Green Crime Havens: A Geo-Spatial Cluster Analysis of Environmental Harm

• In Event: Empirical Analyses of Green/Environmental Crimes

Abstract

Green criminal activity exhibits a highly significant degree of spatial autocorrelation throughout the United States. This suggests that quantitative model estimations are likely suffering from the omitted variable bias by neglecting the overwhelming importance of geography. We put forward the concept of ‘Green Crime Havens’ as a descriptive sociological tool for understanding the variability of different offenders across three types of legislation that correspond to distinct forms of environmental harm. The Comprehensive Environmental Response, Compensation, and Liability Act (CERCLA), Resource Conservation and Recovery Act (RCRA), Clean Water Act (CWA), Clean Air Act (CAA), and Toxin Release Inventory serve as the bases through which these comparative categories are established. Data are geocoded from the US EPA ECHO database, which provides a significant amount of details for each case. Hot-spot and outlier analysis enable the identification of locations bearing disproportionately large burdens of environmental harm. Findings suggest that state level policies, industrial pull factors, and differential enforcement lead to stark differences within environmental inequality.

Authors

• Ryan Thomson, University of Florida

• Johanna Espin, University of Florida

• Tameka Gaye Samuels-Jones, University of Florida