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Subsample stability, change detection and dynamics of oil and metal markets: A recursive approach

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  • Khan, Asad Ul Islam
  • Shahbaz, Muhammad
  • Napari, Ayuba

Abstract

The analysis of historical price data for patterns and using such patterns for predictions and policy recommendations has become ubiquitous in the existing economics literature. These predictions and recommendations are premised on the stability of the statistical properties and inter-variable dynamics for which a single regime or few number of regimes can capture. This, however, is a strong assumption with serious repercussions if violated. In this study, the appropriateness of the stability assumption is questioned using various recursive regressions to test stability, consistency of stationarity and stability in inter-variable dynamics between crude oil, gold, silver, and platinum prices. Using monthly data sourced from the World Bank Commodity Price Data (Pink Sheet) from January 1, 1960 to March 2022, our empirical analysis found level prices of oil, gold, and platinum to be consistently non-stationary with rare exceptions. The level price of silver however is found to be inconsistent with multiple regime switches while the logged series of all variables yielded non-stationarity. The default is stationarity for all the variables when price series are logged differenced and/or differenced for oil, silver, and platinum. Differenced gold prices resulted in inconsistent stationarity with multiple regime changes. Even if rare, the stationarity of all the variables is dependent on time and sample size due to the inconsistence in the stationarity verdict. On the bi-variate relationship in the long run, only level silver prices are found to be cointegrated with oil while logged silver prices are inconsistently cointegrated with logged oil prices. Also, in the short-run, only log of oil prices is found to Granger cause log of silver prices. It is thus recommended that researchers and policy makers be tempered in extrapolating statistical findings in general and the price and inter-price dynamics of oil, gold, silver and platinum into the future.

Suggested Citation

  • Khan, Asad Ul Islam & Shahbaz, Muhammad & Napari, Ayuba, 2023. "Subsample stability, change detection and dynamics of oil and metal markets: A recursive approach," Resources Policy, Elsevier, vol. 83(C).
    • Handle: RePEc:eee:jrpoli:v:83:y:2023:i:c:s0301420723003124
    DOI: 10.1016/j.resourpol.2023.103601
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    as
    1. Chao-Hsiang Yang & Chi-Tai Lin & Yu-Sheng Kao, 2012. "Exploring stationarity and structural breaks in commodity prices by the panel data model," Applied Economics Letters, Taylor & Francis Journals, vol. 19(4), pages 353-361, March.
    2. Nelson, Charles R & Piger, Jeremy & Zivot, Eric, 2001. "Markov Regime Switching and Unit-Root Tests," Journal of Business & Economic Statistics, American Statistical Association, vol. 19(4), pages 404-415, October.
    3. Naliniprava Tripathy, 2017. "Forecasting Gold Price with Auto Regressive Integrated Moving Average Model," International Journal of Economics and Financial Issues, Econjournals, vol. 7(4), pages 324-329.
    4. Godil, Danish Iqbal & Sarwat, Salman & Sharif, Arshian & Jermsittiparsert, Kittisak, 2020. "How oil prices, gold prices, uncertainty and risk impact Islamic and conventional stocks? Empirical evidence from QARDL technique," Resources Policy, Elsevier, vol. 66(C).
    5. Johansen, Soren & Juselius, Katarina, 1990. "Maximum Likelihood Estimation and Inference on Cointegration--With Applications to the Demand for Money," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 52(2), pages 169-210, May.
    6. Zivot, Eric & Andrews, Donald W K, 2002. "Further Evidence on the Great Crash, the Oil-Price Shock, and the Unit-Root Hypothesis," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(1), pages 25-44, January.
    7. Baffes, John, 2007. "Oil spills on other commodities," Resources Policy, Elsevier, vol. 32(3), pages 126-134, September.
    8. M. Hashem Pesaran & Yongcheol Shin & Richard J. Smith, 2001. "Bounds testing approaches to the analysis of level relationships," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 16(3), pages 289-326.
    9. Mehmet Balcilar & Zeynel Abidin Ozdemir & Muhammad Shahbaz, 2019. "On the time‐varying links between oil and gold: New insights from the rolling and recursive rolling approaches," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 24(3), pages 1047-1065, July.
    10. Hossein Hassani & Emmanuel Sirimal Silva & Rangan Gupta & Mawuli K. Segnon, 2015. "Forecasting the price of gold," Applied Economics, Taylor & Francis Journals, vol. 47(39), pages 4141-4152, August.
    11. 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.
    12. Sam, Chung Yan & McNown, Robert & Goh, Soo Khoon, 2019. "An augmented autoregressive distributed lag bounds test for cointegration," Economic Modelling, Elsevier, vol. 80(C), pages 130-141.
    13. Maslyuk, Svetlana & Smyth, Russell, 2008. "Unit root properties of crude oil spot and futures prices," Energy Policy, Elsevier, vol. 36(7), pages 2591-2600, July.
    14. Turhan, M. Ibrahim & Sensoy, Ahmet & Ozturk, Kevser & Hacihasanoglu, Erk, 2014. "A view to the long-run dynamic relationship between crude oil and the major asset classes," International Review of Economics & Finance, Elsevier, vol. 33(C), pages 286-299.
    15. Bruce E. Hansen, 2001. "The New Econometrics of Structural Change: Dating Breaks in U.S. Labour Productivity," Journal of Economic Perspectives, American Economic Association, vol. 15(4), pages 117-128, Fall.
    16. Manuel Landajo & María José Presno & Paula Fernández González, 2021. "Stationarity in the Prices of Energy Commodities. A Nonparametric Approach," Energies, MDPI, vol. 14(11), pages 1-16, June.
    17. Hammoudeh, Shawkat & Yuan, Yuan, 2008. "Metal volatility in presence of oil and interest rate shocks," Energy Economics, Elsevier, vol. 30(2), pages 606-620, March.
    18. Johansen, Soren, 1991. "Estimation and Hypothesis Testing of Cointegration Vectors in Gaussian Vector Autoregressive Models," Econometrica, Econometric Society, vol. 59(6), pages 1551-1580, November.
    19. Jushan Bai & Pierre Perron, 2003. "Computation and analysis of multiple structural change models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 18(1), pages 1-22.
    20. Balcilar, Mehmet & Hammoudeh, Shawkat & Asaba, Nwin-Anefo Fru, 2015. "A regime-dependent assessment of the information transmission dynamics between oil prices, precious metal prices and exchange rates," International Review of Economics & Finance, Elsevier, vol. 40(C), pages 72-89.
    21. Varela, Oscar, 1999. "Futures and realized cash or settle prices for gold, silver, and copper," Review of Financial Economics, Elsevier, vol. 8(2), pages 121-138.
    22. 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.
    23. Bampinas, Georgios & Panagiotidis, Theodore, 2015. "Are gold and silver a hedge against inflation? A two century perspective," International Review of Financial Analysis, Elsevier, vol. 41(C), pages 267-276.
    24. Myeong Hwan Kim & David A. Dilts, 2011. "The Relationship of the value of the Dollar, and the Prices of Gold and Oil: A Tale of Asset Risk," Economics Bulletin, AccessEcon, vol. 31(2), pages 1151-1162.
    25. Sari, Ramazan & Hammoudeh, Shawkat & Soytas, Ugur, 2010. "Dynamics of oil price, precious metal prices, and exchange rate," Energy Economics, Elsevier, vol. 32(2), pages 351-362, March.
    26. Dickey, David A & Fuller, Wayne A, 1981. "Likelihood Ratio Statistics for Autoregressive Time Series with a Unit Root," Econometrica, Econometric Society, vol. 49(4), pages 1057-1072, June.
    27. Venditti, Fabrizio & Veronese, Giovanni, 2020. "Global financial markets and oil price shocks in real time," Working Paper Series 2472, European Central Bank.
    28. 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.
    29. Stephan Pfaffenzeller & Paul Newbold & Anthony Rayner, 2007. "A Short Note on Updating the Grilli and Yang Commodity Price Index," The World Bank Economic Review, World Bank, vol. 21(1), pages 151-163.
    30. Soytas, Ugur & Sari, Ramazan & Hammoudeh, Shawkat & Hacihasanoglu, Erk, 2009. "World oil prices, precious metal prices and macroeconomy in Turkey," Energy Policy, Elsevier, vol. 37(12), pages 5557-5566, December.
    31. 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.
    32. Johansen, Soren, 1995. "Likelihood-Based Inference in Cointegrated Vector Autoregressive Models," OUP Catalogue, Oxford University Press, number 9780198774501, Decembrie.
    33. Hall, Stephen G & Psaradakis, Zacharias & Sola, Martin, 1997. "Cointegration and Changes in Regime: The Japanese Consumption Function," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 12(2), pages 151-168, March-Apr.
    34. Robert S. Pindyck, 1999. "The Long-Run Evolutions of Energy Prices," The Energy Journal, International Association for Energy Economics, vol. 0(Number 2), pages 1-27.
    35. Ahmet Faruk Aysan & Ibrahim Guney & Nicoleta Isac & Asad ul Islam Khan, 2022. "The probabilities of type I and II error of null of cointegration tests: A Monte Carlo comparison," PLOS ONE, Public Library of Science, vol. 17(1), pages 1-15, January.
    36. Adewuyi, Adeolu O. & Wahab, Bashir A. & Adeboye, Olusegun S., 2020. "Stationarity of prices of precious and industrial metals using recent unit root methods: Implications for markets’ efficiency," Resources Policy, Elsevier, vol. 65(C).
    37. Thoma, Mark A., 1994. "Subsample instability and asymmetries in money-income causality," Journal of Econometrics, Elsevier, vol. 64(1-2), pages 279-306.
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    More about this item

    Keywords

    Consistency; Subsample stability; Oil prices; Metal prices;
    All these keywords.

    JEL classification:

    • C01 - Mathematical and Quantitative Methods - - General - - - Econometrics
    • C1 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General
    • O13 - Economic Development, Innovation, Technological Change, and Growth - - Economic Development - - - Agriculture; Natural Resources; Environment; Other Primary Products
    • P28 - Political Economy and Comparative Economic Systems - - Socialist and Transition Economies - - - Natural Resources; Environment

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