Regional Dependence and Location of the Wood Products Sector in the Northeastern United States: Unique Attributes of an Export-Based Industry


  • Scott A. Bowe
  • David W. Marcouiller
  • Michael D. La Bissoniere


Wood products, primary processors, secondary processors, reconstituted processors, firm location, location quotient


Natural resources have long been a source of both raw material supply and value added manufacturing in many rural regions across North America. Contemporary resource management and rural development planning increasingly emphasize the integration of raw material production with forward-linked processing activities. Empirical studies suggest that wood processors locate proximate to raw material supplies. Assessing the regional firm location decisions of wood processors, however, raises important and complex issues of sectoral heterogeneity. In this paper, we initiate analysis of firm location in three wood processing sub-sectors through descriptive location quotients of primary, secondary, and reconstituted wood products manufacturing sectors. Explanatory variables that support these sectoral specific location quotients include proxies for raw material inputs and output markets. Results suggest that important differences exist in locational dependency attributes between wood products sub-sectors.


Abt, R. C. 1987. An analysis of regional factor demand in the U.S. lumber industry. Forest Science33(1): 164-173.nAnselin, L. 2003. Spatial externalities, spatial multipliers, and spatial econometrics. Int. Reg. Sci. Rev.26(2): 153-166.nAruna, P. B., F. Cubbage, K. J. Lee, and C. Redmond. 1997. Regional economic contribution of the forest-based industries in the South. Forest Prod. J.47(7/8):35-45.nAudretsch, D. B. 2003. Innovation and spatial externalities. Int. Reg. Sci. Rev.26(2): 167-174.nCox, B. M., and I. A. Munn. 2001. A comparison of two input-output approaches for investigating regional economic impacts of the forest products industry in the Pacific Northwest and the South. Forest Prod J.51(6):- 39-46.nDissart, J. C. 2003. The role of outdoor recreation facilities in remote rural economic development planning: An exploratory approach. Unpublished Ph.D. dissertation. Department of Urban and Regional Planning, University of Wisconsin, Madison, WI.nFingleton, B. 2003. Externalities, economic geography, and spatial econometrics: Conceptual and modeling developments. Int. Reg. Sci. Rev.26(2): 197-207.nFujita, M., P. Krugman, and A. Venables. 1999. The Spatial economy: cities, regions, and international trade. MIT Press. Cambridge, MA.nFujita, M. 1956. Plant location in theory and practice. University of North Carolina Press, Chapel Hill, NC.nGreenhut, M. L. 1963. Microeconomics and the space economy. Chicago: Scott Foresman & Co.nGunton, T. 2003. Natural resources and regional development: An assessment of dependency and comparative advantage paradigms. Econ. Geogr.79(1):67-94.nKim, K. K. 2002. Effects of natural amenities in the great lakes states: An application of exploratory spatial data analysis (ESDA) and spatial econometrics. Unpublished Ph.D. dissertation. Department of Urban and Regional Planning, University of Wisconsin, Madison, WI.nKrugman, P., 1994. Peddling prosperity: Economic sense and nonsense in the age of diminished expectations. W.W. Norton and Company, New York, NY.nLeigh, N. G. 2000. Planning, spatial, and technological considerations of restructuring in the U.S. woodworking industry. Economic Devel. Quar.14(2):204-220.nLewis, D. K., D. P. Turner, and J. K. Winjum. 1996. An inventory-based procedure to estimate economic costs of forest management on a regional scale to conserve and sequester atmospheric carbon. Ecological Economics16(1996):35-49.nLohmander, P., 1994. Adaptive transportation and production in a multi factory forest company—with regionally distributed stochastic roundwood volumes and product prices. In: F. Helles and M. Linddal, (eds.), Proc. biennial meeting of the Scandinavian Society of Forest Economics, Gilleleje, Denmark, Nov. 22-25, 1993. Scand. Forest Econ.35: 131-140.nMcCann, P., 2002. Classical and neoclassical location—Production models, in Industrial Location Economics. P. McCann, ed. North Hampton, MA: Edward Elgar: 3-31.nMcNulty, S. G., J. A. Moore, L. Iverson, A. Prasad, R. Abt, B. Murray, R. A. Mickler, and J. D. Aber. 2000. Application of linked regional scale growth, biography, and economic models for southeastern United States pine forests. World Resource Rev.12(2):298-321.nMig. 2001. MicroIMPLAN county-level datasets for 1997. Available from Minnesota IMPLAN Group, Inc., 1725 Tower Drive West, Suite 140, Stillwater, MN 55082, Telephone: 651-439-4421.nNorth, D. C. 1955. Location theory and regional economic growth. J. Political Econ.63(3):243-258.nPorter, M. E. 1990. The competitive advantage of firms in global industries. The competitive advantage of nations. The Free Press, New York, NY.nPorter, M. E., 1996. Competitive advantage, agglomeration economies and regional policy. Int. Reg. Sci. Rev.19(1): 85-94.nRichardson, H. W. 1985. Input-output and economic base Multipliers: Looking backward and forward. J. Reg. Sci. 25 (November 1985):607-661.nSmith, P., and I. A. Munn. 1998. Regional cost function analysis of the logging industry in the Pacific Northwest and Southeast. Forest Science44(4):517-525.nUSDA Forest Service. 2003. Forest Inventory and Analysis Data Base Retrieval System. USDA Forest Service.'> Census Bureau. 2002. County-level 2000 Census Data. Available at the U.S. Department of Commerce, Census Bureau website—'>http://www.cencus.govnWebster, H. H. and D. E. Chappelle. 1989. Community and regional economic growth and development. Ellefson, P. V., ed. Forest resource economics and policy research: Strategic directions for the future. Westview Press, Boulder, CO. Pp. 263-275.n






Research Contributions