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Distributional Consequences of Forest-Based Economic Activity

This section summarizes previous research on the distributional impacts of policies, industrial changes, and situations. In assessing situations, we can only examine correlations or associations, because causality between forests, forest-based industries, and distribution has not been determined.

Impact of a project or situation can be assessed by assuming individuals maximize utility consisting of physical, amenity, financial/economic, and institutional/social factors (Xu 1994). Impacts on groups divided by age, generation, income, geography, place in the production chain (producers or consumers), and race can all be assessed. In this discussion, we focus on financial and economic impacts on groups divided by geography (urban/rural), race, and income class, largely because these are what previous studies have addressed.

Previous analyses of distributional impacts in forestry have focused on the (1) public land harvests and (2) tree planting programs (Berck and others 1992, Boyd and Hyde 1989, Wear and Hyde 1992). In addition, several analyses of the impacts of changes in the industry (products of technology) have been conducted (Alavalapati and others 1999, Marcouiller and others 1995, Xu 1994). Other studies have assessed the association between forests, rural communities, and the economic benefits derived from forests, including tourism and wood products (Bliss, J.C.; Bailey, C.; Howze, G.R.; Teeter, L.J. [n.d.] Timber dependency in the American South. SCFER Work. Pap. 74. 18 p. Unpublished manuscript. On file with: USDA Forest Service, Southern Research Station, Southeastern Center for Forest Economics Research, P.O. Box 12254, Research Triangle Park, NC 27709.) (Bliss and others 1994, 1998b; English and others 2000; Lee and Cubbage 1994; Overdevest and Green 1994).

Rural communities are found to be worse off than more urban communities, with lower per capita incomes, lower educational attainment, and higher unemployment (Beaulieu and others 2001, Gale and McGranahan 2001, Ghelfi 2001, Gibbs 2001, McGranahan 2001, Rowley and Freshwater 1999). This disparity is attributed, in part, to a lack of both human capital (education) and human-made capital (buildings and machinery), even in the presence of a wealth of natural capital (Beaulieu and others 2001 ). Social capital and other community attributes can also influence well-being in rural communities (Bliss, J.C.; Bailey, C.; Howze, G.R.; Teeter, L.J. [n.d.] Timber dependency in the American South. SCFER Work. Pap. 74. 18 p. Unpublished manuscript. On file with: USDA Forest Service, Southern Research Station, Southeastern Center for Forest Economics Research, P.O. Box 12254, Research Triangle Park, NC 27709.) (Force and others 2000).

Forests in the South are a major component of the region’s natural capital, but forests are often associated with the absence of human and human-made capital (Joshi and others 2000). Forests are unlikely causes for lower economic well-being, but the negative associations and correlations between well-being and forests have been well documented (Bliss, J.C.; Bailey, C.; Howze, G.R.; Teeter, L.J. [n.d.] Timber dependency in the American South. SCFER Work. Pap. 74. 18 p. Unpublished manuscript. On file with: USDA Forest Service, Southern Research Station, Southeastern Center for Forest Economics Research, P.O. Box 12254, Research Triangle Park, NC 27709.) (Bliss and others 1994, Lee and Cubbage 1994, Overdevest and Green 1994). Berck and others (1992) found that problems in rural communities resulted more from remote locations and transportation costs than from specific forest products industries. Using simulation, they found that maximizing the diversity of the rural community or replacing wood products with other manufacturing sectors did not improve the economic well-being of the community.

Use of private forests for timber and recreation production could also have potentially undesirable distributional consequences. According to Marcouiller and others (1995), because forest land is owned by middle and upper income households, revenue from uses will go to these households. Alavalapati and others (1999), in a study in Canada, found that subsequent wood processing, however, leads to benefits for lower income households through increases in well-paid job opportunities (Alavalapati and others 1999). In contrast, increasing recreation production is likely to produce lower paying jobs locally, with the returns to capital accumulating to higher income households elsewhere. Adding race into the mix (rural, forested, and large minority populations) makes it harder to correct problems of lower human and human-made capital and often exacerbates the regressive distributional effects of rural, forested locations (Bliss and others 1994). Changes in the nature of the wood products sectors can also have distributional impacts. In modeling an expansion of the pulp and paper sector, Alavalapati and others (1999) found that higher income households benefited, while a decline in the lumber sector hurt higher income households more than lower income households.