Over the years, social scientists have amassed an impressive body of knowledge on state repression. Despite our improved understanding, this body of research implicitly assumes that the relationships between the independent variables and state sponsored repression are stationary over space. Current approaches, like OLS regression, cannot capture the spatial heterogeneity of the relationships and may lead to public policy inferences that are poorly specified or completely wrong for some countries. The purpose of the paper is to reexamine the repression model using geographically-weighted regression. We found significant variation in the goodness of fit of the model and strength of coefficients. A closer evaluation of the geographically varying results reveals that these variations have a distinct spatial trend, suggesting processes that might otherwise have gone undetected due to traditional 'global' results.
All Science Journal Classification (ASJC) codes
- Geography, Planning and Development