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Non-renewable resource extraction over the long term: empirical evidence from global copper production

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  • Martin Stuermer

    (International Monetary Fund, Research Department)

Abstract

Global mine production of copper has risen more than 80 times over the last 135 years. What were the main drivers? I examine this question based on copper market data from 1880 to 2020. I employ a structural time series model with sign restrictions to identify demand and supply shocks. I find that a deterministic trend drives most of the output growth. At the same time, unpredictable demand and supply shocks caused substantial fluctuations around the trend. A global commodity demand shock that is, for example, linked to a 3% unexpected expansion of the global economy due to rapid industrialization causes a 10% rise in the real copper price, incentivizing a 5% increase in global copper production. This provides empirical evidence for the feedback control cycle of mineral supply.

Suggested Citation

  • Martin Stuermer, 2022. "Non-renewable resource extraction over the long term: empirical evidence from global copper production," Mineral Economics, Springer;Raw Materials Group (RMG);Luleå University of Technology, vol. 35(3), pages 617-625, December.
    • Handle: RePEc:spr:minecn:v:35:y:2022:i:3:d:10.1007_s13563-022-00352-0
    DOI: 10.1007/s13563-022-00352-0
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    1. Martin L. Weitzman, 1999. "Pricing the Limits to Growth from Minerals Depletion," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 114(2), pages 691-706.
    2. Uhlig, Harald, 2005. "What are the effects of monetary policy on output? Results from an agnostic identification procedure," Journal of Monetary Economics, Elsevier, vol. 52(2), pages 381-419, March.
    3. David S. Jacks & Martin Stuermer, 2021. "Dry bulk shipping and the evolution of maritime transport costs, 1850–2020," Australian Economic History Review, Economic History Society of Australia and New Zealand, vol. 61(2), pages 204-227, July.
    4. Stuermer, Martin, 2018. "150 Years Of Boom And Bust: What Drives Mineral Commodity Prices?," Macroeconomic Dynamics, Cambridge University Press, vol. 22(3), pages 702-717, April.
    5. Christiane Baumeister & Gert Peersman, 2013. "The Role Of Time‐Varying Price Elasticities In Accounting For Volatility Changes In The Crude Oil Market," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 28(7), pages 1087-1109, November.
    6. Juan F. Rubio-Ramírez & Daniel F. Waggoner & Tao Zha, 2010. "Structural Vector Autoregressions: Theory of Identification and Algorithms for Inference," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 77(2), pages 665-696.
    7. Juan Antolín-Díaz & Juan F. Rubio-Ramírez, 2018. "Narrative Sign Restrictions for SVARs," American Economic Review, American Economic Association, vol. 108(10), pages 2802-2829, October.
    8. Daniel F. Waggoner & Tao Zha, 1999. "Conditional Forecasts In Dynamic Multivariate Models," The Review of Economics and Statistics, MIT Press, vol. 81(4), pages 639-651, November.
    9. Atsushi Inoue & Lutz Kilian, 2020. "The Role of the Prior in Estimating VAR Models with Sign Restrictions," Working Papers 2030, Federal Reserve Bank of Dallas.
    10. Baumeister, Christiane & Hamilton, James D., 2020. "Drawing conclusions from structural vector autoregressions identified on the basis of sign restrictions," Journal of International Money and Finance, Elsevier, vol. 109(C).
    11. Lukas Boer & Andrea Pescatori & Martin Stuermer, 2021. "Energy Transition Metals," Discussion Papers of DIW Berlin 1976, DIW Berlin, German Institute for Economic Research.
    12. Stuermer, Martin, 2017. "Industrialization and the demand for mineral commodities," Journal of International Money and Finance, Elsevier, vol. 76(C), pages 16-27.
    13. Canova, Fabio & Nicolo, Gianni De, 2002. "Monetary disturbances matter for business fluctuations in the G-7," Journal of Monetary Economics, Elsevier, vol. 49(6), pages 1131-1159, September.
    14. Domenico Giannone & Michele Lenza & Giorgio E. Primiceri, 2015. "Prior Selection for Vector Autoregressions," The Review of Economics and Statistics, MIT Press, vol. 97(2), pages 436-451, May.
    15. Juan Antolin-Diaz & Juan F. Rubio-Ramirez, 2016. "Narrative Sign Restrictions for SVARs," FRB Atlanta Working Paper 2016-16, Federal Reserve Bank of Atlanta.
    16. Lutz Kilian, 2009. "Not All Oil Price Shocks Are Alike: Disentangling Demand and Supply Shocks in the Crude Oil Market," American Economic Review, American Economic Association, vol. 99(3), pages 1053-1069, June.
    17. Faust, Jon, 1998. "The robustness of identified VAR conclusions about money," Carnegie-Rochester Conference Series on Public Policy, Elsevier, vol. 49(1), pages 207-244, December.
    18. Mark W. Watson, 2019. "Comment on "On the Empirical (Ir)relevance of the Zero Lower Bound Constraint"," NBER Chapters, in: NBER Macroeconomics Annual 2019, volume 34, pages 182-193, National Bureau of Economic Research, Inc.
    19. Christiane Baumeister & James D. Hamilton, 2019. "Structural Interpretation of Vector Autoregressions with Incomplete Identification: Revisiting the Role of Oil Supply and Demand Shocks," American Economic Review, American Economic Association, vol. 109(5), pages 1873-1910, May.
    20. Christiane Baumeister & James D. Hamilton, 2015. "Sign Restrictions, Structural Vector Autoregressions, and Useful Prior Information," Econometrica, Econometric Society, vol. 83(5), pages 1963-1999, September.
    21. Harold Hotelling, 1931. "The Economics of Exhaustible Resources," Journal of Political Economy, University of Chicago Press, vol. 39, pages 137-137.
    22. Lutz Kilian & Daniel P. Murphy, 2014. "The Role Of Inventories And Speculative Trading In The Global Market For Crude Oil," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 29(3), pages 454-478, April.
    23. Antolín-Díaz, Juan & Petrella, Ivan & Rubio-Ramírez, Juan F., 2021. "Structural scenario analysis with SVARs," Journal of Monetary Economics, Elsevier, vol. 117(C), pages 798-815.
    24. Jacks, David S. & Stuermer, Martin, 2020. "What drives commodity price booms and busts?," Energy Economics, Elsevier, vol. 85(C).
    25. William D. Nordhaus, 1992. "Lethal Model 2: The Limits to Growth Revisited," Brookings Papers on Economic Activity, Economic Studies Program, The Brookings Institution, vol. 23(2), pages 1-60.
    26. Rausser, Gordon & Stuermer, Martin, 2020. "A Dynamic Analysis of Collusive Action: The Case of the World Copper Market, 1882-2016," MPRA Paper 104708, University Library of Munich, Germany.
    27. Kilian,Lutz & Lütkepohl,Helmut, 2018. "Structural Vector Autoregressive Analysis," Cambridge Books, Cambridge University Press, number 9781107196575.
    28. Partha Dasgupta & Geoffrey Heal, 1974. "The Optimal Depletion of Exhaustible Resources," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 41(5), pages 3-28.
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    More about this item

    Keywords

    Structural vector autoregression; Copper production; Non-renewable resources; Metals;
    All these keywords.

    JEL classification:

    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • N5 - Economic History - - Agriculture, Natural Resources, Environment and Extractive Industries
    • N50 - Economic History - - Agriculture, Natural Resources, Environment and Extractive Industries - - - General, International, or Comparative
    • Q31 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Nonrenewable Resources and Conservation - - - Demand and Supply; Prices
    • Q33 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Nonrenewable Resources and Conservation - - - Resource Booms (Dutch Disease)

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