Cross-sectional analyses of American state data testing models in which state size is a meaningful predictor face a nonobvious problem of limited observations. Quite simply, the limited number of large states, and especially the presence of the uniquely large state of California, provides few observations to anchor regression estimates. We explore this problem with close attention to Gray and Lowery’s (1996a) energy, stability, area (ESA) model of interest system density, both replicating their results with new data and highlighting the utility and limitations of analyzing unusual cases in comparative state research. After replicating the ESA model, several diagnostics for analyzing outliers, leverage, and influence are examined. We show how supplemental data analyses can be used to assess the source, severity, and, sometimes, the solution of the problem.
All Science Journal Classification (ASJC) codes
- Arts and Humanities (miscellaneous)
- Political Science and International Relations