I provide a systematic analysis of smart-growth activity across the fifty US states from 1998 to 2001, summarizing their efforts across more than twenty policy areas. My analysis then turns to a set of nonlinear regression models for predicting state adoption of smart-growth policy. The empirical results from a variety of models suggest that the rate of per capita housing-start growth, and to a lesser extent, political liberalism, and the percentage of state land devoted to urban uses are all consistent predictors of state smart-growth-policy adoption. In addition, analyses of associations between policy areas reveals positive associative adoption patterns between urban revitalization and land-preservation policy. Positive associations were also found between growth control and housing-affordability policies.
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