The principal research question is “Why do some neighborhoods in U.S. urban areas stay economically healthy and others do not?” This study proposes three hypotheses on diverging paths of neighborhood change: first, neighborhood change is produced by interactions of factors at the metropolitan, municipal, and neighborhood scales; second, “the politics of scale”—city size and the homogeneity level of household interests in a municipality—is an important factor leading to different paths and outcomes of neighborhood change; and third, factors of neighborhood change have altered over time.
The primary data set used in this study is the Neighborhood Change Data Base by GeoLytics that includes the decennial census data across the country from 1970 to 2000 at the census tract level. This study examines the proposed hypotheses with a random sample of 35 metropolitan areas and analyzes the data set using multilevel modeling. Using per capita income and average housing value in neighborhoods, this study develops an index of neighborhood economic condition and uses the change of this index as the dependent variable in the empirical analyses. The explanatory variables included in the model are based on the theories on neighborhood change and the comprehensive model of neighborhood change proposed in this study.
This study finds clear evidence to support the proposed hypotheses. First, neighborhood change is produced by interactions of factors at the metropolitan, municipal, and neighborhood scales. Secondly, the politics of scale matters in neighborhood change in that neighborhoods are more likely improve economically in smaller and more homogeneous cities. Finally, factors affecting neighborhood change have altered over time.
Based on the findings, this study suggests that it is essential to take metropolitan, municipal, and neighborhood contexts into account together in setting public policies for community development. With regard to the politics of scale, larger and more heterogeneous cities should learn from smaller and more homogeneous cities by, for example, working to increase community interaction, which is positively related to city growth. Finally, because the factors associated with neighborhood change were different in different time periods, local governments should plan in preparation for housing market change.
By taking the municipal and metropolitan contexts as well as the neighborhood context into account, this study helps improve our understanding of diverging paths and determinants of neighborhood change. If we know why neighborhoods undergoing changes move in different directions and how the influences of neighborhood change have altered over time, we can do a better job of designing policies to ameliorate different conditions. In a more theoretical vein, this study contributes to the literature by providing a comprehensive model of neighborhood change over space and time.