Measuring Socio-Economic Well-Being in the Northern Forest
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- Croni, Marta
University of Vermont, Department of Plant Biology and Gund Institute for Ecological Economics
mceroni@uvm.edu
- • 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 ChittendenCounty 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 2000. 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.
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