In this application, income and job growth in the eastern United States are explained using a partial adjustment model with regime switching potential and spatial spillover, or “Smooth Transition” spatial process models (STAR). This relatively new class of spatial regression models provides a parametric approach to testing hypotheses about the influence external economies have on “core-periphery” structures characterizing the Dixit-Stiglitz-Krugman type models describing regional economies. Growth is endogenized as a locally contagious process and specific to regimes, which are also endogenously determined by access to urban economies. The estimation approach relaxes distributional assumptions, using instruments to estimate the STAR process models with special attention given to instrument selection and definitions of spatial neighbors. In the empirical analysis, the authors focus on the specification of partial adjustment models by employing a common factor test to discern serial correlation from partial adjustment processes. Finally, an ex post qualitative analysis is conducted using phase diagrams to study convergence and stability properties of the regime-specific equilibrium solutions. A sensitivity analysis suggests that steady state employment levels in counties with Appalachian development highway networks is higher than counties without this infrastructure, but income levels are not different.