Association for Public Policy Analysis & Management

Understanding spatial dependence of income and regional inequality is crucial in the analysis of inequality. This paper deploys a multi-scale, multi-mechanism framework to map and analyze historical patterns of both regional and income inequality in the US by using state and regional panel data for over a century. To unravel the patterns systematically and to see the role of spatial partitioning carefully, we organize the data around several established geographical partitions before conducting various Geographical Information System (GIS) analyses and statistical techniques. We also investigate the spatial dependence of income inequality and regional inequality. We find that spatial autocorrelation exists for both the regional and income inequality in the US; however, the magnitude of spatial dependence for regional inequality is declining while it is volatile for income inequality over time. We also notice that while income inequality is at its peaks in the most recent decades, regional inequality is at its lowest point. As for the choice of partitioning, we observe that within inequality dominates for Census Divisions and BEA Regions. Conversely, we see that between inequality overall contributes the most to the inequality among Census Regions.