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5.5 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 (Boyd and Hyde, Wear and Hyde, Berck and others). In addition, several analyses of the impacts of changes in the industry (products of technology) have been conducted (Xu 1994, Alavalapati and others 1999, Marcouiller and others 1995). Other studies have assessed the association between forests, rural communities, and the economic benefits derived from forests, including tourism and wood products (English and others 2000, Bliss and others (undated), Bliss and others 1994, Lee and Cubbage 1994).

Rural communities are worse off generally than more urban communities. This disparity is attributed to a lack of human and human-made capital, even in the presence of a wealth of natural capital (Beaulieu and others). Social capital and other community attributes can also influence well-being in rural communities (Bliss and others (undated), Force and others 2000). A community needs a balance of many kinds of capital in order to thrive. 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). 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 and others 1994, Bliss and others undated, Lee and Cubbage 1994). Berck and others (1992) found that problems in rural communities resulted more from remote locations and subsequent 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, however, does have potentially undesirable distributional consequences. Because forestland is owned by middle and upper income households, revenue from uses will go to these households (Marcouiller and others 1995). Subsequent wood processing, however, will lead 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 in to 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 distribution 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.