Long-Run Demand Forecasting for Nonfuel Mineral Commodities

David J. Moore, John E. Tilton and Michael R. Walls

No 396230, USDA Miscellaneous from United States Department of Agriculture

Abstract: Purpose and Scope: In the past, experts have produced these long-run demand forecasts for nonfuel mineral commodities on the basis of their subjective judgment. The underlying causal relationships governing the growth in demand were not identified, and no statistical techniques were used. The U.S. Forest Service, believing a more rigorous approach was needed, asked the Colorado School of Mines and specifically the authors of this report to develop an alternative forecasting methodology based on the intensity of metal use technique and to apply the proposed methodology to two mineral commodities. The two commodities examined are copper, a widely used metal, and sand and gravel, a non-metallic mineral product used largely in the construction sector. For each, conditional forecasts are developed for U.S. demand for the years 2020 and 2050. These forecasts are conditional in the sense that they take as given forecasts for U.S. gross domestic product (GDP) for these two years, which the U.S. Forest Service plans to obtain from independent macroeconomic forecasting services.

Keywords: Demand and Price Analysis; Research Research Methods/Statistical Methods; Resource/Energy Economics and Policy (search for similar items in EconPapers)
Pages: 55
Date: 1996-07
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
https://ageconsearch.umn.edu/record/396230/files/D ... rals-CSM-FS-1996.pdf (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:ags:usdami:396230

DOI: 10.22004/ag.econ.396230

Access Statistics for this paper

More papers in USDA Miscellaneous from United States Department of Agriculture
Bibliographic data for series maintained by AgEcon Search ().