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North American Pulp & Paper Model (NAPAP)

  • Peter J. Ince
  • Joseph Buongiorno
Part of the Managing Forest Ecosystems book series (MAFE, volume 14)

This chapter describes the development and structure of the NAPAP model and compares it to other forest sector models. The NAPAP model was based on PELPS and adapted to describe paper and paperboard product demand, pulpwood and recovered paper supply, and production capacity and technology, with spatially dynamic market equilibria. We describe how the model predicts paper and paperboard product demands and trade flows over time, concurrently with regional capacity changes and corresponding shifts in process technology based on Tobin’s q theory of capital investment. We describe how the model was tested and calibrated and then provide examples of applications.

Keywords

Wood Pulp Spot Market Paper Model Forest Sector Paper Sector 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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References

  1. Abe M (1973) Dynamic microeconomic models of production, investment, and technological change of the United States and Japanese iron and steel industries. In: Judge GG, Takayama T (eds) Studies in economic planning over space and time. North-Holland, Amsterdam, pp189-196Google Scholar
  2. Adams DM, Haynes RW (1980) The 1980 softwood timber assessment market model: structure, projections, and policy simulation. Forest Sci Mono 22Google Scholar
  3. Adams DM, Haynes RW (1996) The 1993 timber assessment market model: structure, projections and policy simulations. Gen Tech Rep PNW-368. USDA Forest Service, Pacific Northwest Research Station, Portland, ORGoogle Scholar
  4. American Forest & Paper Association [AF&PA] (1993-2006) Statistics of paper, paperboard and wood pulp, Washington DC, 1993-2006 issues [previously API]Google Scholar
  5. American Paper Institute [API] (1970-1992) Statistics of paper, paperboard and wood pulp, API, New York, 1970-1992 issues [later issues by AF&PA]Google Scholar
  6. Berard P (1977) The changing structure of the paper industry. Translated by RAF Whitbread. Presses Universitaires De Grenoble, Grenoble, FranceGoogle Scholar
  7. Buongiorno J (1981) Outline of a world model of the pulp and paper industry. Paper presented at the meeting on the Analysis of World Trade in Forest Products, International Institute for Applied Systems Analysis, Laxenburg, Austria, 2-4 June 1981Google Scholar
  8. Buongiorno J (1996) Forest sector modeling: a synthesis of econometrics, mathematical programming, and systems dynamics methods. Int J Forecasting 12: 329-343 CrossRefGoogle Scholar
  9. Buongiorno J, Gilless JK (1983a) A model of international trade of forest products (GTM-1). Working Pap WP-83-63, International Institute for Applied Systems Analysis, Laxenburg, AustriaGoogle Scholar
  10. Buongiorno J, Gilless JK (1983b) Concepts used in a regionalized model of pulp and paper production and trade. In: Seppala R, Row C, Morgan A (eds) Forest sector models. AB Academic, Berkhamsted, UK, pp57-90Google Scholar
  11. Buongiorno J, Gilless JK (1984) A model of international trade of forest products, with an application to newsprint. J World Forest Resour Manage 1(1):65-80Google Scholar
  12. Buongiorno J, Zhu S, Zhang D, Turner J, Tomberlin D (2003) The global forest products model: structure, estimation, and applications. Academic Press, San Diego, CAGoogle Scholar
  13. Calmels P, Buongiorno J, Zhang D (1990) PELPS II: a microcomputer priceendogenous linear programming system for economic modeling. Rep R3477. University of Wisconsin-Madison, College of Agric and Life Sciences, Madison, WIGoogle Scholar
  14. Canadian Pulp and Paper Association [CPPA] (1992) Reference tables, 46th edn. Canadian Pulp and Paper Association, Montreal, QuebecGoogle Scholar
  15. Day RH (1973) Recursive programming models: a brief introduction. In: Judge GG, Takayama T (eds) Studies in economic planning over space and time: contributions to economic analysis. American Elsevier, New York, pp 329-344Google Scholar
  16. Duloy JH, Norton RD (1975) Prices and incomes in linear programming models. Am J Agr Econ 57(4):591-600CrossRefGoogle Scholar
  17. Forest Resources Association (2006) Annual pulpwood statistics summary report 2001-2005 (and earlier editions). Forest Resources Association, Rockville, MDGoogle Scholar
  18. Forrester JW (1980) Information sources for modeling the National economy. J Am Stat Assoc 75(371):555-574CrossRefGoogle Scholar
  19. Fox KA (1953) A spatial equilibrium model of the livestock feed economy in the United States. Econometrica 21(4):547-566CrossRefGoogle Scholar
  20. Gilless JK (1983) A model of the pulp and paper sector. Ph.D. dissertation, University of Wisconsin, Madison, WIGoogle Scholar
  21. Gilless JK, Buongiorno J (1985) PELPS: price endogenous linear programming system for economic modeling. Rep R3329. University of Wisconsin-Madison, College of Agriculture and Life Sciences, Madison, WIGoogle Scholar
  22. Gilless JK, Buongiorno J (1987) PAPYRUS: a model of the North American pulp and paper industry. For Sci Mono 28, Supplement to Forest Sci 33(1), Society of American Foresters, Bethesda, MDGoogle Scholar
  23. Gold B (1977) Research, technological change, and economic analysis. Lexington Books, Lexington, MAGoogle Scholar
  24. Guthrie JA (1972) An economic analysis of the pulp and paper industry. Washington State University Press, Pullman, WAGoogle Scholar
  25. Hair D (1967) Use of regression equations for projecting trends in demand for paper and board. Forest Resour Rep 18, GPO, Washington DCGoogle Scholar
  26. Haynes RW (1989) Effects of waste paper recycling on the forest sector. Resour Recycling 8(7):44-46Google Scholar
  27. Haynes RW (coord) (1990) An analysis of the timber situation in the United States: 1989-2040. Gen Tech Rep RM-199. USDA Forest Service, Rocky Mountain Forest and Range Experiment Station, Fort Collins, COGoogle Scholar
  28. Haynes RW (tech coord) (2003) An analysis of the timber situation in the United States: 1952 to 2050. Gen Tech Rep PNW-GTR-560. USDA Forest Service, Pacific Northwest Research Station, Portland, ORGoogle Scholar
  29. Haynes RW, Holley L, King RA (1978) A recursive spatial equilibrium model of the softwood timber sector. Tech Rep No. 57. North Carolina State University, School of Forest Resources, Raleigh, NCGoogle Scholar
  30. Howard JL, Ince PJ, Durbak I, Lange WJ (1988) Modeling technology change and fiber consumption in the U.S. pulp and paper industry. In: Abt R (ed) Proceedings of the 1988 Southern forest economists workshop, Orlando, Florida, May 1988. Department of Forestry, University of Florida, Gainesville, FL, pp 211-219Google Scholar
  31. Howard JL, Skog K, Ince PJ (2002) Projecting recovered paper supply in the United States. Proceedings of the 2001 Society of American Foresters national convention, Denver, Colorado, September 2001. Society of American Foresters, Bethesda, MD, pp464-465Google Scholar
  32. Ince PJ (1985) Pulp and paper science may change technology and increase use of Southern hardwoods. In: Proceedings of Southern forest economics workers conference Athens, Georgia, March 1985. University of Georgia, Athens, GA, pp71-85Google Scholar
  33. Ince PJ (1986) Technology development for increased use of hardwoods. In: Proceedings of fourth biennial southern silvicultural research conference, Atlanta, Georgia, Nov 1986. Gen Tech Rep SE-42. USDA Forest Service, Southeastern Forest Experiment Station, Asheville, NC, pp3-7Google Scholar
  34. Ince PJ (1989) Projected pulpwood consumption in the United States, 2000-2040: implications for timber management? In: Proceedings of the Society of American Foresters 1989 Convention, Spokane, Washington, September 1989. Society of American Foresters, Bethesda, MD, 1990:364-369Google Scholar
  35. Ince PJ (1990) Timber market implications of accelerated wastepaper recycling in the 1990s. In: Proceedings of the Society of American Foresters 1990 Convention, Washington DC, July 1990. Society of American Foresters, Bethesda, MD, pp438-445Google Scholar
  36. Ince PJ (1994a) Recycling and long-range timber outlook. Gen Tech Rep RM-242. USDA Forest Service, Rocky Mountain Forest and Range Experiment Station, Fort Collins, COGoogle Scholar
  37. Ince PJ (1994b) Recycling and long-range timber outlook: background research report 1993 RPA assessment update. Res Pap FPL-RP-534. USDA Forest Service, Forest Products Laboratory, Madison, WIGoogle Scholar
  38. Ince PJ (1999a) Long-range outlook for U.S. paper and paperboard demand, technology, and fiber supply-demand equilibria. In: Proceedings of the Society of American Foresters 1998 national convention. Society of American Foresters, Bethesda, MD, pp330-343Google Scholar
  39. Ince PJ (1999b) Global cycle changes the rules for U.S. pulp and paper. PIMA’s Papermaker, December, pp37-42Google Scholar
  40. Ince PJ (2002) U.S. fiber supply: steady and secure. In: Solutions for people, processes and paper. TAPPI Press, June, pp40-44Google Scholar
  41. Ince PJ, Li X, Zhou M, Buongiorno J, Reuter M (2002) United States paper, paperboard, and market pulp capacity trends by process and location, 1970-2000. Res Pap FPL-RP-602. USDA Forest Service, Forest Products Laboratory, Madison, WI Google Scholar
  42. Ince PJ, Skog KE, Spelter H, Durbak IA, Howard JL (1987) Modeling technological change in wood products processing. In: Cardellichio PA, Adams DM, Haynes RW (eds) Forest sector and trade models: theory and applications. Proceedings of an international symposium, Seattle, Washington DC, November 1987. CINTRAFOR, University of Washington, Seattle, WA, pp257-265Google Scholar
  43. Judge GG, Wallace TD (1958) Estimation of spatial price equilibrium models. J Farm Econ 40(4):801-820CrossRefGoogle Scholar
  44. Kallio M, Dykstra DP, Binkley CS (eds) (1987) The global forest sector: an analytical perspective. Wiley, New YorkGoogle Scholar
  45. Kennedy M (1974) An economic mode of the world oil market. Bell J Econ 5:540-577CrossRefGoogle Scholar
  46. Landau R, Rosenberg N (eds) (1986) The positive sum strategy: harnessing technology for economic growth. National Academy Press, Washington DCGoogle Scholar
  47. Lebow PK, Spelter H, Ince PJ (2003) FPL-PELPS, a price endogenous linear programming system for economic modeling, supplement to PELPS III, version 1.1. Res Pap FPL-RP-614. USDA Forest Service, Forest Products Laboratory, Madison, WIGoogle Scholar
  48. Lonner G (1991) Modelling the Swedish forest sector. Rep No. 20. The Swedish University of Agricultural Sciences, Department of Forest-Industry-Market Studies (SIMS), Uppsala, SwedenGoogle Scholar
  49. Manne AS (1979) Energy policy modeling: a survey. Oper Res 27(1):1-35CrossRefGoogle Scholar
  50. Manne AS (1981) ETA-MACRO: a user’s guide. Prepared for Electric Power Research Institute, Palo Alto, CA. Report EPRI EA-1724 (Interim Report). Stanford University, Department of Operations Research, Stanford, CAGoogle Scholar
  51. Mansfield E (1968) The economics of technological change. Norton, New YorkGoogle Scholar
  52. McCarl BA, Spreen TH (1980) Price endogenous mathematical programming as a tool for sector analysis. Am J Agr Econ 62(1):87-102CrossRefGoogle Scholar
  53. McKillop (1967) Supply and demand for forest products, an econometric study. Hilgardia 38:1-132Google Scholar
  54. Miller Freeman (1990) Pulp & paper North American factbook. Miller Freeman, San Francisco, CAGoogle Scholar
  55. Naylor TH (1972) Policy simulation experiments with macro-econometric models: the state of the art. Am J Agr Econ 52:263-271CrossRefGoogle Scholar
  56. Nelson JR (1973) An interregional recursive programming model of the United States iron and steel industry. In: Judge GG, Takayama T (eds) Studies in economic planning over space and time. North-Holland, Amsterdam, pp197-212Google Scholar
  57. Pilati DA, Chang J, Sparrow FT, Howe SO, Balzer C, McBreen B (1980) A process model of the U.S. pulp and paper industry. Economic Analysis Division, National Center for Analysis of Energy Systems, Department of Energy and Environment, Brookhaven National Laboratory, Associated Universities, under contract No. DE-AC02-76CH00016 with the U.S. Department of Energy. Prepared for Department of Energy, Energy Information Administration, and the Electric Power Research Institute. Report No. BNL 51142, UC-95f. Available from National Technical Information Service, Springfield, VAGoogle Scholar
  58. Rosenberg N (1976) Perspectives on technology. Cambridge University Press, Cambridge, UK Google Scholar
  59. Rosenberg N (1982) Inside the black box: technology and economics. Cambridge University Press, Cambridge, UKGoogle Scholar
  60. Rykiel EJ (1996) Testing ecological models: the meaning of validation. Ecol Model 90:229-244CrossRefGoogle Scholar
  61. Samuelson PA (1952) Spatial price equilibrium and linear programming. Am Econ Rev 42(3):283-303Google Scholar
  62. Schmookler J (1966) Invention and economic growth. University Press, Cambridge, MAGoogle Scholar
  63. Schrader LF, King GA (1962) Regional location of beef cattle feeding. J Farm Econ 44(1):68-81Google Scholar
  64. Schumpeter J (1943) The process of creative destruction. In: Socialism, capitalism and democracy. Allen & Unwin, London, pp81-86Google Scholar
  65. Strange JG (1977) The paper industry, a clinical study. Graphic Communications Center, Appleton, WIGoogle Scholar
  66. Takayama T, Judge GG (1964a) An interregional activity analysis model of the agriculture sector. J Farm Econ 46(2):349-365CrossRefGoogle Scholar
  67. Takayama T, Judge GG (1964b) Equilibrium among spatially separated markets: a reformulation. Econometrica 32(4):510-524CrossRefGoogle Scholar
  68. Takayama T, Judge GG (1970) Alternative spatial equilibrium models. J Regional Sci 10:1-12CrossRefGoogle Scholar
  69. Takayama T, Judge GG (1971) Spatial and temporal price and allocation models. North-Holland, AmsterdamGoogle Scholar
  70. Tobin (1969) A general equilibrium approach to monetary theory. J Money Credit Bank 1:15-29CrossRefGoogle Scholar
  71. Tramel TE, Seale AD Jr (1959) Reactive programming of supply and demand relationships—application to fresh vegetables. J Farm Econ 41(5):1012-1022CrossRefGoogle Scholar
  72. U.S. Department of Agriculture, Forest Service [USDA FS] (1958) Timber resources for America’s future. Forest Resour Rep 14. GPO, Washington DCGoogle Scholar
  73. U.S. Department of Agriculture, Forest Service [USDA FS] (1982) An analysis of the timber situation in the United States 1952-2030. Forest Resour Rep 23. GPO, Washington DCGoogle Scholar
  74. U.S. Department of Agriculture, Forest Service [USDA FS] (1989) RPA assessment of the forest and rangeland situation in the United States, 1989. Forest Resour Rep 26. GPO, Washington DCGoogle Scholar
  75. Whiteman A (1991) The supply and demand for wood in the United Kingdom. Occasional Pap 29. Forestry Commission, Edinburgh, UKGoogle Scholar
  76. Yaron D (1967) Incorporation of income effects into mathematical programming models. Metroeconomica 19(3):141-164CrossRefGoogle Scholar
  77. Zhang D, Buongiorno J (1993) Capacity changes in the U.S. paper and paperboard industries: q theory and empirical models. Can J Forest Res 23:72-80CrossRefGoogle Scholar
  78. Zhang D, Buongiorno J, Calmels P (1991) PELPS II PLUS: A microcomputer price-endogenous linear programming system for economic modeling. Staff Pap Series No. 41, Department of Forestry, University of Wisconsin-Madison, Madison, WIGoogle Scholar
  79. Zhang D, Buongiorno J, Ince P (1993) PELPS III: a microcomputer price endogenous linear programming system for economic modeling: version 1.0. Res Pap FPL-RP-526. USDA Forest Service, Forest Products Laboratory, Madison, WI Google Scholar
  80. Zhang D, Buongiorno J, Ince P (1996) A recursive linear programming analysis of the future of the pulp and paper industry in the United States: changes in supplies and demands, and the effects of recycling. Ann Oper Res 68:109-139CrossRefGoogle Scholar
  81. Zhang Y (1995) Demand for paper and paperboard products in the United States: econometric models and forecasts. Ph.D. dissertation. University of WisconsinMadison, Madison, WIGoogle Scholar

Copyright information

© Springer 2007

Authors and Affiliations

  • Peter J. Ince
    • 1
  • Joseph Buongiorno
    • 2
  1. 1.USDA Forest ServiceForest Products LaboratoryMadisonUSA
  2. 2.Department of Forest Ecology and ManagementUniversity of Wisconsin-MadisonMadisonUSA

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