Measuring socio-economic wellbeing in the Northern Forest

Transcription

1 Measuring socio-economic wellbeing in the Northern Forest Principal Investigator: Marta Ceroni Affiliations/Institutions: Department of Plant Biology and Gund Institute for Ecological Economics, University of Vermont Mailing address: 617 Main Street Collaborators: Roelof Boumans Completion date: The Northern Forest counties of Vermont had higher socio-economic wellbeing than the average US when measured with the Genuine Progress Indicator. The approach is promising for the Northern Forest as whole, provided that additional efforts are placed into data collection. Funding support for this project was provided by the Northeastern States Research Cooperative (NSRC), a partnership of Northern Forest states (New Hampshire, Vermont, Maine, and New York), in coordination with the USDA Forest Service.

2 Project Summary The well-being of the Northern Forest depends on the economic vitality of its communities as well as its natural resource wealth, social interactions, health and knowledge. Yet, classical measures of progress, such as the Gross Domestic Product (GDP), are based solely on economic growth. The overall goal of this project was to use an alternative measure of progress, the Genuine Progress Indicator (GPI), to monitor socio-economic wellbeing over the past 50 years in 6 rural counties of Vermont as a test case for the whole of the Northern Forest. The GPI is a monetary-based indicator (expressed in US dollars per capita) that adjusts for those activities that increase well-being (e.g. volunteer work) as well as those that have a negative effect on quality of life, such as crime, family breakdown and underemployment. This study is the first calculation of local GPI for a U.S. rural area. The study shows that Vermont s per capita GPI is greater than the U.S. average, with Chittenden County having the highest GPI of any Vermont county. GPI in the most rural counties (Caledonia, Essex, Orleans) was below the U.S. average in 1950 but had risen above the national average by For all Vermont counties, per capita GPI has increased at a faster rate than the U.S. average, suggesting that the growth in Vermont s consumption has not led to inequality, social, and environmental disamenities as in the average U.S. Rural counties generally had lower income (hence, personal consumption), generated less solid waste, had less air, water, and noise pollution, and less loss of forest cover and wetlands, though not all these patterns held on a per capita basis. Rural counties had consistently lower crime rates but higher costs of underemployment. Unfortunately, data limitations obscure many of the local distinctions that we expect exist in these rural counties. While rural areas have less crime, we did not have data for many other social components at the local level (hours of household labor, volunteer work, or on the job, and defensive spending to deter crime). Time use data are generally poorly measured at the local scale, with the exception of commuting time. While the GPI in its present formulation revealed interesting trends, special efforts would be needed in data collection at the local level for a more accurate assessment.

3 Background and Justification Knowing whether the quality of life of a community is improving or declining year to year is key to planning development and revitalization strategies. The well-being of the Northern Forest depends on the economic vitality of its communities as well as its natural resource wealth, social interactions, health and knowledge. Yet, classical measures of progress, such as the Gross Domestic Product (GDP), are based solely on economic growth, ignoring environmental or social costs. In a GDP calculation, for example hurricane Katrina would count as a positive given that reconstruction efforts translate into higher economic activity. Since at least the late 1960s, economists have attempted to adjust GDP to better reflect society s well-being. Daly and Cobb 1 developed the Index of Sustainable Economic Welfare (ISEW), which was later revised as the Genuine Progress Indicator (GPI). These authors showed that while GDP kept increasing over time to these days, the more realistic GPI showed that economic well-being has grown till the 1970s and since leveled off or declined slightly. The GPI accounts for income inequality and for environmental and social costs. The inclusion of these components makes GPI better suited than GDP to addressing questions of distribution, societal well-being, and sustainability within the economy. 1. Daly, H.E. and Cobb, J.B., Jr. (1989) For the Common Good: Redirecting the Economy toward Community, the Environment, and a Sustainable Future, Boston, MA: Beacon Press.

4 Background and Justification: the GPI at the local scale The costs and benefits of economic growth are not distributed evenly across a nation. Certain regions may maintain their social capital, pursue stronger environmental protection, have a more even income distribution, or import pollution-intensive manufactured goods or energy from elsewhere. Understanding these local and regional differences has fueled recent interest in developing local-scale GPI studies. In the U.S., GPI was recently calculated for nine counties in the San Francisco Bay area 2 and at the state, county, and city level for Vermont 3. These studies found GPI to be consistently higher in these areas than the national average. This may be due to efforts by Vermont and the San Francisco Bay area to develop strong local economies while preserving environmental quality and social cohesion. These studies also revealed limitations with using GPI at local or regional scales. At least for industrialized nations, data for most of the components used in GPI are readily available at the national level. However, national statistics agencies were not originally designed to collect needed GPI-related data at local scales. In the U.S., historical data may be available only for decennial census years, leaving wide year-to-year gaps. Worse, state and local data may simply not exist. 2. Venetoulis, J. and Cobb, C. (2004) The Genuine Progress Indicator (2004 Update), San Francisco, CA: Redefining Progress. 3. Costanza, R et al Estimates of the Genuine Progress Indicator (GPI) for Vermont, Chittenden County, and Burlington, from 1950 to 2000, Ecological Economics, Vol. 51, pp

5 Methods The GPI begins with a measure of personal consumption, weighted to account for income inequality, and deducts or adds value for various monetized measures of built, social, and natural capital. This can be expressed in the form of the equation (adapted from Hanley et al ): GPI = C adj + G + W D S E N Where: C adj = personal consumption adjusted to account for income distribution, G = growth in capital and net change in international position, W = non-monetary contributions to welfare (e.g., household labor, volunteer work), D = defensive private expenditures, S = depletion of social capital (e.g., cost of crime, family breakdown, lost leisure time), E = costs of environmental degradation, and N = depletion of natural capital. 4. Hanley, N., Moffatt, I., Faichney, R., and Wilson, M. (1999). Measuring sustainability: A series of alternative indicators for Scotland, Ecological Economics Vol. 28, pp

6 Methods: Study area In Vermont, six counties Caledonia, Essex, Franklin, Lamoille, Orleans, and Washington are included in the Northern Forest (Figure 1). These counties are characterized by low population density, abundant forest cover, and a settlement pattern of small New England town centers. Table 1. Comparison between rural and urban counties in northern Vermont Six Northern Forest counties Chittenden County Population density, 2000 census (persons/km 2 ) Percent forested 81% 61% Largest city population 9,291 (Barre) 38,889 (Burlington)

7 Methods To calculate the GPI for the Northern Forest counties, we strove to maintain consistency by following the methods of Costanza et al. 4, who in turn followed those of Anielski and Rowe 5. Since Anielski and Rowe s calculations were at the national level, Costanza et al s local-level adjustments were used as appropriate. When improved data sources or methods were available, we noted these changes. Following Costanza et al., we calculate values for the decennial years , for the 26 components of GPI for the six Northern Forest counties in Vermont (Caledonia, Essex, Franklin, Lamoille, Orleans, and Washington). Where there were changes in methods or data sources, we also recalculated values for Chittenden County to allow comparison between a relatively urban county (Chittenden) to more rural counties of northern Vermont. As such we discuss GPI results from seven of Vermont s 14 counties. All monetary values were converted into year 2000 U.S. dollars using the Consumer Price Index (CPI) from the U.S. Bureau of Labor Statistics. Detailed methods are also available online at 5. Anielski, M. and Rowe, J. (1999) The Genuine Progress Indicator 1998 Update, San Francisco, CA: Redefining Progress.

8 Methods:Data used Table 2. Data used for Vermont GPI studies Column and Variable National Regional State County D. Household labor rates by employment & *, + gender E. Volunteer rates by education *, + H. Crime rate * + H. Defensive spending on crime deterrence *, + o I. Divorce rate * + I. TV ownership * + I. Hours of TV watching *, + J. Hours at work *, + L. Consumer durables spending * + o M, N. Vehicle registrations *, + O. Auto accidents * + U, V. Energy use *, + o Y. Net capital investment *, + * = Costanza et al = Bagstad and Ceroni, this study o = Data available only commercially

9 Results Rural Vermont generally: had lower income (hence, personal consumption) generated less solid waste, had less air, water, and noise pollution, had less loss of forest cover and wetlands Which resulted in higher GPI (see next slide)

10 $/capita Results GPI per capita for U.S., Vermont, and seven Vermont counties for ,000 20,000 15,000 10,000 U.S. Vermont Caledonia Chittenden Essex Franklin Lamoille Orleans Washington 5, Year Vermont s per capita GPI is greater than the U.S. average, with Chittenden County having the highest GPI of any Vermont county.

11 $/capita Results Costs of mobility per capita (Columns G, M, and O) (500) (1,000) U.S. Vermont Caledonia Chittenden Essex Franklin Lamoille Orleans Washington (1,500) (2,000) Year Mobility costs per capita are greatest in Chittenden County and least in the most rural counties. This reflects greater per capita value of services of highways and streets in rural counties combined with lower costs of commuting and crashes in highly rural areas.

12 $/capita Results Costs of natural capital depletion (columns U, V, and W) (1,000) (2,000) (3,000) (4,000) U.S. All Vermont counties (5,000) (6,000) (7,000) (8,000) Year Per capita natural capital depletion was substantially less in Vermont than the U.S. average. This is driven by Vermont s below-average consumption of fossil fuels.

13 Implications and applications in the Northern Forest region The study was conducted on a small sample of Northern Forest counties in Vermont. It would be interesting to apply a similar approach to all remaining counties. We expect that the GPI would help identify differences in socio-economic well-being at the state and regional level. At the community or county level, data limitations might obscure many of the local distinctions that we expect exist in rural counties. In this study for example we did not have data for many other social components at the local level (hours of household labor, volunteer work, or on the job, and defensive spending to deter crime). For a more comprehensive study across the Northern Forest Region, additional resources should be placed in data collection efforts including designing specific surveys for time use data or acquiring commercial data that have been recently made available for certain key columns (see table 2). Data availability and quality has improved in recent years and with widespread use of the internet for disseminating local socioeconomic and environmental data. By incorporating commercial data on consumer spending patterns, researchers can compile most of the needed data at local scales, leading to robust GPI estimates for recent years. Such estimates can provide useful interregional comparisons of well-being.

14 Future directions The GPI concept would be very relevant to the goal of developing a monitoring system for the quality of life in the Northern Forest. Specific efforts should be devised to develop local level surveys for data that are not regularly collected by federal offices. A workshop approach at the community level could be beneficial for identifying key socio-economic indicators to be included in the GPI calculations.

15 List of products 1 presentation: Ceroni, M., Boumans, R., and Chase, L. Assessing and modeling genuine well-being in rural communities of the Northern Forest. Third International Conference on Community Indicators. Burlington, Vermont, December 1-3, scholarly publications: Bagstad, K. and Ceroni, M. Opportunities and challenges in applying the Genuine Progress Indicator at local scales. International Journal of Environment, Workplace and Employment, in press. Bagstad, K. and Ceroni, M. The Genuine Progress Indicator: a new measure of economic development for the Northern Forest. Adirondack Journal of Environmental Studies, in press. 1 proposal resulted from the active dialog with the planning commission in Vergennes. Additional efforts are under way to fund a project to adapt the GPI approach to Vergennes.