Econometric modeling of recycled copper supply
Author(s) • •
Fu, Xinkai
Ueland, Stian M.
Olivetti, Elsa A.
Date Issued
March 3, 2017
Journal
Resources, Conservation and Recycling
Publisher
Elsevier
Citation
The supply of recycled material depends on historic consumption, i.e. what constitutes scrap available today originates from previously made products. Analytical tools, such as materials flow analysis, use this observation to estimate scrap metal flows. The supply of recycled metal also depends on changing economic conditions, e.g. metal consumption rates correlate with changes in gross domestic product. We use an autoregressive distributed lag approach to model the supply of recycled copper as a complementary approach to material flow analysis. We find that both industrial activity and world GDP correlate with total scrap supply, with limited dependence on copper price. We also develop independent models for direct remelt (higher quality) and refined (lower quality) scrap. A 1% increase in industrial production leads to a 2.1% increase in higher quality scrap quantity, while a similar increase in world GDP leads to a 1.4% increase in lower quality scrap. Based on this model dependence, we suggest that a recycling policy aimed at increasing recycling through the use of subsidies, taxes or price incentives should be directed towards the low-end segment of the scrap market and there it may still only have limited impact. Keywords:
Copper; Autoregressive distributed lag; Recycling; Scrap; Price elasticity
Version
Author's final manuscript
Abstract
Fu, Xinkai, et al. “Econometric Modeling of Recycled Copper Supply.” Resources, Conservation and Recycling, vol. 122, July 2017, pp. 219–26.
MIT Department
Massachusetts Institute of Technology. Institute for Data, Systems, and Society
Massachusetts Institute of Technology. Department of Materials Science and Engineering
Terms of Use
Creative Commons Attribution-NonCommercial-NoDerivs License
Persistent DSpace Link
DOI of Published Version
https://doi.org/10.1016/j.resconrec.2017.02.012