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IC 
 
 8966 
 
 Bureau of Mines Information Circular/1984 
 
 Nonfuel Mineral Model Directory 
 
 By Staff, Bureau of Mines 
 
 UNITED STATES DEPARTMENT OF THE INTERIOR 
 
Information Circular 8966 
 
 Nonfuel Mineral Model Directory 
 
 By Staff, Bureau of Mines 
 
 UNITED STATES DEPARTMENT OF THE INTERIOR 
 William P. Clark, Secretary 
 
 BUREAU OF MINES 
 Robert C. Horton, Director 
 

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 c\^ 
 
 
 '^ '\^o<K^ 
 
 Library of Congress Cataloging in Publication Data: 
 
 Nonfuel mineral model directory. 
 
 (Information circular / United States Department of the Interior, Bu- 
 reau of Mines ; 8966) 
 
 Includes index. 
 
 Supt. of Docs no.: I 28.27:8966. 
 
 1. Mines and mineral resources— Mathematical models— Directories. 
 I. United States. Bureau of Mines. II. Series: Information circular 
 (United States. Bureau of Mines) ; 8966. 
 
 'TF295.U4 [TN153] 622s [333.8'5'0724] 83-600342 
 
1 
 
 \^ 
 
 /ij CONTENTS 
 
 \ Page 
 
 Abstract 1 
 
 Introduction 2 
 
 Department of the Interior 4 
 
 Cost estimating system 4 
 
 <^ Mine simulation model 5 
 
 pTi Supply analysis model 6 
 
 ^ U.S. mineral end-use demand projection system 7 
 
 \^ World Integrated model 8 
 
 > MIDAS II engineering supply model 9 
 
 ^ Process analysis model of the requirements of the U.S. steel industry for 
 
 alloys , raw materials , energy , and capital 10 
 
 Potash model 11 
 
 Bureau of Mines interindustry input/output model 12 
 
 Political forecasting portion of South and Central Africa study 14 
 
 Engineering-based demand and supply curves for nickel, copper, aluminum, and 
 
 potash 15 
 
 Generic market model 16 
 
 Department of Agriculture 17 
 
 Copper prediction model 17 
 
 Department of Commerce 18 
 
 World copper market model 18 
 
 Office of Commodity Policy world cobalt market model 19 
 
 World tin market model 20 
 
 Federal Emergency Management Agency 21 
 
 National Defense Stockpile Series 21 
 
 Appendix. — Analytical systems versus policy issues by commodity 23 
 
 TABLES 
 
 A-1 . Cobalt 24 
 
 A-2. Chromium 26 
 
 A-3. Manganese 27 
 
 A-4. Platinum-group metals 29 
 
 A-5. Nickel 30 
 
 A-6. Aluminum (metal, alumina, and bauxite) 31 
 
 A-7. Columbium (niobium) -tantalum 32 
 
 A-8 . Iron ore 33 
 
 A-9. Tungsten 34 
 
 A-10. Tin 35 
 
 A-U. Titanium 36 
 
 A-12. Zinc 37 
 
 A-13. Lead 38 
 
 A-14. Copper 39 
 
 Ok 
 
 ^ 
 
NONFUEL MINERAL MODEL DIRECTORY 
 
 By Staff, Bureau of Mines 
 
 ABSTRACT 
 
 This Bureau of Mines report is a compilation of information on comput- 
 er models of mineral commodity markets in the Federal Government. The 
 directory was compiled by the Analytic Systems Working Group of the 
 Interagency Minerals Information Coordinating Committee to support the 
 formulation of policies related to nonfuel minerals. 
 
INTRODUCTION 
 
 The Nonfuel Mineral Model Directory is 
 a product of the Analytic Systems Working 
 Group of the Interagency Minerals In- 
 formation Coordinating Committee. This 
 Committee was established by Presidential 
 Directive on November 4, 1980. The Com- 
 mittee was charged with the responsi- 
 bility of improving the Federal Govern- 
 ment's capability to collect and analyze 
 
 information necessary to support the for- 
 mulation of policies related to nonfuel 
 minerals. One of the tasks of the Com- 
 mittee and its Analytic Systems Working 
 Group was to compile an inventory of all 
 mineral market models in the Federal Gov- 
 ernment. The membership of the Working 
 Group is shown below: 
 
 Nonfuel Mineral Analytic Systems Working Group Members 
 
 Aldo Barsotti, Chairman 
 
 Joe Colosi 
 
 John H. De Young, Jr. 
 
 Jim Gagnon 
 
 Frank Got t shall 
 
 Ed Johnson 
 
 Skip Jones 
 
 Tau Ming 
 
 William Mo 
 
 Ron Smith 
 
 Ted Tupper 
 
 Bureau of Mines 
 
 Central Intelligence Agency 
 
 U.S. Geological Survey 
 
 Department of State 
 
 Federal Emergency Management Agency 
 
 Bureau of Mines 
 
 Department of Commerce 
 
 Department of Agriculture 
 
 Bureau of Mines 
 
 Minerals Management Service 
 
 Bureau of Mines 
 
 The Analytic Systems Working Group of 
 the Interagency Minerals Information Co- 
 ordinating Committee identified many non- 
 fuel mineral analytical systems in par- 
 ticipating Federal agencies that are used 
 for mineral policy analysis. Information 
 on each of these systems , including meth- 
 odology, functional description, and data 
 requirements, was published in 1982, ^ and 
 an updated version was released in 1983.2 
 
 The Analytic Systems Working Group was 
 then given the task of examining the 
 utility of the inventoried analytical 
 systems-^ for mineral policy analysis and 
 making recommendations regarding any 
 needed improvements. 
 
 Because of the diverse methodologies 
 represented by different disciplines in- 
 volved in development and utilization of 
 
 ^Minerals Data Working Group, Inter- 
 agency Minerals Information Coordinating 
 Committee. Minerals Data Source Direc- 
 tory. BuMines IC 8881, 1982, 296 pp. 
 
 2 . Minerals Data Source Direc- 
 tory, January 1983 (An Update of IC 
 8881). BuMines IC 8935, 1983, 376 pp. 
 
 such analytical systems and because of 
 the different uses to which the systems 
 were put , the Working Group did not see 
 any practical or timely way to compare 
 and measure the utility of these differ- 
 ent methodologies. In addition, the de- 
 velopment of a taxonomy of mineral- 
 related policies and policy issues for 
 measuring the utility of each system 
 would have been a formidable task beyond 
 the scope of the Working Group at this 
 time. 
 
 Therefore, to accomplish the required 
 task, the Working Group decided to select 
 15 mineral commodities important to the 
 strategic and economic well-being of the 
 United States and measure the ability of 
 the analytical systems to address policy 
 
 ■^Since the original inventory of ana- 
 lytic systems was completed in December 
 1981, several changes have occurred. The 
 CIA system dynamic world model, the State 
 Department interaction data system, and 
 Interior's LABMOD, lead, and nickel mod- 
 els have been deleted. Interior's Gener- 
 ic Model and engineering-based demand and 
 supply curves have been added. 
 
issues related to these 15 commodities. 
 Each participating agency was asked to 
 identify current policy-related issues 
 affecting the following 15 commodities: 
 
 Cobalt 
 
 Chromium 
 
 Nickel 
 
 Columbium (niobium) 
 
 Iron ore 
 
 Tin 
 
 Zinc 
 
 Copper 
 
 Manganese 
 Platinum-group 
 
 metals 
 Aluminum 
 Tantalum 
 Tungsten 
 Titanium 
 Lead 
 
 Policy issues were identified by each 
 participating agency. Issues specific to 
 the 15 commodities were then consolidated 
 by commodity. (The issues are stated for 
 the most part exactly as they were pre- 
 sented to the committee by the respective 
 agency.) Agencies responsible for each 
 of the analytical systems then examined 
 alt issues and rated their analytical 
 systems. The results of this effort by 
 the Working Group constitute the appendix 
 of this report. 
 
 Overall, the results of this study in- 
 dicate that virtually all of the issues 
 identified could be addressed by at least 
 one of the inventoried analytical sys- 
 tems. In fact, many of the issues apply 
 
 to more than one commodity and were 
 therefore listed repeatedly. Note that 
 many of the current policy issues identi- 
 fied can be readily addressed using sev- 
 eral of the inventoried systems. Other 
 issues cannot be readily addressed with- 
 out major modification of one or more of 
 the systems labeled "c" in the appendix. 
 
 It cannot be stressed too strongly that 
 any underlying assumption in rating these 
 systems against the issues is that the 
 systems are only tools used to address 
 the issue and/or the possible options for 
 resolving that issue and are subject to 
 user interpretation. 
 
 The next step for the Analytical Sys- 
 tems Working Group will be to examine 
 both the results of this study and the 
 procedure applied to accomplish the 
 Groups 's tasks to date, subsequently mak- 
 ing recommendations, if required, on im- 
 proving both. Expansion to include other 
 commodities will also be considered. 
 
 Analytical systems as well as policy 
 issues change with time. Thus, to be ef- 
 fective, an inventory of such systems 
 will be taken periodically by this Work- 
 ing Group with an expanded list of par- 
 ticipating agencies. 
 
DEPARTMENT OF THE INTERIOR 
 
 Cost Estimating System (CES) 
 
 An interactive cost projection tool used to evaluate possible mine plans. 
 
 Model code I-l. 
 
 Status Active. 
 
 Commodities All except fossil fuels, uranium. 
 
 Users Bureau of Mines . 
 
 Contact H. Bennett, Chief, Minerals Availability Field Office, Bureau of 
 
 Mines, Bldg. 20, Denver Federal Center, Denver, CO 80225. Tele- 
 phone: (303) 234-2535. 
 
 Developer Bureau of Mines . 
 
 Policy areas Economic growth. 
 
 Policy description Not available. 
 
 Key words Costing, mine, mill. 
 
 Methodology description. . . . Interactive computerized version of the STRAAM Capital and Operat- 
 ing Cost Estimating Handbook. 
 Time representation: 
 
 Time set Dynamic. 
 
 Descriptive horizon 5 years. 
 
 Predictive horizon Do. 
 
 Start of time period: 
 
 Historical July 1975. 
 
 Predictive Do. 
 
 Discrete Yes; duration of time step; unit of 1 month. 
 
 Geographic representation.. None. 
 
 Geographic description Evaluates 1 property at a time. 
 
 System description: 
 
 Variable relationship.... Deterministic. 
 
 Documentation Yes . 
 
 Computer requirements: 
 
 Language WANG Basic, COBOL. 
 
 Operational mode Interactive. 
 
 Computer WANG VS 100. 
 
 Core requirements 5000 bytes. 
 
 Additional system None, 
 requirements. 
 
 Data base Not available. 
 
 Proprietary No . 
 
 Functional area: 
 
 Resource Exploration. 
 
 Mine Capacity, production, development. 
 
 Mill Do. 
 
 Intermediate Not available 
 
 Primary Do . 
 
Mine Simulation Model (MINSIM) 
 
 A model used for evaluating the economics of mineral deposits. If model is multicommodity and 
 allows for mining, milling, smelting, refining, and leaching operations, it may be used to cal- 
 culate discounted cash flow rate of return (DCFROR) to figure the necessary price to attain a 
 given DCFROR. Also has the capacity to perform Monte Carlo simulation. 
 
 Model code 1-2 . 
 
 Status Active . 
 
 Commodities Any commodity may be analyzed, given sufficient deposit data. 
 
 Users Bureau of Mines , Bureau of Indian Affairs , Bureau of Land Manage- 
 ment , numerous private companies, and foreign governments. 
 
 Contact H. Bennett, Chief, Minerals Availablity Field Office, Bldg. 20, 
 
 Denver Federal Center, Denver, CO 80225. Telephone: (303) 
 234-2535. 
 
 Developer. Bureau of Mines . 
 
 Policy areas Economic growth, public lands, national security, tax, research and 
 
 development, environmental, transportation, energy, manpower. 
 
 Policy description Used for sensitivity analysis on the impact of financial cost, 
 
 inflation, legislation, and departmental considerations on the 
 economics of individual mineral deposits. 
 
 Key words Point estimates, Monte Carlo simulations. 
 
 Methodology description. . . . Uses point estimates of certain data to determine ne present val- 
 ues and DCFROR or determines commodity prices necessary to attain 
 desired DCFROR. 
 Time representation: 
 
 Time set Static. 
 
 Descriptive horizon 80 years. 
 
 Predictive horizon Do. 
 
 Start of time period: 
 
 Historical Year=l. 
 
 Predictive Do. 
 
 Discrete Yes; time steps variable; units in years. 
 
 Geographic representation.. Global, regional, country. State, county, city. 
 
 Geographic description Capable of evaluating a mineral property no matter where it is 
 
 located. 
 System description: 
 
 Variable relationship.... Stochastic, deterministic. 
 
 Documentation Yes . 
 
 Computer requirements: 
 
 Language FORTRAN. 
 
 Operational mode Interactive, batch. 
 
 Computer Burroughs 6800. 
 
 Core requirements 500,000 bytes. 
 
 Additional system None, 
 requirements. 
 
 Data base Do. 
 
 Proprietary No. 
 
 Functional area: 
 
 Resource Exploration. 
 
 Mine Capacity, production, development, price. 
 
 Mill Do. 
 
 Intermediate Production, development, price. 
 
 Primary Do . 
 
Supply Analysis Model (SAM) 
 
 Automatically updates mining, related costs and indices, and tax data, and simultaneously per- 
 forms financial analysis (DCFROR) on multiple properties to obtain the availability of a commod- 
 ity from these properties. 
 
 Model code 1-3. 
 
 Status Active . 
 
 Commodities All nonfuel minerals plus coal; presently includes MAS data for 
 
 analysis of world copper and aluminum and domestic cobalt, chromi- 
 um, alumina, manganese, and phosphate. 
 
 Users Bureau of Mines . 
 
 Contact Ted Tupper, Bureau of Mines, 2401 E St. NW. , Room 816, Washington, 
 
 DC 20241. Telephone: (202) 634-1144. 
 
 Developer Bureau of Mines . 
 
 Policy areas Economic growth, public lands, national security, taxes, prices, 
 
 research and development, health and safety, transportation, ocean 
 resources, energy, and manpower. 
 Policy description System used for sensitivity analysis on the impact of several leg- 
 islative and departmental policy considerations on domestic avail- 
 ability of 23 commodities critical to the United States. 
 
 Key words Point estimates. 
 
 Methodology description. . . . Uses point estimate to determine net present value of individual 
 
 properties. 
 Time representation: 
 
 Time set Dynamic. 
 
 Descriptive horizon 80 years. 
 
 Predictive horizon Do. 
 
 Start of time period: 
 
 Historical Year=l . 
 
 Predictive Do. 
 
 Discrete Yes, time steps variable; unit in years. 
 
 Geographic representation.. Global, regional, country. State, county, city. 
 
 Geographic description Capable of evaluating 1 or more properties. Representation can be 
 
 either a known given deposit location or all properties for a com- 
 modity worldwide. 
 System description: 
 
 Variable relationship.... Deterministic. 
 
 Documentation Yes . 
 
 Computer requirements: 
 
 Language FORTRAN and COBOL. 
 
 Operational mode Interactive, batch. 
 
 Computer Burroughs 6800. 
 
 Core requirements Circa 150 K. 
 
 Additional system CRT or other terminal for interactive question and response mode, 
 requirements. Tecktronix 4014 CRT for graphics and batch output supply curves. 
 
 Data base Minerals Availability System. 
 
 Proprietary Yes . 
 
 Functional area: 
 
 Resource Capacity, production, exploration, development. 
 
 Mine Capacity, production, development. 
 
 Mill Capacity, production, development, price. 
 
 Intermediate Capacity, production, price. 
 
 Primary Do. 
 
U.S. Mineral End-Use Demand Projection System 
 Projects U.S. mineral demand by end use to the year 2000. 
 
 Model code 1-4 . 
 
 Status Active . 
 
 Commodities All nonfuel mineral: 80 mineral chapters covered In Mineral Facts 
 
 and Problems , published qulnquennlally by Bureau of Mines . 
 
 Users Bureau of Mines . 
 
 Contact Barry Klein, Bureau of Mines, 2401 E St., NW. , Room 635, Washing- 
 ton, DC 20241. Telephone: (202) 634-1036. 
 
 Developer Bureau of Mines . 
 
 Policy areas Economic growth. 
 
 Policy description System used for Mineral Facts and Problems (published every 
 
 5 years) and for Mineral Commodity Profiles in the Interim years. 
 
 Keywords U.S. mineral consumption-demand, least-squares regression. 
 
 Methodology description.... Using simple linear regression analysis, this system estimates the 
 
 relationship between historical data of each mineral commodity's 
 end-use consumption and various macroeconomlc indicators, such as 
 GNP, used as explanatory variables. 
 Time representation: 
 
 Time set Static. 
 
 Descriptive horizon 22 years. 
 
 Predictive horizon Do. 
 
 Start of time period: 
 
 Historical 1960. 
 
 Predictive 1982. 
 
 Discrete Yes . 
 
 Geographic representation.. Country. 
 
 Geographic description United States only. 
 
 System description: 
 
 Variable relationship.... Stochastic. 
 
 Documentation Yes . 
 
 Computer requirements: 
 
 Language Model 204 data base management system (dbms). 
 
 Operational mode Interactive. 
 
 Computer ITEL. 
 
 Core requirements 20 cylinders . 
 
 Additional system Terminal for interactive query and on-line updating, 
 requirements. 
 
 Data base U.S. mineral consumption by end use and U.S. macroeconomlc 
 
 indicators. 
 
 Proprietary Yes . 
 
 Functional area: 
 
 Primary Sectoral . 
 
 Secondary Do. 
 
World Integrated Model (WIM) 
 
 WIM is a global model interrelating nine submodels: population, economic, labor-education, 
 aid-loan, trade and pajnnents, materials, energy, food, and machinery. The model uses a dynamic 
 equilibrium approach (supply and demand balance). 
 
 Model code 1-5. 
 
 Status Active. 
 
 Commodities Aluminum, copper, iron, steel, nickel, and zinc. 
 
 Users Bureau of Mines . 
 
 Contact Thomas Witzig, Bureau of Mines, 2401 E. St., NW. , Room 631, Wash- 
 ington, DC. 20241. Telephone: (202) 634-1289. 
 Developer Case Western Reserve University, Cleveland, OH; Progressive Deci- 
 sion, Cleveland, OH. 
 Policy areas Economic growth, national security, stockpile, price, trade, en- 
 ergy, conservation, manpower. 
 
 Policy description The WIM model is a tool for analyzing various policy areas (issues) 
 
 such as those immediately above. Using alternative scenarios the 
 WIM model can interrelate many factors affecting each other on a 
 global basis and it can indicate future trends. 
 
 Keywords Global , scenarios , large-scale model. 
 
 Methodology description. . . . The world integrated model is a computerized simulation model 
 
 developed to serve as an analytical tool in identifying possible 
 occurrences under various alternative scenarios. The basic meth- 
 odology used in the model is a system dynamic approach. 
 Time representation: 
 
 Time set Dynamic. 
 
 Descriptive horizon 30 years. 
 
 Predictive horizon Do. 
 
 Start of time period: 
 
 Historical 1950. 
 
 Predictive 1980. 
 
 Discrete Yes; time steps variable; units in years. 
 
 Geographic representation.. Global. 
 
 Geographic description WIM has 12 basic regions: North America, Western Europe, Pacific 
 
 developed countries (primarily Japan) , the rest of the developed 
 world (including Australia, New Zealand, and South America), East- 
 ern Europe and the Soviet Union, Latin America, Middle East oil 
 producers, non-oil-producing Arab countries, Africa, South Asia, 
 Southeast Asia, and China. The version of WIM the Bureau is re- 
 ceiving divides North America into the United States and Canada 
 and separates the Soviet Union from Eastern Europe. 
 System description: 
 
 Variable relationship.... Deterministic. 
 
 Documentation Yes (partial) . 
 
 Computer requirements: 
 
 Language FORTRAN, PSALM, and Time Share option. 
 
 Operational mode Interactive, batch. 
 
 Computer ITEL. 
 
 Core requirements About 315 K. 
 
 Additional system Terminals for interactive query and graphics capability. 
 
 requirements. 
 Data base For most major countries macroeconomlc indicators (GNP, popula- 
 tion, etc.) and for the minerals identified above, production- 
 consumption, resource-reserve, and price data. 
 
 Proprietary Enhanced version of WIM is proprietary, but the data may not be. 
 
 Functional areas: 
 
 Mine Capacity , production. 
 
 Primary Sectoral . 
 
 Secondary Do. 
 
MIDAS II Engineering Supply Model (MIDAS II) 
 
 The MIDAS II Model is formulated to provide a partial equilibrium of supply and demand for 
 copper on a worldwide basis. 
 
 Model code 1-6 • 
 
 Status Active. 
 
 Commodities Copper. 
 
 User Bureau of Mines . 
 
 Contact Lou Sousa, Bureau of Mines, 2401 E St., NW. , Washington, DC. 20241. 
 
 Telephone: (202) 634-1044. 
 
 Developer W. R. Hibbard, A. L. Soyster, R. S. Gates, Virginia Polytechnical 
 
 Institute and State University. 
 
 Policy areas Economic growth, prices, trade, environmental. 
 
 Policy description Used to determine impact of pollution abatement costs and reduce 
 
 impact of import availability on U.S. copper industry. Also mea- 
 sured variations in DCFROR of domestic producers and low and high 
 demand on copper prices. 
 
 Keywords Linear, disaggregated, partial equilibrium, econometric. 
 
 Methodology description. . . . The model utilizes time dynamic linear equation with log functions 
 
 for partial equilibrium. Portions of both supply and demand are 
 disaggregated. 
 Time representation: 
 
 Time set Dynamic. 
 
 Descriptive horizon 2 years. 
 
 Predictive horizon 21 years. 
 
 Start of time period: 
 
 Historical 1977. 
 
 Predictive 1979. 
 
 Geographic representation.. Global, regional, country. 
 
 Geographic description World copper market with the United States disaggregated by mine by 
 
 ownership (Canada, Chile-Peru, Zambia-Zaire, Oceania, Japan, Eu- 
 rope, and rest of world). 
 System description: 
 
 Variable relationship.... Stochastic. 
 
 Documentation Yes . 
 
 Computer requirements: 
 
 Language Data Fore MPS-3 Proprietary. 
 
 Operational mode Batch. 
 
 Computer IBM 370-158. 
 
 Core requirements 28 X 9000. 
 
 Additional system None, 
 requirements. 
 
 Data base MIDAS II Data. 
 
 Proprietary No . 
 
 Functional areas: 
 
 Resource Capacity. 
 
 Mine Capacity, production. 
 
 Mill Capacity. 
 
 Intermediate Capacity, stockpile. 
 
 Primary Capacity, stockpile, price. 
 
 Secondary Capacity, production. 
 
 Finished good Substitution. 
 
10 
 
 Process Analysis Model of the Requirements of the U.S. Steel Industry 
 for Alloys, Raw Materials, Energy, and Capital 
 
 Engineering and econometric analyses of finished steel (carbon, alloy, stainless, foundry) de- 
 mand by end use and product shape in the United States. Engineering simulation models of steel 
 production processes. Dynamic model of supply-demand and prices over time. 
 
 Model code 1-7. 
 
 Status Active . 
 
 Commodities Iron and steel, chromium, nickel, cobalt, molybdenum, tantalum, and 
 
 tungsten. 
 
 User Bureau of Mines . 
 
 Contact Choon K. Quan, Bureau of Mines, 2401 E St., NW. , Washington, DC 
 
 20241. Telephone: (202) 634-1044. 
 
 Developer Joel P. Clark, Massachusetts Institute of Technology. 
 
 Policy areas Economic growth, national security, stockpile, prices, trade, re- 
 search and development, energy, manpower. 
 
 Policy description This model analyzes future requirements of the U.S. steel industry 
 
 for raw materials, alloys, energy, and capital under a variety of 
 technological and policy options addressed above. 
 
 Keywords Process flow models, demand for steel products, production costs, 
 
 critical materials. 
 Methodology description. . . . Econometric and engineering analyses of demand for iron and steel 
 
 products combined with process flow models of steel production are 
 used to simulate supply-demand and prices over time. 
 
 Geographic description Model only applies to the United States, but can be extended 
 
 globally. 
 System description: 
 
 Variable relationship.... Deterministic. 
 
 Documentation No, but will be available later. 
 
 Computer requirements: 
 
 Language FORTRAN. 
 
 Operational mode Interactive. 
 
 Computer IBM 370. 
 
 Core requirements Large. 
 
 Additional system None, 
 requirements. 
 
 Data base Various. 
 
 Proprietary No . 
 
 Functional areas: 
 
 Resource Capacity, production. 
 
 Primary Capacity, production, sectoral, intersectoral, trade, stockpile, 
 
 substitution, prices. 
 
 Secondary Do . 
 
 Fabricator Capacity, production, sectoral, intersectoral, trade, prices. 
 
 Finished good Do . 
 
11 
 
 Potash Model 
 
 Seven-equation econometric model of potash supply and demand. 
 
 Model code 1-8. 
 
 Status Active. 
 
 Commodities Potash. 
 
 Users Department of the Interior. 
 
 Contact John Bennett, Bureau of Mines, 2401 E St., NW. , Washington, DC 
 
 20241. Telephone: (202) 634-1289. 
 
 Developer John Bennett , Bureau of Mines . 
 
 Policy areas Public lands, tax, prices, trade. 
 
 Policy description Only policies changing production costs, taxes, or availability of 
 
 leases, or restricting trade. 
 
 Keywords. Econometrics. 
 
 Methodology description. . . . The equations in the model were estimated using the regression 
 
 technique of instrumental variables, a form of two-stage least- 
 square regression. The model was then simulated over the period 
 1971-78. 
 Time representation: 
 
 Time set Dynamic . 
 
 Descriptive horizon 1 year. 
 
 Predictive horizon Do. 
 
 Start of time period: 
 
 Historical 1950. 
 
 Predictive 1979. 
 
 Discrete Yes . 
 
 Geographic representation. , Regional. 
 
 Geographic description Centered on North American potash industry. 
 
 System description: 
 
 Variable relationship.... Deterministic. 
 
 Documentation Yes . 
 
 Computer requirements: 
 
 Language FORTRAN. 
 
 Operational mode Batch. 
 
 Computer IBM and N.l.H. 
 
 Additional system None, 
 requirements. 
 
 Proprietary No. 
 
 Functional areas: Resource Production sectoral, trade, price. 
 
12 
 
 Bureau of Mines Interindustry Input/Output Model 
 
 The system Is a modified Leontlef-type Interindustry model constructed with the 1972 U.S. De- 
 partment of Commerce Input/output table. The standard commodlty-by-commodlty U.S. table has 
 been aggregated to 177 sectors: 172 Interindustry sectors, 4 final demand sectors, and the dum- 
 my sector (to account for scrap, used goods, etc.). The Interindustry sectors Include sectors 
 for cobalt, manganese, chromium, and platinum-palladium that are newly Introduced. Eight Inter- 
 Industry sectors are Identified as cobalt-using industries, six for chromlumm, five for manga- 
 nese, and nine for platinum and palladium. 
 
 Model code 1-9. 
 
 Status Active. 
 
 Commodities Cobalt, chromium, manganese, and platinum-palladium. 
 
 Users Division of Minerals Policy and Analysis , Bureau of Mines . 
 
 Contact Betsy Abbe, Bureau of Mines, 2401 E St., NW. , Room 613, Washington, 
 
 DC 20241. Telephone: (202) 634-1047. 
 
 Developer CONSAD Research Corp., Bureau of Mines, Division of Minerals Policy 
 
 and Analysis. 
 
 Policy description Any policies that can be analyzed by the Bureau of Mines mineral 
 
 market models such as strategic stockpile policy, price guarantee 
 program, tax policy on cobalt, etc., and the labor market. The 
 model primary use was to map results from a mineral market model 
 to determine total economy output. It is also a standard inter- 
 industry matrix and can therefore be used In many types of policy 
 studies. 
 
 Key words Input/output . 
 
 Methodology description.... Each year in the forecasting period, given a level of final demand, 
 
 the model estimates consistent levels of total and intermediate 
 outputs and value added (equivalent to GNP) for each sector of the 
 economy. These are the base case solutions against which compari- 
 sons are made when disruption and policy Impacts are measured. 
 The impact of reduced supplies of a mineral group is transmitted 
 to the general economy through the sectors that purchase the min- 
 eral. Sectors that use a given mineral group, therefore, are made 
 exogenous in place of the final demand sectors of traditional 
 input-output models. A reduced supply for a given mineral thus 
 results in a reduced level of input requirements (or purchases) by 
 the miner-using sectors and consequently a lower output, value 
 added, and employment in most of the other sectors. Another ad- 
 justment made in the exogenous sector is the substitution of other 
 goods for the missing mineral. A certain rate of substitution can 
 be specified not only to account for substitution of other goods 
 for the mineral, but also to correct for the fact that the compo- 
 sition of any industrial sector with respect to a single mineral 
 group is less than 100 percent. 
 Time representation: 
 
 Time set Dynamic. 
 
 Predictive horizon 10 years. 
 
 Start of time period: 
 
 Predictive 1981. 
 
 Discrete Yes. 
 
 Duration 1 year. 
 
 Geographic representation.. Country. 
 
 Geographic description United States. 
 
 System description: 
 
 Variable relationship.... Deterministic. 
 
 Documentation Yes. 
 
 Computer requirements: 
 
 Language FORTRAN. 
 
 Operational mode Interactive (CONSAD), batch (NIH). 
 
 Computer PRIME-450 and IBM-370. 
 
 Core requirements lOOOK. 
 
13 
 
 Computer requirements — Con. 
 
 Additional system In that the input/output model was initially developed on the 
 requirements. CONSAD computer system, some modification of the NIH system (par- 
 
 ticularly with respect to updating the coefficient matrix and the 
 "preprocessor" which converts market model consumption variables 
 into dollar values for appropriate input/output industrial sec- 
 tors) will be necessary for additional investigations of cobalt, 
 chromium, and manganese. Since all portions of the input/output 
 investigation pertaining to the platinum-group metals were devel- 
 oped and perfoirmed on the NIH system, further study of platinum- 
 palladium is immediately feasible. 
 
 Data base The commodity-by-commodity technical coefficient matrix developed 
 
 with the Department of Commerce 1972 U.S. Transaction Table. 
 
 Proprietary Yes . 
 
 Functional areas: Intersectoral, trade, substitution. 
 
 Intermediate. 
 
14 
 
 Political Forecasting Portion of South and Central Africa Study 
 
 Uses experts in several areas — political, economic, mineral — to develop possible scenarios for 
 mineral exporting country, consequent events that may disrupt exports, and the specific effects 
 on exports. All data are collected in form of probabilities of probability distributions. 
 
 Model code I-IO. 
 
 Status Inactive . 
 
 Commodities Generalizable to all imported minerals . 
 
 Users U.S. Department of the Interior (DOI). 
 
 Contact Robert Adams, Bureau of Mines, 2401 E St., NW. , Room 621, Washing- 
 ton, DC 20241. Telephone: (202) 634-1293. 
 
 Developer Tom Gunther, Barbara White, Robert Adams of DOI. 
 
 Policy areas Economic growth, public lands, national security, tax, stockpile, 
 
 prices, research and development, ocean resources, conservation. 
 
 Policy description Attempts to incorporate subjective judgment of experts on economic 
 
 and other policy and its results in source countries. Otherwise 
 acts as input to models that evaluate U.S. policy alternatives to 
 reduce the cost or other impacts of a disruption. Generally, any 
 policy that can be represented as a change in a specific aspect of 
 the evaluation model (i.e., econometric) can be analyzed. 
 
 Key words Subjective probability assessment, scenario simulation. 
 
 Methodology description.... Experts subjective probability assessments of scenarios, events, 
 
 disruptions, durations, and amounts disrupted. Rationales for 
 assessments are included in experts' option. Results are used to 
 (1) prepare a country paper summarizing experts' views and (2) 
 provide the data necessary for a Monte Carlo simulation which gen- 
 erates disruptions as inputs to models to evaluate effects on the 
 United States. 
 Time representation: 
 
 Time set Dynamic. 
 
 Start of time period: 
 
 Historical Background knowledge of experts, background papers. 
 
 Predictive Present . 
 
 Discrete Yes . 
 
 Geographic representation.. Global, regional, country. State. Analysis centers on a single 
 
 country at a time, but can take into account regional global in- 
 fluences and formal linkages from one country to others. 
 System description: 
 
 Variable relationship.... Stochastic. 
 
 Documentation Yes, although incomplete as yet. 
 
 Computer requirements: 
 
 Language FORTRAN. 
 
 Operational mode Interactive. Will be changed to batch. 
 
 Computer NIH system — IBM 370-168. 
 
 Core requirements Approximately 300K core. 
 
 Additional system Contractor-developed program is interactive but with no resulting 
 
 requirements. advantages, and utilizes random access methodology, again with no 
 
 advantages. System is unnecessarily cumbersome, and is being re- 
 programmed to remove these features. Major portion of analytical 
 system is panel sessions during which data is collected. This as- 
 pect will remain unchanged. 
 
 Data base Results from panel sessions. 
 
 Proprietary No . 
 
15 
 
 Engineering- Based Demand and Supply Curves for Nickel, Copper, Aluminum, and Potash 
 
 Demand and supply system for the four commodities. Focus is on U.S. demand and the process by 
 which "switching" to substitutes occurs. 
 
 Model code I-ll. 
 
 Status Active. 
 
 Commodities Nickel, copper, aluminum, potash. 
 
 Users Bureau of Mines . 
 
 Contact Jim Gri char. Bureau of Mines, 2401 E St., NW. , Washington, DC 
 
 20241. Telephone: (202) 634-1288. 
 
 Developer A. D. Little, Inc. 
 
 Policy areas Economic growth, national security, stockpile, prices, trade. 
 
 Policy descriptoin Knowledge of switching prices can be used to develop policy options 
 
 for substitute materials. 
 
 Keywords Models, engineering-based, nickel, copper, aluminum, and potash. 
 
 Methodology description.... (1) Develop simple econometric models; (2) revise parameter esti- 
 mates according to engineering Information; (3) test several 
 parameters and revise as necessary, by developing engineering 
 equations. 
 Time representation: 
 
 Time set Dynamic. 
 
 Descriptive horizon 15-25 years. 
 
 Predictive horizon 10 years. 
 
 Start of time period: 
 
 Predictive 1980. 
 
 Discrete Yes. 
 
 Geographic description Focuses on a breakdown of U.S. demand but includes econometric es- 
 timates of supply and demand for the rest of the world. 
 System description: 
 
 Variable relationship.... Stochastic. 
 
 Documentation Yes . 
 
 Computer requirements: 
 
 Language FORTRAN. 
 
 Operational mode Interactive. 
 
 Computer IBM or IBM compatible. 
 
 Functional areas: 
 
 Primary Capacity, production, sectoral, intersectoral, trade, stockpile, 
 
 substitution, price. 
 Secondary Do. 
 
16 
 
 Generic Market Model (CRA) 
 Partial equilibrium — system of world commodity market. 
 
 Model code 1-12. 
 
 Status Active. 
 
 Commodities Cobalt, chromiiim, manganese, platinum (active). (Can be used for 
 
 any commodity with appropriate data and/or equations.) 
 
 Users Bureau of Mines . 
 
 Contact Ted Tupper, Bureau of Mines, 2401 E St., NW. , Room 816, Washington, 
 
 DC 20241. Telephone: (202) 634-1144. 
 
 Developer Department of the Interior and Charles River Associates . 
 
 Policy areas Economic growth, public lands, national security, tax, stockpile, 
 
 prices, trade. 
 
 Policy description This is an econometric model designed to equilibrate world supply 
 
 and demand and can exercise the effect of alternative policy with 
 this framework. 
 
 Keywords Econometric, simultaneous equation, partial equilibrium. 
 
 Methodology description.... Simultaneous equation, partial equilibrium, econometric-engineering 
 
 estimated parameters. 
 Time representation: 
 
 Time set Dynamic. 
 
 Predictive horizon....... Typically 10 to 20 years. 
 
 Start of time period: 
 
 Historical Typically 5 to 10 years. 
 
 Predictive Current period. 
 
 Discrete Yes . 
 
 Geographic representation.. Global, regional, country. 
 
 Geographic description Equations estimated for individual users in each major consuming 
 
 country, and for individual supplying or potentially supplying 
 country (where data available) . 
 System description: 
 
 Variable relationship.... Stochastic. 
 
 Documentation Yes . 
 
 Computer requirements: 
 
 Language FORTRAN. 
 
 Operational mode Batch. 
 
 Computer NIH IBM-3081. 
 
 Core requirements 244K. 
 
 Data base Imbedded, provided with each model. 
 
 Proprietary No. 
 
 Functional areas: 
 
 Intermediate Capacity, production, trade, stockpile. 
 
 Primary Capacity, production, sectoral, stockpile, substitution, price. 
 
 Secondary Capacity, production, price. 
 
 Finished good Capacity, production, sectoral, price. 
 
17 
 
 DEPARTMENT OF AGRICULTURE 
 
 Copper Prediction Model 
 
 Predict copper mining probability in relation to the copper price on special National Forest 
 Land. 
 
 Model code A- 1 . 
 
 Status Active. 
 
 Commodities Copper. 
 
 Users Forest Service, U.S. Department of Agriculture (USDA). 
 
 Contact Tau K. Ming, M&GM Forest Service, USDA, P.O. Box 2417, Washington, 
 
 DC 20013. 
 
 Developer Larry Dale, Forest Service, USDA. 
 
 Policy areas Economic growth, public lands , manpower. 
 
 Policy description Early prediction of copper mining activity on the National Forest 
 
 Lands will enable the U.S. Forest Service to set priorities in 
 managing Forest Service land. 
 
 Keywords System dynamics , probability. 
 
 Methodology description.... Using past copper mining data of entire Nation, local copper depos- 
 it, and copper price to predict the mining probability at a par- 
 ticular location. 
 Time representation: 
 
 Time set Dynamic. 
 
 Descriptive horizon Year. 
 
 Start of time period: 
 
 Historical January 1, 1900. 
 
 Dis Crete No . 
 
 Geographic representation.. State, city. 
 
 Geographic description None. 
 
 System description: 
 
 Variable relationship.... Deterministic. 
 
 Docvimentation Yes . 
 
 Computer requirements: 
 
 Language FORTRAN/Basic. 
 
 Operational mode Interactive, batch. 
 
 Computer Apple III, UNIVAC 111. 
 
 Core requirements 30 bytes . 
 
 Additional system None, 
 requirements . 
 
 Data base None . 
 
 Proprietary No . 
 
 Functional areas: 
 
 Resource Capacity, production, exploration, development. 
 
 Mine Capacity, production, development. 
 
 Mill Development . 
 
18 
 
 DEPARTMENT OF COMMERCE 
 
 World Copper Market Model 
 
 Simultaneous equations system model of world copper market. 
 
 Model code C-1 . 
 
 Status Active. 
 
 Commodities Copper. 
 
 Users Department of Commerce, Office of Commodity Policy (OCP). 
 
 Contact Russell Jones, Office of Commodity Policy, Room 1015, U.S. De- 
 partment of Commerce, Washington, DC 20230. Telephone: (202) 
 377-5124. 
 
 Developer David McNickel, odified by Russell Jones. 
 
 Policy areas Tax, stockpile, prices, trade. 
 
 Policy description Evaluation of buffer stocking mechanisms in world copper market. 
 
 Keywords Simultaneous-equations system, least-square regression. 
 
 Methodology description.... Uses simultaneous-equations system to balance supply, demand, 
 
 stocks, and price. Equations obtained through Ordinary Least 
 Squares. 
 Time representation: 
 
 Descriptive horizon 23 years. 
 
 Start of time period: 
 
 Historical 1954-76, 
 
 Discrete Yes. 
 
 Geographic representation.. Global, country. 
 
 Geographic description World copper market model with equations for major producing and 
 
 consuming countries. 
 System description: 
 
 Variable relationship.... Deterministic. 
 
 Documentation Yes (limited). 
 
 Computer requirements: 
 
 Language DRI/EPS. 
 
 Operational mode. Interactive. 
 
 Computer Burroughs 7800. 
 
 Core requirements Unknown. 
 
 Data base Self-contained. 
 
 Proprietary No. 
 
 Functional areas: 
 
 Resource Production, sectoral, intersectoral, trade, stockpile, price. 
 
 Mine Do . 
 
19 
 
 Office of Commodity Policy World Cobalt Market Model 
 
 Simultaneous-equations supply-demand balance model of world cobalt market, based on 1960-79 
 period. Contains behavioral equations for U.S. and rest-of-world consumption, price, and supply 
 from Zaire, Zambia, Canada, Australia, and the Philippines. 
 
 Model code C-2. 
 
 Status Active. 
 
 Commodities Cobalt. 
 
 Users Department of Commerce, Office of Commodity Policy (OCP). 
 
 Contact Russell Jones, Office of Commodity Policy, Room 1015, U.S. De- 
 partment of Commerce, Washington, DC 20230. Telephone: (202) 
 377-5124. 
 
 Developer Russell Jones, Office of Commodity Policy. 
 
 Policy areas Tax, stockpile, prices, trade. 
 
 Policy description Have examined impact of excise taxes, domestic production, in- 
 creased private stockholding, and stockpile releases on the cobalt 
 market. 
 
 Keywords Simultaneous equation , supply-demand balance , leas t-square regres- 
 
 sions. 
 
 Methodology description.... Uses simultaneous-equations system to balance supply, demand, 
 
 stocks, and price. Equations obtained through OLS. 
 Time representation: 
 
 Time set Dynamic. 
 
 Descriptive horizon 20 years. 
 
 Predictive horizon Do. 
 
 Start of time period: 
 
 Historical 1960-79. 
 
 Predictive 1980-2000. 
 
 Discrete Yes. 
 
 Geographic representation.. Global, country. 
 
 Geographic description World cobalt market with special emphasis on U.S. market. 
 
 System description: 
 
 Variable relationship.... Deterministic. 
 
 Documentation No. 
 
 Computer requirements: 
 
 Language DRl/EPS. 
 
 Operational mode Interactive. 
 
 Computer Burroughs 7800. 
 
 Core requirements Unknown. 
 
 Data base Self-contained DRI/USCENTRAL and OCP-conq)lle cobalt statistic. 
 
 Proprietary No . 
 
 Functional areas: 
 
 Resource Production, sectoral, intersectoral, stockpile, price. 
 
 Mine Do. 
 
 Primary Production, sectoral, intersectoral. 
 
 Secondary Sectoral, intersectoral. 
 
20 
 
 World Tin Market Model 
 
 Simultaneous equations system model of world tin market. 
 
 Model code C-3 . 
 
 Status Active . 
 
 Commodities Tin. 
 
 Users Department of Commerce, Office of Commodity Policy (OCP), 
 
 Contact Russell Jones, Office of Commodity Policy, Room 1015, U.S. De- 
 partment of Commerce, Washington, DC 20230. Telephone: (202) 
 377-5124. 
 
 Developer Warton Econometric Forecasting Associates Inc., Philadelphia, 
 
 PA 19104, modified by Russell Jones. 
 
 Policy areas Tax, stockpile, prices, trade. 
 
 Policy description Evaluation of market stabilization mechanisms and producer country 
 
 tax policies and export controls. 
 
 Keywords Simultaneous-equations system. 
 
 Methodology description.... Uses simultaneous-equations system to balance supply, demand, 
 
 stocks, and price. 
 Time representation: 
 
 Time set Dynamic. 
 
 Descriptive horizon...... 22 years. 
 
 Predictive horizon Do. 
 
 Start of time period: 
 
 Descriptive 1956-77. 
 
 Discrete Yes . 
 
 Geographic representation.. Global, country. 
 
 Geographic description World tin market with equations for major producing and consuming 
 
 countries. 
 System description: 
 
 Variable relationship.... Deterministic. 
 
 Documentation Yes (limited). 
 
 Computer requirements: 
 
 Language DRI/EPS. 
 
 Operational mode Interactive. 
 
 Computer Burroughs 7800. 
 
 Core requirements Unknown. 
 
 Data base Self-contained. 
 
 Proprietary No. 
 
 Functional areas: 
 
 Resource Production, sectoral, intersectoral, stockpile, price. 
 
 Mine Do. 
 
 Primary Do. 
 
21 
 FEDERAL EMERGENCY MANAGEMENT AGENCY 
 
 National Defense Stockpile Series of Models Used To Devise Wartime Stockpile 
 Requirements (D) , Supply (S), and Goals (G)" 
 
 All countries' 93-commodity supply discounted by war zone, political reliability, and trans- 
 portation losses. Macroeconomic Chase Econometric model, linked to materials-oriented input- 
 output (I/O) by demand impact transformation "bridge" table (DITT). I/O gross output trans- 
 formed into materials demand by materials-gross output sector regressions materials consumption 
 ratio (MCR). 
 
 Model code F-1. 
 
 Status Active. 
 
 Commodities All 93 stockpile critical materials. 
 
 Users Federal Emergency Management Agency, National Preparedness Program, 
 
 Office of Resource Preparedness, Natural Resource Division. 
 
 Contact Douglas P. Scott, Federal Emergency Management Agency, Donahue 
 
 Bldg. , Room 617, 500 C St., SW. , Washington, DC 20472. Telephone: 
 (202) 357-0014. 
 
 Developer Edward K. Zabrowski, Paul K. Krueger, Douglas P. Scott. 
 
 Policy areas Economic growth, stockpile. 
 
 Policy description To determine stockpile goals (demand-supply existing stockpile in- 
 ventories, I) from war scenarios and war planning imports, which 
 drive the macroeconomic model. Variable risk policy choices for 
 defense, essential civilian, and basic industrial tiers (T) , on 
 coBamodity demand and supply planning factors. 
 
 Keywords Material consumption ratio (MCR) , demand impact transformation 
 
 "bridge" table (DITT), macroeconommic war mobilization, stockpile, 
 input-output (I/O) requirements. 
 
 Methodology description.... d""" = materials^ x MCR^ x (I-A)"' x — — x F (war inputs, DOD, NSC). 
 
 ST 
 
 Substitution 
 matrix 
 
 (war zone) x (transportation losses)^ 
 reliability)''' x (U.S. market share)''" > 
 production estimate) . 
 
 ! (political 
 (interior country 
 
 qT = j)T _ gT _ jT- ' ; t''' = T'''" ' - G''' 
 
 (economy divided into three priority tiers for war) . 
 
 Time representation: 
 
 Time set Dynamic. 
 
 Descriptive horizon 1980-81. 
 
 Predictive horizon 1982-84. 
 
 Start of time period: 
 
 Historical 1980. 
 
 Predictive 1982. 
 
 Discrete No. 
 
 Geographic representation.. Country. 
 
 Geographic description All 93 commodities' wartime production estimates for 141 coun- 
 tries — business as usual and full capacity — primary and secondary 
 minerals production. 
 System description: 
 
 Variable relationship.... Stochastic. 
 
 Documentation Yes and No (partial — some are classified) . 
 
 Computer requirements: 
 
 Language Basic. 
 
 Operational mode Batch. 
 
 Computer UNIVAC 1108. 
 
 Core requirements 32K. 
 
 Additional system Matrix arithmetic programming systems (MAPS), 
 requirements . 
 
22 
 
 Computer requirements — Con. 
 
 Data base 1960-78 material consumption by end use sector supply, 141 coun- 
 tries and 93 materials of primary and secondary production. 
 
 Proprietary Yes. 
 
 Functional areas: 
 
 Resource Capacity, production, sectoral, intersectoral, trade, stockpile, 
 
 substitution. 
 
 Primary Do. 
 
 Secondary Capacity, production, trade. 
 
 Fabricator Capacity , production. 
 
 Finished good Capacity, production, sectoral, intersectoral, trade, substitution, 
 
 price. 
 
23 
 
 APPENDIX. —ANALYTICAL SYSTEMS VERSUS POLICY ISSUES BY COMMODITY 
 
 RATING GUIDE 
 
 Each agency examined issues and rated its analytical systems in the following manner: 
 
 a = Primary application — the system is readily capable of addressing the specific 
 issue without any modifications. 
 
 b = Easily adaptable — with minor modifications the system could address the spe- 
 cific policy issue. 
 
 c = Potentially adaptable — significant modification would be required to make the 
 system usable for addressing the issue. 
 
 - = Not adaptable — the system could not be modified to address the issue. 
 
 An asterisk (*) placed next to the rating value indicated that new data or an update 
 of existing data would be required. 
 
 NONFUEL MINERAL MARKET MODEL CODES 
 
 Code 
 Interior: 
 
 Cost estimating system I-l 
 
 Mine simulation model 1-2 
 
 Supply analysis model 1-3 
 
 U.S. mineral end-use demand projection system 1-4 
 
 World integrated model 1-5 
 
 MIDAS II engineering supply model 1-6 
 
 Process analysis of the requirements of the U.S. steel industry for alloys, 
 
 raw materials, energy, and capital 1-7 
 
 Potash model 1-8 
 
 Bureau of Mines interindustry input-output model 1-9 
 
 Political forecasting portion of South and Central Africa study I-IO 
 
 Engineering-based demand and supply curves I- 1 1 
 
 Generic market model 1-12 
 
 Agriculture: Copper prediction model A-1 
 
 Commerce: 
 
 World copper market model C-1 
 
 World cobalt market model C-2 
 
 World tin market model C-3 
 
 FEMA: National Defense Stockpile Services F-1 
 
24 
 
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