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Explanatory Variables for per Capita Stocks and Flows of Copper and Zinc

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  • Claudia R. Binder
  • T. E. Graedel
  • Barbara Reck

Abstract

A number of potential explanatory variables for the stocks and flows of copper and zinc in contemporary technological societies are co‐analyzed with the tools of exploratory data analysis. A one‐year analysis (circa 1994) is performed for 50 countries that comprise essentially all anthropogenic stocks and flows of the two metals. The results show that (1) The key explanatory variable for metal use is gross domestic product (GDP) per capita (purchasing power parity, PPP). By itself, GDP explains between one‐third and one‐half of the variance of per capita copper and zinc use. Other variables that were significantly correlated with copper and zinc use included stock of passenger cars and television sets (per 1, 000 people); two infrastructure variables, wired telephone connections, urban population, and value added inmanufacturing. The results do not provide evidence supporting the Kuznets curve hypothesis for these metals. (2) Metal use per capita can be estimated using multiple regression equations. For copper, the natural logarithm of use is related to the explanatory variables GDP (PPP), value added in manufacturing, and urban population. This model explains 80% of the variance among the different countries (r2= 0.79). The natural logarithm of zinc use is related to GDP (PPP) and value added in manufacturing with an r2 of 0.75; (3) For both metals, rates of metal fabrication, use, net addition to stock, and discard in low‐and high‐income countries differ significantly from each other. Our statistical analyses thus provide a basis for estimating the potential development of metal use, net addition to stock, and discard, using data on explanatory variables that are available at the international level.

Suggested Citation

  • Claudia R. Binder & T. E. Graedel & Barbara Reck, 2006. "Explanatory Variables for per Capita Stocks and Flows of Copper and Zinc," Journal of Industrial Ecology, Yale University, vol. 10(1‐2), pages 111-132, January.
    • Handle: RePEc:bla:inecol:v:10:y:2006:i:1-2:p:111-132
    DOI: 10.1162/108819806775545475
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    1. McMillan, Colin A. & Moore, Michael R. & Keoleian, Gregory A. & Bulkley, Jonathan W., 2010. "Quantifying U.S. aluminum in-use stocks and their relationship with economic output," Ecological Economics, Elsevier, vol. 69(12), pages 2606-2613, October.
    2. Yue, Qiang & Wang, Heming & Gao, Chengkang & Du, Tao & Li, Mingjun & Lu, Zhongwu, 2016. "Analysis of iron in-use stocks in China," Resources Policy, Elsevier, vol. 49(C), pages 315-322.
    3. Song, Yi & Cheng, Jinhua & Zhang, Yijun & Dai, Tao & Huang, Jianbai, 2021. "Direct and indirect effects of heterogeneous technical change on metal consumption intensity: Evidence from G7 and BRICS countries," Resources Policy, Elsevier, vol. 71(C).
    4. Renaud, Karine M. & Manley, Ross & Nassar, Nedal T., 2023. "A comparison of copper use in China and India as a proxy for their economic development," Resources Policy, Elsevier, vol. 80(C).
    5. Nilza Rivera & Juan Ignacio Guzmán & Gustavo Lagos, 2023. "A method to estimate the robustness of the secondary refined copper supply function," Mineral Economics, Springer;Raw Materials Group (RMG);Luleå University of Technology, vol. 36(2), pages 255-277, June.
    6. Hunt, C. & Romero, J. & Jara, J. & Lagos, G., 2021. "Copper demand forecasts and predictions of future scarcity," Resources Policy, Elsevier, vol. 73(C).
    7. Fu, Xinkai & Ueland, Stian M. & Olivetti, Elsa, 2017. "Econometric modeling of recycled copper supply," Resources, Conservation & Recycling, Elsevier, vol. 122(C), pages 219-226.
    8. Shammugam, Shivenes & Rathgeber, Andreas & Schlegl, Thomas, 2019. "Causality between metal prices: Is joint consumption a more important determinant than joint production of main and by-product metals?," Resources Policy, Elsevier, vol. 61(C), pages 49-66.
    9. Elshkaki, Ayman & Reck, Barbara K. & Graedel, T.E., 2017. "Anthropogenic nickel supply, demand, and associated energy and water use," Resources, Conservation & Recycling, Elsevier, vol. 125(C), pages 300-307.
    10. Sourabh, Shalinee & Pavithran, Sagar & Menon, Balagopal G. & Mahanty, Biswajit, 2023. "Econometric modeling for the influence of economic variables on secondary copper production in India," Resources Policy, Elsevier, vol. 86(PB).

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