Differences in the reporting units of data from diverse sources and changes in units over time are common obstacles to analysis of areal data. We compare common approaches to this problem in the context of changes over time in the boundaries of U.S. census tracts. In every decennial census, many tracts are split, consolidated, or changed in other ways from the previous boundaries to reflect population growth or decline. We examine two interpolation methods to create a bridge between years, one that relies only on areal weighting and another that also introduces population weights. Results demonstrate that these approaches produce substantially different estimates for variables that involve population counts, but they have a high degree of convergence for variables defined as rates or averages. Finally, the article describes the Longitudinal Tract Database (LTDB), through which we are making available public-use tools to implement these methods to create estimates within 2010 tract boundaries for any tract-level data (from the census or other sources) that are available for prior years as early as 1970.

Analyses of neighborhood racial composition in 1980–2000 demonstrate that in multiethnic metropolitan regions there is an emerging pathway of change that leads to relatively stable integration Thes...

New technologies and multilevel data sets that include geographic identifiers have heightened sociologists' interest in spatial analysis. I review several of the key concepts, measures, and methods that are brought into play in this work and offer examples of their application in a variety of substantive fields. I argue that the most effective use of the new tools requires greater emphasis on spatial thinking. A device as simple as an illustrative map requires some understanding of how people respond to visual cues; models as complex as hierarchical linear modeling with spatial lags require thoughtful measurement decisions and raise questions about what a spatial effect represents.

Persistent school segregation means not only that children of different racial and ethnic backgrounds attend different schools but also that their schools are unequal in performance. This study documents the extent of disparities nationally in school performance between schools attended by whites and Asians compared with those attended by blacks, Hispanics, and Native Americans. It further examines the geography of school inequality in two ways. First, it analyzes the segregation of students between different types of school profiles based on racial composition, poverty, and metropolitan location. Second, it estimates the independent effects of these and other school and school district characteristics on school performance, identifying which aspects of school segregation are the most important sources of disadvantage. A focus on schools at the bottom of the distribution, as in No Schools Left Behind, would not ameliorate wide disparities between groups that are found across the whole spectrum of school performance.