Between 1990 and 2010, the white population share in US metropolitan areas fell from 73.5 percent to 60.3 percent. This paper explores how this decline affected the number and composition of white census tracts (tracts in which non-Latino whites constitute the largest group). In 1990, white tracts comprised 82 percent of all metropolitan tracts. By 2010, this percentage had fallen to 70 percent, paralleling the percentage point drop in white population share. This loss was concentrated among the most segregated white tracts - those with low diversity. White tracts that were moderately diverse actually doubled in number between 1990 and 2010 although this increase was insufficient to cancel the loss of low diversity white tracts. We model the effects of metropolitan characteristics on white-tract change by metropolitan area. Greater metropolitan-scale diversity increases the probability that low-diversity white tracts transition to moderate-diversity white. Moderately diverse white tracts, however, become more stable with increased diversity. A large metropolitan percentage of blacks or the foreign born, however, reverses this stabilizing effect, increasing the probability that moderately diverse white tracts transition to non-white tracts (i.e. where a non-white group is the largest group). Thus the level and composition of metropolitan diversity matters for the trajectory of moderately diverse white tracts. Overall, the formation of new white tracts, possibly the result of gentrification, coupled with the emergence of moderately diverse white tracts and an increasing share of whites living in such residential environments, suggests a reconfiguration rather than a dissolving of white dominated neighborhood space in response to increased diversity in surrounding metropolitan contexts.

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Georeferenced digital trace data offer unprecedented flexibility in migration estimation. Because of their high temporal granularity, many migration estimates can be generated from the same data set by changing the definition parameters. Yet despite the growing application of digital trace data to migration research, strategies for taking advantage of their temporal granularity remain largely underdeveloped. In this paper, we provide a general framework for converting digital trace data into estimates of migration transitions and for systematically analyzing their variation along a quasi-continuous time scale, analogous to a survival function. From migration theory, we develop two simple hypotheses regarding how we expect our estimated migration transition functions to behave. We then test our hypotheses on simulated data and empirical data from three platforms in two internal migration contexts: geotagged Tweets and Gowalla check-ins in the United States, and cell-phone call detail records in Senegal. Our results demonstrate the need for evaluating the internal consistency of migration estimates derived from digital trace data before using them in substantive research. At the same time, however, common patterns across our three empirical data sets point to an emergent research agenda using digital trace data to study the specific functional relationship between estimates of migration and time and how this relationship varies by geography and population characteristics.

Neighborhoods in US metropolitan areas experienced dramatic changes in racial composition during the 1990s and again during the 2000s. We ask to what extent does the recent period of neighborhood racial change reflect an extension of the local processes operative in the 1990s, processes characteristic of large metropolitan areas or the nation more generally, or reflect new dynamics. After classifying neighborhoods in US metropolitan areas into different types based on their racial composition and having harmonized a set of tracts to consistent boundaries, we use metropolitan-scale tract transition matrices from the 1990s to predict changes in neighborhood racial mix between 2000 and 2010. To capture scale effects, we repeat this using a set of pooled metropolitan-scale tract transition matrices and again using a national tract transition matrix. We show that the main dynamic at work across the metropolitan system is the underprediction of moderately diverse white majority tracts: i.e., in the 2000s, the rate of increase in the racial diversity of white majority tracts that transitioned from being predominantly white to moderately diverse was much higher than expected based on 1990s trends. In some metropolitan areas, shares of moderately diverse white tracts in 2010 are anticipated by their 1990s neighborhood dynamics, suggesting temporal stability and a locational specificity in these processes. Others experience a temporal rupture in these dynamics, and their moderately diverse white tract share is better anticipated by pooling transition information. The study also invites us to think about the nature of residential change currently taking place that we can capture in 2020 census data.