Forest Cover Change in the Northeastern U.S.: A Spatial Assessment in the Context of an Environmental Kuznets Curve

Forest Cover Change in the Northeastern U.S.: A Spatial Assessment in the Context of an Environmental Kuznets Curve

George C. Bentley (University of Connecticut, Storrs, CT, USA), Robert G. Cromley (University of Connecticut, Storrs, CT, USA), Dean M. Hanink (University of Connecticut, Storrs, CT, USA) and C. Patrick Heidkamp (Southern Connecticut State University, New Haven, CT, USA)
Copyright: © 2013 |Pages: 18
DOI: 10.4018/jagr.2013070101


An analysis of the association of forest cover, treated as an environmental good, and income at the county scale in the Northeastern United States was conducted for 2006. Global analysis using a spatial error regression model indicates an environmental Kuznets curve (EKC) type of relationship, with total forest cover, percent forest cover, and forest cover per capita is better associated with per capita income and is better specified as a polynomial rather than in linear terms. Local analysis, using geographically weighted regression, indicates that sub-regional effects are pronounced, and that conformity to an EKC varies spatially and by forest cover measure. The findings should be interpreted strictly within their context of a cross-sectional analysis and within certain statistical limitations, primarily engendered by multicollinearity of the explanatory variables in the regression models.
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Forest resources are very important. From railroad ties to storage sheds, lumber and other wood products are prized as construction materials wherever they are available for both aesthetic and practical reasons. Forest products have multiple uses beyond construction, from fuel to carving material to bedding for livestock. Beyond their resource classification, forests can also be considered as environmental assets, with values yet to be capitalized in markets. They have, as examples, non-market value as wild places (Anas, 1988), and as recreation venues (Englin & Mendelsohn, 1991), which have been recognized for some time. More recently, special attention has been given to the relationship between forests and climate change. Such analyses include research on forests as carbon sinks (Duarte, Cunha-e-Sá, & Rosa, 2009). Along the same lines, Wayburn (2009) has described a series of general strategies of forest use and conservation that can inform climate policy in the U.S. The impact of climate change on the value of forest products and services has also been examined, for example by Ding, Nunes, and Teelucksingh (2010) and by Ding, Silvestri, and Nunes (2010).

Given the importance of forest in both natural resource and environmental asset categories there is a serious concern over its ongoing reduction. Exact global estimates of decline are difficult to assess because of variations in reporting, but the Food and Agriculture Organization reports an estimated global loss of 13 million hectares in 2005 – a reduction from the average of 16 million ha/year from 1990-2000, and an average decrease in global forest biomass of 0.5 gigatons per year from 2005 to 2010 (FAO, 2010). Wayburn (2009) reported an annual loss of forestland in the U.S. of about 680,000 ha/year. Such reports are alarming but hide important variation, not only in rates of decline, but in rates of expansion as well. At the global scale, much of East Asia, West Europe, and North America have been undergoing reforestation at the continental scale, while within the U.S. there are more localized areas of reforestation as well. There are a variety of factors underlying forest reduction and expansion that result in significant spatial variation in forest cover at a variety of spatial scales. The purpose of the analysis reported in this paper is to examine recent regional scale variations in forest cover in the Northeastern U.S. in the context of an environmental Kuznets curve (EKC) – an empirical device that links environmental differences to differences in per capita income.

The EKC form is taken from the income inequality-per capita income relationship described by economist Simon Kuznets in characterizing economic development in a country. At some initial stage, both income inequality and per capita income are at low levels, but inequality increases as per capita income grows, largely because only a small proportion of the country’s population is engaged in the growth sector of the economy. As the country’s growth is spread across sectors, more people are affected, and eventually inequality is decreasing instead of increasing in per capita income. While the original Kuznets curve was supposed to describe temporal change within a country, empirical verification is difficult because of a lack of temporal data. Cross-sectional data are more widely available and the conforming spatial pattern is that in cross-section we should observe that poor countries have low levels of income inequality and so do rich ones, while income inequality is greatest in middle income countries (Gregory & Griffin, 1974). EKCs essentially substitute environmental degradation for income inequality in the original Kuznets curve (Figure 1), including the implication of spatial conformity.

Figure 1.

An environmental Kuznets curve


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