Skip to main content


Social, spatial and environmental data

Research Achievements

Social, spatial and environmental data

UNC's IGERT program builds on linkage, analysis, and interpretation of social, spatial, and environmental data. These data typically bring with them a host of challenges, including (1) spatial heterogeneity, arising (a) from often highly diverse units of analysis (in terms both of geographic area and population size) and (b) from large-scale, long distance regional differentiation; and (2) by localized, small-scale, inter-unit dependence, arising from a host of mechanisms operating in space that serve to make individual units of analysis very much like other units in their neighborhood. These two factors conspire to violate the assumptions of the standard regression model, thereby biasing results. IGERT trainees benefited from the IGERT-focused graduate-level seminar in spatial regression offered for the second time during spring 2010, which focused on these issues from a spatial econometric perspective and explored them using GeoDaTM and the open source programming language R.