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Testing the Environmental Kuznets Curve Hypothesis for Biodiversity Risk in the US: A Spatial Econometric Approach

  • Justin Tevie

    ()

    (Department of Economics, University of New Mexico, Albuquerque, NM 87131, USA)

  • Kristine M. Grimsrud

    ()

    (Department of Economics, University of New Mexico, Albuquerque, NM 87131, USA)

  • Robert P. Berrens

    ()

    (Department of Economics, University of New Mexico, Albuquerque, NM 87131, USA)

This study investigates whether the environmental Kuznets curve (EKC) relationship is supported for a measure of biodiversity risk and economic development across the United States (US). Using state-level data for all 48 contiguous states, biodiversity risk is measured using a Modified Index (MODEX). This index is an adaptation of a comprehensive National Biodiversity Risk Assessment Index. The MODEX differs from other measures in that it is takes into account the impact of human activities and conservation measures. The econometric approach includes corrections for spatial autocorrelation effects, which are present in the data. Modeling estimation results do not support the EKC hypothesis for biodiversity risk in the US. This finding is robust over ordinary least squares, spatial error, and spatial lag models, where the latter is shown to be the preferred model. Results from the spatial lag regression show that a 1% increase in human population density is associated with about a 0.19% increase in biodiversity risk. Spatial dependence in this case study explains 30% of the variation, as risk in one state spills over into adjoining states. From a policy perspective, this latter result supports the need for coordinated efforts at state and federal levels to address the problem of biodiversity loss.

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Article provided by MDPI, Open Access Journal in its journal Sustainability.

Volume (Year): 3 (2011)
Issue (Month): 11 (November)
Pages: 2182

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Handle: RePEc:gam:jsusta:v:3:y:2011:i:11:p:2182-2199:d:14831
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