Advertisement

Mineral Economics

, Volume 25, Issue 2–3, pp 107–127 | Cite as

Spillovers between cobalt, copper and nickel prices: implications for deep seabed mining

  • Simone MartinoEmail author
  • Lindsay M. Parson
Original Paper

Abstract

Interaction between prices of nickel, copper and cobalt, the latter a by-product of nickel and copper in laterites and sulphite deposits, are analysed in relation to the price of oil, the US real interest rate and the real effective exchange rate of dollar using an autoregressive distributed lag model, to draw considerations on the profitability in the exploitation of polymetallic manganese nodules and cobalt crust in a mutually exclusive scenario. The results show co-movements between these variables through the presence of three long-run relationships. Focusing mainly on the cobalt/nickel relationship, it is shown that price of cobalt anticipates and exerts a negative effect on nickel while, as expected, the price of oil has a positive impact and the exchange rate a negative one. Conversely, the impact of the real interest rate is not significant. A Monte Carlo simulation is employed to forecast a robust average price of nickel in the long run, finding that under the actual stagnant economic conditions and an average price of cobalt of $40/kg (at 2000 price equivalence), the price of nickel will remain close to the actual, around $18/kg (at 2000 price equivalence). This result, coupled with the literature findings that in a mutually exclusive scenario, the prevalence of cobalt crust over manganese nodules can be shown only if the price of nickel is below $9/kg (at 2000 price equivalence), justifies why increased attention has been re-directed towards polymetallic nodules.

Keywords

Deep seabed mining Price spillovers ARDL model Toda Yamamoto test Monte Carlo analysis Price forecasting 

JEL classification

C51 E27 E37 E47 L72 Q17 Q43 

Notes

Acknowledgements

The authors gratefully acknowledge critical comments on a draft of this paper discussed during internal debates held at the National Oceanography Centre, Southampton, within the UNCLOS Group. Finally, special thanks to two anonymous reviewers that have improved the quality of the paper suggesting further statistical analysis to check the robustness of our preliminary results.

References

  1. Adrangi B, Chatrath A, Raffiee K, Ripple RD (2001) Alaska North slope crude oil price and the behaviour of diesel prices in California. Energy Econ 23:29–42CrossRefGoogle Scholar
  2. Agarwal HP, Goodrich JD (2003) Extraction of copper, nickel and cobalt from Indian Ocean nodules. Can J Chem Eng 81:303–306CrossRefGoogle Scholar
  3. Akram QF (2009) Commodity prices, interest rates and the dollar. Energy Econ 31:838–851CrossRefGoogle Scholar
  4. Asche F, Gjolberg O, Volker T (2003) Price relationship in the petroleum market, an analysis of crude oil and refined product prices. Energy Econ 25:289–301CrossRefGoogle Scholar
  5. Baffes J (2007) Oil spills on the other commodities. Resour Policy 32:126–134CrossRefGoogle Scholar
  6. Berck P, Roberts M (1996) Natural resource prices: will they ever turn up? J Environ Econ Manag 31:65–78CrossRefGoogle Scholar
  7. Byrne JP, Fazio G, Fiess N (2011) Primary commodity prices. Co-movements, common factors and fundamentals policy. The World Bank. Res Work Pap 5578:35Google Scholar
  8. Breusch TS (1979) Testing for autocorrelation in dynamic linear models. Aust Econ Pap 17:334–355CrossRefGoogle Scholar
  9. Broadus JM (1987) Seabed materials. Science 235:853–860CrossRefGoogle Scholar
  10. Broad JW (2010) Mining the seafloor for rare earth minerals. The New York Times, 8 November 2010Google Scholar
  11. Brooks C (2008) Introductory econometrics for finance. Cambridge University Press, CambridgeGoogle Scholar
  12. Calvo G (2008) Exploding commodity prices, lax monetary policy and sovereign wealth funds. VoxEU, 20th June 2008Google Scholar
  13. Campbell GA (1985) The role of co-products in stabilising the metal mining industry. Resour Policy 11(4):267–274CrossRefGoogle Scholar
  14. Campbell GA (1996) Economic relationship and market trends of the rare earths. J Miner Policy Bus Environ Raw Mater Rep 12(2):2–11CrossRefGoogle Scholar
  15. CDI (2008) The cobalt conference. Cobalt News 3, 9–10. Available from www.thecdi.com/cobaltnews.php. Accessed February 2011
  16. CDI (2010) Production statistics. Cobalt News 2, 3–4. Available from http://www.thecdi.com/cdi/images/news_pdf/cobalt_news_apr10.pdf. Accessed February 2011
  17. Chen MH (2010) Understanding world metals prices-returns, volatility and diversification. Resour Policy 35:127–140CrossRefGoogle Scholar
  18. Cuddington JT, Jerrett D (2008) Super cycles in real metal prices? IMF Staff Pap 55:541–565CrossRefGoogle Scholar
  19. Dickey DA, Fuller WA (1979) Distribution of the estimators for autoregressive time series with a unit root. J Am Stat Assoc 74:427–431Google Scholar
  20. Dickey DA, Fuller WA (1981) Likelihood ratio statistics for autoregressive time series with a unit root. Econom 49:1057–1072CrossRefGoogle Scholar
  21. Donges JB (1984) The economics of deep-sea mining. Springer-Verlag, BerlinGoogle Scholar
  22. ECB (2010) Global commodity cycles and linkages. A FAVAR approach. Working paper series No 1170/April 2010. Available from http://www.ecb.int/pub/pdf/scpwps/ecbwp1170.pdf. Accessed October 2010
  23. EIA (2011) Annual Energy Outlook 2011. Available from www.eia.doe.gov/oiaf/aeo/. Accessed July 2011
  24. Elliott G, Rothenberg TJ, Stock JH (1996) Efficient tests for an autoregressive unit root. Econom 64:813–836CrossRefGoogle Scholar
  25. Engle RF, Granger CWJ (1987) Co-integration and error correction term: representation, estimation and testing. Econom 55:251–276CrossRefGoogle Scholar
  26. Erry B, Johnston P, Santillo D (2000) Seabed mining a technical review, pp.53. Available from www.greenpeace.to/publications/Seabed-mining-technical-note-2000.pdf. Accessed October 2010
  27. Ewing BT, Malik F, Ozfidan O (2002) Volatility transmission in the oil and natural gas markets. Energy Econ 24(6):525–538CrossRefGoogle Scholar
  28. Frankel JA (2008) The effect of monetary policy on real commodity prices. In: Campbell JY (ed) Asset prices and monetary policy. NBER, University of Chicago, Chicago, And NBER Working Paper 12713Google Scholar
  29. Ghatak S, Siddiki J (2001) The use of ARDL approach in estimating virtual exchange rate in India. J Appl Stat 28:573–583CrossRefGoogle Scholar
  30. Gilbert CL (1995) Modelling market fundamentals: a model of the aluminium market. J Appl Econom 10(4):385–410CrossRefGoogle Scholar
  31. Glasby GP (1986) Marine minerals in the Pacific. Oceanogr. and Mar. Biol., an Annu. Rev 24:11–24Google Scholar
  32. Glasby GP (2002) Deep seabed mining: past failure and future prospects. Mar Georesour Geotechnol 20:161–176CrossRefGoogle Scholar
  33. Grosz RWG (2005) Consortium opportunities for deep seabed mining in the Republic of Kiribati, Central Pacific Ocean, based on its competitive advantages vis-à-vis other deep seabed resource owning nations and the International Seabed Authority, 2005. Available from http://www.atollinstitute.org/Institute%20Legal%20Papers/Consortium%20Opportunities%20for%20Deep%20Seabed%20Mining.doc. Accessed July 2010
  34. Gupta S (1982) An econometric analysis of the world zinc market. Empir Econ 7:213–237CrossRefGoogle Scholar
  35. Gupta P, Gupta S (1983) World demand for cobalt. Resour Policy 9(4):261–274CrossRefGoogle Scholar
  36. Halbach PM, Sattler CD, Teichmann F, Wahnser M (1989) Cobalt rich and platinum-bearing manganese crust deposits on seamounts: nature, formation, and metal potential. Mar Georesour Geotechnol 8:8–23Google Scholar
  37. Halfar J, Fujita RM (2002) Precautionary management of deep-sea mining. Mar Policy 26:103–106CrossRefGoogle Scholar
  38. Halicioglu F (2004) An ARDL model of international tourist flows to Turkey. Glob Bus Econ Rev 2004 Anthol. 614–624Google Scholar
  39. Halicioglu F (2009) An econometric study of CO2 emissions, energy consumption, income and foreign trade in Turkey. Energy Policy 37:1156–1164CrossRefGoogle Scholar
  40. Hall AD (1994) Testing for a unit root in time series with pre-test data based model selection. J Bus Econ Stat 12:461–470Google Scholar
  41. Hamilton (1994) Time series analysis. Princeton University Press, PrincetonGoogle Scholar
  42. Hammoudeh S, Sari R, Ewing B (2009) Relationships among strategic commodities and with financial variables: a new look. Contemp Econ Policy 27(2):251–264CrossRefGoogle Scholar
  43. Handschuh R, Schulte E, Grebe H, Schwarz W (2003) Economic simulation for a small scale manganese nodule mining system taking into account new technologies. In: Chung JS (eds) Proceeding of the fifth (2003) Ocean Symposium Tsukuba, Japan, 15–19 September 2003, pp. 71–75Google Scholar
  44. Hein JR et al (2000) Cobalt-rich ferromanganese crusts in the Pacific. In: Cronan DS (ed) Handbook of marine mineral deposits. CRC Press, Boca Raton, pp 239–279Google Scholar
  45. Hoagland P, Beaulieu S, Tivey MA, Eggert RG, German C, Glowka L, Lian J (2010) Deep-sea mining of seafloor massive sulfides. Mar Policy 34:728–732CrossRefGoogle Scholar
  46. Hoagland P (1993) Manganese nodule price trends. Dim prospects for the commercialization of deep seabed mining. Resour Policy 19(4):287–298CrossRefGoogle Scholar
  47. Hua P (1998) On the primary commodity prices: the impact of macroeconomic/monetary shocks. J Policy Model 20(6):767–790CrossRefGoogle Scholar
  48. Humphreys D (2010) The great metals boom: a retrospective. Resour Policy 35:1–13CrossRefGoogle Scholar
  49. IMF (2008) World economic outlook: housing and the business cycle. International Monetary Fund, Washington. Available from http://www.imf.org/external/pubs/ft/weo/2008/01/. Accessed December 2010
  50. ISA (2004) Marine mineral resources. Available from http://www.isa.org.jm/files/documents/EN/Pubs/ISA-Daolos.pdf. Accessed October 2010
  51. ISA (2010) Non-living resources of the continental shelf beyond 200 nautical miles: speculation on the implementation of article 82 of the United Nations convention on the Law of the Sea. Technical study N.5. Available from www.isa.org.jm/files/documents/EN/Pubs/TechStudy5.pdf. Accessed December 2010
  52. Johansen S, Juselius K (1990) Maximum likelihood estimation and inference on cointegration-with application to the demand for money. Oxf Bull Econ Stat 52:169–210CrossRefGoogle Scholar
  53. Johnson CJ, Otto JM (1986) Manganese nodule project economics. Factors relating to the Pacific Region. Resour Policy 12(1):17–28CrossRefGoogle Scholar
  54. Kagraoka Y (2011) Common dynamic factors driving metal and energy prices. Musashi Discussion Paper Series 62, Tokyo, Japan, p.1–62. Available from www.musashi.jp/-kagraoka/research/dynfac_101.pdf. Accessed November 2011
  55. Kamphausen D (1978) Raw materials from the deep sea: what implications for land-based mining in developing countries? Econ Bull 15(8):3–8CrossRefGoogle Scholar
  56. Kesler SE (2007) Mineral supply and demand into the 21st Century. In: Briskey JA, Schulz KJ (ed) Proceedings of the workshop on deposit modelling, Mineral Resource Assessment, and Sustainable Development, pp. 55–62. Available from http://pubs.usgs.gov/circ/2007/1294/reports. Accessed October 2010
  57. Krichene N (2008) Recent inflationary trends in world commodity markets. Working paper 09/130. International Monetary Fund. Available from www.imf.org/external/pubs/ft/wp/2008/wp08130.pdf. Accessed August 2010
  58. Krugman P (2008) Running out of planet to exploit, 21st April, New York Times Op-Ed ColumnistGoogle Scholar
  59. Kwiatkowski D, Phillips PCB, Schmidt P, Shin Y (1992) Testing the null hypothesis of stationarity against the alternative of a unit root. J Econometrics 54:159–178CrossRefGoogle Scholar
  60. Labys WC, Achouch A, Terraza M (1999) Metal prices and the business cycle. Resour Policy 25:229–238CrossRefGoogle Scholar
  61. Lahart J (2006) Ahead of the tape: Dr Copper. WJS, Section C, April 5, 2006Google Scholar
  62. Lanza A, Manera M, Giovannini M (2005) Modeling and forecasting cointegrated relationships among heavy oil and product prices. Energy Econ 27(6):831–848CrossRefGoogle Scholar
  63. Lenoble JP (1993) New scenarios of the world metal markets and the eventual contribution from deep sea mining. In: Proceedings of the 25th Annual Offshore Technology Conference, 3–6 May 1993, OTC 7101, Houston, Texas, USA, pp.197-202Google Scholar
  64. Lenoble J P (2000) A comparison of possible economic returns from mining deep sea polymetallic nodules, polymetallic massive sulphides and cobalt rich ferromanganese crusts. In: ISA (ed) Proceedings of the Workshop on Mineral Resources of the International Seabed Area, Kingston, Jamaica 26–30 June 2000, pp. 1–22Google Scholar
  65. MacKinnon JG (1991) Critical values for cointegration tests, long-run economic relationships. In: Engle RF, Granger CWJ (eds) Long-run economic relationships. Oxford, London, pp 267–276Google Scholar
  66. Martino S, Parson LM (2011) Nodules and crust economics: relationship between cobalt and nickel price. In: Chung JS (ed.) Proceedings of the 9th (2011) ISOPE Ocean Mining Symposium MAUI 19–24. June 2011; pp. 213–220Google Scholar
  67. Martino S, Parson LM (2012) A comparison between manganese nodules and cobalt crust economics in a scenario of mutual exclusivity. Mar Policy 36:790–800CrossRefGoogle Scholar
  68. Marvasti A (1998) An assessment of technology transfer systems and the new law of the sea. Ocean Coast Manag 39:197–210CrossRefGoogle Scholar
  69. Marvasti A (2000) Resource characteristics extraction costs and optimal exploitation of mineral resources. Environ Resour Econ 17:395–408CrossRefGoogle Scholar
  70. Maxwell P (2006) Was there a nickel shakeout? Miner Energy Raw Mater Rep 21(3):42–56CrossRefGoogle Scholar
  71. Murton BJ (2002) A Global review of non-living resources on the extended continental shelf. Braz J Geophys 18(2):281–307Google Scholar
  72. Murton BJ, Parson LM, Hunter PJ, Miles PR (2000) Evaluation of the non-living resources of the continental shelf beyond the 200-mile limit of the world's margins. In: International Seabed Authority (ed) Minerals other than polymetallic nodules of the International Seabed Area, Vol. II. Proceedings of a Workshop held 26–30 June 2000, Kingston, Jamaica, International Seabed Authority, pp. 667–761Google Scholar
  73. Narayan PK (2005) The saving and investment nexus for China: evidence from cointegration tests. Appl Econom 37:1979–1990CrossRefGoogle Scholar
  74. Nazlioglu S, Soytas U (2011) World oil prices and agricultural commodity prices: evidence from an emerging market. Energy Econ 33:488–496CrossRefGoogle Scholar
  75. Ng S, Perron P (1995) Unit root tests in ARMA models with data-dependent methods for the selection of the truncation lag. J Am Stat Assoc 90:268–281CrossRefGoogle Scholar
  76. Papp JF, Bray EL, Edelstein DL, Fenton MD, Guberman DE, Hedrick JB, Jorgenson JD, Kuck PH, Shedd KB, Tolcin AC (2008) Factors that influence the price of Al, Cd, Co, Cu, Fe, Ni, Pb, Rare Earth Elements, and Zn: U.S. Geological Survey Open-File Report 2008–1356, p 61. Available from http://pubs.usgs.gov/of/2008/1356/. Accessed December 2010
  77. Pesaran MH, Shin Y (1999) An autoregressive distributed lag modelling approach to cointegration analysis, In: Storm S, Holly A, Diamond P. (eds) Econometrics and economic theory in the 20th century: the Ragnar Frisch centennial symposium. Cambridge University Press, Cambridge. pp. 371–413Google Scholar
  78. Pesaran MH, Shin Y, Smith RJ (2001) Bounds testing approaches to the analysis of level relationship. J Appl Econom 16:289–326CrossRefGoogle Scholar
  79. Phillips PCB, Perron P (1988) Testing for a unit root in time series regression. Biom 75(2):335–346Google Scholar
  80. Pindyck RS, Rotemberg JJ (1990) The excess co-movement of commodity prices. Econ J 100:1173–1189CrossRefGoogle Scholar
  81. Ouattara B (2004) Foreign aid and fiscal policy in Senegal. The School of Economics Discussion Paper Series 0413, Economics. The University of Manchester. http://ideas.repec.org/e/pou19.html. consulted in May 2011
  82. Rajesh S, Gnanaraj AA, Velmurugan A, Ramesh R, Muthuvel P, Babu MK, Ramesh NR, Deepack CR, Atmanand MA (2011) Qualification tests on underwater mining system with manganese nodule collection and crushing systems, In: Chung JS (ed) Proceeding of the 9th Ocean Mining Symposium, MAUI 19–24 June 2011, pp.110–115Google Scholar
  83. Ridler D, Yandle CA (1972) A simplified method for analysing the effects of exchange rate changes on exports of a primary commodity. IMF Staff Papers XIX: 559–578Google Scholar
  84. Sari R, Hammoudeh S, Soytas U (2010) Dynamics of oil price, precious metal prices and exchange rate. Energy Econ 32:351–362CrossRefGoogle Scholar
  85. Schwarz GE (1978) Estimating the dimension of a model. Ann Stat 6(2):461–464CrossRefGoogle Scholar
  86. Shantini R (2007) Fossil fuel based CO2 emissions, economic growth, and world crude oil price nexus in the United States. MPRA, Munich Personal RePEc Archive. Available from http://mpra.ub.uni-menchen.de/29574. Accessed July 2011
  87. Sims C (1980) Macroeconomics and reality. Econom 48(1):1–48CrossRefGoogle Scholar
  88. Slade ME (1982) Cycles in natural-resource commodity prices: an analysis of the frequency domain. J Environ Econ Manag 9:138–148CrossRefGoogle Scholar
  89. Soreide F, Lund F, Markussen JM (2001) Deep ocean mining reconsidered a study of the manganese nodules deposits in the Cook Islands. In: Proceedings of the Fourth Ocean Mining Symposium Szczecin, Poland, September 23–27, 2001, pp. 88–93Google Scholar
  90. Sorensen PE, Mead W (1968) A cost-benefit analysis of ocean mineral resource development: the case of manganese nodules. Am J Agri Econ 50(5):1611–1620CrossRefGoogle Scholar
  91. Soytas U, Sari R, Hammoudeh S, Hacihasanoglu E (2009) World oil prices, precious metal prices and macroeconomy in Turkey. Energy Policy 37:5557–5566CrossRefGoogle Scholar
  92. Svensson LEO (2006) Comment on Jaffrey Frankel, “Commodity prices and monetary policy. In: Campbell J (ed) Asset prices and monetary policy. University of Chicago Press, ChicagoGoogle Scholar
  93. Svensson LEO (2008) The effect of monetary policy on real commodity prices: comment. In: Campbell JY (ed) Asset prices and monetary policy NBER. University of Chicago, Chicago, pp 291–334, and NBER Working Paper 12713Google Scholar
  94. Tilton JE, Vogely AW (1981) Market instability in the metal industries. Special Issue Mater Soc 5(3)Google Scholar
  95. Tilton JE (1983) The impact of the seabed nodule mining: a qualitative analysis. Laxenburg: International Institute for Applied Systems Analysis, pp. 83–133. Available from www.iiasa.ac.at/Admin/PUB/Documents/RR-83-033.pdf. Accessed September 2011
  96. Tilton JE (1992) Economics of the mineral industries. In: Hatman HL (eds.), Mining Engineering Handbook. Society for Mining, Metallurgy, and Exploration, pp. 47–62Google Scholar
  97. Tilton JE, Lagos G (2007) Assessing the long-run availability of copper. Resour Policy 32:19–23CrossRefGoogle Scholar
  98. Toda HY, Yamamoto T (1995) Statistical inference in vector autoregressions with possibly integrated processes. J Econom 66:225–250CrossRefGoogle Scholar
  99. Xiarchos IM (2005) Steel: Price links between primary and scarp markets. Southern Agricultural Association Annual Meeting, Little rock, Arkansas, 5–9 February, 2005. Available from http://ageconsearch.umn.edu/bitstream/35655/1/sp05xi01.pdf. Accessed September 2011
  100. Xiarchos IM, Fletcher JJ (2009) Price and volatility transmission between primary and scrap metal markets. Resour Conserv Recycl 53:664–673CrossRefGoogle Scholar
  101. Yamazaki T (2002) Development of technical and economical examination method for cobalt rich ferromanganese crusts. In: Proceedings of the twelfth International Offshore and Polar Engineering Conference, Kitalyushu, Japan, May 26–31, 2002, p.454-461Google Scholar
  102. Yamazaki T (2006) Technological issues associated with commercialising cobalt-rich ferromanganese crusts deposits in the Area. In: International Seabed Authority (ed) Proceedings the Workshop on “Mining cobalt-rich ferromanganese crusts and polymetallic sulphides deposits: technological and economic considerations”. Kingston, Jamaica, 31 July–4 August 2006, pp.208–220Google Scholar
  103. Yamazaki T (2008) Model mining units of the 20th century and the economies (production requirements, area requirements and vertical integration). In: ISA (ed) Proceedings of the Technical paper for ISA Workshop on Polymetallic Nodule Mining Technology-Current status and Challenges Ahead. Chennai, India, Feb.18-22,2008, pp. 1–9. Available from http://www.isa.org.jm/files/documents/EN/Workshops/Feb2008/Yamazaki-Abst.pdf
  104. Yoon CH, Park JM, Kang JS, Kim YJ, Park YC, Park SG, Kim C, Kang SS, Kim SB, Kim WT, Kwon SK, Ahn BS, Ha MK (2011) Shallow lifting test for the development of deep ocean mineral resources in Korea, In: Chung JS (eds.), Proceeding of the 9th (2011) ISOPE Ocean Mining Symposium MAUI, 19–24 June 2011, p. 149–152Google Scholar
  105. Zhang YJ, Wei YM (2010) The crude oil market and the gold market: evidence for cointegration causality and price discovery. Resour Policy 35:168–177CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  1. 1.Marine Geoscience GroupNational Oceanography Centre, SouthamptonSouthamptonUK

Personalised recommendations