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3.5 Specific indicators used in the analysis

3.5.1 Income per job

Specific quality-of-life indicators were selected based on consideration of the issues discussed in the Introduction. To provide an indication of the economic benefit received by people working in forest-related industries, total income per sector was divided by the number of jobs per sector for the four forest-related sectors described above. These measures are not wage rates, but represent average income per job. Income per job may be low because wage rates are low or because the "typical" job is only part-time. Income per job was also computed for all jobs in the areas where the forest related sectors were located. This step allowed a comparison to be made between average income per job in the forest related sectors and the "typical" job in those areas.

3.5.2 Social and demographic indicators

To evaluate social indicators in areas with forest-related employment, a subset of social, demographic and economic variables was selected from two recent quality of life studies (Diener 1995, Ferriss 2000). From the socio-economic and demographic indicators used in those studies, six indicators were selected: (1) infant mortality rate, (2) violent crime rate, (3) median household income, (4) unemployment rate, (5) poverty rate, and (6) percent graduating high school.

Evidence in the literature that rural population growth is influenced by the supply of natural amenities caused us to include a measure of population growth in the analysis. Inclusion of a variable measuring the percent change in population allowed us to evaluate the relationship between the degree of industrial concentration in forest-related industries and population dynamics.

Social cohesion is a concern in considering quality of life. Three indicators of social cohesion and the potential for collective social action, used in other quality of life studies (Drielsma 1984, Wish 1986, Hamilton 1993, Hamilton 1999), were included: (1) percentage of owner-occupied housing, (2) divorce rate, and (3) percent voting in recent presidential elections (an indicator of the potential for collective action).

3.5.3 Indicators of forest condition

Five variables were selected to provide a general description of the forest landscape: (1) forest land as a percentage of all land, (2) pine-forest acreage as a percentage of total forest acreage, (3) upland-hardwood acreage as a percentage of total forest acreage, (4) bottomland hardwood acreage as a percentage of total forest acreage, and (5) oak-pine acreage as a percentage of total forest acreage. Correlations of the degree of industrial concentration in various forest related sectors with these descriptive variables provided us with a general sense of the forest types within which the sectors were concentrated.

The review of the literature linking willingness to pay and forest condition led us to include variables that would indicate the degree of naturalness of forest ecosystems. Although "naturalness" may be impossible to define with precision, some aspects can be specified. Anderson's (1991) definition of natural was based on the idea that forests that are more natural would change little if removed from human influence and are made up of a high proportion of native species. Noss and Cooperrider (1994) used this idea to define a gradient of forest ecosystem naturalness that ranged from primary natural forests (virtually uninfluenced by human disturbance), to secondary natural forests (natural regeneration after human disturbance), to plantations (in most, but not all, cases, human planting after human disturbance).

Using these ideas as broad descriptors of the degree of naturalness, we decided that the following indicators of human disturbance in forest ecosystems should be included: (1) plantation acreage as a percentage of all forest acreage, (2) the change in plantation percent between the two most recent forest surveys, (3) pine removal to pine inventory ratio, (4) pine growth to pine inventory ratio, (5) hardwood removal to hardwood inventory ratio, and (6) hardwood growth to hardwood inventory ratio. The first indicator provides information on the extent of intensive forest management in an area, while the second indicator provides information on the growth or decline of intensive forestry. Removal of pine or hardwood as a proportion of the standing inventory provides information on harvest intensity. Growth as a proportion of standing inventory provides information on the age distribution of forests. Because young forests generally grow more rapidly than old forests, a high (low) growth/inventory ratio would be found in areas with younger (older) forests.