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Projections and forecasts of U.S. mineral demand by the U.S. Bureau of Mines.

Public Domain


Details

  • Personal Author:
  • Description:
    The Bureau of Mines forecasting system consists of statistical and contingency analyses. Ordinary least-squares regression analysis is the statistical technique used to obtain U.S. demand projections for mineral commodities by end use categories in the year 2000. The year 2000 projections for the independent or explanatory variables used in these linear regressions are based on the Data Resources, Inc., macroeconomic model that forecasts gross national product and detailed federal reserve board industrial production indexes. Among the resulting regression lines that best explains the variation in the dependent variable is the one that is chosen and its associated end use projection in 2000 is published in the Bureau's mineral commodity profile series. The other important component of the Bureau of Mines forecasting system is contingency forecasting that takes into account the judgmental factors. The effects on demand from such factors as technological advances, environmental issues, government policies and regulations, and consumer tastes are considered. [Description provided by NIOSH]
  • Subjects:
  • Series:
    Mining Publications
  • Document Type:
    Text
  • Genre:
  • Place as Subject:
  • CIO:
    National Institute for Occupational Safety and Health (NIOSH)
  • Division:
    WO - Washington Office
  • Topic:
    Workplace Safety & Health
  • Location:
    North America
  • Pages in Document:
    69-71
  • NIOSHTIC Number:
    nn:10008454
  • Citation:
    Proc 109th AIME Ann Meeting Las Vegas Nev 1980 Feb; :69-71
  • Federal Fiscal Year:
    1980
  • Peer Reviewed:
    False
  • Source Full Name:
    Proc. 109th AIME Ann. Meeting, Las Vegas, Nevada, Feb. 24-29, 1980
  • Collection(s):
  • Main Document Checksum:
    urn:sha-512:7dc847c09aedf140bc731323e8446b4703641ae07d6ad9e7b7238120dab30b8f7dcaa9b938d34d035f87873a0fe7fec262d5d13dcaf290925445e82b6de3b57d
  • Download URL:
  • File Type:
    Filetype[PDF - 168.02 KB ]
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