. 80(C).
    10. Mann, Janelle & Sephton, Peter, 2016. "Global relationships across crude oil benchmarks," Journal of Commodity Markets, Elsevier, vol. 2(1), pages 1-5.
    11. Andrew Phiri, 2020. "Structural changes in exchange rate-stock returns dynamics in South Africa: examining the role of crisis and new trading platform," Economic Change and Restructuring, Springer, vol. 53(1), pages 171-193, February.
    12. Sokbae Lee & Myung Hwan Seo & Youngki Shin, 2017. "Correction," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 112(518), pages 883-883, April.
    13. Chiappini, Raphaël & Jégourel, Yves & Raymond, Paul, 2019. "Towards a worldwide integrated market? New evidence on the dynamics of U.S., European and Asian natural gas prices," Energy Economics, Elsevier, vol. 81(C), pages 545-565.
    14. Sephton, Peter & Mann, Janelle, 2013. "Further evidence of an Environmental Kuznets Curve in Spain," Energy Economics, Elsevier, vol. 36(C), pages 177-181.
    15. Sephton, Peter S., 2022. "Revisiting the inflation-hedging properties of precious metals in Africa," Resources Policy, Elsevier, vol. 77(C).
    16. Gonzalo, Jesùs & Pitarakis, Jean-Yves, 2005. "Threshold effects In multivariate error correction models," Discussion Paper Series In Economics And Econometrics 0501, Economics Division, School of Social Sciences, University of Southampton.
    17. Daiki Maki & Shin-ichi Kitasaka, 2015. "Residual-based tests for cointegration with three-regime TAR adjustment," Empirical Economics, Springer, vol. 48(3), pages 1013-1054, May.
    18. Mohamed Arbi Madani & Zied Ftiti, 2019. "The Generalisation of the DMCA Coefficient to Serve Distinguishing Between Hedge and Safe Haven Capabilities of the Gold," Papers 1912.12590, arXiv.org.
    19. Shu-Chen Chang, 2008. "Asymmetric cointegration relationship among Asian exchange rates," Economic Change and Restructuring, Springer, vol. 41(2), pages 125-141, June.
    20. Salisu, Afees A. & Vo, Xuan Vinh & Lawal, Adedoyin, 2021. "Hedging oil price risk with gold during COVID-19 pandemic," Resources Policy, Elsevier, vol. 70(C).

    More about this item

    Keywords

    Threshold cointegration; Error correction equation; Multivariate adaptive regression splines; Gold price; Brent oil price;
    All these keywords.

    JEL classification:

    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • C58 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Financial Econometrics
    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions
    • Q4 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy

    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:eee:eneeco:v:71:y:2018:i:c:p:273-281. 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/eneco .

    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.